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203 Implementing a hospital-based referral system to connect heart failure patients with payer disease management: approaches and lessons from a pilot study

Published online by Cambridge University Press:  19 April 2022

Mark E. Patterson
Affiliation:
University of Missouri-Kansas City (UMKC) School of Pharmacy; UMKC Health Institute for Innovation and Quality (HI-IQ)
Paul Chan
Affiliation:
University of Missouri-Kansas City (UMKC) School of Pharmacy; UMKC Health Institute for Innovation and Quality (HI-IQ)
Susan Melton
Affiliation:
University of Missouri-Kansas City (UMKC) School of Pharmacy; UMKC Health Institute for Innovation and Quality (HI-IQ)
Tracie Breeding
Affiliation:
University of Missouri-Kansas City (UMKC) School of Pharmacy; UMKC Health Institute for Innovation and Quality (HI-IQ)
Stacy Farr
Affiliation:
University of Missouri-Kansas City (UMKC) School of Pharmacy; UMKC Health Institute for Innovation and Quality (HI-IQ)
John Spertus
Affiliation:
University of Missouri-Kansas City (UMKC) School of Pharmacy; UMKC Health Institute for Innovation and Quality (HI-IQ)
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Abstract

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OBJECTIVES/GOALS: Commercial health insurance payers invest in disease management programs (DM) to coordinate care for complex patients. To overcome gaps in connecting patients hospitalized with heart failure to DM, we implemented a novel warm handoff referral between hospital providers and payer DM using the Implementation Research Logic Model (IRLM). METHODS/STUDY POPULATION: A research and quality improvement team collaborated with champions from one hospital and three payers to build and pilot an inpatient-based referral for hospitalized patients with heart failure who were beneficiaries of one of three payers. The standard process of payers initiating contact with patients by phone was restructured to enable inpatient teams to initiate referrals by screening eligible patients prior to discharge. Between August 2020 and October 2021, 285 patients were hospitalized and eligible for screening. Patient registries were built to track patient referral, eligibility, and enrollment status. Monthly stakeholder meetings were used to collect referral rates and review barriers and facilitators related to implementation. RESULTS/ANTICIPATED RESULTS: Of the 63.6% (N=168) patients screened, 31.4% (N=83) were referred, 17.4% (N=46) declined referral, and 14.8% (N=39) were deemed ineligible by payers. Inpatient screenings were challenged by variability across five units with incomplete/missed referrals, primarily attributed to COVID-19-related staff shortages. Payers were challenged by delayed/incomplete referrals and varying access to the hospitals EHRs. Building patient registries helped inpatient champions track eligibility and referral status, and centralizing screening to one champion improved screening rates and reduced incomplete referrals. Additional challenges being addressed include clarifying each payers unique eligibility requirements, refining payers review of referral emails, and creating descriptions of DM for patients. DISCUSSION/SIGNIFICANCE: Implementing inpatient-based DM referrals requires patient and staff engagement, real-time data sharing, and iterative process improvement. Referrals using robust health IT systems could improve patient engagement by connecting payers, providers, and patients; and improve evaluation efforts with real-time process and outcome data.

Type
Education
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2022. The Association for Clinical and Translational Science