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Development and implementation of a nurse-based remote patient monitoring program for ambulatory disease management.
Coffey, Jordan D; Christopherson, Laura A; Williams, Ryan D; Gathje, Shelby R; Bell, Sarah J; Pahl, Dominick F; Manka, Lukas; Blegen, R Nicole; Maniaci, Michael J; Ommen, Steve R; Haddad, Tufia C.
  • Coffey JD; Center for Digital Health, Mayo Clinic, Rochester, MN, United States.
  • Christopherson LA; Center for Digital Health, Mayo Clinic, Rochester, MN, United States.
  • Williams RD; Center for Digital Health, Mayo Clinic, Rochester, MN, United States.
  • Gathje SR; Integrity & Compliance Office, Mayo Clinic, Rochester, MN, United States.
  • Bell SJ; Research Administrative Services, Mayo Clinic, Rochester, MN, United States.
  • Pahl DF; Center for Digital Health, Mayo Clinic, Rochester, MN, United States.
  • Manka L; Department of Nursing, Mayo Clinic, Rochester, MN, United States.
  • Blegen RN; Center for Digital Health, Mayo Clinic, Rochester, MN, United States.
  • Maniaci MJ; Department of Nursing, Mayo Clinic, Rochester, MN, United States.
  • Ommen SR; Center for Digital Health, Mayo Clinic, Rochester, MN, United States.
  • Haddad TC; Center for Digital Health, Mayo Clinic, Rochester, MN, United States.
Front Digit Health ; 4: 1052408, 2022.
Article in English | MEDLINE | ID: covidwho-2198747
ABSTRACT

Introduction:

Numerous factors are intersecting in healthcare resulting in an increased focus on new tools and methods for managing care in patients' homes. Remote patient monitoring (RPM) is an option to provide care at home and maintain a connection between patients and providers to address ongoing medical issues.

Methods:

Mayo Clinic developed a nurse-led RPM program for disease and post-procedural management to improve patient experience, clinical outcomes, and reduce health care utilization by more directly engaging patients in their health care. Enrolled patients are sent a technology package that includes a digital tablet and peripheral devices for the collection of symptoms and vital signs. The data are transmitted from to a hub integrated within the electronic health record. Care team members coordinate patient needs, respond to vital sign alerts, and utilize the data to inform and provide individualized patient assessment, patient education, medication management, goal setting, and clinical care planning.

Results:

Since its inception, the RPM program has supported nearly 22,000 patients across 17 programs. Patients who engaged in the COVID-19 RPM program experienced a significantly lower rate of 30-day, all-cause hospitalization (13.7% vs. 18.0%, P = 0.01), prolonged hospitalization >7 days (3.5% vs. 6.7%, P = 0.001), intensive care unit (ICU) admission (2.3% vs. 4.2%, P = 0.01), and mortality (0.5% vs. 1.7%, P = 0.01) when compared with those enrolled and unengaged with the technology. Patients with chronic conditions who were monitored with RPM upon hospital discharge were significantly less likely to experience 30-day readmissions (18.2% vs. 23.7%, P = 0.03) compared with those unmonitored. Ninety-five percent of patients strongly agreed or agreed they were likely to recommend RPM to a friend or family member.

Conclusions:

The Mayo Clinic RPM program has generated positive clinical outcomes and is satisfying for patients. As technology advances, there are greater opportunities to enhance this clinical care model and it should be extended and expanded to support patients across a broader spectrum of needs. This report can serve as a framework for health care organizations to implement and enhance their RPM programs in addition to identifying areas for further evolution and exploration in developing RPM programs of the future.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Front Digit Health Year: 2022 Document Type: Article Affiliation country: Fdgth.2022.1052408

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Front Digit Health Year: 2022 Document Type: Article Affiliation country: Fdgth.2022.1052408