Seamless Integration of Computer-Adaptive Patient Reported Outcomes into an Electronic Health Record.

Autor:	Nolla K; Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States., Rasmussen LV; Department of Preventative Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States., Rothrock NE; Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States., Butt Z; Phreesia, Inc, Clinical Content, Wilmington, DE, USA.; Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States., Bass M; Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States., Davis K; Department of Nursing Quality, Stanford Health Care, Stanford, California, United States., Cella D; Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States., Gershon R; Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States., Barnard C; Department of General Internal Medicine, Feinberg School of Medicine, Northwestern University and Northwestern Memorial HealthCare, Chicago, Illinois, United States., Chmiel R; Department of Information Services, Northwestern Memorial HealthCare, Chicago, Illinois, United States., Almaraz F; Department of Information Services, Northwestern Memorial HealthCare, Chicago, Illinois, United States., Schachter M; Department of Information Services, Northwestern Memorial HealthCare, Chicago, Illinois, United States., Nelson T; Clinical and Translational Sciences Institute, Northwestern University, Chicago, Illinois, United States., Langer M; Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States., Starren J; Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States.; Department of Preventative Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, United States.; Clinical and Translational Sciences Institute, Northwestern University, Chicago, Illinois, United States.
Jazyk:	angličtina
Zdroj:	Applied clinical informatics [Appl Clin Inform] 2024 Jan; Vol. 15 (1), pp. 145-154. Date of Electronic Publication: 2023 Dec 28.
DOI:	10.1055/a-2235-9557
Abstrakt:	Background: Patient-reported outcome (PRO) measures have become an essential component of quality measurement, quality improvement, and capturing the voice of the patient in clinical care. In 2004, the National Institutes of Health endorsed the importance of PROs by initiating the Patient-Reported Outcomes Measurement Information System (PROMIS), which leverages computer-adaptive tests (CATs) to reduce patient burden while maintaining measurement precision. Historically, PROMIS CATs have been used in a large number of research studies outside the electronic health record (EHR), but growing demand for clinical use of PROs requires creative information technology solutions for integration into the EHR. Objectives: This paper describes the introduction of PROMIS CATs into the Epic Systems EHR at a large academic medical center using a tight integration; we describe the process of creating a secure, automatic connection between the application programming interface (API) which scores and selects CAT items and Epic. Methods: The overarching strategy was to make CATs appear indistinguishable from conventional measures to clinical users, patients, and the EHR software itself. We implemented CATs in Epic without compromising patient data security by creating custom middleware software within the organization's existing middleware framework. This software communicated between the Assessment Center API for item selection and scoring and Epic for item presentation and results. The middleware software seamlessly administered CATs alongside fixed-length, conventional PROs while maintaining the display characteristics and functions of other Epic measures, including automatic display of PROMIS scores in the patient's chart. Pilot implementation revealed differing workflows for clinicians using the software. Results: The middleware software was adopted in 27 clinics across the hospital system. In the first 2 years of hospital-wide implementation, 793 providers collected 70,446 PROs from patients using this system. Conclusion: This project demonstrated the importance of regular communication across interdisciplinary teams in the design and development of clinical software. It also demonstrated that implementation relies on buy-in from clinical partners as they integrate new tools into their existing clinical workflow. Competing Interests: The authors do not have any direct financial or personal relationships that conflict with the objectivity of this article's content. However, we wish to mention several indirect relationships. The HealthMeasures/PROMIS team which has supported K.N., N.E.R., M.B., and M.L is funded in part by Assessment Center API licensing fees. D.C. served as President of the PROMIS Health Organization in a noncompensated role. Z.B. is an employee of Phreesia, Inc. and receives equity in the company. (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)
Databáze:	MEDLINE
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