Anupam B. Jena

Comparison of Hospital Mortality and Readmission Rates for Medicare Patients Treated by Male vs Female Physicians

Importance Studies have found differences in practice patterns between male and female physicians, with female physicians more likely to adhere to clinical guidelines and evidence-based practice. However, whether patient outcomes differ between male and female physicians is largely unknown. Objective To determine whether mortality and readmission rates differ between patients treated by male or female physicians. Design, Setting, and Participants We analyzed a 20% random sample of Medicare fee-for-service beneficiaries 65 years or older hospitalized with a medical condition and treated by general internists from January 1, 2011, to December 31, 2014. We examined the association between physician sex and 30-day mortality and readmission rates, adjusted for patient and physician characteristics and hospital fixed effects (effectively comparing female and male physicians within the same hospital). As a sensitivity analysis, we examined only physicians focusing on hospital care (hospitalists), among whom patients are plausibly quasi-randomized to physicians based on the physician’s specific work schedules. We also investigated whether differences in patient outcomes varied by specific condition or by underlying severity of illness. Main Outcomes and Measures Patients’ 30-day mortality and readmission rates. Results A total of 1 583 028 hospitalizations were used for analyses of 30-day mortality (mean [SD] patient age, 80.2 [8.5] years; 621 412 men and 961 616 women) and 1 540 797 were used for analyses of readmission (mean [SD] patient age, 80.1 [8.5] years; 602 115 men and 938 682 women). Patients treated by female physicians had lower 30-day mortality (adjusted mortality, 11.07% vs 11.49%; adjusted risk difference, –0.43%; 95% CI, –0.57% to –0.28%; P < .001; number needed to treat to prevent 1 death, 233) and lower 30-day readmissions (adjusted readmissions, 15.02% vs 15.57%; adjusted risk difference, –0.55%; 95% CI, –0.71% to –0.39%; P < .001; number needed to treat to prevent 1 readmission, 182) than patients cared for by male physicians, after accounting for potential confounders. Our findings were unaffected when restricting analyses to patients treated by hospitalists. Differences persisted across 8 common medical conditions and across patients’ severity of illness. Conclusions and Relevance Elderly hospitalized patients treated by female internists have lower mortality and readmissions compared with those cared for by male internists. These findings suggest that the differences in practice patterns between male and female physicians, as suggested in previous studies, may have important clinical implications for patient outcomes.

Prespecified Falsification End Points: Can They Validate True Observational Associations?

AS OBSERVATIONAL STUDIES HAVE INCREASED IN NUMber—fueled by a boom in electronic recordkeeping and the ease with which observational analyses of large databases can be performed—so too have failures to confirm initial research findings. Several solutions to the problem of incorrect observational results have been suggested, emphasizing the importance of a record not only of significant findings but of all analyses conducted. An important and increasingly familiar type of observational study is the identification of rare adverse effects (defined by organizations such as the Council for International Organizations and Medical Sciences as occurring among fewer than 1 per 1000 individuals) from population data. Examples of these studies include whether macrolide antibiotics such as azithromycin are associated with higher rates of sudden cardiac death; whether proton pump inhibitors (PPIs) are associated with higher rates of pneumonia; or whether bisphosphonates are associated with an increased risk of atypical (subtrochanteric) femur fractures. Rare adverse events, such as these examples, occur so infrequently that almost by definition they may not be identified in randomized controlled trials (RCTs). Postmarketing data from thousands of patients are required to identify such low-frequency events. In fact, the ability to conduct postmarketing surveillance of large databases has been heralded as a vital step in ensuring the safe dissemination of medical treatments after clinical trials (phase 4) for precisely this reason. Few dispute the importance of observational studies for capturing rare adverse events. For instance, in early studies of whether bisphosphonate use increases the rate of atypical femur fractures, pooled analysis of RCTs demonstrated no elevated risk. However, these data were based on a limited sample of 14 000 patients with only 284 hip or femur fractures and only 12 atypical fracture events over just more than 3.5 years of follow-up. In contrast, later observational studies addressing the same question were able to leverage much larger and more comprehensive data. One analysis that examined 205 466 women who took bisphosphonates for an average of 4 years identified more than 10 000 hip or femur fractures and 716 atypical fractures. This analysis demonstrated an increased risk of atypical fractures associated with bisphosphonate use and was validated by another large population-based study. However, analyses in large data sets are not necessarily correct simply because they are larger. Control groups might not eliminate potential confounders, or many varying definitions of exposure to the agent may be tested (alternative thresholds for dose or duration of a drug)—a form of multiple-hypothesis testing. Just as small, true signals can be identified by these analyses, so too can small, erroneous associations. For instance, several observational studies have found an association between use of PPIs and development of pneumonia, and it is biologically plausible that elevated gastric pH may engender bacterial colonization. However, it is also possible that even after statistical adjustment for known comorbid conditions, PPI users may have other unobserved health characteristics (such as poor health literacy or adherence) that could increase their rates of pneumonia, apart from use of the drug. Alternatively, physicians who are more likely to prescribe PPIs to their patients also may be more likely to diagnose their patients with pneumonia in the appropriate clinical setting. Both mechanisms would suggest that the observational association between PPI use and pneumonia is confounded. In light of the increasing prevalence of such studies and their importance in shaping clinical decisions, it is important to know that the associations identified are true rather than spurious correlations. Prespecified falsification hypotheses may provide an intuitive and useful safeguard when observational data are used to find rare harms. A falsification hypothesis is a claim, distinct from the one being tested, that researchers believe is highly unlikely to be causally related to the intervention in question. For instance, a falsification hypothesis may be that PPI use increases the rate of soft tissue infection or myocardial infarction. A confirmed falsification test—in this case, a positive association between PPI use and risks of these conditions—

Opioid-Prescribing Patterns of Emergency Physicians and Risk of Long-Term Use

BACKGROUND Increasing overuse of opioids in the United States may be driven in part by physician prescribing. However, the extent to which individual physicians vary in opioid prescribing and the implications of that variation for long‐term opioid use and adverse outcomes in patients are unknown. METHODS We performed a retrospective analysis involving Medicare beneficiaries who had an index emergency department visit in the period from 2008 through 2011 and had not received prescriptions for opioids within 6 months before that visit. After identifying the emergency physicians within a hospital who cared for the patients, we categorized the physicians as being high‐intensity or low‐intensity opioid prescribers according to relative quartiles of prescribing rates within the same hospital. We compared rates of long‐term opioid use, defined as 6 months of days supplied, in the 12 months after a visit to the emergency department among patients treated by high‐intensity or low‐intensity prescribers, with adjustment for patient characteristics. RESULTS Our sample consisted of 215,678 patients who received treatment from low‐intensity prescribers and 161,951 patients who received treatment from high‐intensity prescribers. Patient characteristics, including diagnoses in the emergency department, were similar in the two treatment groups. Within individual hospitals, rates of opioid prescribing varied widely between low‐intensity and high‐intensity prescribers (7.3% vs. 24.1%). Long‐term opioid use was significantly higher among patients treated by high‐intensity prescribers than among patients treated by low‐intensity prescribers (adjusted odds ratio, 1.30; 95% confidence interval, 1.23 to 1.37; P<0.001); these findings were consistent across multiple sensitivity analyses. CONCLUSIONS Wide variation in rates of opioid prescribing existed among physicians practicing within the same emergency department, and rates of long‐term opioid use were increased among patients who had not previously received opioids and received treatment from high‐intensity opioid prescribers. (Funded by the National Institutes of Health.)

Sex Differences in Physician Salary in US Public Medical Schools

IMPORTANCE Limited evidence exists on salary differences between male and female academic physicians, largely owing to difficulty obtaining data on salary and factors influencing salary. Existing studies have been limited by reliance on survey-based approaches to measuring sex differences in earnings, lack of contemporary data, small sample sizes, or limited geographic representation. OBJECTIVE To analyze sex differences in earnings among US academic physicians. DESIGN, SETTING, AND PARTICIPANTS Freedom of Information laws mandate release of salary information of public university employees in several states. In 12 states with salary information published online, salary data were extracted on 10 241 academic physicians at 24 public medical schools. These data were linked to a unique physician database with detailed information on sex, age, years of experience, faculty rank, specialty, scientific authorship, National Institutes of Health funding, clinical trial participation, and Medicare reimbursements (proxy for clinical revenue). Sex differences in salary were estimated after adjusting for these factors. EXPOSURES Physician sex. MAIN OUTCOMES AND MEASURES Annual salary. RESULTS Among 10 241 physicians, female physicians (n = 3549) had lower mean (SD) unadjusted salaries than male physicians (

Hospital Spending and Inpatient Mortality: Evidence From California: An Observational Study

206 641 [

Mandatory use of prescription drug monitoring programs.

88 238] vs

Sexually Transmitted Diseases Among Users of Erectile Dysfunction Drugs: Analysis of Claims Data

257 957 [

Cost-effectiveness analysis and innovation

137 202]; absolute difference,

On Average, Physicians Spend Nearly 11 Percent Of Their 40-Year Careers With An Open, Unresolved Malpractice Claim

51 315 [95% CI,

Presenteeism Among Resident Physicians

46 330-