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Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry

Pratt, J.; Jeffers, D.; King, E. C.; Kappelman, M. D.; Collins, J.; Margolis, P.; Baron, H.; Bass, J. A.; Bassett, M. D.; Beasley, G. L.; Benkov, K. J.; Bornstein, J. A.; Cabrera, J. M.; Crandall, W.; Dancel, L. D.; Garin-Laflam, M. P.; Grunow, J. E.; Hirsch, B. Z.; Hoffenberg, E.; Israel, E.; Jester, T. W.; Kiparissi, F.; Lakhole, A.; Lapsia, S. P.; Minar, P.; Navarro, F. A.; Neef, H.; Park, K. T.; Pashankar, D. S.; Patel, A. S.; Pineiro, V. M.; Samson, C. M.; Sandberg, K. C.; Steiner, S. J.; Strople, J. A.; Sudel, B.; Sullivan, J. S.; Suskind, D. L.; Uppal, V.; Wali, P. D.

EGEMS (Wash DC). 2019 Oct 28; 7(1):51


OBJECTIVE: To implement a quality improvement based system to measure and improve data quality in an observational clinical registry to support a Learning Healthcare System. DATA SOURCE: ImproveCareNow Network registry, which as of September 2019 contained data from 314,250 visits of 43,305 pediatric Inflammatory Bowel Disease (IBD) patients at 109 participating care centers. STUDY DESIGN: The impact of data quality improvement support to care centers was evaluated using statistical process control methodology. Data quality measures were defined, performance feedback of those measures using statistical process control charts was implemented, and reports that identified data items not following data quality checks were developed to enable centers to monitor and improve the quality of their data. PRINCIPAL FINDINGS: There was a pattern of improvement across measures of data quality. The proportion of visits with complete critical data increased from 72 percent to 82 percent. The percent of registered patients improved from 59 percent to 83 percent. Of three additional measures of data consistency and timeliness, one improved performance from 42 percent to 63 percent. Performance declined on one measure due to changes in network documentation practices and maturation. There was variation among care centers in data quality. CONCLUSIONS: A quality improvement based approach to data quality monitoring and improvement is feasible and effective.

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