Literature DB >> 34918098

Comparison of electronic versus manual abstraction for 2 standardized perinatal care measures.

Stephen Schmaltz1, Jocelyn Vaughn2, Tricia Elliott3.   

Abstract

OBJECTIVE: Given that electronic clinical quality measures (eCQMs) are playing a central role in quality improvement applications nationwide, a stronger evidence base demonstrating their reliability is critically needed. To assess the reliability of electronic health record-extracted data elements and measure results for the Elective Delivery and Exclusive Breast Milk Feeding measures (vs manual abstraction) among a national sample of US acute care hospitals, as well as common sources of discrepancies and change over time.
MATERIALS AND METHODS: eCQM and chart-abstracted data for the same patients were matched and compared at the data element and measure level for hospitals submitting both sources of data to The Joint Commission between 2017 and 2019. Sensitivity, specificity, and kappa statistics were used to assess reliability.
RESULTS: Although eCQM denominator reliability had moderate to substantial agreement for both measures and both improved over time (Elective Delivery: kappa = 0.59 [95% confidence interval (CI), 0.58-0.61] in 2017 and 0.84 [95% CI, 083-0.85] in 2019; Exclusive Breast Milk Feeding: kappa = 0.58 [95% CI, 0.54-0.62] in 2017 and 0.70 [95% CI, 0.67-0.73] in 2019), the numerator status reliability was poor for Elective Delivery (kappa = 0.08 [95% CI, 0.03-0.12] in 2017 and 0.10 [95% CI, 0.05-0.15] in 2019) but near perfect for Exclusive Breast Milk Feeding (kappa = 0.85 [0.83, 0.87] in 2017 and 0.84 [0.83, 0.85] in 2019). The failure of the eCQM to accurately capture estimated gestational age, conditions possibly justifying elective delivery, active labor, and medical induction were the main reasons for the discrepancies.
CONCLUSIONS: Although eCQM denominator reliability for the Elective Delivery and Exclusive Breast Milk Feeding measures had moderate agreement when compared to medical record review, the numerator status reliability was poor for Elective Delivery, but near perfect for Exclusive Breast Milk Feeding. Improvements in eCQM data capture of some key data elements would greatly improve the reliability.
© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  Elective Delivery; Exclusive Breast Milk Feeding; eCQM; perinatal care

Mesh:

Year:  2022        PMID: 34918098      PMCID: PMC9006703          DOI: 10.1093/jamia/ocab276

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  26 in total

1.  New paradigms for measuring clinical performance using electronic health records.

Authors:  Jonathan P Weiner; Jinnet B Fowles; Kitty S Chan
Journal:  Int J Qual Health Care       Date:  2012-04-06       Impact factor: 2.038

2.  The challenge of measuring quality of care from the electronic health record.

Authors:  Carol P Roth; Yee-Wei Lim; Joshua M Pevnick; Steven M Asch; Elizabeth A McGlynn
Journal:  Am J Med Qual       Date:  2009-05-29       Impact factor: 1.852

3.  The perceived impact of public reporting hospital performance data: interviews with hospital staff.

Authors:  Joanne M Hafner; Scott C Williams; Richard G Koss; Brette A Tschurtz; Stephen P Schmaltz; Jerod M Loeb
Journal:  Int J Qual Health Care       Date:  2011-08-12       Impact factor: 2.038

4.  The Reliability of Electronic Health Record Data Used for Obstetrical Research.

Authors:  Molly R Altman; Karen Colorafi; Kenn B Daratha
Journal:  Appl Clin Inform       Date:  2018-03-07       Impact factor: 2.342

Review 5.  Health information technology: transforming chronic disease management and care transitions.

Authors:  Shaline Rao; Craig Brammer; Aaron McKethan; Melinda B Buntin
Journal:  Prim Care       Date:  2012-04-24       Impact factor: 2.907

6.  Measuring implementation feasibility of clinical decision support alerts for clinical practice recommendations.

Authors:  Rachel L Richesson; Catherine J Staes; Brian J Douthit; Traci Thoureen; Daniel J Hatch; Kensaku Kawamoto; Guilherme Del Fiol
Journal:  J Am Med Inform Assoc       Date:  2020-04-01       Impact factor: 4.497

7.  Accuracy of electronically reported "meaningful use" clinical quality measures: a cross-sectional study.

Authors:  Lisa M Kern; Sameer Malhotra; Yolanda Barrón; Jill Quaresimo; Rina Dhopeshwarkar; Michelle Pichardo; Alison M Edwards; Rainu Kaushal
Journal:  Ann Intern Med       Date:  2013-01-15       Impact factor: 25.391

8.  e-Measures: insight into the challenges and opportunities of automating publicly reported quality measures.

Authors:  Terhilda Garrido; Sudheen Kumar; John Lekas; Mark Lindberg; Dhanyaja Kadiyala; Alan Whippy; Barbara Crawford; Jed Weissberg
Journal:  J Am Med Inform Assoc       Date:  2013-07-05       Impact factor: 4.497

9.  Evaluating the Reliability of EHR-Generated Clinical Outcomes Reports: A Case Study.

Authors:  Chatrian Kanger; Lisanne Brown; Snigdha Mukherjee; Haichang Xin; Mark L Diana; Anjum Khurshid
Journal:  EGEMS (Wash DC)       Date:  2014-10-23

10.  Quality of EHR data extractions for studies of preterm birth in a tertiary care center: guidelines for obtaining reliable data.

Authors:  Lindsey A Knake; Monika Ahuja; Erin L McDonald; Kelli K Ryckman; Nancy Weathers; Todd Burstain; John M Dagle; Jeffrey C Murray; Prakash Nadkarni
Journal:  BMC Pediatr       Date:  2016-04-29       Impact factor: 2.125

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