Computerized Clinical Decision Support Research Articles

Digital literacy within Master of Pharmacy curricula in the United Kingdom: a mixed-method study

Abstract Introduction As digital health technologies (DHTs) like electronic health records (EHRs), computerised clinical decision support (CCDS), and telehealth become integral to healthcare delivery, there is an increasing demand for digitally literate healthcare professionals, including pharmacists. The General Pharmaceutical Council (GPhC) has emphasised digital competencies in the United Kingdom’s (UK’s) Master of Pharmacy (MPharm) curriculum. The Health Education England (HEE) and the Topol review further emphasises this point, indicating the pressing need for a digitally ready healthcare workforce.[1,2] However, despite these efforts, evidence suggests that digital literacy remains underrepresented in undergraduate pharmacy training. Aim To explore the current and planned inclusion of digital literacy education in the MPharm curricula of UK pharmacy schools. Methods A two-phase study was conducted. Phase 1: we undertook a content analysis of curricula from all GPhC-accredited UK pharmacy schools (n=30) in April 2022. Curriculum materials were procured either directly from schools’ websites or via formal correspondence. The analytical approach was based on a preceding systematic scoping review and further refined through an inductive open coding methodology. Phase 2: a structured 14-item quantitative survey, informed by the HEE Digital Capabilities Framework for the Pharmacy Workforce, was emailed to academic representatives across all UK pharmacy institutions, soliciting data on digital literacy, pedagogical methodologies, and envisaged curriculum trajectories. Results Documents for the content analysis were obtained from 46.7% (14/30) of the UK pharmacy schools. Of these, 71.4% (10/14) included components of digital literacy education or training. We identified themes relating to digital literacy education including: the theoretical understanding of health informatics, applied informatics, information technology skills and the newly emerging field of DHTs including artificial intelligence, pharmacogenomics, and personalised therapies. A total of 53.3% (16/30) schools responded to the survey. Most schools who participated in the survey stated that they had integrated digital literacy into their curricula, with only one exception; alignment with the HEE framework varied. Digital literacy was typically integrated within other teaching sessions, taught through self-learning using online resources (66.7%; 12/18). EHRs and remote counselling were primary focus areas (94.4%; 17/18). Challenges in digital literacy education include expertise shortage (68.4%; 13/19), insufficient support from pharmacy organisations (68.4%; 13/19), and limited time (52.6%; 10/19). Conclusion Although the review of the MPharm curricula revealed evidence of UK pharmacy schools incorporating digital literacy, we identified gaps in training and education relating to the variability in topics across schools, misalignment with the HEE framework, and educators’ concerns about the adequacy of current digital literacy provisions. It is important to acknowledge that our study’s low response rate might introduce sample bias, including schools more proactive in teaching digital literacy, and may not be representative of the broader educational context. The observed gaps underscore the need for collaboration with professional bodies and industry experts to enhance training with the aim of ensuring that future pharmacists are prepared and competent to practice in the digital age.

Computerized Clinical Decision Support to Improve Stroke Prevention Therapy in Primary Care Management of Atrial Fibrillation: A Cluster Randomized Trial

Despite guidelines supporting antithrombotic therapy use in atrial fibrillation (AF), under-prescribing persists. We assessed whether computerized clinical decision support (CDS) would enable guideline-based antithrombotic therapy for AF patients in primary care. This cluster randomized trial of CDS versus usual care (UC) recruited participants from primary care practices across Nova Scotia, following them for 12 months. The CDS tool calculated bleeding and stroke risk scores and provided recommendations for using oral anticoagulants (OAC) per Canadian guidelines. From June 14, 2014 - December 15, 2016, 203 primary care providers (99 UC, 104 CDS) with access to high-speed Internet were recruited, enrolling 1145 eligible patients (543 UC, 590 CDS) assigned to the same treatment arm as their provider. Patient mean age was 72.3 years; most were male (350, 64.5% UC, 351, 59.5% CDS) and from a rural area (298, 54.9% UC, 315, 53.4% CDS). At baseline, a higher than anticipated proportion of patients were receiving guideline-based OAC therapy (373, 68.7% UC, 442, 74.9% CDS; relative risk [RR] 0.97 (95% confidence interval [CI], 0.87-1.07; p=0.511)). At 12 months, prescription data were available for 538 usual care and 570 CDS patients, and significantly more CDS patients were managed according to guidelines (415, 77.1% UC, 479, 84.0% CDS; RR 1.08 (95% CI, 1.01-1.15; p=0.024)). Notwithstanding high baseline rates, primary care provider access to the CDS over 12 months further optimized the prescribing of of OAC therapy per national guidelines to AF patients potentially eligible to receive it. This suggests that CDS can be effective in improving clinical process of care. Clinical Trials NCT01927367. https://clinicaltrials.gov/ct2/show/NCT01927367?term=NCT01927367&draw=2&rank=1.

Clinical Decision Support for Hypertension Management in Chronic Kidney Disease

Chronic kidney disease (CKD) affects 37 million adults in the United States, and for patients with CKD, hypertension is a key risk factor for adverse outcomes, such as kidney failure, cardiovascular events, and death. To evaluate a computerized clinical decision support (CDS) system for the management of uncontrolled hypertension in patients with CKD. This multiclinic, randomized clinical trial randomized primary care practitioners (PCPs) at a primary care network, including 15 hospital-based, ambulatory, and community health center-based clinics, through a stratified, matched-pair randomization approach February 2021 to February 2022. All adult patients with a visit to a PCP in the last 2 years were eligible and those with evidence of CKD and hypertension were included. The intervention consisted of a CDS system based on behavioral economic principles and human-centered design methods that delivered tailored, evidence-based recommendations, including initiation or titration of renin-angiotensin-aldosterone system inhibitors. The patients in the control group received usual care from PCPs with the CDS system operating in silent mode. The primary outcome was the change in mean systolic blood pressure (SBP) between baseline and 180 days compared between groups. The primary analysis was a repeated measures linear mixed model, using SBP at baseline, 90 days, and 180 days in an intention-to-treat repeated measures model to account for missing data. Secondary outcomes included blood pressure (BP) control and outcomes such as percentage of patients who received an action that aligned with the CDS recommendations. The study included 174 PCPs and 2026 patients (mean [SD] age, 75.3 [0.3] years; 1223 [60.4%] female; mean [SD] SBP at baseline, 154.0 [14.3] mm Hg), with 87 PCPs and 1029 patients randomized to the intervention and 87 PCPs and 997 patients randomized to usual care. Overall, 1714 patients (84.6%) were treated for hypertension at baseline. There were 1623 patients (80.1%) with an SBP measurement at 180 days. From the linear mixed model, there was a statistically significant difference in mean SBP change in the intervention group compared with the usual care group (change, -14.6 [95% CI, -13.1 to -16.0] mm Hg vs -11.7 [-10.2 to -13.1] mm Hg; P = .005). There was no difference in the percentage of patients who achieved BP control in the intervention group compared with the control group (50.4% [95% CI, 46.5% to 54.3%] vs 47.1% [95% CI, 43.3% to 51.0%]). More patients received an action aligned with the CDS recommendations in the intervention group than in the usual care group (49.9% [95% CI, 45.1% to 54.8%] vs 34.6% [95% CI, 29.8% to 39.4%]; P < .001). These findings suggest that implementing this computerized CDS system could lead to improved management of uncontrolled hypertension and potentially improved clinical outcomes at the population level for patients with CKD. ClinicalTrials.gov Identifier: NCT03679247.

A67 REDUCING INAPPROPRIATE GAMMA-GLUTAMYL TRANSFERASE TESTING FOR INPATIENTS: A QUALITY IMPROVEMENT INITIATIVE IN LAB WASTE REDUCTION APPLYING THE MODEL FOR CONTINUOUS IMPROVEMENT

Abstract Background Review of the literature identifies a rising trend in laboratory testing, with over 30% of tests estimated to be inappropriately repeated. Laboratory overutilization increases healthcare costs, and can lead to overdiagnosis, overtreatment and negative health outcomes. Indications for repeat Gamma Glutamyl Transferase (GGT) testing in adults are limited, particularly repeat testing within the same admission. Aims Our aim was to reduce the inappropriate ordering of repeat GGT testing by 25% for all inpatients at the London Health Sciences Centre (LHSC) over a one-year study period. Methods An interprofessional team was created to help engage relevant stakeholders, collect baseline data and reassess the indications for GGT testing. A combination of root cause analysis tools, specifically the Ishikawa diagram and Pareto chart, were employed to identify potential factors contributing to the overutilization of GGT testing. After prioritizing potential solutions, intervention bundles were developed, and Plan-Do-Study-Act (PDSA) cycles were created to target correctable factors. In PDSA cycle #1, the process started by eliminating GGT as a laboratory testing option in the three most commonly used admission order care sets. Considering the hierarchy of intervention effectiveness, PDSA cycle #2 involved implementing a computerized Clinical Decision Support (CDS) system to restrict the reordering of GGT tests within 72 hours of the same admission. Results Baseline data showed that in 2022, a total of 62,542 GGT tests were ordered, with an average of approximately 5,200 GGT tests ordered per month. Of these, 16.4% were ordered through the top 3 most prevalent admission order care sets, and around 25% of all GGT tests were repeats within 72 hours of admission. Referring to Figure 1, PDSA cycle #1 yielded no significant reduction in GGT testing. PDSA cycle #2 successfully reduced the proportion of repeat GGT tests ordered by 12% within two months of implementation, leading to an estimated annualized cost savings of approximately $37,440. Conclusions Our results establish the effectiveness of CDS systems in reducing laboratory testing overutilization, suggesting their superiority to individual care set targeting interventions, and emphasize the potential for cost-effective CDS development in contemporary healthcare. Funding Agencies None

Formative evaluation of an emergency department clinical decision support system for agitation symptoms: a study protocol

IntroductionThe burden of mental health-related visits to emergency departments (EDs) is growing, and agitation episodes are prevalent with such visits. Best practice guidance from experts recommends early assessment of at-risk...

Management of Fall Risk Among Older Adults in Diverse Primary Care Settings.

Falls are persistent among community-dwelling older adults despite existing prevention guidelines. We described how urban and rural primary care staff and older adults manage fall risk and factors important to integration of computerized clinical decision support (CCDS). Interviews, contextual inquiries, and workflow observations were analyzed using content analysis and synthesized into a journey map. Sociotechnical and PRISM domains were applied to identify workflow factors important to sustainable CCDS integration. Participants valued fall prevention and described similar approaches. Available resources differed between rural and urban locations. Participants wanted evidence-based guidance integrated into workflows to bridge skills gaps. Sites described similar clinical approaches with differences in resource availability. This implies that a single intervention would need to be flexible to environments with differing resources. Electronic Health Record's inherent ability to provide tailored CCDS is limited. However, CCDS middleware could integrate into different settings and increase evidence use.

Refining Clinical Phenotypes to Improve Clinical Decision Support and Reduce Alert Fatigue: A Feasibility Study.

Chronic kidney disease (CKD) is common and associated with adverse clinical outcomes. Most care for early CKD is provided in primary care, including hypertension (HTN) management. Computerized clinical decision support (CDS) can improve the quality of care for CKD but can also cause alert fatigue for primary care physicians (PCPs). Computable phenotypes (CPs) are algorithms to identify disease populations using, for example, specific laboratory data criteria. Our objective was to determine the feasibility of implementation of CDS alerts by developing CPs and estimating potential alert burden. We utilized clinical guidelines to develop a set of five CPs for patients with stage 3 to 4 CKD, uncontrolled HTN, and indications for initiation or titration of guideline-recommended antihypertensive agents. We then conducted an iterative data analytic process consisting of database queries, data validation, and subject matter expert discussion, to make iterative changes to the CPs. We estimated the potential alert burden to make final decisions about the scope of the CDS alerts. Specifically, the number of times that each alert could fire was limited to once per patient. In our primary care network, there were 239,339 encounters for 105,992 primary care patients between April 1, 2018 and April 1, 2019. Of these patients, 9,081 (8.6%) had stage 3 and 4 CKD. Almost half of the CKD patients, 4,191 patients, also had uncontrolled HTN. The majority of CKD patients were female, elderly, white, and English-speaking. We estimated that 5,369 alerts would fire if alerts were triggered multiple times per patient, with a mean number of alerts shown to each PCP ranging from 0.07-to 0.17 alerts per week. Development of CPs and estimation of alert burden allows researchers to iteratively fine-tune CDS prior to implementation. This method of assessment can help organizations balance the tradeoff between standardization of care and alert fatigue.

Healthcare Professionals' Perceptions, Barriers, and Facilitators towards Adopting Computerised Clinical Decision Support Systems in Antimicrobial Stewardship in Jordanian Hospitals.

Understanding healthcare professionals' perceptions towards a computerised decision support system (CDSS) may provide a platform for the determinants of the successful adoption and implementation of CDSS. This cross-sectional study examined healthcare professionals' perceptions, barriers, and facilitators to adopting a CDSS for antibiotic prescribing in Jordanian hospitals. This study was conducted among healthcare professionals in Jordan's two tertiary and teaching hospitals over four weeks (June-July 2021). Data were collected in a paper-based format from senior and junior prescribers and non-prescribers (n = 254) who agreed to complete a questionnaire. The majority (n = 184, 72.4%) were aware that electronic prescribing and electronic health record systems could be used specifically to facilitate antibiotic use and prescribing. The essential facilitator made CDSS available in a portable format (n = 224, 88.2%). While insufficient training to use CDSS was the most significant barrier (n = 175, 68.9%). The female providers showed significantly lower awareness (p = 0.006), and the nurses showed significantly higher awareness (p = 0.041) about using electronic prescribing and electronic health record systems. This study examined healthcare professionals' perceptions of adopting CDSS in antimicrobial stewardship (AMS) and shed light on the perceived barriers and facilitators to adopting CDSS in AMS, reducing antibiotic resistance, and improving patient safety. Furthermore, results would provide a framework for other hospital settings concerned with implementing CDSS in AMS and inform policy decision-makers to react by implementing the CDSS system in Jordan and globally. Future studies should concentrate on establishing policies and guidelines and a framework to examine the adoption of the CDSS for AMS.

Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy.

How to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced guidelines. Care providers in such settings frequently do not have sufficient training to undertake advanced guideline implementation. Nevertheless, in advanced modern healthcare delivery environments, use of eActions (validated clinical decision support systems) could help overcome the cognitive limitations of overburdened clinicians. Widespread use of eActions will require surmounting current healthcare technical and cultural barriers and installing clinical evidence/data curation systems. The authors expect that increased numbers of evidence-based guidelines will result from future comparative effectiveness clinical research carried out during routine healthcare delivery within learning healthcare systems.

Using the Electronic Health Record User Context in Clinical Decision Support Criteria.

Computerized clinical decision support (CDS) used in electronic health record systems (EHRs) has led to positive outcomes as well as unintended consequences, such as alert fatigue. Characteristics of the EHR session can be used to restrict CDS tools and increase their relevance, but implications of this approach are not rigorously studied. To assess the utility of using "login location" of EHR users-that is, the location they chose on the login screen-as a variable in the CDS logic. We measured concordance between user's login location and the location of the patients they placed orders for and conducted stratified analyses by user groups. We also estimated how often login location data may be stale or inaccurate. One in five CDS alerts incorporated the EHR users' login location into their logic. Analysis of nearly 2 million orders placed by nearly 8,000 users showed that concordance between login location and patient location was high for nurses, nurse practitioners, and physician assistance (all &gt;95%), but lower for fellows (77%) and residents (55%). When providers switched between patients in the EHR, they usually did not update their login location accordingly. CDS alerts commonly incorporate user's login location into their logic. User's login location is often the same as the location of the patient the user is providing care for, but substantial discordance can be observed for certain user groups. While this may provide additional information that could be useful to the CDS logic, a substantial amount of discordance happened in specific user groups or when users appeared not to change their login location across different sessions. Those who design CDS alerts should consider a data-driven approach to evaluate the appropriateness of login location for each use case.

Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Pediatric, Neonatal, and Maternal Inpatients: Scoping Review.

BackgroundSepsis is a severe condition associated with extensive morbidity and mortality worldwide. Pediatric, neonatal, and maternal patients represent a considerable proportion of the sepsis burden. Identifying sepsis cases as early as possible is a key pillar of sepsis management and has prompted the development of sepsis identification rules and algorithms that are embedded in computerized clinical decision support (CCDS) systems.ObjectiveThis scoping review aimed to systematically describe studies reporting on the use and evaluation of CCDS systems for the early detection of pediatric, neonatal, and maternal inpatients at risk of sepsis.MethodsMEDLINE, Embase, CINAHL, Cochrane, Latin American and Caribbean Health Sciences Literature (LILACS), Scopus, Web of Science, OpenGrey, ClinicalTrials.gov, and ProQuest Dissertations and Theses Global (PQDT) were searched by using a search strategy that incorporated terms for sepsis, clinical decision support, and early detection. Title, abstract, and full-text screening was performed by 2 independent reviewers, who consulted a third reviewer as needed. One reviewer performed data charting with a sample of data. This was checked by a second reviewer and via discussions with the review team, as necessary.ResultsA total of 33 studies were included in this review—13 (39%) pediatric studies, 18 (55%) neonatal studies, and 2 (6%) maternal studies. All studies were published after 2011, and 27 (82%) were published from 2017 onward. The most common outcome investigated in pediatric studies was the accuracy of sepsis identification (9/13, 69%). Pediatric CCDS systems used different combinations of 18 diverse clinical criteria to detect sepsis across the 13 identified studies. In neonatal studies, 78% (14/18) of the studies investigated the Kaiser Permanente early-onset sepsis risk calculator. All studies investigated sepsis treatment and management outcomes, with 83% (15/18) reporting on antibiotics-related outcomes. Usability and cost-related outcomes were each reported in only 2 (6%) of the 31 pediatric or neonatal studies. Both studies on maternal populations were short abstracts.ConclusionsThis review found limited research investigating CCDS systems to support the early detection of sepsis among pediatric, neonatal, and maternal patients, despite the high burden of sepsis in these vulnerable populations. We have highlighted the need for a consensus definition for pediatric and neonatal sepsis and the study of usability and cost-related outcomes as critical areas for future research.International Registered Report Identifier (IRRID)RR2-10.2196/24899

DEVELOPMENT OF TELEMEDICINE APPLICATION BASED ON ARTIFICIAL INTELLIGENCE IN THE HANDLING OF DIABET FOOT

Introduction: Diabetes mellitus is a metabolic disorder characterized by increased blood glucose levels (hyperglycemia) due to impaired insulin secretion and insulin action. Diabetic foot ulcers are chronic and difficult to heal is the most common cause of non-traumatic amputations in patients with diabetes mellitus which reaches 82%. Telemedicine technology based on artificial intelligence can be used as a facility for diabetic foot patients by providing education, consultation and direction in treating diabetic feet. Research Methods: The method used in this research is literature study. Literature study conducted by the author is to look for various written sources, either in the form of books, archives, magazines, articles and journals, as well as documents relevant to the problem being studied. Result: Telemedicine application based on artificial intelligence is a solution for DM patients, especially diabetic foot complications. Discussion: The telemedicine application provides 24-hour service by providing education about diabetic foot care to avoid infection, consultation on the administration of drugs such as insulin and other diabetes drugs. Artificial intelligence in telemedicine allows this application to work 24 hours a day. Conclusion: Diabetes mellitus is still a complex problem worldwide. Complications that occur, especially diabetic feet reduce the quality of life of DM patients. Telemedicine application based on artificial intelligence is a solution that can be used to perform routine care for diabetic foot patients.&#x0D; Keywords: Telemedicine, Artificial intelligence, Diabetic foot, Diabetes Mellitus&#x0D;  &#x0D; DAFTAR PUSTAKA&#x0D; &#x0D; Braza DW, Martin JNY. Diabetic Foot and Peripheral Arterial Disease [Internet]. Fourth Edi. Essentials of Physical Medicine and Rehabilitation. Elsevier Inc.; 2020. 719-723 p. 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Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Adult Inpatients: Scoping Review

BackgroundSepsis is a significant cause of morbidity and mortality worldwide. Early detection of sepsis followed promptly by treatment initiation improves patient outcomes and saves lives. Hospitals are increasingly using computerized clinical decision support (CCDS) systems for the rapid identification of adult patients with sepsis.ObjectiveThis scoping review aims to systematically describe studies reporting on the use and evaluation of CCDS systems for the early detection of adult inpatients with sepsis.MethodsThe protocol for this scoping review was previously published. A total of 10 electronic databases (MEDLINE, Embase, CINAHL, the Cochrane database, LILACS [Latin American and Caribbean Health Sciences Literature], Scopus, Web of Science, OpenGrey, ClinicalTrials.gov, and PQDT [ProQuest Dissertations and Theses]) were comprehensively searched using terms for sepsis, CCDS, and detection to identify relevant studies. Title, abstract, and full-text screening were performed by 2 independent reviewers using predefined eligibility criteria. Data charting was performed by 1 reviewer with a second reviewer checking a random sample of studies. Any disagreements were discussed with input from a third reviewer. In this review, we present the results for adult inpatients, including studies that do not specify patient age.ResultsA search of the electronic databases retrieved 12,139 studies following duplicate removal. We identified 124 studies for inclusion after title, abstract, full-text screening, and hand searching were complete. Nearly all studies (121/124, 97.6%) were published after 2009. Half of the studies were journal articles (65/124, 52.4%), and the remainder were conference abstracts (54/124, 43.5%) and theses (5/124, 4%). Most studies used a single cohort (54/124, 43.5%) or before-after (42/124, 33.9%) approach. Across all 124 included studies, patient outcomes were the most frequently reported outcomes (107/124, 86.3%), followed by sepsis treatment and management (75/124, 60.5%), CCDS usability (14/124, 11.3%), and cost outcomes (9/124, 7.3%). For sepsis identification, the systemic inflammatory response syndrome criteria were the most commonly used, alone (50/124, 40.3%), combined with organ dysfunction (28/124, 22.6%), or combined with other criteria (23/124, 18.5%). Over half of the CCDS systems (68/124, 54.8%) were implemented alongside other sepsis-related interventions.ConclusionsThe current body of literature investigating the implementation of CCDS systems for the early detection of adult inpatients with sepsis is extremely diverse. There is substantial variability in study design, CCDS criteria and characteristics, and outcomes measured across the identified literature. Future research on CCDS system usability, cost, and impact on sepsis morbidity is needed.International Registered Report Identifier (IRRID)RR2-10.2196/24899

Clinical Decision Support Systems to Reduce Unnecessary Clostridioides difficile Testing Across Multiple Hospitals.

Inappropriate Clostridioides difficile testing has adverse consequences for patients, hospitals, and public health. Computerized clinical decision support (CCDS) systems in the electronic health record (EHR) may reduce C. difficile test ordering; however, effectiveness of different approaches, ease of use, and best fit into healthcare providers' (HCP) workflow are not well understood. Nine academic and 6 community hospitals in the United States participated in this 2-year cohort study. CCDS (hard stop or soft stop) triggered when a duplicate C. difficile test order was attempted or if laxatives were recently received. The primary outcome was the difference in testing rates pre- and post-CCDS interventions, using incidence rate ratios (IRRs) and mixed-effect Poisson regression models. We performed qualitative evaluation (contextual inquiry, interviews, focus groups) based on a human factors model. We identified themes using a codebook with primary nodes and subnodes. In 9 hospitals implementing hard-stop CCDS and 4 hospitals implementing soft-stop CCDS, C. difficile testing incidence rate (IR) reduction was 33% (95% confidence interval [CI]: 30%-36%) and 23% (95% CI: 21%-25%), respectively. Two hospitals implemented a non-EHR-based human intervention with IR reduction of 21% (95% CI: 15%-28%). HCPs reported generally favorable experiences and highlighted time efficiencies such as inclusion of the patient's most recent laxative administration on the CCDS. Organizational factors, including hierarchical cultures and communication between HCPs caring for the same patient, impact CCDS acceptance and integration. CCDS systems reduced unnecessary C. difficile testing and were perceived positively by HCPs when integrated into their workflow and when displaying relevant patient-specific information needed for decision making.

A scoping review of knowledge authoring tools used for developing computerized clinical decision support systems.

ObjectiveClinical Knowledge Authoring Tools (CKATs) are integral to the computerized Clinical Decision Support (CDS) development life cycle. CKATs enable authors to generate accurate, complete, and reliable digital knowledge artifacts in a relatively efficient and affordable manner. This scoping review aims to compare knowledge authoring tools and derive the common features of CKATs.Materials and MethodsWe performed a keyword-based literature search, followed by a snowball search, to identify peer-reviewed publications describing the development or use of CKATs. We used PubMed and Embase search engines to perform the initial search (n = 1579). After removing duplicate articles, nonrelevant manuscripts, and not peer-reviewed publication, we identified 47 eligible studies describing 33 unique CKATs. The reviewed CKATs were further assessed, and salient characteristics were extracted and grouped as common CKAT features.ResultsAmong the identified CKATs, 55% use an open source platform, 70% provide an application programming interface for CDS system integration, and 79% provide features to validate/test the knowledge. The majority of the reviewed CKATs describe the flow of information, offer a graphical user interface for knowledge authors, and provide intellisense coding features (94%, 97%, and 97%, respectively). The composed list of criteria for CKAT included topics such as simulating the clinical setting, validating the knowledge, standardized clinical models and vocabulary, and domain independence. None of the reviewed CKATs met all common criteria.ConclusionOur scoping review highlights the key specifications for a CKAT. The CKAT specification proposed in this review can guide CDS authors in developing more targeted CKATs.

A Multicenter Evaluation of Probiotic Use for the Primary Prevention of Clostridioides difficile Infection.

Primary prevention of Clostridioides difficile infection (CDI) is a priority for hospitals. Probiotics have the potential to interfere with colonization and CDI. In this study, we evaluated the impact of a computerized clinical decision support (CCDS) tool to prescribe probiotics for primary prevention of CDI among adult hospitalized patients. A CCDS tool was implemented into the electronic medical record at 4 hospitals to prompt prescription of a probiotic preparation at the time of antibiotic prescription in high-risk patients in May 2019. Interrupted time series using segmented regression analysis was conducted to evaluate hospital-wide CDI incidence for the year pre- and post-CCDS implementation. In addition, multivariable logistic regression was used to evaluate CDI incidence in patients who qualified for probiotics in the pre- vs post-intervention periods, adjusting for potential confounders. To adjust for potential differences in patients who received probiotics in the post-intervention period, propensity score-matched pairs were developed to evaluate CDI risk by receipt of probiotics. Quarterly CDI incidence increased over time post-intervention relative to baseline trends (slope change, 1.4; 95% confidence interval [CI], .9-1.9). The odds ratio (OR) of CDI was 1.41 in eligible patients post-intervention compared with pre-intervention (adjusted OR, 1.41; 95% CI, 1.11-1.79). Propensity score-matched analysis showed that patients who received probiotics did not have lower rates of CDI compared with those who did not receive probiotics (OR, 1.46; 95% CI, .87-2.45). Use of probiotics for primary prevention of CDI among adult inpatients receiving antibiotics is not supported.

Evaluation of Clinical Decision Support to Reduce Sedative-Hypnotic Prescribing in Older Adults.

We sought to characterize the performance of inpatient and outpatient computerized clinical decision support (CDS) alerts aimed at reducing inappropriate benzodiazepine and nonbenzodiazepine sedative medication prescribing in older adults 18 months after implementation. We reviewed the performance of two CDS alerts in the outpatient and inpatient settings in 2019. To examine the alerts' effectiveness, we analyzed metrics including overall alert adherence, provider-level adherence, and reasons for alert trigger and override. In 2019, we identified a total of 14,534 and 4,834 alerts triggered in the outpatient and inpatient settings, respectively. Providers followed only 1% of outpatient and 3% of inpatient alerts. Most alerts were ignored (68% outpatient and 60% inpatient), while providers selected to override the remaining alerts. In each setting, the top 2% of clinicians were responsible for approximately 25% of all ignored or overridden alerts. However, a small proportion of clinicians (2% outpatient and 4% inpatient) followed the alert at least half of the time and accounted for a disproportionally large fraction of the total followed alerts. Our analysis of the free-text comments revealed that many alerts were to continue outpatient prescriptions or for situational anxiety. Our findings highlight the importance of evaluation of CDS performance after implementation. We found large variation in response to the inpatient and outpatient alerts, both with respect to follow and ignore rates. Reevaluating the alert design by providing decision support by indication may be more helpful and may reduce alert fatigue.

88. Impact of a Computerized Clinical Decision Support Tool on clostridioides Difficile Testing and Oral Vancomycin Utilization as a Balancing Metric

BackgroundOver diagnosis of hospital-onset Clostridioides difficile infection (HO-CDI) is directly tied to inappropriate C. difficile testing which does not distinguish between infected or colonized individuals. This can lead to inappropriate therapy. Multiple studies have utilized Computerized Clinical Decision Support (CCDS) tools to reduce inappropriate C. difficile testing. Our study looks at the impact of a Self-Assessment CCDS tools on C. difficile testing for HO-CDI and oral vancomycin utilization as a balancing metric.MethodsOur institution utilizes a two-step test to diagnose HO-CDI that consists of toxin A/B enzyme immunoassay followed by a confirmatory PCR. We applied a self-assessment driven CCDS approach to reduce testing for HO-CDI. Our intervention was deployed in the 3rd quarter of 2018. It asked 3 questions about stool frequency, laxative use and previous C. difficile testing in the order itself. Inappropriate indications for testing included any of the following: < 3 bowel movements within 24 hours, receipt of a laxative within the past 48 hours, or a previous C. difficile test within the previous 7 days. Ordering providers would self-answer these questions. A ‘yes’ response to any of the three questions prevented further test ordering; though respondents had the freedom to change the answer and still proceed with the test order. We evaluated 3 metrics that were all calculated per 1000 inpatient census days: oral vancomycin usage, HO-CDI rates and C. difficile testing rates.ResultsCompared to baseline, our intervention resulted in a significant reduction of C. difficile testing and HO-CDI rates (Figure 1, Table 1). Oral vancomycin usage also decreased significantly (Figure 2, Table 1).Figure 1. C. difficile testing and Hospital Onset C. difficile Infection Rates by Month, Before and After Intervention Figure 2. Oral Vancomycin Utilization by Month, Before and After Intervention Table 1. Changes in Median Rates of C. difficile testing, Hospital Onset C. difficile Infections and Vancomycin Utilization, Before and After Intervention. ConclusionOur self-assessment driven CCDS-based diagnostic stewardship resulted in a significant reduction in inappropriate C. difficile testing for HO-CDI and HO-CDI rates. Oral vancomycin utilization as a balancing metric also decreased significantly. This was despite the use of a self-assessment driven approach with the freedom to change the answers in order to proceed with the test order.Disclosures All Authors: No reported disclosures

Use and Evaluation of Computerized Clinical Decision Support Systems for Early Detection of Sepsis in Hospitals: Protocol for a Scoping Review.

BackgroundSepsis is a leading cause of death in hospitals, with high associated costs for both patients and health care systems worldwide. Early detection followed by timely intervention is critical for successful sepsis management and, hence, can save lives. Health care institutions are increasingly leveraging clinical data captured in electronic health records for the development of computerized clinical decision support (CCDS) systems aimed at enhancing the early detection of sepsis. However, a comprehensive evidence base regarding sepsis CCDS systems to inform clinical practice, research, and policy is currently lacking.ObjectiveThis scoping review aims to systematically describe studies reporting on the use and evaluation of CCDS systems for early detection of sepsis in hospitals.MethodsThe methodology for conducting scoping reviews presented by the Joanna Briggs Institute Reviewer’s Manual and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) will be used and adapted as guides. A comprehensive literature search of 10 electronic databases will be conducted to identify all empirical quantitative and qualitative studies that investigate the use of CCDS systems for early detection of sepsis in hospitals. Detailed inclusion and exclusion criteria have been developed. Two reviewers will independently screen all articles based on these criteria. Any discrepancies will be resolved through discussion and further review by a third researcher if required.ResultsElectronic database searches have retrieved 12,139 references after removing 10,051 duplicates. As of the submission date of this protocol, we have completed the title and abstract screening. A total of 372 references will be included for full-text screening. Only 15.9% (59/372) of these studies were focused on children: 11.0% (41/372) for pediatric and 4.8% (18/372) for neonatal patients. The scoping review and the manuscript will be completed by December 2020.ConclusionsResults of this review will guide researchers in determining gaps and shortcomings in the current evidence base for CCDS system use and evaluation in the early detection of sepsis. The findings will be shared with key stakeholders in clinical care, research, policy, and patient advocacy.International Registered Report Identifier (IRRID)PRR1-10.2196/24899

A Randomized Assessment of a Laxative-Based Clostridioides difficile Diagnostic Stewardship Intervention

Background:Clostridiodes difficile is the leading healthcare-associated pathogen, with significant morbidity associated with acute C. difficile infection (CDI). However, polymerase chain reaction stool testing is unable to differentiate colonization from infection, leading to frequent overdiagnosis, unnecessary iatrogenesis, and additional costs. As a result, IDSA guidelines do not recommend C. difficile testing in patients with diarrheal symptoms attributed to other causes, including laxatives. Our group has previously investigated the use of a computerized clinical decision support (CCDS) tool to reduce inappropriate C. difficile testing in a single tertiary-care health system, with a subsequent 41% reduction in testing. We investigated the reduction in proportion of inappropriately completed tests with the randomized addition of a laxative alert to our existing CCDS. Methods: An existing electronic medical record-based CCDS tool was augmented by the addition of an automatic alert that notified the user if a patient received any of a set of identified laxative medications within 48 hours. During the 78-day pilot period, users encountered the existing CCDS or the CCDS with laxative alert (CCDS-LA), randomized by patient identification number. A proportional χ2 analysis was used to compare the proportion of aborted to completed tests among patients who met laxative criteria in the CCDS versus CCDS-LA groups. Results: In total, 187 test orders were attempted during the pilot period in 119 patients meeting the laxative alert criteria, with 43.3% order attempts randomized to the existing CCDS and 56.7% to the CCDS-LA. Of order attempts via the CCDS-LA, 50.0% were completed, compared to 64.2% of orders completed via the existing CCDS (22.1% relative reduction in test completion; P = .0525). Conclusions: We demonstrated substantially fewer completed C. difficile tests among patients receiving laxatives who were randomized to modified laxative-alert CCDS. Although our result did not reach statistical significance, the trend toward reduced inappropriate testing prompted the CCDS-LA alert to be adopted hospital-wide following completion of the test period. Further analyses of the pre- and postintervention periods are required to determine whether this intervention significantly impacts testing rates over time, as well as to determine the durability and safety of the CCDS-LA. Additional analyses are also needed to assess the impacts on hospital-onset CDI rate and the associated costs.Funding: NoneDisclosures: None