SynthesisBMC health services research2021
The effectiveness of different patient referral systems to shorten waiting times for elective surgeries: systematic review.
Synthesis in BMC health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A Bibliometric Analysis and Visualization of Decision Support Systems for Healthcare Referral Strategies.International journal of environmental research and public health · 2022Pooled it
- Patient prioritisation methods to shorten waiting times for elective surgery: A systematic review of how to improve access to surgery.PloS one · 2021Pooled it
- Article
- Mapping strategies for reducing inequalities in adult elective surgical care in the United Kingdom: a living scoping review.BMC health services research · 2026Article
- Article
- Article
- OpenNotes in dentistry as a strategy for patient engagement: opportunities, barriers, and a framework for implementation.Frontiers in oral health · 2026Review
- Preoperative waiting time and no-show risk in day surgery: a large-scale cohort study.Frontiers in medicine · 2026Article
- Optimizing people's movement across the health system: a scoping review of referral systems within a primary health care approach.Primary health care research & development · 2025Article
- Review
- Development and Feasibility Study of a Triage Tool for Early Referral to Spinal Cord Stimulation for Patients With Chronic Low Back and Leg Pain.European journal of pain (London, England) · 2025Article
- Identifying and prioritizing inefficiency causes in Iran's health system.Cost effectiveness and resource allocation : C/E · 2024Article
- Developing a Nomogram for Prioritizing Hysteroscopy in Endometrial Cancer Diagnosis: A Case-Control Study.Journal of clinical medicine · 2024Article
- Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.Frontiers in artificial intelligence · 2024Article
- Scenarios to Improve the Patient Experience Time in a Tertiary Academic Hospital Using Simulation.Cureus · 2022Article
- Analyzing historical and future acute neurosurgical demand using an AI-enabled predictive dashboard.Scientific reports · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLong waiting times for elective surgery are common to many publicly funded health systems. Inefficiencies in referral systems in high-income countries are more pronounced than lower and middle-income countries. Primary care practitioners play a major role in determining which patients are referred to surgeon and might represent an opportunity to improve this situation. With conventional methods of referrals, surgery clinics are often overcrowded with non-surgical referrals and surgical patients experience longer waiting times as a consequence. Improving the quality of referral communications should lead to more timely access and better cost-effectiveness for elective surgical care. This review summarises the research evidence for effective interventions within the scope of primary-care referral methods in the surgical care pathway that might shorten waiting time for elective surgeries.
methodsWe searched PubMed, EMBASE, SCOPUS, Web of Science and Cochrane Library databases in December-2019 to January-2020, for articles published after 2013. Eligibility criteria included major elective surgery lists of adult patients, excluding cancer related surgeries. Both randomised and non-randomised controlled studies were eligible. The quality of evidence was assessed using ROBINS-I, AMSTAR 2 and CASP, as appropriate to the study method used. The review presentation was limited to a narrative synthesis because of heterogeneity. The PROSPERO registration number is CRD42019158455.
resultsThe electronic search yielded 7543 records. Finally, nine articles were considered as eligible after deduplication and full article screening. The eligible research varied widely in design, scope, reported outcomes and overall quality, with one randomised trial, two quasi-experimental studies, two longitudinal follow up studies, three systematic reviews and one observational study. All the six original articles were based on referral methods in high-income countries. The included research showed that patient triage and prioritisation at the referral stage improved timely access and increased the number of consultations of surgical patients in clinics.
conclusionsThe available studies included a variety of interventions and were of medium to high quality researches. Managing patient referrals with proper triaging and prioritisation using structured referral formats is likely to be effective in health systems to shorten the waiting times for elective surgeries, specifically in high-income countries.
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What Socratic holds
Registered trials
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 Socratic graph.