: Several national organizations have proposed metrics for measuring quality of care in the ambulatory setting. These metrics, however, are all limited by the fact that they were largely designed to measure ambulatory care in isolation, independent of interactions with other health care providers and other health care settings. Innovations in health care driven by implementation of health information technology (HIT) with health information exchange (HIE) require revised sets of quality metrics that can capture the types of effects these interventions promise. For example, new metrics are needed to capture effects on care that arise from sharing data among generalists and specialists in the ambulatory setting and from sharing data across transitions between inpatient and outpatient settings. Existing quality metrics were also derived with the expectation that the data would be collected from manual chart review, administrative data and/or claims data. These methods of data collection are limited by time and expense (manual chart review) or lack of clinical detail (administrative and claims data). New quality metrics are needed to capitalize on the rich clinical data that could be extracted from electronic health records (EHRs) and other electronic sources. ? ? We propose to derive a set of quality metrics that builds on existing metrics but adds metrics that can ? capture the effects of HIT with HIE and that can be retrieved electronically (Aim 1). We will achieve this aim through the contributions of the Health Information Technology Evaluation Collaborative (HITEC, a multi-institutional academic collaborative established to evaluate HIT and HIE initiatives in New York State), the New York State Department of Health and 4 regional health information organizations (RHIOs) that are implementing HIT with HIE and focusing on the ambulatory setting. We will present our quality metric set to 2 groups for validation: a panel of national experts in quality measurement and the New York eHealth Collaborative, a multi-stakeholder organization dedicated to advancing health care performance measurement, as supported by HIT (Aim 2). We will refine our metric set with the expert panel using the RAND method for selecting quality indicators (Aim 2). We will then test the accuracy of electronic retrieval of data for our metric set, compared to the gold standard of manual chart review, using performance data from one of the RHIOs, the Taconic Health Information Network and Community (THINC) (Aim 3). Finally, we will apply our metric set to evaluate the effects on quality of using HIT with HIE; specifically, EHRs and electronic portals (Aim 4). To achieve this last aim, we will prospectively follow a randomly selected sample of physicians in THINC's ambulatory practices and determine if quality improves over 1 year of using HIT with HIE. ? ? This work has the potential to move closer toward capitalizing on the promise of HIT for improving ? quality measurement. If validated and effective, the metrics developed and interventions studied through this proposal could also be disseminated widely to other ambulatory care communities. ? ? ? ?
| Kern, Lisa M; Edwards, Alison M; Pichardo, Michelle et al. (2015) Electronic health records and health care quality over time in a federally qualified health center. J Am Med Inform Assoc 22:453-8 |
| Kern, Lisa M; Malhotra, Sameer; Barron, Yolanda et al. (2013) Accuracy of electronically reported ""meaningful use"" clinical quality measures: a cross-sectional study. Ann Intern Med 158:77-83 |
| Kern, Lisa M; Dhopeshwarkar, Rina; Barrón, Yolanda et al. (2009) Measuring the effects of health information technology on quality of care: a novel set of proposed metrics for electronic quality reporting. Jt Comm J Qual Patient Saf 35:359-69 |
