A Machine Learning Application to Classify Patients at Differing Levels of Risk of Opioid Use Disorder: Clinician-Based Validation Study.

Background: Despite restrictive opioid management guidelines, opioid use disorder (OUD) remains a major public health concern. Machine learning (ML) offers a promising avenue for identifying and alerting clinicians about OUD, thus supporting better clinical decision-making regarding treatment. Objective: This study aimed to assess the clinical validity of an ML application designed to identify and alert clinicians of different levels of OUD risk by comparing it to a structured review of medical records by clinicians. Methods: The ML application generated OUD risk alerts on outpatient data for 649,504 patients from 2 medical centers between 2010 and 2013. A random sample of 60 patients was selected from 3 OUD risk level categories (n=180). An OUD risk classification scheme and standardized data extraction tool were developed to evaluate the validity of the alerts. Clinicians independently conducted a systematic and structured review of medical records and reached a consensus on a patient's OUD risk level, which was then compared to the ML application's risk assignments. Results: A total of 78,587 patients without cancer with at least 1 opioid prescription were identified as follows: not high risk (n=50,405, 64.1%), high risk (n=16,636, 21.2%), and suspected OUD or OUD (n=11,546, 14.7%). The sample of 180 patients was representative of the total population in terms of age, sex, and race. The interrater reliability between the ML application and clinicians had a weighted kappa coefficient of 0.62 (95% CI 0.53-0.71), indicating good agreement. Combining the high risk and suspected OUD or OUD categories and using the review of medical records as a gold standard, the ML application had a corrected sensitivity of 56.6% (95% CI 48.7%-64.5%) and a corrected specificity of 94.2% (95% CI 90.3%-98.1%). The positive and negative predictive values were 93.3% (95% CI 88.2%-96.3%) and 60.0% (95% CI 50.4%-68.9%), respectively. Key themes for disagreements between the ML application and clinician reviews were identified. Conclusions: A systematic comparison was conducted between an ML application and clinicians for identifying OUD risk. The ML application generated clinically valid and useful alerts about patients' different OUD risk levels. ML applications hold promise for identifying patients at differing levels of OUD risk and will likely complement traditional rule-based approaches to generating alerts about opioid safety issues.

The cost-effectiveness of metformin in the US diabetes prevention program trial: Simple interpretations need not apply.

Based on previously published US Diabetes Prevention Program (DPP) cost-effectiveness analyses (CEAs) metformin continues to be promoted as "cost-effective." We review the DPP within-trial CEA to assess this claim. Treatment alternatives included placebo (plus standard lifestyle advice), branded metformin and individual lifestyle modification. We added generic metformin as an alternative. Original published CEA data were taken as given and re-analyzed according to accepted principles for calculating incremental cost-effectiveness ratios (ICERs) in the economic evaluation field. With more than two treatments as in the DPP, these require attention to the rankings of interventions according to cost or effect prior to stipulating appropriate ICERs to calculate. With proper ICERs neither branded nor generic metformin was cost-effective, regardless of the value assumed for the willingness to pay for the quality-adjusted life year outcome assessed. Metformin alternatives were technically inefficient compared to placebo or the lifestyle modification alternative. Net loss calculations indicated substantial costs/health losses to using metformin instead of the optimal lifestyle alternative in response to metformin having been inaccurately labelled "cost-effective" in the original CEA. That CEA and subsequent analyses and citations of such analyses continue to claim that both metformin and lifestyle modification are cost-effective in diabetes prevention based on DPP data. Using metformin implies substantial costs and health losses compared to the cost-effective lifestyle modification. It may be that metformin has a role in cost-effective diabetes prevention, but this has yet to be shown based on DPP data.

Assessing the Assessment-Developing and Deploying a Novel Tool for Evaluating Clinical Notes' Diagnostic Assessment Quality.

BACKGROUND: Ambulatory diagnostic errors are increasingly being recognized as an important quality and safety issue, and while measures of diagnostic quality have been sought, tools to evaluate diagnostic assessments in the medical record are lacking. OBJECTIVE: To develop and test a tool to measure diagnostic assessment note quality in primary care urgent encounters and identify common elements and areas for improvement in diagnostic assessment. DESIGN: Retrospective chart review of urgent care encounters at an urban academic setting. PARTICIPANTS: Primary care physicians. MAIN MEASURES: The Assessing the Assessment (ATA) instrument was evaluated for inter-rater reliability, internal consistency, and findings from its application to EHR notes. KEY RESULTS: ATA had reasonable performance characteristics (kappa 0.63, overall Cronbach's alpha 0.76). Variability in diagnostic assessment was seen in several domains. Two components of situational awareness tended to be well-documented ("Don't miss diagnoses" present in 84% of charts, red flag symptoms in 87%), while Psychosocial context was present only 18% of the time. CONCLUSIONS: The ATA tool is a promising framework for assessing and identifying areas for improvement in diagnostic assessments documented in clinical encounters.

Important Factors in Remote Experiential Education.

Onsite and in-person experiential education has been well established to prepare practice-ready healthcare professionals, such as pharmacists. From COVID-19, the integration of remote educational delivery has occurred. As healthcare disciplines adjust to new experiential styles and innovate traditional methods, this paper highlights key areas for remote experiential education that can influence student experiences. Factors that are of importance to continuous quality improvement are described. A survey, utilizing the cloud-based software platform Qualtrics® headquartered in the United States, was developed to evaluate whether remote rotation delivery was comparable to traditional onsite experiential education, to assist with quality improvement for virtual experiential education, and to ensure the redesigned educational model meets accreditation standards for two schools of pharmacy. Numerous factors including work, time zone, Office of Experiential Education and preceptor responsiveness, and technology, were examined. Chi-Square test, t-test for proportions and odds ratios were utilized to evaluate results. Students with technology concerns throughout a remote rotation had a more than two-fold increase in identifying the virtual experience as worse than most/all other in-person rotations (p = 0.01). Preceptor responsiveness to questions and concerns significantly impact student perceptions of educational quality (p < 0.05). The majority of students perceived remote experiential education is equal to onsite experiences. Since continuous quality improvement is required by pharmacy accreditors and many other healthcare programs offering clinical opportunities, identifying factors is of importance to make future interventions in the remote experiential education delivery. This type of experiential learning became essential with COVID-19 impacting onsite clinical placements, and information can be used across health science disciplines at large.

Comparison of Amitriptyline and US Food and Drug Administration-Approved Treatments for Fibromyalgia: A Systematic Review and Network Meta-analysis.

Importance: Amitriptyline is an established medication used off-label for the treatment of fibromyalgia, but pregabalin, duloxetine, and milnacipran are the only pharmacological agents approved by the US Food and Drug Administration (FDA) to treat fibromyalgia. Objective: To investigate the comparative effectiveness and acceptability associated with pharmacological treatment options for fibromyalgia. Data Sources: Searches of PubMed/MEDLINE, Cochrane Library, Embase, and Clinicaltrials.gov were conducted on November 20, 2018, and updated on July 29, 2020. Study Selection: Randomized clinical trials (RCTs) comparing amitriptyline or any FDA-approved doses of investigated drugs. Data Extraction and Synthesis: This study follows the Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guideline. Four independent reviewers extracted data using a standardized data extraction sheet and assessed quality of RCTs. A random-effects bayesian network meta-analysis (NMA) was conducted. Data were analyzed from August 2020 to January 2021. Main Outcomes and Measures: Comparative effectiveness and acceptability (defined as discontinuation of treatment owing to adverse drug reactions) associated with amitriptyline (off-label), pregabalin, duloxetine, and milnacipran (on-label) in reducing fibromyalgia symptoms. The following doses were compared: 60-mg and 120-mg duloxetine; 150-mg, 300-mg, 450-mg, and 600-mg pregabalin; 100-mg and 200-mg milnacipran; and amitriptyline. Effect sizes are reported as standardized mean differences (SMDs) for continuous outcomes and odds ratios (ORs) for dichotomous outcomes with 95% credible intervals (95% CrIs). Findings were considered statistically significant when the 95% CrI did not include the null value (0 for SMD and 1 for OR). Relative treatment ranking using the surface under the cumulative ranking curve (SUCRA) was also evaluated. Results: A total of 36 studies (11 930 patients) were included. The mean (SD) age of patients was 48.4 (10.4) years, and 11 261 patients (94.4%) were women. Compared with placebo, amitriptyline was associated with reduced sleep disturbances (SMD, -0.97; 95% CrI, -1.10 to -0.83), fatigue (SMD, -0.64; 95% CrI, -0.75 to -0.53), and improved quality of life (SMD, -0.80; 95% CrI, -0.94 to -0.65). Duloxetine 120 mg was associated with the highest improvement in pain (SMD, -0.33; 95% CrI, -0.36 to -0.30) and depression (SMD, -0.25; 95% CrI, -0.32 to -0.17) vs placebo. All treatments were associated with inferior acceptability (higher dropout rate) than placebo, except amitriptyline (OR, 0.78; 95% CrI, 0.31 to 1.66). According to the SUCRA-based relative ranking of treatments, duloxetine 120 mg was associated with higher efficacy for treating pain and depression, while amitriptyline was associated with higher efficacy for improving sleep, fatigue, and overall quality of life. Conclusions and Relevance: These findings suggest that clinicians should consider how treatments could be tailored to individual symptoms, weighing the benefits and acceptability, when prescribing medications to patients with fibromyalgia.

Comparative Value of Cholinesterase Inhibitors and Memantine in Persons with Moderate-to-Severe Alzheimer's Disease in the United States: A Cost-Effectiveness Analysis.

BACKGROUND: Pharmacological treatment of Alzheimer's disease (AD) involves symptomatic improvement of cognition using cholinesterase inhibitors (ChEIs) and memantine. The cost-effectiveness of these medications will guide decision-makers in making judicious use of scarce healthcare resources, particularly during the advanced disease stages. OBJECTIVE: To evaluate the cost-effectiveness of ChEIs, memantine, and ChEI-memantine combinations in persons with moderate-to-severe AD from the US healthcare perspective. METHODS: This pharmacoeconomic evaluation study used a state-transition Markov cohort model to simulate the costs and effectiveness of ChEI-memantine combinations compared with monotherapies of ChEI (donepezil, galantamine and rivastigmine) and memantine in persons with moderate-to-severe AD over a lifetime horizon with a 1-year cycle length. We estimated expected quality-adjusted life-years (QALYs), costs (in 2020 $US), net monetary benefits, and incremental cost-effectiveness ratios (ICERs). We discounted future costs and QALYs at the rate of 3%. RESULTS: In this study, donepezil monotherapy, galantamine-memantine combination, and rivastigmine transdermal patch formed the cost-effectiveness frontier. Findings suggests that rivastigmine transdermal patch is the optimal treatment strategy at a willingness-to-pay (WTP) threshold of $150,000/QALY (ICER = $93,307/QALY [versus donepezil monotherapy]). Results across subgroups by age and sex also suggest that the rivastigmine transdermal patch is the optimal treatment strategy with the highest net benefit. CONCLUSION: From the US healthcare perspective, we found that, for persons with moderate-to-severe AD at a WTP threshold of $150,000/QALY, the rivastigmine transdermal patch is the most cost-effective pharmacological treatment option. Given that the transdermal patch is a preferred route of administration for persons with AD and their caregivers due to its convenience, our findings provide additional incentives for its use.

Personal Formularies of Primary Care Physicians Across 4 Health Care Systems.

Importance: More conservative prescribing has the potential to reduce adverse drug events and patient harm and cost; however, no method exists defining the extent to which individual clinicians prescribe conservatively. One potential domain is prescribing a more limited number of drugs. Personal formularies-defined as the number and mix of unique, newly initiated drugs prescribed by a physician-may enable comparisons among clinicians, practices, and institutions. Objectives: To develop a method of defining primary care physicians' personal formularies and examine how they differ among primary care physicians at 4 institutions; evaluate associations between personal formularies and patient, physician, and practice site characteristics; and empirically derive and examine the variability of the top 200 core drugs prescribed at the 4 sites. Design, Setting, and Participants: This retrospective cohort study was conducted at 4 US health care systems among 4655 internal and family medicine physicians and 4 930 707 patients who had at least 1 visit to these physicians between January 1, 2017, and December 31, 2018. Exposures: Personal formulary size was defined as the number of unique, newly initiated drugs. Main Outcomes and Measures: Personal formulary size and drugs used, physician and patient characteristics, core drugs, and analysis of selected drug classes. Results: The study population included 4655 primary care physicians (2274 women [48.9%]; mean [SD] age, 48.5 [4.4] years) and 4 930 707 patients (16.5% women; mean [SD] age, 51.9 [8.3] years). There were 41 378 903 outpatient prescriptions written, of which 9 496 766 (23.0%) were new starts. Institution median personal formulary size ranged from 150 (interquartile range, 82.0-212.0) to 296 (interquartile range, 230.0-347.0) drugs. In multivariable modeling, personal formulary size was significantly associated with panel size (total number of unique patients with face-to-face encounters during the study period; 1.2 medications per 100 patients), physician's total number of encounters (5.7 drugs per 10% increase), and physician's sex (-6.2 drugs per 100 patients for female physicians). There were 1527 unique, newly prescribed drugs across the 4 sites. Fewer than half the drugs (626 [41.0%]) were used at every site. Physicians' prescribing of drugs from a pooled core list varied from 0% to 100% of their prescriptions. Conclusions and Relevance: Personal formularies, measured at the level of individual physicians and institutions, reveal variability in size and mix of drugs. Similarly, defining a list of commonly prescribed core drugs in primary care revealed interphysician and interinstitutional differences. Personal formularies and core medication lists enable comparisons and may identify outliers and opportunities for safer and more appropriate prescribing.

Extended duration venous thromboembolism prophylaxis with betrixaban for patients re-admitted with venous thromboembolism.

Patients hospitalized for an acute medical illness remain at risk of developing venous thromboembolism (VTE) post-discharge. Betrixaban, an oral direct Factor Xa inhibitor, is approved for extended VTE thromboprophylaxis in acutely ill medical patients. The primary objective of this study was to evaluate patients re-admitted with VTE within 30 days of discharge to determine if they would have been eligible for extended duration VTE prophylaxis during the index admission. We used three different sets of eligibility criteria: the APEX study criteria, the Bevyxxa® (betrixaban) package insert, and Mass General Brigham HealthCare System's Center for Drug Policy Guidelines. A secondary aim was to describe the reasons for ineligibility. Within 30 days of the index hospital admission, 226 patients were re-admitted with new VTE between January 2017 and December 2018. Of these, 134 (59%) were excluded based on pre-defined exclusion criteria. Of the remaining 92, 22 patients (23.9%) were eligible based on the APEX study criteria, 26 patients (28.2%) based on Mass General Brigham HealthCare System's Center for Drug Policy Guidelines, and 92 patients (100%) based on the Bevyxxa® package insert. There were 22 patients (23.9%) who were eligible for VTE prophylaxis with betrixaban based on all three criteria. Appropriate betrixaban use may have prevented some of the VTE events and re-admissions that occurred within 30 days of initial hospital discharge.

Detection of adverse drug events in e-prescribing and administrative health data: a validation study.

BACKGROUND: Administrative health data are increasingly used to detect adverse drug events (ADEs). However, the few studies evaluating diagnostic codes for ADE detection demonstrated low sensitivity, likely due to narrow code sets, physician under-recognition of ADEs, and underreporting in administrative data. The objective of this study was to determine if combining an expanded ICD code set in administrative data with e-prescribing data improves ADE detection. METHODS: We conducted a prospective cohort study among patients newly prescribed antidepressant or antihypertensive medication in primary care and followed for 2 months. Gold standard ADEs were defined as patient-reported symptoms adjudicated as medication-related by a clinical expert. Potential ADEs in administrative data were defined as physician, ED, or hospital visits during follow-up for known adverse effects of the study medication, as identified by ICD codes. Potential ADEs in e-prescribing data were defined as study drug discontinuations or dose changes made during follow-up for safety or effectiveness reasons. RESULTS: Of 688 study participants, 445 (64.7%) were female and mean age was 64.2 (SD 13.9). The study drug for 386 (56.1%) patients was an antihypertensive, and for 302 (43.9%) an antidepressant. Using the gold standard definition, 114 (16.6%) patients experienced an ADE, with 40 (10.4%) among antihypertensive users and 74 (24.5%) among antidepressant users. The sensitivity of the expanded ICD code set was 7.0%, of e-prescribing data 9.7%, and of the two combined 14.0%. Specificities were high (86.0-95.0%). The sensitivity of the combined approach increased to 25.8% when analysis was restricted to the 27% of patients who indicated having reported symptoms to a physician. CONCLUSION: Combining an expanded diagnostic code set with e-prescribing data improves ADE detection. As few patients report symptoms to their physician, higher detection rates may be achieved by collecting patient-reported outcomes via emerging digital technologies such as patient portals and mHealth applications.

How often do prescribers include indications in drug orders? Analysis of 4 million outpatient prescriptions.

PURPOSE: To examine the extent to which outpatient clinicians currently document drug indications in prescription instructions. METHODS: Free-text sigs were extracted from all outpatient prescriptions generated by the computerized prescriber order entry system of a major academic institution during a 5-year period. Natural language processing was used to identify drug indications. The data set was analyzed to determine the rates at which prescribers included indications. It was stratified by provider specialty, drug class, and specific medications, to determine how often these indications were in prescriptions for as-needed (PRN) versus non-PRN medications. RESULTS: During the study period, 4,356,086 prescriptions were ordered. Indications were included in 322,961 orders (7.41%). From these orders, 249,262 indications (77.18%) were written for PRN orders. Although internal medicine prescribers generated the highest number of medication orders, they included indications in only 6.26% of their prescriptions, whereas orthopedic surgery providers had the highest rate of documenting indications (33.41%). Pain was the most common indication, accounting for 30.35% of all documented indications. The drug class with the highest number of sigs-containing indications was narcotic analgesics. Non-PRN chronic medication prescriptions rarely included the indication. CONCLUSION: Prescribers rarely included drug indications in electronic free-text prescription instructions, and, when they did, it was mostly for PRN uses such as pain.

Assessment of Reported Comparative Effectiveness and Safety of Atypical Antipsychotics in the Treatment of Behavioral and Psychological Symptoms of Dementia: A Network Meta-analysis.

Importance: Atypical antipsychotics offer modest effectiveness compared with placebo but with serious safety risks, including a boxed warning for the risk of death in the treatment of behavioral and psychological symptoms of dementia (BPSD). Their comparative effectiveness and safety are not fully known. Objective: To assess the relative benefits and safety of atypical antipsychotics in the treatment of BPSD shown in randomized clinical trials using network meta-analysis. Data Sources: PubMed/MEDLINE, Embase, PsychINFO, and Cochrane Library were searched from their inception until May 31, 2018. Key terms included dementia and atypical antipsychotics. Study Selection: Randomized clinical trials comparing any atypical antipsychotic with another atypical antipsychotic or with placebo were included in the analysis. Data Extraction and Synthesis: Two independent reviewers used a standardized data extraction and quality assessment form. Random-effects network meta-analyses were performed. Effect sizes were reported as standardized mean differences (SMDs) for continuous outcomes and odds ratios (ORs) for dichotomous outcomes with 95% CIs. In addition to ORs, the surface under the cumulative ranking curve (SUCRA) was ascertained, which represents the percentage of the effectiveness or safety for each treatment compared with a hypothetical treatment that would be ranked first without uncertainty. Main Outcomes and Measures: The primary effectiveness outcome assessed was the Neuropsychiatric Inventory (NPI); secondary effectiveness outcomes were the Brief Psychiatric Rating Scale (BPRS) and Cohen-Mansfield Agitation Inventory (CMAI). The primary safety outcomes were death and cerebrovascular adverse events (CVAEs). Secondary safety outcomes were extrapyramidal signs/symptoms; somnolence/sedation; falls, fracture, or injury; and urinary tract infection/incontinence. Results: Seventeen studies (5373 patients) were included. The mean (SD) age of all participants was 80.8 (3.1) years, and most were women (3748 [69.8%]). Compared with placebo, aripiprazole was associated with improvement in outcomes on the NPI (SMD, -0.17; 95% CI, -0.31 to -0.02), BPRS (SMD, -0.20; 95% CI, -0.35 to -0.05), and CMAI (SMD, -0.30; 95% CI, -0.55 to -0.05); quetiapine was associated with improvement in outcomes on the BPRS (SMD, -0.24; 95% CI, -0.46 to -0.01), and risperidone was associated with improvement in outcomes on the CMAI (SMD, -0.26; 95% CI, -0.37 to -0.15). Differences between atypical antipsychotics were not significant for effectiveness, death, or CVAE. Compared with placebo, risperidone (OR, 3.85; 95% CI, 1.55-9.55) and olanzapine (OR, 4.28; 95% CI, 1.26-14.56) were associated with increased risk of CVAEs. The SUCRA estimated relative ranking of treatments suggested that aripiprazole might be the most effective and safe atypical antipsychotic and that olanzapine provides the least benefit overall; however, these results should be interpreted with caution where point estimates (OR and SMD) show that there is no statistically significant difference. Conclusions and Relevance: This network meta-analysis supports the existence of a trade-off between the effectiveness and safety of atypical antipsychotics in the treatment of BPSD and confirms that a single most effective and safe treatment option does not exist. Clinicians should individualize the assessment of safety risks against expected benefits when prescribing these medications to patients with dementia.

Comparison of a Prototype for Indications-Based Prescribing With 2 Commercial Prescribing Systems.

Importance: The indication (reason for use) for a medication is rarely included on prescriptions despite repeated recommendations to do so. One barrier has been the way existing electronic prescribing systems have been designed. Objective: To evaluate, in comparison with the prescribing modules of 2 leading electronic health record prescribing systems, the efficiency, error rate, and satisfaction with a new computerized provider order entry prototype for the outpatient setting that allows clinicians to initiate prescribing using the indication. Design, Setting, and Participants: This quality improvement study used usability tests requiring internal medicine physicians, residents, and physician assistants to enter prescriptions electronically, including indication, for 8 clinical scenarios. The tool order assignments were randomized and prescribers were asked to use the prototype for 4 of the scenarios and their usual system for the other 4. Time on task, number of clicks, and order details were captured. User satisfaction was measured using posttask ratings and a validated system usability scale. The study participants practiced in 2 health systems' outpatient practices. Usability tests were conducted between April and October of 2017. Main Outcomes and Measures: Usability (efficiency, error rate, and satisfaction) of indications-based computerized provider order entry prototype vs the electronic prescribing interface of 2 electronic health record vendors. Results: Thirty-two participants (17 attending physicians, 13 residents, and 2 physician assistants) used the prototype to complete 256 usability test scenarios. The mean (SD) time on task was 1.78 (1.17) minutes. For the 20 participants who used vendor 1's system, it took a mean (SD) of 3.37 (1.90) minutes to complete a prescription, and for the 12 participants using vendor 2's system, it took a mean (SD) of 2.93 (1.52) minutes. Across all scenarios, when comparing number of clicks, for those participants using the prototype and vendor 1, there was a statistically significant difference from the mean (SD) number of clicks needed (18.39 [12.62] vs 46.50 [27.29]; difference, 28.11; 95% CI, 21.47-34.75; P < .001). For those using the prototype and vendor 2, there was also a statistically significant difference in number of clicks (20.10 [11.52] vs 38.25 [19.77]; difference, 18.14; 95% CI, 11.59-24.70; P < .001). A blinded review of the order details revealed medication errors (eg, drug-allergy interactions) in 38 of 128 prescribing sessions using a vendor system vs 7 of 128 with the prototype. Conclusions and Relevance: Reengineering prescribing to start with the drug indication allowed indications to be captured in an easy and useful way, which may be associated with saved time and effort, reduced medication errors, and increased clinician satisfaction.

Systematic assessment of decision analytic models for the cost-effectiveness of bariatric surgery for morbid obesity.

Bariatric surgery among patients with morbid obesity is very effective for providing long-term weight loss and remission of obesity-related co-morbidities. However, it is very expensive and its cost effectiveness is commonly argued. Long-term cost-effectiveness evaluations of bariatric surgery have often relied on decision models. A systematic review was performed on the methodologic approaches and their quality, evaluated the quality of reporting, and summarized findings and conclusions in published cost-effectiveness models of bariatric surgery for morbid obesity. A search from different databases with an end date of October 15, 2017 was completed. The initial search for title and abstract screening resulted in 741 articles. A total of 50 articles were included for full-text review and 23 economic evaluation studies were included in the systematic review. The reporting quality scores of most articles were rated as acceptable between 61% and 100%. Most studies (89%) were modeled for adult patients with age range between 25 and 75 years old. Sixty-one percent of studies defined their health states by the existence or absence of different obesity-related co-morbidities. Eleven percent of studies took the societal perspective. Most studies (61%) used a lifetime horizon. Thirty-nine percent of studies identified the extent of weight loss as the most sensitive and influential parameter. Seventeen (74%) did not report a formal model validation. Laparoscopic Roux-en-Y gastric bypass was reported as the most cost-effective strategy most often when it compared with no treatment or medical management. While most had acceptable quality of reporting levels, several gaps in the quality of reporting and quality of methods emerged, which led to recommendations for how to improve quality in future studies.

Incorporating medication indications into the prescribing process.

PURPOSE: The incorporation of medication indications into the prescribing process to improve patient safety is discussed. SUMMARY: Currently, most prescriptions lack a key piece of information needed for safe medication use: the patient-specific drug indication. Integrating indications could pave the way for safer prescribing in multiple ways, including avoiding look-alike/sound-alike errors, facilitating selection of drugs of choice, aiding in communication among the healthcare team, bolstering patient understanding and adherence, and organizing medication lists to facilitate medication reconciliation. Although strongly supported by pharmacists, multiple prior attempts to encourage prescribers to include the indication on prescriptions have not been successful. We convened 6 expert panels to consult high-level stakeholders on system design considerations and requirements necessary for building and implementing an indications-based computerized prescriber order-entry (CPOE) system. We summarize our findings from the 6 expert stakeholder panels, including rationale, literature findings, potential benefits, and challenges of incorporating indications into the prescribing process. Based on this stakeholder input, design requirements for a new CPOE interface and workflow have been identified. CONCLUSION: The emergence of universal electronic prescribing and content knowledge vendors has laid the groundwork for incorporating indications into the CPOE prescribing process. As medication prescribing moves in the direction of inclusion of the indication, it is imperative to design CPOE systems to efficiently and effectively incorporate indications into prescriber workflows and optimize ways this can best be accomplished.

Cost-Effectiveness Analysis of Bariatric Surgery for Morbid Obesity.

BACKGROUND: In the USA, three types of bariatric surgeries are widely performed, including laparoscopic sleeve gastrectomy (LSG), laparoscopic Roux-en-Y gastric bypass (LRYGB), and laparoscopic adjustable gastric banding (LAGB). However, few economic evaluations of bariatric surgery are published. There is also scarcity of studies focusing on the LSG alone. Therefore, this study is evaluating the cost-effectiveness of bariatric surgery using LRYGB, LAGB, and LSG as treatment for morbid obesity. METHODS: A microsimulation model was developed over a lifetime horizon to simulate weight change, health consequences, and costs of bariatric surgery for morbid obesity. US health care prospective was used. A model was propagated based on a report from the first report of the American College of Surgeons. Incremental cost-effectiveness ratios (ICERs) in terms of cost per quality-adjusted life-year (QALY) gained were used in the model. Model parameters were estimated from publicly available databases and published literature. RESULTS: LRYGB was cost-effective with higher QALYs (17.07) and cost ($138,632) than LSG (16.56 QALYs; $138,925), LAGB (16.10 QALYs; $135,923), and no surgery (15.17 QALYs; $128,284). Sensitivity analysis showed initial cost of surgery and weight regain assumption were very sensitive to the variation in overall model parameters. Across patient groups, LRYGB remained the optimal bariatric technique, except that with morbid obesity 1 (BMI 35-39.9 kg/m2) patients, LSG was the optimal choice. CONCLUSION: LRYGB is the optimal bariatric technique, being the most cost-effective compared to LSG, LAGB, and no surgery options for most subgroups. However, LSG was the most cost-effective choice when initial BMI ranged between 35 and 39.9 kg/m2.

The impact of bariatric surgery on pulmonary function: a meta-analysis.

Morbid obesity may affect several body systems and cause ill effects to the cardiovascular, hepatobiliary, endocrine, and mental health systems. However, the impact on the pulmonary system and pulmonary function has been debated in the literature. A systematic review and meta-analysis for studies that have evaluated the impact of bariatric surgery on pulmonary function were pooled for this analysis. PubMed, Cochrane, and Embase databases were evaluated through September 31, 2016. They were used as the primary search engine for studies evaluating the impact pre- and post-bariatric surgery on pulmonary function. Pooled effect estimates were calculated using random-effects model. Twenty-three studies with 1013 participants were included in the final meta-analysis. Only 8 studies had intervention and control groups with different time points, but 15 studies had matched groups with different time points. Overall, pulmonary function score was significantly improved after bariatric surgery, with a pooled standardized mean difference of .59 (95% confidence interval: .46-.73). Heterogeneity test was performed by using Cochran's Q test (I2 = 46%; P heterogeneity = .10). Subgroup analysis and univariate meta-regression based on study quality, age, presurgery body mass index, postsurgery body mass index, study design, female patients only, study continent, asthmatic patients in the study, and the type of bariatric surgery confirmed no statistically significant difference among these groups (P value>.05 for all). A multivariate meta-regression model, which adjusted simultaneously for these same covariates, did not change the results (P value > .05 overall). Assessment of publication bias was done visually and by Begg's rank correlation test and indicated the absence of publication bias (asymmetric shape was observed and P = .34). This meta-analysis shows that bariatric surgery significantly improved overall pulmonary functions score for morbid obesity.

Medication-related clinical decision support alert overrides in inpatients.

Objective: To define the types and numbers of inpatient clinical decision support alerts, measure the frequency with which they are overridden, and describe providers' reasons for overriding them and the appropriateness of those reasons. Materials and Methods: We conducted a cross-sectional study of medication-related clinical decision support alerts over a 3-year period at a 793-bed tertiary-care teaching institution. We measured the rate of alert overrides, the rate of overrides by alert type, the reasons cited for overrides, and the appropriateness of those reasons. Results: Overall, 73.3% of patient allergy, drug-drug interaction, and duplicate drug alerts were overridden, though the rate of overrides varied by alert type (P < .0001). About 60% of overrides were appropriate, and that proportion also varied by alert type (P < .0001). Few overrides of renal- (2.2%) or age-based (26.4%) medication substitutions were appropriate, while most duplicate drug (98%), patient allergy (96.5%), and formulary substitution (82.5%) alerts were appropriate. Discussion: Despite warnings of potential significant harm, certain categories of alert overrides were inappropriate >75% of the time. The vast majority of duplicate drug, patient allergy, and formulary substitution alerts were appropriate, suggesting that these categories of alerts might be good targets for refinement to reduce alert fatigue. Conclusion: Almost three-quarters of alerts were overridden, and 40% of the overrides were not appropriate. Future research should optimize alert types and frequencies to increase their clinical relevance, reducing alert fatigue so that important alerts are not inappropriately overridden.

Evaluation of medication-related clinical decision support alert overrides in the intensive care unit.

PURPOSE: Medication-related clinical decision support (CDS) has been identified as a method to improve patient outcomes but is historically frequently overridden and may be inappropriately so. Patients in the intensive care unit (ICU) are at a higher risk of harm from adverse drug events (ADEs) and these overrides may increase patient harm. The objective of this study is to determine appropriateness of overridden medication-related CDS overrides in the ICU. MATERIALS AND METHODS: We evaluated overridden medication-related alerts of four alert categories from January 2009 to December 2011. The primary outcome was the appropriateness of a random sample of overrides based on predetermined criteria. Secondary outcomes included the incidence of adverse drug events (ADEs) that resulted from the overridden alert. RESULTS: A total of 47,449 overridden alerts were included for evaluation. The appropriateness rate for overridden alerts varied by alert category (allergy: 94%, drug-drug interaction: 84%, geriatric: 57%, renal: 27%). A total of seven actual ADEs were identified in the random sample and where the medication(s) was administered (n=366), with an increased risk of ADEs associated with inappropriately overridden alerts (p=0.0078). CONCLUSIONS: The appropriateness of medication-related clinical decision support overrides in the ICU varied substantially by the type of alert. Inappropriately overridden alerts were associated with an increased risk of ADEs compared to appropriately overridden alerts.

Off-label indications for antidepressants in primary care: descriptive study of prescriptions from an indication based electronic prescribing system.

Objective To examine off-label indications for antidepressants in primary care and determine the level of scientific support for off-label prescribing.Design Descriptive study of antidepressant prescriptions written by primary care physicians using an indication based electronic prescribing system.Setting Primary care practices in and around two major urban centres in Quebec, Canada.Participants Patients aged 18 years or older who visited a study physician between 1 January 2003 and 30 September 2015 and were prescribed an antidepressant through the electronic prescribing system.Main outcome measures Prevalence of off-label indications for antidepressant prescriptions by class and by individual drug. Among off-label antidepressant prescriptions, the proportion of prescriptions in each of the following categories was measured: strong evidence supporting use of the prescribed drug for the respective indication; no strong evidence for the prescribed drug but strong evidence supporting use of another drug in the same class for the indication; or no strong evidence supporting use of the prescribed drug and all other drugs in the same class for the indication. Results 106 850 antidepressant prescriptions were written by 174 physicians for 20 920 adults. By class, tricyclic antidepressants had the highest prevalence of off-label indications (81.4%, 95% confidence interval, 77.3% to 85.5%), largely due to a high off-label prescribing rate for amitriptyline (93%, 89.6% to 95.7%). Trazodone use for insomnia was the most common off-label use for antidepressants, accounting for 26.2% (21.9% to 30.4%) of all off-label prescriptions. For only 15.9% (13.0% to 19.3%) of all off-label prescriptions, the prescribed drug had strong scientific evidence for the respective indication. For 39.6% (35.7% to 43.2%) of off-label prescriptions, the prescribed drug did not have strong evidence but another antidepressant in the same class had strong evidence for the respective indication. For the remaining 44.6% (40.2% to 49.0%) of off-label prescriptions, neither the prescribed drug nor any other drugs in the class had strong evidence for the indication.Conclusions When primary care physicians prescribed antidepressants for off-label indications, these indications were usually not supported by strong scientific evidence, yet often another antidepressant in the same class existed that had strong evidence for the respective indication. There is an important need to generate and provide physicians with evidence on off-label antidepressant use to optimise prescribing decisions.

Automated Extraction of VTE Events From Narrative Radiology Reports in Electronic Health Records: A Validation Study.

BACKGROUND: Surveillance of venous thromboembolisms (VTEs) is necessary for improving patient safety in acute care hospitals, but current detection methods are inaccurate and inefficient. With the growing availability of clinical narratives in an electronic format, automated surveillance using natural language processing (NLP) techniques may represent a better method. OBJECTIVE: We assessed the accuracy of using symbolic NLP for identifying the 2 clinical manifestations of VTE, deep vein thrombosis (DVT) and pulmonary embolism (PE), from narrative radiology reports. METHODS: A random sample of 4000 narrative reports was selected among imaging studies that could diagnose DVT or PE, and that were performed between 2008 and 2012 in a university health network of 5 adult-care hospitals in Montreal (Canada). The reports were coded by clinical experts to identify positive and negative cases of DVT and PE, which served as the reference standard. Using data from the largest hospital (n=2788), 2 symbolic NLP classifiers were trained; one for DVT, the other for PE. The accuracy of these classifiers was tested on data from the other 4 hospitals (n=1212). RESULTS: On manual review, 663 DVT-positive and 272 PE-positive reports were identified. In the testing dataset, the DVT classifier achieved 94% sensitivity (95% CI, 88%-97%), 96% specificity (95% CI, 94%-97%), and 73% positive predictive value (95% CI, 65%-80%), whereas the PE classifier achieved 94% sensitivity (95% CI, 89%-97%), 96% specificity (95% CI, 95%-97%), and 80% positive predictive value (95% CI, 73%-85%). CONCLUSIONS: Symbolic NLP can accurately identify VTEs from narrative radiology reports. This method could facilitate VTE surveillance and the evaluation of preventive measures.