EXPANDING THE EVIDENCE BASE IN OUTCOMES RESEARCH: USING LINKED ELECTRONIC MEDICAL RECORDS (EMR) AND CLAIMS DATA. ISPOR Workshop, May 22, 2013
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1 EXPANDING THE EVIDENCE BASE IN OUTCOMES RESEARCH: USING LINKED ELECTRONIC MEDICAL RECORDS (EMR) AND CLAIMS DATA ISPOR Workshop, May 22, 2013
2 Agenda Introduction to linked claims-emr database Obesity case study Hypertension case study Discussion
3 Strengths And Limitations Of Claims Data For Outcomes Research Strengths Payer-based systems tend to capture all medical services while the patient is eligible for benefits Objective information on utilization and cost Large sample sizes Limitations Claims only include information related to provision of medical services Undiagnosed conditions will not be captured Only one valid ICD-9 diagnosis code is required for payment Clinical detail may be lost when payments for services are bundled (e.g., inpatient drug administrations) ICD-9 coding is relatively high level Level of severity is generally not known 3
4 Strengths And Limitations Of EMR Data For Outcomes Research Strengths Detailed laboratory results, vitals, and clinical data collected at the point of care Patients generally are not restricted by source of insurance Data is available in a timely manner following each visit Over the counter medications are captured Longitudinal view based on repeated clinical assessments Limitations The EMR reflects the view of a particular clinical provider Office-based EMR data does incorporate inpatient clinical data and vice versa Cost and reimbursement data are not captured Medication prescriptions may not be filled and consumed There is no denominator population 4
5 Rationale for Marketscan-Quintiles EMR Linkage Insured patients have a primary payer that receives claims for all medical services (inpatient, outpatient, pharmacy) Archives of paid claims provide comprehensive patient-level record of medical utilization Truven s Marketscan is a HIPAA-compliant archive for >200 payers Most patients have a primary care provider that has the most complete medical record for that individual Many large primary care practices use electronic medical records (EMRs) Quintiles receives HIPAA-compliant EMR data from a large installed base in primary care offices The primary care provider s EMR can enrich the longitudinal data set provided by insurance claims 5
6 Source Databases, MarketScan Research Databases Health insurance claims from private and Medicare health plans All medical and pharmacy services utilized by plan members Paid amounts, including health plan and patient shares million enrollees Quintiles EMR Database Ambulatory medical records from >30,000 care providers Diagnostic and treatment information Biometric data Clinical laboratory test results Other quantitative and categorical assessments 27.3 million patients represented 6
7 Linkage Method Create pseudo-id based on year and month of birth, sex, and 3-digit ZIP Each unique combination may represent dozens of persons in the population For each pseudo-id, match patient records if they have at least 3 visit dates in common Exclude matches if less than 75% of EMR visit dates within the period of health plan eligibility have corresponding claims 7
8 Demographics of Linked Patients Matched Patients Source Populations MarketScan Claims Quintiles EMR Total Patients 1,712, ,597,775 27,348,905 Percent Female 58.2% 54.1% 57.6% Mean Age (y) Age Group % 20.0% 14.8% % 23.0% 21.2% % 14.4% 13.0% % 15.8% 14.8% % 14.5% 14.5% % 7.6% 10.8% % 2.8% 6.8% 85 - Up 2.5% 1.9% 4.1% 8
9 Frequently Occurring Diagnoses Number of Diagnosis Category Patients Lipid Abnormalities 706,311 Essential Hypertension 643,423 Sinusitis 574,130 Osteoarthritis, Except Spine 328,266 Urinary Tract Infections 327,863 Headache 323,738 Diabetes Mellitus Type 2 322,850 Depression 311,490 Bursitis 309,223 Hernia, Hiatal or Reflux Esophagitis 307,788 Otitis Media 262,145 Hypothyroidism 229,602 Generalized Anxiety Disorder 215,330 Asthma 205,153 Osteoarthritis, Lumbar Spine 194,537 Coronary Artery Disease without Prior Coronary Revascularization 192,324 Arrhythmias 186,673 Dysfunctional Uterine Bleeding 169,741 Obesity 154,159 9
10 For More Information White paper available at Booth #3031 or by request: 10
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