Department of Public Health and Nursing, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Norwegian Center for E-Health Research, University Hospital of North Norway, Tromsø, Norway.
BMC Health Serv Res. 2024 Oct 24;24(1):1279. doi: 10.1186/s12913-024-11715-4.
The Adjusted Clinical Groups (ACG) System is a validated electronic risk stratification system. However, there is a lack of studies on the association between different ACG risk scores and the utilisation of different healthcare services using different sources of input data. The aim of this study was therefore to assess the validity of the association between five different ACG risk scores and the utilisation of a range of different healthcare services using input data from either general practitioners (GPs) or hospitals.
Registry-based study of all adult inhabitants in four Norwegian municipalities that received somatic healthcare in one year (N = 168 285). The ACG risk scores resource utilisation band, unscaled ACG concurrent risk, unscaled concurrent risk, frailty flag and chronic condition count were calculated using age, sex and diagnosis codes from GPs and a hospital, respectively. Healthcare utilisation covered GP, municipal and hospital services. Areas under the receiver operating curve (AUC) were calculated and compared to the AUC of a model using only age and sex.
Utilisation of all healthcare services increased with increasing scores in the "resource utilisation band" (RUB) and all other investigated ACG risk scores. The risk scores overall distinguished well between levels of utilisation of GP visits (AUC up to 0.84), hospitalisation (AUC up to 0.8) and specialist outpatient visits (AUC up to 0.72), but not out-of-hours GP visits (AUC up to 0.62). The score "unscaled ACG concurrent risk" overall performed best. Risk scores based on data from either GPs or hospitals performed better for the classification of healthcare services in their respective domains. The model based on age and sex performed better for distinguishing between levels of utilisation of municipal services (AUC 0.83-0.90 compared to 0.46-0.79).
Risk scores from the ACG system is valid for classifying GP visits, hospitalisation and specialist outpatient visits. It does not outperform simpler models in the classification of utilisation of municipal services such as nursing homes and home services and outpatient emergency care in primary healthcare. The ACG system can be applied in Norway using administrative data from either GPs or hospitals.
调整后的临床分组（ACG）系统是一种经过验证的电子风险分层系统。然而，关于不同 ACG 风险评分与使用不同输入数据的不同医疗保健服务之间的关联，缺乏研究。因此，本研究的目的是评估使用来自全科医生或医院的输入数据，通过五种不同的 ACG 风险评分评估与一系列不同医疗保健服务的使用之间的关联的有效性。
对四个挪威市的所有接受一年躯体保健的成年居民进行基于登记的研究（N=168285）。使用全科医生和医院的年龄、性别和诊断代码，分别计算 ACG 风险评分资源利用带、未经调整的 ACG 同期风险、未经调整的同期风险、脆弱性标志和慢性疾病计数。医疗保健的使用涵盖了全科医生、市和医院的服务。计算了接收器操作特性曲线（AUC）的面积，并与仅使用年龄和性别的模型的 AUC 进行了比较。
利用所有医疗保健服务的分数随着“资源利用带”（RUB）和所有其他调查的 ACG 风险评分的增加而增加。风险评分总体上很好地区分了全科医生就诊（AUC 高达 0.84）、住院（AUC 高达 0.8）和专科门诊就诊（AUC 高达 0.72）的利用率水平，但无法区分非工作时间的全科医生就诊（AUC 高达 0.62）。“未经调整的 ACG 同期风险”的评分总体上表现最佳。基于来自全科医生或医院的数据的风险评分，在其各自领域的医疗保健服务分类方面表现更好。基于年龄和性别的模型在区分市服务利用率水平方面表现更好（AUC 为 0.83-0.90，而 0.46-0.79）。
ACG 系统的风险评分可用于分类全科医生就诊、住院和专科门诊就诊。它在分类市服务的利用率方面，如疗养院和家庭服务以及初级保健中的门诊急救服务方面，并不优于更简单的模型。ACG 系统可在挪威使用来自全科医生或医院的管理数据进行应用。
