scholarly journals Resource allocation for depression management in general practice: A simple data-based filter model

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246728
Author(s):  
Breanne Hobden ◽  
Mariko Carey ◽  
Rob Sanson-Fisher ◽  
Andrew Searles ◽  
Christopher Oldmeadow ◽  
...  
Keyword(s):  
Patient Outcome ◽  
Primary Care ◽  
Treatment Response ◽  
Potential Utility ◽  
Detection Rates ◽  
Treatment Pathway ◽  
Filter Model ◽  
Treatment Uptake ◽  
Depression Management ◽  
Simple Filter

Background This study aimed to illustrate the potential utility of a simple filter model in understanding the patient outcome and cost-effectiveness implications for depression interventions in primary care. Methods Modelling of hypothetical intervention scenarios during different stages of the treatment pathway was conducted. Results Three scenarios were developed for depression related to increasing detection, treatment response and treatment uptake. The incremental costs, incremental number of successes (i.e., depression remission) and the incremental costs-effectiveness ratio (ICER) were calculated. In the modelled scenarios, increasing provider treatment response resulted in the greatest number of incremental successes above baseline, however, it was also associated with the greatest ICER. Increasing detection rates was associated with the second greatest increase to incremental successes above baseline and had the lowest ICER. Conclusions The authors recommend utility of the filter model to guide the identification of areas where policy stakeholders and/or researchers should invest their efforts in depression management.

Comparison of postal and non-postal post-vasectomy semen sample submission strategies on compliance and failures: an 11-year analysis of the audit database of the Association of Surgeons in Primary Care of the UK

2021 ◽  
pp. bmjsrh-2021-201064
Author(s):  
Melanie Atkinson ◽  
Gareth James ◽  
Katie Bond ◽  
Zoe Harcombe ◽  
Michel Labrecque
Keyword(s):  
Primary Care ◽  
Semen Analysis ◽  
Failure Detection ◽  
Semen Sample ◽  
Failure Rates ◽  
Early Failure ◽  
Detection Rates ◽  
Late Failure ◽  
The Difference ◽  
The Uk

BackgroundVasectomy occlusive success is defined by the recommendation of ‘clearance’ to stop other contraception, and is elicited by post-vasectomy semen analysis (PVSA). We evaluated how the choice of either a postal or non-postal PVSA submission strategy was associated with compliance to PVSA and effectiveness of vasectomy.MethodsWe studied vasectomies performed in the UK from 2008 to 2019, reported in annual audits by Association of Surgeons in Primary Care members. We calculated the difference between the two strategies for compliance with PVSA, and early and late vasectomy failure. We determined compliance by adding the numbers of men with early failure and those given clearance. We performed stratified analyses by the number of test guidance for clearance (one-test/two-test) and the study period (2008–2013/2014–2019).ResultsAmong 58 900 vasectomised men, 32 708 (56%) and 26 192 (44%) were advised submission by postal and non-postal strategies, respectively. Compliance with postal (79.5%) was significantly greater than with non-postal strategy (59.1%), the difference being 20.4% (95% CI 19.7% to 21.2%). In compliant patients, overall early failure detection was lower with postal (0.73%) than with non-postal (0.94%) strategy (−0.22%, 95% CI −0.41% to −0.04%), but this difference was neither clinically nor statistically significant with one-test guidance in 2014–2019. There was no difference in late failure rates.ConclusionsPostal strategy significantly increased compliance to PVSA with similar failure detection rates. This resulted in more individuals receiving clearance or early failure because of the greater percentage of postal samples submitted. Postal strategy warrants inclusion in any future guidelines as a reliable and convenient option.

scholarly journals Translating Evidence-Based Depression Management Services to Community-Based Primary Care Practices

2004 ◽  
Vol 82 (4) ◽  
pp. 631-659 ◽  
Author(s):  
AMY M. KILBOURNE ◽  
HERBERT C. SCHULBERG ◽  
EDWARD P. POST ◽  
BRUCE L. ROLLMAN ◽  
BEA HERBECK BELNAP ◽  
...  
Keyword(s):  
Primary Care ◽  
Evidence Based ◽  
Community Based ◽  
Depression Management ◽  
Care Practices ◽  
Primary Care Practices ◽  
Management Services

The Medical Reception Station: a new primary care capability for 3 Commando Brigade

2016 ◽  
Vol 102 (1) ◽  
pp. 4-7
Author(s):  
D McMenamin ◽  
J Baker ◽  
M Middleton
Keyword(s):  
Primary Care ◽  
General Practitioner ◽  
Large Scale ◽  
Care Facility ◽  
Junior Doctors ◽  
Medical Facility ◽  
Potential Utility ◽  
Military Operations ◽  
Primary Care Facility ◽  
First Time

Abstract3 Commando Brigade’s delivery of pre-hospital (Role 1) care has until now largely been based around junior doctors delivering trauma-based resuscitation and limited primary care from small self-contained Regimental Aid Posts (RAPs). With the drawdown of large scale operations in Iraq and Afghanistan, and the diversity of potential future military operations, the deficiency of General Practitioner(GP)-led care in the deployed setting has become more evident, and this has driven the requirement for a deployable primary care facility in the form of a Medical Reception Station (MRS). This paper describes the evolution of this project, the realities of deploying a new medical capability for the first time, some of the issues faced, and the potential utility of such a medical facility in future.

Depression management in primary care

2005 ◽  
Vol 15 (10) ◽  
pp. 20-22
Author(s):  
Penny Louch
Keyword(s):  
Primary Care ◽  
Depression Management

The Importance of Efficient Depression Management in Primary Care

2008 ◽  
Vol 148 (7) ◽  
pp. 562
Author(s):  
Christos G. Theleritis ◽  
Thomas J. Paparrigopoulos ◽  
George N. Papadimitriou
Keyword(s):  
Primary Care ◽  
Depression Management

scholarly journals A simple filter model to guide the allocation of healthcare resources for improving the treatment of depression among cancer patients

BMC Cancer ◽  
2018 ◽  
Vol 18 (1) ◽  
Author(s):  
Robert W. Sanson-Fisher ◽  
Natasha E. Noble ◽  
Andrew M. Searles ◽  
Simon Deeming ◽  
Rochelle E. Smits ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Healthcare Resources ◽  
Filter Model ◽  
Treatment Of Depression ◽  
Simple Filter

scholarly journals Epidemiology and Clinical Symptoms Related to Seasonal Coronavirus Identified in Patients with Acute Respiratory Infections Consulting in Primary Care over Six Influenza Seasons (2014–2020) in France

Viruses ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 630
Author(s):  
Shirley Masse ◽  
Lisandru Capai ◽  
Natacha Villechenaud ◽  
Thierry Blanchon ◽  
Rémi Charrel ◽  
...  
Keyword(s):  
Primary Care ◽  
General Practice ◽  
Clinical Features ◽  
Clinical Symptoms ◽  
Respiratory Infections ◽  
Epidemiological Data ◽  
Influenza Surveillance ◽  
Respiratory Pathogens ◽  
Detection Rates ◽  
Representative Samples

There is currently debate about human coronavirus (HCoV) seasonality and pathogenicity, as epidemiological data are scarce. Here, we provide epidemiological and clinical features of HCoV patients with acute respiratory infection (ARI) examined in primary care general practice. We also describe HCoV seasonality over six influenza surveillance seasons (week 40 to 15 of each season) from the period 2014/2015 to 2019/2020 in Corsica (France). A sample of patients of all ages presenting for consultation for influenza-like illness (ILI) or ARI was included by physicians of the French Sentinelles Network during this period. Nasopharyngeal samples were tested for the presence of 21 respiratory pathogens by real-time RT-PCR. Among the 1389 ILI/ARI patients, 105 were positive for at least one HCoV (7.5%). On an annual basis, HCoVs circulated from week 48 (November) to weeks 14–15 (May) and peaked in week 6 (February). Overall, among the HCoV-positive patients detected in this study, HCoV-OC43 was the most commonly detected virus, followed by HCoV-NL63, HCoV-HKU1, and HCoV-229E. The HCoV detection rates varied significantly with age (p = 0.00005), with the age group 0–14 years accounting for 28.6% (n = 30) of HCoV-positive patients. Fever and malaise were less frequent in HCoV patients than in influenza patients, while sore throat, dyspnoea, rhinorrhoea, and conjunctivitis were more associated with HCoV positivity. In conclusion, this study demonstrates that HCoV subtypes appear in ARI/ILI patients seen in general practice, with characteristic outbreak patterns primarily in winter. This study also identified symptoms associated with HCoVs in patients with ARI/ILI. Further studies with representative samples should be conducted to provide additional insights into the epidemiology and clinical features of HCoVs.

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