National Centre for Emergency Primary Health Care, NORCE Norwegian Research Centre, Bergen, Norway.
Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.
Scand J Prim Health Care. 2022 Jun;40(2):305-312. doi: 10.1080/02813432.2022.2097617. Epub 2022 Jul 13.
In epidemiological studies it is often necessary to describe morbidity. The aim of the present study is to construct and validate a morbidity index based on the International Classification of Primary Care (ICPC-2).
This is a cohort study based on linked data from national registries. An ICPC morbidity index was constructed based on a list of longstanding health problems in earlier published Scottish data from general practice and adapted to diagnostic ICPC-2 codes recorded in Norwegian general practice 2015 - 2017.
The index was constructed among Norwegian born people only ( = 4 509 382) and validated in a different population, foreign-born people living in Norway ( = 959 496).
Predictive ability for death in 2018 in these populations was compared with the Charlson index. Multiple logistic regression was used to identify morbidities with the highest odds ratios (OR) for death and predictive ability for different combinations of morbidities was estimated by the area under receiver operating characteristic curves (AUC).
An index based on 18 morbidities was found to be optimal, predicting mortality with an AUC of 0.78, slightly better than the Charlson index (AUC 0.77). External validation in a foreign-born population yielded an AUC of 0.76 for the ICPC morbidity index and 0.77 for the Charlson index.
The ICPC morbidity index performs equal to the Charlson index and can be recommended for use in data materials collected in primary health care.Key pointsThis is the first morbidity index based on the International Classification of Primary Care, 2 edition (ICPC-2)It predicted mortality equal to the Charlson index and validated acceptably in a different populationThe ICPC morbidity index can be used as an adjustment variable in epidemiological research in primary care databases.
在流行病学研究中，通常需要描述发病率。本研究旨在构建和验证基于初级保健国际分类（ICPC-2）的发病率指数。
这是一项基于国家登记处相关数据的队列研究。根据以前发表的苏格兰普通科医生数据中列出的长期健康问题，构建了一个 ICPC 发病率指数，并根据 2015-2017 年挪威普通科医生记录的诊断 ICPC-2 代码进行了调整。
该指数仅在挪威出生的人群中构建（n=4509382），并在不同人群（居住在挪威的外国出生人群，n=959496）中进行验证。
比较了这些人群中 2018 年死亡的预测能力，与 Charlson 指数进行比较。采用多因素逻辑回归确定病死率最高的发病率，并通过接受者操作特征曲线下面积（AUC）估计不同发病率组合的预测能力。
发现基于 18 种疾病的指数是最佳的，预测死亡率的 AUC 为 0.78，略优于 Charlson 指数（AUC 0.77）。在外国出生人群中的外部验证中，ICPC 发病率指数的 AUC 为 0.76，Charlson 指数为 0.77。
ICPC 发病率指数与 Charlson 指数相当，可推荐用于初级保健数据资料中。
这是第一个基于初级保健国际分类，第二版（ICPC-2）的发病率指数。它预测死亡率与 Charlson 指数相当，并在不同人群中得到可接受的验证。ICPC 发病率指数可作为初级保健数据库中流行病学研究的调整变量。
