Evidence map›Paper›PMID 39443848›Full record

Observational studyBMC primary care2024

Redesigning telemedicine: preliminary findings from an innovative assisted telemedicine healthcare model.

Arun Pulikkottil Jose, Aprajita Kaushik, Huibert Tange, Trudy van der Weijden, Nikki Pandey, Anshika Sharma, Ruksar Sheikh, Nazneen Ali, Savitesh Kushwaha, Dimple Kondal and 2 more

Abstract readObservational Study
In one paragraph

Observational study in BMC primary care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
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  3. Review
  4. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Arun Pulikkottil JoseBRIDGE Centre for Digital Health, Centre for Chronic Disease Control, New Delhi, India. arunp.jose@ccdcindia.org.
Aprajita KaushikSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Huibert TangeDepartment of Family Medicine, Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands.
Trudy van der WeijdenDepartment of Family Medicine, Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands.
Nikki PandeyBRIDGE Centre for Digital Health, Centre for Chronic Disease Control, New Delhi, India.
Anshika SharmaBRIDGE Centre for Digital Health, Centre for Chronic Disease Control, New Delhi, India.
Ruksar SheikhBRIDGE Centre for Digital Health, Centre for Chronic Disease Control, New Delhi, India.
Nazneen AliUniversity of Cambridge, Cambridge, UK.
Savitesh KushwahaPublic Health Foundation of India, New Delhi, India.
Dimple KondalCentre for Chronic Disease Control, New Delhi, India.
Abhishek ChaturvediCentre for Chronic Disease Control, New Delhi, India.
Dorairaj PrabhakaranCentre for Chronic Disease Control, New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTelemedicine holds immense potential to revolutionise healthcare delivery, particularly in resource-limited settings and for patients with chronic diseases. Despite proven benefits and policy reforms, the use of telemedicine remains low due to several patient, technology, and system-level barriers. Assisted telemedicine employs trained health professionals to connect patients with physicians, which can improve access and scope of telemedicine. The study aims to describe the design, service utilisation and chronic disease outcomes following the implementation of an assisted telemedicine initiative.

methodsThis is an observational implementation study. Barriers and potential solutions to the implementation of telemedicine were identified through interviews with key stakeholders. The assisted telemedicine solution using an interoperable platform integrating electronic health records, point-of-care diagnostics, and electronic clinical decision support systems was designed and piloted at three telemedicine clinics in Tamil Nadu, India. Nurses were trained in platform use and facilitation of tele-consultations. Health records of all patients from March 2021 to June 2023 were included in the analysis. Data were analysed to assess the utilisation of clinic services and improvements in health outcomes in patients with diabetes mellitus and hypertension.

resultsOver 2.4 years, 11,388 patients with a mean age of 45 (± 20) years and median age of 48 years, predominantly female (59.3%), accessed the clinics. The team completed 15,437 lab investigations and 26,998 consultations. Among 5542 (48.6%) patients that reported chronic conditions, diabetes mellitus (61%) and hypertension (45%) were the most frequent. In patients with diabetes mellitus and hypertension, 43% and 75.3% were newly diagnosed, respectively. Diabetes mellitus and hypertension patients had significant reductions in fasting blood sugar (-33.0 mg/dL (95% CI (-42.4, -23.7, P < 0.001)), and systolic (-9.6 mmHg (95% CI (-12.1, -7.0), P < 0.0001)) and diastolic blood pressure (-5.5 mmHg (95% CI (-7.0, -4.08), P < 0.0001)) at nine months from first visit, respectively.

conclusionsThe 'Digisahayam' model demonstrated feasibility in enhancing healthcare accessibility and quality by bridging healthcare gaps, diagnosing chronic conditions, and improving patient outcomes. The model presents a scalable and sustainable approach to revolutionising patient care and achieving digital health equity, with the potential for adaptation in similar settings worldwide.

Indexed as

HypertensionTelemedicineAdultChronic DiseaseDecision Support Systems, ClinicalDelivery of Health CareDiabetes MellitusElectronic Health RecordsFemaleHumansIndiaMaleMiddle AgedDigital equityDigital healthGuideline adherenceHealthcare accessHealth technologyTelemedicine

Identifiers

PMID39443848
PMCPMC11515714

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.