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Cited by 0Telemedicine and Telehealth ImplementationMobile Health and mHealth ApplicationsNon-Invasive Vital Sign Monitoring

Clinical Efficacy and Patient Adherence Hurdles of Remote Patient Monitoring (RPM) Frameworks in Managing Hypertension and Type 2 Diabetes: A Scoping Review

Open access
Athukorala, Susith C·2026·Cureus
DOI 10.7759/cureus.113642PMC PMC13525622
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Abstract

Remote patient monitoring (RPM) frameworks represent a critical paradigm shift in chronic disease management, enabling continuous physiological tracking outside traditional clinical environments; however, large-scale clinical deployment is frequently bottlenecked by operational attrition, patient compliance barriers, and therapeutic provider inertia. This scoping review maps the global evidence regarding the technical configurations, data integration architectures, and human factor friction points that dictate the implementation efficacy of RPM platforms for hypertension and type 2 diabetes. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) consensus standards, a systematic search was executed across PubMed, Embase, and Scopus, utilizing a hybrid data extraction approach combining manual triage with a local, regular expression-driven text-mining pipeline to chart a final corpus of 400 full-text peer-reviewed source publications, yielding 701 distinct technical and operational evaluation entries. The comprehensive data charting pipeline mapped exactly 701 unique architectural and behavioral evaluation layers across the included literature. Quantitative synthesis indicated that automated upper-arm oscillometric blood pressure cuffs constituted the primary remote monitoring hardware (32.8%; n=230), while continuous glucose monitors/glucometers and wearable sensors demonstrated symmetrical distributions (11.1%; n=78 each). Ingestion architectures heavily favored automated, passive cloud-native uplinks (43.2%; n=303) over short-range active Bluetooth middleware pairing (19.4%; n=136). Implementation barrier cross-tabulation revealed that clinical workflow friction and daily routine disruption constituted the single most prevalent deployment bottleneck (27.1%; n=190). Patient-centric human factors included digital health literacy gaps (15%; n=105) and technology anxiety or alert fatigue (9.3%; n=65), while systemic provider therapeutic inertia was documented in 8.4% (n=59) of settings. Bivariate co-occurrence analysis established that operational workflow friction frequently compounded alongside digital literacy deficiencies (n=10) and clinical inertia (n=7). Ultimately, RPM deployment longevity is directly governed by technical architecture selections and the optimization of downstream clinician workflows. To minimize patient attrition and avoid technical debt, future health informatics implementations must move past isolated device deployments, prioritizing semantic interoperability via Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) standards.

AI snapshot

Written from the paper’s full text.

TL;DR

This PRISMA-ScR scoping review maps 400 full-text publications and 701 extraction records on remote patient monitoring for hypertension and type 2 diabetes, finding automated cloud uplinks and oscillometric blood pressure cuffs dominate technical configurations while workflow friction is the leading implementation barrier. It concludes RPM sustainability depends on architecture choices and clinician workflow redesign, especially HL7 FHIR interoperability and automated decision support.

Key findings

  • Across 701 charted elements, oscillometric blood pressure cuffs were the most common hardware (32.8%, n=230); continuous glucose monitors/glucometers and wearable sensors each accounted for 11.1% (n=78). Automated cloud uplinks dominated telemetry ingestion (43.2%, n=303), followed by Bluetooth app middleware (19.4%, n=136), direct cellular sync (4.1%, n=29), and manual web portal (3.7%, n=26).
  • Clinical workflow/routine disruption was the single most prevalent barrier (27.1%, n=190), followed by digital health literacy gaps (15%, n=105), technology-induced anxiety or alert fatigue (9.3%, n=65), and therapeutic/clinical inertia (8.4%, n=59).
  • Co-occurrence analysis found workflow friction intersected with digital literacy gaps (n=10) and clinical inertia (n=7). Cross-tabulation showed blood pressure cuffs had the highest absolute workflow friction (n=67) and literacy deficits (n=33); wearables had workflow friction (n=20) but low literacy barriers (n=8); glucometers/CGMs split symmetrically between workflow friction (n=13) and literacy gaps (n=13).
  • Clinical endpoints were dominated by blood pressure monitoring (55.1%, n=386), followed by glycemic control indices (25.5%, n=179) and clinical process/behavioral endpoints (7.6%, n=53).

Methods

  • PRISMA-ScR scoping review searching PubMed, Embase, and Scopus through July 2026, using a PCC framework for adults aged ≥18 years with hypertension, type 1 diabetes, or type 2 diabetes in global healthcare delivery contexts.
  • Screening identified 722 records, removed 14 duplicates, screened 708 titles/abstracts, excluded 240, sought 468 full texts, could not retrieve 68, and included 400 articles in final charting.
  • Data charting used a standardized matrix with an automated Python-driven regular expression classification framework, calibrated on a 10% pilot sample, yielding 701 distinct records across hardware modality, data synchronization model, clinical endpoints, and workflow/implementation barriers, coded as binary variables.

Limitations

  • Stated by the paper: English-language peer-reviewed database searches introduce retrieval bias by omitting non-English studies, grey literature, and conference proceedings; the dual unit of analysis (701 records from 400 articles) gives multi-component studies multiple data points and variable weighting; regex string-matching risks overlooking nuanced phrasing; no formal critical appraisal or quality assessment was performed per PRISMA-ScR; and many included studies focused on short-term feasibility in well-resourced systems, underreporting long-term attrition, technical degradation, and LMIC generalizability.
  • Evident from the text: the reported percentages and counts are based on 701 extraction elements rather than 400 studies, so they are not study-level prevalence estimates; the cross-tabulation counts are small and descriptive, with no inferential testing reported.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.7759/cureus.113642

Cites

12 of 12 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

23 of 26 cited sources checked · 2 supported · 0 flagged · accuracy not yet measured

  • Premisecitation

    Contemporary deployment failures of RPM are increasingly attributed to operational and human factors.

    “contemporary deployment failures are increasingly attributed to operational and human factors [5,6].”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [5] Micocci M, Butt O, Zhou S, El-Osta A, Buckle P, Hanna GB. Integrating remote blood pressure monitoring into NHS primary care: a human factors perspective. Front Digit Health. 2026, 8:1697787. 10.3389/fdgth.2026.1697787 source

      The Results section (‘Challenges and barriers to implementation’; page unavailable) identifies workload, digital literacy, role allocation, and system integration as barriers to remote blood-pressure monitoring in NHS primary care. It does not establish that deployments failed or that attribution to operational and human factors is increasing over time; the claim extends beyond the study’s setting. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [6] Saver BG, Marquard JL, Gummeson J, Stekler J, Scanlon JM. Buy or build: challenges developing consumer digital health interventions. Appl Clin Inform. 2023, 14:803-10. 10.1055/a-2148-8036 source

      The Discussion describes deployment barriers involving clinician workflow and EHR integration, while the structured analysis describes staff workload and vendor disruptions. These support operational challenges, but the paper does not establish that RPM deployment failures are increasingly attributed to operational and human factors; its focus is on technology and integration problems. (LLM, conf=0.78)

      Experimental — accuracy not yet measured
  • Interpretationcitation

    Smartphone middleware adds architectural dependencies that contribute to operational points of failure, such as pairing drops, OS-level application terminations, and local sync bottlenecks.

    “While smartphone middleware allows for rich local user interfaces, it adds architectural dependencies that contribute to operational points of failure, such as pairing drops, OS-level application terminations, and local sync bottlenecks [11].”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [11] Tasic N, Tasic D, Kovacevic Z, et al.. Improving blood pressure control using digital communication methods in Serbia. Diagnostics (Basel). 2022, 12:914. 10.3390/diagnostics12040914 source

      Section 4.6 (Study Limitations) says the study used manual entry, mentions Bluetooth transfer in other studies, and notes unspecified technical limits on SMS/email frequency. It does not address smartphone middleware dependencies or the claimed pairing drops, OS-level application terminations, or local synchronization bottlenecks; searches for those terms and related technical failures found no supporting passage. (LLM, conf=0.74)

      Experimental — accuracy not yet measured
  • Interpretationcitation

    When an RPM platform shifts administrative or technical burdens onto clinical teams without automated triaging, it triggers alert fatigue.

    “when an RPM platform shifts administrative or technical burdens onto clinical teams without automated triaging, it triggers alert fatigue [7].”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [7] Tobe SW, Wentworth J, Ironstand L, et al.. DreamTel; diabetes risk evaluation and management tele-monitoring study protocol. BMC Endocr Disord. 2009, 9:13. 10.1186/1472-6823-9-13 source

      The Methods and design section describes a planned system of graded alerts, and the Discussion describes remote monitoring. Neither addresses whether shifting administrative or technical work to clinical teams without automated triaging causes alert fatigue. Searches for alert fatigue, triaging, and staff workload found no passage making that connection. (LLM, conf=0.75)

      Experimental — accuracy not yet measured
  • Interpretationcitation

    The high prevalence of automated cloud and server-side uplinks reflects an industry-wide effort to minimize patient compliance burdens by removing active transmission steps.

    “The high prevalence of automated cloud and server-side uplinks reflects an industry-wide effort to minimize patient compliance burdens by removing active transmission steps [1,5].”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [1] Stephen MJ, Akhavan B, Chu MB, Batra K, Sagaribay R. The current landscape of remote patient monitoring regarding diabetes mellitus and hypoglycemia: protocol for a scoping review. JMIR Res Protoc. 2026, 15:e88197. 10.2196/88197 source

      The Methods (Inclusion and Exclusion Criteria; page unavailable) describe digital glucose-data transmission, and the Introduction (Background; page unavailable) mentions improved treatment adherence. Neither passage addresses the prevalence of automated cloud or server-side uplinks, removal of active transmission steps, or an industry-wide effort to reduce patient burden. Searches for those terms and for automatic data transmission found no supporting passage in our copy. (LLM, conf=0.75)

      Experimental — accuracy not yet measured
    • cites [5] Micocci M, Butt O, Zhou S, El-Osta A, Buckle P, Hanna GB. Integrating remote blood pressure monitoring into NHS primary care: a human factors perspective. Front Digit Health. 2026, 8:1697787. 10.3389/fdgth.2026.1697787 source

      The Results (Field study; page unavailable) discuss data-synchronisation problems between a monitoring platform and electronic health records, not the prevalence of automated cloud or server-side uplinks. Searches for automated transmission and patient submission of readings found no passage establishing an industry-wide effort to remove active transmission steps. (LLM, conf=0.76)

      Experimental — accuracy not yet measured
  • Interpretationcitation

    Providers default to therapeutic inertia, failing to titrate medications despite receiving actionable physiological data.

    “Consequently, providers default to therapeutic inertia, failing to titrate medications despite receiving actionable physiological data [7,8].”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [7] Tobe SW, Wentworth J, Ironstand L, et al.. DreamTel; diabetes risk evaluation and management tele-monitoring study protocol. BMC Endocr Disord. 2009, 9:13. 10.1186/1472-6823-9-13 source

      The Discussion (page unavailable) describes clinical inertia in poorly controlled diabetes and reports that more than 50% of patients referred to specialists had no treatment intensification within four months of a high-A1c lab report. The Methods and design section defines intensification to include increasing a medication dose. This supports failure to adjust treatment despite an actionable result, but not the broader claim that providers generally default to inertia despite receiving physiological data. (LLM, conf=0.83)

      Experimental — accuracy not yet measured
    • cites [8] Gushrowski MN, Rush MJ, Kier KL, Hinson J. Description of a pharmacist-led employee wellness hypertension program utilizing remote monitoring devices. Am J Health Syst Pharm. 2025, 82:1265-70. 10.1093/ajhp/zxaf084 source
  • May combine two claims. 15
  • Classified as probably not a substantial claim. 10

  • May combine two claims.

    Premisecitation

    Large-scale implementation of RPM across healthcare delivery organizations remains fragmented and frequently plagued by high attrition rates.

    “large-scale implementation across healthcare delivery organizations remains fragmented and frequently plagued by high attrition rates [5,6].”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [5] Micocci M, Butt O, Zhou S, El-Osta A, Buckle P, Hanna GB. Integrating remote blood pressure monitoring into NHS primary care: a human factors perspective. Front Digit Health. 2026, 8:1697787. 10.3389/fdgth.2026.1697787 source

      The Discussion (Interoperability challenges; page unavailable) describes fragmented IT systems across organisations, and the Results (Challenges and barriers to implementation; page unavailable) describe uneven adoption and patient engagement. These passages support implementation difficulties, but not a claim about large-scale RPM implementation across healthcare delivery organisations or frequent high attrition rates. (LLM, conf=0.82)

      Experimental — accuracy not yet measured
    • cites [6] Saver BG, Marquard JL, Gummeson J, Stekler J, Scanlon JM. Buy or build: challenges developing consumer digital health interventions. Appl Clin Inform. 2023, 14:803-10. 10.1055/a-2148-8036 source

      The Discussion reports that few patient-generated health data interventions successfully integrated with electronic health records, supporting the claim of implementation barriers. It does not establish that large-scale RPM implementation is fragmented across healthcare organizations or report high attrition rates. (LLM, conf=0.84)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Interpretationcitation

    Automated oscillometric blood pressure cuffs faced the highest absolute operational friction, combining significant workflow routine disruptions with digital literacy gaps.

    “Automated oscillometric blood pressure cuffs faced the highest absolute operational friction, combining significant workflow routine disruptions with digital literacy gaps [6].”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [6] Saver BG, Marquard JL, Gummeson J, Stekler J, Scanlon JM. Buy or build: challenges developing consumer digital health interventions. Appl Clin Inform. 2023, 14:803-10. 10.1055/a-2148-8036 source

      The Structured Analysis of Our “Buy or Build” Decisions (Table 1; page not specified) describes operational difficulties with the home BP cuff system, including clinic staff taking over data uploads and technical fixes when connections broke. It does not rank cuffs as having the highest absolute friction or identify digital literacy gaps as a cause of those difficulties. (LLM, conf=0.85)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    The study protocol was structured in accordance with PRISMA-ScR guidelines.

    “The study protocol was structured in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines [1].”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [1] Stephen MJ, Akhavan B, Chu MB, Batra K, Sagaribay R. The current landscape of remote patient monitoring regarding diabetes mellitus and hypoglycemia: protocol for a scoping review. JMIR Res Protoc. 2026, 15:e88197. 10.2196/88197 source

  • May combine two claims.

    Premisecitation

    Patients frequently struggle with digital health literacy gaps, technology-induced anxiety, and the logistical burden of integrating rigid measurement protocols into their daily routines.

    “patients frequently struggle with digital health literacy gaps, technology-induced anxiety, and the logistical burden of integrating rigid measurement protocols into their daily routines [9,10].”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [9] Ondiege B, Clarke M. Investigating user identification in remote patient monitoring devices. Bioengineering (Basel). 2017, 4:76. 10.3390/bioengineering4030076 source

      The Results (section 3.2) describe concerns about complex technology and a need for training, while the Discussion (section 4.1) discusses technology-related anxiety. The Discussion (section 4.2) also links missed measurements to other commitments and bulky equipment. But the Results (section 3.3) report that 90% adhered to the monitoring regimen, and section 4.1 says most participants were willing to use the technology; these findings do not support the claim that patients frequently struggle with all three barriers. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
    • cites [10] Poblete JY, Vawter NL, Lewis SV, et al.. Digitally based blood pressure self-monitoring program that promotes hypertension self-management and health education among patients with low-income: usability study. JMIR Hum Factors. 2023, 10:e46313. 10.2196/46313 source

      Table 6 (pp. 3–4) reports device-operation difficulties, busy schedules, and fear of viewing worrisome results; Principal Findings reports that only 27% met the measurement threshold and suggests it may be too stringent. These support practical barriers to monitoring, but the paper does not establish frequent technology-induced anxiety. Fear of a blood-pressure result is not the same as anxiety caused by the technology. (LLM, conf=0.85)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Interpretationcitation

    Glucometers and CGMs demonstrated a symmetrical distribution between workflow and literacy challenges, illustrating the dual burden of learning invasive or semi-invasive peripheral operation alongside data-logging routines.

    “Glucometers and CGMs demonstrated a symmetrical distribution between workflow and literacy challenges [2,4], illustrating the dual burden of learning invasive or semi-invasive peripheral operation alongside data-logging routines.”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [2] Omboni S, Ballatore T, Rizzi F, Tomassini F, Panzeri E, Campolo L. Telehealth at scale can improve chronic disease management in the community during a pandemic: an experience at the time of COVID-19. PLoS One. 2021, 16:e0258015. 10.1371/journal.pone.0258015 source

      The Materials and methods section (page not provided) lists glucometers among home devices and says patients manually entered readings in an app. The Discussion notes that manual entry may have limited app use among older patients. Neither passage reports CGMs, a symmetrical distribution of workflow and literacy challenges, or difficulties learning invasive device operation. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [4] Cai J, Xu H, Jiang S, Sung J, Sawhney R, Broadley S, Sun J. Effectiveness of telemonitoring intervention on glycaemic control in patients with type 2 diabetes mellitus: a systematic review and meta-analysis. Diabetes Res Clin Pract. 2023, 201:110727. 10.1016/j.diabres.2023.110727 source

      Section 2.6 (page unavailable) describes manual data input and education in self-measurement skills, which relate to the claimed data-logging and learning tasks. Neither that section nor the Discussion (page unavailable) reports a symmetrical distribution of workflow and literacy challenges for glucometers and CGMs, or characterizes device operation and logging as a dual burden. (LLM, conf=0.76)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation

    Clinical teams routinely experience alert fatigue, increased administrative workloads, and persistent therapeutic inertia when attempting to titrate medications based on remotely transmitted data.

    “clinical teams routinely experience alert fatigue, increased administrative workloads, and persistent therapeutic inertia (delays in escalating treatment despite recorded clinical need) when attempting to titrate medications based on remotely transmitted data [7,8].”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [7] Tobe SW, Wentworth J, Ironstand L, et al.. DreamTel; diabetes risk evaluation and management tele-monitoring study protocol. BMC Endocr Disord. 2009, 9:13. 10.1186/1472-6823-9-13 source

      The Discussion describes clinical inertia as a failure to intensify diabetes treatment despite evidence of poor control, and the Methods and design section describes adjusting medication using remotely available glucose readings. But the paper does not say that teams routinely experience alert fatigue or increased administrative workloads, or that remote-data titration itself causes persistent inertia. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [8] Gushrowski MN, Rush MJ, Kier KL, Hinson J. Description of a pharmacist-led employee wellness hypertension program utilizing remote monitoring devices. Am J Health Syst Pharm. 2025, 82:1265-70. 10.1093/ajhp/zxaf084 source

  • May combine two claims.

    Premisecitation

    The clinical value proposition of RPM systems is well-documented; systematically tracking physiological metrics allows for early detection of clinical deterioration, optimization of pharmacological regimens, and reduction of emergency department utilization.

    “The clinical value proposition of these systems is well-documented; systematically tracking physiological metrics allows for the early detection of clinical deterioration, optimization of pharmacological regimens, and reduction of emergency department utilization [2,4].”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [2] Omboni S, Ballatore T, Rizzi F, Tomassini F, Panzeri E, Campolo L. Telehealth at scale can improve chronic disease management in the community during a pandemic: an experience at the time of COVID-19. PLoS One. 2021, 16:e0258015. 10.1371/journal.pone.0258015 source

      Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

      Experimental — accuracy not yet measured
    • cites [4] Cai J, Xu H, Jiang S, Sung J, Sawhney R, Broadley S, Sun J. Effectiveness of telemonitoring intervention on glycaemic control in patients with type 2 diabetes mellitus: a systematic review and meta-analysis. Diabetes Res Clin Pract. 2023, 201:110727. 10.1016/j.diabres.2023.110727 source

      Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    The review included a final corpus of 400 full-text peer-reviewed source publications.

    “a final corpus of 400 full-text peer-reviewed source publications”
    • Also stated in: § Review · plain
      “A final pool of 400 articles met all eligibility criteria and were successfully retrieved for full-text evaluation and systematic data charting.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Wearable sensors faced substantial routine integration and workflow friction (n=20) but demonstrated minimal susceptibility to digital literacy barriers (n=8).

    “wearable sensors, faced substantial routine integration and workflow friction but demonstrated minimal susceptibility to digital literacy barriers (n=8)”
    • Also stated in: § Review · plain
      “Wearable sensors | 20 | 8 | 9 | 7”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Direct cellular network integration utilizing embedded SIM modules bypassed localized home network infrastructure in 4.1% (n=29) of configurations.

    “Direct cellular network integration utilizing embedded SIM modules (e.g., cellular-enabled standalone blood pressure cuffs) bypassed localized home network infrastructure in 4.1% (n=29) of configurations”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Legacy manual web portal entry or wired computer interfaces comprised 3.7% (n=26) of configurations.

    “legacy manual web portal entry or wired computer interfaces comprised 3.7% (n=26)”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    The data charting pipeline yielded 701 distinct technical and operational evaluation entries.

    “yielding 701 distinct technical and operational evaluation entries”
    • Also stated in: § Review · plain
      “Programmatic extraction mapping across the 400 articles generated 701 distinct contextual text records evaluating RPM infrastructure.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    The automated Python-driven regular expression classification framework carries inherent risks of overlooking nuanced phrasing or complex semantic contexts despite iterative calibration.

    “while the automated Python-driven regular expression (Regex) classification framework provided scalable data charting, programmatic string-matching carries inherent risks of overlooking nuanced phrasing or complex semantic contexts despite iterative calibration on sample subsets.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Regex patterns were engineered using domain-specific keyword dictionaries, word boundary matching, and case-insensitive string variations, followed by iterative sensitivity calibration on a 10% pilot sample to ensure extraction accuracy.

    “Regex patterns were algorithmically engineered in Python using domain-specific keyword dictionaries, word boundary matching, and case-insensitive string variations, followed by iterative sensitivity calibration on a 10% pilot sample to ensure extraction accuracy.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductreasoning

    The dual unit of analysis, synthesizing 701 contextual text records derived across 400 unique articles, means that studies describing multi-component interventions contributed multiple data points, creating variable weighting across thematic pillars.

    “the dual unit of analysis, synthesizing 701 contextual text records derived across 400 unique articles, means that studies describing multi-component interventions contributed multiple data points, creating variable weighting across thematic pillars.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Workflow routine friction frequently co-occurs with clinical inertia and digital health literacy deficits, creating a compounding negative feedback loop that leads to provider alert fatigue and compromised clinical outcomes.

    “Crucially, workflow routine friction frequently co-occurs with clinical inertia and digital health literacy deficits, creating a compounding negative feedback loop that leads to provider alert fatigue and compromised clinical outcomes.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Passive telemetry via automated cloud uplinks dominates modern infrastructure, minimizing immediate user compliance friction.

    “This scoping review, mapping the global literature and its distinct contextual records, demonstrates that passive telemetry via automated cloud uplinks dominates modern infrastructure, minimizing immediate user compliance friction.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    Textual formatting anomalies and column alignment shifts were audited and programmatically repaired to ensure cross-tabulation accuracy.

    “Textual formatting anomalies and column alignment shifts caused by unquoted internal punctuation within article metadata were audited and programmatically repaired to ensure absolute cross-tabulation accuracy.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    Two reviewers independently screened titles and abstracts against predefined eligibility criteria, followed by independent full-text evaluation, with discrepancies resolved through iterative joint consensus discussions.

    “Two reviewers independently screened titles and abstracts against predefined eligibility criteria using the PCC framework, followed by independent full-text evaluation. Any screening discrepancies were resolved through iterative joint consensus discussions.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation

    Direct cellular-enabled peripherals eliminate localized network failure points but introduce higher recurring hardware and data subscription costs, presenting a trade-off between deployment reliability and financial scalability.

    “Completely infrastructure-independent solutions, like direct cellular-enabled peripherals, eliminate these localized network failure points but introduce higher recurring hardware and data subscription costs, presenting a clear trade-off between deployment reliability and financial scalability [8].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [8] Gushrowski MN, Rush MJ, Kier KL, Hinson J. Description of a pharmacist-led employee wellness hypertension program utilizing remote monitoring devices. Am J Health Syst Pharm. 2025, 82:1265-70. 10.1093/ajhp/zxaf084 source

  • May combine two claims.

    Study design and conductreasoning

    No formal critical appraisal or quality assessment of included literature was performed, leaving risk of bias unquantified across the corpus.

    “in accordance with PRISMA-ScR guidelines for scoping reviews, a formal critical appraisal or quality assessment of the included literature was not performed, leaving risk of bias unquantified across the corpus.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Patients find consumer wearables intuitive to operate, but integrating continuous physical tracking into daily habits remains a persistent challenge.

    “This indicates that while patients find consumer wearables intuitive to operate, integrating continuous physical tracking into their daily habits, such as managing charging cycles, skin irritation, and device compliance, remains a persistent challenge.”
    Quote in the paperSubstantial claim
22 of 22

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Type 1 diabetes is both included and omitted from eligibility criteria

    Minor

    The PCC eligibility framework includes adults with type 1 diabetes, but Table 2 limits eligible target conditions to essential hypertension and type 2 diabetes.

  • Figure 2 is assigned two different contents

    Minor

    The text says Figure 2 details the search and screening outcomes, while its caption describes hardware distributions and a barrier co-occurrence matrix. The search and screening flow is instead assigned to Figure 1.

  • PRISMA-ScR guidelines citation points to a review protocol

    Minor

    The cited reference [1] is titled as a protocol for a scoping review, not as the PRISMA-ScR guidelines named in the methods.

3 of 3

Cites

Flagged first, then by citations

Cited by

Still being checked.

Authors
Athukorala, S. C.
Affiliations
Post Graduate Institute of Medicine, University of Colombo, Sri Lanka (LK)
Corresponding author
Athukorala, Susith C
ORCID
Athukorala, Susith C
Venue
Cureus
Publisher
Springer Science and Business Media LLC
Published
2026-07-30
Volume
18
Issue
7
Pages
e113642-e113642
ISSN
2168-8184 (ISSN-L)
DOI
10.7759/cureus.113642
PMC
PMC13525622
OpenAlex
W7171862623
Semantic Scholar
df2522d43f80591a1c2fe9a81a63495d6a74aee3
Cited by
0
References
12
FWCI
0.00
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Cureus (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion, cc-by)
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
Keywords
remote patient monitoring, hypertension, type 2 diabetes, patient adherence, implementation barriers, clinical workflow disruption, digital health literacy, alarm fatigue, blood pressure cuff, continuous glucose monitoring, wearable sensors, Bluetooth, FHIR interoperability, chronic disease management

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-09.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-09.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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