医疗数据中病种隐私的计量与分析

Measurement and Analysis of Disease Privacy in Medical Data

[目的/意义]计量医疗数据中的病种隐私值,并基于人口统计变量对病种隐私进行敏感性分析,为医疗隐私保护和医疗数据利用提供基础条件。[方法/过程]采用联合分析法,计算患者对医疗数据保护服务每个属性的边际支付意愿,求得医疗数据中病种的隐私值,通过独立样本T检验和单因素方差分析,研究不同个体特征之间病种隐私的差异是否具有统计学意义。[结果/结论]基于访谈法的预调查结果,艾滋病隐私值为最高;采用联合分析法和Logit模型,计量其他病种隐私值,结果显示,降序排列隐私值较高的病种为精神疾病、传染病(艾滋病除外)、恶性肿瘤、心脏与脑血管疾病;基于人口统计变量的隐私值分析显示,性别、年龄、受教育程度3个变量下医疗数据中病种隐私差异具有显著性,且男性高于女性,年龄段为41~65岁的人群高于其他年龄段人群,教育程度越高隐私越大。

[Purpose/Significance]Measuring the privacy value of the disease in medical data and sensitivity analysis of disease privacy based on demographic variables provide basic conditions for medical privacy protection and medical data utilization.[Method/Process]Using the method of conjoint analysis,the privacy values of the diseases in medical data were obtained by calculating the patients'marginal willingness to pay for each attribute of medical data protection service.And independent sample T-test and one-way ANOVA were used to investigate whether the differences in disease privacy between different individual characteristics were statistically significant.[Result/Conclusion]Pre-survey results based on interviews showed that AIDS had the highest privacy value;using the method of conjoint analysis and Logit model to measure the privacy value of other diseases,the results showed that the diseases with higher privacy value in descending order were mental diseases,infectious diseases(except AIDS),malignant tumors,heart and cerebrovascular diseases;Privacy value analysis based on demographic variables showed that there were significant differences in disease privacy among three variables:gender,age and education level.Males were higher than females,adults were higher than other age groups,and the higher education level,the greater privacy.