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IIR 15-452 – HSR&D Study

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IIR 15-452
Evaluating Use of Patient-Collected Audio Recorded Encounters for Provider Audit Feedback to Reduce Contextual Errors
Saul J. Weiner MD
Jesse Brown VA Medical Center, Chicago, IL
Chicago, IL
Funding Period: November 2016 - October 2019

BACKGROUND/RATIONALE:
Contextualizing care is the process of adapting care plans to patients' individual needs and circumstances. Identifying contextual errors requires listening to an audio recording of the encounter and coding the audio for specific indicators of context and clinicians' attention to them. An extensive program of research on preventing contextual errors culminated in a VISN 12 funded quality improvement initiative that is based on audit and feedback, in which audio recorded data is collected by Veterans on provider attention to care planning, analyzed and organized using Content Coding for Contextualization of Care ("4C") system and fed back to PACTs and clinicians to facilitate continuous quality improvement.

OBJECTIVE(S):
To identify the most efficient, effective, and acceptable data driven strategy for improving contextualization of care in VHA through an implementation and efficacy study of the expansion of an audit and feedback contextualization of care intervention package ("package") in VISN 12. The study assesses the efficacy of the intervention package at two levels of intensity, the effectiveness of implementation strategies, and the potential of the intervention to pay for itself by reducing unnecessary care..

METHODS:
We are employing an Effectiveness-Implementation Type 2 Hybrid design because we have two co-primary aims - optimizing implementation and evaluating the intervention's effectiveness. In addition, we seek to document the costs and cost savings of the intervention package to ascertain its budget impact. The project has added four additional sites to the two currently engaged in the package, two in VISN 12 and two outside. The rollout of the package follows a randomized stepped wedge design comparing baseline at the four new sites (no intervention) to both a standard and enhanced feedback intervention, with the latter more intensive but more costly.

FINDINGS/RESULTS:
The successful role out at all six sites, with over 2000 patient-collected audios, the generation of reports based on clinician performance data extracted from the audios, and the engagement of peer clinical champions to share the data with colleagues, demonstrates the feasibility and scalability of the program. 419 anonymous exit surveys of patients indicate comfort with participation with over 90% indicating that they agree or strongly agree that they "feel comfortable recording my visit with my doctor." Over half of participating physicians agree or strongly agree that the program has "changed how I practice," that the feedback provided "has been valuable to me," that the "potential benefits of the program are clear to me," and that I "feel comfortable having my primary care visits recorded."

IMPACT:
This study will demonstrate the feasibility and scalability of engaging patients in collecting data on the quality of their own care, and assess a quality improvement project to reduce contextual errors, ascertaining, and optimizing its potential to transform Veterans' care and to reduce overuse and misuse of medical services.

PUBLICATIONS:

Center Products

  1. Hecht MI, Hanks D, Weiner SJ. Podcast: Contextual Errors and Improving Primary Care Encounters for Homeless Veterans. 2017 Dec 14. 2 (12). Available from: https://www.hsrd.research.va.gov/news/podcasts/default.cfm.
Government Briefings

  1. Weiner SJ. Process Improvement - Outcomes of Unannounced Standardized Veteran Effort and open discussion on way forward: Briefing before the The Advisory Committee on Homeless Veterans (ACHV) Chairman, Mark Johnston, the Designated Federal Officer, Anthony Love, and other senior VA Leadership participating; 2017 May 11; Washington, DC.


DRA: Health Systems, Diabetes and Related Disorders
DRE: Treatment - Implementation
Keywords: Implementation, System Performance Measures
MeSH Terms: none