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1.

Introduction

The Consolidated Standards for Reporting Trials (CONSORT) were published to standardize reporting and improve the quality of clinical trials. The objective of this study is to assess CONSORT adherence in randomized clinical trials (RCT) of disease specific clinical decision support (CDS).

Methods

A systematic search was conducted of the Medline, EMBASE, and Cochrane databases. RCTs on CDS were assessed against CONSORT guidelines and the Jadad score.

Result

32 of 3784 papers identified in the primary search were included in the final review. 181 702 patients and 7315 physicians participated in the selected trials. Most trials were performed in primary care (22), including 897 general practitioner offices. RCTs assessing CDS for asthma (4), diabetes (4), and hyperlipidemia (3) were the most common. Thirteen CDS systems (40%) were implemented in electronic medical records, and 14 (43%) provided automatic alerts. CONSORT and Jadad scores were generally low; the mean CONSORT score was 30.75 (95% CI 27.0 to 34.5), median score 32, range 21–38. Fourteen trials (43%) did not clearly define the study objective, and 11 studies (34%) did not include a sample size calculation. Outcome measures were adequately identified and defined in 23 (71%) trials; adverse events or side effects were not reported in 20 trials (62%). Thirteen trials (40%) were of superior quality according to the Jadad score (≥3 points). Six trials (18%) reported on long-term implementation of CDS.

Conclusion

The overall quality of reporting RCTs was low. There is a need to develop standards for reporting RCTs in medical informatics.  相似文献   

2.
3.
ObjectiveTo assess usability and usefulness of a machine learning-based order recommender system applied to simulated clinical cases.Materials and Methods43 physicians entered orders for 5 simulated clinical cases using a clinical order entry interface with or without access to a previously developed automated order recommender system. Cases were randomly allocated to the recommender system in a 3:2 ratio. A panel of clinicians scored whether the orders placed were clinically appropriate. Our primary outcome included the difference in clinical appropriateness scores. Secondary outcomes included total number of orders, case time, and survey responses.ResultsClinical appropriateness scores per order were comparable for cases randomized to the order recommender system (mean difference -0.11 order per score, 95% CI: [-0.41, 0.20]). Physicians using the recommender placed more orders (median 16 vs 15 orders, incidence rate ratio 1.09, 95%CI: [1.01-1.17]). Case times were comparable with the recommender system. Order suggestions generated from the recommender system were more likely to match physician needs than standard manual search options. Physicians used recommender suggestions in 98% of available cases. Approximately 95% of participants agreed the system would be useful for their workflows.DiscussionUser testing with a simulated electronic medical record interface can assess the value of machine learning and clinical decision support tools for clinician usability and acceptance before live deployments.ConclusionsClinicians can use and accept machine learned clinical order recommendations integrated into an electronic order entry interface in a simulated setting. The clinical appropriateness of orders entered was comparable even when supported by automated recommendations.  相似文献   

4.
There is wide variability in the use and adoption of recommendations generated by computerized clinical decision support systems (CDSSs) despite the benefits they may bring to clinical practice. We conducted a systematic review to explore the barriers to, and facilitators of, CDSS uptake by physicians to guide prescribing decisions. We identified 58 studies by searching electronic databases (1990–2007). Factors impacting on CDSS use included: the availability of hardware, technical support and training; integration of the system into workflows; and the relevance and timeliness of the clinical messages. Further, systems that were endorsed by colleagues, minimized perceived threats to professional autonomy, and did not compromise doctor-patient interactions were accepted by users. Despite advances in technology and CDSS sophistication, most factors were consistently reported over time and across ambulatory and institutional settings. Such factors must be addressed when deploying CDSSs so that improvements in uptake, practice and patient outcomes may be achieved.  相似文献   

5.
目的:更好地表示临床指南知识,以支持临床决策支持系统的构建。方法:以缺血性卒中为例,在系统梳理临床指南知识表示方法的基础上,提出使用解释节点、数据获取节点、动作节点、复合节点,以及有向边和无向边对指南诊疗流程进行表示,同时考虑实际的电子病历数据格式,设计自然语言处理模块,提高指南与电子病历系统的数据交互能力。结果:在实证研究中,使用8个节点、7条边,以及节点和边中的4个逻辑推理式表示了缺血性卒中患者临床类型判断流程,同时使用9个节点、8条边,以及节点和边中的6个逻辑推理式表示了缺血性卒中急性期的血糖管理,详细说明了临床指南知识表示建模过程。结论:本研究提出的临床指南知识表示方法可以使用节点、边、数据、逻辑推理算法等表示临床指南知识及推理逻辑,以支撑临床决策支持系统的构建。  相似文献   

6.

Background and objective

Accurate and informed prescribing is essential to ensure the safe and effective use of medications in pediatric patients. Computerized clinical decision support (CCDS) functionalities have been embedded into computerized physician order entry systems with the aim of ensuring accurate and informed medication prescribing. Owing to a lack of comprehensive analysis of the existing literature, this review was undertaken to analyze the effect of CCDS implementation on medication prescribing and use in pediatrics.

Materials and methods

A literature search was performed using keywords in PubMed to identify research studies with outcomes related to the implementation of medication-related CCDS functionalities.

Results and discussion

Various CCDS functionalities have been implemented in pediatric patients leading to different results. Medication dosing calculators have decreased calculation errors. Alert-based CCDS functionalities, such as duplicate therapy and medication allergy checking, may generate excessive alerts. Medication interaction CCDS has been minimally studied in pediatrics. Medication dosing support has decreased adverse drug events, but has also been associated with high override rates. Use of medication order sets have improved guideline adherence. Guideline-based treatment recommendations generated by CCDS functionalities have had variable influence on appropriate medication use, with few studies available demonstrating improved patient outcomes due to CCDS use.

Conclusion

Although certain medication-related CCDS functionalities have shown benefit in medication prescribing for pediatric patients, others have resulted in high override rates and inconsistent or unknown impact on patient care. Further studies analyzing the effect of individual CCDS functionalities on safe and effective prescribing and medication use are required.  相似文献   

7.

Objective

To evaluate the impact of a real-time computerized decision support tool in the emergency department that guides medication dosing for the elderly on physician ordering behavior and on adverse drug events (ADEs).

Design

A prospective controlled trial was conducted over 26 weeks. The status of the decision support tool alternated OFF (7/17/06–8/29/06), ON (8/29/06–10/10/06), OFF (10/10/06–11/28/06), and ON (11/28/06–1/16/07) in consecutive blocks during the study period. In patients ≥65 who were ordered certain benzodiazepines, opiates, non-steroidals, or sedative-hypnotics, the computer application either adjusted the dosing or suggested a different medication. Physicians could accept or reject recommendations.

Measurements

The primary outcome compared medication ordering consistent with recommendations during ON versus OFF periods. Secondary outcomes included the admission rate, emergency department length of stay for discharged patients, 10-fold dosing orders, use of a second drug to reverse the original medication, and rate of ADEs using previously validated explicit chart review.

Results

2398 orders were placed for 1407 patients over 1548 visits. The majority (49/53; 92.5%) of recommendations for alternate medications were declined. More orders were consistent with dosing recommendations during ON (403/1283; 31.4%) than OFF (256/1115; 23%) periods (p≤0.0001). 673 (43%) visits were reviewed for ADEs. The rate of ADEs was lower during ON (8/237; 3.4%) compared with OFF (31/436; 7.1%) periods (p=0.02). The remaining secondary outcomes showed no difference.

Limitations

Single institution study, retrospective chart review for ADEs.

Conclusion

Though overall agreement with recommendations was low, real-time computerized decision support resulted in greater acceptance of medication recommendations. Fewer ADEs were observed when computerized decision support was active.  相似文献   

8.

Objective

To identify key principles for establishing a national clinical decision support (CDS) knowledge sharing framework.

Materials and methods

As part of an initiative by the US Office of the National Coordinator for Health IT (ONC) to establish a framework for national CDS knowledge sharing, key stakeholders were identified. Stakeholders'' viewpoints were obtained through surveys and in-depth interviews, and findings and relevant insights were summarized. Based on these insights, key principles were formulated for establishing a national CDS knowledge sharing framework.

Results

Nineteen key stakeholders were recruited, including six executives from electronic health record system vendors, seven executives from knowledge content producers, three executives from healthcare provider organizations, and three additional experts in clinical informatics. Based on these stakeholders'' insights, five key principles were identified for effectively sharing CDS knowledge nationally. These principles are (1) prioritize and support the creation and maintenance of a national CDS knowledge sharing framework; (2) facilitate the development of high-value content and tooling, preferably in an open-source manner; (3) accelerate the development or licensing of required, pragmatic standards; (4) acknowledge and address medicolegal liability concerns; and (5) establish a self-sustaining business model.

Discussion

Based on the principles identified, a roadmap for national CDS knowledge sharing was developed through the ONC''s Advancing CDS initiative.

Conclusion

The study findings may serve as a useful guide for ongoing activities by the ONC and others to establish a national framework for sharing CDS knowledge and improving clinical care.  相似文献   

9.
Objective Clinical decision support (CDS) is essential for delivery of high-quality, cost-effective, and safe healthcare. The authors sought to evaluate the CDS capabilities across electronic health record (EHR) systems.Methods We evaluated the CDS implementation capabilities of 8 Office of the National Coordinator for Health Information Technology Authorized Certification Body (ONC-ACB)-certified EHRs. Within each EHR, the authors attempted to implement 3 user-defined rules that utilized the various data and logic elements expected of typical EHRs and that represented clinically important evidenced-based care. The rules were: 1) if a patient has amiodarone on his or her active medication list and does not have a thyroid-stimulating hormone (TSH) result recorded in the last 12 months, suggest ordering a TSH; 2) if a patient has a hemoglobin A1c result >7% and does not have diabetes on his or her problem list, suggest adding diabetes to the problem list; and 3) if a patient has coronary artery disease on his or her problem list and does not have aspirin on the active medication list, suggest ordering aspirin.Results Most evaluated EHRs lacked some CDS capabilities; 5 EHRs were able to implement all 3 rules, and the remaining 3 EHRs were unable to implement any of the rules. One of these did not allow users to customize CDS rules at all. The most frequently found shortcomings included the inability to use laboratory test results in rules, limit rules by time, use advanced Boolean logic, perform actions from the alert interface, and adequately test rules.Conclusion Significant improvements in the EHR certification and implementation procedures are necessary.  相似文献   

10.
电子病历的临床决策支持   总被引:2,自引:0,他引:2  
目前电子病历正向智能化和知识化发展,其核心价值是满足临床诊疗现场的信息需求及能够有效地改善医生的临床决策支持.电子病历的开放式结构化数据录入使临床描述信息结构化,并使临床医疗和科研活动充分利用这些数据成为可能.  相似文献   

11.
患者药物不良反心(ADEs)对医院医疗质量有重要影响,绝大部分ADEs事件都能通过信息系统进行预防,由于资金投入以及一作流氍的改变,临床电子陕嘱(CPOE)应用遇到了许多困难。上海交通大学附属第六人民医院通过将CPOE与临床决策支持结合,显著降低了医疗差错.通过减少不必要的临床环节节省了大景医疗成本,并且约26个月就可以完全收回系统的投资成本。CPOE应用为医院电了病历应用水平提升提供了重要契机,也为循证医疗提供了重要的信息化发展基础。  相似文献   

12.
13.
ObjectivesThe study sought to assess the clinical performance of a machine learning model aiming to identify unusual medication orders.Materials and MethodsThis prospective study was conducted at CHU Sainte-Justine, Canada, from April to August 2020. An unsupervised machine learning model based on GANomaly and 2 baselines were trained to learn medication order patterns from 10 years of data. Clinical pharmacists dichotomously (typical or atypical) labeled orders and pharmacological profiles (patients’ medication lists). Confusion matrices, areas under the precision-recall curve (AUPRs), and F1 scores were calculated.ResultsA total of 12 471 medication orders and 1356 profiles were labeled by 25 pharmacists. Medication order predictions showed a precision of 35%, recall (sensitivity) of 26%, and specificity of 97% as compared with pharmacist labels, with an AUPR of 0.25 and an F1 score of 0.30. Profile predictions showed a precision of 49%, recall of 75%, and specificity of 82%, with an AUPR of 0.60, and an F1 score of 0.59. The model performed better than the baselines. According to the pharmacists, the model was a useful screening tool, and 9 of 15 participants preferred predictions by medication, rather than by profile.DiscussionPredictions for profiles had higher F1 scores and recall compared with medication order predictions. Although the performance was much better for profile predictions, pharmacists generally preferred medication order predictions.ConclusionsBased on the AUPR, this model showed better performance for the identification of atypical pharmacological profiles than for medication orders. Pharmacists considered the model a useful screening tool. Improving these predictions should be prioritized in future research to maximize clinical impact.  相似文献   

14.
国内外医疗决策支持系统研究热点   总被引:1,自引:0,他引:1       下载免费PDF全文
目的:了解医疗决策支持系统领域的研究现状并预测未来发展方向,为相关学者选择研究方向时提供参考和依据。方法:以PubMed数据库中文献记录为样本,用医学主题词(MeSh)制定检索策略进行检索,获取关于医疗决策支持系统研究主题的相关文献,用BICOMB软件对文献中主要主题词进行频次统计并截取高频词,形成高频主题词-论文矩阵。对论文中的高频主题词利用gCLUTO软件对进行聚类分析,找出当前医疗决策支持系统领域的研究方向。结果:当前医疗决策支持系统的研究热点为临床决策支持系统具体构建技术的研究和临床决策支持系统社会学相关问题的研究。结论:医疗决策支持系统是一个新兴并值得重点深入关注的领域,以BICOMB和gCLUTO软件为基础的文献计量学方法,能够给临床医学及临床信息管理领域的研究者提供全面信息及热点参考。  相似文献   

15.

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.  相似文献   

16.

Background

For eye diseases, such as glaucoma and age-related macular degeneration (ARMD), involved in long-term degeneration procedure, longitudinal comparison of retinal images is a common step for reliable diagnosis of these kinds of diseases.

Aims

To provide a retinal image registration approach for longitudinal retinal image alignment and comparison.

Method

Two image registration solutions were proposed for facing different image qualities of retinal images to make the registration methods more robust and feasible in a clinical application system.

Results

Thirty pairs of longitudinal retinal images were used for the registration test. The experiments showed both solutions provided good performance for the accurate image registrations with efficiency.

Conclusion

We proposed a set of retinal image registration solutions for longitudinal retinal image observation and comparison targeting a clinical application environment.  相似文献   

17.

Objective

Individual users’ attitudes and opinions help predict successful adoption of health information technology (HIT) into practice; however, little is known about pediatric users’ acceptance of HIT for medical decision-making at the point of care.

Materials and methods

We wished to examine the attitudes and opinions of pediatric users’ toward the Child Health Improvement through Computer Automation (CHICA) system, a computer decision support system linked to an electronic health record in four community pediatric clinics. Surveys were administered in 2011 and 2012 to all users to measure CHICA''s acceptability and users’ satisfaction with it. Free text comments were analyzed for themes to understand areas of potential technical refinement.

Results

70 participants completed the survey in 2011 (100% response rate) and 64 of 66 (97% response rate) in 2012. Initially, satisfaction with CHICA was mixed. In general, users felt the system held promise; however various critiques reflected difficulties understanding integrated technical aspects of how CHICA worked, as well as concern with the format and wording on generated forms for families and users. In the subsequent year, users’ ratings reflected improved satisfaction and acceptance. Comments also reflected a deeper understanding of the system''s logic, often accompanied by suggestions on potential refinements to make CHICA more useful at the point of care.

Conclusions

Pediatric users appreciate the system''s automation and enhancements that allow relevant and meaningful clinical data to be accessible at point of care. Understanding users’ acceptability and satisfaction is critical for ongoing refinement of HIT to ensure successful adoption into practice.  相似文献   

18.
罕见病的发病率极低,但其总体患病人数不少。罕见病引起的病变后果严重,对患者及其家庭和社会造成了沉重负担。虽然当前利用基因测序技术、临床决策支持系统结合人工智能技术辅助临床进行遗传病诊断的研究火热,但临床诊断罕见病仍是非常大的技术挑战。本文简要综述了罕见病临床决策系统,旨在分析人工智能技术在罕见病中的发展现状和挑战。  相似文献   

19.
Objective To assess the effectiveness of computer-aided clinical decision support systems (CDSS) in improving antibiotic prescribing in primary care.Methods A literature search utilizing Medline (via PubMed) and Embase (via Embase) was conducted up to November 2013. Randomized controlled trials (RCTs) and cluster randomized trials (CRTs) that evaluated the effects of CDSS aiming at improving antibiotic prescribing practice in an ambulatory primary care setting were included for review. Two investigators independently extracted data about study design and quality, participant characteristics, interventions, and outcomes.Results Seven studies (4 CRTs, 3 RCTs) met our inclusion criteria. All studies were performed in the USA. Proportions of eligible patient visits that triggered CDSS use varied substantially between intervention arms of studies (range 2.8–62.8%). Five out of seven trials showed marginal to moderate statistically significant effects of CDSS in improving antibiotic prescribing behavior. CDSS that automatically provided decision support were more likely to improve prescribing practice in contrast to systems that had to be actively initiated by healthcare providers.Conclusions CDSS show promising effectiveness in improving antibiotic prescribing behavior in primary care. Magnitude of effects compared to no intervention, appeared to be similar to other moderately effective single interventions directed at primary care providers. Additional research is warranted to determine CDSS characteristics crucial to triggering high adoption by providers as a perquisite of clinically relevant improvement of antibiotic prescribing.  相似文献   

20.
ObjectivesElectronic health record-based clinical decision support (CDS) has the potential to improve health outcomes. This systematic review investigates the design, effectiveness, and economic outcomes of CDS targeting several common chronic diseases.Material and MethodsWe conducted a search in PubMed (Medline), EBSCOHOST (CINAHL, APA PsychInfo, EconLit), and Web of Science. We limited the search to studies from 2011 to 2021. Studies were included if the CDS was electronic health record-based and targeted one or more of the following chronic diseases: cardiovascular disease, diabetes, chronic kidney disease, hypertension, and hypercholesterolemia. Studies with effectiveness or economic outcomes were considered for inclusion, and a meta-analysis was conducted.ResultsThe review included 76 studies with effectiveness outcomes and 9 with economic outcomes. Of the effectiveness studies, 63% described a positive outcome that favored the CDS intervention group. However, meta-analysis demonstrated that effect sizes were heterogenous and small, with limited clinical and statistical significance. Of the economic studies, most full economic evaluations (n = 5) used a modeled analysis approach. Cost-effectiveness of CDS varied widely between studies, with an estimated incremental cost-effectiveness ratio ranging between USD$2192 to USD$151 955 per QALY.ConclusionWe summarize contemporary chronic disease CDS designs and evaluation results. The effectiveness and cost-effectiveness results for CDS interventions are highly heterogeneous, likely due to differences in implementation context and evaluation methodology. Improved quality of reporting, particularly from modeled economic evaluations, would assist decision makers to better interpret and utilize results from these primary research studies.RegistrationPROSPERO (CRD42020203716)  相似文献   

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