Understanding how the design and implementation of online consultations impact primary care quality: Systematic review of evidence with recommendations for designers, providers, and researchers (Preprint): Systematic Review of Evidence With Recommendations for Designers, Providers, and Researchers

Sarah Darley, Tessa Coulson, Niels Peek, Susan Moschogianis, Sabine N van der Veer, David C Wong, Benjamin C Brown

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Abstract

Background: Online consultations (OCs) allow patients to contact their care providers on the web. Worldwide, OCs have been rolled out in primary care rapidly owing to policy initiatives and COVID-19. There is a lack of evidence regarding how OC design and implementation influence care quality. Objective: We aimed to synthesize research on the impacts of OCs on primary care quality, and how these are influenced by system design and implementation. Methods: We searched databases from January 2010 to February 2022. We included quantitative and qualitative studies of real-world OC use in primary care. Quantitative data were transformed into qualitative themes. We used thematic synthesis informed by the Institute of Medicine domains of health care quality, and framework analysis informed by the nonadoption, abandonment, scale-up, spread, and sustainability framework. Strength of evidence was judged using the GRADE-CERQual approach. Results: We synthesized 63 studies from 9 countries covering 31 OC systems, 14 (22%) of which used artificial intelligence; 41% (26/63) of studies were published from 2020 onward, and 17% (11/63) were published after the COVID-19 pandemic. There was no quantitative evidence for negative impacts of OCs on patient safety, and qualitative studies suggested varied perceptions of their safety. Some participants believed OCs improved safety, particularly when patients could describe their queries using free text. Staff workload decreased when sufficient resources were allocated to implement OCs and patients used them for simple problems or could describe their queries using free text. Staff workload increased when OCs were not integrated with other software or organizational workflows and patients used them for complex queries. OC systems that required patients to describe their queries using multiple-choice questionnaires increased workload for patients and staff. Health costs decreased when patients used OCs for simple queries and increased when patients used them for complex queries. Patients using OCs were more likely to be female, younger, and native speakers, with higher socioeconomic status. OCs increased primary care access for patients with mental health conditions, verbal communication difficulties, and barriers to attending in-person appointments. Access also increased by providing a timely response to patients’ queries. Patient satisfaction increased when using OCs owing to better primary care access, although it decreased when using multiple-choice questionnaire formats. Conclusions: This is the first theoretically informed synthesis of research on OCs in primary care and includes studies conducted during the COVID-19 pandemic. It contributes new knowledge that, in addition to having positive impacts on care quality such as increased access, OCs also have negative impacts such as increased workload. Negative impacts can be mitigated through appropriate OC system design (eg, free text format), incorporation of advanced technologies (eg, artificial intelligence), and integration into technical infrastructure (eg, software) and organizational workflows (eg, timely responses).

Original languageEnglish
Article numbere37436
Pages (from-to)e37436
JournalJOURNAL OF MEDICAL INTERNET RESEARCH
Volume24
Issue number10
DOIs
Publication statusPublished - 24 Oct 2022

Keywords

  • COVID-19
  • OC
  • care provider
  • general practice
  • health care professional
  • health outcome
  • pandemic
  • patient care
  • primary care
  • primary health care
  • remote consultation
  • systematic review
  • telemedicine
  • triage
  • workforce
  • Pandemics
  • United States
  • Artificial Intelligence
  • Humans
  • Male
  • Female
  • Referral and Consultation
  • Quality of Health Care

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