Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry. Issue 1 (30th September 2019)
- Record Type:
- Journal Article
- Title:
- Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry. Issue 1 (30th September 2019)
- Main Title:
- Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry
- Authors:
- 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, KT
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.
… (more) - 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.
- Is Part Of:
- EGEMS. Volume 7:Issue 1(2019)
- Journal:
- EGEMS
- Issue:
- Volume 7:Issue 1(2019)
- Issue Display:
- Volume 7, Issue 1 (2019)
- Year:
- 2019
- Volume:
- 7
- Issue:
- 1
- Issue Sort Value:
- 2019-0007-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2019-09-30
- Subjects:
- Quality Improvement -- Data Quality -- Registry
Medical records -- Data processing -- Periodicals
Medical care -- Data processing -- Periodicals
Medical Records
Automatic Data Processing
Medical care -- Data processing
Medical records -- Data processing
Periodicals
Periodicals
651.504261 - Journal URLs:
- https://egems.academyhealth.org/ ↗
http://bibpurl.oclc.org/web/49556 ↗
http://repository.academyhealth.org/egems/ ↗
http://search.ebscohost.com/direct.asp?db=a9h&jid=GD7Z ↗
http://www.ncbi.nlm.nih.gov/pmc/journals/2686/ ↗ - DOI:
- 10.5334/egems.262 ↗
- Languages:
- English
- ISSNs:
- 2327-9214
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 14747.xml