approach to integrated care and population health management … · approach to integrated care and...

Insight and Action in Behavioral Health

Care Management Technologies

Data Analytics: A 21st Century Approach to Integrated Care and Population Health Management

OPEN MINDS Planning & Innovation InstituteJune 12, 2013

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Why Now?

Advances in use of technology in healthcare Cost of US healthcare relative to health of nation Advances in evidence-based medicine/practice Mental health parity/health integration Aging population

Drivers

Leading to:

Competition Payment Reform: value-based reimbursements and quality performance

Focus on Integration Complexity of patientCoordination Across Multiple Provider Systems

Ability to see what is going on inside and outside a provider system/health home

Evidence-based Guidance

Improving care while lowering costs

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• Benefit restriction• Prior authorization/edits• Medical services only • Limit provider rates• Pay based on utilization • Focus on utilization• 1-800 #• Outsourced• Healthy population

• Mental health parity • Genetic markers • Nonmedical benefit• Pay for performance• Incentive Based Pay• Focus on quality• Boots on the ground• Insourced• Complex needs population

20th Century vs. 21st CenturyHealth and Financial Management Techniques

20th Century 21th Century

# 4

What is Big Data?

• Examples Web searches “you may also like” Drug companies use influence mapping to identify doctors in

common with a single patient to promote adoption of a newly introduced drug.

http://www.nytimes.com/2013/05/17/business/a-data-trove-now-guides-drug-company-pitches Obama 2012 campaign shows Facebook users the photos of ten

friends they were “most likely to influence”http://www.forbes.com/sites/kashmirhill/2013/04/16/obama-campaign-misjudged-mac-users-based-on-orbitzs-experience-says-chief-data-scientist

Big data is the term used for the evolving technology and science of data management and analysis.

Big data is the term used for the evolving technology and science of data management and analysis.

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Electronic Records Are Not Big DataDigital Age = Electronic RecordsDigital Age = Electronic Records

Data Types Pt Record Practice Mgt Pop Health Mgt

Quantitative Lab Values Productivity Value

AuthorizationCounts

Qualitative Text Docs Customer Feedback

CustomerComplaints

Transactional Data Service Codes Billing Codes Payment Codes

Rich Data Repository

# 6

One Patient Metabolic Screening Data

CMT Healthcare OnlineName Value Method Opt-out Comments Date

Taken

✗ Height 65.00 inches Actual 02/14/2013

✗ Weight 214.00 Pounds Actual 02/14/2013

✗ BMI 35.6076 Actual 02/14/2013

✗ Waist No Data Inches Automated 02/14/2013

✗ BP Systolic 120.00 mmHg Automated 02/14/2013

✗ BP Diastolic 80.00 mmHg Automated 02/14/2013

✗ Blood Glucose 92.00 mg/dl Actual 02/14/2013

✗ HbA1c No Data % Automated 02/14/2013

✗ Total Cholesterol 218.00 mg/dl Actual 02/14/2013

✗ LDL 127.00 mg/dl Actual 02/14/2013

✗ HDL 58.00 mg/dl Actual 02/14/2013

✗ Triglycerides 163.00 mg/dl Actual 02/14/2013

✗ Antipsychotic Use Yes Yes 02/14/2013

✗ Pregnant No No 02/14/2013

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What happens when you have multiples of thousands?

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BIG DATA TECHNIQUESLeverage the Richness of Data Repository

314.940 records

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Drill Down of the Thousands

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Example 2

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Example 3

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Value Opportunity

• Expanding capacity for knowledge gains Shift best practice based on outcomes Capturing clinical nuggets from unstructured data

• Knowledge Dissemination Distillation of vast data into “news you can use”

• Personalized Medicine Tying genomics to health record data Tying personalized information to standard of practices

• Direct to Consumer Linking health data to other data – job, housing, diet,

entertainment

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Challenges

• Patient confidentiality

• Interoperability

• Balance of human vs. machine

• Using big data for specific gain

• Professional shift – independent decision to evidence-based guidance

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Tools in the Analytic Tool Kit

• Registries

• Dashboard Reports

• Health Information Exchanges

• Decision Support Tools

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Data Analytic Tools = Finding Key Determinants

http://www.moillusions.com/2009/08/camouflaged-toads-optical-illusion.html/ng9

# 16

Registries

• Often tracks a specific clinical issue

• Track the magnitude of the problem

• Benchmark clinical care across providers

• Often is outside of the electronic record

• Often used for real world research

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One Patient Metabolic Screening Data

CMT Healthcare OnlineName Value Method Opt-out Comments Date

Taken

✗ Height 65.00 inches Actual 02/14/2013

✗ Weight 214.00 Pounds Actual 02/14/2013

✗ BMI 35.6076 Actual 02/14/2013

✗ Waist No Data Inches Automated 02/14/2013

✗ BP Systolic 120.00 mmHg Automated 02/14/2013

✗ BP Diastolic 80.00 mmHg Automated 02/14/2013

✗ Blood Glucose 92.00 mg/dl Actual 02/14/2013

✗ HbA1c No Data % Automated 02/14/2013

✗ Total Cholesterol 218.00 mg/dl Actual 02/14/2013

✗ LDL 127.00 mg/dl Actual 02/14/2013

✗ HDL 58.00 mg/dl Actual 02/14/2013

✗ Triglycerides 163.00 mg/dl Actual 02/14/2013

✗ Antipsychotic Use Yes Yes 02/14/2013

✗ Pregnant No No 02/14/2013

# 18

What happens when you have 32,000 of these records?

# 19

Risk Stratification via Diabetes RegistryMembers of Behavioral Health Home

(31494 members)

+ Diabetes Diagnosis (3732 members)

Service Claims Data

+ Use of 1 or more Antipsychotic Meds(411 members)

Pharmacy Claims

+ BMI > 30(109 members)

EMR Data

+ Antipsychotic medications contraindicated with Diabetes (95 members (24 members)

31,494 members

314.940 records

Members with Diabetes Diagnosis (3732 members)

3742 records

Use of 1 or More Antipsychotic Meds (411 members)

3742 records

Members with BMI > 30 (109 members)

3742 records

Antipsychotic Med Contraindication (95 members)

3742 records

Member Drill Down

95 records

Decision Support within the Registry

95 records

Health Alert 1009Diabetes and Use of Clozapine and OlanzapineAccording to our data this patient has evidence of diabetes and of treatment with Clozapine or Olanzapine. According to the Mt. Sinai Consensus Conference; clozapine and olanzapine pose an increased risk of weight gain, diabetes and worsening lipid profiles.(Am J Psychiatry 2004 161:1334-1349)

# 27

Dashboard Reporting

• Typically tied to metrics (clinical or quality)

• Used to monitor and benchmark performance

• Can be used to improve patient specific outcomes

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Performance Tracking

Predictive ModelingMeasures

Flagged

DM17 Diabetes LDL Control (A)

% of patients 18-75 years of age with a diagnosis of diabetes (type1 or type 2) who had a LDL <100 mg/dl.

1426 29 98.01 1.99 70 -68.01

DM19 Diabetes BP Control (A)

% of patients 18-75 years of age with a diagnosis of diabetes (type1 or type 2) who had a blood pressure <140/90 mmHg.

1414 41 97.18 2.82 70 -67.182.82

CMT Healthcare Online

98.01 1.99

97.18

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MCO Dashboard Report for Call Center

Call Timeliness2012-07

2012-08

2012-09

2012-10

2012-11

2012-12

2013-01

2013-02

2013-03

2013-04

2013-05

2013-06 YTD

YTD as % Total

# Calls Answered 4,800 4,700 3,950 5,200 4,900 5,100 4,900 4,700 5,400 43,650

# Calls Abandoned 29 20 25 32 55 12 15 21 22 231

Total Number of Calls 4,829 4,720 3,975 5,232 4,955 5,112 4,915 4,721 5,422 - - - 43,881

% Abandoned (Goal <1%) 0.6% 0.4% 0.6% 0.6% 1.1% 0.2% 0.3% 0.4% 0.4% 0.5%

Avg Speed to Answer Calls (seconds)

5.8 5.8 5.7 6.0 5.6 5.8 5.9 5.8 5.4 52

% Answered within 30 seconds (Goal 100%)

99% 99% 99% 99% 99% 99% 100% 99% 100% 99%

Call Volume

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Health Information Exchanges

An Integrated IT Platform that collects data from multiple sources, mobilizes

and integrates the information and returns it to the end user.

An Integrated IT Platform that collects data from multiple sources, mobilizes

and integrates the information and returns it to the end user.

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Gaps Across Care Venues

Lab

ClinicImaging Center

Urgent Care

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Goal is to Close the Gaps

State Medicaid Office

Group Home

CMMS

Clinic

Lab

Imaging Center

Physician Office

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Decision Support

• Computer application that supports clinicians in improved decision making

• Usually rules based

• Usually tied to evidence

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Decision Support DisplayQuality Indicator™ Title Patients % Pts MDs PUPM

Use of 3 or More Psychotropics for 60 or More Days 1,537 2.62% 603 $229.52

Patient Failed to Refill Newly Prescribed Antidepressant within 30 Days of Prescription Ending 936 1.60% 438 $15.09

Use of a Non-mood Stabilizing Anticonvulsant in a Patient with Presumptive Bipolar Disorder without Evidence of a Failed Trial of a Mood Stabilizer

293 0.50% 185 $71.89

Use of an Atypical Antipsychotic at a Lower Than Recommended Dose for 45 or More Days 268 0.46% 115 $119.87

Patient Failed to Refill a Mood Stabilizer within 30 Days of Prescription Ending 236 0.40% 105 $27.81

Use of 2 or More Benzodiazepines for 60 or More Days 179 0.31% 106 $19.56

Patient Failed to Refill an Antipsychotic within 30 Days of Prescription Ending 135 0.23% 63 $126.11

Multiple Prescribers of the Same Class of Psychotropic Drug for 45 or More Days 113 0.19% 153 $127.47

Use of 2 or More Insomnia Agents for 60 or More Days 102 0.17% 77 $52.53

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Decision Support Educational Tool

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Best Practices for Analytic Tools

• Credibility of data

• Prioritization of effort – risk stratification methods

• Actionable

• Measureable

• Automated work flows

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CMT’s ProAct Analytics

A BIG DATA TOOL

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CMT is a BIG DATA TOOL

Decision Support

Aids clinical decisions Based in evidence tied to data

Registry Driven

Specific disease states

DashboardTrack performance across

providersAids patient care improvements

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CMT’s ProAct Supports

Population Health

Comprehensive Care Management

Compliance Measurement

• Evidence-based Guidelines• Quality Improvement Actions

• Care Coordination• Care Transitions• Health Promotion/Prevention• Adherence

• NOMS• SAMHSA• State Contractual Measures

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Newly Proposed NCQA Standards Quality Pathway: CMT Solution

Subheading NCQA Code CMT’s Solution

Quality Improvement Activities

QI6A Using claims data for screening, e.g., metabolic syndrome and antipsychotics; depression and chronic illness

QI8J CMT’s ProAct supports standard QI process flows

Care Coordination QI8A CMT’s ProAct provides views of integrated data to support case management outreach

CC1:ABC&D CMT uses data to track issues relevant to care fragmentation e.g., multiple prescribers

CC4A CMT’s ProAct is a technology tool

Complex Care Management

QI8A&C ProAct uses claims data to identify members in need

QI8B CMT uses claims data to update members and needs regularly

Appropriate Care QI8F CMT identifies underlying SA disorders or confounding dependencies

CC1B/CC2A&B CMT is specifically designed to track appropriate use of medicines

EBP Care QI6C CMT’s QIs can be used to track EBP

QI8E CMT’s QIs can be used to manage and communicate EBP

QI19A&B CMT’s Clinical Considerations™ and health alerts can be used to promote adoption of EBP guidelines

QI10: Element C CMT specifically tracks 3 of the 7 referenced measures

Population Health: Evidence-based Guidelines/Quality Improvement Actions Compliance Measurement: Accreditation Body

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CMT’s Solution to the New NQF Behavioral Health Measures

NQF Behavioral Health Measure Endorsed By Addressed by CMT

Initiation and Engagement of Alcohol and Other Drug Dependence Treatment NCQA

Medical Assistance with Smoking and Tobacco Use Cessation NCQA

Preventive Care & Screening: Tobacco Use: Screening & Cessation Intervention AMA-PCPI ✔Adherence to Antipsychotic Medications for Individuals with Schizophrenia CMS ✔Diabetes Screening for People with Schizophrenia or Bipolar Disorder Who Are Prescribed Antipsychotic Medications NCQA ✔Cardiovascular Health Screening for People with Schizophrenia or Bipolar Disorder Who Are Prescribed Antipsychotic Medications NCQA ✔Cardiovascular Health Monitoring for People with Cardiovascular Disease and Schizophrenia NCQA ✔Diabetes Monitoring for People with Diabetes and Schizophrenia NCQA ✔Follow-Up After Hospitalization for Schizophrenia (7- and 30-day) NCQA ✔Follow-Up After Hospitalization for Mental Illness NCQA ✔

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Clinical Pathway #1High Risk-Failure to Refill

• High rate of readmission for those with serious depression who fail to refill

• 50% nonadherent rate for prescribed antidepressants

Sample data How many in 90 days: 963 adults; 46 elderly

Establish clinical criteria for outreach

• 1st refill or later refill• Other medical co-morbidities• Recent hospitalization• No evidence of BH services

Determine outreach/intervention

• Patient outreach—nurse/care management call• Assignment to ongoing care coordination/case mgt• Medical plan collaborative treatment review• Provider outreach• Write up as a QI project for accreditation or health plan

reviewScreen • Failure to refill Quality Indicators™ monthly

Comprehensive Care Management: Adherence

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Clinical Pathway #2High Risk – Use of Multiple Benzodiazepines

• High rate of readmission for those triggering 2+ Benzodiazepines for 60 or more days

Sample data How many: 105 adults; 139 elderly


• Other medical co-morbidities• Evidence of falls, accidents or other similar impairment• Evidence of dementia for the elderly• Recent hospitalization• No evidence of BH services


• Patient outreach—nurse/care management call• Offer Stress Management/Wellness supports and

resources; peer support group• Assignment to ongoing care coordination/case mgt• Medical plan collaborative treatment review• Provider outreach

Screen • High Risk Benzodiazapine Quality Indicators™ monthly

Comprehensive Care Management: Care Coordination/Health Preventions

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Clinical Pathway #3High Risk: 5+ Psychotropics for Children

• Top six high volume clinical issue

• One patient with $10,000 in psychotropic spend in 90 day period

Sample data How many in 90 days: 43


• No evidence of psychiatric evaluation• Multiple prescriber pattern• Recent hospitalization• No evidence of BH services


• Recommend prior authorization post 3 medicines for certain period of time

• Establish proper BH family and child services if absent• Patient outreach—nurse/care management call• Assignment to ongoing care coordination/case mgt• Provider consultation• Write up as a QI project for accreditation or health plan

reviewScreen • Failure to refill Quality Indicators™ monthly

Population Health: Evidence-based Guidelines

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Clinical Pathway #4Antipsychotic Use in Children

Sample data • Approximately 720 users• 40 with Quality Indicators™• Four children under 4 with antipsychotic script


• Review clinical records• Establish criteria for assignment to interventions Family-based intervention in place Developmental evaluation complete Transitions/disruptions in home or day care Other medications in combination BH specialty services in place


• Recommend prior authorization • Outreach to parent with resource information• Peer consultation to prescriber• Engagement in more intensive behavioral health

services• Care coordination meeting with health plan

Screen • Repeat process quarterly to screen for newly identified children

Population Health: Evidence-based Guidelines

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Clinical Pathway #5Low Dose Antipsychotic Use in Adults

Sample data Approximately 268 adult triggers


• Evaluate diagnostic/treating condition • Establish criteria for assignment to interventions Off label use Dose Ineffective for treating diagnosis Other medications in combination BH specialty services in place


• Peer consultation to prescriber• Engagement in more intensive behavioral health

services• Patient outreach

Screen • Repeat process quarterly to screen for newly identified adults

• Represents undertreatment or possibly off label use for sleep aid

Comprehensive Care Management: Care Coordination

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Clinical Pathway #6Multiple Prescribers

Sample data How Many: 113 prescribers associated with Prescribing of Same Class of Medicine


• Sort by high volume prescribers


• Conduct “alert messaging” to the high volume providers• Recommend a prior authorization process for 2nd or 3rd

prescriber of same class medication• Write up as a QI project for accreditation or health plan

reviewScreen • Quarterly

Population Health: Quality Improvement ActionsComprehensive Care Management: Care Coordination

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Clinical Pathway #7Improved Prescribing

Sample data • Approximately 1/3 of prescribers trigger at least one QI


• Focus on the top prescribers account for majority of triggering rate.


• Educational and targeted messaging• Peer consultation • Increased authorization protocol for those in your

network based on response to above • Write up as a QI initiative for your health plan or

accreditation review Screen • Process quarterly

Population Health: Evidence-based Guidelines/Quality Improvement Actions

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Reference List• Atkins, R. Using Information Systems to Develop Clinical Performance

Scorecards: Reporting Behavioral Health & Social Service Clinical Team Performance, Open Minds Archive.

• Farias, M., et al. (2013) A Better Alternative To Clinical Practice Guidelines, Health Affairs vol 32 (5) 911-918.

• Kayyali, B., Knott, D., Van Kuiken, S. The big-data revolution in US health care: Accelerating value and innovation. (April 2013) McKinsey & Company Insights & Publications. Retrieved from http://www.mckinsey.com/insights/health_systems/The_big-data_revolution_in_US_health_care

• Murdoch, T., Desky, A. (2013) The Inevitable Application of Big Data to HealthCare. JAMA, vol 309 (13)

• Punke, H. Best Practices for data analytics in value based reimbursement. (February 21, 2013) found on www.beckershospitalreview.

• Quality Management as a Strategy for Utilization Management: Using Statistical Process Control to Manage the Care of High Risk Patients, Open Minds Archive.

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Carol’s Contact Info

One Copley Parkway, Suite 534Morrisville, NC 27560

Tel: 919-674-2547Fax: 919-674-2538Cell: 919-491-0819

[email protected]


Tel: 919-674-2547Fax: 919-674-2538Cell: 919-491-0819

[email protected] Duncan Clayton, PhDChief Executive OfficerCarol Duncan Clayton, PhDChief Executive Officer


Tel: 919-674-2547Fax: 919-674-2538Cell: 919-491-0819

[email protected] Duncan Clayton, PhDChief Executive Officer

Insight and Action in Behavioral Health

Care Management Technologies

Case Study: How Missouri is utilizing data analytics to support the state health home initiative

OPEN MINDS Planning & Innovation InstituteJune 12, 2013

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MO Coalition of CMHCs

• Represent 33 member organizations Community Mental Health Centers Alcohol and drug abuse treatment agencies Affiliated Community Psychiatric Rehab (CPR) service providers

Clinical call center

• Over 9,000 staff providing treatment and support services to approx. 250,000 people each year

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Coalition Provider Locations

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CMHC Healthcare Homes

• Coalition is a partner in the design and development of the CMHC Healthcare Home (HCH)

• Coalition represents all 28 CMHC HCHs• Coalition provides training and technical assistance to the CMHC HCHs

• Coalition aims to improve quality and clinical outcomes

• Coalition is “hands‐on” and transparent with BIG data

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Missouri’s History with BIG Data

2005MO + CMT

2008+ Nurse Liaisons

2010+ DM3700 Outreach

2012+ HealthcareHome

Email notifications

Mailings

Disease registryProAct

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Growing Pains

• Implementation How to add MORE data What to do with the data

• Becoming “tech savy” Training, Training, Training Support, Support, Support

• More cooks in the kitchen• Transparency• Adapting to...

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Growing Pains

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Growing Pains

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Value Opportunity

• Expanding capacity for knowledge gains Know what we didn’t know before

• Knowledge Dissemination Broadcast alerts to the treatment team Celebrate successes

Achieve complianceand

Improve health outcomes

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Managing Big Data

• Avoiding information and data “overload”

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ProAct

• Behavioral Pharmacy Management (QI)• Disease Management (compliance measures)• Medication Adherence (adherence)• Integrated Health Profile (IHP)

Clinical Updates Metabolic Syndrome Screening Database

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Behavioral Pharmacy Management (BPM)

• Identifies clinicians whose prescribing patterns deviate from current clinical best practices

• Identifies consumers who fail to refill their BH medications and/or are seeing multiple prescribers for the same class of medications

• Uses CMT’s Quality Indicators™(QIs) to analyze MO’s pharmacy claims data

• Provides spend amounts and numbers of patients and prescribers that trigger each QI

• PDF of Clinical Considerations available

# 64

BPM Healthcare Home Measures

Performance Measure Goal

Quality Prescribing Psychiatric Medications (A) ‐% of prescriptions flagged as potentially inconsistent with quality practices.(i.e. use of 3 or more antipsychotics for 45 or more days, use of 2 or more Benzodiazephinesfor 60 or more days).

<10%

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BPM MailingPrescriber Summary &Benchmark Report

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BPM MailingPrescriber Summary &Benchmark Report

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BPMClinicalConsideration

# 68

BPM CMHC Benchmark Report (Adult)

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BPM CMHC Benchmark Report (Child)

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BPM Data Checkpoint

Population/Risk StratificationClients flagging high risk QIs or multiple QIsClients flagging failure to refillClients flagging multiple prescribers

Care Coordination Interventions with a specific outlier prescriber (internal and external docs) with high volume of clients

Interventions with a specific outlier prescriber with high cost of care

Notify case manager of multiple prescribers and failure to refill concerns

DATADATA

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HCH Management Report BPM Summary

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Disease Management (DM)

• Also known as Compliance Measures.• Identifies consumers with selected health conditions for whom appropriate screening and treatment activities appear to be lacking.

• Based on pharmacy/medical claims and Metabolic Screening data/disease registry.

• Assists care coordination by quickly identifying patients for whom intervention is necessary.

• Provides list of patients that flag each measure and the number of measures flagged by each patient.

• Ability to print letters allowing for provider feedback.

# 73

DM Healthcare Home Measures


Asthma Med (A&C) ‐ % of clients 5‐64 identified as having persistent asthma and were appropriately prescribed medication during the measurement period.

70%

BP Control HTN (A) ‐ % of clients 18 and older with a dx of hypertension with reported BP <140/90 mmHg during the most recent office visit in previous 12 months.

60%

LDL Control Cardio (A) ‐ % of clients 18‐75 with a dx of CAD with reported LDL <100 mg/dL in previous 12 months.

70%

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Diabetes BP Control (A) ‐ % of clients 18‐75 with a dx of diabetes (type 1 or 2) with reported BP <140/90 mmHg in previous 12 months.

65%

Diabetes A1c Control (A) ‐ % of clients 18‐75 with a dx of diabetes (type 1 or 2) with reported HbA1c <8.0% in previous 12 months.

60%

Diabetes LDL Control (A) ‐ % of clients 18‐75 with a dx of diabetes (type 1 or 3) with reported LDL <100 mg/dL in previous 12 months.

36%

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No Tobacco Use (A&C) ‐ % of clients reporting no tobacco use in previous 12 months. 56%

Metabolic Screen (A&C) ‐ % of clients with completed MBS screening in previous 12 months.Includes: BMI, BP, blood glucose/HbA1c, lipid panel, and use of anti‐psychotic medication and tobacco.

80%

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DMCare Coordination &Quality Care ConsiderationProvider Letter

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DM Data Checkpoint

Population/Risk StratificationClients flagging multiple measures or measure of the same chronic condition

Clients flagging focus measuresClients flagging metabolic screening measure

Care CoordinationTEAMcare meetings for high risk clientsPrint DM Provider Letter and fax to client’s PCP and/or send copy to case manager

Refer client to chronic disease education/support groups, tobacco cessation groups, and wellness programs

DATADATA

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Healthcare Home Management Report DM (Adults)

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Medication Adherence

• Displays MPR for seven classes of maintenance medications.

• MPR is based on a 3 month or 90 day period.

• Uses Medicaid paid prescription claims data only. Not included: cash payments, samples received, and Medicare paid drugs

Anti‐hypertensivesCardiovascularDiabetesCOPD

AntipsychoticsAntidepressantsMood Stabilizers

# 80

Adherence Healthcare Home Measures


All members with diagnosis, medication adherence to antipsychotics, antidepressants and mood stabilizers.

90%

All members with diagnosis, medication adherence to anti‐hypertensive and cardiovascular medications.

90%

All members with diagnosis, medication adherence to asthma and/or COPD medications. 90%

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Adherence Data Checkpoint

Population/Risk StratificationClients with MPRs < or = 0.8

Of multiple drug typesOf a targeted drug type

Clients with MPRs < or = 0.8 and flags related diabetes, hypertension or CAD treatment alerts in DM

Care CoordinationNotify case managers and PCP of adherence concerns

DATADATA

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HCH Management Report Adherence Summary

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IHP-Member List

• Looks like a mini EMR.• The IHP contains detailed information on your selected client gleaned from Medicaid claims data.

• IHP includes diagnosis, flagged measures, medication list, MPR graph, ER/inpatient data, etc.

• Contains “clinical update” feature allowing end users to note “incorrect diagnosis”, “treatment complete”, or “alternate treatment approved.”

• Contains “Metabolic Screening Data”/disease registry.

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IHP-Member List Data Checkpoint

Population/Risk StratificationClients flagging multiple indicators/measures across all reports

High hospital and ER utilizersClients with high comorbid medical diagnosis counts

Care CoordinationTEAMcare meetings for high risk clientsNotify case managers and PCP of health concerns

DATADATA

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Integrated Health Profile (IHP)

• Looks like a mini EMR.• The IHP contains detailed information on your selected client gleaned from Medicaid claims data.

• IHP includes diagnosis, flagged measures, medication list, MPR graph, ER/inpatient data, etc.

• Contains “clinical update” feature allowing end users to note “incorrect diagnosis”, “treatment complete”, or “alternate treatment approved.”

• Contains “Metabolic Screening Data”/disease registry.

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IHP

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Metabolic Screening Database

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ProAct Healthcare Home Measures


Use of ProAct per member per month for non‐MCO enrollees. One record access

utilization PMPM

# 89

ProActProAct View Report

# 90

ProActProAct Intensity Report

# 91

Contact Info

Rachelle GlavinDirector of Clinical OperationsMissouri Coalition of Community Mental Health Centers

[email protected] – office

approach to integrated care and population health management … · approach to integrated care and...

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