Health and social care delivery research最新文献

{"title":"Linkage of routinely collected NHS data to evaluate liaison mental health services: challenges and lessons learned.","authors":"Elspeth Guthrie, Allan House, Chris Smith, Sam Relton, Daniel Romeu, Sonia Saraiva, Peter Trigwell, Robert West, Farag Shuweihdi, Mike Crawford, Matt Fossey, Jenny Hewison, Claire Hulme, Sandy Tubeuf","doi":"10.3310/WCPA5283","DOIUrl":"https://doi.org/10.3310/WCPA5283","url":null,"abstract":"<p><strong>Background: </strong>Liaison mental health services provide mental health care to patients in acute hospital settings. Evaluation of liaison services is challenging due to their heterogeneous organisation and delivery, high case throughput and varied patient case mix. We aimed to link routinely collected National Health Service data from secondary care settings, chosen for their service characteristics, to data from primary care to evaluate hospital-based liaison mental health services in England.</p><p><strong>Methods: </strong>We planned to compare patients referred to hospital-based liaison services with comparable patients in the same hospital not referred to liaison services and comparable patients in hospitals without any liaison services. We designed and enacted a methodology to link data from: (1) Hospital Episode Statistics, a database controlled by the National Health Service Digital and (2) ResearchOne, a primary care database controlled by The Phoenix Partnership.</p><p><strong>Results: </strong>Obtaining approvals for the steps prespecified in the methodological protocol took 907 days. Enactment following approvals took 385 days. Data supplied from Hospital Episode Statistics contained 181,063 patients from 6 hospitals (mean = 30,177, standard deviation = 28,875.86) who matched the inclusion and exclusion criteria. Data supplied from ResearchOne contained 33,666 (18.6%) of these patients from the 6 hospitals (mean = 5611, standard deviation = 5206.59).</p><p><strong>Discussion: </strong>Time required for approvals and enactment was attributable to slowness of data handling processes within each data holder and to resolution of technical and organisational queries between them. Variation in number of patients for which data was supplied between databases and between hospitals was attributable to coding inconsistencies and to the limited intersection of patient populations between databases and variation in recording practices between hospitals.</p><p><strong>Conclusion: </strong>Although it is technically feasible to link primary and secondary care data, the current system is challenging, complicated, unnecessarily bureaucratic, time consuming and costly. This limits the number of studies that could be conducted with these rich data sources.</p><p><strong>Funding: </strong>This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme as award number 13/58/08.</p>","PeriodicalId":519880,"journal":{"name":"Health and social care delivery research","volume":" ","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140900697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of different models of general practitioners working in or alongside emergency departments: a mixed-methods realist evaluation.","authors":"Freya Davies, Michelle Edwards, Delyth Price, Pippa Anderson, Andrew Carson-Stevens, Mazhar Choudhry, Matthew Cooke, Jeremy Dale, Liam Donaldson, Bridie Angela Evans, Barbara Harrington, Shaun Harris, Julie Hepburn, Peter Hibbert, Thomas Hughes, Faris Hussain, Saiful Islam, Rhys Pockett, Alison Porter, Aloysius Niroshan Siriwardena, Helen Snooks, Alan Watkins, Adrian Edwards, Alison Cooper","doi":"10.3310/JWQZ5348","DOIUrl":"10.3310/JWQZ5348","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Emergency healthcare services are under intense pressure to meet increasing patient demands. Many patients presenting to emergency departments could be managed by general practitioners in general practitioner-emergency department service models.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objectives: &lt;/strong&gt;To evaluate the effectiveness, safety, patient experience and system implications of the different general practitioner-emergency department models.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Design: &lt;/strong&gt;Mixed-methods realist evaluation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Phase 1 (2017-8), to understand current practice: rapid realist literature review, national survey and follow-up key informant interviews, national stakeholder event and safety data analysis. Phase 2 (2018-21), to collect and analyse qualitative (observations, interviews) and quantitative data (time series analysis); cost-consequences analysis of routine data; and case site data for 'marker condition' analysis from a purposive sample of 13 case sites in England and Wales. Phase 3 (2021-2), to conduct mixed-methods analysis for programme theory and toolkit development.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;General practitioners commonly work in emergency departments, but delivery models vary widely in terms of the scope of the general practitioner role and the scale of the general practitioner service. We developed a taxonomy to describe general practitioner-emergency department service models (Integrated with the emergency department service, Parallel within the emergency department, Outside the emergency department on the hospital site) and present a programme theory as principal output of the study to describe how these service models were observed to operate. Routine data were of variable quality, limiting our analysis. Time series analysis demonstrated trends across intervention sites for: increased time spent in the emergency department; increased emergency department attendances and reattendances; and mixed results for hospital admissions. Evidence on patient experience was limited but broadly supportive; we identified department-level processes to optimise the safety of general practitioner-emergency department models.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Limitations: &lt;/strong&gt;The quality, heterogeneity and extent of routine emergency department data collection during the study period limited the conclusions. Recruitment was limited by criteria for case sites (time series requirements) and individual patients (with 'marker conditions'). Pandemic and other pressures limited data collection for marker condition analysis. Data collected and analysed were pre pandemic; new approaches such as 'telephone first' and their relevance to our findings remains unexplored.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;Findings suggest that general practitioner-emergency department service models do not meet the aim of reducing the overall emergency department waiting times and improving patient flow with limited evidence of cost savings. Quali","PeriodicalId":519880,"journal":{"name":"Health and social care delivery research","volume":"12 10","pages":"1-152"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140873763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}