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Accepted for/Published in: JMIR Research Protocols

Date Submitted: Oct 25, 2022
Open Peer Review Period: Oct 24, 2022 - Dec 19, 2022
Date Accepted: May 3, 2023
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Design and Implementation of a Digitally Enabled Care Pathway to Improve Management of Depression in a Large Health Care System: Protocol for the Implementation of a Patient Care Platform

Khatib R, McCue M, Blair C, Roy A, Franco J, Fehnert B, King J, Sarkey S, Chrones L, Martin M, Kabir C, Kemp DE

Design and Implementation of a Digitally Enabled Care Pathway to Improve Management of Depression in a Large Health Care System: Protocol for the Implementation of a Patient Care Platform

JMIR Res Protoc 2023;12:e43788

DOI: 10.2196/43788

PMID: 37351941

PMCID: 10337403

Study Design and Implementation of a Digitally Enabled Care Pathway to Improve Management of Depression in a Large Healthcare System

  • Rasha Khatib; 
  • Maggie McCue; 
  • Chris Blair; 
  • Anit Roy; 
  • John Franco; 
  • Ben Fehnert; 
  • James King; 
  • Sara Sarkey; 
  • Lambros Chrones; 
  • Michael Martin; 
  • Chris Kabir; 
  • David E. Kemp

ABSTRACT

Background:

Major depressive disorder (MDD) is a serious public health concern worldwide. A treatment approach that incorporates measurement-based care (MBC) and shared decision-making (SDM) between patients with MDD and their providers may foster patient engagement and improve clinical outcomes. While digital tools such as mobile apps show promise for expanding health interventions, these apps are rarely integrated into clinical practice.

Objective:

The primary objective of this ongoing study is to determine whether implementation of a digital tool—the Pathway Platform—in primary care improves adherence to MBC practices; here we present the study methods.

Methods:

This large-scale, real-world implementation study is based on a pilot study of an earlier iteration of a mobile app (the Pathway App) that confirmed the feasibility of its use in patients with MDD and showed a positive trend in patient engagement in the app arm. In addition, a user-centered design approach that included qualitative assessments from patients and providers was used to improve understanding of the patient journey and care team workflows. User feedback highlighted the need for enhanced features, education modules, and real-time data sharing via integration with the electronic health record (EHR). The current iteration of the Platform includes the newest version of the Pathway App, education modules for both patients and providers, and real-time patient-level data sharing with the EHR. The study takes place in primary care sites within the Advocate Aurora Health system in Illinois and includes adult patients with MDD who were recently prescribed monotherapy antidepressant medication (defined as a new start, medication switch, or dose change in the past 3 months). Clinical performance and selected patient outcomes will be compared pre- and post-implementation of the Platform.

Results:

Patient recruitment was completed in July 2022, with initial results expected in January 2023.

Conclusions:

This study will provide useful insights into real-world integration of a digital platform within a large health system. The methods presented here highlight the unique user-centric development of the Pathway Platform, which has resulted in an enhanced digital tool with the potential to foster MBC and SDM, improve patient-provider communication, and ultimately lead to optimized treatment outcomes for patients with MDD. Clinical Trial: ClinicalTrials.gov ID: NCT04891224


 Citation

Please cite as:

Khatib R, McCue M, Blair C, Roy A, Franco J, Fehnert B, King J, Sarkey S, Chrones L, Martin M, Kabir C, Kemp DE

Design and Implementation of a Digitally Enabled Care Pathway to Improve Management of Depression in a Large Health Care System: Protocol for the Implementation of a Patient Care Platform

JMIR Res Protoc 2023;12:e43788

DOI: 10.2196/43788

PMID: 37351941

PMCID: 10337403

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