一项混合方法研究探讨了护理数据的优点、缺点和利用:EPI-CAL早期精神病学习卫生保健网络的发现。

IF 3.6 2区 医学 Q1 PSYCHIATRY
Sabrina Ereshefsky , Regina Gemignani , Mark Savill , Katherine C. Sanford , Lindsay M. Banks , Valerie L. Tryon , Kathleen E. Nye , Katherine M. Pierce , Madison J. Miles , Chelyah Miller , Khanh Linh H. Nguyen , Nitasha Sharma , Merissa Kado-Walton , Christopher K. Hakusui , Leigh Smith , Viviana E. Padilla , Amanda P. McNamara , Maliha Safdar , Andrew J. Padovani , Rachel L. Loewy , Tara A. Niendam
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引用次数: 0

摘要

利用在常规护理中收集的数据为治疗提供信息是学习型卫生系统(LHS)的一个关键特征。在本研究中,我们探讨了服务使用者和提供者在早期精神病(EP)专科护理环境中采用基于测量的护理(MBC)的经验。在加州早期精神病干预网络(EPI-CAL)的18个项目中,对32名提供者和12名服务用户进行了定性访谈。这些结果与Beehive的定量数据、EPI-CAL的数据收集和综述应用进行了比较。关于MBC在EP中的临床益处,确定了三个主要主题-支持安全监测和反应,评估过程和心理治疗的提供。在直接临床护理之外,Beehive被认为支持临床监督和外部报告,而服务用户报告数据收集促进了自我反思。从23个EP项目中收集的定量Beehive应用数据中,安全警报系统的高利用率是显而易见的(总共349个警报,其中338个[96.85%]在中位数2.03天内得到解决)。然而,服务用户的关键调查数据仅在32.22%(441例中的142例)的案例中由指定的提供者审查。虽然供应商和服务用户看到了Beehive的许多好处,但警报系统之外的利用率却高度不一致。展望未来,有必要进一步考虑如何最好地支持EP提供者在护理中始终如一地使用数据,以最大限度地发挥LHS方法的效用,并对结果产生积极影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A mixed-methods study exploring the benefits, drawbacks, and utilization of data in care: Findings from the EPI-CAL early psychosis learning health care network
Using data collected in routine care delivery to inform treatment is a key feature of a learning health system (LHS). In this study, we explored the experiences of service users and providers adopting measurement-based care (MBC) in early psychosis (EP) specialty care settings. Qualitative interviews were conducted with 32 providers and 12 service users across 18 programs in the Early Psychosis Intervention Network of California (EPI-CAL). These findings were compared with quantitative data from Beehive, EPI-CAL's data collection and review application. Regarding the clinical benefits of MBC in EP, three broad themes were identified – supporting safety monitoring and response, the assessment process, and delivery of psychotherapy. Powered by Editorial Manager® and ProduXion Manager® from Aries Systems Corporation Outside of direct clinical care, Beehive was considered to support clinical supervision and external reporting, while service users reported data collection facilitated selfreflection. In the quantitative Beehive application data collected from 23 EP programs, high utilization of the safety alert system was evident (349 alerts in total, of which 338 [96.85 %] were resolved at a median of 2.03 days). However, service users' key survey data was only reviewed by assigned providers in 32.22 % (142 of 441) of cases. While providers and service users saw many benefits to Beehive, utilization was highly inconsistent outside of the alert system. Going forward, further consideration of how best to support EP providers to consistently use data in care is necessary to maximize the utility of the LHS approach and positively impact outcomes.
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来源期刊
Schizophrenia Research
Schizophrenia Research 医学-精神病学
CiteScore
7.50
自引率
8.90%
发文量
429
审稿时长
10.2 weeks
期刊介绍: As official journal of the Schizophrenia International Research Society (SIRS) Schizophrenia Research is THE journal of choice for international researchers and clinicians to share their work with the global schizophrenia research community. More than 6000 institutes have online or print (or both) access to this journal - the largest specialist journal in the field, with the largest readership! Schizophrenia Research''s time to first decision is as fast as 6 weeks and its publishing speed is as fast as 4 weeks until online publication (corrected proof/Article in Press) after acceptance and 14 weeks from acceptance until publication in a printed issue. The journal publishes novel papers that really contribute to understanding the biology and treatment of schizophrenic disorders; Schizophrenia Research brings together biological, clinical and psychological research in order to stimulate the synthesis of findings from all disciplines involved in improving patient outcomes in schizophrenia.
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