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Telemedicine via Continuous Remote Care: A Proactive, Patient-Centered Approach to Improve Clinical Outcomes.
Hallberg, Sarah; Harrison, David.
  • Hallberg S; Virta Health, West Lafayette, IN, United States.
  • Harrison D; Virta Health, Boston, MA, United States.
JMIR Diabetes ; 6(4): e23646, 2021 Nov 02.
Article in English | MEDLINE | ID: covidwho-1403377
ABSTRACT
The COVID-19 pandemic has revolutionized health care for patients and providers alike. Telemedicine has moved from the periphery of our health care system to center stage more rapidly than anyone could have envisioned. Currently, virtual care has quite effectively replicated the traditional health system's care delivery model and reimbursement structure-a patient makes an appointment, then sees a physician (except with video or phone replacing in-office visits) who makes a care plan, and the patient and physician meet again at a later timepoint to assess progress. Replicating this episodic care paradigm virtually has been invaluable for delivering care swiftly during the COVID-19 pandemic; however, we can and should do more with the connectedness and convenience that telemedicine technology enables. Continuous remote care, with a data-driven, proactive outreach to patients, represents a decisive step forward in contrast to the currently available episodic, reactive, patient-initiated care. In the context of continuous remote care, patient biometric and symptom data (patient entered and connected data) are assimilated in real time by artificial intelligence-enabled clinical platforms to bring physicians' and other health care team members' attention to those patients who need intervention, whether this is via medication adjustments, acute care management, or lifestyle coaching. In this paper, we discuss how an innovative continuous remote care approach has improved outcomes in another deadly pandemic-type 2 diabetes mellitus.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: JMIR Diabetes Year: 2021 Document Type: Article Affiliation country: 23646

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: JMIR Diabetes Year: 2021 Document Type: Article Affiliation country: 23646