Translating 10 Lessons From Lean Six Sigma Project in Paper-Based Training Site to Electronic Health Record–Based Primary Care Practice

Unintended omission of warfarin, an anticoagulant used to prevent and treat thromboembolic events, can lead to serious medical complications. These complications include increased medical costs, hospitalisations and significant patient harm, including increased risk of thrombosis and mortality. Chart review of discharged patients at our institution revealed an average of one patient/month with warfarin omitted from the discharge plan despite intention to continue therapy. Lean Six Sigma methodology was used to improve the process. A system alert was implemented in the electronic health record to alert providers of patients who received warfarin during admission, the discharge medication reconciliation was complete, and there was no prescription for warfarin. Date and time of last warfarin dose and international normalised ratio were included in the alert. Providers had the option to return to the chart to update the discharge medication plan and add the warfarin prescription or to choose an appropriate over-ride reason. The number of patients discharged without an intended warfarin prescription following alert implementation was reduced from 10.5% (4/38) to 0% (0/40) (two proportion test, p=0.03). Alert tracking enhanced the ability to identify patients at risk for warfarin omissions. Process sustainability has been achieved by embedding system alerts in the electronic health record to trigger process steps.

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Designing and implementing an electronic health record system in primary care practice in sub-Saharan Africa: a case study from Cameroon

Journal of Innovation in Health Informatics ◽

10.14236/jhi.v13i3.595 ◽

2005 ◽

Vol 13 (3) ◽

pp. 179-186 ◽

Cited By ~ 5

Author(s):

Raoul Kamadjeu ◽

Euloge Tapang ◽

Roland Moluh

Keyword(s):

Primary Care ◽

Electronic Health Record ◽

Primary Care Practice ◽

Electronic Health Record System ◽

Sub Saharan Africa ◽

Care Practice ◽

Health Record ◽

Record System ◽

Sub Saharan

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Physician Burnout and Timing of Electronic Health Record Use

ACI Open ◽

10.1055/s-0039-3401815 ◽

2020 ◽

Vol 04 (01) ◽

pp. e1-e8 ◽

Cited By ~ 3

Author(s):

Mark A. Micek ◽

Brian Arndt ◽

Wen-Jan Tuan ◽

Elizabeth Trowbridge ◽

Shannon M. Dean ◽

...

Keyword(s):

Internal Medicine ◽

Primary Care ◽

Electronic Health Record ◽

Work Hours ◽

Care Practice ◽

Health Record ◽

Physician Burnout ◽

After Hours ◽

Electronic Health ◽

The Relationship

Abstract Background Rates of burnout among physicians have been high in recent years. The electronic health record (EHR) is implicated as a major cause of burnout. Objective This article aimed to determine the association between physician burnout and timing of EHR use in an academic internal medicine primary care practice. Methods We conducted an observational cohort study using cross-sectional and retrospective data. Participants included primary care physicians in an academic outpatient general internal medicine practice. Burnout was measured with a single-item question via self-reported survey. EHR time was measured using retrospective automated data routinely captured within the institution's EHR. EHR time was separated into four categories: weekday work-hours in-clinic time, weekday work-hours out-of-clinic time, weekday afterhours time, and weekend/holiday after-hours time. Ordinal regression was used to determine the relationship between burnout and EHR time categories. Results EHR use during in-clinic sessions was related to burnout in both bivariate (odds ratio [OR] = 1.04, 95% confidence interval [CI]: 1.01, 1.06; p = 0.007) and adjusted (OR = 1.07, 95% CI: 1.03, 1.1; p = 0.001) analyses. No significant relationships were found between burnout and after-hours EHR use. Conclusion In this small single-institution study, physician burnout was associated with higher levels of in-clinic EHR use but not after-hours EHR use. Improved understanding of the variability of in-clinic EHR use, and the EHR tasks that are particularly burdensome to physicians, could help lead to interventions that better integrate EHR demands with clinical care and potentially reduce burnout. Further studies including more participants from diverse clinical settings are needed to further understand the relationship between burnout and after-hours EHR use.

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Use of certain electronic health record features is associated with improved primary care quality measures

PsycEXTRA Dataset ◽

10.1037/e667672010-010 ◽

2010 ◽

Keyword(s):

Primary Care ◽

Electronic Health Record ◽

Quality Measures ◽

Care Quality ◽

Health Record ◽

Primary Care Quality ◽

Electronic Health

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Approaches for combining primary care electronic health record data from multiple sources: a systematic review of observational studies

BMJ Open ◽

10.1136/bmjopen-2020-037405 ◽

2020 ◽

Vol 10 (10) ◽

pp. e037405

Author(s):

Daniel Dedman ◽

Melissa Cabecinha ◽

Rachael Williams ◽

Stephen J W Evans ◽

Krishnan Bhaskaran ◽

...

Keyword(s):

Systematic Review ◽

Primary Care ◽

Electronic Health Record ◽

Observational Studies ◽

Meta Analysis ◽

Data Sources ◽

Health Record ◽

Two Stage ◽

One Stage ◽

Electronic Health

ObjectiveTo identify observational studies which used data from more than one primary care electronic health record (EHR) database, and summarise key characteristics including: objective and rationale for using multiple data sources; methods used to manage, analyse and (where applicable) combine data; and approaches used to assess and report heterogeneity between data sources.DesignA systematic review of published studies.Data sourcesPubmed and Embase databases were searched using list of named primary care EHR databases; supplementary hand searches of reference list of studies were retained after initial screening.Study selectionObservational studies published between January 2000 and May 2018 were selected, which included at least two different primary care EHR databases.Results6054 studies were identified from database and hand searches, and 109 were included in the final review, the majority published between 2014 and 2018. Included studies used 38 different primary care EHR data sources. Forty-seven studies (44%) were descriptive or methodological. Of 62 analytical studies, 22 (36%) presented separate results from each database, with no attempt to combine them; 29 (48%) combined individual patient data in a one-stage meta-analysis and 21 (34%) combined estimates from each database using two-stage meta-analysis. Discussion and exploration of heterogeneity was inconsistent across studies.ConclusionsComparing patterns and trends in different populations, or in different primary care EHR databases from the same populations, is important and a common objective for multi-database studies. When combining results from several databases using meta-analysis, provision of separate results from each database is helpful for interpretation. We found that these were often missing, particularly for studies using one-stage approaches, which also often lacked details of any statistical adjustment for heterogeneity and/or clustering. For two-stage meta-analysis, a clear rationale should be provided for choice of fixed effect and/or random effects or other models.

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