Do computerised clinical decision support systems for prescribing change practice? A systematic review of the literature (1990-2007)

Impact of Clinical Decision Support Within the Electronic Medical Record on Opioid Prescribing and Dispensing

INTRODUCTION

Clinical decision support tools support prescribers and pharmacists as they select and verify appropriate opioid regimens in efforts to combat the high variability in opioid prescribing. This study seeks to examine the impact of alerts within the electronic medical record and pharmacy system on day supply of initial opioid prescribing and dispensing.

METHODS

This retrospective study compared a 6-month pre- and postimplementation of clinical decision support tool alerts at an integrated health care system. Data were analyzed to assess changes in the day supply of an opioid at the point of initial prescribing and dispensing based on alerts.

RESULTS

The best practice alert in the electronic medical record was associated with a 27% change (p = 0.007) in prescribing by the physician, which resulted in a reduction of average day supply from 12.09 to 6.58 days. The alert in the pharmacy system was associated with a 41.3% change (p < 0.001) in dispensing, which resulted in a reduction of average day supply from 13.46 to 6.96 days.

DISCUSSION

To promote judicious opioid prescribing, the best practice alert in the electronic medical record led to a statistically significant change in prescribing. To support appropriate dispensing, the alert in the pharmacy system led to a statistically significant change in dispensing.

CONCLUSION

Implementation of two clinical decision support tools that mirrored Centers for Disease Control and Prevention recommendations of prescribing less than a 7-day supply when initiating opioids resulted in a decrease in day supply of the opioid prescription for patients identified as opioid-naïve at the point of prescribing and dispensing.

Improvement in Pharmacy Student Responses to Medication-Related Problems with and without Clinical Decision Support Alerts

OBJECTIVE

To assess pharmacy student responses to medication problems with and without clinical decision support (CDS) alerts during simulated order verification.

METHODS

Three classes of students completed an order verification simulation. The simulation randomized students to a different series of 10 orders with varying CDS alert frequency. Two of the orders contained medication-related problems. The appropriateness of the students' interventions and responses to the CDS alerts were evaluated. In the following semester for 2 classes, 2 similar simulations were completed. All 3 simulations contained 1 problem with and 1 without an alert.

RESULTS

During the first simulation, 384 students reviewed an order with a problem and an alert. Students exposed to prior inappropriate alerts within the simulation had less appropriate responses (66% vs 75%). Of 321 students who viewed a second order with a problem, those reviewing an order lacking an alert recommended an appropriate change less often (45% vs 87%). Among 351 students completing the second simulation, those who participated in the first simulation appropriately responded to the alert for a problem more often than those who only received a didactic debrief (95% vs 87%). Among those completing all 3 simulations, appropriate responses increased between simulations for problems with (n = 238, 72-95-93%) and without alerts (n = 49, 53-71-90%).

CONCLUSIONS

Some pharmacy students displayed baseline alert fatigue and overreliance on CDS alerts for medication problem detection during order verification simulations. Exposure to the simulations improved CDS alert response appropriateness and detection of problems.

Use of an Electronic Medication Management Support System in Patients with Polypharmacy in General Practice: A Quantitative Process Evaluation of the AdAM Trial

Polypharmacy is associated with a risk of negative health outcomes. Potentially inappropriate medications, interactions resulting from contradicting medical guidelines, and inappropriate monitoring, all increase the risk. This process evaluation (PE) of the AdAM study investigates implementation and use of a computerized decision-support system (CDSS). The CDSS analyzes medication appropriateness by including claims data, and hence provides general practitioners (GPs) with full access to patients’ medical treatments. We based our PE on pseudonymized logbook entries into the CDSS and used the four dimensions of the Medical Research Council PE framework. Reach, which examines the extent to which the intended study population was included, and Dose, Fidelity, and Tailoring, which examine how the software was actually used by GPs. The PE was explorative and descriptive. Study participants were representative of the target population, except for patients receiving a high level of nursing care, as they were treated less frequently. GPs identified and corrected inappropriate prescriptions flagged by the CDSS. The frequency and intensity of interventions documented in the form of logbook entries lagged behind expectations, raising questions about implementation barriers to the intervention and the limitations of the PE. Impossibility to connect the CDSS to GPs’ electronic medical records (EMR) of GPs due to technical conditions in the German healthcare system may have hindered the implementation of the intervention. Data logged in the CDSS may underestimate medication changes in patients, as documentation was voluntary and already included in EMR.

The impact of clinical decision support systems on provider behavior in the inpatient setting: A systematic review and meta-analysis

BACKGROUND

Clinical decision support systems (CDSS) are used to improve processes of care. CDSS proliferation may have unintended consequences impacting effectiveness.

OBJECTIVE

To evaluate the effectiveness of CDSS in altering clinician behavior.

DESIGN

Electronic searches were performed in EMBASE, PubMed, and Cochrane Central Register of Control Trials for randomized controlled trials testing the impacted of CDSS on clinician behavior from 2000-2021. Extracted data included study design, CDSS attributed and outcomes, user characteristics, settings, and risk of bias. Eligible studies were analyzed qualitatively to describe CDSS types. Studies with sufficient outcome data were included in the meta-analysis.

SETTING AND PARTICIPANTS

Adult inpatients in the United States.

INTERVENTION

Clinical decision support system versus non-clinical decision support system.

MAIN OUTCOME AND MEASURE

A random-effects model measured the pooled risk difference (RD) and odds ratio of clinicians' adherence to CDSS; subgroup analyses tested differences in CDSS effectiveness over time and by CDSS type.

RESULTS

Qualitative synthesis included 22 studies. Eleven studies reported sufficient outcome data for inclusion in the meta-analysis. CDSS did not result in a statistically significant increase in clinician adoption of desired practicies (RD = 0.04 [95% confidence interval {CI} 0.00, 0.07]). CDSS from 2010-2015 (n = 5) did not increase clinician adoption of desired practice [RD -0.01, (95% CI -0.04, 0.02)].CDSS from 2016-2021 (n = 6) were associated with an increase in targeted practices [RD 0.07 (95% CI0.03, 0.12)], pInteraction = 0.004. EHR [RD 0.04 (95% CI 0.00, 0.08)] vs. non-EHR [RD 0.01 (95% CI -0.01, 0.04)] based CDSS interventions did not result in different adoption of desired practices (pInteraction = 0.27). The meta-analysis did not find an overall positive impact of CDSS on clinician behavior in the inpatient setting.

Implementation strategies for knowledge products in primary healthcare: a systematic review of systematic reviews (Preprint)

Background

The underuse or overuse of knowledge products leads to waste in health care, and primary care is no exception.

Objective

This study aimed to characterize which knowledge products are frequently implemented, the implementation strategies used in primary care, and the implementation outcomes that are measured.

Methods

We performed a systematic review (SR) of SRs using the Cochrane systematic approach to include eligible SRs. The inclusion criteria were any primary care contexts, health care professionals and patients, any Effective Practice and Organization of Care implementation strategies of specified knowledge products, any comparators, and any implementation outcomes based on the Proctor framework. We searched the MEDLINE, EMBASE, CINAHL, Ovid PsycINFO, Web of Science, and Cochrane Library databases from their inception to October 2019 without any restrictions. We searched the references of the included SRs. Pairs of reviewers independently performed selection, data extraction, and methodological quality assessment by using A Measurement Tool to Assess Systematic Reviews 2. Data extraction was informed by the Effective Practice and Organization of Care taxonomy for implementation strategies and the Proctor framework for implementation outcomes. We performed a descriptive analysis and summarized the results by using a narrative synthesis.

Results

Of the 11,101 records identified, 81 (0.73%) SRs were included. Of these 81, a total of 47 (58%) SRs involved health care professionals alone. Moreover, 15 SRs had a high or moderate methodological quality. Most of them addressed 1 type of knowledge product (56/81, 69%), common clinical practice guidelines (26/56, 46%) or management, and behavioral or pharmacological health interventions (24/56, 43%). Mixed strategies were used for implementation (67/81, 83%), predominantly education-based (meetings in 60/81, 74%; materials distribution in 59/81, 73%; and academic detailing in 45/81, 56%), reminder (53/81, 36%), and audit and feedback (40/81, 49%) strategies. Education meetings (P=.13) and academic detailing (P=.11) seemed to be used more when the population was composed of health care professionals alone. Improvements in the adoption of knowledge products were the most commonly measured outcome (72/81, 89%). The evidence level was reported in 12% (10/81) of SRs on 62 outcomes (including 48 improvements in adoption), of which 16 (26%) outcomes were of moderate or high level.

Conclusions

Clinical practice guidelines and management and behavioral or pharmacological health interventions are the most commonly implemented knowledge products and are implemented through the mixed use of educational, reminder, and audit and feedback strategies. There is a need for a strong methodology for the SR of randomized controlled trials to explore their effectiveness and the entire cascade of implementation outcomes.

Deep Learning-Based Emergency Care Process Reengineering of Interventional Data for Patients with Emergency Time-Series Events of Myocardial Infarction

This paper proposes a representation learning framework HE-LSTM model for heterogeneous temporal events, which can automatically adapt to the multiscale sampling frequency of multisource heterogeneous data. The proposed model also demonstrates its superiority over other typical approaches on real data sets. A controlled study is performed according to computerized randomization, with 38 patients in each of the two groups. The study group has a higher resuscitation success rate and patient satisfaction than the conventional group (P < 0.05), and the time from the first consultation to the completion of the first ECG, the time from the completion of the ECG to the activation of the path lab, and the time from the emergency admission to the balloon dilation were significantly shorter in the study group than in the conventional group (P < 0.05). The emergency care process reengineering intervention helps patients with acute myocardial infarction to be treated quickly and effectively, thus improving their resuscitation success rate and satisfaction rate, and is worthy to be caused in the clinic and widely applied.

Cost-effectiveness and Economic Benefit of Continuous Professional Development for Drug Prescribing: A Systematic Review

Importance

The economic impact of continuous professional development (CPD) education is incompletely understood.

Objective

To systematically identify and synthesize published research examining the costs associated with physician CPD for drug prescribing.

Evidence Review

MEDLINE, Embase, PsycInfo, and the Cochrane Database were searched from inception to April 23, 2020, for comparative studies that evaluated the cost of CPD focused on drug prescribing. Two reviewers independently screened all articles for inclusion and reviewed all included articles to extract data on participants, educational interventions, study designs, and outcomes (costs and effectiveness). Results were synthesized for educational costs, health care costs, and cost-effectiveness.

Findings

Of 3338 articles screened, 38 were included in this analysis. These studies included at least 15 659 health care professionals and 1 963 197 patients. Twelve studies reported on educational costs, ranging from $281 to $183 554 (median, $15 664). When economic outcomes were evaluated, 31 of 33 studies (94%) comparing CPD with no intervention found that CPD was associated with reduced health care costs (drug costs), ranging from $4731 to $6 912 000 (median, $79 373). Four studies found reduced drug costs for 1-on-1 outreach compared with other CPD approaches. Regarding cost-effectiveness, among 5 studies that compared CPD with no intervention, the incremental cost-effectiveness ratio for a 10% improvement in prescribing ranged from $15 390 to $437 027 to train all program participants. Four comparisons of alternative CPD approaches found that 1-on-1 educational outreach was more effective but more expensive than group education or mailed materials (incremental cost-effectiveness ratio, $18-$4105 per physician trained).

Conclusions and Relevance

In this systematic review, CPD for drug prescribing was associated with reduced health care (drug) costs. The educational costs and cost-effectiveness of CPD varied widely. Several CPD instructional approaches (including educational outreach) were more effective but more costly than comparators.

Improving Clinician Decisions and Communication in Critical Care Using Novel Information Technology

INTRODUCTION

The electronic medical record (EMR) is presumed to support clinician decisions by documenting and retrieving patient information. Research shows that the EMR variably affects patient care and clinical decision making. The way information is presented likely has a significant impact on this variability. Well-designed representations of salient information can make a task easier by integrating information in useful patterns that clinicians use to make improved clinical judgments and decisions. Using Cognitive Systems Engineering methods, our research team developed a novel health information technology (NHIT) that interfaces with the EMR to display salient clinical information and enabled communication with a dedicated text-messaging feature. The software allows clinicians to customize displays according to their role and information needs. Here we present results of usability and validation assessments of the NHIT.

MATERIALS AND METHODS

Our subjects were physicians, nurses, respiratory therapists, and physician trainees. Two arms of this study were conducted, a usability assessment and then a validation assessment. The usability assessment was a computer-based simulation using deceased patient data. After a brief five-minute orientation, the usability assessment measured individual clinician performance of typical tasks in two clinical scenarios using the NHIT. The clinical scenarios included patient admission to the unit and patient readiness for surgery. We evaluated clinician perspective about the NHIT after completing tasks using 7-point Likert scale surveys. In the usability assessment, the primary outcome was participant perceptions about the system's ease of use compared to the legacy system.A subsequent cross-over, validation assessment compared performance of two clinical teams during simulated care scenarios: one using only the legacy IT system and one using the NHIT in addition to the legacy IT system. We oriented both teams to the NHIT during a 1-hour session on the night before the first scenario. Scenarios were conducted using high-fidelity simulation in a real burn intensive care unit room. We used observations, task completion times, semi-structured interviews, and surveys to compare user decisions and perceptions about their performance. The primary outcome for the validation assessment was time to reach accurate (correct) decision points.

RESULTS

During the usability assessment, clinicians were able to complete all tasks requested. Clinicians reported the NHIT was easier to use and the novel information display allowed for easier data interpretation compared to subject recollection of the legacy EMR.In the validation assessment, a more junior team of clinicians using the NHIT arrived at accurate diagnoses and decision points at similar times as a more experienced team. Both teams noted improved communication between team members when using the NHIT and overall rated the NHIT as easier to use than the legacy EMR, especially with respect to finding information.

CONCLUSIONS

The primary findings of these assessments are that clinicians found the NHIT easy to use despite minimal training and experience and that it did not degrade clinician efficiency or decision-making accuracy. These findings are in contrast to common user experiences when introduced to new EMRs in clinical practice.

The impact of the implementation of a clinical decision support system on the quality of healthcare services in a primary care setting

Background

In July 2015, King Faisal Hospital Family Medicine clinics (KFH-FMC) successfully implemented a paperless, fully integrated, electronic healthcare system. The aim of this study is to evaluate the impact of moving to a fully integrated electronic medical record system, with clinical decision support (CDS) systems, on the quality of healthcare services in a primary care setting. We aim to evaluate the impact of CDS on clinical outcomes such as screening and diagnosis of breast and colorectal cancers, as well as the management of chronic diseases such as diabetes and hypertension, and the uptake of immunizations.

Inclusion and Exclusion Criteria

Our study included all adult patients, over the age of 18, registered in the Family Medicine clinic linked to King Faisal Hospital, seen between January 2012 and December 2018.

Design

Retrospective cohort study.

Setting

Family Medicine clinics at King Faisal Hospital (KFH-FMC).

Materials and Methods

Data were collected retrospectively from the electronic health records of all adult patients above 18 years of age, who were seen in KFH-FMC between January 2012 and December 2018. We analyzed several processes of care and a number of clinical outcomes, comparing results for the three and a half years before CDS implementation with the three and a half years after implementation. Data collected included blood pressure measurements, lipid levels, HbA1c for diabetic patients, screening tests done, including PAP smear, mammogram, fecal occult blood tests, and bone densitometry. Other data included cancer diagnoses and immunizations received.

Results

Significant increases were found in adult vaccine uptake ranging from an 11-fold increase in influenza uptake, to a 22-fold increase in pneumococcal 23 uptake. The uptake of all the cancer screening tests increased (FOB 66%, mammogram 33%, PAP smear 16%). Diagnoses of breast and colorectal cancer showed significant increases. Breast cancer diagnoses increased from 2 to 14, and colorectal cancer from 3 to 11. No significant improvement was found in chronic disease outcomes.

Discussion

The electronic health record with CDS led to significantly improved uptake of immunizations and screening tests, with earlier diagnoses of breast and colon cancer. Evidence of improvement in chronic disease outcomes is still lacking.

Clinical decision support systems-based interventions to improve medication outcomes: A systematic literature review on features and effects

Background: Clinical decision support systems (CDSSs) interventions were used to improve the life quality and safety in patients and also to improve practitioner performance, especially in the field of medication. Therefore, the aim of the paper was to summarize the available evidence on the impact, outcomes and significant factors on the implementation of CDSS in the field of medicine. Methods: This study is a systematic literature review. PubMed, Cochrane Library, Web of Science, Scopus, EMBASE, and ProQuest were investigated by 15 February 2017. The inclusion requirements were met by 98 papers, from which 13 had described important factors in the implementation of CDSS, and 86 were medicated-related. We categorized the system in terms of its correlation with medication in which a system was implemented, and our intended results were examined. In this study, the process outcomes (such as; prescription, drug-drug interaction, drug adherence, etc.), patient outcomes, and significant factors affecting the implementation of CDSS were reviewed. Results: We found evidence that the use of medication-related CDSS improves clinical outcomes. Also, significant results were obtained regarding the reduction of prescription errors, and the improvement in quality and safety of medication prescribed. Conclusion: The results of this study show that, although computer systems such as CDSS may cause errors, in most cases, it has helped to improve prescribing, reduce side effects and drug interactions, and improve patient safety. Although these systems have improved the performance of practitioners and processes, there has not been much research on the impact of these systems on patient outcomes.

Artificial Intelligence in Decision-Making for Colorectal Cancer Treatment Strategy: An Observational Study of Implementing Watson for Oncology in a 250-Case Cohort

Background

Personalized and novel evidence-based clinical treatment strategy consulting for colorectal cancer has been available through various artificial intelligence (AI) supporting systems such as Watson for Oncology (WFO) from IBM. However, the potential effects of this supporting tool in cancer care have not been thoroughly explored in real-world studies. This research aims to investigate the concordance between treatment recommendations for colorectal cancer patients made by WFO and a multidisciplinary team (MDT) at a major comprehensive gastrointestinal cancer center.

Methods

In this prospective study, both WFO and the blinded MDT's treatment recommendations were provided concurrently for enrolled colorectal cancers of stages II to IV between March 2017 and January 2018 at Shanghai Minimally Invasive Surgery Center. Concordance was achieved if the cancer team's decisions were listed in the "recommended" or "for consideration" classification in WFO. A review was carried out after 100 cases for all non-concordant patients to explain the inconsistency, and corresponding feedback was given to WFO's database. The concordance of the subsequent cases was analyzed to evaluate both the performance and learning ability of WFO.

Results

Overall, 250 patients met the inclusion criteria and were recruited in the study. Eighty-one were diagnosed with colon cancer and 189 with rectal cancer. The concordances for colon cancer, rectal cancer, or overall were all 91%. The overall rates were 83, 94, and 88% in subgroups of stages II, III, and IV. When categorized by treatment strategy, concordances were 97, 93, 89, 87, and 100% for neoadjuvant, surgery, adjuvant, first line, and second line treatment groups, respectively. After analyzing the main factors causing discordance, relative updates were made in the database accordingly, which led to the concordance curve rising in most groups compared with the initial rates.

Conclusion

Clinical recommendations made by WFO and the cancer team were highly matched for colorectal cancer. Patient age, cancer stage, and the consideration of previous therapy details had a significant influence on concordance. Addressing these perspectives will facilitate the use of the cancer decision-support systems to help oncologists achieve the promise of precision medicine.

An EMR-Based Alert with Brief Provider-Led ART Adherence Counseling: Promising Results of the InfoPlus Adherence Pilot Study Among Haitian Adults with HIV Initiating ART

To promote HIV antiretroviral therapy (ART) outcomes in Haiti, we developed a culturally relevant intervention (InfoPlus Adherence) that combines an electronic medical record alert identifying patients at elevated risk of treatment failure and provider-delivered brief problem-solving counseling. We conducted a quasi-experimental mixed-methods study among 146 patients at two large ART clinics in Haiti with 728 historical controls. We conducted quantitative assessments of patients at baseline and intervention completion (6 months) as well as focus groups with health workers and exit interviews with patients. The primary quantitative outcome measures were HIV viral suppression according to medical record and ART adherence in terms of ≥ 90% for "proportion of days covered" (PDC) according to pharmacy dispensing data. Results indicated that the proportion of intervention patients with suppressed VL during the study/historical periods was 80.0%/86.0% and 76.8%/87.4% for controls. In a difference-in-differences (DID) analytic model, the adjusted relative risk for viral suppression with the intervention was 1.15 (95% CI 0.92-1.45, p = 0.21), representing favorable but non-significant association between the intervention and the trajectory of VL outcomes. PDC ≥ 90% during the study/historical periods was 30.9%/11.0% among intervention participants and 16.9%/19.4% among controls. In the adjusted DID model, the relative risk for of PDC ≥ 90% with the intervention was 4.00 (95% CI 1.91-8.38, p < 0.001), representing a highly favorable association between the intervention and the trajectory of PDC outcomes. Qualitative data affirmed acceptability of the intervention, although providers reported some challenges consistently implementing it. Future research is needed to demonstrate efficacy and explore optimal implementation strategies.

[Decision support systems, assistance systems and telemedicine in epileptology]

Hintergrund

Die wissenschaftlichen Erkenntnisse über Epilepsien und deren klinische Implikationen nehmen rasant zu. Für Nichtexperten stellt sich die zunehmende Herausforderung, den Überblick hierüber zu bewahren. Hier setzen Clinical-decision-support-Systeme (CDSS) an, indem sie standard- und expertengetriggertes Wissen zur Diagnostik und Therapie individualisiert und automatisiert liefern. Zudem sind Medizin-Apps und telemedizinische Verfahren zur Diagnostik und Therapie sowie Assistenzsysteme zur Anfallsdetektion bei Epilepsien verfügbar.

Ziel der Arbeit

Es soll ein Überblick über die aktuellen Entwicklungen und Anwendungsmöglichkeiten verfügbarer tele-epileptologischer Methoden gegeben werden.

Material und Methoden

Auf der Basis persönlicher Kenntnis und eines Literaturreviews werden epilepsiespezifische CDSS, Medizin-Apps, Assistenzsysteme sowie telemedizinische Anwendungen charakterisiert und deren klinische Einsatzmöglichkeiten dargestellt.

Ergebnisse und Diskussion

Personen mit Epilepsie könnten aufgrund des chronischen Verlaufs und der Komplexität der Erkrankung und ihrer Folgen von CDSS profitieren. Es erscheint wünschenswert, dass epilepsiespezifische CDSS sowohl für die Behandelnden als auch für Patienten nutzbar werden. Apps für Menschen mit Epilepsie dienen derzeit meist der Verlaufsdokumentation von Anfallsfrequenz, Medikamentencompliance und Nebenwirkungen. Gegenwärtige Anfallsdetektionssysteme erkennen vor allem generalisiert tonisch-klonische Anfälle (GTKA). Ein klinischer Nutzen ist noch nicht hinreichend belegt, erscheint aber wahrscheinlich, insbesondere da GTKA mit dem Risiko eines plötzlichen Todes von Epilepsiepatienten assoziiert sind und Interventionen als wirksam gelten.

Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by behavioral alterations and currently affect about 1% of children. Significant genetic factors and mechanisms underline the causation of ASD. Indeed, many affected individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single-gene disorders or variants. However, a range of metabolic abnormalities has been highlighted in many patients, by identifying biofluid metabolome and proteome profiles potentially usable as ASD biomarkers. Indeed, next-generation sequencing and other omics platforms, including proteomics and metabolomics, have uncovered early age disease biomarkers which may lead to novel diagnostic tools and treatment targets that may vary from patient to patient depending on the specific genomic and other omics findings. The progressive identification of new proteins and metabolites acting as biomarker candidates, combined with patient genetic and clinical data and environmental factors, including microbiota, would bring us towards advanced clinical decision support systems (CDSSs) assisted by machine learning models for advanced ASD-personalized medicine. Herein, we will discuss novel computational solutions to evaluate new proteome and metabolome ASD biomarker candidates, in terms of their recurrence in the reviewed literature and laboratory medicine feasibility. Moreover, the way to exploit CDSS, performed by artificial intelligence, is presented as an effective tool to integrate omics data to electronic health/medical records (EHR/EMR), hopefully acting as added value in the near future for the clinical management of ASD.

A Conceptual Framework to Study the Implementation of Clinical Decision Support Systems (BEAR): Literature Review and Concept Mapping

Background

The implementation of clinical decision support systems (CDSSs) as an intervention to foster clinical practice change is affected by many factors. Key factors include those associated with behavioral change and those associated with technology acceptance. However, the literature regarding these subjects is fragmented and originates from two traditionally separate disciplines: implementation science and technology acceptance.

Objective

Our objective is to propose an integrated framework that bridges the gap between the behavioral change and technology acceptance aspects of the implementation of CDSSs.

Methods

We employed an iterative process to map constructs from four contributing frameworks—the Theoretical Domains Framework (TDF); the Consolidated Framework for Implementation Research (CFIR); the Human, Organization, and Technology-fit framework (HOT-fit); and the Unified Theory of Acceptance and Use of Technology (UTAUT)—and the findings of 10 literature reviews, identified through a systematic review of reviews approach.

Results

The resulting framework comprises 22 domains: agreement with the decision algorithm; attitudes; behavioral regulation; beliefs about capabilities; beliefs about consequences; contingencies; demographic characteristics; effort expectancy; emotions; environmental context and resources; goals; intentions; intervention characteristics; knowledge; memory, attention, and decision processes; patient–health professional relationship; patient’s preferences; performance expectancy; role and identity; skills, ability, and competence; social influences; and system quality. We demonstrate the use of the framework providing examples from two research projects.

Conclusions

We proposed BEAR (BEhavior and Acceptance fRamework), an integrated framework that bridges the gap between behavioral change and technology acceptance, thereby widening the view established by current models.

Association of out-of-pocket costs on adherence to common neurologic medications

OBJECTIVE

To determine the association between out-of-pocket costs and medication adherence in 3 common neurologic diseases.

METHODS

Utilizing privately insured claims from 2001 to 2016, we identified patients with incident neuropathy, dementia, or Parkinson disease (PD). We selected patients who were prescribed medications with similar efficacy and tolerability, but differential out-of-pocket costs (neuropathy with gabapentinoids or mixed serotonin/norepinephrine reuptake inhibitors [SNRIs], dementia with cholinesterase inhibitors, PD with dopamine agonists). Medication adherence was defined as the number of days supplied in the first 6 months. Instrumental variable analysis was used to estimate the association of out-of-pocket costs and other patient factors on medication adherence.

RESULTS

We identified 52,249 patients with neuropathy on gabapentinoids, 5,246 patients with neuropathy on SNRIs, 19,820 patients with dementia on cholinesterase inhibitors, and 3,130 patients with PD on dopamine agonists. Increasing out-of-pocket costs by $50 was associated with significantly lower medication adherence for patients with neuropathy on gabapentinoids (adjusted incidence rate ratio [IRR] 0.91, 0.89-0.93) and dementia (adjusted IRR 0.88, 0.86-0.91). Increased out-of-pocket costs for patients with neuropathy on SNRIs (adjusted IRR 0.97, 0.88-1.08) and patients with PD (adjusted IRR 0.90, 0.81-1.00) were not significantly associated with medication adherence. Minority populations had lower adherence with gabapentinoids and cholinesterase inhibitors compared to white patients.

CONCLUSIONS

Higher out-of-pocket costs were associated with lower medication adherence in 3 common neurologic conditions. When prescribing medications, physicians should consider these costs in order to increase adherence, especially as out-of-pocket costs continue to rise. Racial/ethnic disparities were also observed; therefore, minority populations should receive additional focus in future intervention efforts to improve adherence.

Computerized Clinical Decision Support System for Prompting Brief Alcohol Interventions with Treatment Seeking Smokers: A Sex-Based Secondary Analysis of a Cluster Randomized Trial

Although brief alcohol intervention can reduce alcohol use for both men and women, health care providers (HCPs) are less likely to discuss alcohol use or deliver brief intervention to women compared to men. This secondary analysis examined whether previously reported outcomes from a cluster randomized trial of a clinical decision support system (CDSS)-prompting delivery of a brief alcohol intervention (an educational alcohol resource) for patients drinking above cancer guidelines-were moderated by patients' sex. Patients (n = 5702) enrolled in a smoking cessation program at primary care sites across Ontario, Canada, were randomized to either the intervention (CDSS) or control arm (no CDSS). Logistic generalized estimating equations models were fit for the primary and secondary outcome (HCP offer of resource and patient acceptance of resource, respectively). Previously reported results showed no difference between treatment arms in HCP offers of an educational alcohol resource to eligible patients, but there was increased acceptance of the alcohol resource among patients in the intervention arm. The results of this study showed that these CDSS intervention effects were not moderated by sex, and this can help inform the development of a scalable strategy to overcome gender disparities in alcohol intervention seen in other studies.

High-risk nonsteroidal anti-inflammatory drugs prescribing in primary care: results from National Medical Care Survey Malaysia

Background Information on the extent of high-risk prescribing for nonsteroidal anti-inflammatory drugs (NSAIDs) across developing countries is scarce. Objectives This study examines the prescribing pattern for NSAIDs in primary care, assesses the extent of high-risk NSAIDs prescribing and identifies associated factors. Setting 129 public and 416 private primary care clinics in Malaysia. Methods Data were derived from the National Medical Care Survey 2014, a cross-sectional survey on primary care morbidity patterns and clinical activities in Malaysia. Types of NSAIDs, indications for NSAIDs use and proportion of high-risk NSAIDs prescribing were assessed. Factors associated with high-risk NSAIDs prescribing were identified with a multivariable logistic regression. Weighted results, adjusted for sampling design and non-response were presented. Main outcome measures Prescribing pattern of NSAIDs, proportion of high-risk NSAIDs prescribing and its associated factors. Results Among the 55,489 patients who received NSAIDs, diclofenac was the most frequently prescribed NSAID (40.5%, 95% CI 40.1-40.9%), followed by mefenamic acid (29.2%, 95% CI 28.8-29.6%). The commonest indications for NSAIDs use were musculoskeletal condition and respiratory tract infection, both at 17.8% (95% CI 17.4-18.1%). A total of 22.9% (95% CI 22.6-23.3%) patients received high-risk NSAID prescriptions. Of these, 47.8% (95% CI 46.9-48.7%) did not receive adequate gastroprotection despite being at risk, 24.8% (95% CI 24.0-25.5%) were prescribed NSAIDs despite having cardiovascular comorbidities and 22.4% (95% CI 21.7-23.2%) were prescribed high-dose NSAIDs. The odds of receiving high-risk NSAID prescriptions increased with the number of drugs prescribed (OR 1.23, 95% CI 1.06-1.43) and the number of diagnoses in one visit (OR 2.21, 95% CI 1.71-2.86). The odds of being prescribed high-risk NSAID prescriptions were lower in patients with secondary (OR 0.52, 95% CI 0.35-0.77) and tertiary education (OR 0.39, 95% CI 0.22-0.68) compared to patients without formal education. Patients' citizenship, indication for NSAID prescriptions and whether a medical certificate was issued were also significantly associated with the likelihood of receiving high-risk NSAID prescriptions. Conclusions A quarter of NSAIDs prescribed in Malaysian primary care setting is categorised as high-risk prescribing. Targeted strategies are necessary to improve patient safety.

Do computerized clinical decision support systems improve the prescribing of oral anticoagulants? A systematic review

BACKGROUND

Serious adverse drug reactions have been associated with the underuse or the misuse of oral anticoagulant therapy. We systematically reviewed the impact of computerized clinical decision support systems (CDSS) on the prescribing of oral anticoagulants and we described CDSS features associated with success or failure.

METHODS

We searched Medline, Embase, CENTRAL, CINHAL, and PsycINFO for studies that compared CDSS for the initiation or monitoring of oral anticoagulants with routine care. Two reviewers performed study selection, data collection, and risk-of-bias assessment. Disagreements were resolved with a third reviewer. Potentially important CDSS features, identified from previous literature, were evaluated.

RESULTS

Sixteen studies were included in our qualitative synthesis. Most trials were performed in primary care (n = 7) or hospitals (n = 6) and included atrial fibrillation (AF) patients (n = 9). Recommendations mainly focused on anticoagulation underuse (n = 11) and warfarin-drug interactions (n = 5). Most CDSS were integrated in electronic records or prescribing and provided support automatically at the time and location of decision-making. Significant improvements in practitioner performance were found in 9 out of 16 studies, while clinical outcomes were poorly reported. CDSS features seemed slightly more common in studies that demonstrated improvement.

CONCLUSIONS

CDSS might positively impact the use of oral anticoagulants in AF patients at high risk of stroke. The scope of CDSS should now evolve to assist prescribers in selecting the most appropriate and tailored medication. Efforts should nevertheless be made to improve the relevance of notifications and to address implementation outcomes.

Randomized controlled trial of a clinical decision support system for painful polyneuropathy

INTRODUCTION

Despite the existence of guidelines, painful neuropathy is often inappropriately treated. We sought to determine the effectiveness of a clinical decision support system on guideline-recommended medication use.

METHODS

We randomized neurology providers, stratified by subspecialty, to a best practice alert (BPA) linked to a Smartset or a BPA alone when seeing patients with neuropathy. The primary outcome was the proportion of patients with uncontrolled nerve pain prescribed a guideline-recommended medication. Generalized estimating equations were used to assess effectiveness.

RESULTS

Seventy-five neurology providers (intervention 38, control 37) treated 2697 patients with neuropathy (intervention 1026, control 671). Providers did not acknowledge the BPA in 1928 (71.5%) visits. Only four of eight intervention arm neurologists who treated patients with uncontrolled nerve pain opened the Smartset. The intervention was not associated with guideline-recommended medication use (odds ratio 0.52, 0.18-1.48; intervention 52%, control 54.8%).

DISCUSSION

Our intervention did not improve prescribing practices for painful neuropathy. Physicians typically ignored the BPAs/Smartset; therefore, future studies should mandate their use or employ alternate strategies.

Merits, features, and desiderata to be considered when developing electronic health records with embedded clinical decision support systems in Palestinian hospitals: a consensus study

BACKGROUND

Electronic health records (EHRs) with embedded clinical decision support systems (CDSSs) have the potential to improve healthcare delivery. This study was conducted to explore merits, features, and desiderata to be considered when planning for, designing, developing, implementing, piloting, evaluating, maintaining, upgrading, and/or using EHRs with CDSSs.

METHODS

A mixed-method combining the Delphi technique and Analytic Hierarchy Process was used. Potentially important items were collected after a thorough search of the literature and from interviews with key contact experts (n = 19). Opinions and views of the 76 panelists on the use of EHRs were also explored. Iterative Delphi rounds were conducted to achieve consensus on 122 potentially important items by a panel of 76 participants. Items on which consensus was achieved were ranked in the order of their importance using the Analytic Hierarchy Process.

RESULTS

Of the 122 potentially important items presented to the panelists in the Delphi rounds, consensus was achieved on 110 (90.2%) items. Of these, 16 (14.5%) items were related to the demographic characteristics of the patient, 16 (14.5%) were related to prescribing medications, 16 (14.5%) were related to checking prescriptions and alerts, 14 (12.7%) items were related to the patient's identity, 13 (11.8%) items were related to patient assessment, 12 (10.9%) items were related to the quality of alerts, 11 (10%) items were related to admission and discharge of the patient, 9 (8.2%) items were general features, and 3 (2.7%) items were related to diseases and making diagnosis.

CONCLUSIONS

In this study, merits, features, and desiderata to be considered when planning for, designing, developing, implementing, piloting, evaluating, maintaining, upgrading, and/or using EHRs with CDSSs were explored. Considering items on which consensus was achieved might promote congruence and safe use of EHRs. Further studies are still needed to determine if these recommendations can improve patient safety and outcomes in Palestinian hospitals.

Subcutaneous Insulin Dosing Calculators for Inpatient Glucose Control

PURPOSE OF REVIEW

The goal of this review is to summarize information about insulin dosing software and calculators used as computerized decision support systems or electronic glucose management systems (eGMS). These are used for hospitalized, insulin-treated patients with diabetes. We describe the advantages and disadvantages and the rationale for their use.

RECENT FINDINGS

We compared commercially available insulin dosing software, namely, Glucommander™, EndoTool®, GlucoStabilizer®, and GlucoTab®, in addition to computerized order entry systems that are available in electronic health records. The common feature among these eGMS is their ability to limit occurrences of hypoglycemia while achieving and maintaining patients at target blood glucose level. More research needs to be done examining the efficacy of eGMS in disease-specific states and their benefits and utility in preventing adverse outcomes. Their long-term benefits to health care systems are beginning to emerge in cost-saving benefits and prevention of readmissions.

Differential impact of cognitive computing augmented by real world evidence on novice and expert oncologists

INTRODUCTION

Cognitive computing point-of-care decision support tools which ingest patient attributes from electronic health records and display treatment options based on expert training and medical literature, supplemented by real world evidence (RWE), might prove useful to expert and novice oncologists. The concordance of augmented intelligence systems with best medical practices and potential influences on physician behavior remain unknown.

METHODS

Electronic health records from 88 breast cancer patients evaluated at a USA tertiary care center were presented to subspecialist experts and oncologists focusing on other disease states with and without reviewing the IBM Watson for Oncology with Cota RWE platform.

RESULTS

The cognitive computing "recommended" option was concordant with selection by breast cancer experts in 78.5% and "for consideration" option was selected in 9.4%, yielding agreements in 87.9%. Fifty-nine percent of non-concordant responses were generated from 8% of cases. In the Cota observational database 69.3% of matched controls were treated with "recommended," 11.4% "for consideration", and 19.3% "not recommended." Without guidance from Watson for Oncology (WfO)/Cota RWE, novice oncologists chose 75.5% recommended/for consideration treatments which improved to 95.3% with WfO/Cota RWE. The novices were more likely than experts to choose a non-recommended option (P < .01) without WfO/Cota RWE and changed decisions in 39% cases.

CONCLUSIONS

Watson for Oncology with Cota RWE options were largely concordant with disease expert judged best oncology practices, and was able to improve treatment decisions among breast cancer novices. The observation that nearly a fifth of patients with similar disease characteristics received non-recommended options in a real world database highlights a need for decision support.

Developing a framework for evidence-based grading and assessment of predictive tools for clinical decision support

BACKGROUND

Clinical predictive tools quantify contributions of relevant patient characteristics to derive likelihood of diseases or predict clinical outcomes. When selecting predictive tools for implementation at clinical practice or for recommendation in clinical guidelines, clinicians are challenged with an overwhelming and ever-growing number of tools, most of which have never been implemented or assessed for comparative effectiveness. To overcome this challenge, we have developed a conceptual framework to Grade and Assess Predictive tools (GRASP) that can provide clinicians with a standardised, evidence-based system to support their search for and selection of efficient tools.

METHODS

A focused review of the literature was conducted to extract criteria along which tools should be evaluated. An initial framework was designed and applied to assess and grade five tools: LACE Index, Centor Score, Well's Criteria, Modified Early Warning Score, and Ottawa knee rule. After peer review, by six expert clinicians and healthcare researchers, the framework and the grading of the tools were updated.

RESULTS

GRASP framework grades predictive tools based on published evidence across three dimensions: 1) Phase of evaluation; 2) Level of evidence; and 3) Direction of evidence. The final grade of a tool is based on the highest phase of evaluation, supported by the highest level of positive evidence, or mixed evidence that supports a positive conclusion. Ottawa knee rule had the highest grade since it has demonstrated positive post-implementation impact on healthcare. LACE Index had the lowest grade, having demonstrated only pre-implementation positive predictive performance.

CONCLUSION

GRASP framework builds on widely accepted concepts to provide standardised assessment and evidence-based grading of predictive tools. Unlike other methods, GRASP is based on the critical appraisal of published evidence reporting the tools' predictive performance before implementation, potential effect and usability during implementation, and their post-implementation impact. Implementing the GRASP framework as an online platform can enable clinicians and guideline developers to access standardised and structured reported evidence of existing predictive tools. However, keeping GRASP reports up-to-date would require updating tools' assessments and grades when new evidence becomes available, which can only be done efficiently by employing semi-automated methods for searching and processing the incoming information.

Analysis of dosing-button compliance

PURPOSE

A project was undertaken at an academic medical center to assess use of available dosing buttons within the computerized provider-order-entry (CPOE) system in order to identify opportunities for optimization of medication builds.

METHODS

A retrospective observational study was conducted to identify medication records within a CPOE system meeting prespecified inclusion and exclusion criteria. A report capturing all inpatient adult medication orders associated with the identified medication records over a 6-month period was generated. The primary endpoint was percent dosing-button compliance, calculated as the number of orders with doses consistent with existing dosing-button options divided by the total number of orders during the study period. Secondary study objectives included a comparison of high- and low-performing medication record samples and identification of potential reasons for lack of dosing-button use.

RESULTS

A total of 2,506 CPOE medication records associated with a total of 694,877 medication orders entered during the study period were analyzed. Median percent dosing-button compliance was 99.92% (interquartile range, 83.33-100%). High-performing records (n = 1243) were more likely to be associated with anti-infective medications (p = 0.041) and medications not on formulary at the study institution (p < 0.001). Medications in the sample of poor-performing CPOE records (n = 614) were more likely to be agents delivered via the i.v. route (p < 0.001). There were 45 records for which poor dosing-button compliance was attributed to lack of a clinically reasonable dosing option.

CONCLUSION

A high level of dosing-button compliance was demonstrated despite the lack of routine revalidation of dosing buttons after initial medication builds. Some opportunity for optimization was identified during the project, which established a quality assurance method to facilitate future auditing of medication builds.

Clinical decision support for therapeutic decision-making in cancer: A systematic review

Cancer management, including supportive care, is complex and requires availability and synthesis of published and patient-specific data to make appropriate therapeutic decisions. Clinical decision support (CDS) may be an effective implementation strategy to support complex decision making although it is unclear whether it improves process outcomes, patient outcomes or both in cancer settings. We therefore conducted a systematic review to identify CDS that have been used to support therapeutic decision making in clinical cancer settings. Outcomes of interest included the effect of CDS on the process, such as clinician's decision making and effect on patient outcomes. Ten studies met inclusion criteria, with variability in the study design, setting, and intervention. Of the nine studies that measured process outcomes, five demonstrated significant improvement; and of the six that measured patient outcomes, four demonstrated significant improvement. All included studies utilized CDS that were informed by clinical practice guidelines. In conclusion, CDS to guide cancer therapeutic decision making is an understudied but promising area. Further research is needed.

Effect of Electronic Prescribing Strategies on Medication Error and Harm in Hospital: a Systematic Review and Meta-analysis

BACKGROUND

Computerized physician order entry and clinical decision support systems are electronic prescribing strategies that are increasingly used to improve patient safety. Previous reviews show limited effect on patient outcomes. Our objective was to assess the impact of electronic prescribing strategies on medication errors and patient harm in hospitalized patients.

METHODS

MEDLINE, EMBASE, CENTRAL, and CINAHL were searched from January 2007 to January 2018. We included prospective studies that compared hospital-based electronic prescribing strategies with control, and reported on medication error or patient harm. Data were abstracted by two reviewers and pooled using random effects model. Study quality was assessed using the Effective Practice and Organisation of Care and evidence quality was assessed using Grading of Recommendations Assessment, Development, and Evaluation.

RESULTS

Thirty-eight studies were included; comprised of 11 randomized control trials and 27 non-randomized interventional studies. Electronic prescribing strategies reduced medication errors (RR 0.24 (95% CI 0.13, 0.46), I² 98%, n = 11) and dosing errors (RR 0.17 (95% CI 0.08, 0.38), I² 96%, n = 9), with both risk ratios significantly affected by advancing year of publication. There was a significant effect of electronic prescribing strategies on adverse drug events (ADEs) (RR 0.52 (95% CI 0.40, 0.68), I² 0%, n = 2), but not on preventable ADEs (RR 0.55 (95% CI 0.30, 1.01), I² 78%, n = 3), hypoglycemia (RR 1.03 (95% CI 0.62-1.70), I² 28%, n = 7), length of stay (MD - 0.18 (95% - 1.42, 1.05), I² 94%, n = 7), or mortality (RR 0.97 (95% CI 0.79, 1.19), I² 74%, n = 9). The quality of evidence was rated very low.

DISCUSSION

Electronic prescribing strategies decrease medication errors and adverse drug events, but had no effect on other patient outcomes. Conservative interpretations of these findings are supported by significant heterogeneity and the preponderance of low-quality studies.

How to Prevent or Reduce Prescribing Errors: An Evidence Brief for Policy

- Preventing prescribing errors is critical to improving patient safety.

- We developed an evidence brief for policy to identify effective interventions to avoid or reduce prescribing errors.

- Four options were raised: promoting educational actions on prudent prescribing directed to prescribers; incorporating computerized alert systems into clinical practice; implementing the use of tools for guiding medication prescribing; and, encouraging patient care by a multidisciplinary team, with the participation of a pharmacist.

- These options can be incorporated into health systems either alone or together, and for that, it is necessary that the context be considered.

- Aiming to inform decision makers, we included considerations on the implementation of these options regarding upper-middle income countries, like the Brazilian, and we also present considerations regarding equity.

Computerized Clinical Decision Support Systems and Antibiotic Prescribing: A Systematic Review and Meta-analysis

PURPOSE

The aim of this study was to perform a systematic review and meta-analysis of studies performed in primary care centers and hospital facilities that evaluated the effectiveness of computerized clinical decision support systems (CDSSs) in decision making on the prescription of any given antibiotic.

METHODS

We conducted a search of the MEDLINE and EMBASE databases. A meta-analysis was then conducted of all variables with results reported in >2 studies.

FINDINGS

A total of 42 of the 46 studies included in the review identified a statistically significant advantage for CDSSs in ≥1 study variables. The effect of CDSSs on the percentage accuracy of the antibiotic spectrum prescribed empirically with respect to the microbial agent's susceptibility, which is one of the most frequently studied outcome variables, was examined in 7 studies, all undertaken in hospital settings. In all these studies but one, CDSSs resulted in a statistically significant increase in percentage accuracy. The other study variables present in >2 studies had more inconsistent results. Although the results of the meta-analysis of the variables percentage accuracy, antibiotic prescription rate in hospital, percentage adherence to antibiotic prescription guidelines in primary care or hospital, and percentage of inappropriate prescriptions for antibiotics in primary care were statistically significantly favorable to CDSSs; in the case of hospital length of stay and mortality, they were favorable although not statistically significantly.

IMPLICATIONS

CDSSs appear to be useful for variables such as the percentage of appropriate empirical treatment in the hospital setting or to induce changes in antibiotics prescription rate. Even so, more better quality studies are required to draw clearer conclusions in respect of morbidity and mortality outcome variables and other settings.

Development and implementation of "Check of Medication Appropriateness" (CMA): advanced pharmacotherapy-related clinical rules to support medication surveillance

Background

To improve medication surveillance and provide pharmacotherapeutic support in University Hospitals Leuven, a back-office clinical service, called “Check of Medication Appropriateness” (CMA), was developed, consisting of clinical rule based screening for medication inappropriateness. The aim of this study is twofold: 1) describing the development of CMA and 2) evaluating the preliminary results, more specifically the number of clinical rule alerts, number of actions on the alerts and acceptance rate by physicians.

Methods

CMA focuses on patients at risk for potentially inappropriate medication and involves the daily checking by a pharmacist of high-risk prescriptions generated by advanced clinical rules integrating patient specific characteristics with details on medication. Pharmacists’ actions are performed by adding an electronic note in the patients’ medical record or by contacting the physician by phone. A retrospective observational study was performed to evaluate the primary outcomes during an 18-month study period.

Results

39,481 clinical rule alerts were checked by pharmacists for which 2568 (7%) electronic notes were sent and 637 (1.6%) phone calls were performed. 37,782 (96%) alerts were checked within four pharmacotherapeutic categories: drug use in renal insufficiency (25%), QTc interval prolonging drugs (11%), drugs with a restricted indication or dosing (14%) and overruled very severe drug-drug interactions (50%). The emergency department was a frequently involved ward and anticoagulants are the drug class for which actions are most frequently carried out. From the 458 actions performed for the four abovementioned categories, 69% were accepted by physicians.

Conclusions

These results demonstrate the added value of CMA to support medication surveillance in synergy with already integrated basic clinical decision support and bedside clinical pharmacy. Otherwise, the study also highlighted a number of limitations, allowing improvement of the service.

Electronic supplementary material

The online version of this article (10.1186/s12911-019-0748-5) contains supplementary material, which is available to authorized users.

Improving medication-related clinical decision support

PURPOSE

Current uses of medication-related clinical decision support (CDS) and recommendations for improving these systems are reviewed.

SUMMARY

Using a systematic approach, articles published from 2007 through 2014 were identified in MEDLINE and EMBASE using MeSH terms and keywords relating to the 5 basic medication-related CDS functionalities. A total of 156 full-text articles and 28 conference abstracts were reviewed across each of the 5 areas: drug-drug interaction (DDI) checks (n = 78), drug allergy checks (n = 20), drug dose support (n = 55), drug duplication checks (n = 11), and drug formulary support (n = 20). The success of medication-related CDS depends on users finding the alerts valuable and acting on the information received. Improving alert specificity and sensitivity is important for all domains. Tiering is important for improving the acceptance of DDI alerts. The ability to perform appropriate cross-sensitivity checks is key to producing appropriate drug allergy checks. Drug dosage alerts should be individualized and deliver practical recommendations. How the system is configured to identify certain drug duplications is important to prevent possible patient toxicity. Accurate knowledge databases are needed to produce relevant drug formulary alerts and encourage formulary adherence. Medication-related CDS is still relatively immature in some organizations and has substantial room for improvement. For example, decision support should consider more patient-specific factors, human factors principles should always be considered, and alert specificity must be improved in order to reduce alert fatigue.

CONCLUSION

Standardization, integration of patient-specific parameters, and consideration of human factors design principles are central to realizing the potential benefits of medication-related CDS.

Behavioral Economics Interventions in Clinical Decision Support Systems

Background:  Clinical decision support (CDS) systems can improve safety and facilitate evidence-based practice. However, clinical decisions are often affected by the cognitive biases and heuristics of clinicians, which is increasing the interest in behavioral and cognitive science approaches in the medical field.

Objectives:  This review aimed to identify decision biases that lead clinicians to exhibit irrational behaviors or responses, and to show how behavioral economics can be applied to interventions in order to promote and reveal the contributions of CDS to improving health care quality.

Methods:  We performed a systematic review of studies published in 2016 and 2017 and applied a snowball citationsearch method to identify topical publications related to studies forming part of the BEARI (Application of Behavioral Economics to Improve the Treatment of Acute Respiratory Infections) multisite, cluster-randomized controlled trial performed in the United States.

Results:  We found that 10 behavioral economics concepts with nine cognitive biases were addressed and investigated for clinician decision-making, and that the following five concepts, which were actively explored, had an impact in CDS applications: social norms, framing effect, status-quo bias, heuristics, and overconfidence bias.

Conclusions:  Our review revealed that the use of behavioral economics techniques is increasing in areas such as antibiotics prescribing and preventive care, and that additional tests of the concepts and heuristics described would be useful in other areas of CDS. An improved understanding of the benefits and limitations of behavioral economics techniques is also still needed. Future studies should focus on successful design strategies and how to combine them with CDS functions for motivating clinicians.

Best practices for preventing malfunctions in rule-based clinical decision support alerts and reminders: Results of a Delphi study

OBJECTIVE

Developing effective and reliable rule-based clinical decision support (CDS) alerts and reminders is challenging. Using a previously developed taxonomy for alert malfunctions, we identified best practices for developing, testing, implementing, and maintaining alerts and avoiding malfunctions.

MATERIALS AND METHODS

We identified 72 initial practices from the literature, interviews with subject matter experts, and prior research. To refine, enrich, and prioritize the list of practices, we used the Delphi method with two rounds of consensus-building and refinement. We used a larger than normal panel of experts to include a wide representation of CDS subject matter experts from various disciplines.

RESULTS

28 experts completed Round 1 and 25 completed Round 2. Round 1 narrowed the list to 47 best practices in 7 categories: knowledge management, designing and specifying, building, testing, deployment, monitoring and feedback, and people and governance. Round 2 developed consensus on the importance and feasibility of each best practice.

DISCUSSION

The Delphi panel identified a range of best practices that may help to improve implementation of rule-based CDS and avert malfunctions. Due to limitations on resources and personnel, not everyone can implement all best practices. The most robust processes require investing in a data warehouse. Experts also pointed to the issue of shared responsibility between the healthcare organization and the electronic health record vendor.

CONCLUSION

These 47 best practices represent an ideal situation. The research identifies the balance between importance and difficulty, highlights the challenges faced by organizations seeking to implement CDS, and describes several opportunities for future research to reduce alert malfunctions.

The GUIDES checklist: development of a tool to improve the successful use of guideline-based computerised clinical decision support

Background

Computerised decision support (CDS) based on trustworthy clinical guidelines is a key component of a learning healthcare system. Research shows that the effectiveness of CDS is mixed.

Multifaceted context, system, recommendation and implementation factors may potentially affect the success of CDS interventions. This paper describes the development of a checklist that is intended to support professionals to implement CDS successfully.

Methods

We developed the checklist through an iterative process that involved a systematic review of evidence and frameworks, a synthesis of the success factors identified in the review, feedback from an international expert panel that evaluated the checklist in relation to a list of desirable framework attributes, consultations with patients and healthcare consumers and pilot testing of the checklist.

Results

We screened 5347 papers and selected 71 papers with relevant information on success factors for guideline-based CDS. From the selected papers, we developed a 16-factor checklist that is divided in four domains, i.e. the CDS context, content, system and implementation domains. The panel of experts evaluated the checklist positively as an instrument that could support people implementing guideline-based CDS across a wide range of settings globally. Patients and healthcare consumers identified guideline-based CDS as an important quality improvement intervention and perceived the GUIDES checklist as a suitable and useful strategy.

Conclusions

The GUIDES checklist can support professionals in considering the factors that affect the success of CDS interventions. It may facilitate a deeper and more accurate understanding of the factors shaping CDS effectiveness. Relying on a structured approach may prevent that important factors are missed.

Electronic supplementary material

The online version of this article (10.1186/s13012-018-0772-3) contains supplementary material, which is available to authorized users.

Clinical decision support alert malfunctions: analysis and empirically derived taxonomy

Objective

To develop an empirically derived taxonomy of clinical decision support (CDS) alert malfunctions.

Materials and Methods

We identified CDS alert malfunctions using a mix of qualitative and quantitative methods: (1) site visits with interviews of chief medical informatics officers, CDS developers, clinical leaders, and CDS end users; (2) surveys of chief medical informatics officers; (3) analysis of CDS firing rates; and (4) analysis of CDS overrides. We used a multi-round, manual, iterative card sort to develop a multi-axial, empirically derived taxonomy of CDS malfunctions.

Results

We analyzed 68 CDS alert malfunction cases from 14 sites across the United States with diverse electronic health record systems. Four primary axes emerged: the cause of the malfunction, its mode of discovery, when it began, and how it affected rule firing. Build errors, conceptualization errors, and the introduction of new concepts or terms were the most frequent causes. User reports were the predominant mode of discovery. Many malfunctions within our database caused rules to fire for patients for whom they should not have (false positives), but the reverse (false negatives) was also common.

Discussion

Across organizations and electronic health record systems, similar malfunction patterns recurred. Challenges included updates to code sets and values, software issues at the time of system upgrades, difficulties with migration of CDS content between computing environments, and the challenge of correctly conceptualizing and building CDS.

Conclusion

CDS alert malfunctions are frequent. The empirically derived taxonomy formalizes the common recurring issues that cause these malfunctions, helping CDS developers anticipate and prevent CDS malfunctions before they occur or detect and resolve them expediently.

The use of electronic alerts in primary care computer systems to identify the excessive prescription of short-acting beta2-agonists for people with asthma: a systematic review

Computers are increasingly used to improve prescribing decisions in the management of long-term conditions however the effects on asthma prescribing remain unclear. We aimed to synthesise the evidence for the use of computerised alerts that identify excessive prescribing of short-acting beta₂-agonists (SABAs) to improve asthma management for people with asthma. MEDLINE, CINAHL, Embase, Cochrane and Scopus databases (1990–2016) were searched for randomised controlled trials using electronic alerts to identify excessive prescribing of SABAs for people with asthma in primary care. Inclusion eligibility, quality appraisal (Cochrane risk of bias tool) and data extraction were performed by two independent reviewers. Findings were synthesised narratively. A total of 2035 articles were screened and four trials were eligible. Three studies had low risk of bias: one reported a positive effect on our primary outcome of interest, excessive SABA prescribing; another reported positive effects on the ratio of inhaled corticosteroid (ICS)-SABA prescribing, and asthma control; a third reported no effect on outcomes of interest. One study at high risk of bias reported a reduction in exacerbations and primary care consultations. There is some evidence that electronic alerts reduce excessive prescribing of SABAs, when delivered as part of a multicomponent intervention in an integrated health care system. However due to the variation in health care systems, intervention design and outcomes measured, further research is required to establish optimal design of alerting and intervening systems.

Identifying Which Urban Children With Asthma Benefit Most From Clinician Prompting: Subgroup Analyses From the Prompting Asthma Intervention in Rochester-Uniting Parents and Providers (PAIR-UP) Trial

OBJECTIVE

Clinician prompts increase the likelihood of guideline-recommended corrective actions (preventive medication prescription, dose change, and/or adherence promotion) for symptomatic children with poorly controlled or persistent asthma in the primary care setting, but it is unclear if all children equally benefit. The objectives of this study were to identify whether asthma severity, visit type, and current preventive medication use were predictive of corrective actions during visits for children with symptomatic asthma, and determine whether these factors modified the effect of a prompting intervention.

METHODS

We conducted prespecified subgroup analyses of a cluster randomized controlled trial of physician prompting that promoted guideline-based asthma management for urban children with symptomatic asthma. We tested predictors of corrective actions with bivariate and multivariate multilevel logistic regressions, compared intervention effects across factor categories via stratified analyses, and characterized effect modification with interaction term analyses.

RESULTS

Prompting intervention exposure, moderate/severe disease, asthma-focused visits, and current preventive medication use were predictive of corrective actions. The prompting intervention significantly increased the rate of corrective actions for children across categories of disease severity, visit type, and preventive medication use. However, the intervention effect was significantly smaller for children already using a preventive medication (adjusted odds ratio [OR], 2.01; 95% confidence interval [CI], 1.19-3.38) compared with children without preventive medication use (adjusted OR, 6.25; 95% CI, 3.39-11.54).

CONCLUSIONS

Prompting increases the likelihood of corrective actions during clinic encounters; however, children already using preventive medication benefit less. It is critical for providers to recognize the need for corrective actions among these symptomatic children.

Present Situation and Prospect of Medical Knowledge Based Systems in German-speaking Countries

Background: After a decrease of interest in classical medical expert systems, the publication activity concerning the medical application of Artificial Intelligence and the interest in medical decision support have markedly increased. Nonetheless, no systematic exploratory study has yet been carried out, which directly considers the actual fields of applications, exemplary approaches, obstacles, challenges, and future prospect as seen by pioneering users and developers in a given region.

Objectives: This paper reports the results of an online survey designed to fill this gap with the “Knowledge Based Systems” working group of the German Society for Medical Informatics, Biometry and Epidemiology (GMDS) in 2010.

Methods: The survey was based on an online questionnaire (5 single and multiple choice questions, 8 Likert-scaled items, 7 free text questions) consented to by the working group. The answers were analyzed by descriptive statistics and a qualitative analysis (bottom-up coding). All academic institutions of Medical Informatics in the German-speaking countries and contributors reporting KBS-related projects at the relevant scientific conferences and in a journal specialized in the field were invited to participate.

Results: The survey reached a response rate of 33.4%. The results show a gap between the reported obstacles of medical KBS (mainly low acceptance and rare use in clinical practice) and their future prospect as stated by the participants. Problems previously discussed in the literature like low acceptance, integration, and sustainability of KBS projects were confirmed. The current situation was characterized by naming exemplary existing systems and specifying promising fields of application.

Conclusions: The field of KBS in medicine is more diversified and has evolved beyond expectations in the German-speaking countries.

A new clinical decision support tool for improving the adequacy of anticoagulant therapy and reducing the incidence of stroke in nonvalvular atrial fibrillation: A randomized clinical trial in primary care

INTRODUCTION

Atrial fibrillation (AF) is the most common cardiac arrhythmia and increases the risk of ischemic stroke 4 to 5-fold. The first choice of anticoagulant therapy (AT) is the vitamin K antagonist (VKA). Contraindication to VKA or poor control of the International Normalized Ratio leads to the administration of direct-acting oral anticoagulants. There is a trend toward inadequate AT in nonvalvular AF (NVAF) patients.

AIM

To evaluate the impact of the implementation of a decision support tool linked to the digital clinical history on the adequacy of AT, the incidence of complications, and the mortality in patients with NVAF in primary care centers (PCCs) of the Catalan Institute of Health (ICS).

METHODS AND ANALYSIS

Randomized clinical trial in 287 PCCs, formed by 2 groups (intervention and control).

POPULATION

patients controlled in PCCs, diagnosed with NVAF 1 year before the implementation of the decision support tool and with VKA treatment over a minimum of 1 year. A simple randomization method will be performed at a sector level. The decision support tool will be available for 1 year. The time in therapeutic range (TTR) will be available in the digital clinical history only to professionals of the intervention group. The information system for primary care research development database will be used for the data extraction. Statistical analysis will be done at 3 time points: before the implementation of the tool, at 1 year, and at 2 years after the beginning of the intervention. Multilevel (patient and professional levels) logistic regression models will be used to estimate the effect of the intervention.

ETHICS AND DISSEMINATION

This study protocol was approved by the Ethical Committee of Clinical Investigation of the Institut Universitari d'Investigació en Atenció Primària Jordi Gol (code P17/091). Articles will be published in scientific journals.

TRIAL REGISTRATION

Clinical-Trials.gov: NCT03367325.

Impact on process results of clinical decision support systems (CDSSs) applied to medication use: overview of systematic reviews

Objective

The purpose of this overview (systematic review of systematic reviews) is to evaluate the impact of clinical decision support systems (CDSS) applied to medication use in the care process.

Methods

A search for systematic reviews that address CDSS was performed on Medline following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Cochrane recommendations. Terms related to CDSS and systematic reviews were used in combination with Boolean operators and search field tags to build the electronic search strategy. There was no limitation of date or language for inclusion. We included revisions that investigated, as a main or secondary objective, changes in process outcomes. The Revised Assessment of Multiple Systematic Reviews (R-AMSTAR) score was used to evaluate the quality of the studies.

Results

The search retrieved 954 articles. Five articles were added through manual search, totaling an initial sample of 959 articles. After screening and reading in full, 44 systematic reviews met the inclusion criteria. In the medication-use processes where CDSS was used, the most common stages were prescribing (n=38 (86.36%) and administering (n=12 (27.27%)). Most of the systematic reviews demonstrated improvement in the health care process (30/44 - 68.2%). The main positive results were related to improvement of the quality of prescription by the physicians (14/30 - 46.6%) and reduction of errors in prescribing (5/30 - 16.6%). However, the quality of the studies was poor, according to the score used.

Conclusion

CDSSs represent a promising technology to optimize the medication-use process, especially related to improvement in the quality of prescriptions and reduction of prescribing errors, although higher quality studies are needed to establish the predictors of success in these systems.

Comparison of Two Sources of Clinical Audit Data to Assess the Delivery of Diabetes Care in Aboriginal Communities

The objective of this study was to determine the concordance between data extracted from two Clinical Decision Support Systems regarding diabetes testing and monitoring at Aboriginal Community Controlled Health Services in Australia. De-identified PenCAT and Communicare Systems data were extracted from the services allocated to the intervention arm of a diabetes care trial, and intra-class correlations for each extracted item were derived at a service level. Strong to very strong correlations between the two data sources were found regarding the total number of patients with diabetes per service (Intra-class correlation [ICC] = 0.99), as well as the number (ICC = 0.98–0.99) and proportion (ICC = 0.96) of patients with diabetes by gender. The correlation was moderate for the number and proportion of Type 2 diabetes patients per service in the group aged 18–34 years (ICC = 0.65 and 0.8–0.82 respectively). Strong to very strong correlations were found for numbers and proportions of patients being tested for diabetes, and for appropriate monitoring of patients known to have diabetes (ICC = 0.998–1.00). This indicated a generally high degree of concordance between whole-service data extracted by the two Clinical Decision Support Systems. Therefore, the less expensive or less complex option (depending on the individual circumstances of the service) may be appropriate for monitoring diabetes testing and care. However, the extraction of data about subgroups of patients may not be interchangeable.

Warfarin monitoring in nursing homes assessed by case histories. Do recommendations and electronic alerts affect judgements?

PURPOSE

Older adults treated with warfarin are prone to complications, and high-quality monitoring is essential. The aim of this case history based study was to assess the quality of warfarin monitoring in a routine situation, and in a situation with an antibiotic-warfarin interaction, before and after receiving an electronic alert.

MATERIALS AND METHODS

In April 2014, a national web-based survey with two case histories was distributed among Norwegian nursing home physicians and general practitioners working part-time in nursing homes. Case A represented a patient on stable warfarin treatment, but with a substantial INR increase within the therapeutic interval. Case B represented a more challenging patient with trimethoprim sulfamethoxazole (TMS) treatment due to pyelonephritis. In both cases, the physicians were asked to state the next warfarin dose and the INR recall interval. In case B, the physicians could change their suggestions after receiving an electronic alert on the TMS-warfarin interaction.

RESULTS

Three hundred and ninety eight physicians in 292 nursing homes responded. Suggested INR recall intervals and warfarin doses varied substantially in both cases. In case A, 61% gave acceptable answers according to published recommendations, while only 9% did so for case B. Regarding the TMS-warfarin interaction in case history B, the electronic alert increased the percentage of respondents correctly suggesting a dose reduction from 29% to 53%. Having an INR instrument in the nursing home was associated with shortened INR recall times.

CONCLUSIONS

Practical advice on handling of warfarin treatment and drug interactions is needed. Electronic alerts as presented in electronic medical records seem insufficient to change practice. Availability of INR instruments may be important regarding recall time.

The effectiveness of computerised decision support on antibiotic use in hospitals: A systematic review

Background

Inappropriate 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.

Objectives

To evaluate the evidence for CDS in improving quantitative and qualitative measures of antibiotic prescribing in inpatient hospital settings.

Methods

A systematic literature search was conducted of articles published from inception to 20^th 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 1^st 2015 to October 1^st 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.

Results

Eighty-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.

Conclusions

CDS has the potential to improve the adequacy of antibiotic coverage and marginally decrease mortality in hospital-related settings.

Computer-generated reminders delivered on paper to healthcare professionals: effects on professional practice and healthcare outcomes

BACKGROUND

Clinical practice does not always reflect best practice and evidence, partly because of unconscious acts of omission, information overload, or inaccessible information. Reminders may help clinicians overcome these problems by prompting them to recall information that they already know or would be expected to know and by providing information or guidance in a more accessible and relevant format, at a particularly appropriate time. This is an update of a previously published review.

OBJECTIVES

To evaluate the effects of reminders automatically generated through a computerized system (computer-generated) and delivered on paper to healthcare professionals on quality of care (outcomes related to healthcare professionals' practice) and patient outcomes (outcomes related to patients' health condition).

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, six other databases and two trials registers up to 21 September 2016 together with reference checking, citation searching and contact with study authors to identify additional studies.

SELECTION CRITERIA

We included individual- or cluster-randomized and non-randomized trials that evaluated the impact of computer-generated reminders delivered on paper to healthcare professionals, alone (single-component intervention) or in addition to one or more co-interventions (multi-component intervention), compared with usual care or the co-intervention(s) without the reminder component.

DATA COLLECTION AND ANALYSIS

Review authors working in pairs independently screened studies for eligibility and abstracted data. For each study, we extracted the primary outcome when it was defined or calculated the median effect size across all reported outcomes. We then calculated the median improvement and interquartile range (IQR) across included studies using the primary outcome or median outcome as representative outcome. We assessed the certainty of the evidence according to the GRADE approach.

MAIN RESULTS

We identified 35 studies (30 randomized trials and five non-randomized trials) and analyzed 34 studies (40 comparisons). Twenty-nine studies took place in the USA and six studies took place in Canada, France, Israel, and Kenya. All studies except two took place in outpatient care. Reminders were aimed at enhancing compliance with preventive guidelines (e.g. cancer screening tests, vaccination) in half the studies and at enhancing compliance with disease management guidelines for acute or chronic conditions (e.g. annual follow-ups, laboratory tests, medication adjustment, counseling) in the other half.Computer-generated reminders delivered on paper to healthcare professionals, alone or in addition to co-intervention(s), probably improves quality of care slightly compared with usual care or the co-intervention(s) without the reminder component (median improvement 6.8% (IQR: 3.8% to 17.5%); 34 studies (40 comparisons); moderate-certainty evidence).Computer-generated reminders delivered on paper to healthcare professionals alone (single-component intervention) probably improves quality of care compared with usual care (median improvement 11.0% (IQR 5.4% to 20.0%); 27 studies (27 comparisons); moderate-certainty evidence). Adding computer-generated reminders delivered on paper to healthcare professionals to one or more co-interventions (multi-component intervention) probably improves quality of care slightly compared with the co-intervention(s) without the reminder component (median improvement 4.0% (IQR 3.0% to 6.0%); 11 studies (13 comparisons); moderate-certainty evidence).We are uncertain whether reminders, alone or in addition to co-intervention(s), improve patient outcomes as the certainty of the evidence is very low (n = 6 studies (seven comparisons)). None of the included studies reported outcomes related to harms or adverse effects of the intervention.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that computer-generated reminders delivered on paper to healthcare professionals probably slightly improves quality of care, in terms of compliance with preventive guidelines and compliance with disease management guidelines. It is uncertain whether reminders improve patient outcomes because the certainty of the evidence is very low. The heterogeneity of the reminder interventions included in this review also suggests that reminders can probably improve quality of care in various settings under various conditions.

GPs' perspectives on prescribing for older people in primary care: a qualitative study

AIMS

The aim of this study was firstly to reveal the determinants of GP prescribing behaviour for older adults in primary care and secondly to elicit GPs' views on the potential role for broad intervention strategies involving pharmacists and/or information technology systems in general practice.

METHODS

Semi-structured qualitative interviews were carried out with a purposive sample of GPs. Three multidisciplinary researchers independently coded the interview data using a framework approach. Emerging themes were mapped to the Theoretical Domains Framework (TDF), a tool used to apply behaviour change theories.

RESULTS

Sixteen GPs participated in the study. The following domains in the TDF were identified as being important determinants of GP prescribing behaviour: 'Knowledge', 'Skills', 'Reinforcement', 'Memory Attention and Decision Process', 'Environmental Context and Resources', 'Social Influences', 'Social/Professional Role and Identity'. Participants reported that the challenges associated with prescribing for an increasingly older population will require them to become more knowledgeable in pharmacology and drug interactions and they called for extra training in these topics. GPs viewed strategies such as academic detailing sessions delivered by pharmacists or information technology systems as having a positive role to play in optimizing prescribing.

CONCLUSION

This study highlights the complexities of behavioural determinants of prescribing for older people in primary care and the need for additional supports to optimize prescribing for this growing cohort of patients. Interventions that incorporate, but are not limited to interprofessional collaboration with pharmacists and information technology systems, were identified by GPs as being potentially useful for improving prescribing behaviour, and therefore require further exploration.