The Veterans Administration was an early adopter of quality measurement, performance accountability, and the use of EHRs. The VA is into their second decade of using EHRs along with quality measures to help care for veterans. Originally, most nationally recognized quality measures were implemented in a “one size fits all” manner.
Joseph Francis, MD., from the Office of Informatics and Analytics within the VA’s Central Office, provides commentary on quality measures on the VA’s Health Services Research & Development Service site. As he reports, most quality measures today focus on a single episode of care, and therefore, they may also fail to capture appropriate clinical decisions and changes in the patient’s health status and risk over a longitudinal timeframe.
His commentary points out that the EHR VistA-CPRS remains limited in its ability to capture clinical concepts using standardized data elements. As a result, the VA currently uses chart abstraction on a sample of veterans to estimate performance based on HEDIS a set of performance measures maintained by NCQA and Joint Commission measures.
When structured clinical data is captured electronically, it often occurs through relatively inflexible clinical reminders, which can create challenges for clinicians due to the poor context-sensitivity of the reminders and their interference with workflow.
The situation today is that nearly $20 billion in incentive payments have been made available to hospitals and providers to accelerate EHR adoption as part of the HITECH Act. Providers and hospitals that adopt certified EHRs must demonstrate Meaningful Use by generating and reporting quality measures and public health information.
Also, Stage 2 and 3 of Meaningful Use will require information sent electronically to providers to use nationally recognized data standards so that health information will be shared seamlessly across multiple health systems and providers. In addition, rapid advances in computer science especially the use of natural language processing for complex analytics are allowing the use of much richer information to provide context-sensitive, patient-centric decision support.
As a result of these developments, new ways have to be considered on how to measure quality in the future with the need to:
- Develop longitudinal quality measurements that incorporate clinical actions
- Develop risk-tailored quality measurements
- Develop patient-centered quality measurements
