Evidence map›Paper›PMID 39453703›Full record

Observational studyJMIR medical informatics2024

The Impact of International Classification of Disease-Triggered Prescription Support on Telemedicine: Observational Analysis of Efficiency and Guideline Adherence.

Tarso Augusto Duenhas Accorsi, Anderson Aires Eduardo, Carlos Guilherme Baptista, Flavio Tocci Moreira, Renata Albaladejo Morbeck, Karen Francine Köhler, Karine de Amicis Lima, Carlos Henrique Sartorato Pedrotti

Abstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in JMIR medical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

8 authors.

Tarso Augusto Duenhas AccorsiTelemedicine Department, Hospital Israelita Albert Einstein, São Paulo, Brazil.ORCID 0000-0002-8023-3466
Anderson Aires EduardoDigital Platform, Hospital Israelita Albert Einstein, São Paulo, Brazil.ORCID 0000-0001-8045-8043
Carlos Guilherme BaptistaTelemedicine Department, Hospital Israelita Albert Einstein, São Paulo, Brazil.ORCID 0000-0002-5910-6278
Flavio Tocci MoreiraTelemedicine Department, Hospital Israelita Albert Einstein, São Paulo, Brazil.ORCID 0000-0001-6574-3866
Renata Albaladejo MorbeckTelemedicine Department, Hospital Israelita Albert Einstein, São Paulo, Brazil.ORCID 0000-0003-1789-1738
Karen Francine KöhlerTelemedicine Department, Hospital Israelita Albert Einstein, São Paulo, Brazil.ORCID 0000-0002-8348-4623
Karine de Amicis LimaTelemedicine Department, Hospital Israelita Albert Einstein, São Paulo, Brazil.ORCID 0000-0002-9936-2436
Carlos Henrique Sartorato PedrottiTelemedicine Department, Hospital Israelita Albert Einstein, São Paulo, Brazil.ORCID 0000-0002-0634-7086

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIntegrating decision support systems into telemedicine may optimize consultation efficiency and adherence to clinical guidelines; however, the extent of such effects remains underexplored.

objectiveThis study aims to evaluate the use of ICD (International Classification of Disease)-coded prescription decision support systems (PDSSs) and the effects of these systems on consultation duration and guideline adherence during telemedicine encounters.

methodsIn this retrospective, single-center, observational study conducted from October 2021 to March 2022, adult patients who sought urgent digital care via direct-to-consumer video consultations were included. Physicians had access to current guidelines and could use an ICD-triggered PDSS (which was introduced in January 2022 after a preliminary test in the preceding month) for 26 guideline-based conditions. This study analyzed the impact of implementing automated prescription systems and compared these systems to manual prescription processes in terms of consultation duration and guideline adherence.

resultsThis study included 10,485 telemedicine encounters involving 9644 patients, with 12,346 prescriptions issued by 290 physicians. Automated prescriptions were used in 5022 (40.67%) of the consultations following system integration. Before introducing decision support, 4497 (36.42%) prescriptions were issued, which increased to 7849 (63.57%) postimplementation. The physician's average consultation time decreased significantly to 9.5 (SD 5.5) minutes from 11.2 (SD 5.9) minutes after PDSS implementation (P<.001). Of the 12,346 prescriptions, 8683 (70.34%) were aligned with disease-specific international guidelines tailored for telemedicine encounters. Primary medication adherence in accordance with existing guidelines was significantly greater in the decision support group than in the manual group (n=4697, 93.53% vs n=1389, 49.14%; P<.001).

conclusionsMost of the physicians adopted the PDSS, and the results demonstrated the use of the ICD-code system in reducing consultation times and increasing guideline adherence. These systems appear to be valuable for enhancing the efficiency and quality of telemedicine consultations by supporting evidence-based clinical decision-making.

Indexed as

Decision Support Systems, ClinicalGuideline AdherenceInternational Classification of DiseasesTelemedicineAdultAgedDrug PrescriptionsFemaleHumansMaleMiddle AgedRetrospective Studiesclinical decision support systemsconsultation efficiencyeHealthelectronic prescriptionsguideline adherenceInternational Classification of Disease–coded prescriptionsteleheathtelemedicine

Identifiers

PMID39453703
PMCPMC11549578

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.