Development and evaluation of best practice advisory alert for patient eligibility in a hospital‐at‐home program: A multicenter retrospective study

Author:

Maniaci Michael J.1ORCID,Torres‐Guzman Ricardo A.2,Avila Francisco R.2,Maita Karla2,Garcia John P.2,Forte Antonio J.2,Rutledge Rachel3,Dugani Sagar B.45ORCID,Campbell Shannon M.1,Pritchard Ingrid J.1,Paulson Margaret R.6

Affiliation:

1. Division of Hospital Internal Medicine Mayo Clinic Jacksonville Florida USA

2. Division of Plastic Surgery Mayo Clinic Jacksonville Florida USA

3. Administrative Operations Mayo Clinic Jacksonville Florida USA

4. Division of Hospital Internal Medicine Mayo Clinic Rochester Minnesota USA

5. Division of Health Care Delivery Research, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery Mayo Clinic Rochester Minnesota USA

6. Division of Hospital Internal Medicine Mayo Clinic Health Systems Eau Claire Wisconsin USA

Abstract

AbstractBackgroundHospital‐at‐home (HaH) is a growing model of care that has been shown to improve patient outcomes, satisfaction, and cost‐effectiveness. However, selecting appropriate patients for HaH is challenging, often requiring burdensome manual screening by clinicians. To facilitate HaH enrollment, electronic health record (EHR) tools such as best practice advisories (BPAs) can be used to alert providers of potential HaH candidates.ObjectiveTo describe the development and implementation of a BPA for identifying HaH eligible patients in Mayo Clinic's Advanced Care at Home (ACH) program, and to evaluate the provider response and the patient characteristics that triggered the BPA.Design, Setting, and ParticipantsWe conducted a retrospective multicenter study of hospitalized patients who triggered the BPA notification for ACH eligibility between March and December 2021 at Mayo Clinic in Jacksonville, FL and Mayo Clinic Health System in Eau Claire, WI. We extracted demographic and diagnosis data from the patients as well as characteristics of the providers who received the BPA notification.InterventionThe BPA was developed based on the ACH inclusion and exclusion criteria, which were derived from clinical guidelines, literature review, and expert consensus. The BPA was integrated into the EHR and displayed a pop‐up message to the provider when a patient met the criteria for ACH eligibility. The provider could choose to refer the patient to ACH, dismiss the notification, or defer the decision.Main Outcomes and MeasuresThe main outcomes were the number and proportion of BPA notifications that resulted in a referral to ACH, and the number and proportion of referrals that were accepted by the ACH clinical team and transferred to ACH. We also analyzed the factors associated with the provider's decision to refer or not refer the patient to ACH, such as the provider's role, location, and specialty.ResultsDuring the study period, 8962 notifications were triggered for 2847 patients. Providers opted to refer 711 (11.4%) of the total notifications linked to 324 unique patients. After review by the ACH clinical team, 31 of the 324 referrals (9.6%) met clinical and social criteria and were transferred to ACH. In multivariable analysis, Wisconsin nurses, physician assistants, and in‐training personnel had lower odds of referring the patients to ACH when compared to attending physicians.

Publisher

Wiley

Subject

Assessment and Diagnosis,Care Planning,Health Policy,Fundamentals and skills,General Medicine,Leadership and Management

Reference7 articles.

1. Implementation of a virtual and in-person hybrid hospital-at-home model in two geographically separate regions utilizing a single command center: a descriptive cohort study

2. An overview of clinical decision support systems: benefits, risks, and strategies for success

3. Overall patient experience with a virtual hybrid hospital at home program

4. Science MCCoMa.Residencies and Fellowships. Mayo Clinic College of Medicine and Science. 2022. Accessed June 22 2023.https://college.mayo.edu/academics/residencies-and-fellowships/programs-a-z/

5. United States Census Bureau.Population estimates July 1 2023 (V2023). United States Census Bureau. Accessed November 3 2023.https://www.census.gov/quickfacts/fact/table/

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