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Electronic Health Record Messaging Patterns of Health Care Professionals in Inpatient Medicine

Small, William; Iturrate, Eduardo; Austrian, Jonathan; Genes, Nicholas
PMID: 38147337
ISSN: 2574-3805
CID: 5623492

Novel Note Templates to Enhance Signal and Reduce Noise in Medical Documentation: Prospective Improvement Study

Feldman, Jonah; Goodman, Adam; Hochman, Katherine; Chakravartty, Eesha; Austrian, Jonathan; Iturrate, Eduardo; Bosworth, Brian; Saxena, Archana; Moussa, Marwa; Chenouda, Dina; Volpicelli, Frank; Adler, Nicole; Weisstuch, Joseph; Testa, Paul
Background: The introduction of electronic workflows has allowed for the flow of raw uncontextualized clinical data into medical documentation. As a result, many electronic notes have become replete of "noise" and deplete clinically significant "signals." There is an urgent need to develop and implement innovative approaches in electronic clinical documentation that improve note quality and reduce unnecessary bloating. Objective: This study aims to describe the development and impact of a novel set of templates designed to change the flow of information in medical documentation. Methods: This is a multihospital nonrandomized prospective improvement study conducted on the inpatient general internal medicine service across 3 hospital campuses at the New York University Langone Health System. A group of physician leaders representing each campus met biweekly for 6 months. The output of these meetings included (1) a conceptualization of the note bloat problem as a dysfunction in information flow, (2) a set of guiding principles for organizational documentation improvement, (3) the design and build of novel electronic templates that reduced the flow of extraneous information into provider notes by providing link outs to best practice data visualizations, and (4) a documentation improvement curriculum for inpatient medicine providers. Prior to go-live, pragmatic usability testing was performed with the new progress note template, and the overall user experience was measured using the System Usability Scale (SUS). Primary outcome measures after go-live include template utilization rate and note length in characters. Results: In usability testing among 22 medicine providers, the new progress note template averaged a usability score of 90.6 out of 100 on the SUS. A total of 77% (17/22) of providers strongly agreed that the new template was easy to use, and 64% (14/22) strongly agreed that they would like to use the template frequently. In the 3 months after template implementation, general internal medicine providers wrote 67% (51,431/76,647) of all inpatient notes with the new templates. During this period, the organization saw a 46% (2768/6191), 47% (3505/7819), and 32% (3427/11,226) reduction in note length for general medicine progress notes, consults, and history and physical notes, respectively, when compared to a baseline measurement period prior to interventions. Conclusions: A bundled intervention that included the deployment of novel templates for inpatient general medicine providers significantly reduced average note length on the clinical service. Templates designed to reduce the flow of extraneous information into provider notes performed well during usability testing, and these templates were rapidly adopted across all hospital campuses. Further research is needed to assess the impact of novel templates on note quality, provider efficiency, and patient outcomes.
SCOPUS:85154550880
ISSN: 2561-326x
CID: 5499932

Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial

Major, Vincent J; Jones, Simon A; Razavian, Narges; Bagheri, Ashley; Mendoza, Felicia; Stadelman, Jay; Horwitz, Leora I; Austrian, Jonathan; Aphinyanaphongs, Yindalon
BACKGROUND: We previously developed and validated a predictive model to help clinicians identify hospitalized adults with coronavirus disease 2019 (COVID-19) who may be ready for discharge given their low risk of adverse events. Whether this algorithm can prompt more timely discharge for stable patients in practice is unknown. OBJECTIVES/OBJECTIVE: The aim of the study is to estimate the effect of displaying risk scores on length of stay (LOS). METHODS: We integrated model output into the electronic health record (EHR) at four hospitals in one health system by displaying a green/orange/red score indicating low/moderate/high-risk in a patient list column and a larger COVID-19 summary report visible for each patient. Display of the score was pseudo-randomized 1:1 into intervention and control arms using a patient identifier passed to the model execution code. Intervention effect was assessed by comparing LOS between intervention and control groups. Adverse safety outcomes of death, hospice, and re-presentation were tested separately and as a composite indicator. We tracked adoption and sustained use through daily counts of score displays. RESULTS: Enrolling 1,010 patients from May 15, 2020 to December 7, 2020, the trial found no detectable difference in LOS. The intervention had no impact on safety indicators of death, hospice or re-presentation after discharge. The scores were displayed consistently throughout the study period but the study lacks a causally linked process measure of provider actions based on the score. Secondary analysis revealed complex dynamics in LOS temporally, by primary symptom, and hospital location. CONCLUSION/CONCLUSIONS: An AI-based COVID-19 risk score displayed passively to clinicians during routine care of hospitalized adults with COVID-19 was safe but had no detectable impact on LOS. Health technology challenges such as insufficient adoption, nonuniform use, and provider trust compounded with temporal factors of the COVID-19 pandemic may have contributed to the null result. TRIAL REGISTRATION/BACKGROUND: ClinicalTrials.gov identifier: NCT04570488.
PMCID:9329139
PMID: 35896506
ISSN: 1869-0327
CID: 5276672

Quantitative and Qualitative Evaluation of Provider Use of a Novel Machine Learning Model for Favorable Outcome Prediction

Yang, Elisabeth; Aphinyanaphongs, Yin; Punjabi, Paawan V; Austrian, Jonathan; Wiesenfeld, Batia
Predictive models may be particularly beneficial to clinicians when they face uncertainty and seek to develop a mental model of disease progression, but we know little about the post-implementation effects of predictive models on clinicians' experience of their work. Combining survey and interview methods, we found that providers using a predictive algorithm reported being significantly less uncertain and better able to anticipate, plan and prepare for patient discharge than non-users. The tool helped hospitalists form and develop confidence in their mental models of a novel disease (Covid-19). Yet providers' attention to the predictive tool declined as their confidence in their own mental models grew. Predictive algorithms that not only offer data but also provide feedback on decisions, thus supporting providers' motivation for continuous learning, hold promise for more sustained provider attention and cognition augmentation.
PMCID:10148285
PMID: 37128409
ISSN: 1942-597x
CID: 5542392

Applying A/B Testing to Clinical Decision Support: Rapid Randomized Controlled Trials

Austrian, Jonathan; Mendoza, Felicia; Szerencsy, Adam; Fenelon, Lucille; Horwitz, Leora I; Jones, Simon; Kuznetsova, Masha; Mann, Devin M
BACKGROUND:Clinical decision support (CDS) is a valuable feature of electronic health records (EHRs) designed to improve quality and safety. However, due to the complexities of system design and inconsistent results, CDS tools may inadvertently increase alert fatigue and contribute to physician burnout. A/B testing, or rapid-cycle randomized tests, is a useful method that can be applied to the EHR in order to rapidly understand and iteratively improve design choices embedded within CDS tools. OBJECTIVE:This paper describes how rapid randomized controlled trials (RCTs) embedded within EHRs can be used to quickly ascertain the superiority of potential CDS design changes to improve their usability, reduce alert fatigue, and promote quality of care. METHODS:A multistep process combining tools from user-centered design, A/B testing, and implementation science was used to understand, ideate, prototype, test, analyze, and improve each candidate CDS. CDS engagement metrics (alert views, acceptance rates) were used to evaluate which CDS version is superior. RESULTS:To demonstrate the impact of the process, 2 experiments are highlighted. First, after multiple rounds of usability testing, a revised CDS influenza alert was tested against usual care CDS in a rapid (~6 weeks) RCT. The new alert text resulted in minimal impact on reducing firings per patients per day, but this failure triggered another round of review that identified key technical improvements (ie, removal of dismissal button and firings in procedural areas) that led to a dramatic decrease in firings per patient per day (23.1 to 7.3). In the second experiment, the process was used to test 3 versions (financial, quality, regulatory) of text supporting tobacco cessation alerts as well as 3 supporting images. Based on 3 rounds of RCTs, there was no significant difference in acceptance rates based on the framing of the messages or addition of images. CONCLUSIONS:These experiments support the potential for this new process to rapidly develop, deploy, and rigorously evaluate CDS within an EHR. We also identified important considerations in applying these methods. This approach may be an important tool for improving the impact of and experience with CDS. TRIAL REGISTRATION/BACKGROUND:Flu alert trial: ClinicalTrials.gov NCT03415425; https://clinicaltrials.gov/ct2/show/NCT03415425. Tobacco alert trial: ClinicalTrials.gov NCT03714191; https://clinicaltrials.gov/ct2/show/NCT03714191.
PMID: 33835035
ISSN: 1438-8871
CID: 4840962

Supporting Acute Advance Care Planning with Precise, Timely Mortality Risk Predictions

Wang, Erwin; Major, Vincent J; Adler, Nicole; Hauck, Kevin; Austrian, Jonathan; Aphinyanaphongs, Yindalon; Horwitz, Leora I
ORIGINAL:0015307
ISSN: n/a
CID: 5000212

Giving Your Electronic Health Record a Checkup After COVID-19: A Practical Framework for Reviewing Clinical Decision Support in Light of the Telemedicine Expansion

Feldman, Jonah; Szerencsy, Adam; Mann, Devin; Austrian, Jonathan; Kothari, Ulka; Heo, Hye; Barzideh, Sam; Hickey, Maureen; Snapp, Catherine; Aminian, Rod; Jones, Lauren; Testa, Paul
BACKGROUND:The transformation of health care during COVID-19, with the rapid expansion of telemedicine visits, presents new challenges to chronic care and preventive health providers. Clinical decision support (CDS) is critically important to chronic care providers, and CDS malfunction is common during times of change. It is essential to regularly reassess an organization's ambulatory CDS program to maintain care quality. This is especially true after an immense change, like the COVID-19 telemedicine expansion. OBJECTIVE:Our objective is to reassess the ambulatory CDS program at a large academic medical center in light of telemedicine's expansion in response to the COVID-19 pandemic. METHODS:Our clinical informatics team devised a practical framework for an intrapandemic ambulatory CDS assessment focused on the impact of the telemedicine expansion. This assessment began with a quantitative analysis comparing CDS alert performance in the context of in-person and telemedicine visits. Board-certified physician informaticists then completed a formal workflow review of alerts with inferior performance in telemedicine visits. Informaticists then reported on themes and optimization opportunities through the existing CDS governance structure. RESULTS:Our assessment revealed that 10 of our top 40 alerts by volume were not firing as expected in telemedicine visits. In 3 of the top 5 alerts, providers were significantly less likely to take action in telemedicine when compared to office visits. Cumulatively, alerts in telemedicine encounters had an action taken rate of 5.3% (3257/64,938) compared to 8.3% (19,427/233,636) for office visits. Observations from a clinical informaticist workflow review included the following: (1) Telemedicine visits have different workflows than office visits. Some alerts developed for the office were not appearing at the optimal time in the telemedicine workflow. (2) Missing clinical data is a common reason for the decreased alert firing seen in telemedicine visits. (3) Remote patient monitoring and patient-reported clinical data entered through the portal could replace data collection usually completed in the office by a medical assistant or registered nurse. CONCLUSIONS:In a large academic medical center at the pandemic epicenter, an intrapandemic ambulatory CDS assessment revealed clinically significant CDS malfunctions that highlight the importance of reassessing ambulatory CDS performance after the telemedicine expansion.
PMCID:7842852
PMID: 33400683
ISSN: 2291-9694
CID: 4767802

Treating COVID-19 With Hydroxychloroquine (TEACH): A Multicenter, Double-Blind Randomized Controlled Trial in Hospitalized Patients

Ulrich, Robert J; Troxel, Andrea B; Carmody, Ellie; Eapen, Jaishvi; Bäcker, Martin; DeHovitz, Jack A; Prasad, Prithiv J; Li, Yi; Delgado, Camila; Jrada, Morris; Robbins, Gabriel A; Henderson, Brooklyn; Hrycko, Alexander; Delpachitra, Dinuli; Raabe, Vanessa; Austrian, Jonathan S; Dubrovskaya, Yanina; Mulligan, Mark J
Background/UNASSIGNED:Effective therapies to combat coronavirus 2019 (COVID-19) are urgently needed. Hydroxychloroquine (HCQ) has in vitro antiviral activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), but the clinical benefit of HCQ in treating COVID-19 is unclear. Randomized controlled trials are needed to determine the safety and efficacy of HCQ for the treatment of hospitalized patients with COVID-19. Methods/UNASSIGNED:We conducted a multicenter, double-blind randomized clinical trial of HCQ among patients hospitalized with laboratory-confirmed COVID-19. Subjects were randomized in a 1:1 ratio to HCQ or placebo for 5 days and followed for 30 days. The primary efficacy outcome was a severe disease progression composite end point (death, intensive care unit admission, mechanical ventilation, extracorporeal membrane oxygenation, and/or vasopressor use) at day 14. Results/UNASSIGNED: = .350). There were no significant differences in COVID-19 clinical scores, number of oxygen-free days, SARS-CoV-2 clearance, or adverse events between HCQ and placebo. HCQ was associated with a slight increase in mean corrected QT interval, an increased D-dimer, and a trend toward an increased length of stay. Conclusions/UNASSIGNED:In hospitalized patients with COVID-19, our data suggest that HCQ does not prevent severe outcomes or improve clinical scores. However, our conclusions are limited by a relatively small sample size, and larger randomized controlled trials or pooled analyses are needed.
PMCID:7543602
PMID: 33134417
ISSN: 2328-8957
CID: 4655862

Design and implementation of a clinical decision support tool for primary palliative Care for Emergency Medicine (PRIM-ER)

Tan, Audrey; Durbin, Mark; Chung, Frank R; Rubin, Ada L; Cuthel, Allison M; McQuilkin, Jordan A; Modrek, Aram S; Jamin, Catherine; Gavin, Nicholas; Mann, Devin; Swartz, Jordan L; Austrian, Jonathan S; Testa, Paul A; Hill, Jacob D; Grudzen, Corita R
BACKGROUND:The emergency department is a critical juncture in the trajectory of care of patients with serious, life-limiting illness. Implementation of a clinical decision support (CDS) tool automates identification of older adults who may benefit from palliative care instead of relying upon providers to identify such patients, thus improving quality of care by assisting providers with adhering to guidelines. The Primary Palliative Care for Emergency Medicine (PRIM-ER) study aims to optimize the use of the electronic health record by creating a CDS tool to identify high risk patients most likely to benefit from primary palliative care and provide point-of-care clinical recommendations. METHODS:A clinical decision support tool entitled Emergency Department Supportive Care Clinical Decision Support (Support-ED) was developed as part of an institutionally-sponsored value based medicine initiative at the Ronald O. Perelman Department of Emergency Medicine at NYU Langone Health. A multidisciplinary approach was used to develop Support-ED including: a scoping review of ED palliative care screening tools; launch of a workgroup to identify patient screening criteria and appropriate referral services; initial design and usability testing via the standard System Usability Scale questionnaire, education of the ED workforce on the Support-ED background, purpose and use, and; creation of a dashboard for monitoring and feedback. RESULTS:The scoping review identified the Palliative Care and Rapid Emergency Screening (P-CaRES) survey as a validated instrument in which to adapt and apply for the creation of the CDS tool. The multidisciplinary workshops identified two primary objectives of the CDS: to identify patients with indicators of serious life limiting illness, and to assist with referrals to services such as palliative care or social work. Additionally, the iterative design process yielded three specific patient scenarios that trigger a clinical alert to fire, including: 1) when an advance care planning document was present, 2) when a patient had a previous disposition to hospice, and 3) when historical and/or current clinical data points identify a serious life-limiting illness without an advance care planning document present. Monitoring and feedback indicated a need for several modifications to improve CDS functionality. CONCLUSIONS:CDS can be an effective tool in the implementation of primary palliative care quality improvement best practices. Health systems should thoughtfully consider tailoring their CDSs in order to adapt to their unique workflows and environments. The findings of this research can assist health systems in effectively integrating a primary palliative care CDS system seamlessly into their processes of care. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov Identifier: NCT03424109. Registered 6 February 2018, Grant Number: AT009844-01.
PMCID:6988238
PMID: 31992301
ISSN: 1472-6947
CID: 4294142

The Financial and Clinical Impact of an Electronic Health Record Integrated Pathway in Elective Colon Surgery

Austrian, Jonathan S; Volpicelli, Frank; Jones, Simon; Bernstein, Mitchell A; Padikkala, Jane; Bagheri, Ashley; Blecker, Saul
BACKGROUND: Enhanced Recovery after Surgery (ERAS) pathways have been shown to reduce length of stay, but there have been limited evaluations of novel electronic health record (EHR)-based pathways. Compliance with ERAS in real-world settings has been problematic. OBJECTIVE: This article evaluates a novel ERAS electronic pathway (E-Pathway) activity integrated with the EHR for patients undergoing elective colorectal surgery. METHODS: We performed a retrospective cohort study of surgical patients age ≥ 18 years hospitalized from March 1, 2013 to August 31, 2016. The primary cohort consisted of patients admitted for elective colon surgery. We also studied a control group of patients undergoing other elective procedures. The E-Pathway was implemented on March 2, 2015. The primary outcome was variable costs per case. Secondary outcomes were observed to expected length of stay and 30-day readmissions. RESULTS: = 0.231) decrease in monthly costs of 0.57% (95% CI 1.51 to - 0.37%) postintervention. For the 30-day readmission rates, there were no statistically significant changes in either cohort. CONCLUSION/CONCLUSIONS: Our study is the first to report on the reduced costs after implementation of a novel sophisticated E-Pathway for ERAS. E-Pathways can be a powerful vehicle to support ERAS adoption.
PMCID:7002169
PMID: 32023638
ISSN: 1869-0327
CID: 4301432