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Building digital innovation capacity at a large academic medical center.

ABSTRACT: Academic medical centers (AMCs) today prioritize digital innovation. In efforts to develop and disseminate the best technology for their institutions, challenges arise in organizational structure, cross-disciplinary collaboration, and creative and agile problem solving that are essential for successful implementation. To address these challenges, the Digital DesignLab was created at NYU Langone Health to provide structured processes for assessing and supporting the capacity for innovative digital development in our research and clinical community. Digital DesignLab is an enterprise level, multidisciplinary, digital development team that guides faculty and student innovators through a digital development "pipeline", which consists of intake, discovery, bootcamp, development. It also provides a framework for digital health innovation and dissemination at the institution. This paper describes the Digital DesignLab's creation and processes, and highlights key lessons learned to support digital health innovation at AMCs.

SUBMITTER: Mann DM

PROVIDER: S-EPMC6550180 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Building digital innovation capacity at a large academic medical center.

Mann Devin M DM Chokshi Sara Kuppin SK Lebwohl Rachel R Mainiero Michael M Dinh-Le Catherine C Driscoll Katherine K Robinson Steven S Egger Helen H

NPJ digital medicine 20190307

Academic medical centers (AMCs) today prioritize digital innovation. In efforts to develop and disseminate the best technology for their institutions, challenges arise in organizational structure, cross-disciplinary collaboration, and creative and agile problem solving that are essential for successful implementation. To address these challenges, the Digital DesignLab was created at NYU Langone Health to provide structured processes for assessing and supporting the capacity for innovative digita ...[more]

PMID: 31304362

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Project description:ImportanceSome patients are avoiding essential care for fear of contracting coronavirus disease 2019 (COVID-19) in hospitals. There are few data, however, on the risk of acquiring COVID-19 in US hospitals.ObjectiveTo assess the incidence of COVID-19 among patients hospitalized at a large US academic medical center in the 12 weeks after the first inpatient case was identified.Design, setting, and participantsThis cohort study included all patients admitted to Brigham and Women's Hospital (Boston, Massachusetts) between March 7 and May 30, 2020. Follow-up occurred through June 17, 2020. Medical records for all patients who first tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by reverse-transcription polymerase chain reaction (RT-PCR) on hospital day 3 or later or within 14 days of discharge were reviewed.ExposuresA comprehensive infection control program was implemented that included dedicated COVID-19 units with airborne infection isolation rooms, personal protective equipment in accordance with US Centers for Disease Control and Prevention recommendations, personal protective equipment donning and doffing monitors, universal masking, restriction of visitors, and liberal RT-PCR testing of symptomatic and asymptomatic patients.Main outcomes and measuresWhether infection was community or hospital acquired based on timing of tests, clinical course, and exposures.ResultsOver the 12-week period, 9149 patients (mean [SD] age, 46.1 [26.4] years; median [IQR] age, 51 years [30-67 years]; 5243 female [57.3%]) were admitted to the hospital, for whom 7394 SARS-CoV-2 RT-PCR tests were performed; 697 COVID-19 cases were confirmed, translating into 8656 days of COVID-19-related care. Twelve of the 697 hospitalized patients with COVID-19 (1.7%) first tested positive on hospital day 3 or later (median, 4 days; range, 3-15 days). Of these, only 1 case was deemed to be hospital acquired, most likely from a presymptomatic spouse who was visiting daily and diagnosed with COVID-19 before visitor restrictions and masking were implemented. Among 8370 patients with non-COVID-19-related hospitalizations discharged through June 17, 11 (0.1%) tested positive within 14 days (median time to diagnosis, 6 days; range, 1-14 days). Only 1 case was deemed likely to be hospital acquired, albeit with no known exposures.Conclusions and relevanceIn this cohort study of patients in a large academic medical center with rigorous infection control measures, nosocomial COVID-19 was rare during the height of the pandemic in the region. These findings may inform practices in other institutions and provide reassurance to patients concerned about contracting COVID-19 in hospitals.

Project description:BACKGROUND:The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey is the first publicly reported nationwide survey to evaluate and compare hospitals. Increasing patient satisfaction is an important goal as it aims to achieve a more effective and efficient healthcare delivery system. In this study, we develop and apply an integrative, data-driven approach to identify clinical risk factors that associate with patient satisfaction outcomes. METHODS:We included 1,771 unique adult patients who completed the HCAHPS survey and were discharged from the inpatient Medicine service from 2010 to 2012. We collected 266 clinical features including patient demographics, lab measurements, medications, disease categories, and procedures. We developed and applied a data-driven approach to identify risk factors that associate with patient satisfaction outcomes. FINDINGS:We identify 102 significant risk factors associating with 18 surveyed questions. The most significantly recurrent clinical risk factors were: self-evaluation of health, education level, Asian, White, treatment in BMT oncology division, being prescribed a new medication. Patients who were prescribed pregabalin were less satisfied particularly in relation to communication with nurses and pain management. Explanation of medication usage was associated with communication with nurses (q = 0.001); however, explanation of medication side effects was associated with communication with doctors (q = 0.003). Overall hospital rating was associated with hospital environment, communication with doctors, and communication about medicines. However, patient likelihood to recommend hospital was associated with hospital environment, communication about medicines, pain management, and communication with nurse. CONCLUSIONS:Our study identified a number of putatively novel clinical risk factors for patient satisfaction that suggest new opportunities to better understand and manage patient satisfaction. Hospitals can use a data-driven approach to identify clinical risk factors for poor patient satisfaction to support development of specific interventions to improve patients' experience of care.

Dataset Information

Building digital innovation capacity at a large academic medical center.

Publications

Building digital innovation capacity at a large academic medical center.

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