Using Health Data to Measure Performance: Are We Going to be Successful?

Sourcing Data to Describe Health Care Quality and Performance Quality Metrics From Paid Claims EHR Sourced Quality Metrics Each source is driven by a very different purpose. The questions is: are EHR data better?

Sourcing Health Data Claims-based reporting is a view through the rear view mirror. It has little or no effect on clinical decision-making – Data have been available, so we have constructed “quality measures” from this source [when HEDIS started in 1991, EMRs were rudimentary and claims data ruled]. – It has shaped our thinking about what’s broken in the industry and what to focus on for improvement. – But does it really lead to improvement in clinical outcomes in populations? If not, then why continue doing it?

Industry Symptoms Clinicians do not reference the Washington Health Alliance Community Checkup reports (claims data). Administrators do. Clinicians complain that claims based reporting is not clinically relevant. Little evidence that claims-based performance reporting leads to improved clinical outcomes.

Improving Population Health with the Wrong Tool is Like:

EHRs as the Data Source Harvest desired data to a warehouse on a daily basis Each practice has a dashboard that profiles real time performance (% complete) on each “quality” measure of interest for all patient groups of interest Missing your target? - click to a view listing patient names and contact for follow up. Work flow self correction results in improved performance in reporting

Barriers…and Solutions Not everyone uses Epic (!) In an IPA of 520 providers (Northwest Physicians) 49 different EMR platforms are in use. NPN is beginning to use a SaaS solution using semantic technologies to suck out, digest and report back clinically meaningful information from non-standard platforms with an ability to modify or adapt measures easily. Measurement selection is driven in part by clinical interest and relevancy to the practice.

The Assumption Does Population Health hold the keys to increasing Value? Value Increases WHEN: Quality increases, even if expenditures are constant OR Value Increases WHEN: Costs are reduced, but quality is held constant Value = Quality ÷ Cost

ACO Cost-Quality Comparison… Y axis - Average annual Medicare cost per patient. X axis- Average quality percentile score on 22 MSSP CQMs. Each dot represents a practice in the ACO. Y axis - Average annual Medicare cost per patient. X axis- Average quality percentile score on 22 MSSP CQMs. Each dot represents a practice in the ACO.

ACO Clinical Quality Measurement Scorecard… Snapshot of one ACO’s performance on the 22 CQMs under MSSP. Identifies clinical areas that need improvement. Snapshot of one ACO’s performance on the 22 CQMs under MSSP. Identifies clinical areas that need improvement.

ACO Practice Scorecard… Compares performance of practices within an ACO. Helps identify underperforming practices and is a tool to drive improvement. Compares performance of practices within an ACO. Helps identify underperforming practices and is a tool to drive improvement.

Stratifying Patients by Gaps… Patient stratification based on urgency of preventing and/or closing specific gaps in care.

Caution Ahead EHR data are only as good as the coding detail. For many common disease groups (e.g. T2 diabetes, asthma, CHF) ~ 50% of the codes submitted with billing are NOS or lack significant detail, offering little relevance for profiling, intervention and clinical management improvement. To date, coding performance has been miserable; ICD-10 will be a real challenge. Improvement in coding specificity is a key to population health improvement. Coding precision needs to become valued for clinical reasons; it’s not just a business intrusion in medicine. The clinical relevance of population data is determined by their specificity.