The Unfinished Ecosystem: Why Remote Patient Monitoring Has Matured Unevenly, and What Closing the Gap Will Require.

Publication date: Jun 14, 2026

Remote patient monitoring (RPM) is widely framed as a foundational technology for the next generation of chronic-disease care. Specific applications-pacemaker follow-up, hypertension cohorts, structured heart-failure programmes, post-surgical biosensor protocols, and virtual wards-now generate measurable clinical and economic value. Yet a decade of evaluations and implementation studies suggests that the surrounding ecosystem has matured unevenly: working applications coexist with persistent cross-cutting fragility. In this Perspective we argue that four structural gaps continue to constrain RPM’s promise at scale: (i) economic models that do not credibly compensate the asynchronous clinical work that RPM generates; (ii) ambiguous frameworks for professional liability and accountability for continuous data streams, intensified by artificial-intelligence (AI)-mediated decision support; (iii) privacy, equity, and benefit-sharing arrangements that do not yet make patients unambiguous net beneficiaries-a gap visible across very different health systems internationally; and (iv) engagement and adherence dynamics that determine whether programmes deliver value at all, but are still treated as secondary outcomes. The COVID-19 emergency briefly suspended much of the friction in this ecosystem and produced a useful natural experiment: what scaled rapidly under emergency conditions, and what subsequently atrophied, illuminates which gaps are technical, which are economic, and which are institutional. We close with a six-point research and policy agenda intended to move RPM from localised successes to a trustworthy, generalisable standard of care.

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Concepts Keywords
Basel adherence
Decade chronic-disease management
Economic COVID-19
Privacy data privacy
Surgical digital health
federated learning
health equity
patient engagement
professional liability
reimbursement
remote patient monitoring
telemedicine
virtual ward

Semantics

Type Source Name
disease MESH hypertension
disease MESH COVID-19
disease MESH emergency
drug DRUGBANK Coenzyme M
disease MESH chronic disease
disease MESH heart failure
drug DRUGBANK Trestolone
disease MESH eco
disease MESH included
disease MESH ers
drug DRUGBANK Etoperidone
disease MESH fac
disease MESH infection
disease MESH ics
drug DRUGBANK Nonoxynol-9
disease MESH asthma
pathway KEGG Asthma
disease MESH cystic fibrosis
disease MESH mul
disease MESH Critically Ill
drug DRUGBANK Troleandomycin
drug DRUGBANK (S)-Des-Me-Ampa
disease MESH Cas
disease MESH Park
disease MESH Diabetes Mellitus
disease MESH Hypoglycemia
disease MESH Mild Cognitive Impairment
disease MESH Parkinson’s Disease
disease MESH injury

Original Article

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