Impact of a clinical decision support system on pharmacy clinical interventions, documentation efforts, and costs.
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SUBMITTER: Calloway S
PROVIDER: S-EPMC3857121 | biostudies-other | 2013 Oct
REPOSITORIES: biostudies-other
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Project description:ObjectiveTo perform a systematic review of studies that assessed the potential of patient decision support interventions (decision aids) to generate savings.DesignSystematic review.Data sourcesAfter registration with PROSPERO, we searched 12 databases, from inception to 15 March 2013, using relevant MeSH terms and text words. Included studies were assessed with Cochrane's risk of bias method and Drummond's quality checklist for economic studies. Per patient costs and projected savings associated with introducing patient decision support interventions were calculated, as well as absolute changes in treatment rates after implementation.Eligibility criteriaStudies were included if they contained quantitative economic data, including savings, spending, costs, cost effectiveness analysis, cost benefit analysis, or resource utilization. We excluded studies that lacked quantitative data on savings, costs, monetary value, and/or resource utilization.ResultsAfter reviewing 1508 citations, we included seven studies with eight analyses. Of these seven studies, four analyses predicted system-wide savings, with two analyses from the same study. The predicted savings range from $8 (£5, €6) to $3068 (£1868, €2243) per patient. Larger savings accompanied reductions in treatment utilization rates. The impact on utilization rates was mixed. Authors used heterogeneous methods to allocate costs and calculate savings. Quality scores were low to moderate (median 4.5, range 0-8 out of 10), and risk of bias across the studies was moderate to high (3.5, range 3-6 out of 6), with studies predicting the most savings having the highest risk of bias. The range of issues identified in the studies included the relative absence of sensitivity analyses, the absence of incremental cost effectiveness ratios, and short time periods.ConclusionAlthough there is evidence to show that patients choose more conservative approaches when they become better informed, there is insufficient evidence, as yet, to be confident that the implementation of patient decision support interventions leads to system-wide savings. Further work-with sensitivity analyses, longer time horizons, and more contexts-is required to avoid premature or unrealistic expectations that could jeopardize implementation and lead to the loss of already proved benefits.RegistrationPROSPERO registration CRD42012003421.
| S-EPMC3900320 | biostudies-literature
Project description:Clinical decision support systems (CDSSs) are intended to detect drug-related problems in real time and might be of value in healthcare institutions with a clinical pharmacy team. The objective was to report the detection of drug-related problems through a CDSS used by an existing clinical pharmacy team over 22 months. It was a retrospective single-center study. A CDSS was integrated in the clinical pharmacy team in July 2019. The investigating clinical pharmacists evaluated the pharmaceutical relevance and physician acceptance rates for critical alerts (i.e., alerts for drug-related problems arising during on-call periods) and noncritical alerts (i.e., prevention alerts arising during the pharmacist's normal work day) from the CDSS. Of the 3612 alerts triggered, 1554 (43.0%) were critical, and 594 of these 1554 (38.2%) prompted a pharmacist intervention. Of the 2058 (57.0%) noncritical alerts, 475 of these 2058 (23.1%) prompted a pharmacist intervention. About two-thirds of the total pharmacist interventions (PI) were accepted by physicians; the proportion was 71.2% for critical alerts (i.e., 19 critical alerts per month vs. 12.5 noncritical alerts per month). Some alerts were pharmaceutically irrelevant-mainly due to poor performance by the CDSS. Our results suggest that a CDSS is a useful decision-support tool for a hospital pharmacist's clinical practice. It can help to prioritize drug-related problems by distinguishing critical and noncritical alerts. However, building an appropriate organizational structure around the CDSS is important for correct operation.
| S-EPMC10048130 | biostudies-literature
Project description:BACKGROUND:Unnecessary healthcare utilization, non-adherence to current clinical guidelines, or insufficient personalized care are perpetual challenges and remain potential major cost-drivers for healthcare systems around the world. Implementing decision support systems into clinical care is promised to improve quality of care and thereby yield substantial effects on reducing healthcare expenditure. In this article, we evaluate the economic impact of clinical decision support (CDS) interventions based on electronic health records (EHR). METHODS:We searched for studies published after 2014 using MEDLINE, CENTRAL, WEB OF SCIENCE, EBSCO, and TUFTS CEA registry databases that encompass an economic evaluation or consider cost outcome measures of EHR based CDS interventions. Thereupon, we identified best practice application areas and categorized the investigated interventions according to an existing taxonomy of front-end CDS tools. RESULTS AND DISCUSSION:Twenty-seven studies are investigated in this review. Of those, twenty-two studies indicate a reduction of healthcare expenditure after implementing an EHR based CDS system, especially towards prevalent application areas, such as unnecessary laboratory testing, duplicate order entry, efficient transfusion practice, or reduction of antibiotic prescriptions. On the contrary, order facilitators and undiscovered malfunctions revealed to be threats and could lead to new cost drivers in healthcare. While high upfront and maintenance costs of CDS systems are a worldwide implementation barrier, most studies do not consider implementation cost. Finally, four included economic evaluation studies report mixed monetary outcome results and thus highlight the importance of further high-quality economic evaluations for these CDS systems. CONCLUSION:Current research studies lack consideration of comparative cost-outcome metrics as well as detailed cost components in their analyses. Nonetheless, the positive economic impact of EHR based CDS interventions is highly promising, especially with regard to reducing waste in healthcare.
| S-EPMC7491136 | biostudies-literature
Project description: Not available
| S-EPMC10843373 | biostudies-literature
Project description:ObjectiveTo evaluate economic costs from the health system perspective of an electronic health record-based clinical decision support (CDS) tool, TeenBP, designed to assist in the recognition and management of hypertension in youth.MethodsTwenty primary care clinics within an integrated health system were randomized to the TeenBP CDS or usual care (UC), with patient enrollment from 4/15/14 to 4/14/16. The 12-month change in standardized medical care costs for insured patients aged 10 to 17 years without prior hypertension were calculated for each study arm. The primary analysis compared patients with ≥1 visit with blood pressure (BP) ≥95th percentile (isolated hypertensive BP), and secondary analyses compared patients with ≥3 visits within one year with BP ≥95th percentile (incident hypertension). Generalized estimating equation models estimated the difference-in-differences in costs between groups over time.ResultsAmong 925 insured patients with an isolated hypertensive BP, the pre-to-post change in overall costs averaged $22 more for TeenBP CDS versus UC patients over 12 months, but this difference was not statistically significant (P = .723). Among 159 insured patients with incident hypertension, the pre-to-post change in overall costs over 12 months was higher by $227 per person on average for TeenBP CDS versus UC patients, but this difference also was not statistically significant (P = .313).ConclusionsThe TeenBP CDS intervention was previously found to significantly improve identification and management of hypertensive BP in youth, and in this study, we find that this tool did not significantly increase care costs in its first 12 months of clinical use.
| S-EPMC7872738 | biostudies-literature
Project description:We developed a prototype genomic archiving and communications system to securely store genome data and provide clinical decision support (CDS). This system operates on a client-server model. The client encrypts the data, and the server stores data and performs the computations necessary for CDS. Computations are directly performed on encrypted data, and the client decrypts results. The server cannot decrypt inputs or outputs, which provides strong guarantees of security. We have validated our system with three genomics-based CDS applications. The results demonstrate that it is possible to resolve a long-standing dilemma in genomic data privacy and accessibility, by using a principled cryptographical framework and a mathematical representation of genome data and CDS questions.
| S-EPMC8577277 | biostudies-literature
Project description:BackgroundAutomated clinical decision support systems (CDSS) are associated with improvements in health care delivery to those with long-term conditions, including diabetes. A CDSS was introduced to two Scottish regions (combined diabetes population ~30 000) via a national diabetes electronic health record. This study aims to describe users' reactions to the CDSS and to quantify impact on clinical processes and outcomes over two improvement cycles: December 2013 to February 2014 and August 2014 to November 2014.MethodsFeedback was sought via patient questionnaires, health care professional (HCP) focus groups, and questionnaires. Multivariable regression was used to analyze HCP SCI-Diabetes usage (with respect to CDSS message presence/absence) and case-control comparison of clinical processes/outcomes. Cases were patients whose HCP received a CDSS messages during the study period. Closely matched controls were selected from regions outside the study, following similar clinical practice (without CDSS). Clinical process measures were screening rates for diabetes-related complications. Clinical outcomes included HbA1c at 1 year.ResultsThe CDSS had no adverse impact on consultations. HCPs were generally positive toward CDSS and used it within normal clinical workflow. CDSS messages were generated for 5692 cases, matched to 10 667 controls. Following clinic, the probability of patients being appropriately screened for complications more than doubled for most measures. Mean HbA1c improved in cases and controls but more so in cases (-2.3 mmol/mol [-0.2%] versus -1.1 [-0.1%], P = .003).Discussion and conclusionsThe CDSS was well received; associated with improved efficiencies in working practices; and large improvements in guideline adherence. These evidence-based, early interventions can significantly reduce costly and devastating complications.
| S-EPMC5851216 | biostudies-literature
Project description:BACKGROUND:People with low back pain (LBP) in the community often do not receive evidence-based advice and management. Community pharmacists can play an important role in supporting people with LBP as pharmacists are easily accessible to provide first-line care. However, previous research suggests that pharmacists may not consistently deliver advice that is concordant with guideline recommendations and may demonstrate difficulty determining which patients require prompt medical review. A clinical decision support system (CDSS) may enhance first-line care of LBP, but none exists to support the community pharmacist-client consultation. OBJECTIVE:This study aimed to develop a CDSS to guide first-line care of LBP in the community pharmacy setting and to evaluate the pharmacist-reported usability and acceptance of the prototype system. METHODS:A cross-platform Web app for the Apple iPad was developed in conjunction with academic and clinical experts using an iterative user-centered design process during interface design, clinical reasoning, program development, and evaluation. The CDSS was evaluated via one-to-one user-testing with 5 community pharmacists (5 case vignettes each). Data were collected via video recording, screen capture, survey instrument (system usability scale), and direct observation. RESULTS:Pharmacists' agreement with CDSS-generated self-care recommendations was 90% (18/20), with medicines recommendations was 100% (25/25), and with referral advice was 88% (22/25; total 70 recommendations). Pharmacists expressed uncertainty when screening for serious pathology in 40% (10/25) of cases. Pharmacists requested more direction from the CDSS in relation to automated prompts for user input and page navigation. Overall system usability was rated as excellent (mean score 92/100, SD 6.5; 90th percentile compared with similar systems), with acceptance rated as good to excellent. CONCLUSIONS:A novel CDSS (high-fidelity prototype) to enhance pharmacist care of LBP was developed, underpinned by clinical practice guidelines and informed by a multidisciplinary team of experts. User-testing revealed a high level of usability and acceptance of the prototype system, with suggestions to improve interface prompts and information delivery. The small study sample limits the generalizability of the findings but offers important insights to inform the next stage of system development.
| S-EPMC7248808 | biostudies-literature
Project description:BackgroundElectronic medical records are widely used in family practices across Canada and can improve health outcomes. However, recent reports indicate that physicians using electronic medical records work longer and have less direct patient contact which may contribute to burnout. Therefore, new and innovative digital tools are essential to reduce physician workloads and improve patient-physician interaction to address physician burnout. The objective of this study was to assess the efficiency and accuracy of clinical decision-making when using a new preventive care point-of-care clinical decision support system (CDSS). An estimate of the potential annual time savings was also determined. This study also assessed physician reported perceived usefulness and ease of use of the CDSS.MethodsQuantitative and qualitative data were collected during this study. Each participant evaluated two simulated patient charts and identified which preventive care metrics were due. The participants recorded their decisions and the time required to assess each chart. Participants then completed a Technology Acceptance Model survey regarding the perceived usefulness and ease of use of the CDSS, which included qualitative feedback. The amount of time saved was determined and participants' clinical decision-making accuracy was scored against current Canadian preventive care guidelines. The number of preventive care specific visits completed per year was determined using clinic billing data.ResultsThe preventive care CDSS saved an average of 195.7 s of chart review time (249.5 s vs 445.2 s; P < 0.001). A total of 1520 preventive visits were performed at Primrose and Bruyère Family Medicine Centres. Extrapolated across the organization, implementation of the new tool could save 82.6 h per year. Decision-making accuracy was not affected by the new tool (78.4% vs 80.9%, P > 0.05). Participants rated the perceived ease of use and usefulness to be very high.ConclusionsNew digital tools may reduce providers' workload without impacting clinical decision-making accuracy. Participants indicated that the preventive care CDSS was useful and easy to use. Further software development and clinical studies are required to further improve and characterize the effect this new CDSS has when implemented in clinical practice.
| S-EPMC8588582 | biostudies-literature
Project description:BackgroundSpinal disorders are highly prevalent worldwide with high socioeconomic costs. This cost is associated with the demand for treatment and productivity loss, prompting the exploration of technologies to improve patient outcomes. Clinical decision support systems (CDSSs) are computerized systems that are increasingly used to facilitate safe and efficient health care. Their applications range in depth and can be found across health care specialties.ObjectiveThis scoping review aims to explore the use of CDSSs in patients with spinal disorders.MethodsWe used the Joanna Briggs Institute methodological guidance for this scoping review and reported according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) statement. Databases, including PubMed, Embase, Cochrane, CINAHL, Web of Science, Scopus, ProQuest, and PsycINFO, were searched from inception until October 11, 2022. The included studies examined the use of digitalized CDSSs in patients with spinal disorders.ResultsA total of 4 major CDSS functions were identified from 31 studies: preventing unnecessary imaging (n=8, 26%), aiding diagnosis (n=6, 19%), aiding prognosis (n=11, 35%), and recommending treatment options (n=6, 20%). Most studies used the knowledge-based system. Logistic regression was the most commonly used method, followed by decision tree algorithms. The use of CDSSs to aid in the management of spinal disorders was generally accepted over the threat to physicians' clinical decision-making autonomy.ConclusionsAlthough the effectiveness was frequently evaluated by examining the agreement between the decisions made by the CDSSs and the health care providers, comparing the CDSS recommendations with actual clinical outcomes would be preferable. In addition, future studies on CDSS development should focus on system integration, considering end user's needs and preferences, and external validation and impact studies to assess effectiveness and generalizability.Trial registrationOSF Registries osf.io/dyz3f; https://osf.io/dyz3f.
| S-EPMC10988379 | biostudies-literature