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The effect of a Computerised Decision Support System (CDSS) on compliance with the prehospital assessment process: results of an interrupted time-series study.

ABSTRACT: Errors in the decision-making process are probably the main threat to patient safety in the prehospital setting. The reason can be the change of focus in prehospital care from the traditional "scoop and run" practice to a more complex assessment and this new focus imposes real demands on clinical judgment. The use of Clinical Guidelines (CG) is a common strategy for cognitively supporting the prehospital providers. However, there are studies that suggest that the compliance with CG in some cases is low in the prehospital setting. One possible way to increase compliance with guidelines could be to introduce guidelines in a Computerized Decision Support System (CDSS). There is limited evidence relating to the effect of CDSS in a prehospital setting. The present study aimed to evaluate the effect of CDSS on compliance with the basic assessment process described in the prehospital CG and the effect of On Scene Time (OST).In this time-series study, data from prehospital medical records were collected on a weekly basis during the study period. Medical records were rated with the guidance of a rating protocol and data on OST were collected. The difference between baseline and the intervention period was assessed by a segmented regression.In this study, 371 patients were included. Compliance with the assessment process described in the prehospital CG was stable during the baseline period. Following the introduction of the CDSS, compliance rose significantly. The post-intervention slope was stable. The CDSS had no significant effect on OST.The use of CDSS in prehospital care has the ability to increase compliance with the assessment process of patients with a medical emergency. This study was unable to demonstrate any effects of OST.

SUBMITTER: Andersson Hagiwara M

PROVIDER: S-EPMC4136405 | biostudies-other | 2014 Aug

REPOSITORIES: biostudies-other

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The effect of a Computerised Decision Support System (CDSS) on compliance with the prehospital assessment process: results of an interrupted time-series study.

Andersson Hagiwara Magnus M Suserud Björn-Ove BO Andersson-Gäre Boel B Sjöqvist Bengt- Arne B Henricson Maria M Jonsson Anders A

BMC medical informatics and decision making 20140809

<h4>Background</h4>Errors in the decision-making process are probably the main threat to patient safety in the prehospital setting. The reason can be the change of focus in prehospital care from the traditional "scoop and run" practice to a more complex assessment and this new focus imposes real demands on clinical judgment. The use of Clinical Guidelines (CG) is a common strategy for cognitively supporting the prehospital providers. However, there are studies that suggest that the compliance wi ...[more]

PMID: 25106732

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Project description:ObjectivesThe cancer multidisciplinary team (MDT) meeting (MDM) is regarded as the best platform to reduce unwarranted variation in cancer care through evidence-compliant management. However, MDMs are often overburdened with many different agendas and hence struggle to achieve their full potential. The authors developed an interactive clinical decision support system called MATE (Multidisciplinary meeting Assistant and Treatment sElector) to facilitate explicit evidence-based decision making in the breast MDMs.DesignAudit study and a questionnaire survey.SettingBreast multidisciplinary unit in a large secondary care teaching hospital.ParticipantsAll members of the breast MDT at the Royal Free Hospital, London, were consulted during the process of MATE development and implementation. The emphasis was on acknowledging the clinical needs and practical constraints of the MDT and fitting the system around the team's workflow rather than the other way around. Delegates, who attended MATE workshop at the England Cancer Networks' Development Programme conference in March 2010, participated in the questionnaire survey.Outcome measuresThe measures included evidence-compliant care, measured by adherence to clinical practice guidelines, and promoting research, measured by the patient identification rate for ongoing clinical trials.ResultsMATE identified 61% more patients who were potentially eligible for recruitment into clinical trials than the MDT, and MATE recommendations demonstrated better concordance with clinical practice guideline than MDT recommendations (97% of MATE vs 93.2% of MDT; N=984). MATE is in routine use in breast MDMs at the Royal Free Hospital, London, and wider evaluations are being considered.ConclusionsSophisticated decision support systems can enhance the conduct of MDMs in a way that is acceptable to and valued by the clinical team. Further rigorous evaluations are required to examine cost-effectiveness and measure the impact on patient outcomes. The decision support technology used in MATE is generic and if found useful can be applied across medicine.

Project description:ObjectiveTo evaluate effectiveness, safety and cost-effectiveness of Computerised Clinical Decision Support (CCDS) for paramedics attending older people who fall.DesignCluster trial randomised by paramedic; modelling.Setting13 ambulance stations in two UK emergency ambulance services.Participants42 of 409 eligible paramedics, who attended 779 older patients for a reported fall.InterventionsIntervention paramedics received CCDS on Tablet computers to guide patient care. Control paramedics provided care as usual. One service had already installed electronic data capture.Main outcome measuresEffectiveness: patients referred to falls service, patient reported quality of life and satisfaction, processes of care.SafetyFurther emergency contacts or death within one month.Cost-effectivenessCosts and quality of life. We used findings from published Community Falls Prevention Trial to model cost-effectiveness.Results17 intervention paramedics used CCDS for 54 (12.4%) of 436 participants. They referred 42 (9.6%) to falls services, compared with 17 (5.0%) of 343 participants seen by 19 control paramedics [Odds ratio (OR) 2.04, 95% CI 1.12 to 3.72]. No adverse events were related to the intervention. Non-significant differences between groups included: subsequent emergency contacts (34.6% versus 29.1%; OR 1.27, 95% CI 0.93 to 1.72); quality of life (mean SF12 differences: MCS -0.74, 95% CI -2.83 to +1.28; PCS -0.13, 95% CI -1.65 to +1.39) and non-conveyance (42.0% versus 36.7%; OR 1.13, 95% CI 0.84 to 1.52). However ambulance job cycle time was 8.9 minutes longer for intervention patients (95% CI 2.3 to 15.3). Average net cost of implementing CCDS was £208 per patient with existing electronic data capture, and £308 without. Modelling estimated cost per quality-adjusted life-year at £15,000 with existing electronic data capture; and £22,200 without.ConclusionsIntervention paramedics referred twice as many participants to falls services with no difference in safety. CCDS is potentially cost-effective, especially with existing electronic data capture.Trial registrationISRCTN Register ISRCTN10538608.

Project description:ObjectivesAdoption of emergency department (ED) initiation of buprenorphine (BUP) for opioid use disorder (OUD) into routine emergency care has been slow, partly due to clinicians' unfamiliarity with this practice and perceptions that it is complicated and time-consuming. To address these barriers and guide emergency clinicians through the process of BUP initiation, we implemented a user-centered computerized clinical decision support system (CDS). This study was conducted to assess the feasibility of implementation and to evaluate the preliminary efficacy of the intervention to increase the rate of ED-initiated BUP.MethodsAn interrupted time series study was conducted in an urban, academic ED from April 2018 to February 2019 (preimplementation phase), March 2019 to August 2019 (implementation phase), and September 2019 to December 2019 (maintenance phase) to study the effect of the intervention on adult ED patients identified by a validated electronic health record (EHR)-based computable phenotype consisting of structured data consistent with potential cases of OUD who would benefit from BUP treatment. The intervention offers flexible CDS for identification of OUD, assessment of opioid withdrawal, and motivation of readiness to start treatment and automates EHR activities related to ED initiation of BUP (including documentation, orders, prescribing, and referral). The primary outcome was the rate of ED-initiated BUP. Secondary outcomes were launch of the intervention, prescription for naloxone at ED discharge, and referral for ongoing addiction treatment.ResultsOf the 141,041 unique patients presenting to the ED over the preimplementation and implementation phases (i.e., the phases used in primary analysis), 906 (574 preimplementation and 332 implementation) met OUD phenotype and inclusion criteria. The rate of BUP initiation increased from 3.5% (20/574) in the preimplementation phase to 6.6% (22/332) in the implementation phase (p = 0.03). After the temporal trend of the number of physician's with X-waiver training and other covariates were adjusted for, the relative risk of BUP initiation rate was 2.73 (95% confidence interval [CI] = 0.62 to 12.0, p = 0.18). Similarly, the number of unique attendings who initiated BUP increased modestly 7/53 (13.0%) to 13/57 (22.8%, p = 0.10) after offering just-in-time training during the implementation period. The rate of naloxone prescribed at discharge also increased (6.5% preimplementation and 11.5% implementation; p < 0.01). The intervention received a system usability scale score of 82.0 (95% CI = 76.7 to 87.2).ConclusionImplementation of user-centered CDS at a single ED was feasible, acceptable, and associated with increased rates of ED-initiated BUP and naloxone prescribing in patients with OUD and a doubling of the number of unique physicians adopting the practice. We have implemented this intervention across several health systems in an ongoing trial to assess its effectiveness, scalability, and generalizability.

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Project description:BackgroundTelemedicine offers a unique opportunity to improve coordination and administration for urgent patient care remotely. In an emergency setting, it has been used to support first responders by providing telephone or video consultation with specialists at hospitals and through the exchange of prehospital patient information. This technological solution is evolving rapidly, yet there is a concern that it is being implemented without a demonstrated clinical need and effectiveness as well as without a thorough economic evaluation.ObjectiveOur objective is to systematically review whether the clinical outcomes achieved, as reported in the literature, favor telemedicine decision support for medical interventions during prehospital care.MethodsThis systematic review included peer-reviewed journal articles. Searches of 7 databases and relevant reviews were conducted. Eligibility criteria consisted of studies that covered telemedicine as data- and information-sharing and two-way teleconsultation platforms, with the objective of supporting medical decisions (eg, diagnosis, treatment, and receiving hospital decision) in a prehospital emergency setting. Simulation studies and studies that included pediatric populations were excluded. The procedures in this review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. The Risk Of Bias In Non-randomised Studies-of Interventions (ROBINS-I) tool was used for the assessment of risk of bias. The results were synthesized based on predefined aspects of medical decisions that are made in a prehospital setting, which include diagnostic decision support, receiving facility decisions, and medical directions for treatment. All data extractions were done by at least two reviewers independently.ResultsOut of 42 full-text reviews, 7 were found eligible. Diagnostic support and medical direction and decision for treatments were often reported. A key finding of this review was the high agreement between prehospital diagnoses via telemedicine and final in-hospital diagnoses, as supported by quantitative evidence. However, a majority of the articles described the clinical value of having access to remote experts without robust quantitative data. Most telemedicine solutions were evaluated within a feasibility or short-term preliminary study. In general, the results were positive for telemedicine use; however, biases, due to preintervention confounding factors and a lack of documentation on quality assurance and protocol for telemedicine activation, make it difficult to determine the direct effect on patient outcomes.ConclusionsThe information-sharing capacity of telemedicine enables access to remote experts to support medical decision making on scene or in prolonged field care. The influence of human and technology factors on patient care is poorly understood and documented.

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Project description:BackgroundInappropriate antimicrobial use has been shown to be an important determinant of the emergence of antimicrobial resistance (AMR). Health information technology (HIT) in the form of Computerised Decision Support (CDS) represents an option for improving antimicrobial prescribing and containing AMR.ObjectivesTo evaluate the evidence for CDS in improving quantitative and qualitative measures of antibiotic prescribing in inpatient hospital settings.MethodsA systematic literature search was conducted of articles published from inception to 20th December 2014 using eight electronic databases: MEDLINE, EMBASE, PUBMED, Web of Science, CINAHL, Cochrane Library, HMIC and PsychINFo. An updated systematic literature search was conducted from January 1st 2015 to October 1st 2016 using PUBMED. The search strategy used combinations of the following terms: (electronic prescribing) OR (clinical decision support) AND (antibiotic or antibacterial or antimicrobial) AND (hospital or secondary care or inpatient). Studies were evaluated for quality using a 10-point rating scale.ResultsEighty-one studies were identified matching the inclusion criteria. Seven outcome measures were evaluated: adequacy of antibiotic coverage, mortality, volume of antibiotic usage, length of stay, antibiotic cost, compliance with guidelines, antimicrobial resistance, and CDS implementation and uptake. Meta-analysis of pooled outcomes showed CDS significantly improved the adequacy of antibiotic coverage (n = 13; odds ratio [OR], 2.11 [95% CI, 1.67 to 2.66, p ≤ 0.00001]). Also, CDS was associated with marginally lowered mortality (n = 20; OR, 0.85 [CI, 0.75 to 0.96, p = 0.01]). CDS was associated with lower antibiotic utilisation, increased compliance with antibiotic guidelines and reductions in antimicrobial resistance. Conflicting effects of CDS on length of stay, antibiotic costs and system uptake were also noted.ConclusionsCDS has the potential to improve the adequacy of antibiotic coverage and marginally decrease mortality in hospital-related settings.

Dataset Information

The effect of a Computerised Decision Support System (CDSS) on compliance with the prehospital assessment process: results of an interrupted time-series study.

Publications

The effect of a Computerised Decision Support System (CDSS) on compliance with the prehospital assessment process: results of an interrupted time-series study.

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