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

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 pediatri...

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ubiquity Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6777196/
https://www.ncbi.nlm.nih.gov/pubmed/31646151
http://dx.doi.org/10.5334/egems.262
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author 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.
author_facet 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.
author_sort Pratt, Jesse
collection PubMed
description 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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spelling pubmed-67771962019-10-23 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, 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. EGEMS (Wash DC) Empirical Research 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. Ubiquity Press 2019-09-30 /pmc/articles/PMC6777196/ /pubmed/31646151 http://dx.doi.org/10.5334/egems.262 Text en Copyright: © 2019 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.
spellingShingle Empirical Research
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.
Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry
title Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry
title_full Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry
title_fullStr Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry
title_full_unstemmed Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry
title_short Implementing a Novel Quality Improvement-Based Approach to Data Quality Monitoring and Enhancement in a Multipurpose Clinical Registry
title_sort implementing a novel quality improvement-based approach to data quality monitoring and enhancement in a multipurpose clinical registry
topic Empirical Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6777196/
https://www.ncbi.nlm.nih.gov/pubmed/31646151
http://dx.doi.org/10.5334/egems.262
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