A CHRONIC DISEASE SCORE FROM AUTOMATED PHARMACY DATA
A CHRONIC DISEASE SCORE FROM AUTOMATED PHARMACY DATA
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DOI：
10.1016/0895-4356(92)90016-g
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发表时间：
1992-02-01
影响因子：
7.2
通讯作者：
SAUNDERS, K
中科院分区：
文献类型：
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作者：
VONKORFF, M;WAGNER, EH;SAUNDERS, K
使用基于人群的自动化药房数据，在1年的时间段内，通过一致性判断过程确定的所选处方药的使用模式用于构建慢性疾病状态的测量（慢性疾病评分）。该评分根据其随时间的稳定性及其与其他健康状况指标的相关性进行评估。在一个试点测试样本的高利用率的门诊医疗保健众所周知，他们的医生（n = 219），慢性病评分（CDS）与医生的身体疾病严重程度的评级（r = 0.57）。在第二个随机样本中（n = 722），其与医生评定的疾病严重程度的相关性为0.46。在总人口分析（n = 122，911）中，发现在控制年龄，性别和医疗保健访问后，它可以预测下一年的住院和死亡率。在人群样本（n = 790）中，CDS显示出较高的年间稳定性（r = 0.74）。基于健康调查数据，CDS显示出与自我评定的健康状况和自我报告的残疾中度相关。与自我评定的健康状况和医疗保健利用不同，CDS与抑郁或焦虑无关。我们的结论是，评分自动药房数据可以提供一个稳定的慢性疾病状态的措施，控制医疗保健利用后，与医生评定的疾病严重程度，患者评定的健康状况，并预测随后的死亡率和住院率。对自动化药房数据进行评分以衡量全球慢性病状态的具体方法可能需要适应当地的处方实践。通过对加权因子的经验估计，可以改善评分，以优化死亡率和其他健康状况指标的预测。
Using population-based automated pharmacy data, patterns of use of selected prescription medications during a 1 year time period identified by a concensus judgement process were used to construct a measure of chronic disease status (Chronic Disease Score). This score was evaluated in terms of its stability over time and its association with other health status measures. In a pilot test sample of high utilizers of ambulatory health care well known to their physicians (n = 219), Chronic Disease Score (CDS) was correlated with physician ratings of physical disease severity (r = 0.57). In a second random sample of patients (n = 722), its correlation with physician-rated disease severity was 0.46. In a total population analysis (n = 122,911), it was found to predict hospitalization and mortality in the following year after controlling for age, gender and health care visits. In a population sample (n = 790), CDS showed high year to year stability (r = 0.74). Based on health survey data, CDS showed a moderate association with self rated health status and self reported disability. Unlike self-rated health status and health care utilization, CDS was not associated with depression or anxiety. We conclude that scoring automated pharmacy data can provide a stable measure of chronic disease status that, after controlling for health care utilization, is associated with physician-rated disease severity, patient-rated health status, and predicts subsequent mortality and hospitalization rates. Specific methods of scoring automated pharmacy data to measure global chronic disease status may require adaptation to local prescribing practices. Scoring might be improved by empirical estimation of weighting factors to optimize prediction of mortality and other health status measures.