Evidence map›Paper›PMID 34435176›Full record

ArticleJAMIA open2021

The influence of a Sprint optimization and training intervention on time spent in the electronic health record (EHR).

Amber Sieja, Melanie D Whittington, Vanessa Paul Patterson, Katie Markley, Heather Holmstrom, Stephen Rotholz, Christine Gonzalez, Michael Scott Carpenter, Chen-Tan Lin

Abstract read
In one paragraph

Article in JAMIA open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 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

10 citing papers in PubMed, 1 synthesis or guideline 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

9 authors.

Amber SiejaDepartment of Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA.ORCID https://orcid.org/0000-0003-4541-0647
Melanie D WhittingtonNavigation Lab, Data Science to Patient Value, University of Colorado School of Medicine, Aurora, Colorado, USA.
Vanessa Paul PattersonNavigation Lab, Data Science to Patient Value, University of Colorado School of Medicine, Aurora, Colorado, USA.ORCID https://orcid.org/0000-0002-6573-9936
Katie MarkleyUniversity of Colorado Health Medical Group and University of Colorado Health, Aurora, Colorado, USA.
Heather HolmstromDepartment of Family Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA.
Stephen RotholzDepartment of Obstetrics and Gynecology, University of Colorado School of Medicine, Aurora, Colorado, USA.
Christine GonzalezUniversity of Colorado Health, Aurora, Colorado, USA.
Michael Scott CarpenterUniversity of Colorado Health, Aurora, Colorado, USA.
Chen-Tan LinDepartment of Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveWe report the influence of Sprint electronic health record (EHR) training and optimization on clinician time spent in the EHR. MATERIALS AND

methodsWe studied the Sprint process in one academic internal medicine practice with 26 providers. Program offerings included individualized training sessions, and the ability to clean up, fix, or build new EHR tools during the 2-week intervention. EHR usage log data were available for 24 clinicians, and the average clinical full-time equivalent was 0.44. We used a quasi-experimental study design with an interrupted time series specification, with 8 months of pre- and 12 months of post-intervention data to evaluate clinician time spent in the EHR.

resultsWe discovered a greater than 6 h per day reduction in clinician time spent in the EHR at the clinic level. At the individual clinician level, we demonstrated a time savings of 20 min per clinician per day among those who attended at least 2 training sessions. DISCUSSION: We can promote EHR time savings for clinicians who engage in robust EHR training and optimization programs. To date, programs have shown a positive correlation between participation and subjective EHR satisfaction, efficiency, or time saved. The impact of EHR training and optimization on objective time savings remains elusive. By measuring time in the EHR, this study contributes to an ongoing conversation about the resources and programs needed to decrease clinician EHR time.

conclusionsWe have demonstrated that Sprint is associated with time savings for clinicians for up to 6 months. We suggest that an investment in EHR optimization and training can pay dividends in clinician time saved.

Indexed as

burnoutelectronic health recordelectronic medical recordoptimizationtraining

Identifiers

PMID34435176
PMCPMC8382277

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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.