Networks for research in primary health care.
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ABSTRACT:
SUBMITTER: Thomas P
PROVIDER: S-EPMC1119786 | biostudies-literature | 2001 Mar
REPOSITORIES: biostudies-literature
Publications
Networks for research in primary health care.
Thomas P P Griffiths F F Kai J J O'Dwyer A A
BMJ (Clinical research ed.) 20010301 7286
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Project description:There are practically no quantitative tools for understanding how much stress a health care system can absorb before it loses its ability to provide care. We propose to measure the resilience of health care systems with respect to changes in the density of primary care providers. We develop a computational model on a 1-to-1 scale for a countrywide primary care sector based on patient-sharing networks. Nodes represent all primary care providers in a country; links indicate patient flows between them. The removal of providers could cause a cascade of patient displacements, as patients have to find alternative providers. The model is calibrated with nationwide data from Austria that includes almost all primary care contacts over 2 y. We assign 2 properties to every provider: the "CareRank" measures the average number of displacements caused by a provider's removal (systemic risk) as well as the fraction of patients a provider can absorb when others default (systemic benefit). Below a critical number of providers, large-scale cascades of patient displacements occur, and no more providers can be found in a given region. We quantify regional resilience as the maximum fraction of providers that can be removed before cascading events prevent coverage for all patients within a district. We find considerable regional heterogeneity in the critical transition point from resilient to nonresilient behavior. We demonstrate that health care resilience cannot be quantified by physician density alone but must take into account how networked systems respond and restructure in response to shocks. The approach can identify systemically relevant providers.
| S-EPMC6883827 | biostudies-literature
Project description:PurposeUK primary care provides a rich data source for research. The impact of proposed data collection restrictions is unknown. This study aimed to assess the impact of restricting the scope of electronic health record (EHR) data collection on the ability to conduct research. The study estimated the consequences of restricted data collection on published Clinical Practice Research Datalink studies from high impact journals or referenced in clinical guidelines.MethodsA structured form was used to systematically analyse the extent to which individual studies would have been possible using a database with data collection restrictions in place: (1) retrospective collection of specified diseases only; (2) retrospective collection restricted to a 6- or 12-year period; (3) prospective and retrospective collection restricted to non-sensitive data. Outcomes were categorised as unfeasible (not reproducible without major bias); compromised (feasible with design modification); or unaffected.ResultsOverall, 91% studies were compromised with all restrictions in place; 56% studies were unfeasible even with design modification. With restrictions on diseases alone, 74% studies were compromised; 51% were unfeasible. Restricting collection to 6/12 years had a major impact, with 67 and 22% of studies compromised, respectively. Restricting collection of sensitive data had a lesser but marked impact with 10% studies compromised.ConclusionEHR data collection restrictions can profoundly reduce the capacity for public health research that underpins evidence-based medicine and clinical guidance. National initiatives seeking to collect EHRs should consider the implications of restricting data collection on the ability to address vital public health questions.
| S-EPMC6618795 | biostudies-literature
Project description:BackgroundFunding for research is under pressure to be accountable in terms of benefits and translation of research findings into practice and policy. Primary health care research has considerable potential to improve health care in a wide range of settings, but little is known about the extent to which these impacts actually occur. This study examines the impact of individual primary health care research projects on policy and practice from the perspective of Chief Investigators (CIs).MethodsThe project used an online survey adapted from the Buxton and Hanney Payback Framework to collect information about the impacts that CIs expected and achieved from primary health care research projects funded by Australian national competitive grants.Results and discussionChief Investigators (CIs) provided information about seventeen completed projects. While no CI expected their project to have an impact in every domain of the framework used in the survey, 76% achieved at least half the impacts they expected. Sixteen projects had published and/or presented their work, 10 projects included 11 doctorate awards in their research capacity domain. All CIs expected their research to lead to further research opportunities with 11 achieving this. Ten CIs achieved their expectation of providing information for policy making but only four reported their research had influenced policy making. However 11 CIs achieved their expectation of providing information for organizational decision making and eight reported their research had influenced organizational decision making.ConclusionCIs reported that nationally funded primary health care research projects made an impact on knowledge production, staff development and further research, areas within the realm of influence of the research team and within the scope of awareness of the CIs. Some also made an impact on policy and organizational decision-making, and on localized clinical practice and service delivery. CIs reported few broader economic benefits from their research. Routine use of an instrument of this type would facilitate primary health care research funders' determination of the payback for funding of research in this sector.
| S-EPMC3256100 | biostudies-literature
Project description:BackgroundPrimary care, and its transformation into Primary Health Care (PHC), has become an area of intense policy interest around the world. As part of this trend Alberta, Canada, has implemented Primary Care Networks (PCNs). These are decentralized organizations, mandated with supporting the delivery of PHC, funded through capitation, and operating as partnerships between the province's healthcare administration system and family physicians. This paper provides an implementation history of the PCNs, giving a detailed account of how people, time, and culture have interacted to implement bottom up, incremental change in a predominantly Fee-For-Service (FFS) environment.MethodsOur implementation history is built out of an analysis of policy documents and qualitative interviews. We conducted an interpretive analysis of relevant policy documents (n = 20) published since the first PCN was established. We then grounded 12 semi-structured interviews in that initial policy analysis. These interviews explored 11 key stakeholders' perceptions of PHC transformation in Alberta generally, and the formation and evolution of the PCNs specifically. The data from the policy review and the interviews were coded inductively, with participants checking our emerging analyses.ResultsOver time, the PCNs have shifted from an initial Frontier Era that emphasized local solutions to local problems and featured few rules, to a present Era of Accountability that features central demands for standardized measures, governance, and co-planning with other elements of the health system. Across both eras, the PCNs have been first and foremost instruments and supporters of family physician authority and autonomy. A core group of people emerged to create the PCNs and, over time, to develop a long-term Quality Improvement (QI) vision and governance plan for them as organizations. The continuing willingness of both these groups to work at understanding and aligning one another's cultures to achieve the transformation towards PHC has been central to the PCNs' survival and success.ConclusionsGeneralizable lessons from the implementation history of this emerging policy experiment include: The need for flexibility within a broad commitment to improving quality. The importance of time for individuals and organizations to learn about: quality improvement; one another's cultures; and how best to support the transformation of a system while delivering care locally.
| S-EPMC7718828 | biostudies-literature
Project description:IntroductionEthiopia has made notable progress in reducing maternal and perinatal mortality, yet challenges remain in meeting the 2030 Sustainable Development Goals. Persistent issues such as low service utilization, coupled with poor quality, fragmented care, and ineffective referral systems hinder progress. The "Improve Primary Health Care Service Delivery (IPHCSD)" project, implemented by JSI and Amref Health Africa since April 2022, seeks to address these gaps through a Networks of Care (NoCs) approach. This paper describes the lessons learned from implementing the NoCs approach to optimize primary health care in Ethiopia.MethodsThe project incorporates embedded implementation science, guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework. Key implementation strategies co-designed included strengthening community engagement, establishing NoCs, and introducing quality improvement initiatives using the Model for Improvement. Routine program monitoring data, NoCs process evaluation, and facility service statistics were utilized for this study. Service statistics were analyzed using Student's t-test and interrupted time-series analysis to compare maternal and child care outcomes before and after the NoCs intervention, with counterfactual estimates generated to assess the intervention's impact. Qualitative data from key informant interviews were transcribed, coded, and analyzed to identify themes and patterns using Atlas.ti.ResultsThe NoCs approach has significantly enhanced relational linkages between primary health care facilities and health care providers, fostering stronger collaboration and communication. This has fostered trust, improved care coordination, optimized primary health care performance, and increased health service utilization within woreda health systems. The interrupted time series analysis indicated that the rate of ANC 8+ visits was 29.8% per month higher than expected without the NoCs strategy (Coef: 2.39; p-value < 0.01) and an 18.4% increase in obstetric complications managed (Coef: 1.71; p-value = 0.050), with a 43% overall increase. Perinatal mortality decreased by 34%, from 31.3 to 20.1 per 1,000 births [t-test: 2.12; p-value: 0.040)].ConclusionThe NoCs approach in Ethiopia has proven effective in enhancing the relational elements, care coordination, and quality of primary health care services, leading to better maternal and child health outcomes. The findings expand the existing body of research on NoCs implementation best practices and further confirm that it provides a scalable model for strengthening health services in low-resource settings.
| S-EPMC11698449 | biostudies-literature
Project description:BackgroundSelf-reported substance use is more likely to be influenced by underreporting bias compared to the biological markers. Underreporting bias or validity of self-reported substance use depends on the study population and cannot be generalized to the entire population. This study aimed to compare the validity of self-reported substance use between research setting and primary health care setting from the same source population.Methods and materialsThe population in this study included from Rafsanjan Youth Cohort Study (RYCS) and from primary care health centers. The sample from RYCS is made up 607 participants, 113 (18.62%) women and 494 (81.38%) men and sample from PHC centers is made up 522 individuals including 252 (48.28%) women and 270 (51.72%) men. We compared two groups in respect of prevalence estimates based on self-reported substance use and urine test. Then for evaluating validity of self-reported substance use in both group, the results of reference standard, urine tests, were compared with the results of self-reported drug use using measures of concordance.ResultsThe prevalence of substance use based on urine test was significantly higher in both settings compared to self-reported substance use over the past 72 h. The sensitivity of self-report substance use over the past 72 h in research setting was 39.4, 20, 10% and zero for opium, methadone, cannabis and amphetamine, respectively and in primary health care setting was 50, 20.7, 12.5% and zero for opium, methadone, cannabis and amphetamine, respectively. The level of agreement between self-reported substance use over the past 72 h and urine test indicated fair and moderate agreement for opium in both research and primary health care settings, respectively and also slight agreement for methadone and cannabis in both settings were reported. There was no significant difference between the two groups in terms of self-reported substance use. For all substances, the level of agreement increased with longer recall periods. The specificity of self-report for all substances in both groups was more than 99%.ConclusionIndividuals in primary health care setting were more likely to self-reported substance use than in research setting, but setting did not have a statistically significant effect in terms of self-reported substance use. Programs that rely on self-reported substance use may not estimate the exact prevalence of substance use in both research and primary health care settings, especially for substances that have a higher social stigma. Therefore, it is recommended that self-report and biological indicators be used for more accurate evaluation in substance use studies. It is also suggested that future epidemiological studies be performed to reduce bias of social desirability and find a method providing the highest level of privacy.
| S-EPMC8439053 | biostudies-literature
Project description:BACKGROUND:This paper aims to discuss how physical activity (PA) brief assessment, brief counseling, and self-monitoring tools were designed and implemented in the Portuguese National Health Service (NHS), and to report on their current use by health professionals and citizens. METHODS:Three digital tools to facilitate PA promotion in primary health care (PHC) were developed: 1) a PA brief assessment tool was incorporated in the electronic health record platform "SClínico Cuidados de Saúde Primários"; 2) a brief counseling tool was developed in the software "PEM-Prescrição Eletrónica Médica" (electronic medical prescription); and 3) a "Physical Activity Card" was incorporated in an official NHS smartphone app called "MySNS Carteira". RESULTS:From September 2017 to June 2019, 119,386 Portuguese patients had their PA assessed in PHC. Between December 2017 and June 2019, a total of 7957 patients received brief intervention for PA by a medical doctor. Regarding the app "MySNS Carteira", 93,320 users activated the "Physical Activity Card", between February 2018 and December 2018. CONCLUSIONS:These tools represent key actions to promote PA among Portuguese citizens using PHC as a priority setting. Further initiatives will follow, including proper assessment of their clinical impact and training programs for health care professionals on PA promotion.
| S-EPMC7038181 | biostudies-literature
Project description:The last twenty years of health care research has seen a steady stream of common health care data models implemented for multi-organization research. Each model offers a uniform interface on data from the diverse organizations that implement them, enabling the sharing of research tools and data. While the groups designing the models have had various needs and aims, and the data available has changed significantly in this time, there are nevertheless striking similarities between them. This paper traces the evolution of common data models, describing their similarities and points of departure. We believe the history of this work should be understood and preserved. The work has empowered collaborative research across competing organizations and brought together researchers from clinical practice, universities and research institutes around the planet. Understanding the eco-system of data models designed for collaborative research allows readers to evaluate where we have been, where we are going as a field, and to evaluate the utility of different models to their own work.
| S-EPMC6437693 | biostudies-literature
Project description:BackgroundThough artificial intelligence (AI) has the potential to augment the patient-physician relationship in primary care, bias in intelligent health care systems has the potential to differentially impact vulnerable patient populations.ObjectiveThe purpose of this scoping review is to summarize the extent to which AI systems in primary care examine the inherent bias toward or against vulnerable populations and appraise how these systems have mitigated the impact of such biases during their development.MethodsWe will conduct a search update from an existing scoping review to identify studies on AI and primary care in the following databases: Medline-OVID, Embase, CINAHL, Cochrane Library, Web of Science, Scopus, IEEE Xplore, ACM Digital Library, MathSciNet, AAAI, and arXiv. Two screeners will independently review all abstracts, titles, and full-text articles. The team will extract data using a structured data extraction form and synthesize the results in accordance with PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines.ResultsThis review will provide an assessment of the current state of health care equity within AI for primary care. Specifically, we will identify the degree to which vulnerable patients have been included, assess how bias is interpreted and documented, and understand the extent to which harmful biases are addressed. As of October 2020, the scoping review is in the title- and abstract-screening stage. The results are expected to be submitted for publication in fall 2021.ConclusionsAI applications in primary care are becoming an increasingly common tool in health care delivery and in preventative care efforts for underserved populations. This scoping review would potentially show the extent to which studies on AI in primary care employ a health equity lens and take steps to mitigate bias.International registered report identifier (irrid)PRR1-10.2196/27799.
| S-EPMC8486995 | biostudies-literature
Project description:BackgroundTeam-based care is an essential part of primary health care (PHC), and its team service delivery process is a systematic one involving multiple and complex influences. Research on the formation mechanism can help improve the effectiveness of primary health care teams (PHCTs).MethodsFirst, based on the Donabedian model, we explored the theoretical framework of a PHC team's effectiveness formation mechanism. Semi-structured interviews were conducted with 23primary health care team members in Hangzhou, Zhejiang Province, China. A total of seven factors were then included as conditional variables using the crisp set qualitative comparative analysis (csQCA) to explore the complex influences between them and the outcome variable through univariate necessity analysis and path configuration analysis.ResultsUnivariate necessity analysis showed that only "Clear Goals" in the structural dimension were necessary for team effectiveness perception. Six pathways to good primary health care team perception of effectiveness were identified. Two of these paths were more typical.Conclusion"Clear Goals" was the core variable that should be emphasized when exploring the mechanism of PHCT formation. The results suggest that human resources in the management team should be rationally allocated, goal-oriented, and given good attention. Future studies should explore complex combinations of PHCT factors to improve the effectiveness of PHCTs.
| S-EPMC10823627 | biostudies-literature