Difference between revisions of "Journal:Implementing a novel quality improvement-based approach to data quality monitoring and enhancement in a multipurpose clinical registry"
Shawndouglas (talk | contribs) (Created stub. Saving and adding more.) |
Shawndouglas (talk | contribs) (Saving and adding more.) |
||
| Line 4: | Line 4: | ||
|alt = <!-- Alternative text for images --> | |alt = <!-- Alternative text for images --> | ||
|caption = | |caption = | ||
|title_full = 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<br />in a multipurpose clinical registry | ||
|journal = ''The Journal for Electronic Health Data and Methods'' | |journal = ''The Journal for Electronic Health Data and Methods'' | ||
|authors = Pratt, J.; Jeffers, D.; King, E.C.; Kappelman, M.D.; Collins, J.; Margolis, P.; Bron, 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. | |authors = Pratt, J.; Jeffers, D.; King, E.C.; Kappelman, M.D.; Collins, J.; Margolis, P.; Bron, H.; Bass, J.A.;<br />Bassett, M.D.; Beasley, G.L.; Benkov, K.J.; Bornstein, J.A.; Cabrera, J.M.; Crandall, W.; Dancel, L.D.;<br />Garin-Laflam, M.P.; Grunow, J.E.; Hirsch, B.Z.; Hoffenberg, E.; Israel, E.; Jester, T.W.; Kiparissi, F.;<br />Lakhole, A.; Lapsia, S.P.; Minar, P.; Navarro, F.A.; Neef, H.; Park, K.T.; Pashankar, D.S.; Patel, A.S.;<br />Pineiro, V.M.; Samson, C.M.; Sandberg, K.C.; Steiner, S.J.; Strople, J.A.; Sudel, B.; Sullivan, J.S.;<br />Suskind, D.L.; Uppal, V.; Wali, P.D. | ||
|affiliations = Various (see the original for all affiliations) | |affiliations = Various (see the original for all affiliations) | ||
|contact = Email: eileen dot king at cchmc dot org | |contact = Email: eileen dot king at cchmc dot org | ||
| Line 39: | Line 39: | ||
==Introduction== | ==Introduction== | ||
There is growing interest in the potential for clinical registries that can simultaneously support clinical care, quality improvement (QI), and [[research]]. This multi-purpose model is consistent with the Institute of Medicine’s (IOM’s) vision of a learning health system which “draws research closer to clinical practice by building knowledge development and application into each stage of the health care delivery process.”<ref name="OlsenTheLearn07">{{cite book |title=The Learning Healthcare System: Workshop Summary |editor=Olsen, L.; Aisner, D.; McGinnis, J.M. |publisher=Institute of Medicine of the National Academies |year=2007 |isbn=9780309133937 |doi=10.17226/11903}}</ref> Gliklich ''et al.''<ref name="GliklichRegist14">{{cite book |title=Registries for Evaluating Patient Outcomes: A User's Guide |editor=Gliklich, R.E.; Dreyer, N.A.; Leavy, M.B. |edition=3rd |publisher=Agency for Healthcare Research and Quality |year=2014 |pmid=24945055}}</ref> define a registry as “an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes.” Most pediatric chronic illnesses meet the [[National Institutes of Health]]'s (NIH) definition for rare disease<ref name="GARDAbout">{{cite web |url=https://rarediseases.info.nih.gov/ |title=About GARD |work=Genetic and Rare Diseases Information Center |publisher=National Institutes of Health |accessdate=02 November 2017}}</ref>, and as such, multi-center registries are especially important to study and improve care for children with chronic diseases. Some multi-center networks are beginning to adopt principles of open science, or network-based production<ref name="BenklerIntell04">{{cite journal |title=Intellectual property: Commons-based strategies and the problems of patents |journal=Science |author=Benkler, Y. |volume=305 |issue=5687 |pages=1110–1 |year=2004 |doi=10.1126/science.1100526 |pmid=15326340}}</ref>, to foster collaborative improvement, research, data sharing, and innovation. In this setting, the registry functions not only to provide access to condition-specific [[information]] in a uniform way to support clinical care but also to support QI and research to improve patient outcomes. | |||
Revision as of 20:51, 9 December 2019
| Full article title |
Implementing a novel quality improvement-based approach to data quality monitoring and enhancement in a multipurpose clinical registry |
|---|---|
| Journal | The Journal for Electronic Health Data and Methods |
| Author(s) |
Pratt, J.; Jeffers, D.; King, E.C.; Kappelman, M.D.; Collins, J.; Margolis, P.; Bron, 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. |
| Author affiliation(s) | Various (see the original for all affiliations) |
| Primary contact | Email: eileen dot king at cchmc dot org |
| Year published | 2019 |
| Volume and issue | 7(1) |
| Page(s) | 51 |
| DOI | [1] |
| ISSN | 2327-9214 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://egems.academyhealth.org/articles/10.5334/egems.262/ |
| Download | https://egems.academyhealth.org/articles/10.5334/egems.262/galley/434/download/ (PDF) |
 |
This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
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: quality improvement, data quality, registry
Introduction
There is growing interest in the potential for clinical registries that can simultaneously support clinical care, quality improvement (QI), and research. This multi-purpose model is consistent with the Institute of Medicine’s (IOM’s) vision of a learning health system which “draws research closer to clinical practice by building knowledge development and application into each stage of the health care delivery process.”[1] Gliklich et al.[2] define a registry as “an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes.” Most pediatric chronic illnesses meet the National Institutes of Health's (NIH) definition for rare disease[3], and as such, multi-center registries are especially important to study and improve care for children with chronic diseases. Some multi-center networks are beginning to adopt principles of open science, or network-based production[4], to foster collaborative improvement, research, data sharing, and innovation. In this setting, the registry functions not only to provide access to condition-specific information in a uniform way to support clinical care but also to support QI and research to improve patient outcomes.
References
- ↑ Olsen, L.; Aisner, D.; McGinnis, J.M., ed. (2007). The Learning Healthcare System: Workshop Summary. Institute of Medicine of the National Academies. doi:10.17226/11903. ISBN 9780309133937.
- ↑ Gliklich, R.E.; Dreyer, N.A.; Leavy, M.B., ed. (2014). Registries for Evaluating Patient Outcomes: A User's Guide (3rd ed.). Agency for Healthcare Research and Quality. PMID 24945055.
- ↑ "About GARD". Genetic and Rare Diseases Information Center. National Institutes of Health. https://rarediseases.info.nih.gov/. Retrieved 02 November 2017.
- ↑ Benkler, Y. (2004). "Intellectual property: Commons-based strategies and the problems of patents". Science 305 (5687): 1110–1. doi:10.1126/science.1100526. PMID 15326340.
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. Grammar was cleaned up for smoother reading. In some cases important information was missing from the references, and that information was added.
