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

Jesse Pratt; Daniel Jeffers; Eileen C. King; Michael D. Kappelman; Jennifer Collins; Peter Margolis; Howard Baron; Julie A. Bass; Mikelle D. Bassett; Genie L. Beasley; Keith J. Benkov; Jeffrey A. Bornstein; Jose M. Cabrera; Wallace Crandall; Liz D. Dancel; Monica P. Garin-Laflam; John E. Grunow; Barry Z. Hirssch; Edward Hoffenberg; Esther Israel; Traci W. Jester; Fevronia Kiparissi; Arathi Lakhole; Sameer P. Lapsia; Phillip Minar; Fernando A. Navarro; Haley Neef; KT Park; Dinesh S. Pashankar; Ashish S. Patel; Victor M. Pineiro; Chrles M. Samson; Kelly C. Sandberg; Steven J. Steiner; Jennifer A. Strople; Boris Sudel; Jillian S. Sullivan; David L. Suskind; Vikas Uppal; Prateek D. Wali

doi:10.5334/egems.262

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

Jesse Pratt, Daniel Jeffers, Eileen C. King, Michael D. Kappelman, Jennifer Collins, Peter Margolis, Howard Baron, Julie A. Bass, Mikelle D. Bassett, Genie L. Beasley, Keith J. Benkov, Jeffrey A. Bornstein, Jose M. Cabrera, Wallace Crandall, Liz D. Dancel, Monica P. Garin-Laflam, John E. Grunow, Barry Z. Hirssch, Edward Hoffenberg, Esther IsraelTraci W. Jester, Fevronia Kiparissi, Arathi Lakhole, Sameer P. Lapsia, Phillip Minar, Fernando A. Navarro, Haley Neef, KT Park, Dinesh S. Pashankar, Ashish S. Patel, Victor M. Pineiro, Chrles M. Samson, Kelly C. Sandberg, Steven J. Steiner, Jennifer A. Strople, Boris Sudel, Jillian S. Sullivan, David L. Suskind, Vikas Uppal, Prateek D. Wali

Wright State University

Research output: Contribution to journal › Article › peer-review

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.

Original language	American English
Journal	eGEMs
Volume	7
DOIs	https://doi.org/10.5334/egems.262
State	Published - Sep 30 2019

Keywords

Data Quality
Quality Improvement
Registry

Disciplines

Medical Specialties
Medicine and Health Sciences
Pediatrics

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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., Hirssch, B. Z., Hoffenberg, E., ... Wali, P. D. (2019). Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry. eGEMs, 7. https://doi.org/10.5334/egems.262

Pratt, J, Jeffers, D, King, EC, Kappelman, MD, Collins, J, Margolis, P, Baron, H, Bass, JA, Bassett, MD, Beasley, GL, Benkov, KJ, Bornstein, JA, Cabrera, JM, Crandall, W, Dancel, LD, Garin-Laflam, MP, Grunow, JE, Hirssch, BZ, Hoffenberg, E, Israel, E, Jester, TW, Kiparissi, F, Lakhole, A, Lapsia, SP, Minar, P, Navarro, FA, Neef, H, Park, KT, Pashankar, DS, Patel, AS, Pineiro, VM, Samson, CM, Sandberg, KC, Steiner, SJ, Strople, JA, Sudel, B, Sullivan, JS, Suskind, DL, Uppal, V & Wali, PD 2019, 'Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry', eGEMs, vol. 7. https://doi.org/10.5334/egems.262

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

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.",

keywords = "Data Quality, Quality Improvement, Registry",

author = "Jesse Pratt and Daniel Jeffers and King, {Eileen C.} and Kappelman, {Michael D.} and Jennifer Collins and Peter Margolis and Howard Baron and Bass, {Julie A.} and Bassett, {Mikelle D.} and Beasley, {Genie L.} and Benkov, {Keith J.} and Bornstein, {Jeffrey A.} and Cabrera, {Jose M.} and Wallace Crandall and Dancel, {Liz D.} and Garin-Laflam, {Monica P.} and Grunow, {John E.} and Hirssch, {Barry Z.} and Edward Hoffenberg and Esther Israel and Jester, {Traci W.} and Fevronia Kiparissi and Arathi Lakhole and Lapsia, {Sameer P.} and Phillip Minar and Navarro, {Fernando A.} and Haley Neef and KT Park and Pashankar, {Dinesh S.} and Patel, {Ashish S.} and Pineiro, {Victor M.} and Samson, {Chrles M.} and Sandberg, {Kelly C.} and Steiner, {Steven J.} and Strople, {Jennifer A.} and Boris Sudel and Sullivan, {Jillian S.} and Suskind, {David L.} and Vikas Uppal and Wali, {Prateek D.}",

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doi = "10.5334/egems.262",

language = "American English",

volume = "7",

journal = "eGEMs",

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TY - JOUR

T1 - Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry

AU - Pratt, Jesse

AU - Jeffers, Daniel

AU - King, Eileen C.

AU - Kappelman, Michael D.

AU - Collins, Jennifer

AU - Margolis, Peter

AU - Baron, Howard

AU - Bass, Julie A.

AU - Bassett, Mikelle D.

AU - Beasley, Genie L.

AU - Benkov, Keith J.

AU - Bornstein, Jeffrey A.

AU - Cabrera, Jose M.

AU - Crandall, Wallace

AU - Dancel, Liz D.

AU - Garin-Laflam, Monica P.

AU - Grunow, John E.

AU - Hirssch, Barry Z.

AU - Hoffenberg, Edward

AU - Israel, Esther

AU - Jester, Traci W.

AU - Kiparissi, Fevronia

AU - Lakhole, Arathi

AU - Lapsia, Sameer P.

AU - Minar, Phillip

AU - Navarro, Fernando A.

AU - Neef, Haley

AU - Park, KT

AU - Pashankar, Dinesh S.

AU - Patel, Ashish S.

AU - Pineiro, Victor M.

AU - Samson, Chrles M.

AU - Sandberg, Kelly C.

AU - Steiner, Steven J.

AU - Strople, Jennifer A.

AU - Sudel, Boris

AU - Sullivan, Jillian S.

AU - Suskind, David L.

AU - Uppal, Vikas

AU - Wali, Prateek D.

PY - 2019/9/30

Y1 - 2019/9/30

N2 - 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.

AB - 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.

KW - Data Quality

KW - Quality Improvement

KW - Registry

UR - https://corescholar.libraries.wright.edu/pediatrics/478

U2 - 10.5334/egems.262

DO - 10.5334/egems.262

M3 - Article

VL - 7

JO - eGEMs

JF - eGEMs

ER -

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

Abstract

Keywords

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