Sinha Shyamashree, Jensen Mark, Mullin Sarah, Elkin Peter L
Department of Biomedical Informatics, University at Buffalo State University of New York.
Department of Anesthesiology, University at Buffalo State University of New York.
Online J Public Health Inform. 2017 Sep 8;9(2):e193. doi: 10.5210/ojphi.v9i2.8034. eCollection 2017.
Background Prescription opioid pain medication overuse, misuse and abuse have been a significant contributing factor in the opioid epidemic. The rising death rates from opioid overdose have caused healthcare practitioners and researchers to work on optimizing pain therapy and limiting the prescriptions for pain medications. The state of New York has implemented a prescription drug monitoring program(PDMP), amended public health law to limit the prescription of opioids for acute pain and utilized the resources of the state and county health departments to help in curbing this epidemic. The recent publication of guidelines for prescription opioids from CDC [1] and ASIPP (American Society of Interventional pain practitioners) have independently reviewed literature and found good evidence of limiting opioid prescription for acute and chronic non cancer pain. [2] Method Over the last decade, advanced technology has increased the complexity of electronic health records systems leading to the development of Clinical Decision Support Systems (CDSS) to aid the work flow of healthcare providers. There are several systematic reviews on the effectiveness and utility of CDSSs. A common consensus is that commercially and locally developed CDSS are effective in improving patient measures while actual workload improvement and efficient cost-cutting measure are not significantly improved by CDSS. Patient provider involvement in developing CDSS is a determinant of its success and utilization rates. [7] Therefore, a plug and play form of CDSS which can be implemented from an external platform through secure channels would be more effective. Design The Health Level Seven's (HL7) open licensed interoperability standard Fast Health Interoperability Resources (FHIR) has a platform, Substitutable Medical Applications and Reusable Technologies (SMART) for CDSS app development by a third party. [3] We adopted these open source standard to plan to develop an app for accessible and efficient implementation of the recently published guidelines for management of pain with prescription opioid medications.
背景 处方阿片类镇痛药的过度使用、误用和滥用一直是阿片类药物流行的一个重要促成因素。阿片类药物过量致死率的上升促使医疗从业者和研究人员致力于优化疼痛治疗并限制镇痛药的处方。纽约州实施了处方药监测计划（PDMP），修订了公共卫生法以限制阿片类药物用于急性疼痛的处方，并利用州和县级卫生部门的资源来帮助遏制这一流行趋势。疾病控制与预防中心（CDC）[1]和美国介入性疼痛从业者协会（ASIPP）最近发布的阿片类药物处方指南各自独立回顾了文献，并发现有充分证据表明应限制阿片类药物用于急性和慢性非癌性疼痛的处方。[2] 方法 在过去十年中，先进技术增加了电子健康记录系统的复杂性，从而促使临床决策支持系统（CDSS）的发展以辅助医疗服务提供者的工作流程。关于CDSS有效性和实用性有多项系统评价。一个普遍的共识是，商业开发和本地开发的CDSS在改善患者指标方面是有效的，而CDSS在实际工作量改善和有效成本削减措施方面并未得到显著改善。患者和提供者参与CDSS的开发是其成功和利用率的一个决定因素。[7] 因此，一种可以通过安全渠道从外部平台实施的即插即用形式的CDSS会更有效。 设计 健康级别七（HL7）的开放许可互操作性标准快速健康互操作性资源（FHIR）有一个平台，即可替代医疗应用和可重复使用技术（SMART），用于第三方开发CDSS应用程序。[3]我们采用这些开源标准，计划开发一个应用程序，以便能够方便且高效地实施最近发布的处方阿片类药物疼痛管理指南。
