Type of infertility and prevalence of congenital malformations.

BACKGROUND: Children conceived with assisted reproductive technologies (ART) or after a long waiting time have a higher prevalence of congenital malformations, but few studies have examined the contribution of type of infertility. OBJECTIVES: To quantify the association between causes of infertility and prevalence of malformations. METHODS: We compared the prevalence at birth of all and severe malformations diagnosed up to age 2 between 6656 children born in 1996-2017 to parents who had previously been assessed for infertility a an academic fertility clinic ("exposed") and 10,382 children born in the same period to parents with no recent medical history of infertility ("reference"). We estimated prevalence ratios (PR) and prevalence differences (PD), by infertility status, type of treatment (non-ART, ART), and infertility diagnosis, in all children and among singletons. RESULTS: Compared with children of parents with no infertility, children of parents with infertility had a higher prevalence of malformations (both definitions), particularly following ART conceptions. After accounting for treatment, ovulatory disorders were associated with a higher prevalence of both all (PR 1.49, 95% confidence interval (CI) 1.15, 1.93; PD 3.8, 95% CI 1.0, 6.6) and severe (PR 1.53, 95% CI 1.02, 2.29; PD 1.8, 95% CI -0.2, 3.7) malformations (the estimates refer to exposed children conceived without treatment). Unexplained and male factor infertility were associated with all and severe malformations, respectively. Estimates among singletons were similar. A diagnosis of ovulatory disorders was associated with all malformations also in analyses restricted to exposed children, regardless of treatment (we did not examine severe malformations, due to limited power). CONCLUSIONS: In this study, ovulatory disorders were consistently associated with a higher prevalence of congenital malformations (including severe malformations) among live births, regardless of mode of conception.

Comparison of Different Modeling Approaches for Prescription Opioid Use and Its Association With Adverse Events.

Previous research linking opioid prescribing to adverse drug events has failed to properly account for the time-varying nature of opioid exposure. This study aimed to explore how the risk of opioid-related emergency department visits, readmissions, or deaths (composite outcome) varies with opioid dose and duration, comparing different novel modeling techniques. A prospective cohort of 1,511 hospitalized patients discharged from 2 McGill-affiliated hospitals in Montreal, 2014-2016, was followed from the first postdischarge opioid dispensation until 1 year after discharge. Marginal structural Cox proportional hazards models and their flexible extensions were used to explore the association between time-varying opioid use and the composite outcome. Weighted cumulative exposure models assessed cumulative effects of past use and explored how its impact depends on the recency of exposure. The patient mean age was 69.6 (standard deviation = 14.9) years; 57.7% were male. In marginal structural model analyses, current opioid use was associated with a 71% increase in the hazard of opioid-related adverse events (adjusted hazard ratio = 1.71, 95% confidence interval: 1.21, 2.43). The weighted cumulative exposure results suggested that the risk cumulates over the previous 50 days of opioid consumption. Flexible modeling techniques helped assess how the risk of opioid-related adverse events may be associated with time-varying opioid exposures while accounting for nonlinear relationships and the recency of past use.

Clinical competence, communication ability and adherence to choosing wisely recommendations for lipid reducing drug use in older adults.

BACKGROUND: Although lipid-lowering drugs are not recommended for primary prevention in patients 75+, prevalence of use is high and there is unexplained variation in prescribing between physicians. The objective of this study was to determine if physician communication ability and clinical competence are associated with prescribing lipid-lowering drugs for primary and secondary prevention. METHODS: We used a cohort of 4,501 international medical graduates, 161,214 U.S. Medicare patients with hyperlipidemia (primary prevention) and 49,780 patients with a history of cardiovascular disease (secondary prevention) not treated with lipid-lowering therapy who were seen by study physicians in ambulatory care. Clinical competence and communication ability were measured by the ECFMG clinical assessment examination. Physician citizenship, age, gender, specialty and patient characteristics were also measured. The outcome was an incident prescription of lipid-lowering drug, evaluated using multivariable GEE logistic regression models for primary and secondary prevention for patients 75+ and 65-74. RESULTS: Patients 75+ were less likely than those 65-74 to receive lipid-lowering drugs for primary (OR 0.62, 95% CI 0.59-0.66) and secondary (OR 0.70, 95% CI 0.63-0.78) prevention. For every 20% increase in clinical competence score, the odds of prescribing therapy for primary prevention to patients 75+ increased by 24% (95% CI 1.02-1.5). Communication ability had the opposite effect, reducing the odds of prescribing for primary prevention by 11% per 20% score increase (95% CI 0.8-0.99) for both age groups. Physicians who were citizens of countries with higher proportions of Hispanic (South/Central America) or Asian (Asia/Oceania) people were more likely to prescribe treatment for primary prevention, and internal medicine specialists were more likely to treat for secondary prevention than primary care physicians. CONCLUSION: Clinical competence, communication ability and physician citizenship are associated with lipid-lowering drug prescribing for primary prevention in patients aged 75+.

Predictors of frequent emergency department visits among hospitalized cancer patients: a comparative cohort study using integrated clinical and administrative data to improve care delivery.

BACKGROUND: Frequent emergency department (FED) visits by cancer patients represent a significant burden to the health system. This study identified determinants of FED in recently hospitalized cancer patients, with a particular focus on opioid use. METHODS: A prospective cohort discharged from surgical/medical units of the McGill University Health Centre was assembled. The outcome was FED use (≥ 4 ED visits) within one year of discharge. Data retrieved from the universal health insurance system was analyzed using Cox Proportional Hazards (PH) model, adopting the Lunn-McNeil approach for competing risk of death. RESULTS: Of 1253 patients, 14.5% became FED users. FED use was associated with chemotherapy one-year pre-admission (adjusted hazard ratio (aHR) 2.60, 95% CI: 1.80-3.70), ≥1 ED visit in the previous year (aHR: 1.80, 95% CI 1.20-2.80), ≥15 pre-admission ambulatory visits (aHR 1.54, 95% CI 1.06-2.34), previous opioid and benzodiazepine use (aHR: 1.40, 95% CI: 1.10-1.90 and aHR: 1.70, 95% CI: 1.10-2.40), Charlson Comorbidity Index ≥ 3 (aHR: 2.0, 95% CI: 1.2-3.4), diabetes (aHR: 1.60, 95% CI: 1.10-2.20), heart disease (aHR: 1.50, 95% CI: 1.10-2.20) and lung cancer (aHR: 1.70, 95% CI: 1.10-2.40). Surgery (cardiac (aHR: 0.33, 95% CI: 0.16-0.66), gastrointestinal (aHR: 0.34, 95% CI: 0.14-0.82) and thoracic (aHR: 0.45, 95% CI: 0.30-0.67) led to a decreased risk of FED use. CONCLUSIONS: Cancer patients with higher co-morbidity, frequent use of the healthcare system, and opioid use were at increased risk of FED use. High-risk patients should be flagged for preventive intervention.

Do clinical and communication skills scores on credentialing exams predict potentially inappropriate antibiotic prescribing?

BACKGROUND: There is considerable variation among physicians in inappropriate antibiotic prescribing, which is hypothesized to be attributable to diagnostic uncertainty and ineffective communication. The objective of this study was to evaluate whether clinical and communication skills are associated with antibiotic prescribing for upper respiratory infections and sinusitis. METHODS: A cohort study of 2,526 international medical graduates and 48,394 U.S. Medicare patients diagnosed by study physicians with an upper respiratory infection or sinusitis between July 2014 and November 2015 was conducted. Clinical and communication skills were measured by scores achieved on the Clinical Skills Assessment examination administered by the Educational Commission for Foreign Medical Graduates (ECFMG) as a requirement for entry into U.S residency programs. Medicare Part D data were used to determine whether patients were dispensed an antibiotic following an outpatient evaluation and management visit with the study physician. Physician age, sex, specialty and practice region were retrieved from the ECFMG databased and American Medical Association (AMA) Masterfile. Multivariate GEE logistic regression was used to evaluate the association between clinical and communication skills and antibiotic prescribing, adjusting for other physician and patient characteristics. RESULTS: Physicians prescribed an antibiotic in 71.1% of encounters in which a patient was diagnosed with sinusitis, and 50.5% of encounters for upper respiratory infections. Better interpersonal skills scores were associated with a significant reduction in the odds of antibiotic prescribing (OR per score decile 0.93, 95% CI 0.87-0.99), while greater proficiency in clinical skills and English proficiency were not. Female physicians, those practicing internal medicine compared to family medicine, those with citizenship from the US compared to all other countries, and those practicing in southern of the US were also more likely to prescribe potentially unnecessary antibiotics. CONCLUSIONS: Based on this study, physicians with better interpersonal skills are less likely to prescribe antibiotics for acute sinusitis and upper respiratory infections. Future research should examine whether tailored interpersonal skills training to help physicians manage patient expectations for antibiotics could reduce unnecessary antibiotic prescribing.

The influence of regulation of medically assisted reproduction on the risk of hospitalization in the first 2 years of life.

STUDY QUESTION: Do publicly funded fertility treatment and single embryo transfer (SET) result in lower hospitalization rates of children of parents with infertility? SUMMARY ANSWER: Following the 2010 Quebec law introducing free fertility treatment and SET, neonatal intensive care unit (NICU) admissions decreased among all children born to parents with infertility, but not among singletons, whose risk remained slightly higher than that of children of parents without infertility, even accounting for treatment and maternal age. WHAT IS KNOWN ALREADY: Previous studies reported lower NICU admission rates among children conceived with ART after the 2010 law; however, children conceived without ART by parents with infertility were not considered. STUDY DESIGN, SIZE, DURATION: Cohort study of children born in 1997-2017 to patients evaluated for infertility ('exposed') at an academic fertility center in Montreal (Canada) in 1996-2015. A random sample of births to Montreal residents served as comparison. Outcomes were identified from Quebec administrative databases. PARTICIPANTS/MATERIALS, SETTING, METHODS: We compared children's healthcare utilization before and after the 2010 law in 6273 exposed and 12 583 randomly sampled births (6846 and 12 775 children, respectively). We repeated the analysis among children conceived in the 63 months before and after the law ('restricted period'), and examined whether differences in twinning, fertility treatment, and maternal age explained the higher risk of NICU admission among children of parents with infertility. MAIN RESULTS AND THE ROLE OF CHANCE: In the exposed cohort, the proportion of twin births and of several adverse outcomes declined after the law. NICU admission and duration of NICU stay decreased overall, but not in singletons. Both measures remained higher in exposed children. Except for NICU admission, hospitalization rates were similar in exposed and random sample children. After accounting for fertility treatment and maternal age, exposed singletons were 17% more likely to be admitted to the NICU than children of parents with no medical history of infertility. LIMITATIONS, REASONS FOR CAUTION: Sample size was relatively small; infertile patients were from a single center and the random sample from one city. Despite some limitations, administrative databases are likely to accurately reflect healthcare utilization. WIDER IMPLICATIONS OF THE FINDINGS: Universal access to treatment and, particularly, SET results in an overall reduction of adverse outcomes among children conceived with treatment; however, children of parents with infertility are at a slightly higher risk, regardless of treatment. STUDY FUNDING/COMPETING INTEREST(S): This study was funded by the Canadian Institutes for Health Research (CIHR, grant no. 123362). No competing interests. TRIAL REGISTRATION NUMBER: N/A.

Association of Antidepressant Prescription Filling With Treatment Indication and Prior Prescription Filling Behaviors and Medication Experiences.

BACKGROUND: Given the wide range of uses for antidepressants, understanding indication-specific patterns of prescription filling for antidepressants provide valuable insights into how patients use these medications in real-world settings. OBJECTIVE: The objective of this study was to determine the association of antidepressant prescription filling with treatment indication, as well as prior prescription filling behaviors and medication experiences. DESIGN: This retrospective cohort study took place in Quebec, Canada. PARTICIPANTS: Adults with public drug insurance prescribed antidepressants using MOXXI (Medical Office of the XXIst Century)-an electronic prescribing system requiring primary care physicians to document treatment indications and reasons for prescription stops or changes. MEASURES: MOXXI provided information on treatment indications, past prescriptions, and prior medication experiences (treatment ineffectiveness and adverse drug reactions). Linked claims data provided information on dispensed medications and other patient-related factors. Multivariable logistic regression models estimated the independent association of not filling an antidepressant prescription (within 90 d) with treatment indication and patients' prior prescription filling behaviors and medication experiences. RESULTS: Among 38,751 prescriptions, the prevalence of unfilled prescriptions for new and ongoing antidepressant therapy was 34.2% and 4.1%, respectively. Compared with depression, odds of not filling an antidepressant prescription varied from 0.74 to 1.57 by indication and therapy status. The odds of not filling an antidepressant prescription was higher among adults filling < 50% of their medication prescriptions in the past year and adults with an antidepressant prescription stopped or changed in the past year due to treatment ineffectiveness. CONCLUSION: Antidepressant prescription filling behaviors differed by treatment indication and were lower among patients with a history of poor prescription filling or ineffective treatment with antidepressants.

Opioid prescribing among new users for non-cancer pain in the USA, Canada, UK, and Taiwan: A population-based cohort study.

BACKGROUND: The opioid epidemic in North America has been driven by an increase in the use and potency of prescription opioids, with ensuing excessive opioid-related deaths. Internationally, there are lower rates of opioid-related mortality, possibly because of differences in prescribing and health system policies. Our aim was to compare opioid prescribing rates in patients without cancer, across 5 centers in 4 countries. In addition, we evaluated differences in the type, strength, and starting dose of medication and whether these characteristics changed over time. METHODS AND FINDINGS: We conducted a retrospective multicenter cohort study of adults who are new users of opioids without prior cancer. Electronic health records and administrative health records from Boston (United States), Quebec and Alberta (Canada), United Kingdom, and Taiwan were used to identify patients between 2006 and 2015. Standard dosages in morphine milligram equivalents (MMEs) were calculated according to The Centers for Disease Control and Prevention. Age- and sex-standardized opioid prescribing rates were calculated for each jurisdiction. Of the 2,542,890 patients included, 44,690 were from Boston (US), 1,420,136 Alberta, 26,871 Quebec (Canada), 1,012,939 UK, and 38,254 Taiwan. The highest standardized opioid prescribing rates in 2014 were observed in Alberta at 66/1,000 persons compared to 52, 51, and 18/1,000 in the UK, US, and Quebec, respectively. The median MME/day (IQR) at initiation was highest in Boston at 38 (20 to 45); followed by Quebec, 27 (18 to 43); Alberta, 23 (9 to 38); UK, 12 (7 to 20); and Taiwan, 8 (4 to 11). Oxycodone was the first prescribed opioid in 65% of patients in the US cohort compared to 14% in Quebec, 4% in Alberta, 0.1% in the UK, and none in Taiwan. One of the limitations was that data were not available from all centers for the entirety of the 10-year period. CONCLUSIONS: In this study, we observed substantial differences in opioid prescribing practices for non-cancer pain between jurisdictions. The preference to start patients on higher MME/day and more potent opioids in North America may be a contributing cause to the opioid epidemic.

Postoperative duration of opioid use and acute healthcare services use in cancer patients hospitalized for thoracic surgery.

BACKGROUND: Postoperative pain control is an important cancer care component. However, opioid consumption has resulted in a surge of adverse events, with thoracic surgery patients having the highest rate of persistent use. The effect of opioid duration post-discharge and the risk of increased acute healthcare use in this population remains unclear. METHODS: A prospective cohort of non-metastatic cancer patients was assembled from an academic health center in Montreal (Canada). Clinical data linked to administrative claims from the universal healthcare program was used to determine the association between time-varying opioid patterns and emergency department (ED) visits/re-admissions/death 3 months following thoracic surgery. RESULTS: Of the 610 patients, 77% had at least one opioid dispensed post-discharge. Compared to non-opioid users, <15 days of use was associated with a 42% decreased risk of acute healthcare events, adjusted HR 0.58, 95% CI (0.40-0.85); longer durations were not associated with an increased risk. Compared to short-term use (<15 days), use of >30 days was associated with a 72% increased risk of the outcome, aHR: 1.72, 95% CI (1.01-2.93). CONCLUSION: There was a variation in the risk of acute healthcare use associated with postsurgical opioid use. Findings from this study may be used to inform postoperative prescribing practices.

Incidence and Variables Associated With Inconsistencies in Opioid Prescribing at Hospital Discharge and Its Associated Adverse Drug Outcomes.

OBJECTIVES: Opioid-related medication errors (MEs) can have a significant impact on patient health and contribute to opioid misuse. The objective of this study was to estimate the incidence of and variables associated with the receipt of an opioid prescription and opioid-related MEs (omissions, duplications, or dose changes) at hospital discharge. We also determined rates of adverse drug events and risks of emergency department visits, readmissions, or death 30 days and 90 days post discharge associated with MEs. METHODS: A cohort of hospitalized patients discharged from the McGill University Health Centre between 2014 and 2016 was assembled. The impact of opioid-related MEs was assessed in a propensity score-adjusted logistic regression models. Multivariable logistic regression was used to determine characteristics associated with MEs and discharge opioid prescription. RESULTS: A total of 1530 (43.9%) of 3486 patients were prescribed opioids, of which 13.4% (n = 205) of patients had at least 1 opioid-related ME. Rates of MEs were higher in handwritten prescriptions compared to the electronic reconciliation discharge prescription group (20.6% vs 1.2%). Computer-based prescriptions were associated with a 69% lower risk of opioid-related MEs (adjusted odds ratio: 0.31, 95% confidence interval: 0.14-0.65) as well as 63% lower risk of receiving an opioid prescription. Opioid-related MEs were associated with a 2.3 times increased risk of healthcare utilization in the 30 days postdischarge period (adjusted odds ratio: 2.32, 95% confidence interval: 1.24-4.32). CONCLUSIONS: Opioid-related MEs are common in handwritten discharge prescriptions. Our findings highlight the need for computer-based prescribing platforms and careful review of medications during critical periods of care such as hospital transitions.

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

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

Can Hyperparameter Tuning Improve the Performance of a Super Learner?: A Case Study.

BACKGROUND: Super learning is an ensemble machine learning approach used increasingly as an alternative to classical prediction techniques. When implementing super learning, however, not tuning the hyperparameters of the algorithms in it may adversely affect the performance of the super learner. METHODS: In this case study, we used data from a Canadian electronic prescribing system to predict when primary care physicians prescribed antidepressants for indications other than depression. The analysis included 73,576 antidepressant prescriptions and 373 candidate predictors. We derived two super learners: one using tuned hyperparameter values for each machine learning algorithm identified through an iterative grid search procedure and the other using the default values. We compared the performance of the tuned super learner to that of the super learner using default values ("untuned") and a carefully constructed logistic regression model from a previous analysis. RESULTS: The tuned super learner had a scaled Brier score (R) of 0.322 (95% [confidence interval] CI = 0.267, 0.362). In comparison, the untuned super learner had a scaled Brier score of 0.309 (95% CI = 0.256, 0.353), corresponding to an efficiency loss of 4% (relative efficiency 0.96; 95% CI = 0.93, 0.99). The previously-derived logistic regression model had a scaled Brier score of 0.307 (95% CI = 0.245, 0.360), corresponding to an efficiency loss of 5% relative to the tuned super learner (relative efficiency 0.95; 95% CI = 0.88, 1.01). CONCLUSIONS: In this case study, hyperparameter tuning produced a super learner that performed slightly better than an untuned super learner. Tuning the hyperparameters of individual algorithms in a super learner may help optimize performance.

Ability to Predict New-Onset Psychological Distress Using Routinely Collected Health Data: A Population-Based Cohort Study of Women Diagnosed With Breast Cancer.

Objectives: The primary objective of this study was to identify the predictors of new-onset psychological distress available in routinely collected administrative health databases for women diagnosed with breast cancer. The secondary objective was to explore whether the predictors vary based on the period of cancer care. Methods: A population-based cohort study followed 16,495 female patients with newly diagnosed breast cancer who did not experience psychological distress during the 14 months before breast cancer surgery. The incidence of psychological distress was reported overall and by type of mental health problem. Time-varying Cox proportional hazards models were developed to identify predictors of new-onset psychological distress during 2 key periods of cancer care: (1) hospital-based treatment during which women undergo treatment with breast surgery, chemotherapy, and/or radiation, and (2) 1-year transitional survivorship when women begin follow-up care. Results: The incidence of psychological distress was 16% within each period. Anxiety was present in 85.1% and 65.5% of new cases during hospital-based treatment and transitional survivorship, respectively. Predictors during both periods were younger age, receipt of axillary lymph node dissection, rheumatologic disease, and baseline menopausal symptoms, as well as new opioid dispensations, emergency department visits, and hospital contacts that occurred during follow-up. Other predictors varied based on the period of cancer care. More advanced breast cancer and type of treatment were associated with onset of psychological distress during hospital-based treatment. Psychological distress during transitional survivorship was predicted by diagnosis of localized breast disease, shorter duration of hospital-based treatment, receipt of additional hospital-based treatment in survivorship, and newly diagnosed comorbidities or symptoms. Conclusions: This study identified the predictors of new-onset psychological distress available in routinely collected administrative health databases, and showed how predictors change between hospital-based treatment and transitional survivorship periods. The results highlight the importance of developing predictive models tailored to the period of cancer care.

Assessment of potential bias in research grant peer review in Canada.

BACKGROUND: Peer review is used to determine what research is funded and published, yet little is known about its effectiveness, and it is suspected that there may be biases. We investigated the variability of peer review and factors influencing ratings of grant applications. METHODS: We evaluated all grant applications submitted to the Canadian Institutes of Health Research between 2012 and 2014. The contribution of application, principal applicant and reviewer characteristics to overall application score was assessed after adjusting for the applicant's scientific productivity. RESULTS: Among 11 624 applications, 66.2% of principal applicants were male and 64.1% were in a basic science domain. We found a significant nonlinear association between scientific productivity and final application score that differed by applicant gender and scientific domain, with higher scores associated with past funding success and h-index and lower scores associated with female applicants and those in the applied sciences. Significantly lower application scores were also associated with applicants who were older, evaluated by female reviewers only (v. male reviewers only, -0.05 points, 95% confidence interval [CI] -0.08 to -0.02) or reviewers in scientific domains different from the applicant's (-0.07 points, 95% CI -0.11 to -0.03). Significantly higher application scores were also associated with reviewer agreement in application score (0.23 points, 95% CI 0.20 to 0.26), the existence of reviewer conflicts (0.09 points, 95% CI 0.07 to 0.11), larger budget requests (0.01 points per $100 000, 95% CI 0.007 to 0.02), and resubmissions (0.15 points, 95% CI 0.14 to 0.17). In addition, reviewers with high expertise were more likely than those with less expertise to provide higher scores to applicants with higher past success rates (0.18 points, 95% CI 0.08 to 0.28). INTERPRETATION: There is evidence of bias in peer review of operating grants that is of sufficient magnitude to change application scores from fundable to nonfundable. This should be addressed by training and policy changes in research funding.

Assessing the accuracy of using diagnostic codes from administrative data to infer antidepressant treatment indications: a validation study.

PURPOSE: To assess the accuracy of using diagnostic codes from administrative data to infer treatment indications for antidepressants prescribed in primary care. METHODS: Validation study of administrative diagnostic codes for 13 plausible indications for antidepressants compared with physician-documented treatment indications from an indication-based electronic prescribing system in Quebec, Canada. The analysis included all antidepressant prescriptions written by primary care physicians between January 1, 2003 and December 31, 2012 using the electronic prescribing system. Patient prescribed antidepressants were linked to physician claims and hospitalization data to obtain all diagnoses recorded in the past year. RESULTS: Diagnostic codes had poor sensitivity for all treatment indications, ranging from a high of only 31.2% (95% CI, 26.8%-35.9%) for anxiety/stress disorders to as low as 1.3% (95% CI, 0.0%-5.2%) for sexual dysfunction. Sensitivity was notably worse among older patients and patients with more chronic comorbidities. Physician claims data were a better source of diagnostic codes for antidepressant treatment indications than hospitalization data. CONCLUSIONS: Administrative diagnostic codes are poor proxies for antidepressant treatment indications. Future work should determine whether the use of other variables in administrative data besides diagnostic codes can improve the ability to predict antidepressant treatment indications.

Assumptions made when preparing drug exposure data for analysis have an impact on results: An unreported step in pharmacoepidemiology studies.

PURPOSE: Real-world data for observational research commonly require formatting and cleaning prior to analysis. Data preparation steps are rarely reported adequately and are likely to vary between research groups. Variation in methodology could potentially affect study outcomes. This study aimed to develop a framework to define and document drug data preparation and to examine the impact of different assumptions on results. METHODS: An algorithm for processing prescription data was developed and tested using data from the Clinical Practice Research Datalink (CPRD). The impact of varying assumptions was examined by estimating the association between 2 exemplar medications (oral hypoglycaemic drugs and glucocorticoids) and cardiovascular events after preparing multiple datasets derived from the same source prescription data. Each dataset was analysed using Cox proportional hazards modelling. RESULTS: The algorithm included 10 decision nodes and 54 possible unique assumptions. Over 11 000 possible pathways through the algorithm were identified. In both exemplar studies, similar hazard ratios and standard errors were found for the majority of pathways; however, certain assumptions had a greater influence on results. For example, in the hypoglycaemic analysis, choosing a different variable to define prescription end date altered the hazard ratios (95% confidence intervals) from 1.77 (1.56-2.00) to 2.83 (1.59-5.04). CONCLUSIONS: The framework offers a transparent and efficient way to perform and report drug data preparation steps. Assumptions made during data preparation can impact the results of analyses. Improving transparency regarding drug data preparation would increase the repeatability, reproducibility, and comparability of published results.

Effect of a Pharmacist-Led Educational Intervention on Inappropriate Medication Prescriptions in Older Adults: The D-PRESCRIBE Randomized Clinical Trial.

Importance: High rates of inappropriate prescribing persist among older adults in many outpatient settings, increasing the risk of adverse drug events and drug-related hospitalizations. Objective: To compare the effectiveness of a consumer-targeted, pharmacist-led educational intervention vs usual care on discontinuation of inappropriate medication among community-dwelling older adults. Design, Setting, and Participants: A cluster randomized trial (D-PRESCRIBE [Developing Pharmacist-Led Research to Educate and Sensitize Community Residents to the Inappropriate Prescriptions Burden in the Elderly]) that recruited community pharmacies in Quebec, Canada, from February 2014 to September 2017, with follow-up until February 2018, and randomly allocated them to intervention or control groups. Patients included were adults aged 65 years and older who were prescribed 1 of 4 Beers Criteria medications (sedative-hypnotics, first-generation antihistamines, glyburide, or nonsteroidal anti-inflammatory drugs), recruited from 69 community pharmacies. Patients were screened and enrolled before randomization. Interventions: Pharmacists in the intervention group were encouraged to send patients an educational deprescribing brochure in parallel to sending their physicians an evidence-based pharmaceutical opinion to recommend deprescribing. The pharmacists in the control group provided usual care. Randomization occurred at the pharmacy level, with 34 pharmacies randomized to the intervention group (248 patients) and 35 to the control group (241 patients). Patients, physicians, pharmacists, and evaluators were blinded to outcome assessment. Main Outcomes and Measures: Discontinuation of prescriptions for inappropriate medication at 6 months, ascertained by pharmacy medication renewal profiles. Results: Among 489 patients (mean age, 75 years; 66% women), 437 (89%) completed the trial (219 [88%] in the intervention group vs 218 [91%] in the control group). At 6 months, 106 of 248 patients (43%) in the intervention group no longer filled prescriptions for inappropriate medication compared with 29 of 241 (12%) in the control group (risk difference, 31% [95% CI, 23% to 38%]). In the intervention vs control group, discontinuation of inappropriate medication occurred among 63 of 146 sedative-hypnotic drug users (43.2%) vs 14 of 155 (9.0%), respectively (risk difference, 34% [95% CI, 25% to 43%]); 19 of 62 glyburide users (30.6%) vs 8 of 58 (13.8%), respectively (risk difference, 17% [95% CI, 2% to 31%]); and 19 of 33 nonsteroidal anti-inflammatory drug users (57.6%) vs 5 of 23 (21.7%), respectively (risk difference, 35% [95% CI, 10% to 55%]) (P for interaction = .09). Analysis of the antihistamine drug class was not possible because of the small sample size (n = 12). No adverse events requiring hospitalization were reported, although 29 of 77 patients (38%) who attempted to taper sedative-hypnotics reported withdrawal symptoms. Conclusions and Relevance: Among older adults in Quebec, a pharmacist-led educational intervention compared with usual care resulted in greater discontinuation of prescriptions for inappropriate medication after 6 months. The generalizability of these findings to other settings requires further research. Trial Registration: ClinicalTrials.gov Identifier: NCT02053194.

Predictors of distress in female breast cancer survivors: a systematic review.

PURPOSE: Unmanaged distress has been shown to adversely affect survival and quality of life in breast cancer survivors. Fortunately, distress can be managed and even prevented with appropriate evidence-based interventions. Therefore, the objective of this systematic review was to synthesize the published literature around predictors of distress in female breast cancer survivors to help guide targeted intervention to prevent distress. METHODS: Relevant studies were located by searching MEDLINE, Embase, PsycINFO, and CINAHL databases. Significance and directionality of associations for commonly assessed candidate predictors (n ≥ 5) and predictors shown to be significant (p ≤ 0.05) by at least two studies were summarized descriptively. Predictors were evaluated based on the proportion of studies that showed a significant and positive association with the presence of distress. RESULTS: Forty-two studies met the target criteria and were included in the review. Breast cancer and treatment-related predictors were more advanced cancer at diagnosis, treatment with chemotherapy, longer primary treatment duration, more recent transition into survivorship, and breast cancer recurrence. Manageable treatment-related symptoms associated with distress included menopausal/vasomotor symptoms, pain, fatigue, and sleep disturbance. Sociodemographic characteristics that increased the risk of distress were younger age, non-Caucasian ethnicity, being unmarried, and lower socioeconomic status. Comorbidities, history of mental health problems, and perceived functioning limitations were also associated. Modifiable predictors of distress were lower physical activity, lower social support, and cigarette smoking. CONCLUSIONS: This review established a set of evidence-based predictors that can be used to help identify women at higher risk of experiencing distress following completion of primary breast cancer treatment.

Validation of Diagnostic Groups Based on Health Care Utilization Data Should Adjust for Sampling Strategy.

OBJECTIVE: Valid measurement of outcomes such as disease prevalence using health care utilization data is fundamental to the implementation of a "learning health system." Definitions of such outcomes can be complex, based on multiple diagnostic codes. The literature on validating such data demonstrates a lack of awareness of the need for a stratified sampling design and corresponding statistical methods. We propose a method for validating the measurement of diagnostic groups that have: (1) different prevalences of diagnostic codes within the group; and (2) low prevalence. METHODS: We describe an estimation method whereby: (1) low-prevalence diagnostic codes are oversampled, and the positive predictive value (PPV) of the diagnostic group is estimated as a weighted average of the PPV of each diagnostic code; and (2) claims that fall within a low-prevalence diagnostic group are oversampled relative to claims that are not, and bias-adjusted estimators of sensitivity and specificity are generated. APPLICATION: We illustrate our proposed method using an example from population health surveillance in which diagnostic groups are applied to physician claims to identify cases of acute respiratory illness. CONCLUSIONS: Failure to account for the prevalence of each diagnostic code within a diagnostic group leads to the underestimation of the PPV, because low-prevalence diagnostic codes are more likely to be false positives. Failure to adjust for oversampling of claims that fall within the low-prevalence diagnostic group relative to those that do not leads to the overestimation of sensitivity and underestimation of specificity.