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澳大利亚全科医生(家庭医生)劳动力:比较调查、邮寄名单和医疗保险的地理数据。

General practitioner (family physician) workforce in Australia: comparing geographic data from surveys, a mailing list and medicare.

机构信息

APHCRI, Australian National University, Building 63, Cnr Mills and Eggleston Rds, Canberra, ACT 0200, Australia.

出版信息

BMC Health Serv Res. 2013 Sep 3;13:343. doi: 10.1186/1472-6963-13-343.

Abstract

BACKGROUND

Good quality spatial data on Family Physicians or General Practitioners (GPs) are key to accurately measuring geographic access to primary health care. The validity of computed associations between health outcomes and measures of GP access such as GP density is contingent on geographical data quality. This is especially true in rural and remote areas, where GPs are often small in number and geographically dispersed. However, there has been limited effort in assessing the quality of nationally comprehensive, geographically explicit, GP datasets in Australia or elsewhere.Our objective is to assess the extent of association or agreement between different spatially explicit nationwide GP workforce datasets in Australia. This is important since disagreement would imply differential relationships with primary healthcare relevant outcomes with different datasets. We also seek to enumerate these associations across categories of rurality or remoteness.

METHOD

We compute correlations of GP headcounts and workload contributions between four different datasets at two different geographical scales, across varying levels of rurality and remoteness.

RESULTS

The datasets are in general agreement with each other at two different scales. Small numbers of absolute headcounts, with relatively larger fractions of locum GPs in rural areas cause unstable statistical estimates and divergences between datasets.

CONCLUSION

In the Australian context, many of the available geographic GP workforce datasets may be used for evaluating valid associations with health outcomes. However, caution must be exercised in interpreting associations between GP headcounts or workloads and outcomes in rural and remote areas. The methods used in these analyses may be replicated in other locales with multiple GP or physician datasets.

摘要

背景

家庭医生或全科医生(GP)的高质量空间数据对于准确衡量初级医疗保健的地理可及性至关重要。计算健康结果与 GP 可及性指标(如 GP 密度)之间关联的有效性取决于地理数据的质量。在农村和偏远地区,这种情况尤其如此,那里的 GP 数量通常较少且分布广泛。然而,在评估澳大利亚或其他地方全国性、地理明确、全面的 GP 数据集的质量方面,所做的努力有限。

我们的目标是评估澳大利亚不同空间明确的全国性 GP 劳动力数据集之间的关联或一致性程度。这很重要,因为不一致意味着不同数据集与初级医疗保健相关结果之间存在不同的关系。我们还试图在农村或偏远程度的不同类别中列举这些关联。

方法

我们在两个不同的地理尺度上,针对不同程度的农村和偏远程度,计算了四个不同数据集之间的 GP 人头数和工作量贡献的相关性。

结果

这些数据集在两个不同的尺度上通常是一致的。在农村地区,人头数的绝对数量较少,并且临时 GP 的相对比例较大,这导致统计估计不稳定,并且数据集之间存在差异。

结论

在澳大利亚的背景下,许多可用的地理 GP 劳动力数据集可用于评估与健康结果的有效关联。但是,在解释农村和偏远地区的 GP 人头数或工作量与结果之间的关联时必须谨慎。这些分析中使用的方法可以在具有多个 GP 或医师数据集的其他地区复制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3686/3766700/6b6e984a4d29/1472-6963-13-343-1.jpg

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