Interface Design for Evaluation of Clinical Decision Support for Quality Improvement

Clinical Decision Support Tools

Clinical decision support software (CDSS) has been increasingly implemented to assist improved prescribing practice. Reviews and studies report generally positive results regarding prescribing changes and, to a lesser extent, patient outcomes. Little information is available, however, concerning the use of CDSS in community pharmacy practice. Given the apparent paucity of publications examining this topic, we conducted a review to determine whether CDSS in community pharmacy practice can improve medication use and patient outcomes. A literature search of articles on CDSS relevant to community pharmacy and published between 1 January 2005 and 21 October 2013 was undertaken. Articles were included if the healthcare setting was community pharmacy and the article indicated that pharmacy use of CDSS was part of the study intervention. Eight studies were found which assessed counselling, selected drug interactions, inappropriate prescribing and under-prescribing. One study was halted due to insufficient data collection. Six studies showed statistically significant improvements in the measured outcomes: increased patient counselling, 31% reduced frequency of drug-drug interactions (DDIs), reduced frequency of inappropriate medications in the elderly (2·2-1·8% patients) and in pregnant women (5·5-2·9% patients), and increased pharmacists' interventions for under-prescribed low-dose aspirin (1·74 vs. 0·91 per 100 patients with type 2 diabetes) and over-prescribed high-dose proton-pump inhibitors (PPIs) (1·67 vs. 0·17 interventions per 100 high-dose PPI prescriptions). Most studies showed improved prescribing practice, via direct communication between pharmacists and doctors or indirectly via patient education. Factors limiting the impact of improved prescribing included alert fatigue and clinical inertia. No study investigated patient outcomes and little investigation had been undertaken on how CDSS could be best implemented. Few studies have been undertaken in community pharmacy practice, and based on the positive findings reported, further research should be directed in this area, including investigation of patient outcomes.

Association of Clinical Guidelines and Decision Support with Computed Tomography Use in Pediatric Mild Traumatic Brain Injury

Chronic disease may lead to life threatening health complications like heart disease, stroke, and diabetes that diminish the quality of life. CDSS (Clinical Decision Support System) helps physician in effective utilization of patient's clinical information at the time of diagnosis and medication. This paper points out the importance of social media and interaction integration in existing Smart CDSS for chronic diseases. The proposed system monitors health conditions, emotions and interests of patients from patients' tweets, trajectory and email analysis. We extract keywords, concepts and sentiments from patient's tweets data. Trajectory analysis identifies the focused activities after considering imperative location and semantic tags. Email analysis finds interesting patterns and communication trends from daily routine of patient. All these outputs are supplied to Smart CDSS into vMR (virtual Medical Record) format through social media adapter. This helps the health practitioners to understand the behavior and lifestyle of patients for better decision making about treatment. Consequently, patients can get continuous relevant recommendations from Smart CDSS based on their personalized profile. To verify and validate the working of proposed methodology, we have implemented a proof of concept prototype that reflects its complete working with potential outcomes.

Introduction/Background/Significance: Clinical decision support systems (CDSS) use information and communication technologies developed through evidenced-based methodologies such as algorithms and logical regression to provide relevant knowledge and information to providers to assist with the decision making process to support the health care and clinical outcomes of the patient.Common formats of CDSS include alerts and 'pop-up' messages.The overall success of the CDSS depends on five stages.Each stage builds on the previous stage and the lowest two factors impacting success include firing rates and override rates.This literature review seeks to evaluate the relationship between the two factors of alert fatigue and alert overrides to the success of CDSS. Problem/Purpose Statements:The problem is that electronic medical record (EMR) systems which actively depend on CDSS generally have a large quantity of alerts and these alerts have been shown to create alert fatigue for providers.Given the significance of alert fatigue and the potential negative outcomes that result from alert overrides, the aim of this systematic literature review is to answer three questions: Does the use of CDSS when used in the care of a patient improve clinical outcomes?,Is there a threshold with the level or quantity of alerts that has been shown to create provider alert fatigue?, Is there a relationship between the number of CDSS alert messages presentations and the frequency rate of alert overrides? Methods:The literature search focused on two databases using key search terms and Boolean operators.Sixteen articles (n = 16) were utilized after the inclusion and exclusion criteria were applied, abstract and full-text reviews were assessed for significance to the research purpose and quality assessments were completed.A data collection matrix was used to organize the data.Results/Findings: Several benefits were found to support the use of CDSS to support clinical outcomes.Precautions and possible consequences were also identified.Several theories were identified which explain the alert fatigue phenomenon.Several recommendations for both CDSS and alert design and implementation were identified.Discussion/Conclusions: Subgroup analysis did not provide enough evidence at this time to conclude that quantity alone can explain the relationship between CDSS alert messages presentations and the frequency of alert overrides.Best practice guidelines and recommendations are provided for CDSS and alert design and implementation as well as recommendations for the use of CDSS in conjunction with health information technologies (HITs) to support decision making processes.This literature review has implications for designers, implementation specialists, system analysts and additional health informatics (HI) professionals.Additionally, it adds value to the existing knowledge base surrounding CDSS while presenting areas for further research to examine additional heterogeneous factors which may impact the success of CDSS.

Clinical decision support systems (CDSSs) provides vital information for managing patients by advising clinicians through an alert or reminders about adverse events and medication errors. Clinicians receive a high number of alerts, resulting in alert override and workflow disruptions. A systematic review was carried out to identify factors affecting CDSS alert appropriateness in supporting clinical workflows using a recently introduced framework. The review findings identified several influencing factors of CDSS alert appropriateness including: technology (usability, alert presentation, workload and data entry), human (training, knowledge and skills, attitude and behavior), organization (rules and regulation, privacy and security) and process (waste, delay, tuning and optimization). The findings can be used to guide the design of CDSS alert and minimise potential safety hazards associated with CDSS use.

Multimorbidity, the presence of more than one condition in a single individual, is a global health issue in primary care. Multimorbid patients tend to have a poor quality of life and suffer from a complicated care process. Clinical decision support systems (CDSSs) and telemedicine are the common information and communication technologies that have been used to reduce the complexity of patient management. However, each element of telemedicine and CDSSs is often examined separately and with great variability. Telemedicine has been used for simple patient education as well as more complex consultations and case management. For CDSSs, there is variability in data inputs, intended users, and outputs. Thus, there are several gaps in knowledge about how to integrate CDSSs into telemedicine and to what extent these integrated technological interventions can help improve patient outcomes for those with multimorbidity. Our aims were to (1) broadly review system designs for CDSSs that have been integrated into each function of telemedicine for multimorbid patients in primary care, (2) summarize the effectiveness of the interventions, and (3) identify gaps in the literature. An online search for literature was conducted up to November 2021 on PubMed, Embase, CINAHL, and Cochrane. Searching from the reference lists was done to find additional potential studies. The eligibility criterion was that the study focused on the use of CDSSs in telemedicine for patients with multimorbidity in primary care. The system design for the CDSS was extracted based on its software and hardware, source of input, input, tasks, output, and users. Each component was grouped by telemedicine functions: telemonitoring, teleconsultation, tele-case management, and tele-education. Seven experimental studies were included in this review: 3 randomized controlled trials (RCTs) and 4 non-RCTs. The interventions were designed to manage patients with diabetes mellitus, hypertension, polypharmacy, and gestational diabetes mellitus. CDSSs can be used for various telemedicine functions: telemonitoring (eg, feedback), teleconsultation (eg, guideline suggestions, advisory material provisions, and responses to simple queries), tele-case management (eg, sharing information across facilities and teams), and tele-education (eg, patient self-management). However, the structure of CDSSs, such as data input, tasks, output, and intended users or decision-makers, varied. With limited studies examining varying clinical outcomes, there was inconsistent evidence of the clinical effectiveness of the interventions. Telemedicine and CDSSs have a role in supporting patients with multimorbidity. CDSSs can likely be integrated into telehealth services to improve the quality and accessibility of care. However, issues surrounding such interventions need to be further explored. These issues include expanding the spectrum of medical conditions examined; examining tasks of CDSSs, particularly for screening and diagnosis of multiple conditions; and exploring the role of the patient as the direct user of the CDSS.

ObjectivesThe Clinical Decision Support System (CDSS), which analyzes and uses electronic health records (EHR) for medical care, pursues patient-centered medical care. It is necessary to establish the CDSS in Korean medical services for objectification and standardization. For this purpose, analyses were performed on the points to be followed for CDSS implementation with a focus on herbal medicine prescription.MethodsTo establish the CDSS in the prescription of Traditional Korean Medicine, the current prescription practices of Traditional Korean Medicine doctors were analyzed. We also analyzed whether the prescription support function of the electronic chart was implemented. A questionnaire survey was conducted querying Traditional Korean Medicine doctors working at Traditional Korean Medicine clinics and hospitals, to investigate their desired CDSS functions, and their perceived effects on herbal medicine prescription. The implementation of the CDSS among the audit software developers used by the Korean medical doctors was examined.ResultsOn average, 41.2% of Traditional Korean Medicine doctors working in Traditional Korean Medicine clinics manipulated 1 to 4 herbs, and 31.2% adjusted 4 to 7 herbs. On average, 52.5% of Traditional Korean Medicine doctors working in Traditional Korean Medicine hospitals adjusted 1 to 4 herbs, and 35.5% adjusted 4 to 7 herbs. Questioning the desired prescription support function in the electronic medical record system, the Traditional Korean Medicine doctors working at Korean medicine clinics desired information on ‘medicine name, meridian entry, flavor of medicinals, nature of medicinals, efficacy,’ ‘herb combination information’ and ‘search engine by efficacy of prescription.’ The doctors also desired compounding contraindications (eighteen antagonisms, nineteen incompatibilities) and other contraindicatory prescriptions, ‘medicine information’ and ‘prescription analysis information through basic constitution analyses.’ The implementation of prescription support function varied by clinics and hospitals.ConclusionIn order to implement and utilize the CDSS in a medical service, clinical information must be generated and managed in a standardized form. For this purpose, standardization of terminology, coding of prescriptions using a combination of herbal medicines, and unification such as the preparation method and the weights and measures should be integrated.

Despite increasing emphasis on the role of clinical decision-support systems (CDSSs) for improving care and reducing costs, evidence to support widespread use is lacking. To evaluate the effect of CDSSs on clinical outcomes, health care processes, workload and efficiency, patient satisfaction, cost, and provider use and implementation. MEDLINE, CINAHL, PsycINFO, and Web of Science through January 2011. Investigators independently screened reports to identify randomized trials published in English of electronic CDSSs that were implemented in clinical settings; used by providers to aid decision making at the point of care; and reported clinical, health care process, workload, relationship-centered, economic, or provider use outcomes. Investigators extracted data about study design, participant characteristics, interventions, outcomes, and quality. 148 randomized, controlled trials were included. A total of 128 (86%) assessed health care process measures, 29 (20%) assessed clinical outcomes, and 22 (15%) measured costs. Both commercially and locally developed CDSSs improved health care process measures related to performing preventive services (n= 25; odds ratio [OR], 1.42 [95% CI, 1.27 to 1.58]), ordering clinical studies (n= 20; OR, 1.72 [CI, 1.47 to 2.00]), and prescribing therapies (n= 46; OR, 1.57 [CI, 1.35 to 1.82]). Few studies measured potential unintended consequences or adverse effects. Studies were heterogeneous in interventions, populations, settings, and outcomes. Publication bias and selective reporting cannot be excluded. Both commercially and locally developed CDSSs are effective at improving health care process measures across diverse settings, but evidence for clinical, economic, workload, and efficiency outcomes remains sparse. This review expands knowledge in the field by demonstrating the benefits of CDSSs outside of experienced academic centers. Agency for Healthcare Research and Quality.

Supporting healthcare decision-making that is patient-centered and evidence-based requires investments in the development of tools and techniques for dissemination of patient-centered outcomes research findings via methods such as clinical decision support (CDS). This article explores the technical landscape for patient-centered CDS (PC CDS) and the gaps in making PC CDS more shareable, standards-based, and publicly available, with the goal of improving patient care and clinical outcomes. This landscape assessment used: (1) a technical expert panel; (2) a literature review; and (3) interviews with 18 CDS stakeholders. We identified 7 salient technical considerations that span 5 phases of PC CDS development. While progress has been made in the technical landscape, the field must advance standards for translating clinical guidelines into PC CDS, the standardization of CDS insertion points into the clinical workflow, and processes to capture, standardize, and integrate patient-generated health data.

Electronic health records (EHRs) and clinical decision support systems (CDSSs) have the potential to enhance antimicrobial stewardship. Numerous EHRs and CDSSs are available and have the potential to enable all clinicians and antimicrobial stewardship programs (ASPs) to more efficiently review pharmacy, microbiology, and clinical data. Literature evaluating the impact of EHRs and CDSSs on patient outcomes is lacking, although EHRs with integrated CDSSs have demonstrated improvements in clinical and economic outcomes. Both technologies can be used to enhance existing ASPs and their implementation of core ASP strategies. Resolution of administrative, legal, and technical issues will enhance the acceptance and impact of these systems. EHR systems will increase in value when manufacturers include integrated ASP tools and CDSSs that do not require extensive commitment of information technology resources. Further research is needed to determine the true impact of current systems on ASP and the ultimate goal of improved patient outcomes through optimized antimicrobial use.

The objective was to investigate clinician knowledge of and attitudes toward clinical decision support (CDS) and its incorporation into the electronic health record (EHR). This was an electronic survey of emergency physicians (EPs) within an integrated health care delivery system that uses a complete EHR. Randomly assigned respondents completed one of two questionnaires, both including a hypothetical vignette and self-reported knowledge of and attitudes about CDS. One vignette version included CDS, and the other did not (NCDS). The vignette described a scenario in which a cranial computed tomography (CCT) is not recommended by validated prediction rules (the Pediatric Emergency Care Applied Research Network [PECARN] rules). In both survey versions, subjects responded first with their likely approach to evaluation and then again after receiving either CDS (the PECARN prediction rules) or no additional support. Descriptive statistics were used for self-reported responses and multivariate logistic regression was used to identify predictors of self-reported knowledge and use of the PECARN rules, as well as use of vignette responses. There were 339 respondents (68% response rate), with 172 of 339 (51%) randomized to the CDS version. Initially, 25% of respondents to each version indicated they would order CCTs. After CDS, 30 of 43 (70%) of respondents who initially would order CCTs changed their management decisions to no CCT versus two of 41 (5%) with the NCDS version (chi-square, p = 0.003). In response to self-report questions, 81 of 338 respondents (24%) reported having never heard of the PECARN prediction rules, 122 of 338 (36%) were aware of the rules but not their specifics, and 135 of 338 (40%) reported knowing the rules and their specifics. Respondents agreed with favorable statements about CDS (75% to 96% agreement across seven statements) and approaches to its implementation into the EHR (60% to 93% agreement across seven statements). In multivariable analyses, EPs with tenure of 5 to 14 years (odds ratio [AOR] = 0.51, 95% confidence interval [CI] = 0.30 to 0.86) and for 15 years or more (AOR = 0.37, 95% CI = 0.20 to 0.70) were significantly less likely to report knowing the specifics of the PECARN prediction rules compared with EPs who practiced for fewer than 5 years. In addition, in the initial vignette responses (across both versions), physicians with ≥15 years of ED tenure compared to those with fewer than 5 years of experience (AOR = 0.30, 95% CI = 0.13 to 0.69), and those reporting knowing the specifics of the PECARN prediction rules were less likely to order CCTs (AOR = 0.53, 95% CI = 0.30 to 0.92). EPs incorporated pediatric head trauma CDS via the EHR into their clinical judgment in a hypothetical scenario and reported favorable opinions of CDS in general and their inclusion into the EHR.

Safdar and Aslam's narrative evaluation of primary care chronic kidney disease management provides a comprehensive overview of current evidence-based approaches [1]. While their review effectively summarizes contemporary CKD screening, diagnosis, and management protocols, we propose focusing on two specific, well-evidenced implementation strategies that could substantially enhance the translation of these guidelines into routine primary care practice. Electronic health record-integrated clinical decision support (CDS) systems represent a promising yet complex intervention for addressing CKD management gaps in primary care. The largest cluster randomized trial to date, conducted by Sperl-Hillen et al. [2], involved 32 primary care clinics and 6420 patients with CKD stages G3–G4. This rigorous study provides critical insights into CDS effectiveness for CKD management. The trial demonstrated modest improvements favoring CDS intervention, though none achieved statistical significance: CKD diagnosis documentation increased from 21.8% to 26.6% (RR 1.17; 95% CI 0.91–1.51, p = 0.21), and nephrology referrals improved from 36.1% to 38.7% (RR 1.02; 95% CI 0.79–1.32, p = 0.86). However, other outcomes showed minimal differences, with blood pressure control remaining essentially unchanged (20.2% vs. 20.4%). The study revealed critical implementation barriers that limited CDS effectiveness. COVID-19 pandemic disruptions substantially reduced intervention exposure, with CDS print rates recovering to only 67% of pre-pandemic levels [2]. Team-based CKD management demonstrates substantially stronger evidence for clinical effectiveness compared to CDS systems alone. The nationwide Japanese multicenter study by Masanori et al. [3] examined 2954 CKD patients and provided compelling evidence for multidisciplinary care superiority. Additionally, implementation of a primary care CKD registry has been shown to improve identification and management of at-risk patients, facilitating team-based care and tracking outcomes in high-need populations [4]. Multidisciplinary care significantly reduced the composite endpoint of renal replacement therapy initiation and all-cause mortality compared to conventional care (HR 0.71; 95% CI 0.60–0.85, p = 0.0001) [3]. Teams involving more healthcare disciplines showed superior outcomes, with inpatient-based multidisciplinary care (mean 4.5 professionals) outperforming outpatient-based care (mean 2.6 professionals). Effective teams require nephrologists, specialist nurses, registered dietitians, pharmacists, and social workers working collaboratively [3]. For healthcare systems serving diverse populations, systematic cultural competency interventions show measurable effectiveness. Kanagaratnam et al.'s systematic review [5] identified specific culturally adapted CKD interventions with demonstrated clinical benefits. Cultural Health Liaison Officers, implemented in six studies involving 106 patients, improved clinical outcomes including blood pressure reduction compared to routine care [5]. Community-based interventions designed with local input and delivered through trusted community partners achieved superior outcomes compared to hospital-based programs. While CDS systems show promise, implementation requires careful attention to workflow integration, competing clinical priorities, and sustained organizational support to achieve effectiveness. Shaher Yar conceived, wrote, and revised the manuscript. Fizza Asghar revised the manuscript. Zahin Shahriar worked on references and data collection. Muhammad Shahzad Asif supervised the project. The authors have nothing to report. The authors declare no conflicts of interest. This article is linked to Safdar and Aslam papers. To view these articles, visit https://doi.org/10.1002/jgf2.70054. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

A CDSS (Clinical Decision Support System) aiming to support the exploitation of CG (Clinical Guidelines) by HCP (Health Care Practitioners) has been designed, able to consider the available knowledge about the patient’s health stored within the CIS (Clinical Information System), using the CIS native, well-trained functions and ergonomics. Amongst the main methods used, figure rule based decision trees to represent the CG knowledge, concept dictionary bonded to international standard terminological systems for semantic indexing, usage of CIS components as part of the CDSS to ensure the respect of the clinical workflow. The results obtained are threefold: 1) a CG model structure adapted for such CDSS; 2) a semantic interoperability platform populated with SNOMED 3.5 international terminology system between CDSS and Electronic Healthcare Records; 3) a workflow of clinical information systems elements coupled by a rule engine solution allowing authoring CG as decision trees. The semantic interoperability platform is up and running in more than sixty large French healthcare organizations, the CDSS is available for first exploitation experiments.

The role of standardized data and terminological systems in computerized clinical decision support systems: Literature review and survey