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Assessing the accuracy of an inter-institutional automated patient-specific health problem list

机译：评估机构间自动针对患者的健康问题清单的准确性

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Background Health problem lists are a key component of electronic health records and are instrumental in the development of decision-support systems that encourage best practices and optimal patient safety. Most health problem lists require initial clinical information to be entered manually and few integrate information across care providers and institutions. This study assesses the accuracy of a novel approach to create an inter-institutional automated health problem list in a computerized medical record (MOXXI) that integrates three sources of information for an individual patient: diagnostic codes from medical services claims from all treating physicians, therapeutic indications from electronic prescriptions, and single-indication drugs. Methods Data for this study were obtained from 121 general practitioners and all medical services provided for 22,248 of their patients. At the opening of a patient's file, all health problems detected through medical service utilization or single-indication drug use were flagged to the physician in the MOXXI system. Each new arising health problem were presented as 'potential' and physicians were prompted to specify if the health problem was valid (Y) or not (N) or if they preferred to reassess its validity at a later time. Results A total of 263,527 health problems, representing 891 unique problems, were identified for the group of 22,248 patients. Medical services claims contributed to the majority of problems identified (77%), followed by therapeutic indications from electronic prescriptions (14%), and single-indication drugs (9%). Physicians actively chose to assess 41.7% (n = 106,950) of health problems. Overall, 73% of the problems assessed were considered valid; 42% originated from medical service diagnostic codes, 11% from single indication drugs, and 47% from prescription indications. Twelve percent of problems identified through other treating physicians were considered valid compared to 28% identified through study physician claims. Conclusion Automation of an inter-institutional problem list added over half of all validated problems to the health problem list of which 12% were generated by conditions treated by other physicians. Automating the integration of existing information sources provides timely access to accurate and relevant health problem information. It may also accelerate the uptake and use of electronic medical record systems.
机译：背景技术健康问题清单是电子健康记录的关键组成部分，有助于制定鼓励最佳实践和最佳患者安全的决策支持系统。大多数健康问题列表要求手动输入初始临床信息，并且很少整合跨医疗提供者和机构的信息。这项研究评估了一种新颖方法的准确性，该方法可以在计算机病历（MOXXI）中创建机构间自动化健康问题列表，该列表整合了单个患者的三种信息来源：医疗服务的诊断代码，所有主治医生的索赔，治疗电子处方和单指药物的适应症。方法该研究的数据来自121位全科医生，为22,248位患者提供了所有医疗服务。在打开患者档案时，通过医疗服务使用或单指药物使用检测到的所有健康问题都将标记给MOXXI系统中的医师。每个新出现的健康问题均以“潜在”表示，并提示医生说明该健康问题是否有效（是）（N），或者他们是否愿意在以后重新评估其有效性。结果为22,248例患者确定了总计263,527例健康问题，代表891个独特的问题。医疗服务索赔导致发现的大多数问题（77％），其次是电子处方（14％）和单指药物（9％）的治疗指征。医师积极选择评估41.7％（n = 106,950）的健康问题。总体而言，评估的问题中有73％被认为是有效的。 42％来自医疗服务诊断代码，11％来自单一适应症药物，47％来自处方适应症。通过其他主治医师发现的问题中有12％被认为是有效的，而通过研究医师的主张发现的这一比例为28％。结论机构间问题清单的自动化将所有已验证问题的一半以上添加到健康问题清单中，其中12％是由其他医生治疗的疾病所引起的。自动集成现有信息源可及时访问准确且相关的健康问题信息。它还可以加速电子病历系统的使用和使用。

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