Interpreting Healthcare Data: Start with a Good Denominator
Guest post by Michael Barbouche, founder and CEO, Forward Health Group.
As clearly identified in the PCAST Report on Health Information Technology (2011), and as echoed in the recent GAO report Electronic Health Record Programs — Participation Has Increased, but Action Needed to Achieve Goals Including Improved Quality of Care (2014), healthcare continues to have a data problem. The country has invested significantly to advance EHR adoption.
In simpler terms, healthcare data is messy and makes for building of accurate, actionable metadata a problem. It’s clear that the next generation of standards that are being developed by the numerous committees and acronyms and professional societies tackling measure development, harmonization and testing will now need to address the relevance of each measure.
More than a decade ago, a coalition of purchasers, payers and providers came together across Wisconsin to form the Wisconsin Collaborative for Healthcare Quality (www.wchq.org). Groundbreaking initiatives like Get with the Guidelines, Leapfrog and JCAHO revealed that “quality” and “healthcare” could be used in the same sentence (or displayed on a website). These efforts were largely inpatient-focused. Measurement in the outpatient setting, long considered the keystone of payment reform, was an unsolved riddle. WCHQ, at the urging of the IOM, IHI and others accepted the challenge of tackling performance in the ambulatory arena.
At the direction of some very engaged employers, and with input from most of the state’s payers, WCHQ was charged with one very simple goal — apples to apples quality measurement, regardless of health IT infrastructure. The focus had to include both processes of care and outcomes. Oh, and if health systems didn’t have any health IT in place, data still needed to be included for these groups in the measurement effort. What transpired over an 18-month period was remarkable. With unwavering support from administrative and clinical leadership, health systems rolled up their sleeves and dug into their very messy data. Each Monday, we would devise a fiendish list of new tasks to be completed in the next four business days.