Using Primary care data metrics to inform policy and practice: Human Health Resource implications.

IF 1.6 Q3 HEALTH CARE SCIENCES & SERVICES International Journal of Population Data Science Pub Date : 2022-08-25 DOI:10.23889/ijpds.v7i3.2051
E. Frymire, M. Green, R. Glazier, Shahriar Khan, Kamila Premji, I. Bayoumi, L. Jaakkimainen, T. Kiran, P. Gozdyra
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Abstract

ObjectivesTo produce open access Primary Care Data Reports using standard health administrative measures in primary care in conjunction with measures for attachment to a primary care provider. Illustrate the importance of incorporating patient attachment data as an essential component in Human Health Resource (HHR) planning. ApproachThis cohort study uses standard health administrative linked data in primary care in conjunction with measures of attachment to a primary care provider for the population of Ontario, Canada (14,632,575). Data includes attached and uncertainly attached patients stratified according to key demographics, patient characteristics, health care utilization and primary care indicators. We stratified based on health utilization characteristics and produced 6 priority populations of interest by region. ResultsThe factors most often utilized in informing human health resource planning were based on policy and practice users input and included:1.Patient enrolment model, 2.Attachment to a primary care provider, 3.Who does and does not receive care, 4.Continuity with regular source of care. Policy planners use the reports for improved understanding of the scope of issues in regions and improved understanding of primary care involvement with priority populations. Policy planners have used this report as a data support and measurement tool to identify supply (physician) and demand (patient) data essential in HHR planning.   Health system reform initiatives can use this data to inform improvements in the quality of, and equitable access to, primary care services in specific jurisdictions. ConclusionsThese reports contain key physician and patient data characteristics that correspond to primary care attachment rates. This data is essential to HHR planning when the goal is improving access to primary care for both attached and uncertainly attached patients. Data visualization in the form of mapping is especially impactful for policy and practice stakeholders.
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使用初级保健数据指标为政策和实践提供信息:对人类健康资源的影响。
目的使用初级保健中的标准健康管理措施以及与初级保健提供者的联系措施,编制开放获取的初级保健数据报告。说明将患者依恋数据作为人力资源规划的重要组成部分的重要性。方法这项队列研究使用了初级保健中的标准卫生行政相关数据,并结合加拿大安大略省人口对初级保健提供者的依恋程度(14632575)。数据包括根据关键人口统计、患者特征、医疗保健利用率和初级保健指标进行分层的附加和不确定附加患者。我们根据健康利用特征进行了分层,并按地区产生了6个感兴趣的优先人群。结果在人力卫生资源规划中最常使用的因素是基于政策和实践用户的输入,包括:1.患者登记模式,2.与初级保健提供者的关系,3.谁接受和不接受护理,4.与常规护理来源的连续性。政策规划者利用这些报告来更好地了解各地区的问题范围,并更好地了解优先人群参与初级保健的情况。政策规划者将本报告用作数据支持和测量工具,以确定HHR规划中必不可少的供应(医生)和需求(患者)数据。卫生系统改革举措可以利用这些数据为改善特定司法管辖区的初级保健服务质量和公平获得初级保健服务提供信息。结论这些报告包含与初级保健依恋率相对应的关键医生和患者数据特征。当目标是改善依恋和不确定依恋患者获得初级保健的机会时,这些数据对HHR规划至关重要。映射形式的数据可视化对政策和实践利益相关者尤其有影响。
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来源期刊
CiteScore
2.50
自引率
0.00%
发文量
386
审稿时长
20 weeks
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