de Graaf-Ruizendaal W A, van der Hoek L, de Bakker D H
NIVEL: Netherlands Institute for Health Service Research, PO Box 1568, 3500, BN, Utrecht, The Netherlands.
Scientific centre for care and welfare, Tranzo, Tilburg University, PO Box 90153, 5000, LE, Tilburg, The Netherlands.
BMC Fam Pract. 2018 Apr 25;19(1):46. doi: 10.1186/s12875-018-0732-7.
General practice care plays a key role in keeping healthcare effective and cost-efficient. However, variation in the utilization rates of practices may reveal variation in practice performance. Our research goal is to investigate whether the socio-demographic profile of the patients' area of residence and practice organization characteristics influence the low or high utilization of general practice care.
Data on the utilization of general practice care were derived from the electronic health records of 232 general practices participating in the NIVEL Primary Care Database for the year 2013. Census data for the year 2013 were matched with the postal code of the patients. A small area estimation (SAE) technique was used to calculate the estimated utilization rate for general practice care per practice based on the socio-demographic profile of the patients' area of residence. Subsequently, the actual utilization rates were compared to the estimated rates per practice. Linear regression analysis was used to link the differences between the actual and estimated utilization rates to practice organization characteristics.
The socio-demographic profile of the patients' area of residence accounted for 25.7% of the estimated utilization rates per practice. Practice organization characteristics accounted for 19.3% of the difference between the actual utilization rates and the estimated rates. Practices had higher utilization rates than estimated when a practice was a dual practice, when it employed female GPs, when it employed other healthcare providers and/or when it offered more services related to a disease management programme.
We found that utilization rates of general practice care can be partially explained by the socio-demographic profile of the patients' area of residence, but also by practice organization characteristics. Insight into these factors provides both GPs and the other stakeholders involved in the organization of general practice care with information to help reflect on the utilization of care.
全科医疗在保持医疗保健的有效性和成本效益方面发挥着关键作用。然而,不同医疗机构的利用率差异可能反映出其医疗服务表现的差异。我们的研究目标是调查患者居住地区的社会人口统计学特征和医疗机构组织特征是否会影响全科医疗的低利用率或高利用率。
2013年参与NIVEL初级保健数据库的232家全科医疗机构的电子健康记录提供了全科医疗利用率数据。2013年的人口普查数据与患者的邮政编码相匹配。采用小区域估计(SAE)技术,根据患者居住地区的社会人口统计学特征计算每家医疗机构的全科医疗估计利用率。随后,将实际利用率与每家医疗机构的估计利用率进行比较。使用线性回归分析将实际利用率与估计利用率之间的差异与医疗机构组织特征联系起来。
患者居住地区的社会人口统计学特征占每家医疗机构估计利用率的25.7%。医疗机构组织特征占实际利用率与估计利用率之间差异的19.3%。当一家医疗机构为双重执业机构、雇佣女全科医生、雇佣其他医疗服务提供者和/或提供更多与疾病管理计划相关的服务时,其利用率高于估计值。
我们发现,全科医疗的利用率可以部分由患者居住地区的社会人口统计学特征来解释,但也与医疗机构组织特征有关。深入了解这些因素可为全科医生以及参与全科医疗组织的其他利益相关者提供信息,以帮助他们反思医疗服务的利用情况。