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Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry.
Pratt, Jesse; Jeffers, Daniel; King, Eileen C; Kappelman, Michael D; Collins, Jennifer; Margolis, Peter; Baron, Howard; Bass, Julie A; Bassett, Mikelle D; Beasley, Genie L; Benkov, Keith J; Bornstein, Jeffrey A; Cabrera, José M; Crandall, Wallace; Dancel, Liz D; Garin-Laflam, Monica P; Grunow, John E; Hirsch, Barry Z; Hoffenberg, Edward; Israel, Esther; Jester, Traci W; Kiparissi, Fevronia; Lakhole, Arathi; Lapsia, Sameer P; Minar, Phillip; Navarro, Fernando A; Neef, Haley; Park, K T; Pashankar, Dinesh S; Patel, Ashish S; Pineiro, Victor M; Samson, Charles M; Sandberg, Kelly C; Steiner, Steven J; Strople, Jennifer A; Sudel, Boris; Sullivan, Jillian S; Suskind, David L; Uppal, Vikas; Wali, Prateek D.
Afiliação
  • Pratt J; Pharmaceutical Product Development, US.
  • Jeffers D; Total Quality Logistics, US.
  • King EC; Cincinnati Children's Hospital Medical Center, University of Cincinnati, US.
  • Kappelman MD; University of North Carolina at Chapel Hill, US.
  • Collins J; Cincinnati Children's Hospital Medical Center, US.
  • Margolis P; Cincinnati Children's Hospital Medical Center, University of Cincinnati, US.
  • Baron H; Pediatric Gastroenterology & Nutrition Associates, US.
  • Bass JA; Children's Mercy, US.
  • Bassett MD; OHSU Doernbecher Children's Hospital, US.
  • Beasley GL; UF Health Pediatric Gastroenterology, Hepatology and Nutrition, US.
  • Benkov KJ; Kravis Children's Hospital at Mount Sinai, US.
  • Bornstein JA; Arnold Palmer Hospital for Children, US.
  • Cabrera JM; Children's Hospital of Wisconsin, US.
  • Crandall W; Eli Lilly and Company, US.
  • Dancel LD; Greenville Health System, Children's Hospital, US.
  • Garin-Laflam MP; Carilion Clinic Children's Hospital, US.
  • Grunow JE; Oklahoma University Medical Center, US.
  • Hirsch BZ; Baystate Medical Center, US.
  • Hoffenberg E; Children's Hospital Colorado, US.
  • Israel E; MassGeneral Hospital for Children, US.
  • Jester TW; Children's of Alabama, US.
  • Kiparissi F; Great Ormond Street Hospital, GB.
  • Lakhole A; UCSF Benioff Children's Hospital Oakland, US.
  • Lapsia SP; Children's Hospital of the King's Daughters, US.
  • Minar P; Cincinnati Children's Hospital Medical Center, University of Cincinnati, US.
  • Navarro FA; Children's Memorial Hermann Hospital - UT Houston, US.
  • Neef H; University of Michigan - C.S. Mott Children's Hospital, US.
  • Park KT; Genentech, US.
  • Pashankar DS; Yale-New Haven Children's Hospital, US.
  • Patel AS; UT Southwestern/Children's Health, US.
  • Pineiro VM; Levine Children's Hospital, US.
  • Samson CM; St. Louis Children's Hospital - Washington University, US.
  • Sandberg KC; Dayton Children's Hospital, US.
  • Steiner SJ; Riley Hospital for Children, US.
  • Strople JA; Ann and Robert H. Lurie Children's Hospital of Chicago, US.
  • Sudel B; University of Minnesota, US.
  • Sullivan JS; The University of Vermont Children's Hospital, US.
  • Suskind DL; Seattle Children's Hospital, US.
  • Uppal V; Nemours Children's Health System - Wilmington, US.
  • Wali PD; Upstate Golisano Children's Hospital, US.
EGEMS (Wash DC) ; 7(1): 51, 2019 Sep 30.
Article em En | MEDLINE | ID: mdl-31646151
ABSTRACT

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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: EGEMS (Wash DC) Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: EGEMS (Wash DC) Ano de publicação: 2019 Tipo de documento: Article