Business School, Jilin University, Changchun, 130012, China.
Centre for Health Economics Research and Evaluation (CHERE), University of Technology Sydney, Level 2 Building 5 Block D, 1-59 Quay St., Haymarket, NSW, 2000, Australia.
BMC Health Serv Res. 2020 Apr 19;20(1):325. doi: 10.1186/s12913-020-05137-1.
Regional variation in the use of health care services is widespread. Identifying and understanding the sources of variation and how much variation is unexplained can inform policy interventions to improve the efficiency and equity of health care delivery.
We examined the regional variation in the use of general practitioners (GPs) using data from the Social Health Atlas of Australia by Statistical Local Area (SLAs). 756 SLAs were included in the analysis. The outcome variable of GP visits per capita by SLAs was regressed on a series of demand-side factors measuring population health status and demographic characteristics and supply-side factors measuring access to physicians. Each group of variables was entered into the model sequentially to assess their explanatory share on regional differences in GP usage.
Both demand-side and supply-side factors were found to influence the frequency of GP visits. Specifically, areas in urban regions, areas with a higher percentage of the population who are obese, who have profound or severe disability, and who hold concession cards, and areas with a smaller percentage of the population who reported difficulty in accessing services have higher GP usage. The availability of more GPs led to higher use of GP services while the supply of more specialists reduced use. 30.56% of the variation was explained by medical need. Together, both need-related and supply-side variables accounted for 32.24% of the regional differences as measured by the standard deviation of adjusted GP-consultation rate.
There was substantial variation in GP use across Australian regions with only a small proportion of them being explained by population health needs, indicating a high level of unexplained clinical variation. Supply factors did not add a lot to the explanatory power. There was a lot of variation that was not attributable to the factors we could observe. This could be due to more subtle aspects of population need or preferences and therefore warranted. However, it could be due to practice patterns or other aspects of supply and be unexplained. Future work should try to explain the remaining unexplained variation.
医疗服务的使用在地区间存在广泛差异。识别和理解这种差异的来源以及有多少差异是无法解释的,可以为改善医疗服务提供的效率和公平性的政策干预措施提供信息。
我们利用澳大利亚社会卫生地图集按统计地方行政区(SLAs)的数据,研究了普通医生(GP)使用的地区差异。共纳入了 756 个 SLAs 进行分析。使用 SLAs 的 GP 就诊人次作为因变量,按需求侧衡量人口健康状况和人口统计学特征的因素以及供应侧衡量医生可及性的因素进行回归。将每一组变量依次输入模型,以评估其对 GP 使用地区差异的解释程度。
需求侧和供应侧因素都被发现会影响 GP 就诊的频率。具体而言,城市地区、肥胖人口比例较高、有严重或深度残疾和持有优惠卡的人口比例较高、以及报告服务获取困难的人口比例较低的地区,GP 的使用频率更高。更多 GP 的可及性导致 GP 服务使用增加,而更多专科医生的供应则减少了使用。医疗需求解释了 30.56%的变异。需要相关和供应侧变量共同解释了 GP 就诊率调整后标准差所衡量的地区差异的 32.24%。
澳大利亚各地区的 GP 使用存在很大差异,只有一小部分可以用人口健康需求来解释,这表明存在大量无法解释的临床差异。供应因素并没有增加多少解释能力。有很多无法归因于我们所能观察到的因素的差异。这可能是由于人口需求或偏好的更微妙方面,因此是合理的。但是,这也可能是由于实践模式或供应的其他方面造成的,并且无法解释。未来的工作应尝试解释剩余的无法解释的变异。