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TRANSCRIPT
CONTENTS
S.No Contents Page No.
1 Introduction 4
2 IT tools and there benefits 5
3 Company Profile 6
4 Technology and operation solutions 7
5 IT TOOL-Medinsight 7
6 Medinsight-Architecture 10
7 Key Features 13
8 Medinsight-Technical overview 15
9 Case study 21
10 Medinsight version 7.0 23
11 Solutions 24
12 Conclusion 28
13 Reference 28
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DATABASE MANAGEMENT SOLUTION-A case study of Milliman
Medinsight”.
INTRODUCTION
Initially in insurance company and other organizations, internal reporting was made
manually and only periodically, as a by-product of the accounting system and with some
additional statistic(s), and gave limited and delayed information on management
performance. Previously, data had to be separated individually by the people as per the
requirement and necessity of the organization. Later, data was distinguished from
information, and so instead of the collection of mass of data, important and to the point
data that is needed by the organization was stored.
Earlier, business computers were mostly used for relatively simple operations such as
tracking sales or payroll data, often without much detail. Over time, these applications
became more complex and began to store increasing amount of information while also
interlinking with previously separate information systems. As more and more data was
stored and linked man began to analyze this information into further detail, creating entire
management reports from the raw, stored data. The term "MIS" arose to describe these
kinds of applications, which were developed to provide managers with information about
sales, claims, premium, inventories, and other data that would help in managing the
enterprise. Today, the term is used broadly in a number of contexts and includes (but is
not limited to): decision support systems, resource and people management
applications, enterprise resource planning (ERP), enterprise performance
management (EPM), supplychainmanagement(SCM), customerrelationshipmanagement
(CRM), project management and database retrieval applications.
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IT TOOLS AND THERE BENEFITS FOR HEALTH INSURANCE CO’S
Payers, employers, and third-party administrators (TPAs) operating in the current
business environment are facing some of the most difficult market conditions in decades.
From the recession and high unemployment to the uncertainty associated with the future
of this country’s healthcare policy, companies are under unprecedented pressure to
manage operating costs and improve margins. There are cases, however, of sophisticated
executives using the power of their own data to succeed in these difficult times. For more
than 10 years, the health insurance industry—from commercial payers, Blue Cross Blue
Shield organizations, and government-focused insurers to self-funded employers and
TPAs—has invested consistently in decision-support systems. These systems are made
up of business intelligence technology that organizes a variety of healthcare data into an
integrated warehouse and, through the application of various analytic tools, processes that
data into useful information. Reports are then generated to make that information usable
and easy to understand. Examples include simple cost and utilization reports that
illustrate in detail what specific components are driving the medical loss ratio for a
company, provider profiles that describe how your network providers are performing
relative to their peers and predictive modeling that projects which members of a health
plan are in need of proactive outreach and care. A variety of software vendors have
launched numerous analytic products during the past decade and investment in this type
of technology has been heavy. As the decision-support market within health insurance
has matured somewhat, there are fewer stories of success than one might have expected.
The economic value derived from these investments is not only difficult to measure, but
also in many cases it does not exist. Nearly half of all healthcare data warehousing
projects fail to meet their original objectives. There are many reasons for the lack of
return on investment (ROI). The biggest reason has less to do with the strength or
weakness of a specific product and more to do with the type of specific action a company
takes, or does not take, based on an undesirable metric or statistic that the product
produces. Organizations are busy with many priorities—just running the day to day
business is often a challenge in itself. Solving the underlying, difficult problems is often
swept under the rug for fear of how expensive or time-intensive such work may become.
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Forward-thinking executives who have moved swiftly to deal with these problems
through not only sophisticated technology, but also with consulting guidance, are the
ones whose companies are winning the competitive battles in the marketplace. Making
the investment in decision-support systems on its own is insufficient. Supplementing that
with consulting advice from a partner who can make a difference is the most effective
way to drive meaningful value from your decision-support investment
COMPANY PROFILE
Milliman is among the world's largest independent actuarial and consulting firms, with
revenues of $676 million in 2010. Founded in Seattle in 1947, they currently have 53
offices in key locations worldwide .Staff of 2,500 people includes more than 1,300
qualified consultants and actuaries. They are owned and managed by approximately 350
principals—senior consultants whose selection is based on their technical, professional
and business achievements.
Through consulting practices in employee benefits, healthcare, investment, life insurance
and financial services, and property and casualty insurance, Milliman serves the full
spectrum of business, financial, government, union, education, and nonprofit
organizations. In addition to there consulting actuaries, Milliman's body of professionals
includes numerous other specialists, ranging from clinicians to economists.
Wide variety of products and services in all major insurance areas. Major IT based
products include MG Alfa (life), MUGs / Care Guidelines / MedInsight (health) and
ReservePro / Affinity (P&C)
Milliman team in Gurgaon comprises of 48 people, including actuarial, clinical and IT
professionals. The team has significant health data warehousing and data analysis
expertise, since 2006:
Extensive experience on health data analysis for Indian insurers over the past 4
years
Extensive experience in analysis of health insurance data from UK, USA and
China
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Continues to manage data loading, warehousing and MIS function remotely for
US clients, some for more than 3 years
A number of strategic consulting assignments including business & operations
planning and rural & social market strategies
Highly structured process, integration of clinicians in process is key strength, with
focus on providing business intelligence for strategic decisions
Technology and Operations Solutions
As an integral part of the Milliman organization, Milliman Technology and Operations
Solutions focuses on helping healthcare organizations meet the operational and
technological challenges that are the norm in this dynamic industry. A consulting firm is
defined, in large part, by the quality, experience, and skills of its professionals. There
entrepreneurial culture attracts independent men and women who seek out challenges and
are willing to take risks. Each of there consultants has significant experience in the
healthcare industry, in addition to sophisticated technological expertise in the design and
development of solutions to complex problems.
There consultants work closely with the actuaries, clinicians, academics, and other
healthcare experts from the Milliman team. The result of this collaborative consulting
approach is that there clients benefit from the most complete combination of healthcare
management expertise in the industry. In the healthcare industry, every client is unique.
There are no one-size-fits-all remedies to the challenges that face their client’s needs
IT TOOL-MEDINSIGHT
MedInsight is an established, integrated Management Information System (MIS),
Decision Support System (DSS) and data warehouse platform specifically developed for
health insurance. It is in its 12th year and version 7.MedInsight offers sophisticated data
cleaning, reconciliation, analysis, benchmarking and report generation function.
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Since 1997, MedInsight has been implemented across more than 35 clients. According to
a recent Gartner Group review, MedInsight was identified as the most popular business
intelligence tool in the healthcare insurer market.
Milliman maintains a cluster of about 70 servers in its data center; MedInsight currently
handles about 80 million lives and processes about 2 billion transactions. MedInsight is
extremely versatile and easily scalable as it currently manages client’s ranges from a
hundred gigabytes to a few terabytes. Significantly adapted to Indian health insurance
data. MedInsight is an established, successful data warehousing approach developed by
Milliman Inc.’s (Milliman) Technology and Operations Solutions (TOPS) specifically for
the healthcare marketplace. MedInsight can be deployed as a stand-alone data warehouse
or it can be integrated and layered with existing data warehousing systems and initiatives.
Implemented as a stand-alone system, MedInsight offers the advantage of rapid
deployment, open systems architecture, and proven healthcare oriented data structures.
MedInsight works with existing claims, enrollment, and medical management systems, so
it is not necessary to abandon current operational systems in order to add data
warehousing capability.
Integrated with existing data warehousing systems and initiatives, MedInsight helps
healthcare organizations harness and leverage the power of the industry’s most
comprehensive performance measurement and analysis product
Management information system (MIS) is a system that provides information needed to
manage organizations efficiently and effectively. Management information systems
involve three primary resources: technology, information, and people. It's important to
recognize that while all three resources are key components when studying management
information systems, the most important resource is people . Management information
systems are regarded as a subset of the overall internal controls procedures in a business,
which cover the application of people, documents, technologies, and procedures used
by management accountants to solve business problems such as costing a product, service
or a business-wide strategy.
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Decision-support systems (DSS) are computer program applications used by middle
management to compile information from a wide range of sources to solve problems and
make decisions
Database management system (DBMS) Software to create a computerized database; add,
delete and manipulate data and create forms and reports
Example of Database Management System
1. MS Access2. Oracle3. Sybase4. Adabas5. Paradox6. Visual Fox Pro
Data warehouse (DW) is a database used for reporting and analysis. The data stored in
the warehouse is uploaded from the operational systems. The data may pass through an
operational data store for additional operations before it is used in the DW for reporting.
A data warehouse maintains its functions in three layers: staging, integration, and
access. Staging is used to store raw data for use by developers. The integration layer is
used to integrate data and to have a level of abstraction from users. The access layer is for
getting data out for users.
This definition of the data warehouse focuses on data storage. The main source of the
data is cleaned, transformed, catalogued and made available for use by managers and
other business professionals for data mining, online analytical processing, market
research and decision support. However, the means to retrieve and analyze data,
to extract, transform and load data, and to manage the data dictionary are also considered
essential components of a data warehousing system. Many references to data
warehousing use this broader context. Thus, an expanded definition for data warehousing
includes business intelligence tools, tools to extract, transform and load data into the
repository, and tools to manage and retrieve metadata
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MedInsight-Architecture
MedInsight was developed on the foundation of Milliman’s 50 plus years of healthcare data analysis and experience. Its architecture specifically addresses an organization’s need to retain data accuracy and integrity over time
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Acquire, Transform, LoadData can be loaded into MedInsight from any number of client data sources by one of two
primary methods:
o Database specific loading tools, such as SQL Server DTS or
o Ardent, a third-party ETL tool that is provided and supported by Milliman.
Both types of tools have the ability to move data from virtually any source or source
format into MedInsight. Raw source data is moved into the Staging (or source) Area of
the MedInsight data model. It is moved completely in an unchanged form so that
downstream results can always be audited and reconciled against the raw data. Data
loading procedures move data from the Staging Area to MedInsight’s Base Area. The
purpose of this area is to hold all cleaned, standardized and scrubbed data for analysis and
reporting. The base table data model seldom changes and is therefore a consistent
repository of good, accurate information. All standard MedInsight analyses obtain data
from the Base Tables. MedInsight contains a user customizable region called the User
Area. This region is the repository for any custom data tables, stored procedures or
analyses. The User Area may access data structures from the Base Tables or Staging Area
but may not modify the data structures in those areas (modified structures and views can,
however, be stored in the User Area).
AggregateMedInsight contains a collection of data analysis procedures and routines that summarize
base table data utilizing MedInsight Performance Measures and Benchmarks. These
summarizations update information in MedInsight’s Analysis Data Marts.
DistributeMedInsight contains a collection of data analysis procedures and routines that summarize
base table data against MedInsight Performance Measures and Benchmarks. These
summarizations update information in MedInsight’s Analysis Data Marts. These data
marts provide OLAP-optimized, reconcilable, multi-dimensional views of the medical,
financial, operational, marketing, and administrative information in a client’s data
repository.
The data analysis data marts can be categorized as follows:
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o Claim Payment Audit
o Disease Identification
o HCG Utilization
o Medical Cost
o Operational Performance
o Profit and Loss
o Provider Profiling
o Risk and Severity Adjustment
Executive Information SystemThe MedInsight Executive Information System includes a comprehensive suite of
standard performance measurement and analysis reports. These reports were developed
with and display utilizing Crystal Decisions’ Crystal Reports functionality and are
accessible through an Internet browser. Because this system is optimized from summary
tables and analyses, parameterized reports can be regenerated nearly instantaneously. The
Executive Information System contains approximately 50 standard reports that can be run
through user-input parameters to generate well over 5,000 different views of the data.
Decision Support SystemMedInsight is integrated with an analysis and decision support system that provides
multidimensional data visualization, analysis, and reporting capabilities to our clients.
The system has a simple easy-to-use client interface for non-technical users. Decision
makers across all functional areas of a corporation can access MedInsight data quickly
and intuitively.
Platform Independence, Scalable Architecture, HIPAA CompliantMedInsight is an open system designed for portability and scalability. The system has
been implemented on Microsoft SQL-Server, Oracle, and DB2. MedInsight functions
within a client’s Microsoft Windows 2000 and NT computing environments MedInsight
is engineered to conform to HIPAA standards and can be used to ease an organization’s
HIPAA compliance efforts.
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MetaData Tool
The MetaData tool is designed to assist in the management of the metadata during a MedInsight implementation. It provides a single source to view stored procedures, views, tables, fields, notes, and other details about the current implementation database environment.
Data Auditing, Data Reconciliation, and Data Editing Tools
Data auditing, process logging, and data reconciliation are supported both within the
MedInsight environment and through the use of electronic workbooks.
Flexible Scheduling
Data loading and data analysis procedures can be scheduled and run over any user-
defined period. Since MedInsight analysis procedures are modular Transact-SQL
routines, they will integrate with virtually any job/batch-scheduling engine
Key Features
Performance Measurement
The Performance Measurement component of MedInsight provides a comprehensive
performance measurement tool for health plans, insurers and TPAs. It contains more than
145 financial, medical management, and operational measures covering every department
and aspect of the organization. Nearly 70% of the performance measures contain
associated Milliman benchmarks that describe the Worst, Median and Best performance
in the industry for that measure.
Medical Cost Analysis
The Medical Cost Analysis component of MedInsight creates summaries of medical
utilization and reserve information from the underlying detailed repository data. These
summaries provide intelligent views of utilization measures by Product, Line of Business,
Group and PCP for:
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o Admits/1,000
o Days/1,000
o LOS
o Utilization/1,000
o PMPM
o Average Cost Per Service
Risk and Severity Adjustment
The MedInsight Risk and Severity Adjustment (RSA) engine utilizes age/sex and
condition/episode profiling techniques to determine retrospective and prospective
medical risk factors. The risk factors are used as primary input into rating, underwriting
and provider profiling processes.The RSA engine is unique in the industry in that it
develops risk factors, for 13 different utilization and cost measures, for each member for
each month of eligibility. The risk factors, themselves, are presented as a multiplier of the
total population for each of the utilization categories (defined as a risk factor of 1.0).
Because the RSA engine develops factors for each patient for 13 utilization categories,
the user is able to risk adjust not only total costs, but more specifically measures like drug
utilization and cost, inpatient days and costs, etc. This is invaluable in that each risk
category inherently produces distinct utilization profiles.
Milliman Health Cost Guidelines (HCG) Grouping and Utilization
The HCG Grouper categorizes health care claims data into Milliman’s Health Cost
Guidelines categories (which are groupings of similar types of services). The ability to
categorize health care claims data into the groupings is useful for many purposes
including:
o Benchmarking
o Utilization tracking
o Inpatient days / 1,000
o Office visits / 1,000
o Prescription drug scripts / 1,000
o Average charge tracking
o Analyzing the claim cost dollar
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Disease Identification
MedInsight’s Disease Identification module facilitates the development and maintenance
of algorithms for identifying specific diseases and conditions. In addition, the module
automates the process of interrogating MedInsight’s claims data against the algorithms
and returning a resultant data mart of applicable information.
In addition the Disease Identification module:
o Provides a flexible way to define and maintain complex disease (and disease state)
criteria.
o Identifies patients who meet criteria.
o Can be used in a variety of analyses or studies to create data marts of individuals
meeting selected criteria
.
MedInsight -Technical Overview
MedInsight® is modeled on the data warehouse design principle known as Star Schema.
MedInsight consists of five parts databases, reports, OLAP (online analytical processing),
backups (optional), and client computers.The dimension and fact tables make up the
OLAP cubes. The cubes are a part of objects logically defined as Data Marts. Data Marts
contain specialized data derived from the Data warehouse and are meant to be tactical to
meet specific requirements. MedInsight has data marts for Enrollment, Claims, Medical
costs etc .MedInsight contains approximately 80 standard reports that can be run through
user-input parameters to generate well over 5,000 different views of the data
Components of portalDashboard Report Library Analytic tools Reference libraryEnrollment MedInsight Reports Cubes DocumentationClaims Custom Reports Extract Builder User ManualClinicalFinancial
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FIG: Infrastructure setup for a single installation
Solution Architecture
MedInsight will include:
1. An ETL tool/interface
2. OLAP engine
3. Analysis tools (cubes and reports)
4. Other applications/utilities/tools to gather and deliver data
Methodology facilitates modeling and integrating a large volume of operational data and
sources. The data will be represented in multidimensional format to enable highly precise
visualization of data by summarizing, aggregating, drilling down, slicing and dicing.
MedInsight will provide the Users with intuitive and secure browser-based interface to
conveniently search , combine and analyze this data repository that enables data
visualization at varying granularity and allows for data import in various formats.
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Solution Architecture
Centralized 2-tier solution
For a comprehensive, enterprise-wide solution based on centralization of data as also
with a projected significant growth in enrollments and claims, they propose implementing
a centralized 2-tier data warehouse solution for Client
Solution Architecture
2 - Tier
Components:
Source Data: Client database consisting of consolidated Enrollment and Claims data
from various sources.
Firewall: Monitor, control and restrict all inward connections to the server. Will have a
Router to connect to the warehouse servers
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Source Database: In a single Tier architecture this server contains the data as well as the
application for querying and analyzing. It contains the data warehouse and data marts
depending upon overall data size and functionality.
In case of two-tier, this would contain the source (operational or legacy) data (historical,
pre-processed) and the ETL tool. This is the back-end server. This will also be the FTP
server for source data transfer. In this case the data is simply stored in 2-dimensional
format within the RDBMS.
Data warehouse/Cubes/Reporting server: In case of two-tier architecture, this server
would contain Data marts and cubes which are objects in data warehousing that hold
processed, specialized, aggregated, summarized and multi dimensional data for querying.
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Scalability to N-Tier
Additional application/middleware layer(s), containing business rules, is segregated .
This is a scalability related approach and can be implemented based on issues such as
surge in data, data load balancing, increased analytics, performance issues etc. A scenario
for this could be an unusually increasing demand on the underlying data warehouse
system.
Implementation steps
Project Scoping and Planning Infrastructure Setup Base MedInsight Installation Data Procurement Data Mapping Run Benchmarks Run Analytics and Setup Reports Run Cubes Portal Set -up and Deployment User Acceptance Testing Training Move to Production
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CASE STUDY
{1}A member attrition mysteryAn 85,000-member health plan was experiencing rapid membership attrition. Anecdotal
evidence from sales suggested uncompetitive premium rates. However, providers claimed
the plan offered low reimbursement compared to competitors.
MedInsight analysis
To analyze several potential root causes for the client's membership decline,
MedInsight was used to:
Benchmark utilization against competitors.
Audit the claims payment process.
Examine capitation and reimbursement levels.
Results
MedInsight showed that physician costs were 34.8% higher than median commercial
levels and pinpointed specific contributors to cost increases:
Utilization: 8.0%
Overpaid claims: 4.5%
Above-market capitation: 10.5%
Above-market fee schedule: 11.8%
The client implemented several corrective actions to eliminate cost variances: It
improved claims processing procedures, worked to reduce claim over-payments, adjusted
capitation rates, implemented a new fee schedule, created a maximum allowable fee
schedule for out-of-network claims, and began to actively drive care into the network.
{2}Medical management savings
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A 600,000-member health plan was concerned about the effectiveness of its medical
management initiatives, and was looking for ways to further reduce costs.
MedInsight analysis
The client used MedInsight® to benchmark performance, conduct trend analysis, identify
high-cost and high-risk populations, and analyze disease categories. These analyses
revealed startling findings:
Surgical admissions exceeded the benchmark by 20%.
Emergency room costs per member per month were twice the benchmark—over-
utilization was the main driver.
Physician office services were twice the benchmark—cost per visit was the main
driver.
Radiology was four times the benchmark—one delivery system was responsible.
Congestive heart failure patients accounted for more than $11 million per year,
and cost per case was increasing nearly 20% annually.
Results
The client identified more than $38 per member per month in potential savings. It
refocused existing medical management activities and implemented new initiatives to
target problem areas identified by MedInsight. The system also gave the client credible
information to use in modifying emergency room benefits and renegotiating provider
contracts.
{3}Inpatient costs: A sudden increase
A 250,000-member health plan started experiencing upward reserve adjustment on a
monthly basis. It could not get a handle on its liabilities even though there did not appear
to be any substantial changes in their claims processing area or reimbursement rates.
MedInsight analysis
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MedInsight's completion-based trend analysis showed a sudden and dramatic increase in
inpatient costs due largely to an increasing average cost per day on inpatient care.
Using MedInsight, the client discovered that a recently implemented contract clause that
reverts to percent of billed reimbursement when billed charges exceeded $30,000, has
resulted in a substantially higher number of claims being billed in excess of $30,000.
This new clause was on its way to costing the company $20 million per year. MedInsight
further identified $8 million in overpaid claims. ($2.67 per member per month in savings
for 250,000 members).
Results
The client immediately began the process of renegotiating hospital contracts and
recovering the overpaid claims. Cost trends were eventually brought back down to more
competitive levels, saving the client in excess of $15 million per year and stabilizing its
reserves.
MedInsight version 7.0With the launch of MedInsight 7.0, Milliman now offers an even stronger solution to the
healthcare industry. This significant upgrade provides many additional benefits,
including:
Tighter integration of Milliman Health Cost Guidelines ™ (HCGs) with improved
drill-down paths
Improved provider attribution capabilities to support medical home initiatives
New Medicare regulatory reporting capabilities
New clinical trend analysis and population management capabilities (CCHGs)
that pinpoint clinical drivers of trend
Enhanced benchmarking with adjustment factors and full alignment with HCGs
Integration of Milliman's new risk-adjustment models (MARA), providing the
industry's most powerful predictive models
Greatly expanded employer group reports to support your clients' reporting needs
The release of Version 7.0 builds upon MedInsight's existing capabilities and provides
your organization with a way to achieve even more value from the industry's most
comprehensive performance measurement and analysis solution
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SOLUTIONS
All-payer Claims Database Program
For years, health plans have explored ways to reduce costs and improve quality of care
delivered to patients. Many states are evaluating ways to accomplish these same goals.
With healthcare reform in full swing, state governments are willing to invest in strategies
that support quality improvement and cost containment.
An example of an increasingly popular strategy is the All-payer Claims Database
(APCD), which aims to promote transparency by making healthcare information
available to consumers and patients. Because the idea has been embraced by many—
including employers, healthcare providers, health plans, consumers, and state agencies—
APCDs will likely continue to sprout up for years to come.
Data collection
Level 1 validation
Level 2 validation
.
Standardized prices
Clinical data integration
Analytics/metrics
Data access/portals
Public use datasets and applications: Standard and customized datasets
Public policy: Support/data analysis
Project/account management
Ongoing support
.
Community Health Exchange Program
Community-based quality collaboratives, now active in many areas of the United States,
are demonstrating that it is possible to use health data from multiple sources to improve
healthcare quality and transparency.These organizations provide reporting based on
quality measurements (usually tied to providers or facilities) in order to establish a
baseline for improvement and for measuring the impact of other initiatives. They are an
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important component of the nation's evolving healthcare delivery system. However,
building, developing, and managing a viable community health exchange presents
significant challenges related to infrastructure and technological standardization.
Chronic Conditions Hierarchical Groups (CCHGs)
Chronic Conditions Hierarchical Groups (CCHGs) is a unique clinical-care-based
identification methodology for patients and chronic conditions designed to more
accurately identify cost trend drivers and effectively allocate disease and care
management resources. Coupled with traditional actuarial analyses, this new and highly
effective patient-centric model produces an information-driven management process that
results in more effective care and lower administrative costs.
CCHGs was developed at Milliman in collaboration with David Mirkin, MD. Before
CCHGs, analytical tools were unable to capture 100% of a patient's hospital experience.
Standard models like the NCQA HEDIS measures often failed to identify and separate
the incremental cost and trends for individuals with multiple conditions.
Benefits
The CCHG software application assigns all patients, including healthy individuals, to one
of 36 unique and mutually exclusive categories, using a clinically relevant hierarchy
based on the way physicians make treatment decisions. By focusing care management
interventions on factors that are most affected by clinical decisions, the user can make
smart and informed disease management decisions.
HCG Grouper
The Milliman MedInsight HCG Grouper software application categorizes medical and
pharmacy claims data into healthcare categories that can be used to analyze and
benchmark medical utilization and cost. It is integrated into the MedInsight Analytic
Platform, but is also offered as a standalone application. HCG Grouper leverages
Milliman's Health Cost Guidelines™ (HCGs), the industry standard for tracking claim
costs by hospital, surgical, medical, and other benefit service categories. HCG research
employs multiple sources of data, more than 30 million patients, and more than 2 billion
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claim records across data sets from both the public and private sector. HCGs can be used
to adjust national average healthcare costs for specific geographic areas, benefits,
reimbursement structures, and plan characteristics. Traditional health insurers, managed
care organizations, and third-party administrators find them valuable for product
evaluation and pricing. The HCG Grouper application utilizes HCGs to assign detailed
information to claims. Each line of claim detail is assigned an HCG service cost category,
number of admits or cases, number of days or procedures, and procedure grouped
families, as well as identification of continuous stay claims.
Benefits
The HCG Grouper application helps quantify your organization's performance and can be
used to analyze cost and utilization for many different types of population data, such as
product lines, line of business, employer groups, primary care panels, disease
populations, and many others.
MedInsight Benchmarks
The combination of looming healthcare reform and trying economic times is driving
health plans to create new strategies to improve financial and clinical performance. A
crucial piece of every strategy is the use of benchmarks for setting goals and
communicating objectives to a wide range of staff. Often, health plans perform one-time
benchmark studies using external bodies and their static benchmarks. This use of external
data is no longer adequate for today’s fiercely competitive marketplace.
Common issues with the use of external benchmarks include:
Benchmarks that are based on limited sample sizes
Aggregated empirical data devoid of local market adjustments and unable to
provide a realistic picture of the marketplace
Lack of drill-down capabilities that facilitate a greater depth of understanding
Impractical benchmarking methods that require significant data integration efforts
in addition to in-depth analytic review
Difficulty tracking external benchmarks over time
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The MedInsight Benchmarks application integrates vast empirical data, intimate local
market knowledge, and a wide number of plan and provider agreement variables. These
adjustments turn normative data into valuable, meaningful benchmarks. The MedInsight
Benchmark tool is accessed as a standalone web application, but is also part of the
MedInsight Analytic Platform.
Benefits
MedInsight Benchmarks offers the ability to generate custom benchmarks with deep
drill-downs of insight for any commercial or Medicare population, geographic region,
and benefit plan(s).
The vast Milliman empirical database, rigorous organizational methods, and advanced
adjustment factors let you effectively use your data to:
Measure cost and rating development.
Review procedural efficiency.
Create custom methods or combine your desired methods with Milliman's
advanced local market-adjustment factors.
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CONCLUSION
Medinsight maintains a copy of information from the source transaction systems. This
architectural complexity provides the opportunity to: Maintain data history, even if the
source transaction systems do not. Integrate data from multiple source systems, enabling
a central view across the enterprise. This benefit is always valuable, but particularly so
when the organization has grown by merger. Improve data, by providing consistent codes
and descriptions, flagging or even fixing bad data. Present the organization's information
consistently. Provide a single common data model for all data of interest regardless of the
data's source. Restructure the data so that it makes sense to the business users.
Restructure the data so that it delivers excellent query performance, even for complex
analytic queries, without impacting the operational systems. Add value to operational
business applications. Integrated with existing data warehousing systems and initiatives,
MedInsight helps healthcare organizations harness and leverage the power of the
industry’s most comprehensive performance measurement and analysis product
REFERENCE:
http://www.medinsight.milliman.com
http://www.mi60 systemoverview.com
http://www.medinsight.com/solutions/enterprise-solutions/medinsight-analytic-platform/
index.php
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