Kjaersgaard Maiken Ina Siegismund, Vedsted Peter, Parner Erik Thorlund, Bech Bodil Hammer, Vestergaard Mogens, Flarup Kaare Rud, Fenger-Grøn Morten
Section for Biostatistics.
Research Unit for General Practice.
Clin Epidemiol. 2016 Aug 9;8:273-83. doi: 10.2147/CLEP.S108307. eCollection 2016.
The patient list system in Denmark assigns virtually all residents to a general practice. Nevertheless, historical information on this link between patient and general practice is not readily available for research purposes.
To develop, implement, and evaluate the performance of an algorithm linking individual patients to their general practice by using information from the Danish National Health Service Register and the Danish Civil Registration System.
The National Health Service Register contains information on all services provided by general practitioners from 1990 and onward. On the basis of these data and information on migration history and death obtained from the Civil Registration System, we developed an algorithm that allocated patients to a general practice on a monthly basis. We evaluated the performance of the algorithm between 2002 and 2007. During this time period, we had access to information on the link between patients and general practices. Agreement was assessed by the proportion of months for which the algorithm allocated patients to the correct general practice. We also assessed the proportion of all patients in the patient list system for which the algorithm was able to suggest an allocation.
The overall agreement between algorithm and patient lists was 98.6%. We found slightly higher agreement for women (98.8%) than for men (98.4%) and lower agreement in the age group 18-34 years (97.1%) compared to all other age groups (≥98.6%). The algorithm had assigned 83% of all patients in the patient list system after 1 year of follow-up, 91% after 2 years of follow-up, and peaked at 94% during the fourth year.
We developed an algorithm that enables valid and nearly complete linkage between patients and general practices. The algorithm performs better in subgroups of patients with high health care needs. The algorithm constitutes a valuable tool for primary health care research.
丹麦的患者名单系统几乎将所有居民都分配到一家全科诊所。然而,关于患者与全科诊所之间这种联系的历史信息并非随时可用于研究目的。
通过使用丹麦国家卫生服务登记册和丹麦民事登记系统中的信息,开发、实施并评估一种将个体患者与其全科诊所相联系的算法的性能。
国家卫生服务登记册包含自1990年及以后由全科医生提供的所有服务的信息。基于这些数据以及从民事登记系统获得的移民历史和死亡信息,我们开发了一种算法,该算法每月将患者分配到一家全科诊所。我们评估了2002年至2007年期间该算法的性能。在此期间,我们可以获取患者与全科诊所之间联系的信息。通过算法将患者分配到正确全科诊所的月份比例来评估一致性。我们还评估了患者名单系统中所有患者中该算法能够给出分配建议的比例。
算法与患者名单之间的总体一致性为98.6%。我们发现女性的一致性(98.8%)略高于男性(98.4%),并且与所有其他年龄组(≥98.6%)相比,18 - 34岁年龄组的一致性较低(97.1%)。随访1年后,该算法已为患者名单系统中83%的所有患者进行了分配,随访2年后为91%,在第四年达到峰值94%。
我们开发了一种算法,能够在患者与全科诊所之间实现有效且近乎完整的联系。该算法在医疗保健需求高的患者亚组中表现更好。该算法是初级卫生保健研究的一个有价值的工具。