Impact of Question Content on e-Consultation Outcomes

Telemed J E Health. 2016 Mar;22(3):216-22. doi: 10.1089/tmj.2015.0081. Epub 2015 Aug 17.

Abstract

Background: By facilitating direct communication of primary care providers (PCPs) with specialists for advice, electronic consult (e-consult) services can reduce the need for patients to wait for and travel to face-to-face consultations with specialists. An association between avoiding face-to-face referrals using an e-consult service and specific content within each e-consult has not been rigorously explored.

Materials and methods: Cases submitted to the Champlain Building Access to Specialists through eConsultation service between April 2011 to May 2013 were evaluated. Factors analyzed include question type (e.g., diagnosis or management), formulation (if interventions or outcomes were specified), and the addressed specialty. An avoided referral was present if the PCP indicated so in a mandatory close-out survey. A discrepancy was present if the PCP made a referral when the specialist did not indicate one was necessary, or if the PCP did not request a referral despite the specialist recommending one.

Results: There were 426 (40%) avoided referrals among 1,055 cases analyzed. Questions associated with the highest avoided referral rates included ones pertaining to diagnosis (44%), nonspecific requests for direction (44%), questions without specified interventions or outcomes (47%), and dermatology cases (49.5%). Specialists agreed on the need for a referral in 82% of cases, with most discrepancies due to the PCP making a referral without the specialist recommending one.

Conclusions: Referral outcomes are associated with the type of question being asked, the formulation of each question, and the specialty being addressed. Discrepancies among PCPs and specialists regarding which patients require face-to-face referrals may help identify knowledge gaps and guide professional development.

Keywords: e-health; information management; telehealth; telemedicine.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged, 80 and over
  • Clinical Competence*
  • Cost-Benefit Analysis
  • Delivery of Health Care / methods
  • Female
  • Health Care Surveys
  • Humans
  • Male
  • Medicine / methods*
  • Middle Aged
  • Ontario
  • Outcome Assessment, Health Care*
  • Primary Health Care / economics
  • Primary Health Care / methods*
  • Referral and Consultation / economics
  • Referral and Consultation / statistics & numerical data
  • Remote Consultation / economics
  • Remote Consultation / methods*