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Improving the Care of Diabetic Patients in a Primary Care Practice via Affiliation with a Multi-Site Accountable Care Organization

Capstone Project Fall 2011

Mary DallasDavid MadisonMichael PetersonNatalie Schwartz

Copyright © 2011

Diabetic Quality Improvement Project

EXECUTIVE SUMMARY

Best Health Medical Associates (BHMA) must adapt to 21st Century health care finance based on accountable care. Partners in BHMA are pioneering the future of medicine through participation in an ACO (Accountable Care Organization). Core to the ACO concept is disease prevention and value based purchasing. The only universal fact regarding ACOs is that “there currently exists no surefire model for success.” Successful ACOs will be created as unique entities in response to the local environment. Dallas, Madison, Peterson and Schwartz Consulting, Ltd recommends sweeping practice changes to ensure BHMA remains the foremost primary care group in the Chicagoland area, highly regarded by patients for effective compassionate care and a model for financial success. Summarized below are our recommendations as detailed in the extended treatise.

Vision:

Mary Dallas, David Madison, Michael Peterson, Natalie Schwartz Page 1


The above diagram is a model of the function of ACO in its simplest form. The crux of the question being answered in this consultation is “what does BHMA do with data (i.e. isolated facts void of context or meaning) to create information in context which will be used to:

re-engineer the delivery of medical care deliver necessary healthcare interventions avoid duplication of testing plan resource deployment determine expenses attributable to ACO participation determine savings attributable to BHMA providers within improved

healthcare paradigms”?

Supporting Technologies:BHMA was prescient to have implemented EPIC EHR. Having this in place will allow expedient participation in Health Information Exchange (HIE) which is foundational to successful acquisition of patient data required to manage ACO patients. BHMA must lobby with the ACO to adopt the MetroChicago Healthcare HIE (MCHIE). Strong points in favor of this choice:

Initial wide adoption by hospitals and providers in the region of BHMA and the ACO

MCHIE positioned to become the default HIE for the vast majority of providers in proximity to the catchment area of the ACO

Centralized duplicated database structure of Amalga will empower ease of reporting by central data normalization

Practice Redesign:“Insanity: doing the same thing over and over again and expecting different results.” (Albert Einstein). Without redesign, BHMA will not achieve the desired outcomes. Strategies for redesign center around extending practice responsibility beyond the confines of the typical provider-patient encounter. By actively filling in the information gaps, duplicative testing can be avoided, patient compliance can be monitored, provider compliance can be monitored (i.e. are the patient quality metrics being met?) and practice variation can be avoided.

Several high-value interventions recommended:

Redesign patient scheduling to drive efficient workflow and cost avoidance-empowered by clinical decision support and active data mining of HIE



Improved medication management by active review of prescription use Monitor for clinical inertia—are patients having appropriate escalation of

their therapies according to standardized algorithms of care? Strengthen patient engagement/involvement in their own care through

education, and case management spanning the spectrum of care venues.

Risks and Barriers:Participation in an ACO is true pioneering with great risks. Participation in an ACO requires large technology investments up front without guarantee of return. Fortunately for BHMA the greatest expense, that of implementing an EHR, has been in place for 18 months.

There is a paucity of information surrounding ACO financial outcomes. As there exists only a few pilot sites that can report longitudinal results and each of these is structurally unique, their results are not generalizable. This translates to an imperative for BHMA to monitor and benchmark results as close to real-time as possible.

Next Steps:BHMA must actively participate in the ACO as outlined, if there is an expectation of achieving both improved quality of care and shared savings. In preparation for the ACO go-live, BHMA must:

Immediately begin to report on the diabetic patients within the practice:1. Search for ICD 9 codes2. Search for HbA1c3. Identify sources for compliance with preventative measure4. Import SureScripts data for reporting on patient diabetic medication

compliance Begin workflow analysis to incorporate midlevel providers in the care and

education of patients

Once BHMA has established and initiated the practice changes necessary to improve diabetes care, BHMA must expeditiously move forward with other chronic disease management efforts to maximize the outcomes from participating in an ACO, as well as continuously monitor the clinical and financial performance of the practice through real-time dashboard reporting.

Dallas, Madison, Peterson and Schwartz Consulting, LTD



TABLE OF CONTENTS:

EXECUTIVE SUMMARY.............................................................................1Vision:............................................................................................................................................1Supporting Technologies:..........................................................................................................2Practice Redesign:.......................................................................................................................2Risks and Barriers:......................................................................................................................3Next Steps:....................................................................................................................................3

PURPOSE:...................................................................................................7Best Health Medical Associates Environmental Background.............................................................7

HEALTHCARE BACKGROUND:................................................................7Current State of Health Care in the United States-.................................................................7Patient-Centered Medical Home Model-...................................................................................8Accountable Care Organizations-..............................................................................................8

DIABETES CARE IN THE UNITED STATES:...........................................10Diabetic Registries-....................................................................................................................11

ACO PROPOSED SPECIFIC QUALITY MEASUREMENTS RELATING TO DIABETES CARE-...............................................................................12CREATING REPORTS TO MEASURE DIABETIC CARE........................15

Strategic Reports:......................................................................................................................22Operational Reports:......................................................................................................................25

ANALYSIS METHOD.................................................................................26TECHNICAL SOLUTIONS TO SUPPORT ACO.......................................29

Health Information Exchange (HIE).........................................................................................30HIE Model........................................................................................................................................31

TECHNOLOGY ENHANCING CLINICAL DECISION SUPPORT.............34EHR Workflow using HIE Information....................................................37Opportunities for practice redesign.......................................................39

Examining the workflow around prescriptions:....................................................................39Concept of clinical inertia.........................................................................................................41Whose patient is it?...................................................................................................................41Beyond Diabetes Management................................................................................................42Word of caution..........................................................................................................................42

CLINICAL, TECHNICAL AND FINANCIAL ANALYSIS............................43Mary Dallas, David Madison, Michael Peterson, Natalie Schwartz Page 5


Sharing Savings and Sharing Losses.....................................................................................45Assumptions...............................................................................................................................46

ANALYZING THE RETURN ON INVESTMENT (ROI) FOR A QUALITY IMPROVEMENT PROJECT.......................................................................47ACO DIABETES IMPROVEMENT PROJECT ROI...................................48

Program Costs............................................................................................................................48

Summary of Recommendations..............................................................53Short Term Changes (0-6 months):.........................................................................................53Mid Term Changes (6-12 months):..........................................................................................54Long Term Changes (12 to 24 months):.................................................................................55

Bibliography.............................................................................................56APPENDIX:................................................................................................60

Sample Report #1 Identify the BHMA ACO Patients........................................................................60Sample Report #2 Identify the BHMA ACO Patients with Diabetes..................................................61Sample Report #3 Provider attribution patient care based on charges............................................62Sample Report #4 Provider attribution based on episodes of care...................................................63Sample Report #5 Comparative diabetes performance dashboard..................................................64Proposed conceptual approach to reports requirement creation....................................................66



PURPOSE:Implement a diabetic quality improvement project for Best Health Medical Associates to maximize quality of patient outcome and minimize unnecessary expenses.

Best Health Medical Associates Environmental BackgroundBest Health Medical Associates (BHMA), located near Chicago, Illinois has been in existence for over 35 years, and currently employs 10 primary care physicians. There are 3 office locations, several miles apart, in separate zip codes. Four primary care physicians practice solely at the location in Chicago, four other primary care physicians practice solely in Evanston, and two primary care physicians practice solely out of the office in Cicero. Over the past year, the group affiliated with a multi-site Accountable Care Organization, which includes the nearby academic 700 bed teaching hospital, Columbia West. In addition to the on-site primary care physicians, the clinical staff includes registered nurses, nurse practitioners, and medical assistants. Registered dieticians, podiatrists, and cardiologists rotate within the practice, to care for this group of diabetic patients, on a weekly basis.

Best Health Medical Associates will improve diabetic management for the 2,500 diabetic patients within the practice and spanning the continuum of payers-- private insured, Medicare, Medicaid, and uninsured patients.

Best Health Medical Associates adopted EPIC as its EHR 18 months ago, and the on-site providers use the system for full visit documentation, electronic prescribing, and results retrieval. Three different laboratories report into the EHR, using different terms and test combinations. Three main pharmacies receive and respond to electronic prescriptions from the system. Columbia West uses Centricity, as its EHR. Therefore, when patients are hospitalized, the inpatient diabetic care team does not have access to the patient information within the practice’s EHR. Similarly, when patients are discharged from the hospital there is no direct integration of hospital records into the practice’s EHR.

HEALTHCARE BACKGROUND:

Current State of Health Care in the United States-The need for health care reform in this country is indisputable. Escalating health care costs have outstripped inflation, accounting for 17.4% of the country’s gross domestic product, or $2.5 trillion, and $7,960 per capita, in 2009. Despite surpassing most other developed countries in total health care expenditures per capita, the health care system



in the United States remains unacceptably fragmented, poorly coordinated, and achieves poor quality measures. (The Henry J. Kaiser Family Foundation) Medicare fee for service plans are not required to coordinate care, establish provider networks, or have policies to examine their utilization management. Over the past several years, the federal government has formalized a process to evaluate Medicare claims, to determine whether the items or services meet statutory coverage, medical necessity requirements, are correctly coded, and are supported by proper documentation. As a result of implementing this payment review, the Medicare Fee for Service Error rate dropped from 12.4% in 2009 to 10.5% in 2010. (Combs-Dyer, 2011) Proposed health care reform models aim to make the delivery of care more cost-effective, of higher quality, with improved patient and provider satisfaction. (Longworth, 2011)

Patient-Centered Medical Home Model-Originally proposed by the American Academy of Pediatrics in 1967, the concept of a Patient-Centered Medical Home (PCMH) did not gain momentum until 2002, when it received the support of the American Academy of Family Medicine. (Longworth, 2011) The National Committee for Quality Assurance (NCQA), a non-profit organization that voluntarily certifies medical organizations, best describes patient centered medical homes where “ patients have a direct relationship with a provider who coordinates a cooperative team of health care professionals, takes collective responsibility for the care provided to the patient, and arranges for appropriate care with other qualified providers as needed” (National Committee for Quality Assurance (NCQA)). The NCQA first formally licensed patient centered medical homes in 2008, using nine standards and six key elements and a scoring system to rank the level of certification from level 1 (lowest) to level 3 (highest). In 2011, the certification standards became more rigorous, with must-pass elements within each standard. In January 2012, certification will require the additional submission of a standardized patient experience survey, the Consumer Assessment of Healthcare Providers and Systems (CAHPS), highlighting a new emphasis on patient satisfaction in healthcare reform. (Longworth, 2011)

Data from patient centered medical home projects (e.g. The Group Health Cooperative of Puget Sound, the Geisinger Health System Proven-Health Navigator, Blue Cross Blue Shield of South Carolina, and the Johns Hopkins Guided Care Program) have demonstrated significant cost savings, primarily by reducing hospital admissions and patient visits to the emergency room, but also from investing in chronic care coordinators. (Patient Centered Primary Care Collaborative: Grumbach K, Grundy P., 2010)

Accountable Care Organizations-Accountable Care Organizations (ACOs) seek to apply and expand the PCMH model across the continuum of care. The essential premise is to improve care coordination



amongst all the providers and sites of patient care, thus controlling costs, improving measurable outcomes, improving patient safety, and enhancing patient and provider satisfaction. The health care reform bill, also known as the Patient Protection and Affordable Care act, has pushed the ACO model into the public limelight. On March 31, 2011, the Centers for Medicare and Medicaid Services (CMS) published the first draft of proposed rules to implement ACOs for Medicare patients. The original set of rules was considered too financially risky and too onerous for providers by organized medicine and large medical societies, including the American Medical Association and the American Academy of Family Physicians. Final ACO regulations, that were more physician friendly, were released on October 20, 2011. (Lowes, 2011)

The three year minimum ACO contract requires an incorporated (real) or contractually networked (virtual) ACO to have a minimum of 5,000 Medicare beneficiaries, with a specified structure, governance, and management.

According to the proposed rules, Medicare will continue paying individual providers for specific services, as it does under the original Medicare payment system. However, it will develop benchmark performance measures against which the performance of the ACO will be judged. The 33 final performance quality measures fall within 5 broad categories:

Patient and caregiver experience

Care coordination

Patient safety

Preventative health

Managing at-risk populations- including the frail elderly

Medicare will determine if the ACO qualifies to receive shared savings or if it will be held accountable for shared losses. The ACO has a choice of two shared savings options for different levels of ACO readiness. Under the Track one methodology, the ACO will have shared savings calculated for each year of the 3 year agreement term, and only be eligible for bonus payments if savings are realized. There will be no penalty for losses. Track one limits the ACO bonus payment to 50% of realized savings but not to exceed 10% of that years Part A and Part B benchmark. This amount is also capped at 10% of that year’s Part A and Part B benchmark. If the participants wish to continue after the duration of this first term, they must move to the two-sided model of track two. Track two provides higher sharing rates for ACOs, up to 60% to be capped at 15% of that year’s Part A and Part B benchmark, but the ACO is also at risk for shared losses if expenditures exceed expected rates. There will be a minimum sharing rate (MSR) to



account for normal variations in health care spending, and the MSR will vary based on the size of the ACO. For the one-sided model, as the beneficiary pool is larger in size, it is assumed there will be less variation in the expenses, thus the MSR will be smaller. The opposite is true for smaller ACO beneficiary sizes, and the MSR rate will be set between 2% and 3.9%. For the two-sided model, there is a flat rate of 2% for both savings and loss calculations, irrespective of the ACO patient base. The amount of loss an ACO might realize is also limited with a gradual phase in over the 3 year period – 5% the first year, 7.5% the second year, and up to 10% the third year. (CMS, 2011, Nov 2) (US Department of Health and Human Services, 2011)

According to the final rules, there will be a longer phase-in of reported measures over the course of the 3 year contract. The first round of applications for ACOs is due early 2012, with agreements starting 4/1/2012 and 7/1/2012. For the first performance “year” (of 18 or 21 months), the ACO will receive pay for complete and accurate reporting. If they report CY2012 quality measures, they have the option for an interim payment. ACOs are required to report quality measures for CY2013 to qualify for first performance year shared savings. In the 2nd and 3rd year, the ACO will receive pay for reporting and performance. (Centers for Medicare and Medicaid Services, 2011)

CMS will utilize a preliminary prospective ACO assignment method with beneficiaries identified and reported by name, date of birth, sex, and health insurance claim number, quarterly, with final reconciliation after each performance year based on patients actually served by the ACO. (Centers for Medicare and Medicaid Services, 2011)

DIABETES CARE IN THE UNITED STATES:The most recent data from CMS reports that more than 50% of Medicare beneficiaries in the United States have five or more chronic medical conditions. (Centers for Medicare and Medicaid Services, 2011) Furthermore, 75% of all U.S. health care expenditure is related to the treatment of chronic conditions, diabetes being one of the most common of these conditions. There are more than 25.8 million Americans with known diabetes, and an estimated 7 million more with undiagnosed disease. The direct annual cost of caring for this population of diabetic patients is $116 billion. There is an additional annual financial burden of $58 million in disability, work loss, and premature mortality costs. (Rice, 2011) With the growing American trend in obesity, and its implication in the etiology of diabetes, it is critical to engage patients in programs that encourage healthy eating and exercise habits, and comprehensive disease prevention.

Diabetes is a complex disease, requiring intensive monitoring for, and treatment of, both micro-vascular (eye, kidney, and neurologic) and macro-vascular complications, as well as for common co-morbid conditions (hypertension, obesity, hyperlipidemia, heart disease). (American Diabetes Association, 2011) Diabetic patients often visit an



endocrinologist, registered dietician, ophthalmologist, podiatrist, vascular surgeon, or nephrologist, in addition to his/her primary care physician(s) several times a year. There may also be visits to one or more emergency rooms and/or hospitals for glycemic-related or complication-related conditions. Patients often have laboratory results from multiple facilities and medications filled at different pharmacies. Consolidating information from these various sources to get a holistic view of a patient’s health status and care provided is one of the first steps to understanding where to focus efforts to improve diabetes outcomes.

Information management is a critical aspect of caring for this patient population to achieve the standards of medical care promulgated by the American Diabetes Association and the disease management performance standards recognized for NCQA Accreditation and Certification. Obtaining the NCQA Diabetes Provider Recognition based on reporting and benchmark compliance with the specific diabetes performance measurements of the Healthcare Effectiveness Data and Information Set (HEDIS) tool, is an important step in accreditation as a patient centered medical home. (NCQA: HEDIS and Quality Measurement) In the fall of 2011, NCQA will publish a separate accreditation process for ACOs which will focus on the patient centered primary care home practice model, the timely exchange of patient information for the safe transition of patients, optimal care coordination, and measurement and reporting of quality outcomes. (NCQA: HEDIS and Quality Measurement) For this report, we will focus on leveraging information technology to collect and collate information related to diabetes care for patients of BHMA as well as the ACO the group participates in. This will allow for BHMA to continue pursuit of NCQA Diabetes Provider Recognition status and lay the foundation for successful risk sharing in the ACO initiative.

Diabetic Registries-Disease management has become a widely accepted method of supporting and improving health care delivery for vulnerable patient populations, with studies documenting improvement in health care outcomes and lower costs. Diabetes lends itself well to disease management registries and multidisciplinary models of care. Diabetic management of populations and individuals can be supported by novel information technologies. Providers and patients can access web-based systems remotely to improve communication of test results, support home monitoring, provide seamless coordination of care, and bolster compliance with practice-based algorithms of care. “Emerging information management technologies (EIMT) include advances in software, hardware, and networking, all of which share common impact attributes in their ability to improve cost-effectiveness, quality of care, and access to care. Specific examples include interactive websites with the ability to engage patients in the self-care management process, the embedding of biometric devices (digital scales, modem-enabled glucose meters in the home, blood pressure monitoring), workflow and care



coordination that add intelligence via guideline-directed alerts and reminders to the delivery process, registries that include a summary of personal health data that can be used as a reference point for improved clinical decisions, and the systematic collection of aggregated, de-identified clinical, administrative, and cost data into comprehensive data sets to which predictive modeling analytic tools can be applied.” (Nobel, 2003)

Creating a disease registry or similar method of tracking and measuring disease burden is critical to support the ACO in regards to diabetes care and other chronic disease management. Because the ACO is responsible for the quality outcomes for care of all ACO diabetic patients, the data sources for metrics and reporting need to extend beyond those patients within BHMA’s practice group. Until now, the group has been able to report Physician Quality Reporting System (PQRS) measures out of its EPIC EMR, because the documentation of care for its patients has been fairly comprehensive and inclusive only of patients seen by the group. The diagnosis of diabetes is documented within the problem list for each patient seen, and payer information is part of the claims data within the practice management component of the EMR. From this information, the group can estimate the number of Medicare patients within the practice, and identify those with diabetes. Within the ACO, however, the beneficiary population is a larger segment of the community, and includes patients who may not be registered with or seen by BHMA providers. ACO beneficiaries retain the ability to receive care wherever they choose, despite the fact that the ACO participants may now be assuming some risk for their utilization expenses. For this reason, investment in technology to support identification and measurement of diabetes patients across the community is imperative. Our report outlines technology solutions that will enable this type of patient tracking.

ACO PROPOSED SPECIFIC QUALITY MEASUREMENTS RELATING TO DIABETES CARE-CMS has published a table of the 33 measures in the final rule that ACOs will be required to submit for performance monitoring. These measures will be used to determine the % of shared savings or additional costs to allocate back to the ACO. The table below is a summary of the quality measures related to diabetes care that will be used in the quality component of shared savings calculation.



Table 1: Reportable Quality Measurements Related to Diabetes Care in Final ACO Rules

Domain Measure Title

NQF Measure #/Measure Steward

Method of Data Submission

Pay for Performance Phase InR= Reporting P= Performance

P Year 1 P Year 2 P Year 322. At Risk

Population: Diabetes

Diabetes Composite (All or Nothing Scoring):HbA1C <8%

NQF #0729MNCommunityMeasurement

GPRO Web Interface

R P P

23. At Risk Population: Diabetes

Diabetes Composite (All or Nothing Scoring):LDL <100


GPRO Web Interface

R P P


Diabetes Composite (All or Nothing Scoring):BP < 140/90


GPRO Web Interface

R P P


Diabetes Composite (All or Nothing Scoring):Tobacco Non Use


GPRO Web Interface

R P P


Diabetes Composite (All or Nothing Scoring):Aspirin Use


GPRO Web Interface

R P P


Diabetes Mellitus: HbA1C>9%

NQF #59NCQA

GPRO Web Interface

R P P



(CMS, 2011)

The information collected from the ACO will be used to phase into the shared savings program from the pay for performance program. The first year measurement period in 2012 will be reported and used to set the baseline performance threshold, but won’t replace pay for performance targets until years 2 and 3. In year 2, 25 of the measures will become performance measures, and in year 3, that number increased to 32, based on targets set from the 2012 baselines. The diabetes measures listed above will all be included in performance based calculations by year 2 of reporting. The method of transmitting these measures back to CMS is via 3 main sources: patient survey (CMS will use the CAHPS survey), claims data (from billed services for ACO beneficiaries), and GPRO (Group Practice Reporting Option, a web tool for the ACO to transmit data files from their EMR to CMS). There is one additional source of reporting for the ACO measures, which is the % of providers successfully qualifying for the EHR incentive program. This information will come from the incentive program data. One caveat to keep in mind about the CAHPS survey is that CMS will bear the cost of administering the survey for 2012 and 2013, but will require the ACO to assume that cost of survey administration in 2014. Our recommendations for reporting are targeted to those measures to be reported via the GPRO methodology. (CMS, 2011)

CMS plans to incorporate the new measures for ACO quality reporting into the GPRO tool that has been successfully used to capture PQRS quality measures currently. The sampling method will be similar as well, utilizing reporting on a sample size of 411 beneficiaries within each quality metric, unless the total participants for that measure are less than 411, then reporting for that measure must be 100% of beneficiaries. The beneficiaries to be reported on within the tool will be preloaded by CMS, and this group will be initially defined as the beneficiaries assigned to the ACO in 2012. Reporting will occur annually, and further specifics around the timeframes and requirements will be published by the end of the 1st quarter in 2012. Accuracy of the reports will be audited annually as well, with record review of up to 30 beneficiaries in the reporting pool. Inaccuracies noted in the audits will lead to corrective action plans, and potential termination of responsible participants from the program. (CMS, 2011)

As noted in the CMS final rule publication for the shared saving program, physicians who participate in an ACO will be allowed to continue participation in the PQRS program through the first year of ACO participation. This is intended to allow the physicians to keep some incentive payment for quality performance while the baseline performance thresholds are being established for the ACO. Physicians will remain



eligible to participate in other programs not based on shared savings, such as the EHR incentive program (Meaningful Use incentives). Of note, this specific program is important to recognize, as members of the ACO who do achieve meaningful use within the EHR incentive program will successfully complete that reporting measure for ACO performance, and this measure will carry twice the weight of other measures. Because BHMA has successfully adopted the EPIC EHR, we recommend registration for meaningful use attestation in 2012. The ACO must encourage all providers to reach the “Meaningful Use” criteria as these reflect core competency in information management and exchange.

While quality measures for the ACO can be reported manually into the GPRO tool, automating this process with data extracted from electronic sources is preferable. First, the manual labor expense required to enter quality data individually for hundreds of patients is prohibitive, and potential for transcription error and delayed entry of data significant. Second, because the physicians in this group have made an investment in an EHR, leveraging that investment for quality reporting will help avoid duplicate expense for manual data entry into the GPRO. Improved accuracy and ability to monitor performance near real time is also an advantage, so that the group will know where they are meeting or failing specific measures before those are reported externally. The next challenge this introduces is the fact that the patients within the ACO receive care from multiple venues, not all accounted for within the primary care group’s EHR data. This gives the group a limited view of the quality of care and utilization for the patients it is responsible for. Creating reports which focus on solutions to create a more holistic view of the patients’ information is imperative for a successful ACO to manage quality and utilization more effectively, and address opportunities to improve patient care and medical expenses.

CREATING REPORTS TO MEASURE DIABETIC CAREWhile the patients defined as Medicare beneficiaries will be included in the ACO for reporting purposes, it is counterproductive and not in the best interest of patient care to assume these patients will be treated any differently than other patients with respect to quality of care. Therefore, reporting for purposes of examining quality related to diabetes care is recommended to be inclusive of all patients within BHMA’s primary care domain, and include the ability to segment Medicare as a payer, to identify how the ACO shared saving defined population is performing, both related to quality as well as cost of care and utilization. One advantage to this model of reporting is that demonstrating improvement related to quality of care will provide the group with leverage to negotiate with payers outside of CMS for reimbursement based on performance.



Participation in the ACO pushes the group to develop alternative methodologies for examining quality and utilization. Prior to participation with the ACO, the group’s main driver was to report quality and claims based on patients seen solely within the group, and there were no incentives to look at a patient’s information across the continuum of care. Now that the group has a vested interest in care the patient is receiving outside of the practice as well as within the practice, this shifts the BHMA providers’ incentive to help manage care across the continuum, in order to optimize utilization and assure that quality indicators are met regardless of the location of service. This is fundamental to the shared incentive model that CMS has introduced. Technology platforms that support sharing of information in a patient centric manner across different venues of care are required to support participation in the ACO model.

First, the ACO must develop a methodology for taking the historical claims data submitted by CMS for the patients it has assigned to the ACO, and examine where those patients are receiving the majority of their primary care. BHMA will also need to identify the cohort of diabetic patients it is primarily responsible for. By virtue of being a participant in the ACO, the primary care group will now need to refocus on managing the entire population of diabetic patients and expand its efforts to improve care both for those beneficiaries it is directly responsible for, as well as looking at how the ACO can improve care across the entire population. This requires the adoption of a completely new business model, with new data systems, metrics, processes, and skill sets.

The methodology used by CMS to determine the population of patients to account for within the ACO starts with identification of the physicians and others who are defined as primary care providers. This is done through use of the NPI (National Provider Identifier) linked to specialty codes that identify that practitioner as a primary care specialty. In addition, the TIN (Taxpayer Identification Number) is used to cross reference the patient with the service received from claims data. Each primary care provider is limited to registration with a single ACO, but other specialty service providers may be linked to multiple ACOs. In this case, the group needs to look at its claims data to examine which patients within the prior 15 months (there is a 3 month time lag for CMS claims reporting) it submitted claims for that are Medicare beneficiaries. The type of claims that link the provider to the patient for these purposes are those considered to be primary care services defined on page 193 of the final rule. If the services are primary care services, but are provided by a specialist and there is no primary care identified for that patient, these patients will be assigned to the ACO as well. (CMS, 2011) So, in order to identify the diabetes population potentially served by the ACO, reports will need to first capture all patients receiving primary care services, and who, the practitioners submitting those claims are. CMS will give the ACO a list of beneficiaries included in its aggregate reports quarterly. These lists will include basic name and demographic information for the patients, minus those patients who opt out of



inclusion for this reporting. Once the beneficiary pool is identified, BHMA will need to determine which patients within the ACO population are diabetic, which is based on ICD-9 codes within claims information for those patients. This type of data abstraction must occur at the ACO level, to be more inclusive than the EHR data currently employed by the practice group. Each ACO participant group then must have a way of looking at their individual performance for the patients they are identified as the primary care provider for.

Shaping reports to support the diabetes quality metrics required by the ACO to capture and improve on is the next challenge. Understanding how these ACO will receive credit for its performance is key to examining what potential there is for shared savings. First, the 33 measures are grouped into 4 domains – Patient/Caregiver Experience, Care Coordination/Safety, Preventative Health, and At Risk Population. Each domain will have a summary score and carry an equal weight in determining the percentage of shared savings the ACO is eligible. The diabetes care measures are a component of the At Risk Population domain. There are 6 measures related to diabetes care, and these will be reported as an “all or none” type metric. This means that each patient must receive each element of care in order for the diabetes quality measure to be met. These quality elements will all be reported using the GPRO tool, and can be abstracted from the group’s EHR to report. The first 12 months of data collection will help establish the baseline threshold for these measures and requires that the ACO have accurate and complete reporting to receive payment for the first year. The subsequent 2 years will be based on actual performance to these defined standards, and requires a minimum threshold of 30th percentile be met in order to participate in the share savings payment. Groups that perform better than just meeting the threshold will see incremental increases in the ACO performance score, so they will receive more benefit by virtue of a higher percentage of shared savings eligibility. (CMS, 2011)

The primary care group must collect new types of data from multiple data sources, consolidate the data to create strategic and operational reports on the entire diabetic population, and continuously analyze and monitor patient demographics, utilization, quality metrics, risk scores, compliance with best practice, leakage from the network (i.e. care provided by non-network practitioners or hospitals), and costs that will impact its financial success. BHMA must have a continuous source of accurate and updated information to look at population trends, make comparisons to benchmarks, identify gaps, and make rapid workflow improvements (e.g. new guidelines, protocols, templates, clinical decision support tools, new staffing models). Real time feedback to individual providers (via remote alerts) and the entire group of providers (via dashboard and/or desktop alerts) is an essential component of this iterative process.



(Richard E. Wards, 2011)

Figure 1: ACO process of rapid modification of workflows and guidelines based on continuous analyses of quality outcome measurements and costs.

Claims and billing data may provide some of the data elements required for the above processes, as well for measurement of readmission and vaccination rates. Claims data include diagnosis and procedure codes, payment amounts for services provided, and service and payment dates. The ACO must have the capability of accepting and consolidating the claims, billing and EHR data from the data systems of multiple providers and hospitals. Linking patient data from multiple billing systems is complicated and may require special translational processes to create a single view of a patient’s claim history. In addition, the ACO must integrate pharmacy data (which may use different provider identifiers than medical claims data), identify and monitor all diabetes-



related medications for the cohort of diabetic patients, flag when prescriptions are not being filled within prescribed interval times, and report on poorly controlled conditions. It must also obtain laboratory results data, electronically or manually, directly from the laboratory, or from the provider’s office, integrate it with the patient’s medical status and history, report out of range values, and alert providers on critical values. (Singletrack Analytics, LLC, 2011) Many of the quality measures for diabetic care cannot be obtained from claims and billing data, and must be retrieved from data at the point of care.

Therefore, in order to support BHMA’s participation in the ACO, we are recommending two types of datasets to be collated. The first type is defining the ACO patient population with diabetes and contains related diabetes quality measures that will be used to report into the GPRO tool. The elements needed for this dataset are summarized in the following table.

Table 2: Elements required for datasets defining the ACO patient population with diabetes

Measure Source systems Data Type or standards

Abstraction Source and transmission

Notes

Patient Identifiers

Hospital ADT, Ambulatory PM System

HL7 transmission from systems

Link to EMPI to identify patients from different source systems

Patient Demographics

Hospital ADT, Ambulatory PM System

HL7 transmission from systems

Matching algorithm to collate reports across ACO, assists in EMPI matching

Payer Type Hospital ADT, Ambulatory PM System, Medicare Reports to ACO

HL7 transmission from systems XML file from CMS

Identify Medicare beneficiaries, and will require reconciliation with CMS beneficiary reports quarterly

Patient Diagnoses

Hospital and Ambulatory EMR, Medicare Reports to ACO

ICD9, ICD10

HL7 transmission from EMR systems, XML file from CMS

Will also require reconciliation with CMS beneficiary reports quarterly

HbA1c Lab Information LOINC HL7 lab Sent upon completed



Systems transmission testing, Values require normalization across lab sources

LDL Lab Information Systems

LOINC HL7 lab transmission

Sent upon completed testing, Values require normalization across lab sources

Blood Pressure

Hospital EMR, Practice EMR

Discrete values

HL7 transmission from source systems

Most recently recorded BP measurement

Tobacco Non Use

Hospital EMR, Practice EMR

SNOMED HL7 transmission from source systems

Reported Non Use within 12 months

Medications Retail Pharmacy Information System, Hospital and Ambulatory EMR med lists

NDC HL7 transmission

Collated medication list from different sources, includes non-prescription medications

In addition to the core quality information related to diabetes care needed to collate and report into the GPRO tool for the ACO, a second type of data set will be necessary to examine cost of care and utilization for estimation of shared savings or liabilities. This information will also be used to help guide patients and providers into utilization patterns that focus on improving outcomes for patients with diabetes. An example of this data is summarized in the table below.

Table 3: Utilization elements required to examine the cost of caring for the diabetic population

Measure Source systems Data Type or standards

Abstraction Source and transmission

Notes

Lab utilization Lab Information System, Claims Paid

LOINC HL7 transmission

Claims paid estimated from CMS reimbursement rates



Radiology Utilization

Radiology Information System, Claims Paid

CPT codes HL7 transmission


Other Diagnostic Tests (EKGs,

Hospital ADT and Ambulatory PM systems, Claims paid

CPT codes HL7 transmission


Hospitalizations, Surgeries

Hospital ADT registrations, Claims paid

CPT codes, ICD9 codes

HL7 transmission


ED visits ED Registrations, Claims paid

CPT codes, ICD9 codes

HL7 transmission


Specialty Provider Visits

Physician office visits, Claims paid

E&M codes, CPT codes, ICD9 codes

HL7 transmission


The key for collecting and collating this information is to have the ability to look at the summary in both a patient centric way, to enable a summary of utilization patterns, as well as in a provider centric way, to enable direct feedback to ACO participants on their patterns. These are basic steps necessary to examining patterns, and identifying opportunities to change them where appropriate. The ACO has the primary responsibility for monitoring this utilization across its beneficiaries, as well as how it will provide participants with their personal information. Once these data element sources are mapped back to their source systems, such as within the hospital and ambulatory practice EMRs, each participant organization will need to examine whether there is an opportunity to add clinical decision support in their system at the point of care to assure documentation elements are captured consistently and accurately. Determining when the data is sent to the ACO reporting system, such as at the end of each patient encounter or upon discharge from the hospital, will also need to be defined. The value of reports used by the ACO is highly reliant on accuracy of source system data.



Strategic Reports:

It is important for the primary care group to understand the health characteristics, demographics, and service utilization of their population of diabetic patients. The following strategic reports will help the group to better predict and manage quality and cost.

Age distribution:

Not all Medicare beneficiaries are over 65 years of age. Medicare also covers disabled patients under age 65, specifically patients with end-stage renal disease. Since diabetes is the number one cause of end-stage renal disease in the United States, a report of age distribution will help identify those patients requiring the highest levels of care and costs.

Gender distribution:

Patient gender may influence the risk of diabetic complications and co-morbid conditions, compliance with medications and/or office visits, and patient lifestyle. Gender may also influence patient selection of PCP gender.

Co-morbid conditions/ Severity of Illness:

Patients with diabetes have a number of high risk coexisting illnesses, including hyperlipidemia, cardiovascular disease, peripheral vascular disease, vision loss, neuropathy, and kidney failure that will impact on coordination of care, hospitalization and procedural costs, and compliance. Historically, Medicare utilizes hierarchal condition categories (HCCs), based on diagnoses, to compute risk adjusters for each patient. HCCs are helpful for risk-adjusting medical costs and computing risk-adjusted payment budgets. HCC-based risk scores provide a way of evaluating the relative per member per month (PMPM) costs of a PCP. Mapping the practice’s primary care physicians against the HCC risk based scores and PMPM costs of their panels of diabetic patients is helpful to identify gaps in care and opportunities for the practice to implement quality improvement initiatives. Patients with high risk scores and low PMPM costs may indicate suboptimal care of a high risk condition. Conversely, patients with low risk scores and high PMPM costs may indicate overuse of resources or unnecessary treatment, and an opportunity to impact individual physician or overall practice behavior.

Tables should be created to show the overall average risk score for each PCP’s panel of diabetic patients and graphs devised to illustrate the distribution of diabetic patient risk scores for each PCP. (Singletrack Analytics, LLC, 2011)



The following is a table that illustrates the number of physicians at each practice site, the total number of diabetic patients within each individual PCP practice at each practice site, and the average risk score for those diabetic panels. For the 2,500 diabetic patients cared for by BHMA over their 3 locations, the average risk score (based on HCC scoring) is 1.6. This means that the cost of caring for this total group of patients is 1.6 times the average beneficiary cost for one year. The 2,500 patients describe the entire diabetic panel of patients within the practice across all payer types.

Table 4: Number of Diabetic Patients by BMHA Practice Site and PCP and Average Risk Score of Individual PCP Diabetic Panels

PRACTICE PCP # MEMBERS WITH DIAGNOSIS OF

DIABETES

AVERAGE RISK SCORE

Chicago 1 393 0.73Chicago 2 321 2.45Chicago 3 244 1.37Chicago 4 231 0.89TOTAL 1189 1.36

Evanston 5 230 2.11Evanston 6 289 1.76Evanston 7 150 1.9Evanston 8 178 0.83TOTAL 847 1.65

Cicero 9 283 1.89Cicero 10 181 1.67TOTAL 464 1.78

TOTAL BEST HEALTH 2,500 1.6

Socioeconomic status:

The primary care group needs to know the percentage of Medicare beneficiaries who also receive Medicaid benefits, the income of beneficiaries, their highest level education, as well as their level of English proficiency. These factors may impact patient compliance with medications and office visits, patient ability to understand



written and verbal instructions, access to computers, and sophistication with technology, including the ability to participate in patient portals (for registration, appointments, messaging, real time chats, provider communication, pharmacy alerts, patient surveys, laboratory and results acquisition) and effectively utilize home monitoring devices (transmission of real time data to provider tracking systems).

Patient Residence:

Since the primary care group operates out of multiple offices, it is important to have access to the zip codes of the practice’s population of diabetic patients. This will help to determine the allocation of resources across these sites, specific to the care of the diabetic patient, as well as the financial risk for certain PCPs at high volume facilities. This report could also help identify patients in outlying areas, who may utilize providers and/or hospitals outside of the network (network leakage).

Service Utilization:

The success of the ACO depends on proactive care management and preventive care programs across the continuum of patient care, as well as to commitment to “right place and time” care. It requires point of care access to all patient records, seamless communication among providers, consistent evidence based practices, case management, care plans, and discharge plans, consistent clinical decision support systems, and strong medication reconciliation and coordination. When patients are cared for by providers or hospitals outside the ACO network, there is no assurance that their care is being tightly coordinated or that it is in adherence to the best diabetic practices created by the group. By analyzing claims data, reports can be generated which demonstrate, by primary care practice, by office site, and by individual PCP, the number of units of service and the paid amount of service for diabetic patients to specialists and hospitals within and outside the ACO network. Furthermore, specific reports must be generated to demonstrate emergency room (ER) utilization by the cohort of diabetic patients. The reports need to be broken down by primary ER diagnosis, day of the week, and time of day, to define whether visits were appropriate, related to suboptimal ongoing diabetic care by the practice in general, or a PCP in particular, patient non-compliance, or larger issues reflecting on the overall practice’s or individual PCP’s access to care, effectiveness of care, or coordination of care. Reports need to be generated for individual diabetic patients within the practice, for the same metrics, with particular focus on the number of appropriate and inappropriate ER visits per year. Such patients may require more aggressive management, education, or oversight by care coordinators. (Singletrack Analytics, LLC, 2011)



Operational Reports:Ongoing tabular reports need to be created for the care management team. These reports can be converted into graphical summaries that visually reflect opportunities to improve ACO or practice workflows, amend care protocols, and to redistribute resources. Examples of such graphical summaries follow:

PCP 1 PCP 2 PCP 3 PCP 4 PCP 5 PCP 6 PCP 7 PCP 8 PCP 9 PCP 100

20

40

60

80

100

120

Diabetic Quality Measurement Report for Each of the PCPs within BMHA Practice

(% patients meeting metric)

HbA1C<8%LDL<100BP<140/90Non-smokerASA useHbA1C>9%

% pts

Figure 2: Glycemic control and adherence to ACO elements of diabetes care by practice site

020406080

Patient Characteristics by Practice Site

ChicagoEvanstonCicero % pts

Figure 3: Glycemic control and impact of ACO-related diabetes processes by practice site



Based on the above figures, as well as the risk adjustment scores for the individual practices and PCPs, certain deductions can be made. PCP #2 in Chicago and PCP #5 in Evanston care for the most complex patients with diabetes, either because they have severe chronic complications or severe co-existing conditions. Not unexpectedly, it appears that a higher percentage of the diabetic patients cared for by these 2 PCPs have HbA1C levels > 9%, compared to the rest of the PCPs within the practice. It would be helpful to know how many patients within their panels have conditions that would limit their ability to achieve tight glycemic control (e.g. advanced age, severe neuropathy, ischemic heart disease, renal failure, or limited life expectancy) or limit their ability to comply with medical advice (e.g. socioeconomic, language, psychiatric, and/or financial barriers). If we could identify modifiable factors that could be specifically targeted by new workflows (e.g. social workers, home visits, psychological counseling, educational sessions, nutritional counseling in the patient’s native language), we might improve the overall quality measurements reported by the entire practice.

Figure 4 suggests that there are opportunities to improve outcomes by examining the workflows at the individual practice sites. In the Evanston practice, far fewer diabetic patients are being followed by a nurse navigator and at the Cicero site very few diabetic patients are using the patient portal to communicate their fingerstick glucose results to their provider. Re-allocation of BMHA resources might correct these disparities. In addition, forty-two percent of the patients in the Chicago practice have had at least one out of network visit during the reporting year. The practice needs to investigate the reason for these out of network visits and attempt to create greater loyalty to the practice. This might require a change in the hours of operation, processes to allow greater accessibility to a provider after hours, more intensive patient education, more specific feedback from patient satisfaction surveys, and/or a reassessment of the complement of providers within the practice.

ANALYSIS METHODThe ACO and the primary care group, in particular, will be extracting and aggregating quality indicators from different silos of providers, electronic health records, claim submissions, and patient surveys. It will need to avoid duplication of reporting from disparate systems, normalize the platform of different electronic health record systems to allow direct comparability of outcome measurements, and overcome vocabulary mapping issues across different data inputs (CPT, LOINC, ICD), including the obstacle presented by the imminent transition from ICD-9 to ICD-10. Typically, hospital systems utilize the HL7 standard to transfer data in near real time. However, the ACO will be transferring data between billing, cost accounting, quality reporting, and home grown systems that do not all adhere to the same HL7 standards. It will also be integrating population and patient-specific data directly from CMS that are in flat file structures such



as XML, not in HL7 messages. Moreover, some external providers may submit data within spreadsheets that do not have a consistent data structure. The ACO will, therefore, need to rely on sophisticated centralized data integration tools used by data warehouses. (Pearce, 2011)

RESPONSIBILITY OF INDIVIDUAL PHYSICIANS TO MEETING THE GOALS OF THE ACO

One premise of the ACO model is to incentivize the physicians within the ACO to improve quality outcomes, coordination of care, and to reduce overall costs, through novel workflows. Individual physicians have a responsibility for the aggregate quality and cost metrics, and their performance will be aggressively scrutinized. Changing the vital behaviors of the individual physicians within BHMA will be an enormous challenge. While the 10 PCPs within the practice have agreed to join the ACO, most are highly skeptical about the performance bonuses promised relative to the initial investments in IT, staffing, and infrastructure, the early disruptions in productivity, and the heavy administrative burdens. There are few examples of successful integrated delivery systems in this country and all face similar challenges. (Lake, 2011)

Physician buy-in and ownership of change is pivotal to the success of the ACO. It is imperative that the practice identifies physician champions and leaders within the ACO, to foster a culture of transparency, teamwork, and communication. All the physicians within BHMA must be involved in ongoing discussions about organizational change, goals, management of the population of diabetic patients, and compensation parameters. This will help alleviate some of their general fears and resistances to change, shepherd them through some of the new delivery models for the registry of diabetic patients (e.g. evidence-based algorithms, use of navigators and mid-level providers, etc…), and the concerns that individual practitioners might have regarding ACO tracking and consequences of their patient outcomes and costs relative to the complex or non-compliant diabetic patients within their panels.

One of the major concerns of individual PCPs within the practice is the equitability of patient attribution and being held personally accountable for patient outcomes when patients are allowed to receive primary care services from multiple providers, including physicians outside the ACO network. According to the final ACO rules, a PCP will be designated as the accountable PCP if he/she provides the plurality of the beneficiary’s primary care services, with the stipulation that at least one primary care service is documented in the year (by CPT codes). If the beneficiary does not receive any primary care services from a PCP, he/she will be assigned to any physician (regardless of



specialty) who, along with a physician assistant of nurse practitioner, provides the plurality of such services to the beneficiary. The assignment will be updated quarterly and final assignment determined retrospectively at the end of the performance year, based upon the plurality test. This regulation allows the plurality of primary care services to be provided by an endocrinologist, perhaps a more appropriate point of contact for the complicated patient with diabetes. (Pantely, 2011)

From a Medicare reimbursement perspective, the ACO must educate its providers aggressively, about accurate and specific coding and documentation. ICD-9 codes, mapped to hierarchical condition codes (HCCs) drive Medicare reimbursement, so that payments are adjusted based on disease severity, rather than demographics. This is called the Risk Adjustment Payment Model and reflects the cost of caring for Medicare beneficiaries. The HCC is a prediction of the cost of taking care of that patient for the year. Conceptually, therefore, providers are incentivized for caring for sicker patients. Patients are assigned codes based on ICD-9 diagnoses throughout the year. In fact, patients who have multiple chronic diseases and co-morbidities via the HCC system will receive higher payment reimbursement. Payment is based on the most severe HCC documented. Each member’s HCC ICD-9 values are added together and the sum (the Risk Adjustment Factor or RAF) is added to an age/sex adjustor and multiplied by a predetermined dollar amount. This RAF determines the Medicare reimbursement to cover the services provided to that beneficiary for the year and affects the monthly reimbursement for the ACO. If the RAF score is underestimated, by suboptimal capturing of beneficiary diagnoses and inadequate ICD-9 submissions by providers, there can be significant reductions in payment. This underscores the need for providers within the practice and ACO to submit accurate and granular ICD-9 codes within the diabetes model of care and to make sure the documentation to support these ICD-9 codes is indisputable. Furthermore, the providers must be more comfortable with coding for more complex office visits, which will substantiate the face to face encounters to support the higher costs of care.

For a patient with diabetes, ICD-9 codes 250.40, 250.41, 250.42, and 250.43 will all be mapped to HCC 15, Diabetes with Renal or Peripheral Circulatory Manifestation. Therefore, if different providers throughout the year submit claims with different ICD-9 codes for diabetes, CMS will perform a hierarchal analysis and select the code mapped to the highest HCC code. HCC 15 will “outrank” HCC 19 (diabetes without complications) because it will be more expensive to care for the patient with HCC 15. This highlights the need for the practice and ACO to develop processes for the providers to be more granular in assigning ICD-9 codes for the patients with diabetes. It has been demonstrated that most providers list less than 2 ICD-9 codes per patient claim. If our practice does this, the RAF for its diabetic patients will underestimate their disease burden and predicted yearly costs of care. A provider needs to find related



ICD-9 codes that can increase reimbursement. If a claim is made for a diabetic patient with an ICD-9 code 250.40 (diabetes with renal manifestations), there must be processes in place to look for other documentation of disease manifestations that could support co-reporting of ICD-9 code 585.3 (chronic kidney disease), for instance documentation of a low glomerular filtration rate. The latter is mapped to HCC 131, which can be co-reported with HCC 15. Diabetes with renal manifestations (ICD-9 250.40) can also be mapped to RxHCC 17, which allows both components of the Medicare plan to receive increased payments. (Yuil, 2011)

Proper capture of diagnoses will entail other operational changes within the Best Health Medical Associates practice. CMS requires face to face patient visits for documentation of ICD-9 codes. If lab data demonstrates a low glomerular filtration rate on a patient, this cannot be submitted as an ICD-9 code for higher reimbursement unless there has been medical documentation by an acceptable provider via a face to face encounter. CMS performs random audits to validate that HCC codes are supported by the proper medical documentation.

TECHNICAL SOLUTIONS TO SUPPORT ACO

In order to successfully leverage the coordination of care needed to participate and meet the goals of the ACO, a significant investment in a technology infrastructure is required beyond the initial EHR investments already made by the primary care group and hospital. Because the different providers of care within the ACO are not all on a common integrated EHR, disparate data sources present a challenge for collecting, comparing and reporting quality and financial performance metrics. In addition, patients need to be engaged with tools to manage their chronic disease conditions, such as diabetes, in ways not previously utilized with traditional physician based encounters. The opportunity to change the course for diabetes outcomes will be best realized by offering quick and efficient methods of information exchange between both patients and providers and between the care team providers, and applying clinical decision support to guide them to improvement.

One of the keys to monitoring and improving the utilization pattern, thus reducing overall cost of care is for the ACO to have a holistic view of that care across all providers. Currently, there is no mechanism for the ACO governing entity to have visibility into the cost of care, with the exception of quarterly reports from CMS that will summarize the utilization for beneficiaries in the ACO. In order to determine where additional resources should be applied, such as with high risk patients that have comorbid conditions or more significant disease burden, or those patients who have not received recommended preventative care, the ACO needs tools to intelligently track important data across its population of diabetic patients. Shaping this data into predictive



modeling can also highlight areas to focus interventions and apply additional resources. Collectively, patient data will need to be mined, as close to real time as is possible, in order to optimize care and direct utilization where it can be best leveraged for improved outcomes. The ACO will also need to identify how their patient population is performing financially compared to the baseline performance set by CMS for them. By monitoring utilization across the first year of ACO participation, the group will be able to predict whether or not their care model is sufficient to demonstrate shared savings over the following 2 years, and what adjustments will be necessary to do so once the payment model shifts to a performance based one.

Health Information Exchange (HIE)Transformation of BHMA into an accountable care organization demands effective patient information exchange and practice redesign from current state workflows (geared to fee-for-service) to the future state workflows of accountable care. Technology is imperative to empower this transformation and the most critical aspect of this transformation is Health Information Exchange (HIE).

A word of caution regarding HIE’s: Formation of sustainable HIE’s has been a challenge as evidenced by numerous recent failures of well-established RHIO’s (Regional Health Information Organization). In fact, a recent review of HIE’s reported that two-thirds of the respondents did not meet the authors’ criteria for financial viability. (Adler-Milstein, 2011) Though comprehensive review of formation of an HIE is beyond the scope of current discussion there are a number of important considerations to highlight.

First, electronic exchange of healthcare information to coordinate care between providers and patients is required for all stages of Meaningful Use. HIEs have been a reliable platform to exchange electronic healthcare information, but are not available yet in all areas, nor is there a standard model of success emerging from the multitude of initial startups. Meaningful Use was implemented with the HITECH Act of 2009 and describes a series of incentives and penalties for organizations which use or fail to use technology effectively in the care of patients. For BHMA qualification for all stages of Meaningful Use will bring $440,000 in Medicare incentive payments. Penalties for not meeting Meaningful Use Stages begin in 2015 and grow progressively. Healthcare providers who are not actively planning to meet the Meaningful Use stages should be planning their merger with a compliant organization or face their retirement/extinction. BHMA has an EPIC EHR and thus already has a great foundation for meeting Meaningful Use. Attesting for this incentive program will allow for recapture of some of the investment required to implement the EHR.

Second, because HIE is the foundational infrastructure for the ACO to function, BHMA will need to participate in the HIE platform used by the ACO. As BHMA assists the



ACO in choosing an HIE, several features need to be examined in detail: structural model, governance, privacy and security, and cost.

HIE ModelThree primary HIE data models currently exist: Centralized, Federated and Hybrid. In the centralized data model the data from the participants is received and stored in a unified central database. This model creates efficient data access but at a cost of duplicated data and loss of control of an individual participant organization’s data. Queries to the centralized HIE are answered from the central database. In the federated model, the data resides at the local level, and pointers to the data are created in a central repository. Control of data remains at the local level. Queries to federated HIE are processed first centrally and then appropriate queries made to the institutional databases to supply the information. The compromise with this type of model is slower speed of query, and the need to maintain a multitude of point to point connections. Hybrid HIE’s combine the two models to varying degrees. For high value or frequently queried information, hybrid HIEs will often form Data Marts that aggregate the information prospectively, and thus do not rely solely upon query of federated sources. (Rishel, September 29, 2010)

HIE’s can be operated for profit, not for profit, as a public utility, or as a physician-payor collaborative. The majority of HIE’s are not for profit organizations, a structure favored by lower funding requirements and accompanied by tax breaks. Not-for-profits are also often eligible for grant funding to help establish infrastructure. (While grant money may be helpful to initiate formation of an HIE, it should not be necessary to the ongoing operation of the HIE—dependence on this has been the downfall of many HIEs.)

Strong security and privacy controls must be included in the HIE. Controls that BHMA should look for when assessing an HIE include:

1. Accountability with audit logs, and appropriate alerts and alarms2. Authentication –proof that those accessing the system are permitted to

access and that they are who they claim to be3. Access—control to limit access to specific data based on authorization

agreements of the HIE4. Data integrity—methods to insure that data has not been corrupted/altered5. Patient privacy6. Backup/availability

Fortunately, BHMA and the ACO are both located near Chicago, where the MetroChicago Healthcare Council has announced the formation of an HIE which at its inception will include 70% of the metropolitan Chicago hospitals as well as many of the major outpatient healthcare providers. Analysis of the patient demographics for BHMA



shows that the vast majority of their patients receive their care within this region and when seeking consultative care their patients receive care from specialists in the MetroChicago Healthcare region as well. Columbia West, the primary hospital used by BHMA is also a participant in this HIE. MetroChicago Health Information Exchange (MCHIE) is creating a centralized database model, using software from HealthUnity to enable bidirectional data exchange with Microsoft Amalga. This architecture will allow high levels of operational and clinical performance. As well, it should be financially efficient for BHMA to utilize MCHIE to centralize data for transformation and normalization. By partnering with MCHIE, BHMA will be in excellent position for accountable care, as well as Meaningful Use.

Features of the Amalga product which are favorable for BHMA are:

Centralized duplicated near real-time database Centralized data manipulation Ability to create and produce ad hoc queries vs static reporting only

(Holland 2009)

Figure 4: Function of Amalga, described diagrammatically by Microsoft

Participation in the HIE is only a fraction of what must be done to capture the metrics used to judge the care delivered to the diabetic patients in the ACO. Results of care delivered by providers outside of the HIE must also be made available or risk the cost of



redundant care. BHMA must do an inventory of the consultants that they currently utilize. The inventory will identify the consultants who have EHRs and will participate in MCHIE. Assuming there are available consultants who both have EHRs and participate in the HIE, some referrals may need to be redirected to these participants and away from those who cannot provide the information electronically. Referral patterns are often ingrained; thus to effectively change the pattern, workflows must be intentionally redesigned. If consultants who participate in the HIE are not available, then the information from their consultations will need to be added to manually. One way to accomplish this would be through a disease registry which allows providers to log into a central registry on the MCHIE and complete their portion of the information. The Quality Health First program is an example of such a functioning health information exchange disease registry. “The Quality Health First Program allows physicians to reconcile missing or inaccurate data to make patient-specific information as relevant and up-to-date as possible” (Quality Health First Program: Solutions, 2011)



Figure 5: Information flows required for a functional ACO

TECHNOLOGY ENHANCING CLINICAL DECISION SUPPORT

BHMA is fortunate to have had the foresight to implement the EPIC EHR. As a single database which incorporates the clinical and billing data, the EPIC database will be



easier to extract data regarding care delivered and cost of care. However, without redesign of practice, neither the quality metrics nor the cost savings will be consistently achieved.

Patient calls for appointment

Appointment made with physician

Physician sees patient, orders

tests, schedules follow-up

Lab tests performed

Imaging studies

performed

Consultant referral

CURRENT STATE WORKFLOWS

Patient seen at follow-up visit50% testing information

missing

Second patient visit necessary

=Billable Event

Figure 6: Current State Workflow



Above is the current workflow surrounding a patient visit. It is clear that the current state is maximized for fee for service; thus there is great room for improved efficiency with greater provider and patient satisfaction.

Patient calls for appointment

Front office enters

appointment request

CDS runs in background

Is patient diabetic

Routine DM evaluations completed?

High Risk profile for DM?

Needs additional

testing

Gather previous testing

Schedule screening tests per protocol

Patient sees MD all needed testing

complete and available

YES NO

NO YES YES

= BILLABLE EVENT

FUTURE STATE WORKFLOW PATIENT SCHEDULING

(HIMSS, July 2011)

Figure 7: Future State Workflow

In this future state workflow, by simply identifying the diabetic patient early (at the time a request for an appointment is being made), the system can initiate clinical decision support (CDS) which drives scheduling of appropriate care, gathering of available pertinent clinical data, and avoidance of unnecessary or duplicative care. While this example is geared specifically to diabetes care, other disease management care initiatives could be supported with appropriate CDS parameters.

This proposed re-engineering of patient scheduling is an excellent example of using clinical decision support without disrupting workflows. A classic informatics monograph



from 2003 proposed “Ten Commandments of Clinical Decision Support”. As BHMA contemplates the workflow and practice design necessary to achieve accountable care it will benefit to keep these rules in mind:

(BATES 2003)

Capturing patient level data relevant to the care of the ACO diabetic patients which occurs outside of the practice and the HIE will initially be a challenge. Over the next few years it is expected that market pressures will force the majority of providers to adopt an EHR and participate in Health Information Exchange, thus improving this challenge but not totaling eliminating it.

EHR Workflow using HIE InformationParticipation in an HIE does not guarantee that the information available for patient care will be accessible timely or utilized in a manner that can positively impact decision making at the point of care. Examining the physician workflow and presenting pertinent information without requiring additional time for logging into different portals, locating patients in that environment, and searching on what information is available are critical to bringing value without adding to the electronic workflow complexity. The types of information that can be retrieved from the HIE and made available for the physician are:

Encounter information including diagnoses (from other providers, hospitals and EDs)



Medication history (from pharmacy dispensing histories and EHR medication lists)

Test results (from labs and other diagnostic studies) Care summaries (in the form of transcribed reports and CCD formats)

(HIMSS, July 2011)

How this information gets retrieved and presented to the physician during an office visit can be the difference between an extra 10 to 15 minute work effort to hunt for and collate versus a 1 to 2 minute review of what is ready and waiting in the EHR for review. Going beyond web based access to HIE information is necessary to integrate these workflows into the EHR, which will minimize the risk of failure to realize a true return on investment with participation in the HIE. Structuring the HIE connectivity to the BHMA EHR to be automatically queried and cached in the EHR within a patient context is the most effective way to minimize search efforts. The ability to resend information back to the HIE upon completion of an encounter can also be automated, such as when the patient’s note is finalized within the EHR. The primary mechanism for transmission to and from the HIE is via HL7 standards, and will require upfront work with creating single sign on into the HIE from the EHR, patient identification matching between the EHR and HIE to keep patient context accurate, and triggers defined within the EHR workflow to automate information exchange actions. (HIMSS, July 2011) Research with the prospective HIE vendor is important to ensure that this vendor has successfully managed this level of integration with the EPIC EHR.

Another area of HIE functionality to evaluate is patient to provider and provider to provider messaging capabilities. Because the ACO will rely on coordination of care between different specialty groups and services, communication between providers is a critical factor. The EPIC EHR has a functionality to enable provider to provider messaging, but not all groups in the region use EPIC as their EHR, and ancillary services providers are unable to engage as well. Leveraging the HIE vendor for secure messaging across the community will be a logical solution for this problem. This also creates another potential workflow disruption – having 2 different messaging sources to manage for the provider. By routing messages directly into the EHR inbox so that they can be managed from one work queue, this disruption can be avoided.

Patient engagement and communication is another challenge that will ultimately need to be addressed. Currently, BHMA uses EPIC’s “My Care” patient portal to communicate securely with patients and send reminders electronically. What the patient experiences is multiple places to log in and message with different physicians in different groups, and no way to collate their information across the community of health care providers into a single place. Engaging patients to provide more effective health information and self-management tools will require consolidation of existing communication venues and development of more robust interactive tools. The community HIE is a natural venue to



shape for patient engagement, as it becomes the hub of community information in a patient centric way. Secure patient messaging, along with the ability to integrate these functionalities within BHMA’s EHR workflow, are additional functionalities to explore with the HIE vendor.

Opportunities for practice redesignParticipation in an accountable care organization fundamentally changes doctor-patient relationship (without necessarily reciprocity on the part of the patient). In the traditional fee for service, encounter based environment, physicians see the patient, recommend care (test, medications, etc.) and patients may or may not follow through with those recommendations. Because each encounter with the physician or test ordered has potential to generate revenue, there has been little incentive to the physician to manage care outside of the visit. The shift of incentives in the ACO model now drives the physician to oversee care for the patient beyond the brief office visit. The focus is now on managing the patient’s care overall, and promoting optimal utilization of value added services. Providers must concern themselves with results of their recommendations—did the patient pick up the prescription, did the patient have the recommended blood test, does the patient understand their chronic disease sufficiently well to manage the acute exacerbations. When the answers to these questions are left to chance, the quality of the patient’s care suffers and the cost of care increases significantly.

Examining the workflow around prescriptions: In the current state, the provider writes a prescription which the patient fills or doesn’t fill at their discretion. In a recent study of e-prescribed medications, the non-fill rate for anti-diabetic prescriptions was 31%. That same study reviewed prior reports based on patient self-reporting of non-compliance for all medications. Those studies reveal that patients only admitted non-compliance 4-22%. (Fischer MA 2010) Emergency and urgent care for these non-compliant patients will occur far more often and will more often involve hospitalization. If the ACO does not impact the high non-compliance rates, it is unlikely that the desired quality measures will be reached.



Provider ePrescribes medication

Surescripts/Rx Hub

receives Rx

Patient picks up prescription

Patient fails to pick up prescription

Practice queries Surescripts / Rx

Hub

Patient contacted regarding

prescription

Figure 8: Proposed new workflow around prescriptions for diabetic patient population

This proposed new workflow will inform the system of the patient non-compliance, at least at the prescriptive level. Reasons for non-compliance can be examined and potentially changes made to use medications which mitigate the reasons for non-compliance such as side-effects, costs, fear of needles, etc.

Providers will also need to examine the refill history for patients—if medications are not being filled with appropriate frequency this may indicate non-compliance or partial non-compliance on the part of the patient. Presenting this information to the provider at the time of encounter will prompt a discussion of the reasons for non-compliance—even better, monitoring this information continuously will allow even earlier contact with the patient instead of waiting for the next visit (which could be an emergency visit resulting in morbidity, and unnecessary costs). Follow up calls have been shown to be effective in improving diabetes compliance. (Piette, Weinberger et al. 2001)



Concept of clinical inertia Diabetic patients most often are treated initially with oral hypoglycemic agents. There is often a reticence on the part of the patient and the physician to escalate to more intensive treatment, especially when it involves insulin initiation. In a study reported in Diabetic Care in 2005, less than half the patients with elevated HbA1c levels had intensification of their diabetes treatment. (Shah 2005) Clinicians who are not prone to clinical inertia and are more aggressive in their intensification of diabetes therapy have improved HbA1c levels in their patients which has been shown to be associated with lower risk of microvascular complications of diabetes.(Lynch CP 2010)

The following represents a graphical summary of the pattern of insulin use by BHMA providers, relative to the reportable glycemic measures:

0

10

20

30

40

50

60

70

80

Insulin Use by BMHA

HbA1C < 8%HbA1C > 9%

% Pts

Figure 9: Insulin use and non-use by diabetic patients within the BMHA practice

Such visual feedback to the providers can drive practice algorithms to incorporate more aggressive insulin management for patients with poor glycemic control.

Whose patient is it?Clinical inertia is but one example of variation in practice between providers. To be able to analyze provider performance on an individual provider level, BHMA providers must prospectively decide on a paradigm for patient care attribution. Without such an agreement, providers will rationalize away their variation in practice (my patients are sicker . . . . my patients get just the care they need . . . . the data is flawed).

Patient based attribution assigns the entirety of care and cost of care to a single provider. Episode based attribution assigns each episode of care to a provider.



Because patients often see multiple providers, it may be difficult to fairly attribute care to a single provider.

Prospective assignment of patients to a provider allows real-time reporting to each provider a performance dashboard with quality metrics, cost information and case mix severity adjustment. Physicians are in general quite competitive and when presented evidence of their performance vis a vis peers, they will voluntarily alter behavior to meet or exceed the performance of the norm.

Beyond Diabetes ManagementExcellence of diabetes management is but a fraction of behaviors needed to realize shared savings for the ACO. Numerous complementary practice changes must be made to control costs and improve patient outcomes. Briefly some of the ideas include:

o Initiatives to keep patients out of ED and hospital: Patient education resources in diabetes management

Classroom Internet

Greater practice availability through evening and weekend hours Block greater time in schedule for urgent patient visits Emphasize PHR for patients—creates portability of their medical

history when seeing other MDs or travelling Nursing or mid-level telephone follow up

o Initiative to control imaging costs: Implement a radiology decision support system such as OrderRight

or RadPort

Word of cautionBHMA must continuously and actively assess their performance. Just this month in the NEJM, it was reported, “In light of the results of other CMS disease-management programs and the unsuccessful interventions in this large, randomly designed study, it is unlikely that simply managing the care of elderly patients through telephone contact or an occasional visit will achieve the level of savings that Congress had hoped for when it mandated the Medicare Health Support Pilot Program. These findings also suggest that for such programs to be effective, they need to include intensive, costly, personal clinical attention.” (McCall 2011)



CLINICAL, TECHNICAL AND FINANCIAL ANALYSIS

A recent study by the National Institute of Health Care Reform identifies four universal challenges in developing quality initiatives within ACOs. (Timothy K. Lake, 2010) The study examined healthcare organizations that are involved in efforts to improve care coordination and quality, all of which are key activities pursued by ACOs. While each organization faced different challenges in developing infrastructure for coordinated care delivery, the study identified four challenges that were "nearly universal."

1. Funding and the business case for change. ACO-like improvements require substantial investment in both time and money that may not be reimbursed directly, according to the study. While increased payments to ACOs and medical homes could create a business case for these activities, financial rewards from these investments may "not materialize for a long time, if ever."

2. Resistance to change. Staff members are resistant to assuming new responsibilities or delegating work they use to perform. In some cases, the organizations faced challenges in recruiting and training employees with the appropriate skills for these roles.

3. Potential disruptions to productivity. According to the study, "many of the care-delivery and infrastructure improvements [such as EMR and patient registries] required changes in workflow that affected productivity of clinical and administrative staff.”

4. Limited infrastructure to pursue change. Efforts to improve care coordination and delivery require a great deal of accurate data, which presents a fourth challenge to ACOs. Organizations in the study noted inaccurate data inhibits population management and financial incentives for health improvement. Organizations also mentioned concerns about sharing patient data under privacy regulations.These challenges represent the fundamentals which determine the total amount of risk involved in participation in an ACO project. The best approach is to develop a risk analysis tool. Each organization will need to examine the relative advantages and disadvantages in order to quantify the relative risk associated with their participation. We will need to examine:

Scenarios for future reimbursement structures and levels The organization’s risk appetite and the risk appetite of its affiliated providers Access to capital given the ACO’s regulatory environment Administrative capability Opportunity to reduce cost through utilization reduction, relative to current

utilization levels Infrastructure and IT capabilities



Potential synergies with other payers

Table 5: Practice Risk Analysis ToolRisk Characteristics Relevant Criteria

Scenarios for future reimbursement

ACO payment methodology: Medicare Shared Savings Program. ( Medicare fee-for-service)Bundling of payments (future)

Organization’s risk appetite and risk appetite of affiliated providers

Funding and the business case for change.Financial rewards from these investments may "not materialize for a long time, if ever."

Access to capital given the ACO’s regulatory enviroment

ACOs must agree to participate in the demonstration for at least three years.Risk Based Capital (RBC)Down side risks require additional capital

Administrative capability A formal legal structure that would allow the organization to receive and distribute payments for any shared savings.Processes to report on quality and cost measures. The Ability to coordinate care across patient conditions, services, and settings over time.

Opportunity to reduce cost through utilization reduction

Savings achieved in excess of a CMS threshold benchmarks. Defined processes to promote evidence-based medicine.

Infrastructure and IT capabilities

Ability to build and make effective use of information technologies for health care delivery and administration at provider, patient and system level.The ability to integrate systems and aggregate data across multiple sites of care.

Potential synergies with other payers

Shared management of risk.Ability to help providers leverage outcome data.Shared savings models.

Sharing Savings and Sharing Losses



Under the proposed rule, Medicare would continue to pay individual providers and suppliers for specific items and services as it currently does under the Original Medicare payment systems. CMS would also develop a benchmark for each ACO against which ACO performance is measured to assess whether it qualifies to receive shared savings, or be held accountable for losses. The benchmark is an estimate of what the total Medicare FFS Parts A and B expenditures for ACO beneficiaries would otherwise have been in the absence of the ACO, even if all of those services would not have been provided by providers in the ACO. The benchmark would take into account beneficiary characteristics and other factors that may affect the need for health care services. This benchmark would be updated for each performance year within the three-year performance period.

CMS believes this approach would have the advantage of providing an entry point for organizations with less experience with risk models, such as some physician-driven organizations or smaller ACOs, to gain experience with population management before transitioning to a risk-based model, while also providing an opportunity for more experienced ACOs that are ready to share in losses to enter a sharing arrangement that provides a greater share of savings, but at the risk of repaying Medicare a portion of any losses.

If an ACO meets quality standards and achieves savings exceeding the minimum savings rate, the ACO would share in savings, based on the quality score of the ACO. The proposed rule would provide for additional shared savings for ACOs that include beneficiaries who receive services from a Federally Qualified Health Center or Rural Health Clinic during the performance year. (CMS D. H., 2011)

For each year, CMS will develop a target level of spending for each ACO to determine its financial performance. Because health care spending for any group of patients normally varies from year to year, CMS will also establish a minimum savings and minimum loss rate that would account for these variations. This protects the Medicare Trust Funds from sharing savings, and providers against sharing in losses, due to normal variation in Medicare spending. Both shared savings and shared losses will be calculated on the total savings or losses, not just the amount by which the savings or losses exceed the minimum savings or loss rate. In addition, the amount of shared savings would depend on how well the team of providers performs on the quality measures specified in the rule. (HHS, 2011)



(HHS 2011)

Figure 10: CMS Shared Saving Program

Physicians volunteering to be part of the effort would share risk by paying penalties for failing to coordinate care and costing Medicare more money than anticipated. ACOs will work only if all doctors who want to participate are able. Significant barriers must be addressed, including the large capital requirements to fund an ACO and to make required changes to an individual physician's practice. An estimated 1.5 million to 4 million Medicare patients will receive care from an ACO, CMS said in the proposed rule. The agency estimates startup costs and first-year operating expenditures for each ACO would be $1.76 million. Payouts to the 75 to 150 ACOs could reach $800 million in bonuses over three years, although CMS estimates it would assess $40 million in penalties. (Fiegel, 2011)

AssumptionsProviding consultation requires making some general assumptions. We must limit the scope and depth of our analysis. Our analysis will assume that the ACO will fully meet the quality performance measures. This could be difficult for some ACOs, and there is a real possibility that any shared savings could be reduced or eliminated. The shared



savings plan is not a guarantee; this is an opportunity for health care providers. All savings will be based on their ability to provide more efficient quality care. We must also assume that all ACO services are provided by ACO providers. Any proportion of services delivered by a non-ACO provider will lower the cost savings. Our recommendation is: that all services for diabetes quality improvement project are delivered 100% by ACO providers. Your organization does not have any rural health providers, and as such we did not consider their involvement in our report.

ANALYZING THE RETURN ON INVESTMENT (ROI) FOR A QUALITY IMPROVEMENT PROJECT

In analyzing the Return on Investment (ROI) for any Quality Improvement (QI) project, it is important to consider all financial contributors, including those due to secondary effects. Doing so can provide a more complete and accurate view of the financial impact of the project. It can even reveal hidden opportunities that can improve the financials of the project.

Table 6: Primary and Secondary Financial Effects of the Diabetic Quality Improvement Project

Primary Financial Effects of Quality Improvement Project Hard $ Soft $Cost savings due to reduced readmissions

Readmission revenue loss (due to reduction of readmissions)

Medicare reimbursement penalty avoidance (Future)

Cost of quality initiative investments

Patient care quality improvement

Hospital ratings improvement

Secondary Financial Effects of Quality Improvement Project Hard $ Soft $Bed capacity improvement (replacement opportunity)

ED capacity improvement



Medicare reimbursement increase (care transition improvements)Patient satisfaction improvement

Increased staff satisfaction

Reduced adverse medication errors

Reduced medical malpractice costs

Accountable Care Organizations (ACOs) interested in improving patient care quality and safety should naturally be eager to take on quality improvement (QI) initiatives to improve the quality of patient care. However, in the healthcare payer model that exists today, financial incentives reward hospitals for readmissions, and efforts to reduce them appear to incur financial losses—most Chief Financial Officers (CFO) and CEOs thus question such initiatives. Currently, but likely not in the future, payers (Medicare or private insurance) reimburse readmission cases just like new patient admission cases. Although successfully reducing preventable readmissions benefits the healthcare system by reducing overall cost of delivery, it may actually hurt hospitals by lowering their revenues. Notable exceptions to this are hospitals that are part of an Accountable Care Organization (ACO). In an ACO, the provider and payer function as one. Therefore reducing unnecessary readmissions is of immediate financial benefit to the ACO. For the majority of hospitals facing financial pressures in the current economy, it can be very difficult for a hospital CFO to sign off on a QI project that requires incremental investment and reduces revenues, even if it improves patient quality. (Subramanian, 2010)

ACO DIABETES IMPROVEMENT PROJECT ROI

Program Costs

Most interventions require financial investment. This investment may come in the form of additional staffing, training and education, general office operations, equipment, construction, or other direct or indirect expenses. These costs must be accounted for in calculating return on investment.



Table 7: Estimated Program Costs by Year

Pre-Launch Year 1 Year 2 Year 3 Total

Personnel 120,000.00 60,000.00 60,000.00 60,000.00 $300,000.00

Training and Education 95,000.00 30,000.00 27,500.00 27,500.00 $180,000.00

Office Operations 29,000.00 17,000.00 17,000.00 17,000.00 $80,000.00

Technology and Equipment (HIE)

150,000.00 40,000.00 40,000.0040,000.00

Total:

$270,000.00

$ 830,000

Table 8: ROI

ROI (Return on Investment)

Target Population

Eligible Population Adults

Total Membership in Eligible Population 45,000

Clinical Focus Diabetes

Target Strata High Risk

Outreach Goal 99.00%

Ramp-up Period 12 months

Total Target Population Members 2,475

Total Intervention Group Members 2,450

Utilization Assumptions - Cost Increases/Decreases

Year 1 Year 2 Year 3



Inpatient -2.00% -4.00% -6.00%

Emergency Department -4.00% -8.00% -10.00%

Outpatient -2.00% -4.00% -6.00%

Home-Based Care -2.00% -4.00% -5.00%

Laboratory -2.00% -4.00% -7.00%

Pharmacy -4.00% -4.00% -5.00%

Savings per Intervention Group MemberYear 1 Year 2 Year 3 Total

Inpatient $136 $300 $495 $932Emergency Department $253 $582 $836 $1,671Outpatient $89 $209 $370 $667Home-Based Care $73 $160 $220 $452Laboratory $55 $127 $256 $438Pharmacy $84 $92 $126 $302Total per Member $689 $1,469 $2,303 $4,462

Organizational Total $914,701 $3,600,226 $5,642,013 $10,156,940



(Center for Health Care Strategies, 2007)

Figure 11: Estimated Cumulative Return on Investment

An ACO can function with only one payer; however the provider response to shared savings incentives will be enhanced by having a critical mass of payers participate in the program. Ideally, all the payers in the market (both public and private) will participate. A shared savings program that aligns incentives among multiple public and private payers will strengthen an ACO’s incentive to improve efficiency, make necessary investments in infrastructure and process improvement, reduce capacity that does not contribute to higher value, and reduce reporting burden on providers. A unified approach would also minimize incentives to shift utilization outside of the participating payer(s).

The Final Rule intelligently advances a framework that makes it possible for providers to develop and operate the same care management and coordination programs, for multiple payers. Both the fraud and abuse and antitrust policies being promulgated alongside the Final Rule open the door to the development of multi-payer ACO initiatives. The final statement issued by the Department of Justice and the Federal Trade Commission eliminates mandatory antitrust review for arrangements that have a market share of greater than 50 percent and confirms that an ACO participating in a Medicare Shared Savings Program (MSSP) will be deemed clinically integrated with respect to commercial arrangements utilizing the same infrastructure.

Similarly, in the Interim Final Rule relating to the Federal fraud and abuse laws, CMS and the HHS Office of the Inspector General significantly broaden the waivers available



to MSSP ACOs to cover not only shared savings, but also investments in infrastructure and operations as well as incentives to encourage beneficiaries to access preventive care and comply with treatment regimens. Significantly, the expanded waiver authority applies to investments that advance goals of both the Medicare Shared Saving Program and commercial arrangements, creating a much bigger opportunity for multi-payer ACO solutions involving commercial carriers and Medicaid state agencies.

An American cultural truism is that hospitals and doctors apply the same standard of care to all patients regardless of their ability to pay. While this commitment is laudable, the marketplace has shown that it is difficult to sustain financially. (Graf, 2011) Historically, the fiscal health of U.S. hospitals and health systems has been tenuous at best, and largely predicated on these institutions generating profits from commercial health insurance plans to cover losses assumed when caring for individuals who either don’t have insurance or are covered by Medicare or Medicaid (see Figure 12).

(Graf, 2011)

Figure 12: Estimated Gross Profits for a Representative U.S. Hospital (2010-2011)

Commercial health insurance plans typically constitute approximately 45% of net patient revenues associated with hospital visits, procedures and related care conducted annually nationwide. Commercial health insurance plans also generally provide the majority of hospitals’ gross profits because their reimbursement rates are significantlyhigher than those from federal agencies (e.g., 140% of Medicare rates). Conversely, hospitals are typically only reimbursed 92% of their care costs for typical Medicare patients and approximately 83% for Medicaid enrollees. (Graf, 2011) Insurers would be



prudent to use the Medicare standards as a starting point for commercial arrangements with ACOs. The standards that CMS has established for participation in the Medicare Shared Savings program are likely to become standards that are utilized heavily in the commercial sector. There’s a tremendous legal benefit in utilizing the Medicare standards in the commercial market from an antitrust, and even to some degree, from a fraud and abuse standpoint. (Dartmouth Institute, 2008)

The Department of Justice and the Federal Trade Commission in conjunction with the rulemaking issued a proposed policy March 31 for providers on how they could form ACOs without breaching any antitrust laws. “FTC and DOJ have said that if you are approved as an ACO by Medicare, by definition you are considered clinically integrated under the antitrust laws, and that means collective efforts by hospitals and doctors won’t be considered price fixing. You will be insulated from antitrust review. And if your market shares are larger, you can get approvals from the antitrust agencies.

If a Medicare-approved ACO attracts some commercial payers and adopts a completely different framework for how it’s going to manage care, set protocols, and do data collecting and reporting, it’s not clear the ACO will have that same benefit of clinical integration “because it won’t be engaged in the same activities that Medicare constitutes as clinical integration. ACOs that use the same model for distributing savings generated from commercial payers as they do under the Medicare Shared Savings program may be in a stronger position to claim protection on the fraud-and-abuse side for commercial payers as well, given that the new rule contains waivers in certain circumstances from the anti-kickback statute and the Stark law.

This diabetes improvement project presents a tremendous opportunity to demonstrate the business case for improving health care quality. Investing in this program will more effectively manage the care of these high-risk, high-cost beneficiaries and will improve health outcomes, reduce unnecessary utilization, and control Medicare expenditures. This investment can ensure greater value for every Medicare dollar spent, while providing the highest quality of care for those who need it most.

Summary of Recommendations

Short Term Changes (0-6 months):1. Create monthly reporting from EHR to monitor BHMA diabetes based care

quality: Number of patients with specific chronic disease conditions of diabetes,

ischemic vascular disease, hypertension, coronary artery disease, and heart failure by all payers, Medicare only, and non-Medicare



Number of patients with diabetes and have HbA1C not tested within past year, value <8%, value 8-9%, and value >9%, by all payers, Medicare and non-Medicare

Number of patients with diabetes and have BP <140/90, and =>140/90, by all payers, Medicare and non-Medicare

Number of patients with diabetes and have aspirin in their med list by all payers, Medicare and non-Medicare

Number of patients with diabetes and have LDL not tested within past year, <100 or =>100 by all payers, Medicare, and non-Medicare

Patients with a diagnosis of diabetes who have not had a visit within the previous 12 months, by all payers, Medicare and non-Medicare

2. Create reporting from EHR to segment potential ACO patients cared for by BHMA

Number of patients with primary care visits for the group by payer, reconcile with CMS ACO reports quarterly

3. Create reporting from EHR to evaluate cost of care with chronic disease states: For all patients with diabetes, those on insulin therapy with HbA1C values

in the categories defined in 1. For all patients with diabetes, medication cost estimate (using AWP for

meds in patient's med list) by all payers, medicare, non-medicare4. Develop Clinical Decision Support within EPIC EHR:

Alert for medications ordered but not filled within 2 weeks Alert for laboratory tests ordered but not completed within 1 month Alert for missed scheduled appointments for patients with diabetes

5. Employ a diabetes nurse navigator to review BHMA diabetes patient care reports monthly, and target resources to improve patient compliance

Mid Term Changes (6-12 months):1. Evaluate and select HIE vendor for functional capabilities with regards to:

Inventory of community physician participation with HIEs within the state (which physicians are connected with which HIEs)

HIE Vendor Single Sign On capability with EPIC EHR Capture of and normalization local lab values in patient context Capture of claims data for patient community CCD exchange with GE Centricity for Columbia West CCD exchange with EPIC EHR for BHMA CCD exchange with additional community EHRs Web Portal for direct HIE access and ability to update patient information Disease management registry capabilities Reporting capability for ACO patient population and BHMA patient

population



Patient Portal functionality for messaging and maintaining a personal health record with updates from provider EHRs

2. Invest in HIE participation with priority development of the following: Automated data exchange with EPIC EHR to retrieve HIE information

upon patient visit registration and send information to HIE upon patient discharge

Bidirectional medication information exchange from HIE sources into EPIC EHR

Bidirectional lab and radiology results exchange from HIE sources into EPIC EHR

Bidirectional CCD exchange with HIE and EPIC EHR Bidirectional messaging integration with EPIC EHR and HIE messaging

for provider to provider messaging, and patient to provider messaging3. Development of Clinical Decision Support tools at HIE level:

Initiate development of disease based data warehouse in HIE, with the ability to segment ACO patients as a group for reporting and alerting

Alerts to ACO and PCP for ACO concerning beneficiary utilization – such as any ED visit or hospitalization via automating messaging

4. Structure reports from HIE community information to evaluate ACO beneficiary utilization estimates

Define ACO patient beneficiaries within HIE patient population For all ACO patients with diabetes number of ED encounters within past

year sorted by all payers, Medicare and non-medicare For all ACO patients with diabetes number of Ambulatory visits by

specialty type sorted by all payers, Medicare and non-medicare For all ACO patients with diabetes number of Hospital admissions sorted

by all payers, Medicare and non-medicare For all ACO patients with diabetes number of surgical procedures sorted

by all payers, Medicare, and non-medicare5. Structure reports from HIE community information to examine ACO diabetes care

quality Monthly list of ACO diabetes patients who have not had an HbA1C value

reported within the previous 6 months reported to ACO and PCP Monthly list of ACO diabetes patients who have not had an LDL value

reported within the previous 12 months reported to ACO and PCP Monthly list of ACO diabetes patients who have not had a Blood Pressure

reading within the previous 12 months reported to ACO and PCP Monthly list of ACO diabetes patients who have not had a primary care

visit within the previous 12 months reported to ACO and PCP



Monthly list of ACO diabetes patients who have a positive tobacco use history documented reported to ACO and PCP

Summary ACO beneficiary diabetes quality measure report quarterly

Long Term Changes (12 to 24 months):1. Revise model of diabetes care to utilize resources more effectively2. Align ACO reporting to CMS to come directly from HIE, in lieu of individual group

reporting on quality measures Disease registry for ACO beneficiaries created within HIE ACO participants send quality data to HIE via HL7 at the end of each

encounter ACO participants without EHRs can enter data directly into HIE via web

portal HIE reports quality data monthly to CMS

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APPENDIX:

Sample Report #1 Identify the BHMA ACO Patients

This should one of the more straight forward reports to create, assuming that the CMS ACO Database is delivered on time. Depending on the data structure created by the ACO, BHMA can query the ACO database or alternatively the CMS ACO Database. Ideally as mentioned earlier, the entirety of the ACO will, as a matter of business necessity, be participating in a single HIE, in this case the Chicago HIE with its Amalga database. The Amalga database duplicates in a single normalized HIE database the individual contributor’s information.



Data elements to create a match: Name, Date of Birth, Social Security Number, + sex. Advanced algorithms for matching are present in the HIE database. These use probabilistic prediction to compensate to misspellings and typographic errors.



Sample Report #2 Identify the BHMA ACO Patients with Diabetes

Comprehensively identifying which patients of the ACO cohort are diabetic will be a challenge because ACO patients are not obligated to obtain their care from ACO providers. Fortunately because many of the providers in the local region will be participants in the Chicago HIE missing data elements will be available to the ACO. CMS claims data may be used to supplement the data available within the BHMA and ACO data structures. However, the CMS claims data is always time delayed and this delay creates risk to the “real time” management of diabetic patients to meet quality and outcomes criteria.



Sample Report #3 Provider attribution patient care based on charges

Because of group practice, provider vacation/absence/illness, few patients are always seen by only one provider. Attribution of patients is a process of allocating to a provider responsibility for a patient’s care. Attribution of a patient to a provider can be done via one of several schemas, or a blend of the schema. The method demonstrated in this particular report sums a patient’s charges by provider and the provider responsible for the greatest charges is deemed primarily responsible for this patient.



Sample Report #4 Provider attribution based on episodes of care

Another option for patient attribution is to sum the number of visits each patient has with each provider and then attribute the patient to the provider who supplies numerically the greatest number of visits. This method avoids skewing of attribution to providers who are responsible for ordering expensive testing. For instance, a cardiologist may order an expensive cardiac imaging study and only need to see the patient twice. If attribution is done on the basis of dollars spent, the cardiologist is attributed as the patient’s provider. With this method attribution is done based on frequency of visits.



Sample Report #5 Comparative diabetes performance dashboard

This report can be created using either method of patient attribution (based on most visits to a provider, or provider spending the greatest). It should be published for performance comparison amongst providers and will be an integral chart on an ACO dashboard created to allow BHMA providers up to date feedback in their performance.



Sample Report #6 Comparative additional clinical performance dashboard

This report is similar to the previous worksheet and is repurposed for reporting on several other of the core measures for the ACO.



Proposed conceptual approach to reports requirement creation

By conceptualizing BHMA’s participation in the ACO as a problem in relational (set) algebra, BHMA providers can readily and accurately create the requirements for additional reports. In doing this, the provider must simply identify the criteria for selection and the locations where the data resides. The analyst can take these requirements and quickly convert to a database query.


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