Evidence map›Paper›PMID 37379066›Full record

ArticleJournal of medical Internet research2023

The Integration of Clinical Decision Support Systems Into Telemedicine for Patients With Multimorbidity in Primary Care Settings: Scoping Review.

Nutchar Wiwatkunupakarn, Chanchanok Aramrat, Suphawita Pliannuom, Nida Buawangpong, Kanokporn Pinyopornpanish, Nopakoon Nantsupawat, Poppy Alice Carson Mallinson, Sanjay Kinra, Chaisiri Angkurawaranon

Abstract readScoping Review
In one paragraph

Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Trial
  4. Review
  5. Article
  6. Observational
  7. Article
  8. Article
  9. Review
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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

9 authors.

Nutchar WiwatkunupakarnDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.ORCID 0000-0001-7406-9498
Chanchanok AramratDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.ORCID 0000-0003-0384-4850
Suphawita PliannuomDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.ORCID 0000-0003-1315-3295
Nida BuawangpongDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.ORCID 0000-0001-9735-2587
Kanokporn PinyopornpanishDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.ORCID 0000-0001-9068-3834
Nopakoon NantsupawatDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.ORCID 0000-0002-7548-8616
Poppy Alice Carson MallinsonDepartment of Non-communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID 0000-0002-7591-8065
Sanjay KinraDepartment of Non-communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.ORCID 0000-0001-6690-4625
Chaisiri AngkurawaranonDepartment of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.ORCID 0000-0003-4206-9164

Funding

Medical Research Council MC_PC_MR/T038292/1Medical Research Council MR/R020876/1
6 · The paper itself

Abstract

backgroundMultimorbidity, the presence of more than one condition in a single individual, is a global health issue in primary care. Multimorbid patients tend to have a poor quality of life and suffer from a complicated care process. Clinical decision support systems (CDSSs) and telemedicine are the common information and communication technologies that have been used to reduce the complexity of patient management. However, each element of telemedicine and CDSSs is often examined separately and with great variability. Telemedicine has been used for simple patient education as well as more complex consultations and case management. For CDSSs, there is variability in data inputs, intended users, and outputs. Thus, there are several gaps in knowledge about how to integrate CDSSs into telemedicine and to what extent these integrated technological interventions can help improve patient outcomes for those with multimorbidity.

objectiveOur aims were to (1) broadly review system designs for CDSSs that have been integrated into each function of telemedicine for multimorbid patients in primary care, (2) summarize the effectiveness of the interventions, and (3) identify gaps in the literature.

methodsAn online search for literature was conducted up to November 2021 on PubMed, Embase, CINAHL, and Cochrane. Searching from the reference lists was done to find additional potential studies. The eligibility criterion was that the study focused on the use of CDSSs in telemedicine for patients with multimorbidity in primary care. The system design for the CDSS was extracted based on its software and hardware, source of input, input, tasks, output, and users. Each component was grouped by telemedicine functions: telemonitoring, teleconsultation, tele-case management, and tele-education.

resultsSeven experimental studies were included in this review: 3 randomized controlled trials (RCTs) and 4 non-RCTs. The interventions were designed to manage patients with diabetes mellitus, hypertension, polypharmacy, and gestational diabetes mellitus. CDSSs can be used for various telemedicine functions: telemonitoring (eg, feedback), teleconsultation (eg, guideline suggestions, advisory material provisions, and responses to simple queries), tele-case management (eg, sharing information across facilities and teams), and tele-education (eg, patient self-management). However, the structure of CDSSs, such as data input, tasks, output, and intended users or decision-makers, varied. With limited studies examining varying clinical outcomes, there was inconsistent evidence of the clinical effectiveness of the interventions.

conclusionsTelemedicine and CDSSs have a role in supporting patients with multimorbidity. CDSSs can likely be integrated into telehealth services to improve the quality and accessibility of care. However, issues surrounding such interventions need to be further explored. These issues include expanding the spectrum of medical conditions examined; examining tasks of CDSSs, particularly for screening and diagnosis of multiple conditions; and exploring the role of the patient as the direct user of the CDSS.

Indexed as

Decision Support Systems, ClinicalDiabetes, GestationalTelemedicineFemaleHumansMultimorbidityPregnancyPrimary Health CareCDSSchronic diseaseclinical decision support systemdecision supportmultimorbiditypharmaceuticpharmacypolypharmacyprimary carereviewscopingsearch strategytelehealthtelemedicine

Identifiers

PMID37379066
PMCPMC10365574

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.