Publications

OBJECTIVES: To examine the association between statin use and objectively assessed decline in gait speed in community-dwelling older adults.

DESIGN: Longitudinal cohort study.

SETTING: Health, Aging and Body Composition (Health ABC) Study.

PARTICIPANTS: Two thousand five participants aged 70-79 at baseline with medication and gait speed data at 1998-99, 1999-2000, 2001-02, and 2002-03.

MEASUREMENTS: The independent variables were any statin use and their standardized daily doses (low, moderate, high) and lipophilicity. The primary outcome measure was decline in gait speed of 0.1 m/s or more in the following year of statin use. Multivariable generalized estimating equations were used, adjusting for demographic characteristics, health-related behaviors, health status, and access to health care.

RESULTS: Statin use increased from 16.2% in 1998-99 to 25.6% in 2002-03. The overall proportions of those with decline in gait speed of 0.1 m/s or more increased from 22.2% in 1998 to 23.9% in 2003. Statin use was not associated with decline in gait speed of 0.1 m/s or more (adjusted odds ratio (AOR) = 0.90, 95% confidence interval (CI) = 0.77-1.06). Similar nonsignificant trends were also seen with the use of hydrophilic or lipophilic statins. Users of low-dose statins were found to have a 22% lower risk of decline in gait speed than nonusers (AOR = 0.78, 95% CI = 0.61-0.99), which was mainly driven by the results from 1999-2000 follow-up.

CONCLUSION: These results suggest that statin use did not increase decline in gait speed in community-dwelling older adults.

OBJECTIVES: Use of buprenorphine - an effective treatment for opioid use disorders (OUDs) - has increased rapidly in recent years and is often financed by Medicaid. We investigated predictors of buprenorphine treatment, patterns of care, and quality of care in a large state Medicaid program.

METHODS: Data from Pennsylvania Medicaid from 2007 to 2012 provided information regarding diagnoses, demographic characteristics, enrollment, and use of inpatient and outpatient services, and prescription drugs. We identified adult enrollees using buprenorphine, and examined prevalence of OUD diagnosis and patterns of use (duration and dose) and quality of care (physician visits, receipt of behavioral health counseling, urine drug screens, and other prescription drug use). We use a mixed logistic regression model to examine enrollee characteristics associated with buprenorphine use.

RESULTS: The share of enrollees with OUD filling prescriptions for buprenorphine increased from 2985 (9.8%) to 12,691 (25.2%) from 2007 to 2012. Between 26.2 and 32.0% of enrollees using buprenorphine had no diagnosis of OUD, depending on the year. Only 60.1% of enrollees with buprenorphine use received at least one urine drug screen, 41.0% had behavioral health counseling services, and 34.7 and 38.0% had other opioid and benzodiazepine claims, respectively, concomitant with buprenorphine use. Quality of care was lower among those with no OUD diagnosis recorded. The mean daily doses of buprenorphine decreased over time. We found wide variation in likelihood of buprenorphine use among those with OUD based upon age, sex, and race.

CONCLUSIONS: Increases in buprenorphine treatment in a Medicaid population were observed across time; however, increases varied by age, sex, and rate, and the quality of care received seemed to be generally poor. The quality of the provision of buprenorphine treatment occurring in Medicaid populations should be further explored.

BACKGROUND: Quality improvement efforts are frequently tied to patients achieving ≥80% medication adherence. However, there is little empirical evidence that this threshold optimally predicts important health outcomes.

OBJECTIVE: To apply machine learning to examine how adherence to oral hypoglycemic medications is associated with avoidance of hospitalizations, and to identify adherence thresholds for optimal discrimination of hospitalization risk.

METHODS: A retrospective cohort study of 33,130 non-dual-eligible Medicaid enrollees with type 2 diabetes. We randomly selected 90% of the cohort (training sample) to develop the prediction algorithm and used the remaining (testing sample) for validation. We applied random survival forests to identify predictors for hospitalization and fit survival trees to empirically derive adherence thresholds that best discriminate hospitalization risk, using the proportion of days covered (PDC).

OUTCOMES: Time to first all-cause and diabetes-related hospitalization.

RESULTS: The training and testing samples had similar characteristics (mean age, 48 y; 67% female; mean PDC=0.65). We identified 8 important predictors of all-cause hospitalizations (rank in order): prior hospitalizations/emergency department visit, number of prescriptions, diabetes complications, insulin use, PDC, number of prescribers, Elixhauser index, and eligibility category. The adherence thresholds most discriminating for risk of all-cause hospitalization varied from 46% to 94% according to patient health and medication complexity. PDC was not predictive of hospitalizations in the healthiest or most complex patient subgroups.

CONCLUSIONS: Adherence thresholds most discriminating of hospitalization risk were not uniformly 80%. Machine-learning approaches may be valuable to identify appropriate patient-specific adherence thresholds for measuring quality of care and targeting nonadherent patients for intervention.

BACKGROUND: Academic medical centers (AMCs) have increasingly adopted conflict of interest policies governing physician-industry relationships; it is unclear how policies impact prescribing.

OBJECTIVES: To determine whether 9 American Association of Medical Colleges (AAMC)-recommended policies influence psychiatrists' antipsychotic prescribing and compare prescribing between academic and nonacademic psychiatrists.

RESEARCH DESIGN: We measured number of prescriptions for 10 heavily promoted and 9 newly introduced/reformulated antipsychotics between 2008 and 2011 among 2464 academic psychiatrists at 101 AMCs and 11,201 nonacademic psychiatrists. We measured AMC compliance with 9 AAMC recommendations. Difference-in-difference analyses compared changes in antipsychotic prescribing between 2008 and 2011 among psychiatrists in AMCs compliant with ≥ 7/9 recommendations, those whose institutions had lesser compliance, and nonacademic psychiatrists.

RESULTS: Ten centers were AAMC compliant in 2008, 30 attained compliance by 2011, and 61 were never compliant. Share of prescriptions for heavily promoted antipsychotics was stable and comparable between academic and nonacademic psychiatrists (63.0%-65.8% in 2008 and 62.7%-64.4% in 2011). Psychiatrists in AAMC-compliant centers were slightly less likely to prescribe these antipsychotics compared with those in never-compliant centers (relative odds ratio, 0.95; 95% CI, 0.94-0.97; P < 0.0001). Share of prescriptions for new/reformulated antipsychotics grew from 5.3% in 2008 to 11.1% in 2011. Psychiatrists in AAMC-compliant centers actually increased prescribing of new/reformulated antipsychotics relative to those in never-compliant centers (relative odds ratio, 1.39; 95% CI, 1.35-1.44; P < 0.0001), a relative increase of 1.1% in probability.

CONCLUSIONS: Psychiatrists exposed to strict conflict of interest policies prescribed heavily promoted antipsychotics at rates similar to academic psychiatrists and nonacademic psychiatrists exposed to less strict or no policies.

BACKGROUND: Appropriate antibiotic prescribing is an essential strategy to reduce the spread of antibiotic resistance. US prescribing practices have not been thoroughly characterized. We analyzed outpatient antibiotic prescribing data to identify where appropriate antibiotic prescribing interventions could have the most impact.

METHODS: Oral antibiotic prescriptions dispensed during 2011 were extracted from the IMS Health Xponent database. The number of prescriptions and census denominators were used to calculate prescribing rates. Prescription totals were calculated for each provider specialty. Regression modeling was used to examine the association between socioeconomic and population health factors and prescribing rates.

RESULTS: Healthcare providers prescribed 262.5 million courses of antibiotics in 2011(842 prescriptions per 1000 persons). Penicillins and macrolides were the most common antibiotic categories prescribed. The most commonly prescribed individual antibiotic agent was azithromycin. Family practitioners prescribed the most antibiotic courses (24%). The prescribing rate was higher in the South census region (931 prescriptions per 1000 persons) than in the West (647 prescriptions per 1000 persons; P < .001); this pattern was observed among all age groups, including children ≤ 2 and persons ≥ 65 years of age. Counties with a high proportion of obese persons, infants and children ≤ 2 years of age, prescribers per capita, and females were more likely to be high prescribing by multivariable analysis (adjusted odds ratio, >1.0).

CONCLUSIONS: Efforts to characterize antibiotic prescribing practices should focus on the South census region and family practitioners. Further understanding of the factors leading to high prescribing among key target populations will inform appropriate prescribing interventions.

Interprofessional education and patient care have been endorsed by accrediting bodies because interprofessional health care teams improve outcomes while decreasing health care costs. Thus, there has been an increased focus in educating health professional students collectively. The purpose of this study was to investigate the frequency of interprofessional authorship of original research published in high-impact critical care journals. Physicians constituted 76.2% of authors, followed by 10.5% PhDs and 3.0% nonphysician health professionals. From 2001 to 2011, the frequency of physician and nonphysician authors increased significantly ( P < .01 for both). Interprofessional authorship also increased, from 49.9% to 64.3% of published articles ( P < .0001). The enhanced attention on interprofessional education and patient care has translated into an increase in interprofessional authorship for original research articles published in critical care journals. However, collaboration appears to be primarily between physicians and PhDs, not other health care professionals.

This practice forum reports experiences with the development of a unit-specific antibiogram and planning for its implementation. Involvement of internal and external facilitators was a key strategy for addressing issues, including data limitations, coordination, and planning. These activities were incorporated and reported as part of the facility's broader antimicrobial stewardship program, and represent the first step in a set of planned projects to evaluate the impact of antibiograms on provider behavior and patient outcomes.