Effect of a Multi-specialty E-consultation Service on Hospital Referrals: An Interrupted Time-Series Study in the Netherlands

Abstract Background E-consultation services between family physicians and hospital specialists may help manage rising healthcare costs and improve care accessibility. Yet, robust evaluations of e-consultation impact on hospital referral patterns remain scarce. Objective To evaluate the effect of a multi-specialty e-consultation service between family physicians and medical specialists on hospital referral rates. Design An interrupted time series analysis was conducted in the Netherlands between 2015 and 2023, including family practices that submitted e-consultations to 11 specialties at a regional hospital. Participants Family practices from a specific region in the Netherlands that used the e-consultation service were included as the exposed group, and a national sample of family practices from the Nivel Primary Care Database served as the control group. Intervention Implementation of a multi-specialty e-consultation service. Main Measures Monthly referral rates for outpatient clinic visits were analyzed utilizing seasonal autoregressive integrated moving average (SARIMA) models and difference-in-differences analyses to evaluate trends before and after the introduction of the e-consultation service. Sensitivity analyses were performed using various lag periods, and subgroup analyses were conducted based on e-consultation volumes and family physician experience. Key Results There was a limited overall impact of e-consultations on hospital referral trends. Internal Medicine showed a regional reduction in referrals (−1.56% per month, p < 0.01), though this was not significant compared to national trends (difference-in-difference: 0.68%, p = 0.24). Surgery and Neurology showed significant regional increases (Surgery: + 1.76% per month, p < 0.01; Neurology: + 1.75% per month, p = 0.01), which were also significant compared to national trends in the difference-in-difference analysis (Surgery: −1.73%, p < 0.01; Neurology: −1.81%, p = 0.01). Subgroup and sensitivity analyses did not reveal consistent patterns or delayed effects. Conclusions Specialties did not show a clinically meaningful reduction in referrals, likely due to the relatively small proportion of e-consultations compared to regular referrals. While the overall effect was limited, targeted implementation of e-consultations within specific contexts may help optimize referral practices. Further research is needed to explore the contextual factors that influence the effectiveness of e-consultations.

Institutions

Publication Details

Journal
Journal of General Internal Medicine
Published
2026-05-19
DOI
https://doi.org/10.1007/s11606-026-10485-5
Primary Topic
Healthcare Systems and Technology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effect of a Multi-specialty E-consultation Service on Hospital Referrals: An Interrupted Time-Series Study in the Netherlands

Journal of General Internal Medicine
Healthcare Systems and Technology
article

Effect of a Multi-specialty E-consultation Service on Hospital Referrals: An Interrupted Time-Series Study in the Netherlands

article en

Abstract

Abstract Background E-consultation services between family physicians and hospital specialists may help manage rising healthcare costs and improve care accessibility. Yet, robust evaluations of e-consultation impact on hospital referral patterns remain scarce. Objective To evaluate the effect of a multi-specialty e-consultation service between family physicians and medical specialists on hospital referral rates. Design An interrupted time series analysis was conducted in the Netherlands between 2015 and 2023, including family practices that submitted e-consultations to 11 specialties at a regional hospital. Participants Family practices from a specific region in the Netherlands that used the e-consultation service were included as the exposed group, and a national sample of family practices from the Nivel Primary Care Database served as the control group. Intervention Implementation of a multi-specialty e-consultation service. Main Measures Monthly referral rates for outpatient clinic visits were analyzed utilizing seasonal autoregressive integrated moving average (SARIMA) models and difference-in-differences analyses to evaluate trends before and after the introduction of the e-consultation service. Sensitivity analyses were performed using various lag periods, and subgroup analyses were conducted based on e-consultation volumes and family physician experience. Key Results There was a limited overall impact of e-consultations on hospital referral trends. Internal Medicine showed a regional reduction in referrals (−1.56% per month, p < 0.01), though this was not significant compared to national trends (difference-in-difference: 0.68%, p = 0.24). Surgery and Neurology showed significant regional increases (Surgery: + 1.76% per month, p < 0.01; Neurology: + 1.75% per month, p = 0.01), which were also significant compared to national trends in the difference-in-difference analysis (Surgery: −1.73%, p < 0.01; Neurology: −1.81%, p = 0.01). Subgroup and sensitivity analyses did not reveal consistent patterns or delayed effects. Conclusions Specialties did not show a clinically meaningful reduction in referrals, likely due to the relatively small proportion of e-consultations compared to regular referrals. While the overall effect was limited, targeted implementation of e-consultations within specific contexts may help optimize referral practices. Further research is needed to explore the contextual factors that influence the effectiveness of e-consultations.

Journal of General Internal Medicine
Maastricht University Medical Centre (NL), Maastricht University (NL), Netherlands Institute for Health Services Research (NL), Department of Health (TW), Medisch Coördinerend Centrum Omnes (NL), Zuyderland Medisch Centrum (NL), GGD Zuid Limburg (NL), Department of Health Services (NP)
Openalex Percentile: Top 3%
Healthcare Systems and Technology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.