Family practice
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To quantify the different types of health outcomes assessed as primary outcomes in randomized controlled trials (RCTs) in the primary care (PC) setting during the last 20 years and identify whether potential gaps exist in specific types of health care and types of intervention. ⋯ Our evidence map showed research gaps in certain types of health care and interventions. It also showed research gaps in assessing safety and measures to place patient at the centre of health care delivery as primary outcomes.
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Observational Study
Evaluation of telephone triage among chest pain patients in out-of-hours primary care in the Netherlands (TRACE).
Telephone triage is fully integrated in Dutch out-of-hours primary care (OOH-PC). Patients presenting with chest pain are initially assessed according to a standardized protocol ("Netherlands Triage Standard" [NTS]). Nevertheless, little is known about its (diagnostic) performance, nor on the impact of subsequent clinical judgements made by triage assistants and general practitioners (GPs). ⋯ Performance of telephone triage of chest pain appears moderate at best, with acceptable safety yet limited efficiency, even after including further work-up by GPs.
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The Dutch guideline for general practitioners (GPs) advises biannual surveillance of hepatitis B (HBV) patients and referral of every hepatitis C (HCV) patient. We aimed to study the prevalence, incidence, and the management of hepatitis B and C in primary care. ⋯ This study demonstrated a declining prevalence in viral hepatitis B and C in primary care in the Netherlands. However, a substantial part of the patients did not receive adequate surveillance or antiviral therapy. It is therefore crucial to involve GPs in case finding and in follow-up after treatment.
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Homeless populations (HPs) have difficulties obtaining necessary medical care, and primary health care service outreach (PHSO) might be useful to bridge this gap. ⋯ Our review adds to the evidence that PHSO likely improves health care access for HPs. Further studies over longer time periods, involving collaborations with experts with lived experience of homelessness, and utilizing randomized study designs are needed to test outreach efficacy.
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Classification and prediction tasks are common in health research. With the increasing availability of vast health data repositories (e.g. electronic medical record databases) and advances in computing power, traditional statistical approaches are being augmented or replaced with machine learning (ML) approaches to classify and predict health outcomes. ML describes the automated process of identifying ("learning") patterns in data to perform tasks. ⋯ In the future, ML approaches are positioned to become commonplace in family medicine. As such, it is important to understand the objectives that can be addressed using ML approaches and the associated techniques and limitations. This article provides a brief introduction into the use of ML approaches for classification and prediction tasks in family medicine.