基于人工智能的临床决策支持系统早期临床评估的透明化报告

随着人工智能（AI）在医学领域的广泛应用,越来越多基于AI的临床决策支持系统应用于临床诊断与筛查等。早期临床评估对于评价基于AI临床决策支持系统的临床性能、安全性和人为因素具有重要意义,有利于为进一步的大规模临床试验奠定基础,但相关临床研究报告的透明度和完整性尚待提高。2022年5月,基于AI的临床决策支持系统早期临床评估报告指南（DECIDE-AI）正式在线发表。本文将结合DECIDE-AI中的AI相关报告项目及相关文献,探讨基于AI的临床决策支持系统早期临床评估的透明化报告,以期帮助我国系统开发者和研究者更好地理解与应用相关指南,提高基于AI的临床决策支持系统早期临床评估报告的透明度。     

基于案例库构建中医临床决策支持系统

通过分析中医学思维特点、传统的循证医学模式在中医应用的困难以及大脑的认知特点,提出了建立中医全案例库以及利用信息化在中医案例库基础上形成临床决策支持系统的思路。认为中医全案例库必须具有完整性、可学习性、真实有效性及需包括部分误诊误治案例。随着病例库的病例不断完善和不同医者的反复验证,可构建基于案例决策的中医病案库支持下的临床辅助决策系统。而随着人工智能基于自然语言、神经网络、深度学习等能力的不断提高及中医实践者的反复临床验证,中医临床决策系统的准确性将不断提升。     

语义互操作标准在临床决策支持系统中的应用

介绍临床决策支持系统互操作研究基本情况,基于语义互操作标准类别、临床决策支持系统开发与部署的功能需求,对临床决策支持系统中的标准进行分类,探讨各类标准在临床决策支持系统中的应用。     

面向心律失常疾病的临床决策支持系统交互性研究与实现

目的/意义 针对当前临床决策支持系统使用过程中存在的问题,提出界面设计原则并将其应用于心律失常疾病临床决策支持系统建设中。方法/过程 从交互设计角度,针对可解释性、时效性、可用性、相关性、尊重性和循证性6个维度,提出界面设计原则。选取心律失常疾病决策支持作为临床场景,设计临床决策支持系统交互界面原型,阐述界面功能、信息功能、交互功能设计与实现过程。结果/结论 本研究提出的界面设计原则可有效缓解6类问题,经论证具有应用于心律失常疾病临床决策支持原型系统的可行性以及可泛化性,可用于指导多种疾病辅助诊疗工具的交互设计。     

基于临床决策支持系统的静脉血栓防治系统构建与应用

介绍国内静脉血栓栓塞症(Venous Thromboembolism,VTE)防治工作现状,阐述基于临床决策支持系统的智能化VTE防治系统设计思路、应用实践,分析系统建设成效,指出该系统有助于提高临床VTE防治效率和准确性。     

基于临床决策支持系统与知识库的临床数据中心的研究与应用

临床数据中心作为电子病历（EMR）的重要组成部分,是目前医院信息化建设的重点,也代表着今后医疗信息化应用的一个方向。建设临床数据中心需要有临床决策支持系统与临床知识库的支撑,这也是进一步深化EMR系统功能的需要。本文结合我国医疗信息化建设的发展现状,主要对临床决策支持系统与知识库在数据中心建设中的应用,以及存在的问题进行了分析。     

论医疗决策支持系统

介绍了医疗决策支持系统的基本概念、决策支持系统的种类、该系统辅助医疗决策的途径、医疗决策支持系统所运用的知识、医疗决策支持系统中采用的基本方法、以及一个决策支持系统的例子。呼吁国内医疗机构在开发医疗信息处理系统时重视对医疗决策支持系统的开发。     

临床实验室业务管理与决策支持系统开发及应用

阐述以实验室业务数据为基础的区域化临床实验室业务管理与决策支持系统的架构设计、功能设计及应用评价,指出该系统应用能够为实验室精细化管理、科学决策提供数据支撑。     

嵌入式临床智能决策支持系统设计与中医临床知识服务研究

随着医院信息化水平的不断提高,在医院信息系统中开展中医药知识服务不仅具有可行性,且对中医药临床科研的推动极具潜力。研究通过构建嵌入式临床智能决策支持系统与中医临床知识服务平台的开发,提供嵌入电子病历的实时临床决策支持和与临床病例高度相似的典型案例匹配,以及基于临床临床情景的诊疗规范、名家经验、名医名方、临床证据等中医临床知识服务。     

电子病历系统

电子病历系统(Electronic Medical RecordEMR),美国国立医学研究所将定义为:EMR是基于一个特定系统的电子化病人记录,该系统提供用户访问完整准确的数据、警示、提示和临床决策支持系统的能力。     

Clinical decision support with automated text processing for cervical cancer screening

Objective

To develop a computerized clinical decision support system (CDSS) for cervical cancer screening that can interpret free-text Papanicolaou (Pap) reports.

Materials and Methods

The CDSS was constituted by two rulebases: the free-text rulebase for interpreting Pap reports and a guideline rulebase. The free-text rulebase was developed by analyzing a corpus of 49 293 Pap reports. The guideline rulebase was constructed using national cervical cancer screening guidelines. The CDSS accesses the electronic medical record (EMR) system to generate patient-specific recommendations. For evaluation, the screening recommendations made by the CDSS for 74 patients were reviewed by a physician.

Results and Discussion

Evaluation revealed that the CDSS outputs the optimal screening recommendations for 73 out of 74 test patients and it identified two cases for gynecology referral that were missed by the physician. The CDSS aided the physician to amend recommendations in six cases. The failure case was because human papillomavirus (HPV) testing was sometimes performed separately from the Pap test and these results were reported by a laboratory system that was not queried by the CDSS. Subsequently, the CDSS was upgraded to look up the HPV results missed earlier and it generated the optimal recommendations for all 74 test cases.

Limitations

Single institution and single expert study.

Conclusion

An accurate CDSS system could be constructed for cervical cancer screening given the standardized reporting of Pap tests and the availability of explicit guidelines. Overall, the study demonstrates that free text in the EMR can be effectively utilized through natural language processing to develop clinical decision support tools.     

Use of a Personal Digital Assistant for Managing Antibiotic Prescribing for Outpatient Respiratory Tract Infections in Rural Communities

ObjectiveTo assess the acceptability and usage of a standalone personal digital assistant (PDA)-based clinical decision-support system (CDSS) for the diagnosis and management of acute respiratory tract infections (RTIs) in the outpatient setting.DesignObservational study performed as part of a larger randomized trial in six rural communities in Utah and Idaho from January 2002 to March 2004. Ninety-nine primary care providers received a PDA-based CDSS for use at the point-of-care, and were asked to use the tool with at least 200 patients with suspected RTIs.MeasurementsClinical data were collected electronically from the devices at periodic intervals. Providers also completed an exit questionnaire at the end of the study period.ResultsProviders logged 14,393 cases using the CDSS, the majority of which (n=7624; 53%) were from family practitioners. Overall adherence with CDSS recommendations for the five most common diagnoses (pharyngitis, otitis media, sinusitis, bronchitis, and upper respiratory tract infection) was 82%. When antibiotics were prescribed (53% of cases), adherence with the CDSS-recommended antibiotic was high (76%). By logistic regression analysis, the odds of adherence with CDSS recommendations increased significantly with each ten cases completed (P=0.001). Questionnaire respondents believed the CDSS was easy to use, and most (44/65; 68%) did not believe it increased their encounter time with patients, regardless of prior experience with PDAs.ConclusionA standalone PDA-based CDSS for acute RTIs used at the point-of-care can encourage better outpatient antimicrobial prescribing practices and easily gather a rich set of clinical data.     

Research and applications: Formative evaluation of the accuracy of a clinical decision support system for cervical cancer screening

Objectives

We previously developed and reported on a prototype clinical decision support system (CDSS) for cervical cancer screening. However, the system is complex as it is based on multiple guidelines and free-text processing. Therefore, the system is susceptible to failures. This report describes a formative evaluation of the system, which is a necessary step to ensure deployment readiness of the system.

Materials and methods

Care providers who are potential end-users of the CDSS were invited to provide their recommendations for a random set of patients that represented diverse decision scenarios. The recommendations of the care providers and those generated by the CDSS were compared. Mismatched recommendations were reviewed by two independent experts.

Results

A total of 25 users participated in this study and provided recommendations for 175 cases. The CDSS had an accuracy of 87% and 12 types of CDSS errors were identified, which were mainly due to deficiencies in the system''s guideline rules. When the deficiencies were rectified, the CDSS generated optimal recommendations for all failure cases, except one with incomplete documentation.

Discussion and conclusions

The crowd-sourcing approach for construction of the reference set, coupled with the expert review of mismatched recommendations, facilitated an effective evaluation and enhancement of the system, by identifying decision scenarios that were missed by the system''s developers. The described methodology will be useful for other researchers who seek rapidly to evaluate and enhance the deployment readiness of complex decision support systems.     

Clinical decision support system,using expert consensus-derived logic and natural language processing,decreased sedation-type order errors for patients undergoing endoscopy

ObjectiveDetermination of appropriate endoscopy sedation strategy is an important preprocedural consideration. To address manual workflow gaps that lead to sedation-type order errors at our institution, we designed and implemented a clinical decision support system (CDSS) to review orders for patients undergoing outpatient endoscopy.Materials and MethodsThe CDSS was developed and implemented by an expert panel using an agile approach. The CDSS queried patient-specific historical endoscopy records and applied expert consensus-derived logic and natural language processing to identify possible sedation order errors for human review. A retrospective analysis was conducted to evaluate impact, comparing 4-month pre-pilot and 12-month pilot periods.Results22 755 endoscopy cases were included (pre-pilot 6434 cases, pilot 16 321 cases). The CDSS decreased the sedation-type order error rate on day of endoscopy (pre-pilot 0.39%, pilot 0.037%, Odds Ratio = 0.094, P-value < 1e-8). There was no difference in background prevalence of erroneous orders (pre-pilot 0.39%, pilot 0.34%, P = .54).DiscussionAt our institution, low prevalence and high volume of cases prevented routine manual review to verify sedation order appropriateness. Using a cohort-enrichment strategy, a CDSS was able to reduce number of chart reviews needed per sedation-order error from 296.7 to 3.5, allowing for integration into the existing workflow to intercept rare but important ordering errors.ConclusionA workflow-integrated CDSS with expert consensus-derived logic rules and natural language processing significantly reduced endoscopy sedation-type order errors on day of endoscopy at our institution.     

基于统一信息模型的CDSS与EMR接口技术研究与实现

临床决策支持系统(CDSS)的实施和应用具有重要的临床意义,也是医院电子病历系统(EMR)应用水平评价的重要内容。由于CDSS和EMR接口开发的困难,CDSS的部署成本高、效率低,阻碍了CDSS的广泛应用。本文在分析接口开发挑战的基础上,提出了一种基于统一信息模型的接口实现技术,并在临床案例中验证了方法的可行性。     

构建临床决策支持系统的良性生态

在电子病历得到应用后,临床决策支持系统(CDSS)是进一步提升医疗安全与质量的重要手段。但是当前CDSS的应用却遇到许多困难。文章根据我国当前电子病历应用水平评估的情况归纳了临床决策支持应用的6种类型和5种常见的应用场景,分析了技术上促进CDSS应用需要解决的4个主要问题,提出了以优先解决电子病历系统与CDSS接口的标准化作为入手推动临床决策支持应用的方案。通过扩大CDSS的应用带动知识描述标准的建立,进而引导市场化方式发展通用的知识库,由此形成临床决策支持系统良性发展的生态。     

Assessing the Sensibility of Two Clinical Decision Support Systems

Clinicians in Emergency Medicine (EM) are increasingly exposed to guidelines and treatment recommendations. To help access and recall these recommendations, electronic Clinical Decision Support Systems (CDSS) have been developed. This study examined the use and sensibility of two CDSS designed for emergency physicians. CDDS for community acquired pneumonia (CAP) and neutropenic fever (NF) were developed by multidisciplinary teams and have been accessed via an intranet-based homepage (eCPG) for several years. Sensibility is a term coined by Feinstein that describes common sense aspects of a survey instrument. It was modified by emergency researchers to include four main headings: (1) Appropriateness; (2) Objectivity; (3) Content; and (4) Discriminative Power. Sensibility surveys were developed using an iterative approach for both the CAP and NF CDSS and distributed to all 25 emergency physicians at one Canadian site. The overall response rate was 88%. Respondents were 88% male and 83% were less than 40; all were attending EM physicians with specialty designations. A number reported never having used the CAP (21%) or NF (33%) CDSS; 54% (CAP) and 21% (NF) of respondents had used the respective CDSS less than 10 times. Overall, both CDSS were rated highly by users with a mean response of 4.95 (SD 0.56) for CAP and 5.62 (SD 0.62) for NF on a seven-point Likert scale. The majority or respondents (CAP 59%, NF 80%) felt that the NF CDSS was more likely than the CAP CDSS to decrease the chances of making a medical error in medication dose, antibiotic choice or patient disposition (4.61 vs. 5.81, p=0.008). Despite being in place for several years, CDSS for CAP and NF are not used by all EM clinicians. Users were generally satisfied with the CDSS and felt that the NF was more likely than the CAP CDSS to decrease medical errors. Additional research is required to determine the barriers to CDSS use.     

本体在糖尿病临床决策支持系统中的应用

基于电子健康系统的临床决策支持系统（clinical decision support system, CDSS）可以辅助基层医生进行临床决策，提高诊疗效率。其中利用本体构建CDSS的医学知识库和患者数据使CDSS的推理过程和决策结果具有可解释性。本文就糖尿病治疗领域的相关本体及基于本体的CDSS的进展与挑战进行综述。首先，阐明我国糖尿病诊疗的现状与挑战为亟需提高医疗服务效率与质量；在介绍本体的相关知识后，概述使用本体构建CDSS的框架、方法及特点；然后综述国内外糖尿病治疗领域的本体及基于本体的CDSS的案例，总结其构建方法及特点；最后提出该领域的展望:将循证医学与本体相融合，构建可信的临床推荐体系是目前CDSS的发展重点。