Improving Value by Reducing Unnecessary Telemetry and Urinary Catheter Utilization in Hospitalized Patients

Wray, Charlie M; Fahrenbach, John; Bassi, Nikhil; Bhattacharjee, Poushali; Modes, Matthew E.; Howell, Michael D.; Arora, Vineet M.

doi:10.1016/j.amjmed.2017.04.030

Cited by 9 publications

(5 citation statements)

References 14 publications

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“…An earlier narrative review of EHRs identified multivariate modeling as the most common method for targeting confounding and selection bias [17]. Epic's built-in applications and features, CDS tools, and predictive analytic algorithms can guide clinical management and provide a wide variety of opportunities for data analysis and reporting [114,155,159,260,261]. In this review, the most used analytical methods were descriptive statistics, closely followed by multivariable regression modeling, developing algorithms, and other machine learning methods.…”

Section: Current State and Opportunitiesmentioning

confidence: 99%

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Use of Epic Electronic Health Record System for Health Care Research: Scoping Review

Chishtie,

Sapiro,

Wiebe

et al. 2023

J Med Internet Res

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Background Electronic health records (EHRs) enable health data exchange across interconnected systems from varied settings. Epic is among the 5 leading EHR providers and is the most adopted EHR system across the globe. Despite its global reach, there is a gap in the literature detailing how EHR systems such as Epic have been used for health care research. Objective The objective of this scoping review is to synthesize the available literature on use cases of the Epic EHR for research in various areas of clinical and health sciences. Methods We used established scoping review methods and searched 9 major information repositories, including databases and gray literature sources. To categorize the research data, we developed detailed criteria for 5 major research domains to present the results. Results We present a comprehensive picture of the method types in 5 research domains. A total of 4669 articles were screened by 2 independent reviewers at each stage, while 206 articles were abstracted. Most studies were from the United States, with a sharp increase in volume from the year 2015 onwards. Most articles focused on clinical care, health services research and clinical decision support. Among research designs, most studies used longitudinal designs, followed by interventional studies implemented at single sites in adult populations. Important facilitators and barriers to the use of Epic and EHRs in general were identified. Important lessons to the use of Epic and other EHRs for research purposes were also synthesized. Conclusions The Epic EHR provides a wide variety of functions that are helpful toward research in several domains, including clinical and population health, quality improvement, and the development of clinical decision support tools. As Epic is reported to be the most globally adopted EHR, researchers can take advantage of its various system features, including pooled data, integration of modules and developing decision support tools. Such research opportunities afforded by the system can contribute to improving quality of care, building health system efficiencies, and conducting population-level studies. Although this review is limited to the Epic EHR system, the larger lessons are generalizable to other EHRs.

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Section: Current State and Opportunitiesmentioning

confidence: 99%

“…Epic allows for the development, implementation, and validation of CDS tools to improve quality of care [55,66,260,263]. In addition, in-system evaluation is possible within the EHR [59].…”

Section: Current State and Opportunitiesmentioning

confidence: 99%

Use of Epic Electronic Health Record System for Health Care Research: Scoping Review

Chishtie,

Sapiro,

Wiebe

et al. 2023

J Med Internet Res

View full text Add to dashboard Cite

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“…Wray et al performed a prospective study aimed at reducing overall telemetry and urinary catheter use through use of a “silent” EHR indicator that allowed clinicians to perform rapid assessment of need. The silent EHR indicator was a column integrated in the patient list, which signaled the presence of an active telemetry or urinary catheter order.…”

Section: Interventions For Reduction Of Inappropriate Telemetry Usementioning

confidence: 99%

“…Such initiatives should include all members of the health care team because multidisciplinary collaboration can increase the success rate of intervention(s) . It is important to note that education, without active or automated action toward discontinuation, did not yield significant reduction in telemetry use or improve appropriateness—and as such is a weak intervention when performed alone. Education should therefore be coupled with other interventions to improve sustained change and adherence to consensus recommendations.…”

Section: Implementation Blueprintmentioning

confidence: 99%

Eliminating Inappropriate Telemetry Monitoring

et al. 2018

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“…1 Previous studies to reduce telemetry have focused on multifaceted interventions, including education, incentives, feedback, and electronic health record (EHR) interventions. 1,[11][12][13][14][15][16] Other models used EHR interventions alone, including the use of best practice advisories (BPAs) to alert providers to discontinue telemetry. 17,18 While effective, these were single-center studies in academic settings.…”

Section: Introductionmentioning

confidence: 99%

Tell‐a provider about tele: Reducing overuse of telemetry across 10 hospitals in a safety net system

Krouss

Israilov

Alaiev

et al. 2022

Journal of Hospital Medicine

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Background: Telemetry is often a scarce resource at hospitals and is important for arrhythmia and myocardial ischemia detection. Overuse of telemetry monitoring leads to alarm fatigue resulting in failure to respond to arrhythmias, patient harm, and possible unnecessary testing.Methods: This quality improvement initiative was implemented across NYC Health and Hospitals, an 11-hospital urban safety net system. The electronic health record intervention involved the addition of a mandatory indication in the telemetry order and a best practice advisory (BPA) that would fire after the recommended time period for reassessment had passed. Results:The average telemetry hours per patient encounter went from 60.1 preintervention to 48.4 postintervention, a 19.5% reduction (p < .001). When stratified by the 11 hospitals, decreases ranged from 9% to 30%. The BPA had a 53% accept rate and fired 52,682 times, with 27,938 "discontinue telemetry" orders placed. The true accept rate was 50.4%, as there was a 2.6% 24-h reorder rate.There was variation based on clinician specialty and clinician type (attending, fellow, resident, physician associate, nurse practitioner). Conclusion:We successfully reduced telemetry monitoring across a multisite safety net system using solely an electronic health record (EHR) intervention. This expands on previous telemetry monitoring reduction initiatives using EHR interventions at single academic sites. Further study is needed to investigate variation across clinician type, specialty, and post-acute sites.

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Improving Value by Reducing Unnecessary Telemetry and Urinary Catheter Utilization in Hospitalized Patients

Cited by 9 publications

References 14 publications

Use of Epic Electronic Health Record System for Health Care Research: Scoping Review

Use of Epic Electronic Health Record System for Health Care Research: Scoping Review

Eliminating Inappropriate Telemetry Monitoring

Tell‐a provider about tele: Reducing overuse of telemetry across 10 hospitals in a safety net system

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