Evidence map›Paper›PMID 36070801›Full record

ArticleApplied clinical informatics2022

Improving the Quality of Electronic Medical Record Documentation: Development of a Compliance and Quality Program.

Rebecca M Jedwab, Michael Franco, Denise Owen, Anna Ingram, Bernice Redley, Naomi Dobroff

Abstract read
In one paragraph

Article in Applied clinical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Rebecca M JedwabDepartment of Nursing and Midwifery Informatics, Monash Health, Melbourne, Victoria, Australia.
Michael FrancoDepartment of EMR and Informatics, Monash Health, Melbourne, Victoria, Australia.
Denise OwenDepartment of Digital Health Training and Adoption, Monash Health, Melbourne, Victoria, Australia.
Anna IngramDepartment of Medical Informatics, Monash Health, Melbourne, Victoria, Australia.
Bernice RedleySchool of Nursing and Midwifery, Centre for Quality and Patient Safety Research-Monash Health Partnership, Institute for Health Transformation, Deakin University, Melbourne, Victoria, Australia.
Naomi DobroffDepartment of EMR and Informatics, Monash Health, Melbourne, Victoria, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIntroducing an electronic medical record (EMR) system into a complex health care environment fundamentally changes clinical workflows and documentation processes and, hence, has implications for patient safety. After a multisite "big-bang" EMR implementation across our large public health care organization, a quality improvement program was developed and implemented to monitor clinician adoption, documentation quality, and compliance with workflows to support high-quality patient care.

objectiveOur objective was to report the development of an iterative quality improvement program for nursing, midwifery, and medical EMR documentation.

methodsThe Model for Improvement quality improvement framework guided cycles of "Plan, Do, Study, Act." Steps included design, pre- and pilot testing of an audit tool to reflect expected practices for EMR documentation that examined quality and completeness of documentation 1-year post-EMR implementation. Analysis of initial audit results was then performed to (1) provide a baseline to benchmark comparison of ongoing improvement and (2) develop targeted intervention activities to address identified gaps.

resultsAnalysis of 1,349 EMR record audits as a baseline for the first cycle of EMR quality improvement revealed five out of nine nursing and midwifery documentation components, and four out of ten medical documentation components' completion and quality were classified as good (>80%). Outputs from this work also included a framework for strategies to improve EMR documentation quality, as well as an EMR data dashboard to monitor compliance.

conclusionThis work provides the foundation for the development of quality monitoring frameworks to inform both clinician and EMR optimization interventions using audits and feedback. Discipline-specific differences in performance can inform targeted interventions to maximize the effective use of resources and support longitudinal monitoring of EMR documentation and workflows. Future work will include repeat EMR auditing.

Indexed as

DocumentationElectronic Health RecordsHumansPatient SafetyQuality ImprovementQuality of Health Care

Identifiers

PMID36070801
PMCPMC9451950

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.