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Objectives: After the shutdown of most dental services during the COVID‐19 lockdown, the oral health community was concerned about an increase in prescribing opioids and antibiotics by dentists due to patients' limited access to dental offices. Therefore, the objective of this study was to investigate the impact of COVID‐19 pandemic on the pattern of antibiotic and opioid prescriptions by dentists in Alberta, Canada. Methods: Data obtained from the Tracked Prescription Program were divided into antibiotics and opioids. Time periods were outlined as pre‐, during‐, and postlockdown (phase 1 and 2). For the number of prescriptions and average supply, each monthly average was compared to the corresponding prelockdown monthly average, using descriptive analysis. Time series analyses were conducted using regression analyses with an autoregressive error model. Data were trained and tested on monthly observations before lockdown and predicted for during‐ and postlockdown. Results: A total of 1.1 million antibiotics and 400,000 opioids dispense were tracked. Decreases in the number of prescriptions during lockdown presented for antibiotics (n = 24,933 vs. 18,884) and opioids (n = 8892 vs. 6051). Average supplies (days) for the antibiotics (n = 7.10 vs. 7.55) and opioids (n = 3.92 vs. 4.05) were higher during the lockdown period. In the trend analyses, the monthly number of antibiotic and opioid prescriptions showed the same pattern and decreased during lockdown. Conclusion: The COVID‐19 pandemic altered the trends of prescribing antibiotics and opioids by dentists. The full impact of COVID‐19 pandemic on the population's oral health in light of changes in prescribing practices by dentists during and after lockdown warrants further investigation. [ABSTRACT FROM AUTHOR]

Introduction: To promote optimal healthcare delivery, safeguarding older adults from the risks associated with inappropriate medication use is paramount. Objective: This study aims to evaluate the effectiveness of implementing the Qatar Tool for Reducing Inappropriate Medication (QTRIM) in ambulatory older adults to enhance medication safety. Method: The QTRIM was developed by an expert consensus panel using the Beers Criteria and contained a list of potentially inappropriate medications (PIMs) based on the local formulary. Using quality improvement methodology, it was piloted and implemented in two outpatient pharmacy settings serving geriatric medicine and dermatology clinics at Rumailah Hospital, Qatar. Key performance indicators (KPIs) using implementation documentation as a process measure and the percentage reduction in PIM prescriptions as an outcome measure were assessed before and after QTRIM implementation. This study was conducted between July 2022 and September 2023. Results: In the outpatient department (OPD) geriatric pharmacy, the prescription rate of PIMs was reduced from an average of 1.2 ± 0.7 PIMs per 1000 orders in 2022 to an average of 0.8 ± 0.2 PIMs per 1000 orders in 2023. In the OPD geriatric pharmacy, the results showed a 66.6% reduction in tricyclic antidepressants (TCAs) (from 30 to 10), a reduction in first-generation antihistamines by 51.7% (29 to 14), and muscle relaxants by 33.3% (36 to 24). While in dermatology, the older adult prescription rate of PIMs was reduced from an average of 8 ± 3 PIMs per 1000 orders in 2022 to a rate of 5 ± 3 PIMs per 1000 orders in 2023; the most PIM reductions were (49.4%) in antihistamines (from 89 to 45), while muscle relaxants and TCAs showed a minimal reduction. Conclusions: Implementing QTRIM with pharmacy documentation monitoring markedly reduced the PIMs dispensed from two specialized outpatient pharmacies serving older adults. It may be a promising effective strategy to enhance medication safety in outpatient pharmacy settings. [ABSTRACT FROM AUTHOR]

In Japan, pivoxil-conjugated antibodies (PVs) are commonly used to treat infections. However, carnitine deficiency is a known adverse drug reaction associated with PV treatment. This study aimed to research the practical use of PV and assess the risk of carnitine deficiency in patients receiving PV compared to their amoxicillin (AM)-treated counterparts. The Pediatric Medical Information Collection System (P-MICS) served as the data source for this study. The study cohort comprised patients aged 0–15 years prescribed PV between April 2016 and March 2021. Data on the actual PV prescriptions were extracted for each patient. To evaluate the risk of carnitine deficiency, adverse events (AEs) were defined as carnitine deficiency and its associated symptoms. Propensity score matching was employed to compare the AE incidence between the PV and AM groups. The number of cases of PV prescriptions decreased year-on-year between 2016 and 2021, and >80% of prescriptions were dispensed in the clinic. The propensity score matching analysis demonstrated no statistically significant difference in the incidence of carnitine deficiency and its associated symptoms between the PV and AM groups. Our findings suggest that the risk of carnitine deficiency in children treated with PV is not significantly higher than that associated with other antibiotics. [ABSTRACT FROM AUTHOR]

Background: Gout is the most common inflammatory arthritis and is almost exclusively managed in primary care, however the course and severity of the condition is variable and poorly characterised. This research aims improve understanding about the frequency of, and factors associated with, gout flares in the UK and characterise the factors associated with the initiation of ULT. Methods: Using the Clinical Practice Research Database, patients with a coded incident gout diagnosis without a prior prescription for urate-lowering therapy (ULT) were identified. Gout flares post diagnosis and ULT initiation were identified through prescribing and coded data. Patient characteristics, co-morbidities and co-prescribing were co-variants. Factors associated with gout flares and ULT initiation were analysed using cox-proportional hazard model and logistic regression. Results: Fifty-one thousand seven hundred eighty-four patients were identified: 18,605 (35.9%, 95%CI 35.5–36.3%) had experienced ≥ 1 recurrent flare, 17.4% (95%CI 17.1–17.8%) within 12 months of diagnosis. Male sex, black ethnicity, higher BMI, heart failure, CKD, CVD and diuretic use were associated with flares, with the highest HR seen with high serum urate levels (≥ 540 µmol/L HR 4.63, 95%CI 4.03–5.31). ULT initiation was associated with similar variables, although higher alcohol intake and older age were associated with lower odds of ULT initiation but were not associated with flares. ULT was initiated in 27.7% (95%CI 27.3–28.0%): 5.7% (95%CI 5.5–5.9%) within 12 months of diagnosis. ULT initiation rates were higher in patients with recurrent flares. Conclusion: Approximately one in six people with incident gout had a second flare within 12 months. Factors associated with flare recurrence and ULT initiation were similar, but ULT initiation occurred later after diagnosis than previously thought. [ABSTRACT FROM AUTHOR]

Objectives: Electronic medical record (EMR) prescription data may identify high antibiotic prescribers in primary care. However, practitioners doubt that population differences between providers and delayed antibiotic prescriptions are adequately accounted for in EMR-derived prescription rates. This study assessed the validity of using EMR prescription data to produce antibiotic prescription rates, accounting for these factors. Methods: The study was a secondary analysis of antimicrobial prescriptions collected from 4 primary care clinics from 2015 to 2017. For adults with selected respiratory and urinary infections, EMR diagnostic codes, prescription data, clinical diagnoses and demographics were abstracted. Overall and delayed prescription rates were produced for EMR diagnostic codes, clinical diagnoses, by clinic, and types of infection. Direct standardization was used to adjust for case mix differences by clinic. High antibiotic prescribers, above the 75th percentile for prescriptions, were compared with low antibiotic prescribers. Results: Of 3108 EMR visits, there were 2577 (85.4%) eligible visits with a clinical diagnosis and prescription information. Overall antibiotic prescription rates were similar utilizing EMR records (31.6%) or clinical diagnoses (32.6%, P =.40). When delayed prescriptions were removed, prescribing rates were lower (22.4%, P <.01). EMR data overestimated prescribing rates for conditions where antibiotics are usually not indicated (17.7% EMR vs 7.6% clinical diagnoses, P <.001). High antibiotic prescribers saw more cases where antibiotics are usually indicated (23.4%) compared to low prescribers (16.8%; P =.001). Conclusions: Electronic medical record prescribing rates are similar to those using clinical diagnoses overall, but overestimate prescribing by clinicians for conditions usually not needing antibiotics. EMR prescription rates do not account for delayed antibiotic prescriptions or differences in infection case-mix. [ABSTRACT FROM AUTHOR]

Background: Individuals with psoriasis face an increased risk of suffering from various comorbid conditions. However, there haven´t been any studies conducted in Sweden to examine the frequency of comorbidities and the corresponding treatment for these conditions among psoriasis patients. Methods: The Cosmic electronic medical record represents a comprehensive repository of medical information including all residents of Region Jönköping. To conduct a population-based retrospective cross-sectional study, all individuals diagnosed with psoriasis between April 9, 2008 and July 1, 2016, were identified via the electronic medical records using ICD-10 codes. Data on comorbidity and dispensation of prescribed drugs against these comorbid conditions were analyzed. Results: During the study period, 1.7% of the population (4,587 individuals) were diagnosed with psoriasis, with 74.3% of cases classified as mild to moderate psoriasis and 25.7% as severe. The remaining 268,949 individuals did not receive a psoriasis diagnosis. The study showed that psoriasis patients had higher odds of experiencing the majority of the comorbid conditions examined. Arthritis other than psoriasis arthritis was found to be the most prevalent comorbid diagnosis among psoriasis patients (adjusted OR 7.2, CI 95% 6.4-8.2, p < 0.001), followed by obesity (OR 2.4, CI 95% 1.9-3.1, p < 0,001). There was no significant difference in drug prescription for comorbid diseases between patients with psoriasis and patients without psoriasis except for arthritis and smoking cessation treatment. Conclusions: Individuals with psoriasis are more susceptible to experiencing multiple comorbid conditions compared to the general population, particularly those with severe psoriasis. There is no evidence of undertreatment of comorbidity except for arthritis among psoriasis patients. [ABSTRACT FROM AUTHOR]

Background: The emergence of drug resistance in the etiological agents of uncomplicated urinary tract infections (UTIs) emphasizes the need to shift the paradigm towards alternative therapeutic strategies. The objective of the present study was to evaluate the use of a medical device containing xyloglucan, hibiscus, and propolis for reducing UTI symptomatic episodes, antibiotic prescription, and days of sick leave. Materials and Methods: It used retrospective, cross-sectional study data provided by office-based physicians from Germany (Disease Analyzer, IQVIA database), including those on 3586 patients with a diagnosis of UTI treated with Utipro® Plus (Noventure, Barcelona, Spain) from January 2015 to December 2020. Results: The majority of patients were women (94.2%) and had a mean age (standard deviation, SD) of 57.7 years (19.0). Within 12 months after the prescription and compared to the 12 months before, it was observed that there was a reduction in the proportion of patients with at least one UTI diagnosis (from 79.4% to 36.4%, p < 0.001), in antibiotic prescriptions (from 33.5% to 22.1%, p < 0.001), and in the proportion of patients with at least one day of sick leave (from 4.1% to 2.7%). Conclusions: The use of Utipro® Plus is able to decrease UTI recurrence and can lead to the reduction of antibiotic prescriptions and disease burden in individuals affected by uncomplicated cystitis. [ABSTRACT FROM AUTHOR]

Background: In the era of Agri 4.0 and the popularity of Plantwise systems, the availability of Plant Electronic Medical Records has provided opportunities to extract valuable disease information and treatment knowledge. However, developing an effective prescription recommendation method based on these records presents unique challenges, such as inadequate labeling data, lack of structural and linguistic specifications, incorporation of new prescriptions, and consideration of multiple factors in practical situations. Results: This study proposes a plant disease prescription recommendation method called PRSER, which is based on sentence embedding retrieval. The semantic matching model is created using a pre-trained language model and a sentence embedding method with contrast learning ideas, and the constructed prescription reference database is retrieved for optimal prescription recommendations. A multi-vegetable disease dataset and a multi-fruit disease dataset are constructed to compare three pre-trained language models, four pooling types, and two loss functions. The PRSER model achieves the best semantic matching performance by combining MacBERT, CoSENT, and CLS pooling, resulting in a Pearson coefficient of 86.34% and a Spearman coefficient of 77.67%. The prescription recommendation capability of the model is also verified. PRSER performs well in closed-set testing with Top-1/Top-3/Top-5 accuracy of 88.20%/96.07%/97.70%; and slightly worse in open-set testing with Top-1/Top-3/Top-5 accuracy of 82.04%/91.50%/94.90%. Finally, a plant disease prescription recommendation system for mobile terminals is constructed and its generalization ability with incomplete inputs is verified. When only symptom information is available without environment and plant information, our model shows slightly lower accuracy with Top-1/Top-3/Top-5 accuracy of 75.24%/88.35%/91.99% in closed-set testing and Top-1/Top-3/Top-5 accuracy of 75.08%/87.54%/89.84% in open-set testing. Conclusions: The experiments validate the effectiveness and generalization ability of the proposed approach for recommending plant disease prescriptions. This research has significant potential to facilitate the implementation of artificial intelligence in plant disease treatment, addressing the needs of farmers and advancing scientific plant disease management. [ABSTRACT FROM AUTHOR]

OBJECTIVES: To evaluate the appropriateness of the medication management for anyone who might have been affected by the Horizon New Jersey Health Medicaid Health Maintenance Organization (HNJH Medicaid HMO) formulary update from empagliflozin to ertugliflozin and to then optimize drug selection and monitoring. STUDY DESIGN: This is a single-center, 2-phase, pilot project led by 2 pharmacy students and the lead clinical pharmacist at a federally qualified health center in Trenton, New Jersey. METHODS: The primary outcome of the study is the number and percentage of patients whose prescription was changed inappropriately from empagliflozin to ertugliflozin. Secondary outcomes include the number and percentage of patients whose prescription was changed inappropriately because of failure to consider cardiovascular history and/or missed renal function checks and whether pharmacists were able to optimize therapy. Data were generated from electronic health record reports and analyzed in Microsoft Excel. RESULTS: A total of 126 unique patients were identified as receiving empagliflozin and/or ertugliflozin and 16 patients were switched from empagliflozin to ertugliflozin, all of whom had HNJH Medicaid HMO. Thirteen of the 16 (81.3%) patients were managed inappropriately based on their history of cardiovascular disease or inappropriate renal monitoring. Pharmacists recommended 22 interventions for patients who received empagliflozin and/or ertugliflozin, and all recommendations were accepted by providers. CONCLUSIONS: Following the HNJH Medicaid HMO's coverage update from empagliflozin to ertugliflozin, some patients received inappropriate therapy and providers accepted clinical pharmacists' recommendations to optimize therapy. [ABSTRACT FROM AUTHOR]

Polypharmacy has been linked to cognitive decline. However, interventions targeting modifiable risk factors, some of which are targets of the most commonly used drugs, could reduce the prevalence of dementia. Our aim was to determine the drug prescription regimen at baseline, prior to the diagnosis of mild cognitive impairment (MCI), and its possible association with progression to dementia. Data were collected from the electronic medical records of 342 MCI outpatients diagnosed during 2006–2017 at their first neurology consultation. We followed the classical three-step method of statistical analysis, starting with a Latent Class Analysis (LCA) to discover subgroups of drug prescription probability. Half of the patients were under polypharmacy (≥5 drugs), 17.5% had no recorded medication, 33.3% progressed to dementia (94.7% in ≤5 years), and 84.1% of them to Alzheimer's disease (AD). According to the LCA and based on 20 therapeutic indicators obtained from 240 substances and regrouped according the Anatomical Therapeutic Chemical Classification, we identified a four-profile model: (1) low (35.7% of patients); (2) mixed (28.7%); (3) cardio-metabolic (19.3%); and (4) psychotropic (16.4%). The binomial regression logistic model showed that profiles 2 and 3 (and 4 for AD), with a higher drug prescription conditioned probability against classic risk factors, were protective than profile 1 (OR = 0.421, p = 0.004; OR = 0.278, p = 0.000; OR = 0.457, p = 0.040, respectively), despite polypharmacy being significant in profiles 2 and 3 (mean > 7 drugs) vs. profile 1 (1.4 ± 1.6) (p = 0.000). Patients in the latter group were not significantly older, although being aged 65–79 years old quadrupled (OR = 4.217, p = 000) and being >79 tripled (OR = 2.945, p = 0.010) the conversion risk compared to patients <65 years old. According to the proposed analytical model, profiling the heterogeneous association of risk factors, which were taken prior to diagnosis, could be explored as an indicator of prior care and a predictor of conversion to dementia. [ABSTRACT FROM AUTHOR]

Background: Medication adherence is usually defined as the extent of the agreement between the medication regimen agreed to by patients with their healthcare provider and the real-world implementation. Proactive identification of those with poor adherence may be useful to identify those with poor disease control and offers the opportunity for ameliorative action. Adherence can be estimated from Electronic Health Records (EHRs) by comparing medication dispensing records to the prescribed regimen. Several methods have been developed in the literature to infer adherence from EHRs, however there is no clear consensus on what should be considered the gold standard in each use case. Our objectives were to critically evaluate different measures of medication adherence in a large longitudinal Scottish EHR dataset. We used asthma, a chronic condition with high prevalence and high rates of non-adherence, as a case study. Methods: Over 1.6 million asthma controllers were prescribed for our cohort of 91,334 individuals, between January 2009 and March 2017. Eight adherence measures were calculated, and different approaches to estimating the amount of medication supply available at any time were compared. Results: Estimates from different measures of adherence varied substantially. Three of the main drivers of the differences between adherence measures were the expected duration (if taken as in accordance with the dose directions), whether there was overlapping supply between prescriptions, and whether treatment had been discontinued. However, there are also wider, study-related, factors which are crucial to consider when comparing the adherence measures. Conclusions: We evaluated the limitations of various medication adherence measures, and highlight key considerations about the underlying data, condition, and population to guide researchers choose appropriate adherence measures. This guidance will enable researchers to make more informed decisions about the methodology they employ, ensuring that adherence is captured in the most meaningful way for their particular application needs. [ABSTRACT FROM AUTHOR]

Electronic Healthcare Record (EHR) has been actively promoted recently. Healthcare records and paperbased medical prescriptions are scattered and unorganized in medical institutions and clinics, thereby prompting many efforts to advance the EHR from traditional clinical settings to an efficient electronic medical model to regulate health records appropriately and accurately. With the development of technology and data exchange over the Internet or local networks, protecting transmitted data in healthcare records is necessary. This paper presents a secure EHR system utilizing robust authentication and RSA digital signature. We performed formal and informal security analyses utilizing the Scyther tool and the Canetti-Krawczyk (CK) model. Therefore, the proposed scheme has a higher level of security than the previous relevant work by resisting the dangers of well-known cyberattacks, such as impersonation, DoS, replay, man-in-themiddle (MITM), and insider attacks. Our work balances the security complexity and the communication cost, and the comparison tables show that the proposed scheme has the lowest communication cost. Moreover, we presented a secure prescription through a QR code generated using the prescription and the physician's RSA digital signature. [ABSTRACT FROM AUTHOR]

Background: Overprescription of short-acting beta-agonist (SABA) inhalers and blood eosinophil count have strong associations with exacerbation risk in asthma. However, in the authors' recent publication only a minority of patients overprescribed SABA (=6 inhalers in 12 months) were eosinophilic (=0.3 x 109 cells/l). Aim: To compare the characteristics of eosinophilic and non-eosinophilic patients with asthma overprescribed SABA inhalers, and identify latent classes using clinical variables available in primary care. Design & setting: Cross-sectional analysis of patients with asthma in North East London, England, using primary care electronic health record data. Method: Unadjusted and adjusted multi-variate regression models and latent class analysis. Results: Eosinophilia was significantly less likely in female patients (P = 0.004), those with multiple mental health comorbidities (P<0.001), and those with SABA on repeat prescription (P<0.001). Latent class analysis identified the following three classes of patients overprescribed SABA: class 1, which represents classical uncontrolled asthma (oral steroids required for exacerbations, step 2-3 asthma medications, high probability of being eosinophilic); class 2, which represents mild asthma (low exacerbation frequency, low asthma medication step, low probability of being eosinophilic); and class 3, which represents difficult asthma (high exacerbation frequency despite high-strength preventer inhalers, low probability of being eosinophilic). The mild asthma class was the largest. Conclusion: Many patients being overprescribed SABA were non-eosinophilic with a low exacerbation frequency, suggesting disproportionately high SABA prescription compared with other asthma control markers. Potential reasons for high SABA prescription in these patients included repeat prescription (being dispensed but not taken) and use of SABA for non-asthma breathlessness (for example, breathing pattern disorders with anxiety). Further research is needed into management of SABA overuse in patients without other markers of uncontrolled asthma. [ABSTRACT FROM AUTHOR]

Background: Clinical practices have demonstrated that disease treatment can be very complex. Patients with chronic diseases often suffer from more than one disease. Complex diseases are often treated with a variety of drugs, including both primary and auxiliary treatments. This complexity and multidimensionality increase the difficulty of extracting knowledge from clinical data. Methods: In this study, we proposed a subgroup identification algorithm for complex prescriptions (SIAP). We applied the SIAP algorithm to identify the importance level of each drug in complex prescriptions. The algorithm quickly classified and determined valid prescription combinations for patients. The algorithm was validated through classification matching of classical prescriptions in traditional Chinese medicine. We collected 376 formulas and their compositions from a formulary to construct a database of standard prescriptions. We also collected 1438 herbal prescriptions from clinical data for automated prescription identification. The prescriptions were divided into training and test sets. Finally, the parameters of the two sub-algorithms of SIAP and SIAP-All, as well as those of the combination algorithm SIAP + All, were optimized on the training set. A comparison analysis was performed against the baseline intersection set rate (ISR) algorithm. The algorithm for this study was implemented with Python 3.6. Results: The SIAP-All and SIAP + All algorithms outperformed the benchmark ISR algorithm in terms of accuracy, recall, and F1 value. The F1 values were 0.7568 for SIAP-All and 0.7799 for SIAP + All, showing improvements of 8.73% and 11.04% over the existing ISR algorithm, respectively. Conclusion: We developed an algorithm, SIAP, to automatically match sub-prescriptions of complex drugs with corresponding standard or classic prescriptions. The matching algorithm weights the drugs in the prescription according to their importance level. The results of this study can help to classify and analyse the drug compositions of complex prescriptions. [ABSTRACT FROM AUTHOR]

OBJECTIVES: One in 5 people in the United States lives with chronic pain. Many patients with chronic pain experience a subset of specific co-occurring pain conditions that may share a common pain mechanism and that have been designated as chronic overlapping pain conditions (COPCs). Little is known about chronic opioid prescribing patterns among patients with COPCs in primary care settings, especially among socioeconomically vulnerable patients. This study aims to evaluate opioid prescribing among patients with COPCs in US community health centers and to identify individual COPCs and their combinations that are associated with long-term opioid treatment (LOT). STUDY DESIGN: Retrospective cohort study. METHODS: We conducted analyses of more than 1 million patients 18 years and older based on electronic health record data from 449 US community health centers across 17 states between January 1, 2009, and December 31, 2018. Logistic regression models were used to assess the relationship between COPCs and LOT. RESULTS: Individuals with COPCs were prescribed LOT 4 times more often than individuals without a COPC (16.9% vs 4.0%). The presence of chronic low back pain, migraine headache, fibromyalgia, or irritable bowel syndrome combined with any of the other COPCs increased the odds of LOT prescribing compared with the presence of a single COPC. CONCLUSIONS: Although LOT prescribing has declined over time, it remains relatively high among patients with certain COPCs and for those with multiple COPCs. These study findings suggest target populations for future interventions to manage chronic pain among socioeconomically vulnerable patients. [ABSTRACT FROM AUTHOR]

Purpose: Assess the impact of electronic health record interventions on patient access to post-hospital discharge prescriptions. Methods: Five interventions were implemented in the electronic health record to improve patient access to prescriptions after discharge from hospital: electronic prior authorization, alternative medication suggestions, order sets, mail order pharmacy alerts, and medication interchange instructions. This was a retrospective cohort study of patient responses from discharges during 6 months before the first intervention implementation and 6 months after the last intervention implementation documented in the electronic health record and a transition-in-care platform. Primary endpoint was the proportion of discharges with patient-reported issues that would have been prevented by the studied interventions out of number of discharges with at least one prescription, analyzed using Chi-squared test (level of significance.05). Results: Discharges with patient-reported issues that would have been prevented by the studied interventions decreased from 1.68 to 1.07 out of 1000 discharges with prescriptions (P <.001). Conclusion: Interventions in the electronic health record reduced barriers faced by patients to picking up prescriptions post-discharge from hospital, potentially leading to improved patient satisfaction and improved health outcomes. Important factors to consider for electronic health record intervention implementation are workflow development and intrusiveness of clinical decision support. Multiple targeted electronic health record interventions can improve patients' access to prescriptions after discharge from hospital. [ABSTRACT FROM AUTHOR]

BACKGROUND Butylphthalide (NBP) and edaravone (EDV) injection are common acute ischemic stroke medications in China, but there is a lack of large real-world safety studies on them. This study aimed to determine the incidence of adverse events, detect relevant safety signals, and assess the risk factors associated with these medications in real-world populations. METHODS In this study, data of acute ischemic stroke patients were extracted from the electronic medical record database of six tertiary hospitals between January 2019 and August 2021. Baseline confounders were eliminated using propensity score matching. The drugs' safety was estimated by comparing the results of 24 laboratory tests standards on liver function, kidney function, lipid level, and coagulation function. The drugs' relative risk was estimated by logistic regression. A third group with patients who did not receive NBP or EDV was constructed as a reference. Prescription sequence symmetry analysis was used to evaluate the associations between adverse events and NBP and EDV, respectively. RESULTS 81,292 patients were included in this study. After propensity score matching, the NBP, EDV, and third groups with 727 patients in each group. Among the 15 test items, the incidence of adverse events was lower in the NBP group than in the EDV group, and the differences were statistically significant. The multivariate logistic regression equation revealed that NBP injection was not a promoting factor for abnormal laboratory test results, whereas EDV had statistically significant effects on aspartate transaminase, low-density lipoprotein cholesterol and total cholesterol. Prescription sequence symmetry analysis showed that NBP had a weak correlation with abnormal platelet count. EDV had a positive signal associated with abnormal results in gamma-glutamyl transferase, alanine aminotransferase, aspartate aminotransferase, prothrombin time, and platelet count. CONCLUSIONS In a large real-world population, NBP has a lower incidence of adverse events and a better safety profile than EDV or other usual medications. [ABSTRACT FROM AUTHOR]

Objective: To determine whether more patients presented with Attention-deficit/hyperactivity disorder (ADHD)-related visits and/or sought care from family physicians more frequently during the COVID-19 pandemic. Methods: Electronic medical records from the University of Toronto Practice-Based Research Network were used to characterize changes in family physician visits and prescriptions for ADHD medications. Annual patient prevalence and visit rates pre-pandemic (2017–2019) were used to calculate the expected rates in 2020 and 2021. The expected and observed rates were compared to identify any pandemic-related changes. Results: The number of patients presenting for ADHD-related visits during the pandemic was consistent with pre-pandemic trends. However, observed ADHD-related visits in 2021 were 1.32 times higher than expected (95% CI: 1.05–1.75), suggesting that patients visited family physicians more frequently than before the pandemic. Conclusion: Demand for primary care services related to ADHD has continued to increase during the pandemic, with increased health service use among those accessing care. [ABSTRACT FROM AUTHOR]

Introduction: Benzodiazepines are the most commonly prescribed psychotropic medications, but they may place users at risk of serious adverse effects. Developing a method to predict benzodiazepine prescriptions could assist in prevention efforts. Methods: The present study applies machine learning methods to deidentified electronic health record data, in order to develop algorithms for predicting benzodiazepine prescription receipt (yes/no) and number of benzodiazepine prescriptions (0, 1, 2+) at a given encounter. Supportvector machine (SVM) and random forest (RF) approaches were applied to outpatient psychiatry, family medicine, and geriatric medicine data from a large academic medical center. The training sample comprised encounters taking place between January 2020 and December 2021 (N D 204,723 encounters); the testing sample comprised data from encounters taking place between January and March 2022 (N D 28,631 encounters). The following empirically-supported features were evaluated: anxiety and sleep disorders (primary anxiety diagnosis, any anxiety diagnosis, primary sleep diagnosis, any sleep diagnosis), demographic characteristics (age, gender, race), medications (opioid prescription, number of opioid prescriptions, antidepressant prescription, antipsychotic prescription), other clinical variables (mood disorder, psychotic disorder, neurocognitive disorder, prescriber specialty), and insurance status (any insurance, type of insurance). We took a step-wise approach to developing a prediction model, wherein Model 1 included only anxiety and sleep diagnoses, and each subsequent model included an additional group of features. Results: For predicting benzodiazepine prescription receipt (yes/no), all models showed good to excellent overall accuracy and area under the receiver operating characteristic curve (AUC) for both SVM(Accuracy D 0.868-0.883; AUC D 0.864-0.924) and RF (Accuracy D 0.860-0.887; AUC D 0.877-0.953). Overall accuracy was also high for predicting number of benzodiazepine prescriptions (0, 1, 2+) for both SVM (Accuracy D 0.861-0.877) and RF (Accuracy D 0.846-0.878). Discussion: Results suggest SVM and RF algorithms can accurately classify individuals who receive a benzodiazepine prescription and can separate patients by the number of benzodiazepine prescriptions received at a given encounter. If replicated, these predictive models could inform system-level interventions to reduce the public health burden of benzodiazepines. [ABSTRACT FROM AUTHOR]

Introduction: There are more than 80,000 emergency department (ED) visits for non-fatal bullet-related injuries (BRI) per year in the United States. Approximately half of these patients are discharged home from the ED. Our objective in this study was to characterize the discharge instructions, prescriptions, and follow-up plans provided to patients discharged from the ED after BRI. Methods: This was a single-center, cross-sectional study of the first 100 consecutive patients who presented to an urban, academic, Level I trauma center ED with an acute BRI beginning on January 1, 2020. We queried the electronic health record for patient demographics, insurance status, cause of injury, hospital arrival and discharge timestamps, discharge prescriptions, and documented instructions regarding wound care, pain management, and follow-up plans. We analyzed data using descriptive statistics and chi-square tests. Results: During the study period, 100 patients presented to the ED with an acute firearm injury. Patients were predominantly young (median age 29, interquartile range 23-38 years), male (86%), Black (85%), non-Hispanic (98%), and uninsured (70%). We found that 12% of patients did not receive any type of written wound care instruction, while 37% received discharge paperwork that included instructions to take both an NSAID and acetaminophen. Fifty-one percent of patients received an opioid prescription, with a range from 3-42 tablets (median 10 tablets). The proportion of patients receiving an opioid prescription was significantly higher among White patients (77%) than among Black patients (47%). Conclusion: There is variability in prescriptions and instructions provided to survivors of bullet injuries upon ED discharge at our institution. Our data indicates that standardized discharge protocols could improve quality of care and equity in the treatment of patients who have survived a BRI. Current variable quality in discharge planning is an entry point for structural racism and disparity. [ABSTRACT FROM AUTHOR]

Background: Varicella is considered a mild and self-limiting disease, but, in some cases, it may complicate and require hospitalization. Antibiotics are not the first line therapy but in some cases are prescribed either for the management of varicella-related complications or as a preventive strategy. Aim of this study is to analyze the rate and the patterns of antibiotics used in pediatric patients hospitalized for varicella as well as the relative costs in order to increase insights in antibiotic use in varicella. Methods: Patients less than 18 years hospitalized for varicella at the Bambino Gesù Children's IRCCS Hospital in Rome, Italy, from the 1st of November 2005 to the 1st of November 2021 entered the study. Retrospective data were collected from the hospital's database electronic medical records. The rate, the patterns and the costs of antibiotics used were considered. Results: According to the inclusion criteria, we enrolled 810 patients, with a median age of 2.4 years. Out of them, 345 patients (42.6%) underwent antibiotic therapy, of which 307 for a complication (90.0%) and the other 10.0%, antibiotic for the fear of developing complications. The cost for varicella hospitalizations was EUR 2,928,749 (median cost EUR 2689). As for antibiotic therapy, it represented the 5.9% of the total cost (EUR 174,527), with a median cost of EUR 198.8. The cost in patients who underwent antibiotic therapy was significantly higher than in those who did not (p-value < 0.0001), as well as the hospitalization length (p-value < 0.0001). The most commonly prescribed antibiotics were Amoxicillin-clavulanate and Ceftriaxone, which represented the 36.0% and 25.0% of all antibiotic prescription, respectively. Antibiotics may negatively affect the economic cost of hospitalization and the prescription is not always in accordance to guidelines, with potential important repercussions on the development of antimicrobial resistance. Actually, resistance to antibiotics is considered a major risk to the future health of the world population as it may lead to longer hospital stay, increased risk of mortality, health care costs and treatment failures. Conclusion: Strategies to reduce economical cost, hospitalization length and antimicrobial resistance include ensuring appropriate prescription and administration of empiric antibiotics as well as reducing the circulation of preventable infectious diseases through immunization. [ABSTRACT FROM AUTHOR]

Background: Appropriate use of effective treatments is required for satisfactory control of allergic symptoms. Coherent medical care -regular prescribing by the same Health Care Professionals- is a preliminary need. Objective: We investigated the numbers of distinct prescribers, the regularity of medical visits, and the agreement between prescriptions and associated dispensations in individual patients with perennial allergic rhinitis (PAR) and asthma. Methods: In primary care electronic health records (EHRs), a cohort of patients with PAR and asthma was identified. Individual EHRs were linked to corresponding claims recording all dispensations. Prescribing patterns were analyzed for the major treatment classes, and the dispensations linked to individual prescriptions were retrieved to compute the proportions of days covered (PDCs) for asthma and PAR therapy. Results: A total of 3654 patients were included, with 62% being female (mean age, 46.1 years). At inclusion, asthma control was not optimal in 51% of the patients and 48% had received oral corticosteroids. The mean interval between successive prescriptions varied between 93 (leukotriene receptor antagonists, LTRAs) and 103 (inhaled corticosteroids, ICS) days, and 97 (antihistamines, AHs) and 103 days (nasal corticosteroids, NCS). On average, individual prescriptions lead to 1.2, 1.5, 1.7 and 1.8 dispensations of ICS, ICS/Long-Acting Beta-Agonist (LABA) fixed-dose combinations, LABAs, and LTRAs, respectively, and to 1.3 and 1.6 dispensations of NCS and AHs, respectively. PDCs then varied between 37.8% for ICS and 58.6% for LTRAs, and between 39.7% for NCS and 50.4% for AHs. Care was nonetheless coherent, with > 90% of all dispensations related to prescriptions issued by single General Practitioners (GPs). Conclusion: Despite regular healthcare visits and medication prescriptions, allergic patients only partly and selectively refilled their treatments, preferring the less effective therapy, in a context of poor control of asthma symptoms. [ABSTRACT FROM AUTHOR]

Background Studies report an increased risk of self-harm or suicide in people prescribed mirtazapine compared with other antidepressants. Objectives To compare the risk of serious sel-fharm in people prescribed mirtazapine versus other antidepressants as second-line treatments. Design and setting Cohort study using anonymised English primary care electronic health records, hospital admission data and mortality data with study window 1 January 2005 to 30 November 2018. Participants 24 516 people diagnosed with depression, aged 18-99 years, initially prescribed a selective serotonin reuptake inhibitor (SSRI) and then prescribed mirtazapine, a different SSRI, amitriptyline or venlafaxine. Main outcome measures Hospitalisation or death due to deliberate self-harm. Age--sex standardised rates were calculated and survival analyses were performed using inverse probability of treatment weighting to account for baseline covariates. Results Standardised rates of serious self-harm ranged from 3.8/1000 person-years (amitriptyline) to 14.1/1000 person-years (mirtazapine). After weighting, the risk of serious self-harm did not differ significantly between the mirtazapine group and the SSRI or venlafaxine groups (HRs (95% CI) 1.18 (0.84 to 1.65) and 0.85 (0.51 to 1.41) respectively). The risk was significantly higher in the mirtazapine than the amitriptyline group (3.04 (1.36 to 6.79)) but was attenuated after adjusting for dose. Conclusions There was no evidence for a difference in risk between mirtazapine and SSRIs or venlafaxine after accounting for baseline characteristics. The higher risk in the mirtazapine versus the amitriptyline group might reflect residual confounding if amitriptyline is avoided in people considered at risk of self-harm. Clinical implications Addressing baseline risk factors and careful monitoring might improve outcomes for people at risk of serious self-harm. [ABSTRACT FROM AUTHOR]

Introduction: In patients with rheumatoid arthritis (RA), attaining remission or low disease activity (LDA), as recommended by the treat-to-target approach, has shown to yield improvement in symptoms and quality of life. However, limited evidence from real-world settings is available to support the premise that better disease control is associated with lower healthcare costs. This study fills in evidence gaps regarding the cost of care by RA disease activity (DA) states and by therapy. Methods: This retrospective cohort study linked medical and prescription claims from Optum Clinformatics Data Mart to electronic health record data from Illumination Health over 1/1/2010–3/31/2020. Mean annual costs for payers and patients were examined, stratifying on DA state and baseline use of conventional synthetic disease-modifying antirheumatic drugs (csDMARDs), biologics, and targeted synthetic (ts)DMARDs. Subgroup analysis examining within-person change in costs pre- and post-initiation of new therapy was also performed. Descriptive statistics, means, and boot-strapped confidence intervals were analyzed by DA state and by RA therapy. Furthermore, multivariate negative binomial regression analysis adjusting for key baseline characteristics was conducted. Results: Of 2339 eligible patients, 19% were in remission, 40% in LDA, 29% in moderate DA (MDA), and 12% in high DA (HDA) at baseline. Mean annual costs during follow-up were substantially less for patients in remission ($40,072) versus those in MDA ($56,536) and HDA ($59,217). For patients in remission, csDMARD use was associated with the lowest mean annual cost ($25,575), tsDMARD was highest ($75,512), and tumor necrosis factor inhibitor (TNFi) ($69,846) and non-TNFi ($57,507) were intermediate. Among new TNFi (n = 137) and non-TNFi initiators (n = 107), 31% and 26% attained LDA/remission, respectively, and the time to achieve remission/LDA was numerically shorter in TNFi vs. non-TNFi initiators. For those on biologics, mean annual within-person medical and inpatient costs were lower after achieving LDA/remission, although pharmacy costs were higher. Conclusions: Cost of care increased with increasing DA state, with patients in remission having the lowest costs. Optimizing DA has the potential for substantial savings in healthcare costs, although may be partially offset by the high cost of targeted RA therapies. [ABSTRACT FROM AUTHOR]

OBJECTIVES: To assess the accuracy of a real-time benefit tool (RTBT) that is compliant with the standards of the National Council for Prescription Drug Programs (NCPDP) in a large academic medical center. STUDY DESIGN: Observational study of electronic health records and pharmacy records from July 14, 2019, through January 14, 2020, across all ambulatory clinics and outpatient pharmacies in the health system. METHODS: Main assessments included (1| demographic characteristics of patients in whom the RTBT was used and those in whom it was not used, (2| types of changes most frequently made to medication orders upon reviewing the RTBT, and (3| comparison of the out-of-pocket costs for prescriptions vs the RTBT-generated estimates. RESULTS: The most common modifications made to prescriptions due to RTBT use were changes in days' supply (44%) and the quantity of medication (69%). In more than 98% of prescription orders, patients' out-of-pocket costs were either equivalent to or lower than the estimates generated by the RTBT. CONCLUSIONS: Current standards established by NCPDP yield accurate patient out-of-pocket estimates and could serve as a national standard for all Part D sponsors. [ABSTRACT FROM AUTHOR]

Interpersonal violence increases vulnerability to the deleterious effects of opioid use. Increased opioid prescription receipt is a major contributor to the opioid crisis; however, our understanding of prescription patterns and risk factors among those with a history of interpersonal violence remains elusive. This study sought to identify 5-year longitudinal patterns of opioid prescription receipt among patients experiencing interpersonal violence within a large healthcare system and sociodemographic and clinical characteristics associated with prescription patterns. This secondary analysis examined electronic health record data from January 2004–August 2019 for a cohort of patients (N = 1,587) referred for interpersonal violence services. Latent class growth analysis was used to estimate trajectories of opioid prescription receipt over a 5-year period. Standardized differences were calculated to assess variation in sociodemographic and clinical characteristics between classes. Our cohort had a high prevalence of prescription opioid receipt (73.3%) and underlying co-morbidities, including chronic pain (54.6%), substance use disorders (39.0%), and mental health diagnoses (76.9%). Six prescription opioid receipt classes emerged, characterized by probability of any prescription opioid receipt at the start and end of the study period (high, medium, low, never) and change in probability over time (increasing, decreasing, stable). Classes with the highest probability of prescription opioids also had the highest proportions of males, chronic pain diagnoses, substance use disorders, and mental health diagnoses. Black, non-Hispanic and Hispanic patients were more likely to be in low or no prescription opioid receipt classes. These findings highlight the importance of monitoring for synergistic co-morbidities when providing pain management and offering treatment that is trauma-informed, destigmatizing, and integrated into routine care. [ABSTRACT FROM AUTHOR]

Objectives  Pain management remains a point of emphasis given the ongoing opioid crisis. There are no studies in the literature interrogating opioid prescribing and use following endoscopic pituitary surgery. This study investigates provider prescribing tendency, patient utilization of analgesics, and patient outcomes regarding pain management after endoscopic pituitary surgery. Methods  We identified 100 patients undergoing endoscopic pituitary surgery at one institution from 2016 to 2018 in the electronic medical record (EMR) and state narcotic database to determine postoperative analgesic regimens. A telephone survey was used to characterize postoperative analgesic use and satisfaction with prescribed regimen. Results  Fifty-two different pain control regimens were prescribed to the study patients. Also, 93% of study patients were prescribed an opioid postoperatively. The average quantity of opioids prescribed per patient in morphine milligram equivalents (MMEs) was 625 (equivalent 83 oxycodone 5-mg tablets) with an average MME/day of 59 (equivalent 8 oxycodone 5-mg tablets). A total of 71% survey respondents who used opioids reported using <25% of their prescription. The majority of prescription narcotic users consumed >50% of their postoperative opioid intake in the first 24 to 48 hours after discharge. There were no significant differences in pain outcome between opioid users and nonopioid users. Conclusion  Vast heterogeneity exists in narcotic prescribing by providers at our institution following endoscopic pituitary surgery. Narcotic prescribing patterns exceeded most patients' analgesic needs. Opioid analgesics were not superior to nonopioids regimens in patient-reported pain outcomes in this study population. [ABSTRACT FROM AUTHOR]

Objective: Despite guidelines recommending less stringent glycemic goals for older adults with type 2 diabetes, overtreatment is prevalent. Pragmatic approaches for prioritizing patients for optimal prescribing are lacking. We describe glycemic control and medication patterns for older adults with type 2 diabetes in a contemporary cohort, exploring variability by frailty status. Research Design and Methods: This was a cross-sectional observational study based on electronic health record (EHR) data, within an accountable care organization (ACO) affiliated with an academic medical center/health system. Participants were ACO-enrolled adults with type 2 diabetes who were ≥65 years of age as of 1 November 2020. Frailty status was determined by an automated EHR-based frailty index (eFI). Diabetes management was described by the most recent A1C in the past 2 years and use of higher-risk medications (insulin and/or sulfonylurea). Results: Among 16,973 older adults with type 2 diabetes (mean age 75.2 years, 9,154 women [53.9%], 77.8% White), 9,134 (53.8%) and 6,218 (36.6%) were classified as pre-frail (0.10 < eFI ≤0.21) or frail (eFI >0.21), respectively. The median A1C level was 6.7% (50 mmol/mol) with an interquartile range of 6.2–7.5%, and 74.1 and 38.3% of patients had an A1C <7.5% (58 mmol/mol) and <6.5% (48 mmol/mol), respectively. Frailty status was not associated with level of glycemic control (P = 0.08). A majority of frail patients had an A1C <7.5% (58 mmol/mol) (n = 4,544, 73.1%), and among these patients, 1,755 (38.6%) were taking insulin and/or a sulfonylurea. Conclusion: Treatment with insulin and/or a sulfonylurea to an A1C levels <7.5% is common in frail older adults. Tools such as the eFI may offer a scalable approach to targeting optimal prescribing interventions. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate the clinical impact of HLA-B*15:02 pharmacogenomics (PGx) testing before carbamazepine (CBZ)/oxcarbazepine (OXC) prescriptions and to determine whether this PGx testing was associated with the reduction of CBZ/OXC-induced cutaneous adverse drug reactions (CADRs) in Thailand. Methods: This retrospective observational cohort study was conducted by obtaining relevant HLA-B*15:02 PGx-testing and clinical data from electronic medical records during 2011 -2020.384 patient data were included in this study to investigate the clinical decision on CBZ/OXC usage before and after the HLA-B*15:02 PGx testing, and 1,539 patient data were included in this study to demonstrate the incidence of CBZ/OXC-induced SCARs and SJS between HLA-B*15:02 tested and non-tested patients. To analyze and summarize the results, descriptive statistics were employed, and Fisher exact test was used to compare the clinical difference between the HLA-B*15:02 positive and negative groups and to compare the differences of SCARs incidence. Results: 384 patients were included in this study as per the inclusion criteria. Of these, 70 patients carried HLA-B*15:02, of which 63 and 65 patients were not prescribed with CBZ/ OXC before and after the availability of genotyping results, respectively. In the remaining HLA-B*15:02 non-carriers, 48, and 189 patients were prescribed CBZ/OXC before and after genotyping results were available, respectively. The findings of this study showed that HLA-B*15:02 Genotyping as Standard-of-Care in Thailand the incidence of SCARs of CBZ/OXC was significantly lower (p < 0.001) in the HLA-B*15:02 screening arm than in the non-screening arm. Conclusion: HLA-B pharmacogenetics testing influenced the selection of appropriate AEDs. The presence of mild rash in the HLA-B*15:02 negative group indicates that other genetic biomarker (HLA-A*31:01) and/or non-genetic variables are involved in CBZ/OXC-induced CADRs, emphasizing that CBZ/OXC prescriptions necessitate CADR monitoring. The hospital policy and clinical decision support (CDS) alert system is essential to overcome the barriers associated with the utilization of PGx guidelines into clinical practice. [ABSTRACT FROM AUTHOR]

OBJECTIVE To describe patterns of antimicrobial prescriptions for sporadic urinary tract infections (UTIs) in dogs in the United States from 2010 through 2019, including times before and after publication of International Society for Companion Animal Infectious Disease (ISCAID) guidelines. SAMPLE 461,244 qualifying visits for sporadic UTIs. PROCEDURES Veterinary electronic medical records of a private corporation consisting of > 1,000 clinics across the United States were examined to identify canine visits for potential sporadic UTI between January 1, 2010, and December 31, 2019. Proportions of antimicrobial prescriptions were graphed by month and year to identify changes in prescription patterns over time. Interrupted time series analysis was performed for the aminopenicillins. RESULTS A total of 461,244 qualifying visits were examined, with 389,949 (85%) of these resulting in at least 1 antimicrobial prescription. Over the 10-year period, the proportion of visits resulting in no antimicrobial prescription increased (14% in 2010 to 19.7% in 2019). Proportions of prescriptions for amoxicillin (38% to 48%) and amoxicillin-clavulanic acid (2.5% to 10%) also increased. Log-linear regression supported that changes in proportions of amoxicillin and amoxicillin-clavulanic acid prescriptions occurred following the 2011 ISCAID guidelines publication, with the proportion of amoxicillin prescriptions increasing by 13% per year (95% Cl, 12% to 14%; P < 0.01) and the proportion of amoxicillin-clavulanic acid prescriptions increasing by 0.5% per year (95% Cl, 0.2% to 0.8%; P< 0.01). Use of fluoroquinolones and third-generation cephalosporins remained constant. CLINICAL RELEVANCE Resultssuggestthat efforts toguideantimicrobial use in veterinary clinical practiceare having positive effects in this private veterinary company, though continued efforts are warranted. [ABSTRACT FROM AUTHOR]

Background: Comorbidities are common in chronic inflammatory conditions, requiring multidisciplinary treatment approach. Understanding the link between a single disease and its comorbidities is important for appropriate treatment and management. We evaluate the ability of an NLP‐based process for knowledge discovery to detect information about pathologies, patients' phenotype, doctors' prescriptions and commonalities in electronic medical records, by extracting information from free narrative text written by clinicians during medical visits, resulting in the extraction of valuable information and enriching real world evidence data from a multidisciplinary setting. Methods: We collected clinical notes from the Allergy Department of Humanitas Research Hospital written in the last 3 years and used it to look for diseases that cluster together as comorbidities associated to the main pathology of our patients, and for the extent of prescription of systemic corticosteroids, thus evaluating the ability of NLP‐based tools for knowledge discovery to extract structured information from free text. Results: We found that the 3 most frequent comorbidities to appear in our clusters were asthma, rhinitis, and urticaria, and that 991 (of 2057) patients suffered from at least one of these comorbidities. The clusters which co‐occur particularly often are oral allergy syndrome and urticaria (131 patients), angioedema and urticaria (105 patients), rhinitis and asthma (227 patients). With regards to systemic corticosteroid prescription volume by our clinicians, we found it was lower when compared to the therapy the patients followed before coming to our attention, with the exception of two diseases: Chronic obstructive pulmonary disease and Angioedema. Conclusions: This analysis seems to be valid and is confirmed by the data from the literature. This means that NLP tools could have significant role in many other research fields of medicine, as it may help identify other important, and possibly previously neglected clusters of patients with comorbidities and commonalities. Another potential benefit of this approach lies in its potential ability to foster a multidisciplinary approach, using the same drugs to treat pathologies normally treated by physicians in different branches of medicine, thus saving resources and improving the pharmacological management of patients. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the continuity and completeness of electronic health record (EHR) data, and the concordance of select clinical outcomes and baseline comorbidities between EHR and linked claims data, from three healthcare delivery systems in Taiwan. Methods: We identified oral hypoglycemic agent (OHA) users from the Integrated Medical Database of National Taiwan University Hospital (NTUH-iMD), which was linked to the National Health Insurance Research Database (NHIRD), from June 2011 to December 2016. A secondary evaluation involved two additional EHR databases. We created consecutive 90-day periods before and after the first recorded OHA prescription and defined patients as having continuous EHR data if there was at least one encounter or prescription in a 90-day interval. EHR data completeness was measured by dividing the number of encounters in the NTUH-iMD by the number of encounters in the NHIRD. We assessed the concordance between EHR and claims data on three clinical outcomes (cardiovascular events, nephropathy-related events, and heart failure admission). We used individual comorbidities that comprised the Charlson comorbidity index to examine the concordance of select baseline comorbidities between EHRs and claims. Results: We identified 39,268 OHA users in the NTUH-iMD. Thirty-one percent (n = 12,296) of these users contributed to the analysis that examined data continuity during the 6-month baseline and 24-month follow-up period; 31% (n = 3,845) of the 12,296 users had continuous data during this 30-month period and EHR data completeness was 52%. The concordance of major cardiovascular events, nephropathy-related events, and heart failure admission was moderate, with the NTU-iMD capturing 49–55% of the outcome events recorded in the NHIRD. The concordance of comorbidities was considerably different between the NTUH-iMD and NHIRD, with an absolute standardized difference >0.1 for most comorbidities examined. Across the three EHR databases studied, 29–55% of the OHA users had continuous records during the 6-month baseline and 24-month follow-up period. Conclusion: EHR data continuity and data completeness may be suboptimal. A thorough evaluation of data continuity and completeness is recommended before conducting clinical and translational research using EHR data in Taiwan. [ABSTRACT FROM AUTHOR]

Background: Prescription opioid misuse is a serious national crisis; in 2018 the top drugs involved in prescription overdose deaths included pain medications (opioids), benzodiazepines, and stimulants. Health information technology (health IT) provides a means to address this crisis through technologies that streamline the prescribing and discontinuation process. CancelRx is a health IT function that communicates when medications, such as controlled substances, are discontinued at the clinic and therefore should not be filled at the pharmacy. Prior to CancelRx, the communication of discontinued medications was a manual process, requiring the patient or a clinic staff member to personally contact the pharmacy to inform them of the change. The objective of this study was to assess how controlled substance medication discontinuations were communicated over time, before and after the implementation of CancelRx.Methods: Secondary data from a midwestern academic health system electronic health record and pharmacy platform were collected 12-months prior to CancelRx implementation and for 12-months post implementation. The study utilized an interrupted time series analysis (ITSA) to capture the percentage of controlled substance medications that were discontinued in the clinic's electronic health record and discontinued in the pharmacy's dispensing software. The ITSA plotted the percentage of successful discontinuation messages over time, particularly after the health system's implementation of CancelRx, a novel technology.Results: After CancelRx implementation there was an immediate (change = 77.7 percentage point) and significant (p < 0.001) increase in the number of controlled substance medications that were successfully discontinued at the pharmacy after being discontinued in the clinic. This change was sustained in the year following CancelRx (slope = 0.03 pp, 95% CI - 0.050 to 0.110) and did not revert to pre-CancelRx levels. The health IT functionality was able to effectively complete discontinuation tasks and potentially reduce workload for clinic staff.Conclusions: Overall, this study demonstrates the role that technology can play in promoting communication between clinics and pharmacies, especially when medications such as controlled substances are discontinued. [ABSTRACT FROM AUTHOR]

Purpose: The frequency of medication prescribing and polypharmacy has increased in recent years in different settings, including Swiss general practice. We aimed to describe patient age- and sex-specific rates of polypharmacy and of prescriptions of the most frequent medication classes, and to explore practitioner variability in prescribing. Methods: Retrospective cross-sectional study based on anonymized electronic medical records data of 111 811 adult patients presenting to 116 Swiss general practitioners in 2019. We used mixed-effects regression analyses to assess the association of patient age and sex with polypharmacy (≥5 medications) and with the prescription of specific medication classes (second level of the Anatomical Therapeutic Chemical Classification System). Practitioner variability was quantified in terms of the random effects distributions. Results: The prevalence of polypharmacy increased with age from 6.4% among patients aged 18–40 years to 19.7% (41–64 years), 45.3% (65–80 years), and 64.6% (81–92 years), and was higher in women than in men, particularly at younger ages. The most frequently prescribed medication classes were antiinflammatory and antirheumatic products (21.6% of patients), agents acting on the renin-angiotensin system (19.9%), analgesics (18.7%), and drugs for acid related disorders (18.3%). Men were more often prescribed agents targeting the cardiovascular system, whereas most other medications were more often prescribed to women. The highest practitioner variabilities were observed for vitamins , for antiinflammatory and antirheumatic products, and for mineral supplements. Conclusion: Based on practitioner variability, prevalence, and risk potential, antiinflammatory drugs and polypharmacy in older patients appear to be the most pressing issues in current drug prescribing routines. [ABSTRACT FROM AUTHOR]

Purpose: To determine statin prescription patterns and associated factors among type 2 diabetes patients attending the diabetic clinic at Muhimbili National Hospital (MNH) in Dar es Salaam, Tanzania. Patients and Methods: A hospital-based cross-sectional study involving outpatients was conducted from September 2020 to November 2020. Statin prescription history (both type and dosage) was obtained from patients as well as from the electronic medical records for determination of patterns. Participants were categorized as moderate or high risk for cardiovascular disease whereas prescription patterns were categorized as moderate and high intensity statins. Logistic regression was used to examine association, control confounders and effect modifier whereby p < 0.05 was considered statistically significant. Results: Of 400 patients who were approached for the study, 395 (98.8%) were eligible for statin prescriptions. The mean (±SD) age of the study participants was 58.1± 10.3 years, out of which 371 (93.9%) belonged to the age group ≥ 40 years. Two-thirds(241 61.0%) of the patients were female. About two-thirds(257; 69.4%) of patients had health insurance coverage. Statins were prescribed in 47.3% of the participants. Moderate intensity statin was the only pattern prescribed. In the adjusted model, insurance coverage (OR: 0.056; 95% CI: 0.03– 0.12), and hypertension (OR: 0.259; 95% CI: 0.12– 0.54) were associated with an increased likelihood of being prescribed a moderate intensity statin. Conclusion: A significant number of patients at MNH diabetic clinic were not on statins despite qualifying for the prescription. The findings call for further studies on reasons for low statin prescription practices in this tertiary facility. [ABSTRACT FROM AUTHOR]

Background: Antimicrobial stewardship programs promote the appropriate use of antimicrobial substances through the implementation of evidence-based, active and passive interventions. We analyzed the effect of a computer-assisted intervention on antimicrobial use in a tertiary care hospital.Methods: Between 2011 and 2016 we introduced an electronic alert for patients being prescribed meropenem, voriconazole and caspofungin. At prescription and at day 3 of treatment, physicians were informed about the risk related to these antimicrobial substances by an electronic alert in the medical records. Physicians were invited to revoke or confirm the prescription and to contact the infectious disease (ID) team. Using interrupted time series regression, the days of therapy (DOTs) and the number of prescriptions before and after the intervention were compared.Results: We counted 64,281 DOTs for 5549 prescriptions during 4100 hospital stays. Overall, the DOTs decreased continuously over time. An additional benefit of the alert could not be observed. Similarly, the number of prescriptions decreased over time, without significant effect of the intervention. When considering the three drugs separately, the alert impacted the duration (change in slope of DOTs/1000 bed days; P = 0.0017) as well as the number of prescriptions (change in slope of prescriptions/1000 bed days; P < 0.001) of voriconazole only.Conclusions: The introduction of the alert lowered prescriptions of voriconazole only. Thus, self-stewardship alone seems to have a limited impact on electronic prescriptions of anti-infective substances. Additional measures such as face-to-face prompting with ID physicians or audit and feedback are indispensable to optimize antimicrobial use. [ABSTRACT FROM AUTHOR]

Background: Electronic health records (EHR) data can be used to understand population level quality of care especially when supplemented with patient reported data. However, survey non-response can result in biased population estimates. As a case study, we demonstrate that EHR and survey data can be combined to estimate primary care population prescription treatment status for migraine stratified by migraine disability, without and with adjustment for survey non-response bias. We selected disability as it is associated with survey participation and patterns of prescribing for migraine. Methods: A stratified random sample of Sutter Health adult primary care (PC) patients completed a digital survey about headache, migraine, and migraine related disability. The survey data from respondents with migraine were combined with their EHR data to estimate the proportion who had prescription orders for acute or preventive migraine treatments. Separate proportions were also estimated for those with mild disability (denoted "mild migraine") versus moderate to severe disability (denoted mod-severe migraine) without and with correction, using the inverse propensity weighting method, for non-response bias. We hypothesized that correction for non-response bias would result in smaller differences in proportions who had a treatment order by migraine disability status. Results: The response rate among 28,268 patients was 8.2%. Among survey respondents, 37.2% had an acute treatment order and 16.8% had a preventive treatment order. The response bias corrected proportions were 26.2% and 11.6%, respectively, and these estimates did not differ from the total source population estimates (i.e., 26.4% for acute treatments, 12.0% for preventive treatments), validating the correction method. Acute treatment orders proportions were 32.3% for mild migraine versus 37.3% for mod-severe migraine and preventive treatment order proportions were 12.0% for mild migraine and 17.7% for mod-severe migraine. The response bias corrected proportions for acute treatments were 24.8% for mild migraine and 26.6% for mod-severe migraine and the proportions for preventive treatment were 8.1% for mild migraine and 12.0% for mod-severe migraine. Conclusions: In this study, we combined survey data with EHR data to better understand treatment needs among patients diagnosed with migraine. Migraine-related disability is directly related to preventive treatment orders but less so for acute treatments. Estimates of treatment status by self-reported disability status were substantially over-estimated among those with moderate to severe migraine-related disability without correction for non-response bias. [ABSTRACT FROM AUTHOR]

Objective The objective of this work was to develop a risk prediction model for opioid overdose and opioid use disorder for patients at first opioid prescription and compare the predictive accuracy of morphine equivalent total dosage with the predictive accuracy of daily dosage. Design Records from patients 18–79 years of age with opioid prescriptions between January 1, 2016, and June 30, 2019, no prior history of adverse outcomes, and no malignant cancer diagnoses were collected from the electronic health record system of a medium-sized central Ohio health care system (n = 219,276). A Cox proportional-hazards model was developed to predict the adverse outcomes of opioid overdose and opioid use disorder from patient sociodemographic, pharmacological, and clinical diagnosis factors. Results During the study time frame, 573 patients experienced overdoses, and 2,571 patients were diagnosed with opioid use disorder. Morphine equivalent total dosage of opioid prescriptions was identified as a stronger predictor of adverse outcomes (C  = 0.797) than morphine equivalent daily dosage (C  = 0.792), with the best predictions coming from a model that includes both predictors (C  = 0.803). In the model with both daily and total dosage predictors, patients receiving a high total / low daily dosage experienced a higher risk (hazard ratio [HR] = 2.17) than those receiving a low total / high daily dosage (HR = 2.02). Those receiving a high total / high daily dosage experienced the greatest risk of all (HR = 3.09). Conclusions These findings demonstrate the value of including morphine equivalent total dosage as a predictor of adverse opioid outcomes and suggest that total dosage may be more strongly correlated with increased risk than daily dosage. [ABSTRACT FROM AUTHOR]

Overdose prescription errors sometimes cause serious life-threatening adverse drug events, while underdose errors lead to diminished therapeutic effects. Therefore, it is important to detect and prevent these errors. In the present study, we used the one-class support vector machine (OCSVM), one of the most common unsupervised machine learning algorithms for anomaly detection, to identify overdose and underdose prescriptions. We extracted prescription data from electronic health records in Kyushu University Hospital between January 1, 2014 and December 31, 2019. We constructed an OCSVM model for each of the 21 candidate drugs using three features: age, weight, and dose. Clinical overdose and underdose prescriptions, which were identified and rectified by pharmacists before administration, were collected. Synthetic overdose and underdose prescriptions were created using the maximum and minimum doses, defined by drug labels or the UpToDate database. We applied these prescription data to the OCSVM model and evaluated its detection performance. We also performed comparative analysis with other unsupervised outlier detection algorithms (local outlier factor, isolation forest, and robust covariance). Twenty-seven out of 31 clinical overdose and underdose prescriptions (87.1%) were detected as abnormal by the model. The constructed OCSVM models showed high performance for detecting synthetic overdose prescriptions (precision 0.986, recall 0.964, and F-measure 0.973) and synthetic underdose prescriptions (precision 0.980, recall 0.794, and F-measure 0.839). In comparative analysis, OCSVM showed the best performance. Our models detected the majority of clinical overdose and underdose prescriptions and demonstrated high performance in synthetic data analysis. OCSVM models, constructed using features such as age, weight, and dose, are useful for detecting overdose and underdose prescriptions. [ABSTRACT FROM AUTHOR]

Background: The incidence of atrial fibrillation (AF) is increasing, and effective anticoagulation therapy can prevent adverse events. Selecting the appropriate OAC based on patient characteristics has become a challenge. Interventions are going to be a potential area of focus. Objectives: To explore the discrepancies between clinician prescriptions and recommended guidelines of oral anticoagulants (OACs) for patients with atrial fibrillation (AF), and to provide direction for improving anticoagulation strategies for treating patients with AF. Materials and methods: Data were collected from the electronic medical record system of Fuwai Yunnan Cardiovascular Hospital between July 2019 and January 2020. The suitability of prescribed OACs for patients with AF was assessed according to the Rules for Avoiding Prescription Inappropriateness, the prescribed medicine label, and any relevant antithrombotic guidelines for treating patients with AF. Results: A total of 460 patients met the inclusion criteria. Of these, 53.7% received an appropriate prescription and 46.3% received an inappropriate prescription. Of the patients who received inappropriate prescriptions, 15.4% were prescribed without the presenting appropriate indicators, 1.3% were prescribed inappropriate drug selection, and 29.6% were prescribed inappropriate drug doses. For patients prescribed without providing appropriate indicators, 2.2% had no indication for medication and 13.3% had an indication for medication, but not a specific OAC. For patients with inappropriate drug selection, 1, 5 patients were on rivaroxaban, dabigatran respectively. The distribution of NOAC doses was as follows: dabigatran standard dose (45.2%), the low dose (54.8%). Rivaroxaban standard dose (58.9%), low dose (36.8%), high dose (4.3%). A total of 44 patients (9.6%) experienced bleeding events, 12 patients (2.6%) experienced embolic events, and 7 patients experienced other adverse events after dosing. Conclusions: In clinical practice, it is common for patients with AF to receive inappropriate prescriptions of OACs. Therefore there is a need to enhance anticoagulation management in patients with AF to improve the appropriate use of OACs. [ABSTRACT FROM AUTHOR]

Background: Prescription opioids (POs) are commonly used to treat moderate to severe chronic pain in the health system setting. Although they improve quality of life for many patients, more work is needed to identify both the clinical and genetic factors that put certain individuals at high risk for developing opioid use disorder (OUD) following use of POs for pain relief. With a greater understanding of important risk factors, physicians will be better able to identify patients at highest risk for developing OUD for whom non-opioid alternative therapies and treatments should be considered. Methods: We are conducting a prospective observational study that aims to identify the clinical and genetic factors most stongly associated with OUD. The study design leverages an existing biobank that includes whole exome sequencing and array genotyping. The biobank is maintained within an integrated health system, allowing for the large-scale capture and integration of genetic and non-genetic data. Participants are enrolled into the health system biobank via informed consent and then into a second study that focuses on opioid medication use. Data capture includes validated self-report surveys measuring addiction severity, depression, anxiety, and nicotine use, as well as additional clinical, prescription, and brain imaging data extracted from electronic health records. Discussion: We will harness this multimodal data capture to establish meaningful patient phenotypes in order to understand the genetic and non-genetic contributions to OUD. [ABSTRACT FROM AUTHOR]

Background: The USA is in the midst of an opioid overdose epidemic. To address the epidemic, we conducted a large-scale population study on opioid overdose. Objectives: The primary objective of this study was to evaluate the temporal trends and risk factors of inpatient opioid overdose. Based on its patterns, the secondary objective was to examine the innate properties of opioid analgesics underlying reduced overdose effects. Methods: A retrospective cross-sectional study was conducted based on a large-scale inpatient electronic health records database, Cerner Health Facts®, with (1) inclusion criteria for participants as patients admitted between 1 January, 2009 and 31 December, 2017 and (2) measurements as opioid overdose prevalence by year, demographics, and prescription opioid exposures. Results: A total of 4,720,041 patients with 7,339,480 inpatient encounters were retrieved from Cerner Health Facts®. Among them, 30.2% patients were aged 65+ years, 57.0% female, 70.1% Caucasian, 42.3% single, 32.0% from the South, and 80.8% in an urban area. From 2009 to 2017, annual opioid overdose prevalence per 1000 patients significantly increased from 3.7 to 11.9 with an adjusted odds ratio (aOR): 1.16, 95% confidence interval (CI) 1.15–1.16. Compared to the major demographic counterparts, being in (1) age group: 41–50 years (overall aOR 1.36, 95% CI 1.31–1.40) or 51–64 years (overall aOR 1.35, 95% CI 1.32–1.39), (2) marital status: divorced (overall aOR 1.19, 95% CI 1.15–1.23), and (3) census region: West (overall aOR 1.32, 95% CI 1.28–1.36) were significantly associated with a higher odds of opioid overdose. Prescription opioid exposures were also associated with an increased odds of opioid overdose, such as meperidine (overall aOR 1.09, 95% CI 1.06–1.13) and tramadol (overall aOR 2.20, 95% CI 2.14–2.27). Examination on the relationships between opioid analgesic properties and their association strengths, aORs, and opioid overdose showed that lower aOR values were significantly associated with (1) high molecular weight, (2) non-interaction with multi-drug resistance protein 1 or interaction with cytochrome P450 3A4, and (3) non-interaction with the delta opioid receptor or kappa opioid receptor. Conclusions: The significant increasing trends of opioid overdose at the inpatient care setting from 2009 to 2017 suggested an ongoing need for efforts to combat the opioid overdose epidemic in the USA. Risk factors associated with opioid overdose included patient demographics and prescription opioid exposures. Moreover, there are physicochemical, pharmacokinetic, and pharmacodynamic properties underlying reduced overdose effects, which can be utilized to develop better opioids. [ABSTRACT FROM AUTHOR]

Objective: To evaluate a Produce Prescription Programme’s utilisation and its effects on healthy food purchasing and diabetes control among participants with type 2 diabetes.Design: Prospective cohort study using participants’ electronic health records and food transaction data. Participants were categorised as ‘Frequent Spenders’ and ‘Sometimes Spenders’ based on utilisation frequency. Multivariate regressions assessed utilisation predictors and programme effects on fruit/vegetable purchasing (spending, expenditure share and variety) and on diabetes-related outcomes (HbA1c, BMI and blood pressure).Setting: Patients enrolled by clinics in Durham, North Carolina, USA. Participants received $40 monthly for fruits and vegetables at a grocery store chain.Participants: A total of 699 food-insecure participants (353 with diabetes).Results: Being female and older was associated with higher programme utilisation; hospitalisations were negatively associated with programme utilisation. Frequent Spender status was associated with $8·77 more in fruit/vegetable spending (P < 0·001), 3·3 % increase in expenditure share (P = 0·007) and variety increase of 2·52 fruits and vegetables (P < 0·001). For $10 of Produce Prescription Dollars spent, there was an $8·00 increase in fruit/vegetable spending (P < 0·001), 4·1 % increase in expenditure share and variety increase of 2·3 fruits/vegetables (P < 0·001). For the 353 participants with diabetes, there were no statistically significant relationships between programme utilisation and diabetes control.Conclusions: Programme utilisation was associated with healthier food purchasing, but the relatively short study period and modest intervention prevent making conclusions about health outcomes. Produce Prescription Programmes can increase healthy food purchasing among food-insecure people, which may improve chronic disease care. [ABSTRACT FROM AUTHOR]

Background: In response to the opioid epidemic, many states have enacted policies limiting opioid prescriptions. There is a paucity of evidence of the impact of opioid prescribing interventions in primary care populations, including whether unintended consequences arise from limiting the availability of prescribed opioids. Objective: Our aim was to compare changes in opioid overdose and related adverse effects rate among primary care patients following the implementation of state-level prescribing policies. Design: A cohort of primary care patients within an interrupted time series model. Participants: Electronic medical record data for 62,776 adult (18+ years) primary care patients from a major medical center in Vermont from January 1, 2016, to June 30, 2018. Interventions: State-level opioid prescription policy changes limiting dose and duration. Main Measures: Changes in (1) opioid overdose rate and (2) opioid-related adverse effects rate per 100,000 person-months following the July 1, 2017, prescription policy change. Key Results: Among primary care patients, there was no change in opioid overdose rate following implementation of the prescribing policy (incidence rate ratio; IRR: 0.64, 95% confidence interval; CI: 0.22–1.88). There was a 78% decrease in the opioid-related adverse effects rate following the prescribing policy (IRR: 0.22, 95%CI: 0.09–0.51). This association was moderated by opioid prescription history, with decreases observed among opioid-naïve patients (IRR: 0.18, 95%CI: 0.06–0.59) and among patients receiving chronic opioid prescriptions (IRR: 0.17, 95%CI: 0.03–0.99), but not among those with intermittent opioid prescriptions (IRR: 0.51, 95%CI: 0.09–2.82). Conclusions: Limiting prescription opioids did not change the opioid overdose rate among primary care patients, but it reduced the rate of opioid-related adverse effects in the year following the state-level policy change, particularly among patients with chronic opioid prescription history and opioid-naïve patients. Limiting the quantity and duration of opioid prescriptions may have beneficial effects among primary care patients. [ABSTRACT FROM AUTHOR]

Background: The objective of this study was to determine primary prescription adherence for obstructive lung diseases (e.g., asthma, COPD) in an adult primary care patient population over a 3-year period. Methods: A retrospective analysis of electronic medical record and administrative data was performed to determine primary adherence, defined as dispensation of a new prescription within 90 days of the date the prescription was written. Multivariable logistic regression models were used to test predictors of prescription primary adherence. Results: Of 13,220 prescriptions for obstructive airway disease, 75.9% (N = 10,038) were filled. In multivariate analysis, depression, certain age groups (18–44 years), higher income quartile were associated with reduced prescription adherence. However, 1–2 ER visits in the previous year (compared to no ER visits), number of ambulatory visits in the previous year, and number of hospitalizations in the previous year, did not increase the likelihood of prescription adherence. Interpretation: This study provides important insights about factors associated with prescription nonadherence and is the first study examining primary medication adherence with medications for obstructive lung disease in adults, providing indications of prescription nonadherence patterns among a broad population. [ABSTRACT FROM AUTHOR]

Introduction Deaths have increased, and prescription medications are involved in a significant percentage of deaths. Emergency department (ED) changes to managing acute pain and prescription drug monitoring programs (PDMPs) can impact the potential for abuse. Methods We analyzed the impact of a series of quality improvement initiatives on the opioid prescribing habits of emergency department physicians and advanced practice providers. We compared historical prescribing patterns with those after three interventions: 1) the implementation of a PDMP, 2) clinician education on alternatives to opioids (ALTOs), and 3) electronic health record (EHR) process changes. Results There was a 61.8% decrease in the percentage of opioid-eligible ED discharges that received a prescription for an opioid from 19.4% during the baseline period to 7.4% during the final intervention period. Among these discharges, the cumulative effect of the interventions resulted in a 17.3% decrease in the amount of morphine milligram equivalents (MME) prescribed per discharge from a mean of 104.9 MME/discharge during the baseline period to 86.8 MME/discharge. In addition, the average amount of MME prescribed per discharge became aligned with recommended guidelines over the intervention periods. Conclusions Initiating a PDMP and instituting an aggressive ALTO program along with EHR-modified process flows have cumulative benefits in decreasing MME prescribed in an acute ED setting. [ABSTRACT FROM AUTHOR]

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

Psychoactive medications are the most expensive and fastest-growing class of pharmaceutical agents for children. The cost, side effects, and unprecedented growth rate at which these drugs are prescribed have raised alarms from health care clinicians, patient advocates, and agencies about the appropriateness of how these drugs are distributed to parents and their children. This article examines current prescribing of three classes of psychoactive drugs-stimulants, antidepressants, and antipsychotics-and efforts to improve pediatric prescribing of these agents. Federal policy efforts to curb questionable prescribing of psychoactive medications to children have focused particularly on oversight of antipsychotic use among foster care children. The article reviews system-level interventions, including delivery system enhancements, which increase availability of alternatives to medication treatments, employ electronic medical record reminders, and increase cross-sector care coordination; clinician prescribing enhancements, which disseminate best-practice guidelines, create quality and learning collaboratives, and offer "second opinion" psychiatric consultations; and prescriber monitoring programs, which include retrospective review and prospective monitoring of physicians' prescribing to identify patterns suggestive of inappropriate prescribing. Potential interventions to deter inappropriate pediatric prescribing are briefly described, such as transparency in drug prices and incentives among insurers, public agencies, and pharmacy benefit managers; value-based purchasing, specifically value-based payment for medications; and preventive interventions, such as parent training. [ABSTRACT FROM AUTHOR]

Objectives Assessment of the quality of patient-reported medical information in the Dutch Biologic Monitor and evaluation of the representativeness of the sampled participants. Methods Consecutive adult patients using a biologic DMARD (bDMARD) for an immune-mediated inflammatory disease were included in eight Dutch centres. For this substudy, data of 550 patients with inflammatory rheumatic diseases were used. Patient-reported bDMARD prescription, indication and combination therapy were verified for patients that permitted access to their electronic health record using percentage agreement and/or Cohen's kappa (n = 483). Conservative post hoc sensitivity analysis was performed to account for missing data. Population representativeness was tested for the entire substudy population by comparing age, gender and prescribed bDMARD to the centres' reference populations using Mann–Whitney U -test, χ2 goodness-of-fit or Fisher's exact test with Monte Carlo simulation (n = 550). Results The correct bDMARD was reported by 95.8% of the participants. Agreement between patients and electronic health record was almost perfect for indications (κ = 0.832) and substantial for combination therapies (κ = 0.725). Agreement on combination therapies remained substantial after post hoc sensitivity analysis (κ = 0.640). Gender distribution (P > 0.05) and bDMARD use (P > 0.05) were similar to the reference populations. Median age was different (58.0 vs 56.0 years, P = 0.04), but considered clinically irrelevant. Conclusion The Dutch Biologic Monitor seems to be a valid tool to obtain patient-reported medical information. Reported medical information generally corresponded to the electronic health records and the participants represented their reference populations regarding age, gender and prescribed bDMARD. [ABSTRACT FROM AUTHOR]