REAL WORLD EVIDENCE- PROMISE AND PITFALLS OF REAL WORLD DATA

Author(s)

Weir S1, Langham S1, Ratcliffe M21PHMR Associates Ltd, London, United Kingdom, 2PHMR Associates, London, United Kingdom

OBJECTIVES: Clinical trials remain the gold standard for proving efficacy but restrictive enrolment criteria and overly controlled study environments limit generalizability. Increasingly, payers and healthcare providers are interested in real world evidence to support the case for pharmaceutical innovations. We review several sources of real world data available to researchers. METHODS: We compare and contrast the pros and cons of data available from administrative (payment) databases, electronic medical record (EMR) databases, and surveys. RESULTS: Administrative claims databases provide fully-integrated, all-encounter patient data on diagnoses, procedures, and payments. However, data quality varies depending upon whether particular fields are required for provider payment. Data on lab and test values are typically lacking. Prescriptions that are written, but not filled by the patient, are usually not captured. Medical record data overlap, to a certain extent, with administrative data. While information on payments for services may not be included, detailed information on test results and lab values are usually captured in the EMR. Data are included on written prescriptions, but the researcher will not know whether the prescription was filled by the patient. Depending upon the clinical system covered, only some encounters (e.g., ambulatory care in the outpatient setting) may be available. Both administrative and EMR data hold the potential to provide longitudinal patient information that is not subject to recall or social desirability biases that often affect survey data. However, information on satisfaction with care, quality of life, activities of daily living, and many other metrics, may only be captured with survey data. CONCLUSIONS: Several sources of rich, longitudinal patient data are available to provide real world evidence on drug effectiveness and cost. In some cases, data may be combined to overcome limitations of a single source. With care, data may be found that will produce generalizable findings for the population of interest.

Conference/Value in Health Info

2012-11, ISPOR Europe 2012, Berlin, Germany

Value in Health, Vol. 15, No. 7 (November 2012)

Code

PRM33

Topic

Real World Data & Information Systems

Topic Subcategory

Reproducibility & Replicability

Disease

Multiple Diseases

Explore Related HEOR by Topic


Your browser is out-of-date

ISPOR recommends that you update your browser for more security, speed and the best experience on ispor.org. Update my browser now

×