Marcus Wilson, PharmD. First Plenary Session

Transcription

1 Moderator First Plenary Session THE USE OF "BIG DATA" - WHERE ARE WE AND WHAT DOES THE FUTURE HOLD? Marcus Wilson, PharmD HealthCore Wilmington, DE, USA Speakers First Plenary Session THE USE OF "BIG DATA" - WHERE ARE WE AND WHAT DOES THE FUTURE HOLD? David R. Holmes III, PhD Mayo Clinic College of Medicine Rochester, MN, USA William H. Crown, PhD Optum Labs Cambridge, MA, USA Lesley H. Curtis, PhD Duke University Durham, NC, USA

2 The Use of Big Data in Health Care Decisions Where are we and what does the future hold? Marcus D Wilson, Pharm.D. President HealthCore A WellPoint Company Global Healthcare Analytics Market 2020 Projection Introduction Growth Maturity Decline Healthcare Analytics/Medical Analytics Market MarketsandMarkets Report

3 What is Driving the Growth in Analytics Greater amounts of and improved access to electronic healthcare data Advances in analytic methods Improved computation power Increasing concerns with lack of generalizability of traditional clinical trials Emphasis on population applicability from payers Shifting financial risk models Need for more effective clinical decision support Healthcare Analytics Breakdown A means of categorizing analytics: Descriptive (85%) Tells you what ed and often why Predictive (12%) Tells you what will Prescriptive (3%) Tells you what to do about it Descriptive provides the evidence base and Predictive and Prescriptive put this evidence to work powering healthcare decision-making

4 Optimizing Analytics to Improve Outcomes Information on the individual or population Prescriptive Natural History of Aging/Disease/ Condition etc. Predict what will Change what will Predictive Interventional Literature Descriptive How Good is our Evidence Base? Assessing the Evidence Gap 16 current guidelines report levels of evidence In total, these guidelines contain 2,711 recommendations 314 (11%) of these had evidence classified as A Recommendation based upon evidence from multiple randomized trials or metaanalyses Less than half of the recommendations (48.8%) had evidence considered level I Conditions for which there is evidence and/or general agreement that a given procedure or treatment is useful and effective The traditional clinical trials infrastructure in vastly insufficient to facilitate the filling of this gap. Too expensive Too slow Inability to collect many key endpoints including real world outcomes

5 How Good is our Evidence Base? Underlying challenge in knowledge development Variances in populations utilizing technology versus the populations studied Differing age groups (elderly, pediatrics) I II III Post Marketing Evidence Development Utilization Race, ethnicity & gender variances Unstudied co morbid conditions Differing concomitant drugs (including OTC) Lifestyle variances including smoking, dietary habits Differences in disease severity Varying levels of compliance Challenge 1: Improving the speed & efficiency of evidence development Information on the individual or population Natural History of Aging/Disease/ Condition etc. Predict what will Change what will Interventional Literature Descriptive

6 Challenge 2: Developing deeper data on the individual & populations Information on the individual or population Natural History of Aging/Disease/ Condition etc. Predict what will Change what will Interventional Literature Optimizing Analytics Identifying populations and determining endpoints In Claims: How do we determine if a person does (or does not) have a condition? Best balance If you are concerned with making sure all patients identified actually do have HTN, Specificity matters most If you are more concerned with capturing all patients with HTN, Sensitivity matters most *Medical chart utilized as gold standard for hypertension diagnosis. Bullano MF, et al. Med Care. 2006;44:

7 Optimizing Analytics Identifying populations and determining endpoints Claims EHR data integration pilot Extracted two cohorts of members with diabetes from a large group practice and integrated data from the members EHR with claims data on the same members One cohort identified using claims One cohort identified using integrated claims and EHR data Claims Only Claims + EHR Greater than 40 percent increase in number of patients identified with diabetes Accelerating Real World Evidence Development The Evolution of Real World Data The greater the overlap the deeper the insight Health Plan Claims Each Data Source Contributes Unique Information Health Plan Claims provides a broad view, insight into cost of care & information such as actual fill (Rx) history Patient Reported Information Inpatient Chart Information Outpatient Chart Information provides rich clinical information and such endpoints as prescribed medications, lab and test results, OTC advice and reported use, family history Outpatient Chart Information Inpatient Chart Information provides rich clinical information on procedures, conditions treated, medication use, lab and test results

8 Of All the Relationships in Health Care, This One is the Most Important Everything we do must be done with the intent of strengthening the bond and improving decision-making between physician and patient. Explosion in New Medical Evidence Last 50 Years 1,000, , , ,000 Additions to MEDLINE by Year of Publication 872, , , , , , ,000 Source National Library of Medicine Currently houses more than 20 million citations 5,640 journals referenced in PubMed (as of July, 2013) Represents 20 25% of the Journals in circulation

9 Optimizing Analytics to Improve Outcomes Information on the individual or population Prescriptive Natural History of Aging/Disease/ Condition etc. Predict what will Change what will Predictive Interventional Literature Descriptive Moderator First Plenary Session THE USE OF "BIG DATA" - WHERE ARE WE AND WHAT DOES THE FUTURE HOLD? Marcus Wilson, PharmD HealthCore Wilmington, DE, USA