SOA 10 Health Meeting June 28-30, Session # 26 PD: The Use of Electronic Health Information in Actuarial Practice

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1 SOA 10 Health Meeting June 28-30, 2010 Session # 26 PD: The Use of Electronic Health Information in Actuarial Practice David V. Axene, FSA, MAAA, FCA, CERA Radovan Bursac, ASA, MAAA Robert Plesha, ASA, MAAA Marjorie A. Rosenberg, FSA, MAAA

2 Session 26 PD The Use of Electronic Health Information in Actuarial Practice Presented by: David V. Axene, FSA, MAAA, FCA President & Consulting Actuary Overview Introduction Need for this information Case Studies of how this information has helped practice Barriers to broader use Q&A 1

3 Introduction Care is often poorly coordinated because of a lack of information No one is really in charge of a person s care The more information available, the better the care choices will be Most serious issues occur with co- morbidities or dueling conditions Need For This Information Who needs it? The health care provider who sees a current acute issue, but is not aware of other health or care issues in progress Drug interaction: sometimes one drug will work against another, and unless the patient volunteers it, or the provider finds out about it, the problem is never solved. 2

4 Need For This Information Personal example continued Early March I thought I had the seasonal flu even though I had my flu shot After two weeks I started to feel better, but all of a sudden couldn t walk the next morning Ended up in ER, no one knew my background, but they saw I was in serious shape, turned out I had septicemia and I was in septic shock. Need For This Information continued Two weeks later after surgery and a bunch of tests, I am discharged for home physical therapy If I had been in a universal medical record of some type, the would have seen my background, they might have been able to solve my problems more quickly. Without this, they had to start from scratch and eliminate what wasn t a problem 3

5 Case Study #1 Shared Health Shared Health aggregates claims data and some diagnostic data into an easy to use database that providers can access at time of treatment. Database tool is EMR lite. Not a full blown electronic medical record but still providing useful information Case Study #1 Shared Health Performance Observations continued Providers using Shared Health were able to treat more patients since they were more efficient Emergency room services With Shared Health fewer services were required Acuity/severity adjusted cost per visit was lower Fewer services were required when physician used Shared Health 4

6 Case Study #1 Shared Health Pharmacy Services Greater use of generic drugs Great compliance with formulary Lower average cost of drug Primary Care Services Fewer services per visit continued Bottom line - providing useful clinical information to providers around time of service improves the efficiency of the provider s practice. Case Study #2 Kaiser Electronic Medical Record KP HealthConnect: electronic health record built on Epic Software code and customized clinical content from Kaiser Permanente Largest application of Epic Software Optimizing health information technology to transform the way care is delivered. 5

7 Case Study #2 Kaiser Electronic Medical Record continued Fully digital and gain acceptance by physicians, patients, and health plan all the time Drives care pathways, documents provided care, forms basis for care improvement, and enables longitudinal l analyses of care outcomes Barriers To Broader Use Computer-phobia phobia : some providers just don t trust computer based resources Unwillingness to defer current income and invest in resources Not just an age issue Some are making this a requirement at hire within medical group Best implementers have created new culture 6

8 Q&A 7

9 Electronic Health Status Evaluation Tools Radovan Bursac Rob Plesha 2 What is an Electronic Medical Record (EMR)? Electronic collection of health information Primary purpose of providing health care and healthrelated services Can be transmitted, updated, or retrieved, securely and in real-time both at the point of care or remote locations 1

10 3 Summary Screen - Example 4 Advantages Improved quality of care Evidence-based medicine Portability Record Keeping & Organization Multiple data sources Population Reporting Communication Tool Charting Electronic prescribing, referrals, ordering, results Disadvantages Cumbersome Expensive to implement Software Training Workflow changes Potential Privacy Concerns Data Quality Concerns Change 2

11 5 Order Entry Example 6 Data Integration Departmental Systems Administrative Financial Clinical Pharmaceutical Hospital Physician i Offices Billing Disease Management Imaging Lab Pharmacy Data Overview Facilitate Decision-making Rules Engine Alerts/reminders Clinical Protocols Coding assistance Real-time data (lab, pharmacy, imaging) Information Tracking 3

12 7 History Worksheet Example 8 Types of Data in an EMR Lifestyle Data Tobacco Use Body Mass Index (BMI) Alcohol Use Substance Use Pregnancy Info Family History Socioeconomic Family Status Prospective Data Next Surgery Potential Elective Surgery Fertility Treatment Retrospective Data Family History Birth History Pregnancy History 4

13 9 Types of Data in an EMR Medical Data Radiology Images Medication History Surgical History Allergies Other Data Insurance Information Communication Log Patient After Visit Summaries Clinical Data Blood Pressure Pulse Cholesterol (hdl/ldl) Triglycerides A1c 10 Data Quality Data Quality Concerns Misleading Data Change Inconsistent Improved Structure and Controls Self-Reported Potential gaps Misinterpretation of Data Incomplete Data Inconsistent Utilization Omissions Multiple Data Sources Partial Medical Records Translating Data Non-translatable Data Mistranslated Data Incorrect Data Typographical Errors Potential Integration Issues Access to Data Who has access to what data? 5

14 11 Potential Uses of an Electronic Risk Profile IBNR Disease Management Case Management Population Health Management Wellness Programs Underwriting 12 Some Thoughts on Using EMR Data How can we use it? How much data (access) do you have? How much data can you use? Data quality reminder Evaluating Co-morbidities becomes more difficult 6

15 13 Traditional Health Evaluation Tools Premium = [Claims Data* Z] + [Manual * (1-Z)] Claims Data Trending Claims Debit Manuals Benchmarking Analysis Large Claim Review Manual Rates Age/Gender Mix Geographic Location Benefit Level 14 New Underwriting Formula Expected Claims = Experience * (W) + Manual * (X) + HRA/Risk Grouper * (Y) + EMR * (1-W-X-Y) 7

16 15 Additional and Next Tools Claim based Risk Groupers / Risk Adjusters (see SOA) EMR data Health risk assessment data Self reported lifestyle data Social networking data Other public data 16 Health Status Profile Claims Data EMR Information Demographic Data Health Status Profile Health Risk Assessment Results 8

17 17 Adult Tobacco Use Multiple Data Sources Medical Claims Rx Claims EMR Health Risk Assessment Results Member Applications Each Data Source with different Participation Rate Identification Rate 18 Medical Claims 10 Tobacco Users Rx Claims 2 Tobacco Users All Data Sources 20 Tobacco Users EMR 16 Tobacco Users HRA 8 Tobacco Users Data Assumptions 20% Adult Tobacco Use Rate Fictional Group of 100 Adults ~ 20 Tobacco Users Medical Claims 100% Participation 50% Identification Rx Claims 100% Participation 10% Identification EMR Data 100% Participation 80% Identification HRA Data 20% Participation 90% Identification 9

18 19 Conclusion Non-Traditional data sources will become more prevalent Will allow for a more integrated patient experience Amount of data will increase Data quality will continue to be an issue Questions, Comments 10

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