Andrews Carrie E, Baker Krista, Howell Carolyn J, Cuerdo Arlene, Roberts Jamie A, Chaudhary Abdullah, Lechich Stephanie, Nucifora Leslie G, Vaidya Dhananjay, Mojtabai Ramin, Margolis Russell L, Sawa Akira, Nucifora Frederick C
Except for Dr. Vaidya, the authors are with the Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore. Dr. Vaidya is with the Department of General Internal Medicine, Johns Hopkins University School of Medicine, Baltimore. Send correspondence to Dr. Frederick Nucifora, Jr. (e-mail:
Psychiatr Serv. 2017 Aug 1;68(8):847-850. doi: 10.1176/appi.ps.201600334. Epub 2017 Apr 3.
This study examined whether outpatients with a psychotic disorder who are at risk of hospitalization can be identified by using data from electronic medical records (EMRs).
Data from EMRs of outpatients enrolled in two clinics for treatment of psychotic disorders were abstracted. Monthly data were collected for 75 patients over two years. The study examined the association of medication nonadherence, substance use, participation in psychiatric rehabilitation, and long-acting injectable antipsychotic use in any given month with the risk of hospitalization in the subsequent month by using generalized estimating equations.
The only variable found to increase the relative risk of future hospitalization was recorded medication nonadherence (adjusted relative risk=7.19, p<.001).
Results suggest that recording medication nonadherence in EMRs is feasible and that these data may be used to identify patients at high risk of future hospitalization, who may require more intensive intervention.
本研究探讨了能否通过使用电子病历（EMR）数据来识别有住院风险的精神障碍门诊患者。
提取了在两家治疗精神障碍门诊就诊的患者的电子病历数据。在两年时间里收集了75名患者的月度数据。该研究通过使用广义估计方程，考察了在任何给定月份中药物治疗不依从、物质使用、参与精神康复以及使用长效注射用抗精神病药物与次月住院风险之间的关联。
唯一被发现会增加未来住院相对风险的变量是记录的药物治疗不依从（调整后的相对风险=7.19，p<0.001）。
结果表明，在电子病历中记录药物治疗不依从是可行的，并且这些数据可用于识别未来有高住院风险的患者，这些患者可能需要更强化的干预。
