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[基层医疗领域中调整后的发病群组相对于临床风险群组的有效性]

[Validity of adjusted morbidity groups with respect to clinical risk groups in the field of primary care].

作者信息

Monterde David, Vela Emili, Clèries Montse, García Eroles Luis, Pérez Sust Pol

机构信息

Oficina de Estadística, Sistemas de Información, Instituto Catalán de la Salud, Departamento de Salud de la Generalidad de Cataluña, Barcelona, España.

Unidad de Información y del Conocimiento, Servicio Catalán de la Salud, Departamento de Salud de la Generalidad de Cataluña, Barcelona, España.

出版信息

Aten Primaria. 2019 Mar;51(3):153-161. doi: 10.1016/j.aprim.2017.09.012. Epub 2018 Feb 9.

DOI:10.1016/j.aprim.2017.09.012
PMID:29433758
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6836969/
Abstract

OBJECTIVE

To compare the performance in terms of goodness of fit and explanatory power of 2morbidity groupers in primary care (PC): adjusted morbidity groups (AMG) and clinical risk groups (CRG).

DESIGN

Cross-sectional study.

LOCATION

PC in the Catalan Institute for the Health (CIH), Catalonia, Spain.

PARTICIPANTS

Population allocated in primary care centers of the CIH for the year 2014.

MAIN MEASUREMENTS

Three indicators of interest are analyzed such as urgent hospitalization, number of visits and spending in pharmacy. A stratified analysis by centers is applied adjusting generalized lineal models from the variables age, sex and morbidity grouping to explain each one of the 3variables of interest. The statistical measures to analyze the performance of the different models applied are the Akaike index, the Bayes index and the pseudo-variability explained by deviance change.

RESULTS

The results show that in the area of the primary care the explanatory power of the AMGs is higher to that offered by the CRGs, especially for the case of the visits and the pharmacy.

CONCLUSIONS

The performance of GMAs in the area of the CIH PC is higher than that shown by the CRGs.

摘要

目的

比较基层医疗（PC）中两种疾病分组方法在拟合优度和解释力方面的表现，即调整后的疾病分组（AMG）和临床风险分组（CRG）。

设计

横断面研究。

地点

西班牙加泰罗尼亚健康研究所（CIH）的基层医疗。

参与者

2014年分配到CIH基层医疗中心的人群。

主要测量指标

分析三个感兴趣的指标，如紧急住院、就诊次数和药房支出。应用按中心分层分析，从年龄、性别和疾病分组变量调整广义线性模型，以解释三个感兴趣变量中的每一个。用于分析不同模型表现的统计量是赤池指数、贝叶斯指数以及由偏差变化解释的伪方差。

结果

结果表明，在基层医疗领域，AMG的解释力高于CRG，尤其是在就诊次数和药房支出方面。

结论

CIH基层医疗领域中GMA的表现高于CRG。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f05e/6836969/af5a34bdded5/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f05e/6836969/698a532e1210/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f05e/6836969/39dbcfbbdebd/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f05e/6836969/be3b81dadf41/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f05e/6836969/af5a34bdded5/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f05e/6836969/698a532e1210/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f05e/6836969/39dbcfbbdebd/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f05e/6836969/be3b81dadf41/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f05e/6836969/af5a34bdded5/gr3.jpg

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Keep it simple? Predicting primary health care costs with clinical morbidity measures.保持简单？用临床发病率指标预测初级医疗保健成本。
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Comparing measures of multimorbidity to predict outcomes in primary care: a cross sectional study.
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