Challenges to electronic clinical quality measurement using third-party platforms in primary care practices: the healthy hearts in the heartland experience.

Third-party platforms have emerged to support small primary care practices for calculating and reporting electronic clinical quality measures (eCQM) for federal programs like The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) and Merit-based Incentive Payment System (MIPS). Yet little is known about the capabilities and limitations of electronic health record systems (EHRs) to enable data access for these programs. We connected 116 small- to medium-sized practices with seven different EHRs to popHealth, an open-source eCQM platform. We identified the prevalence of following problems with eCQM data for data extraction in seven different EHRs: (1) Lack of coded data in five of seven; (2) Incorrectly categorized data in four of seven; (3) Isosemantic data (data within the incorrect context) in four of seven; (4) Coding that could not be directly evaluated in six of seven; (5) Errors in date assignment and labeled as historical values in five of seven; and (6) Inadequate data to assign the correct code in two of seven. We recommend specific enhancements to EHR systems that can promote effective eCQM implementation and reporting to MACRA and MIPS.

Use of a data warehouse at an academic medical center for clinical pathology quality improvement, education, and research.

BACKGROUND: Pathology data contained within the electronic health record (EHR), and laboratory information system (LIS) of hospitals represents a potentially powerful resource to improve clinical care. However, existing reporting tools within commercial EHR and LIS software may not be able to efficiently and rapidly mine data for quality improvement and research applications. MATERIALS AND METHODS: We present experience using a data warehouse produced collaboratively between an academic medical center and a private company. The data warehouse contains data from the EHR, LIS, admission/discharge/transfer system, and billing records and can be accessed using a self-service data access tool known as Starmaker. The Starmaker software allows users to use complex Boolean logic, include and exclude rules, unit conversion and reference scaling, and value aggregation using a straightforward visual interface. More complex queries can be achieved by users with experience with Structured Query Language. Queries can use biomedical ontologies such as Logical Observation Identifiers Names and Codes and Systematized Nomenclature of Medicine. RESULT: We present examples of successful searches using Starmaker, falling mostly in the realm of microbiology and clinical chemistry/toxicology. The searches were ones that were either very difficult or basically infeasible using reporting tools within the EHR and LIS used in the medical center. One of the main strengths of Starmaker searches is rapid results, with typical searches covering 5 years taking only 1-2 min. A "Run Count" feature quickly outputs the number of cases meeting criteria, allowing for refinement of searches before downloading patient-identifiable data. The Starmaker tool is available to pathology residents and fellows, with some using this tool for quality improvement and scholarly projects. CONCLUSION: A data warehouse has significant potential for improving utilization of clinical pathology testing. Software that can access data warehouse using a straightforward visual interface can be incorporated into pathology training programs.