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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 1

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CONTENTSS.No 1 2 3 4 5 6 7 8 9 10 11 12 13 Contents Introduction IT tools and there benefits Company Profile Technology and operation solutions IT TOOL-Medinsight Medinsight-Architecture Key Features Medinsight-Technical overview Case study Medinsight version 7.0 Solutions Conclusion Reference Page No. 4 5 6 7 7 10 13 15 21 23 24 28 28


DATABASE MANAGEMENT SOLUTION-A case study of Milliman Medinsight. INTRODUCTIONInitially 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 planning (ERP), enterprise management performance applications, enterprise resource

management (EPM), supplychainmanagement(SCM), customerrelationshipmanagement (CRM), project management and database retrieval applications.


IT TOOLS AND THERE BENEFITS FOR HEALTH INSURANCE COSPayers, 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 countrys 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 industryfrom commercial payers, Blue Cross Blue Shield organizations, and government-focused insurers to self-funded employers and TPAshas 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 prioritiesjust 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. 3

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 PROFILEMilliman 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 principalssenior 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 4

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 SolutionsAs 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 clients needs

IT TOOL-MEDINSIGHTMedInsight 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.


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 clients 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 industrys 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.


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 Access 2. Oracle 3. Sybase 4. Adabas 5. Paradox 6. 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


MedInsight-ArchitectureMedInsight was developed on the foundation of Millimans 50 plus years of healthcare data analysis and experience. Its architecture specifically addresses an organizations need to retain data accuracy and integrity over time


Acquire, Transform, Load Data 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 MedInsights 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). Aggregate MedInsight 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 MedInsights Analysis Data Marts. Distribute MedInsight 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 MedInsights Analysis Data Marts. These data marts provide OLAP-optimized, reconcilable, multi-dimensional views of the medical, financial, operational, marketing, and administrative information in a clients data repository. The data analysis data marts can be categorized as follows: 9

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 System The 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 System MedInsight 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 Compliant MedInsight 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 clients Microsoft Windows 2000 and NT computing environments MedInsight is engineered to conform to HIPAA standards and can be used to ease an organizations HIPAA compliance efforts.


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 userdefined period. Since MedInsight analysis procedures are modular Transact-SQL routines, they will integrate with virtually any job/batch-scheduling engine

Key FeaturesPerformance 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: 11

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 Millimans 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 12

Disease Identification MedInsights 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 MedInsights 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 OverviewMedInsight 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 portal Dashboard Report Library Enrollment MedInsight Reports Claims Custom Reports Clinical Financial

Analytic tools Cubes Extract Builder

Reference library Documentation User Manual



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.


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


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.


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


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 savingsA 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 benchmarkoverutilization was the main driver. Physician office services were twice the benchmarkcost per visit was the main driver. Radiology was four times the benchmarkone 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 increaseA 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 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 21

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

SOLUTIONSAll-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 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 23

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 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 todays fiercely competitive marketplace. Common issues with the use of external benchmarks include: Benchmarks that are based on limited sample sizes 24

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 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.


CONCLUSIONMedinsight 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 industrys most comprehensive performance measurement and analysis product

REFERENCE: http://www.mi60