Many benefits are associated with the widespread adoption of interoperable electronic medical-record systems. Automation and cost-effective clinical-quality-performance measurement are perhaps among the most important.
Many experts and policymakers appear to believe that automated performance measurement cannot be achieved until after widespread deployment of EMR systems, but that's not the caseit has already happened.
State Medicaid managed-care programs have been under federal mandates for quality measurement for several years, so waiting for widespread deployment of EMR systems to facilitate automated quality assessment was not an option.
Wisconsin Medicaid's automated measures are called the Medicaid Encounter Data Driven Improvement Core Measure Set, or MEDDIC-MS, which is used in the family Medicaid and State Childrens Health Insurance Program programs, and MEDDIC-MS SSI, which is used in a managed-care delivery system for elderly and disabled individuals eligible for supplemental security income, or SSI.
These systems differ substantially from typical, older provider-level measures that can't readily be automated in a number of key ways:
- Performance measurement data are generated routinely from normal operations. Costly, slow and intrusive paper medical record review for data extraction at the provider level has been eliminated, avoiding medical record privacy issues, duplicative paperwork costs, and administrative inefficiency. Clinics and hospitals need to report any service only once and charts need not be pulled for record review.
- Encounter data can be merged with other state electronic data streams to improve data accuracy and completeness. This is not possible with provider or health plan-reported systems, and probably won't be possible on a routine basis even after broad EMR adoption where provider-reported measures are used.
- All measures can be cost-effectively reported every year, avoiding data gaps caused by "measure rotation," such as that used in older measure systems or other similar administrative cost-reduction strategies.
- Health plans or providers do not calculate or report their own performance measure resultsthose are calculated by an independent third party. This prevents duplicative costs while eliminating inaccuracy caused by variations in interpretations of measure specifications, interrater reliability problems or variations in provider data systems. It also improves consistency and prevents any "gaming" of the results. This supports data integrity in measures used in pay-for-performance incentive programs, public reporting and accountability activities.
- Since the measures are user-defined, they can be added to or modified quickly as program needs dictate and include topics of high importance to Medicaid programs.
- The use of automated measures has resulted in excellent economy in terms of very low per-measure cost for the state and no added cost to providers.
In contrast, average per-measure costs for older, nonautomated measures that require medical record review are much higheras much as $17,833 for data acquisition alone.
Gary Ilminen, R.N.Nurse consultantState of WisconsinDepartment of Health and Family ServicesMadison To submit a letter to YOUR VIEWS, click here. Please include your name, title and hometown.