Your browser doesn't support javascript.
loading
Beyond Getting Rid of Stupid Stuff in the Electronic Health Record (Beyond-GROSS): Protocol for a User-Centered, Mixed-Method Intervention to Improve the Electronic Health Record System.
Otokiti, Ahmed Umar; Craven, Catherine K; Shetreat-Klein, Avniel; Cohen, Stacey; Darrow, Bruce.
Afiliación
  • Otokiti AU; Department of Medicine, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, NY, United States.
  • Craven CK; Clinical Informatics Group, Information Technology Department, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, NY, United States.
  • Shetreat-Klein A; Clinical Informatics Group, Information Technology Department, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, NY, United States.
  • Cohen S; Institute for Health Care Delivery Science, Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, NY, United States.
  • Darrow B; Clinical Informatics Group, Information Technology Department, Icahn School of Medicine at Mount Sinai, Mount Sinai Health System, New York, NY, United States.
JMIR Res Protoc ; 10(3): e25148, 2021 Mar 16.
Article en En | MEDLINE | ID: mdl-33724202
ABSTRACT

BACKGROUND:

Up to 60% of health care providers experience one or more symptoms of burnout. Perceived clinician burden resulting in burnout arises from factors such as electronic health record (EHR) usability or lack thereof, perceived loss of autonomy, and documentation burden leading to less clinical time with patients. Burnout can have detrimental effects on health care quality and contributes to increased medical errors, decreased patient satisfaction, substance use, workforce attrition, and suicide.

OBJECTIVE:

This project aims to improve the user-centered design of the EHR by obtaining direct input from clinicians about deficiencies. Fixing identified deficiencies via user-centered design has the potential to improve usability, thereby increasing satisfaction by reducing EHR-induced burnout.

METHODS:

Quantitative and qualitative data will be obtained from clinician EHR users. The input will be received through a form built in a REDCap database via a link embedded in the home page of the EHR. The REDCap data will be analyzed in 2 main dimensions, based on nature of the input, what section of the EHR is affected, and what is required to fix the issue(s). Identified issues will be escalated to relevant stakeholders responsible for rectifying the problems identified. Data analysis, project evaluation, and lessons learned from the evaluation will be incorporated in a Plan-Do-Study-Act (PDSA) manner every 4-6 weeks.

RESULTS:

The pilot phase of the study began in October 2020 in the Gastroenterology Division at Mount Sinai Hospital, New York City, NY, which includes 39 physicians and 15 nurses. The pilot is expected to run over a 4-6-month period. The results of the REDCap data analysis will be reported within 1 month of completing the pilot phase. We will analyze the nature of requests received and the impact of rectified issues on the clinician EHR user. We expect that the results will reveal which sections of the EHR have the highest deficiencies while also highlighting issues about workflow difficulties. Perceived impact of the project on provider engagement, patient safety, and workflow efficiency will also be captured by evaluation survey and other qualitative methods where possible.

CONCLUSIONS:

The project aims to improve user-centered design of the EHR by soliciting direct input from clinician EHR users. The ultimate goal is to improve efficiency, reduce EHR inefficiencies with the possibility of improving staff engagement, and lessen EHR-induced clinician burnout. Our project implementation includes using informatics expertise to achieve the desired state of a learning health system as recommended by the National Academy of Medicine as we facilitate feedback loops and rapid cycles of improvement. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) PRR1-10.2196/25148.
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: JMIR Res Protoc Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research Idioma: En Revista: JMIR Res Protoc Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos