Computerized Decision Support Research Articles

Computerized decision support is an effective approach to select memory clinic patients for amyloid-PET.

The use of amyloid-PET in dementia workup is upcoming. At the same time, amyloid-PET is costly and limitedly available. While the appropriate use criteria (AUC) aim for optimal use of amyloid-PET, their limited sensitivity hinders the translation to clinical practice. Therefore, there is a need for tools that guide selection of patients for whom amyloid-PET has the most clinical utility. We aimed to develop a computerized decision support approach to select patients for amyloid-PET. We included 286 subjects (135 controls, 108 Alzheimer's disease dementia, 33 frontotemporal lobe dementia, and 10 vascular dementia) from the Amsterdam Dementia Cohort, with available neuropsychology, APOE, MRI and [18F]florbetaben amyloid-PET. In our computerized decision support approach, using supervised machine learning based on the DSI classifier, we first classified the subjects using only neuropsychology, APOE, and quantified MRI. Then, for subjects with uncertain classification (probability of correct class (PCC) < 0.75) we enriched classification by adding (hypothetical) amyloid positive (AD-like) and negative (normal) PET visual read results and assessed whether the diagnosis became more certain in at least one scenario (PPC≥0.75). If this was the case, the actual visual read result was used in the final classification. We compared the proportion of PET scans and patients diagnosed with sufficient certainty in the computerized approach with three scenarios: 1) without amyloid-PET, 2) amyloid-PET according to the AUC, and 3) amyloid-PET for all patients. The computerized approach advised PET in n = 60(21%) patients, leading to a diagnosis with sufficient certainty in n = 188(66%) patients. This approach was more efficient than the other three scenarios: 1) without amyloid-PET, diagnostic classification was obtained in n = 155(54%), 2) applying the AUC resulted in amyloid-PET in n = 113(40%) and diagnostic classification in n = 156(55%), and 3) performing amyloid-PET in all resulted in diagnostic classification in n = 154(54%). Our computerized data-driven approach selected 21% of memory clinic patients for amyloid-PET, without compromising diagnostic performance. Our work contributes to a cost-effective implementation and could support clinicians in making a balanced decision in ordering additional amyloid PET during the dementia workup.

Correlation between antifungal clinical practices and a new clinical decision support system ANTIFON-CLIC® for the treatment of invasive candidiasis: a retrospective multicentre study.

Invasive candidiasis is still recognized as a major cause of morbidity and mortality. To support clinicians in the optimal use of antifungals for the treatment of invasive candidiasis, a computerized decision support system (CDSS) was developed based on institutional guidelines. To evaluate the correlation of this newly developed CDSS with clinical practices, we set-up a retrospective multicentre cohort study with the aim of providing the concordance rate between the CDSS recommendation and the medical prescription (NCT05656157). Adult patients who received caspofungin or fluconazole for the treatment of an invasive candidiasis were included. The analysis of factors associated with concordance was performed using mixed logistic regression models with department as a random effect. From March to November 2022, 190 patients were included from three centres and eight departments: 70 patients from centre A, 84 from centre B and 36 from centre C. Overall, 100 patients received caspofungin and 90 received fluconazole, mostly (59%; 112/190) for empirical/pre-emptive treatment. The overall percentage of concordance between the CDSS and medical prescriptions was 91% (173/190) (confidence interval 95%: 82%-96%). No significant difference in concordance was observed considering the centres (P > 0.99), the department of inclusion (P = 0.968), the antifungal treatment (P = 0.656) or the indication of treatment (P = 0.997). In most cases of discordance (n = 13/17, 76%), the CDSS recommended fluconazole whereas caspofungin was prescribed. The clinical usability evaluated by five clinicians was satisfactory. Our results demonstrated the high correlation between current antifungal clinical practice and this user-friendly and institutional guidelines-based CDSS.

Computational Decision Support for PE Diagnosis based on Ventilation Perfusion Ratio.

The aim of this study is to investigate whether computer-aided, semi-automated 3D lung lobe quantification can support decision-making on PE diagnosis based on the ventilation-perfusion ratio in clinical practice. A study cohort of 100 patients (39 male, 61 female, age 64.8±15.8 years) underwent ventilation/perfusion single photon emission computed tomography (V/Q-SPECT/CT) to exclude acute PE on SPECT/CT OPTIMA NM/CT 640 (GE Healthcare). Two 3D lung lobe quantification software tools (Q. Lung: Xeleris 4.0, GE Healthcare and LLQ: Hermes Hybrid 3D Lung Lobar Quantification, Hermes Medical Solutions) were used to evaluate the numerical lobar ventilation/perfusion ratio (VQR) and lobar volume/perfusion ratio (VPR). A test of linearity and equivalence of the two 3D software tools was performed using Pearson, Spearman, quadratic weighted kappa and the mean squared deviation for VPR/VQR. An algorithm was developed that identified PE candidates using ROC analysis. The agreement between the PE findings of an experienced nuclear medicine expert and the calculated PE candidates was represented by the magnitude of the YOUDEN index (J) and the size of the area under the receiver operating curve (AUC). Both 3D software tools showed good comparability. The YOUDEN index for QLUNG(VPR/VQR)/LLQ(VPR/VQR) was in the range from 0.2 to 0.5. The mean AUC averaged over all lung lobes for QLUNG(VPR) was 0.66, CI95%: ±14.0%, for QLUNG(VQR) 0.66, CI95%: ±13.3%, for LLQ(VPR) 0.64, CI95%: ±14.7% and for LLQ(VQR) 0.65, CI95%: ±13.1%. This study reveals that 3D software tools are feasible for numerical PE detection. The clinical decision can be supported by using a numerical algorithm based on ROC analysis.

Protocol for a trial-based economic evaluation analysis of a complex digital health intervention including a computerised decision support tool: the iFraP intervention

Background Digital health interventions (DHI) are associated with significant promise. In recent years, the need to assess the value of these healthcare technologies has motivated a debate regarding the suitability of existing economic evaluation methods in the context of DHI evaluation. Some have argued that robust economic evaluation methods may not be capable of capturing relevant DHI’s characteristics. Others consider that assessing the value of DHI might not be feasible. This protocol paper challenges that view. More specifically, it describes early Health Technology Assessments (HTA) methods to rigorously assess the value for money of a complex intervention including a digital decision support tool i.e., Improving uptake of Fracture Prevention drug treatments (iFraP) as a tracer intervention. iFraP is a complex intervention consisting of a computerised decision support tool, a clinician training package, and information resources to facilitate shared decision-making, increase informed medicine initiation and reduce levels of medicine discontinuation. iFraP’s development was motivated by a view that good quality shared decision-making conversations have the potential to improve levels of osteoporosis medicine uptake. Methods An early economic evaluation of the iFraP intervention was designed to identify, measure, and evaluate the costs and health benefits of iFraP compared to usual practice in Fracture Liaison Services (FLSs). A within-trial cost-effectiveness from the perspective of the National Health Service and Personal Social Service in England will be conducted using patient’s self-reported health related quality of life (HRQoL) and resource use from the iFraP randomised controlled trial. Microanalysis will be used to estimate iFraP’s intervention cost. Finally, Bayesian Value of Information analysis will allow us to estimate an upper bound for the potential health benefits gained from reducing uncertainty on the impact of the iFraP intervention to support uptake and adherence with osteoporosis medicines. Trial registration ISRCTN10606407 - https://doi.org/10.1186/ISRCTN10606407

A person-centred consultation intervention to improve shared decision-making about, and uptake of, osteoporosis medicines (iFraP): a pragmatic, parallel-group, individual randomised controlled trial protocol

Background Good quality shared decision-making (SDM) conversations involve people with, or at risk of osteoporosis and clinicians collaborating to decide, where appropriate, which evidence-based medicines best fit the person’s life, beliefs, and values. We developed the improving uptake of Fracture Prevention drug treatments (iFraP) intervention comprising a computerised Decision Support Tool (DST), clinician training package and information resources, for use in UK Fracture Liaison Service consultations. Two primary objectives to determine (1) the effect of the iFraP intervention on patient-reported ease in decision-making about osteoporosis medicines, and (2) cost-effectiveness of iFraP intervention compared to usual NHS care. Secondary objectives are to determine the iFraP intervention effect on patient reported outcome and experience measures, clinical effectiveness (osteoporosis medicine adherence), and to explore intervention acceptability, mechanisms, and processes underlying observed effects, and intervention implementation. Methods The iFraP trial is a pragmatic, parallel-group, individual randomised controlled trial in patients referred to a Fracture Liaison Service, with nested mixed methods process evaluation and health economic analysis. Participants aged ≥50 years (n=380) are randomised (1:1 ratio) to one of two arms: (1) iFraP intervention (iFraP-i) or (2) comparator usual NHS care (iFraP-u) and are followed up at 2-weeks and 3-months. The primary outcome is ease of decision-making assessed 2 weeks after the consultation using the Decisional Conflict Scale (DCS). The primary objectives will be addressed by comparing the mean DCS score in each trial arm (using analysis of covariance) for patients given an osteoporosis medicine recommendation, alongside a within-trial cost-effectiveness and value of information (VoI) analysis. Process evaluation data collection includes consultation recordings, semi-structured interviews, and DST analytics. Discussion The iFraP trial will answer important questions about the effectiveness of the new ‘iFraP’ osteoporosis DST, coupled with clinician training, on SDM and informed initiation of osteoporosis medicines. Trial registration: ISRCTN 10606407, 21/11/2022 https://doi.org/10.1186/ISRCTN10606407

The Economics of Medication Safety: A Cost-Benefits Analysis Framework for Evaluating an Electronic Medication System.

Medication prescribing in paediatrics is complex and compounded by the need to provide age and weight related doses, and errors continue to be problematic. Electronic medication systems (EMS) can reduce errors through dosing calculators and computerised decision support. However, evidence on costs and benefits of these systems is limited, particularly in paediatric hospitals. This paper presents the development of a cost-benefit analysis (CBA) framework to assess the impact of an EMS implementation in a paediatric tertiary hospital. An innovative component of the framework is the incorporation of the impact of the effects of the EMS for both the health system as well as for patients and their wider family networks, allowing a net social benefit assessment. We describe the impact of non-clinical out-of-pocket costs of admission and use discrete choice experiments to measure both medication related harm and the importance of medication safety to families and members of the community.

The effect of computerised decision support alerts tailored to intensive care on the administration of high-risk drug combinations, and their monitoring: a cluster randomised stepped-wedge trial

Drug-drug interactions (DDIs) can harm patients admitted to the intensive care unit (ICU). Yet, clinical decision support systems (CDSSs) aimed at helping physicians prevent DDIs are plagued by low-yield alerts, causing alert fatigue and compromising patient safety. The aim of this multicentre study was to evaluate the effect of tailoring potential DDI alerts to the ICU setting on the frequency of administered high-risk drug combinations. We implemented a cluster randomised stepped-wedge trial in nine ICUs in the Netherlands. Five ICUs already used potential DDI alerts. Patients aged 18 years or older admitted to the ICU with at least two drugs administered were included. Our intervention was an adapted CDSS, only providing alerts for potential DDIs considered as high risk. The intervention was delivered at the ICU level and targeted physicians. We hypothesised that showing only relevant alerts would improve CDSS effectiveness and lead to a decreased number of administered high-risk drug combinations. The order in which the intervention was implemented in the ICUs was randomised by an independent researcher. The primary outcome was the number of administered high-risk drug combinations per 1000 drug administrations per patient and was assessed in all included patients. This trial was registered in the Netherlands Trial Register (identifier NL6762) on Nov 26, 2018, and is now closed. In total, 10 423 patients admitted to the ICU between Sept 1, 2018, and Sept 1, 2019, were assessed and 9887 patients were included. The mean number of administered high-risk drug combinations per 1000 drug administrations per patient was 26·2 (SD 53·4) in the intervention group (n=5534), compared with 35·6 (65·0) in the control group (n=4353). Tailoring potential DDI alerts to the ICU led to a 12% decrease (95% CI 5-18%; p=0·0008) in the number of administered high-risk drug combinations per 1000 drug administrations per patient, after adjusting for clustering and prognostic factors. This cluster randomised stepped-wedge trial showed that tailoring potential DDI alerts to the ICU setting significantly reduced the number of administered high-risk drug combinations. Our list of high-risk drug combinations can be used in other ICUs, and our strategy of tailoring alerts based on clinical relevance could be applied to other clinical settings. ZonMw.

Effect of using smaller blood volume tubes and closed blood collection devices on total blood loss in patients undergoing major cardiac and vascular surgery.

Diagnostic laboratory tests are an integral part of managing hospitalized patients. In particular, patients in the intensive care units (ICUs) can experience a concerning amount of blood loss due to diagnostic testing, which can increase the risk developing iatrogenic anemia. Several interventions exist to curtail avoidable blood loss, for example computerized decision support, smaller phlebotomy tubes, and other blood conservation devices. Nevertheless, use of these interventions is not standardized. Therefore, the objective of our study was to quantify the daily phlebotomy volume taken from patients who had undergone major cardiac or vascular surgery. We estimated the number of blood analyses and volumes of drawn blood of 400 consecutive patients (≥18 yr) undergoing major cardiac or vascular surgery. The amount of blood saved using small-volume tubes and in combination with blood conservation device rather than standard-volume tubes was estimated for serum chemistry (serum), ethylenediaminetetraacetic acid (EDTA) tubes, sodium citrate coagulation (SCC) tubes, and arterial blood gas (ABG) analysis. The mean total blood loss due to phlebotomy drawing using standard-volume tubes during hospitalization was 167.9mL (95% confidence interval [CI], 158.0 to 177.8), 255.6mL (95% CI, 226.5 to 284.6), and 695.3mL (95% CI, 544.1 to 846.4) for patients undergoing cardiac surgery with a hospital length of stay (LOS) of 0-10, 11-20, and ≥ 21 days, respectively. The mean total blood loss due to phlebotomy during hospitalization was 80.5mL (95% CI, 70.5 to 90.6), 225.0mL (95% CI, 135.1 to 314.8mL) and 470.3mL (95% CI, 333.5 to 607.1) for vascular surgery patients with LOS 0-10, 11-20, and ≥ 21 days, respectively. Patients with at least a two-day stay at the ICU had a mean blood loss of 146.6mL (95% CI, 134.6 to 158.6mL) and those with ≥ 11 days incurred a loss of 1,428mL (95% CI, 1,117.8 to 1,739.2). The use of closed blood collection device and small-volume tubes (serum, EDTA, SCC, and ABG) reduced blood loss by 82.8mL for patients with an ICU stay of 2 days and up to 824.0mL for patients with a ICU stay of ≥ 11 days. Diagnostic laboratory tests are associated with significant patient blood loss, but are a modifiable risk factor. The use of small-volume tubes and closed blood collection devices decreases the volume of patient blood drawn for analysis and prevents blood waste.

Implementation of the Profile Matching Algorithm to Identify Outstanding Students at Pesantren Modern Misbahul Ulum

This research aims to design a decision support system to identify outstanding students at the Misbahul Ulum Modern Islamic Boarding School. Although determining outstanding students is done by taking the average score from all aspects of the criteria, the evaluation process which is still carried out manually takes quite a long time. Therefore, a computerized decision support system is needed to help make decisions more efficiently and accurately. This system was developed using the PHP programming language. The aim of this research is to overcome obstacles in recognizing outstanding students at the Misbahul Ulum Modern Islamic Boarding School by applying the Profile Matching Algorithm. This method can provide the best data by comparing alternative values and predetermined criteria. This research contributes to the development of educational technology and facilitates the introduction of outstanding students at the Misbahul Ulum Modern Islamic Boarding School. By determining the criteria aspects, determining the weight value of each aspect, finding the GAP value, and carrying out a ranking process, this research produces objective results. Involving 252 students from grades 7-11, this research produced a final grade for each student. The calculation results show that Zikril got the highest score, while Asma Biwi got the lowest score.

American Burn Association Clinical Practice Guidelines on Burn Shock Resuscitation.

This Clinical Practice Guideline (CPG) addresses the topic of acute fluid resuscitation during the first 48 hours following a burn injury for adults with burns ≥20% of the total body surface area (%TBSA). The listed authors formed an investigation panel and developed clinically relevant PICO (Population, Intervention, Comparator, Outcome) questions. A systematic literature search returned 5978 titles related to this topic and after 3 levels of screening, 24 studies met criteria to address the PICO questions and were critically reviewed. We recommend that clinicians consider the use of human albumin solution, especially in patients with larger burns, to lower resuscitation volumes and improve urine output. We recommend initiating resuscitation based on providing 2 mL/kg/% TBSA burn in order to reduce resuscitation fluid volumes. We recommend selective monitoring of intra-abdominal and intraocular pressure during burn shock resuscitation. We make a weak recommendation for clinicians to consider the use of computer decision support software to guide fluid titration and lower resuscitation fluid volumes. We do not recommend the use of transpulmonary thermodilution-derived variables to guide burn shock resuscitation. We are unable to make any recommendations on the use of high-dose vitamin C (ascorbic acid), fresh frozen plasma (FFP), early continuous renal replacement therapy, or vasopressors as adjuncts during acute burn shock resuscitation. Mortality is an important outcome in burn shock resuscitation, but it was not formally included as a PICO outcome because the available scientific literature is missing studies of sufficient population size and quality to allow us to confidently make recommendations related to the outcome of survival at this time.

Allergy recording in clinical systems: comparing general practice and hospital records

Abstract Introduction Healthcare organisations may have different clinical and administrative electronic systems, meaning there may be gaps in how important information about a patient’s care is communicated effectively between organisations.1 Our current hospital discharge summary does not include a record of patients’ allergies and sensitivities despite this being one of the national standards.2 Furthermore, the electronic transfer of allergy/intolerance data must be classed as machine-readable through coded entries using SNOMED CT or dm+d terminology.3 We wanted to determine whether allergy/sensitivity records in primary and secondary care are transferred accurately and if our hospital discharge summaries should be amended to include allergy information for improved flow of data. Aim To record and compare the number of allergies/sensitivities matched on both the hospital electronic prescribing system (EPS, CareFlow Medicines Management) and a GP practice system (SystmOne), and to determine whether inconsistencies within allergy recording between primary and secondary care are significant, and if there is scope to add allergy recording to eDischarges. Methods A random sample of 150 patients registered with a GP practice who had been admitted to hospital and had undergone recent medicines reconciliations (during 2022/23) and had at least one allergy recorded on the hospital EPS was analysed. Allergy entries (medication or class of medication or other) were collated and analysed using Microsoft Excel. As this project falls under the definition of a service evaluation, according to UK NHS Research Ethics Committees, formal ethical approval was not required. This project was registered on the hospital’s clinical audit database. Results The 150 patients (61% female, mean age 63 years, range 1-97) recorded a total of 350 allergy entries in the hospital EPS system and 294 entries in primary care SystmOne. Only 71 (47%) patients had matching records across both systems. Fifty-two (35%) patients had one or more allergies not recorded on SystmOne compared to EPS, whereas only 16 (11%) patients had one or more allergies not recorded on EPS compared to SystmOne. A total of 11 (7%) patients had one or more inconsistencies across both systems. There were significant issues with how medication names were recorded e.g. generic/brand name for the same medicine. The majority of inconsistencies in records were related to penicillin allergies. Discussion/Conclusion Whilst a small-scale study only, we observed that allergy data is often not transferred accurately between primary and secondary care, resulting in unmatched records and discrepancies, particularly in transfer from secondary to primary care. This limits the potential of computerised decision support systems to help alert clinicians to the risk of further reactions. This problem may be due to a lack of allergy information on the current hospital eDischarge summaries; hence any new allergies identified through medicines reconciliation completed during the admission, or reactions to newly prescribed drugs in hospital, are not transferred. One patient safety improvement would be improved interoperability such that allergies on EPS are included on hospital eDischarge summaries in accordance with PRSB Standards.2 Ideally, this information should be coded in a suitable format to ensure effective transfer onto SystmOne.

Summary of the Best Evidence for Nutritional Support in Patients with Acute Gastrointestinal Graft-Versus-Host Disease

[Abstract] Objective: To retrieve, evaluate and integrate the best evidence summary of nutritional support for patients with acute gastrointestinal graft-versus-host disease after hematopoietic stem cell transplantation at home and abroad. Methods: According to the “6S” model, domestic and foreign computer decision support systems, guideline networks, websites of relevant professional societies or institutions, professional books, and comprehensive databases were systematically searched to screen literatures related to nutritional support for patients with acute gastrointestinal graft-versus-host disease, including guidelines, clinical decision-making, evidence summary, expert consensus, expert opinion, systematic review, and original research. The search time limit was from the establishment of the database to March 2023. Five researchers evaluated the quality of the literature, extracted evidence and integrated it. Results: A total of 12 articles were included, including 1 clinical decision, 4 guidelines, 1 evidence summary, 1 expert consensus, 3 systematic reviews, 1 cohort study, 1 expert opinion,. A total of 14 best evidences were summarized from 4 aspects, including scientific diet and tolerance assessment, nutrient selection, nutritional support method selection, and multidisciplinary cooperation. Conclusions: This study systematically integrates the relevant evidence of nutritional support in patients with acute gastrointestinal graft-versus-host disease, and can provide evidence-based evidence for nutritional support in patients with acute gastrointestinal graft-versus-host disease. When applying evidence, it is recommended that clinical nurses comprehensively consider the actual clinical situation and the wishes of patients, and carefully select evidence. Keywords acute gastrointestinal graft-versus-host disease，nutritional support，malnutrition，evidence-based nursing

Impact of a Decision Support System on Fall-Prevention Nursing Practices.

The aim of this study was to develop a computerized decision support system (CDSS) that could automatically calculate the risk of falls using electronic medical record data and provide evidence-based fall-prevention recommendations based on risk factors. Furthermore, we analyzed the usability and effect of the system on fall-prevention nursing practices. A computerized fall-prevention system was developed according to the system development life cycle, and implemented between March and August 2019 in a single medical unit with a high prevalence of falls. The usability was evaluated 1 month after CDSS implementation. In terms of time and frequency, changes in fall-prevention nursing practices were analyzed using survey data and nursing documentation, respectively. Finally, the incidence of falls before and after system implementation was compared to examine the clinical effectiveness of the CDSS. According to the usability test, the average ease of learning score (5.083 of 7) was the highest among 4 dimensions. The time spent engaged in fall-prevention nursing care per patient per shift increased, particularly for nursing diagnoses and planning. Moreover, the mean frequency of daily documented fall-prevention interventions per patient also increased. Particularly, nursing statements related to nonspecific interventions such as environmental modifications increased. However, the incidence of falls did not decrease after implementation of the CDSS. Although adoption of the computerized system increased the time spent and number of records created in terms of fall-prevention practices in nurses, no improvement in clinical outcomes was observed, particularly in terms of fall rate reduction.

Estimation of Crop Water Requirement for Tomato Plant in Afgoye-Somalia, Using CROPWAT 8.0 Model

Crop water requirement or crop evapotranspiration is a vital parameter for irrigation, and it is necessary to determine the quantity of water to be applied for irrigation and develop an effective irrigation schedule. CROPWAT 8.0, decision-support computer software developed by the United Nations Food Agriculture Organization, is used to calculate crop water requirements. In this paper, the CROPWAT 8.0 model was used to estimate the water requirements of tomato crops in Afgoye. The model estimated that the reference evapotranspiration throughout the year reaches 1927.6 mm and the daily reference evapotranspiration is 5.29 mm. The total annual rainfall reaches 584.0 mm with an effective rainfall of 511.1 mm. The total crop evapotranspiration during the growing period was estimated at 678.2 mm and the total irrigation amount was calculated as 452.3 mm with an effective rainfall of 230.6 mm. During the growing period, the net and gross irrigation reaches 392.9 and 561.3 mm respectively. Field experiments should be conducted in the same season and cropping patterns to validate the accuracy of the crop water requirement prediction.

Artificial intelligence systems in surgery: A review of opportunities, limitations, and prospects

Artificial intelligence technologies are increasingly being applied in a variety of medical disciplines. After reviewing 278 publications from 1985 to 2023, 99 articles were selected from the databases elibrary, PubMed, Medline, WoS, Nature, Springer, and Wiley J Database to present the main approaches and a modern picture of the application of artificial intelligence methods and technologies in pediatric surgery and intensive care. The article examines many facets of artificial intelligence systems for medical uses, namely, computer decision support systems or supporting the surgeon throughout the surgical intervention procedure. Computer analysis of 3D visualization and 3D anatomical modeling of images obtained from computed tomography and magnetic resonance imaging investigations can be used to plan operations. Because of the possibilities of sufficiently accurate 3D models and methods for organs and pathological processes, various methodologies and software tools for preoperative planning and intraoperative support of surgical intervention have been developed. Computer (technical) vision analyzes high-quality medical images and interprets them in multimodal three-dimensional images for computer diagnoses and operations under visual control, including augmented reality methods. Robotic surgery involves manipulators, including remotely controlled ones, and intellectualized complexes that independently perform specific actions of the second assistant surgeon. In intensive care, artificial intelligence technologies are being investigated to merge data from bedside monitors and other information about patients conditions to identify critical situations and control mechanical ventilation. Simultaneously, several obstacles impede the adoption of artificial intelligence in surgery. The nature and standardization of the initial data required for their integration, taking into consideration atypical cases, the possibility of bias in the sample used, and the transparency of the decision-making process in machine learning models are examples. The explanation of solutions presented in machine learning models and the transition to full-fledged validation of the systems being built define the prospects for developing and using artificial intelligence systems.

Adoption of cognitive computing decision support system in the assessment of health-care policymaking

Purpose Despite technological advancements to enhance patient health, the risks of not discovering the correct interactions and trends in digital health are high. Hence, a careful policy is required for health coverage tailored to needs and capacity. Therefore, this study aims to explore the adoption of a cognitive computing decision support system (CCDSS) in the assessment of health-care policymaking and validates it by extending the unified theory of acceptance and use of technology model. Design/methodology/approach A survey was conducted to collect data from different stakeholders, referred to as the 4Ps, namely, patients, providers, payors and policymakers. Structural equation modelling and one-way ANOVA were used to analyse the data. Findings The result reveals that the behavioural insight of policymakers towards the assessment of health-care policymaking is based on automatic and reflective systems. Investments in CCDSS for policymaking assessment have the potential to produce rational outcomes. CCDSS, built with quality procedures, can validate whether breastfeeding-supporting policies are mother-friendly. Research limitations/implications Health-care policies are used by lawmakers to safeguard and improve public health, but it has always been a challenge. With the adoption of CCDSS, the overall goal of health-care policymaking can achieve better quality standards and improve the design of policymaking. Originality/value This study drew attention to how CCDSS as a technology enabler can drive health-care policymaking assessment for each stage and how the technology enabler can help the 4Ps of health-care gain insight into the benefits and potential value of CCDSS by demonstrating the breastfeeding supporting policy.

Improving computerized decision support system interventions: a qualitative study combining the theoretical domains framework with the GUIDES Checklist

BackgroundComputerized clinical decision support systems (CDSSs) can improve care by bridging knowledge to practice gaps. However, the real-world uptake of such systems in health care settings has been suboptimal. We sought to: (1) use the Theoretical Domains Framework (TDF) to identify determinants (barriers/enablers) of uptake of the Electronic Asthma Management System (eAMS) CDSS; (2) match identified TDF belief statements to elements in the Guideline Implementation with Decision Support (GUIDES) Checklist; and (3) explore the relationship between the TDF and GUIDES frameworks and the usefulness of this sequential approach for identifying opportunities to improve CDSS uptake.MethodsIn Phase 1, we conducted semistructured interviews with primary care physicians in Toronto, Canada regarding the uptake of the eAMS CDSS. Using content analysis, two coders independently analyzed interview transcripts guided by the TDF to generate themes representing barriers and enablers to CDSS uptake. In Phase 2, the same reviewers independently mapped each belief statement to a GUIDES domain and factor. We calculated the proportion of TDF belief statements that linked to each GUIDES domain and the proportion of TDF domains that linked to GUIDES factors (and vice-versa) and domains.ResultsWe interviewed 10 participants before data saturation. In Phase 1, we identified 53 belief statements covering 12 TDF domains; 18 (34.0%) were barriers, and 35 (66.0%) were enablers. In Phase 2, 41 statements (77.4%) linked to at least one GUIDES factor, while 12 (22.6%) did not link to any specific factor. The GUIDES Context Domain was linked to the largest number of belief statements (19/53; 35.8%). Each TDF domain linked to one or more GUIDES factor, with 6 TDF domains linking to more than 1 factor and 8 TDF domains linking to more than 1 GUIDES domain.ConclusionsThe TDF provides unique insights into barriers and enablers to CDSS uptake, which can then be mapped to GUIDES domains and factors to identify required changes to CDSS context, content, and system. This can be followed by conventional mapping of TDF domains to behaviour change techniques to optimize CDSS implementation. This novel step-wise approach combines two established frameworks to optimize CDSS interventions, and requires prospective validation.

Resource use and cost associated with computerized decision support system and usual care in managing patients with atrial fibrillation: analysis of IMPACT-AF randomized trial data

BackgroundIMPACT-AF is a prospective, randomized, cluster design trial comparing atrial fibrillation (AF) management with a computerized decision support system (CDS) to usual care (control) in the primary care setting of Nova Scotia, Canada. The objective of this analysis was to compare the resource use and costs between CDS and usual care groups.MethodsCase costing data, 12-month self-administered questionnaires, and monthly diaries from IMPACT-AF were used in this analysis. Descriptive statistics were used to compare costs and resource use between groups. All costs are presented in 2021 Canadian dollars and cover the 12-month period of participation in the study.ResultsA total of 1,145 patients enrolled in the trial. Case costing data were available for 466 participants (41.1%), 12-month self-administered questionnaire data for 635 participants (56.0%) and monthly diary data for 223 participants (19.7%). Emergency department visits and hospitalizations comprised the most expensive component of AF care. Across all three datasets, there were no statistically significant differences in costs or resource use between CDS and usual care groups.ConclusionsAlthough there were no significant differences in resource use or costs among CDS and usual care groups in the IMPACT-AF trial, this study provides insight into the methodology and practical challenges of collecting economic data alongside a trial.RegistrationClinicaltrials.gov (registration number: NCT01927367, date of registration: 2013-08-20).

Assessment of Drug-Induced QTc Prolongation in Mental Health Practice: Validation of an Evidence-Based Algorithm.

Drug-induced QTc interval prolongation (QTcIP) can lead to serious consequences and is often a concern for mental health practitioners, as access to experts such as cardiologists, for consultation is time-limiting and can delay treatment decisions. This research aimed at validating the content of an algorithm for the assessment, management and monitoring of drug-induced QTcIP in mental health practice. Following an initial face validity by content experts, a cross-sectional survey of mental health care practitioners with a 4-point Likert-type scale was used to assess the validity of the decision steps on the QTcIP algorithm (QTcIPA) by estimating the content validity index (CVI) and the modified kappa statistic (κ*). Participants' open-ended comments were also thematically analyzed. Mental health practitioners found the QTcIPA to be appropriate, safe, and evidence-based, as indicated by the high individual item CVI scores ranging from 0.89 to 1 for all of the steps/decision statements in the three domains assessed: appropriateness, safety and reliability of the references used. Five themes emerged from the qualitative analysis of the open-ended comments, of which three were identified as strengths, including practical usability, reliable references and beneficial for pharmacists. Two themes were recognized as limitations, namely, the need for additional clinical content and application barriers. These results suggest that the QTcIPA may be a useful tool for mental health clinicians at the time of prescribing medications with potential risk of QTcIP. Future research will explore the implementation of the QTcIPA into clinical practice using computerized decision support tools through web-based and mobile applications.

Implementation of a Best Practice Advisory to Improve Infection Screening Prior to New Prescriptions of Biologics and Targeted Synthetic Drugs.

Use of biologic and targeted synthetic DMARDs (b/tsDMARDs) in patients with pre-existing tuberculosis (TB), hepatitis B virus (HBV), or hepatitis C virus (HCV) infection can have serious consequences. Although various society guidelines recommend routine screening for these infections prior to initiating certain b/tsDMARDs adherence to these recommendations varies widely. This quality improvement initiative evaluated local compliance with screening and assessed if automated computerized decision support system (CDSS) in the form of a best practice advisory (BPA) in the electronic health record could improve patient screening. Established patients with autoimmune rheumatic disease (ARD) aged 18 years or older with at least one visit to our rheumatology practice between 10/1/2017 and 3/3/2022 were included. When prescribing a new b/tsDMARD, clinicians were alerted via a BPA that showed the most recent results for TB, HBV, and HCV. Screening proportions for TB, HBV, and HCV before BPA initiation were compared with those of eligible patients after the BPA implementation. A total of 711 patients pre-BPA and 257 patients post-BPA implementation were included in the study. The BPA implementation was associated with statistically significant improvement in screening for TB from 66% to 82% (p=<0.001), HCV from 60 to 79% (p=<0.001), hepatitis B core antibody (HBcAb) 32% to 51% (p=<0.001), and hepatitis B surface antigen (HBsAg) from 51% to 70% (p=<0.001). Implementation of a BPA can improve infectious disease screening for patients with ARD who are started on b/tsDMARD and has potential to improve patient safety. This article is protected by copyright. All rights reserved.