Publications

OBJECTIVE: To conduct a contemporary detailed assessment of outpatient antibiotic prescribing and outcomes for positive urine cultures in a mixed-sex cohort.

DESIGN: Multicenter retrospective cohort review.

SETTING: The study was conducted using data from 31 Veterans' Affairs medical centers.

PATIENTS: Outpatient adults with positive urine cultures.

METHODS: From 2016 to 2019, data were extracted through a nationwide database and manual chart review. Positive urine cultures were reviewed at the chart, clinician, and aggregate levels. Cases were classified as cystitis, pyelonephritis, or asymptomatic bacteriuria (ASB) based upon documented signs and symptoms. Preferred therapy definitions were applied for subdiagnoses: ASB (no antibiotics), cystitis (trimethoprim-sulfamethoxazole, nitrofurantoin, β-lactams), and pyelonephritis (trimethoprim-sulfamethoxazole, fluoroquinolone). Outcomes included 30-day clinical failure or hospitalization. Odds ratios for outcomes between treatments were estimated using logistic regression.

RESULTS: Of 3,255 cases reviewed, ASB was identified in 1,628 cases (50%), cystitis was identified in 1,156 cases (36%), and pyelonephritis was identified in 471 cases (15%). Of all 2,831 cases, 1,298 (46%) received preferred therapy selection and duration for cases where it could be defined. The most common antibiotic class prescribed was a fluoroquinolone (34%). Patients prescribed preferred therapy had lower odds of clinical failure: preferred (8%) versus nonpreferred (10%) (unadjusted OR, 0.74; 95% confidence interval [CI], 0.58-0.95; P = .018). They also had lower odds of 30-day hospitalization: preferred therapy (3%) versus nonpreferred therapy (5%) (unadjusted OR, 0.55; 95% CI, 0.37-0.81; P = .002). Odds of clinical treatment failure or hospitalization was higher for β-lactams relative to ciprofloxacin (unadjusted OR, 1.89; 95% CI, 1.23-2.90; P = .002).

CONCLUSIONS: Clinicians prescribed preferred therapy 46% of the time. Those prescribed preferred therapy had lower odds of clinical failure and of being hospitalized.

OBJECTIVE: To compare clinical outcomes associated with appropriate and inappropriate management of asymptomatic bacteriuria (ASB) and urinary tract infection (UTI) among inpatients with neurogenic bladder (NB).

DESIGN: Multicenter, retrospective cohort.

SETTING: The study was conducted across 4 Veterans' Affairs hospitals.

PARTICIPANTS: The study included veterans with NB due to spinal cord injury or disorder (SCI/D), multiple sclerosis (MS), or Parkinson's disease (PD) hospitalized between January 1, 2017, and December 31, 2018, with diagnosis of ASB or UTI.

INTERVENTIONS: In a medical record review, we classified ASB and UTI diagnoses and treatments as appropriate or inappropriate based on national guidelines.

MAIN OUTCOME MEASURES: Frequencies of Clostridioides difficile infection, acute kidney injury, 90-day hospital readmission, postculture length-of-stay (LOS), and multidrug-resistant organisms in subsequent urine cultures were compared between those who received appropriate and inappropriate management.

RESULTS: We included 170 encounters with ASB (30%) or UTI (70%) diagnoses occurring for 166 patients. Overall, 86.1% patients were male, 47.6% had SCI/D and 77.6% used bladder catheters. All ASB encounters had appropriate diagnoses, and 96.1% had appropriate treatment. In contrast, 37 UTI encounters (31.1%) had inappropriate diagnoses and 61 (51.3%) had inappropriate treatment, including 30 encounters with true ASB. Among patients with SCI/D or MS, appropriate ASB or UTI diagnosis was associated with a longer postculture LOS (median, 14 vs 7.5 days; P = .02). We did not detect any significant associations between appropriate versus inappropriate diagnosis and treatment and other outcomes.

CONCLUSIONS: Almost one-third of UTI diagnoses and half of treatments in hospitalized patients with NB are inappropriate. Opportunities exist to improve ASB and UTI management in patients with NB to minimize inappropriate antibiotic use.

BACKGROUND: Use of SGLT2 inhibitors (SGLT2i) and GLP-1 receptor agonists (GLP1-RA) among older adults with type 2 diabetes (T2D) has been limited.

OBJECTIVE: To examine factors associated with initiation of an SGLT2i or GLP-1RA among Medicare beneficiaries with T2D in the early years after their market approval, with a particular focus on formulary restrictions (e.g. prior authorization, step therapy requirements, higher co-pays).

METHODS: A retrospective cohort study using data from a 5% random sample of Medicare beneficiaries with T2D followed from 1/1/2015-12/31/16. Formulary restrictiveness was defined as: (1) the number of target drugs (i.e. SGLT2is or GLP1-RAs) included in tiers 1-3 of a beneficiary's formulary (greater number of drugs in tiers 1-3 being less restrictive) and (2) the number of drugs without prior authorization or step therapy (requirement to try less expensive drugs prior to "stepping up" to more expensive therapies). We used multivariable logistic regression models to estimate the association between measures of formulary restrictiveness and initiation of a target drug, controlling for patient demographics, diabetes duration, clinical comorbidities, and provider specialty.

RESULTS: Among 112,985 beneficiaries with T2D, 5,619 (5%) initiated an SGLT2i or GLP1-RA. After adjusting for baseline characteristics, patients enrolled in formularies with ≥ 2 target drugs available in tiers 1-3 had 17% higher odds of initiating an SGLT2i or GLP1-RA (aOR 1.17, 95% CI 1.05-1.31) compared to patients enrolled in formularies with 0 drugs available in tiers 1-3. There was no significant association between the number of drugs without prior authorization or step therapy requirements and initiation of a target drug (aOR 0.96, 95% CI, 0.85-1.09). Age 75 years or older (vs < 65, aOR 0.23, 95% CI 0.21-0.26) and black race (vs white, aOR 0.65, 95% CI 0.59-0.71) were associated with lower odds of initiating a target drug.

CONCLUSIONS: Having a greater number of target drugs available on less expensive formulary tiers is associated with increased odds of initiating an SGLT2i or GLP-1RA among Medicare beneficiaries with T2D.

BACKGROUND: Racial and ethnic disparities in anticoagulation exist in atrial fibrillation management in Medicare and the Veterans Health Administration, but the influence of dual Veterans Health Administration and Medicare enrollment is unclear. We compared anticoagulant initiation by race and ethnicity in dually enrolled patients and assessed the role of Medicare part D enrollment on anticoagulation disparities.

METHODS: We identified patients with incident atrial fibrillation (2014-2018) dually enrolled in Veterans Health Administration and Medicare. We assessed any anticoagulant initiation (warfarin or direct-acting oral anticoagulants [DOACs]) within 90 days of atrial fibrillation diagnosis and DOAC use among anticoagulant initiators. We modeled anticoagulant initiation, adjusting for patient, provider, and facility factors, including main effects for race and ethnicity and Medicare part D enrollment and an interaction term for these variables.

RESULTS: In 43 789 patients, 8.9% were Black, 3.6% Hispanic, and 87.5% White; 10.9% participated in Medicare part D. Overall, 29 680 (67.8%) patients initiated any anticoagulant, of whom 17 568 (59.2%) initiated DOACs. Lower proportions of Black (65.2%) than Hispanic (67.6%) or White (68.0%) patients initiated any anticoagulant (P=0.001) and, lower proportions of Black (56.3%) and Hispanic (55.9%) than White (59.6%) patients (P=0.001) initiated DOACs. Compared with White patients, Black patients had significantly lower initiation of any anticoagulant (adjusted odds ratio, 0.89 [95% CI, 0.82-0.97]). The adjusted odds ratios for DOAC initiation were significantly lower for Black (0.72 [95% CI, 0.65-0.81]) and Hispanic (0.84 [95% CI, 0.70-1.00]) than White patients. The interaction between race and ethnicity and Medicare part D enrollment was nonsignificant for any anticoagulant (P=0.99) and DOAC (P=0.27) therapies.

CONCLUSIONS: In dually enrolled Veterans Health Administration and Medicare patients with atrial fibrillation, Black patients were less likely to initiate any anticoagulant, and Black and Hispanic patients were less likely to initiate DOACs. Medicare part D enrollment did not moderate the associations between race and ethnicity and anticoagulant therapies.

BACKGROUND: Newer glucose-lowering drugs, including sodium glucose co-transporter 2 inhibitors (SGLT2i) and GLP-1 agonists, have a key role in the pharmacologic management of type 2 diabetes. No studies have measured primary nonadherence for these two drug classes, defined as when a medication is prescribed for a patient but ultimately not dispensed to them.

OBJECTIVE: To describe the incidence and predictors of primary nonadherence to SGLT2i (canagliflozin, empagliflozin) or GLP-1 agonists (dulaglutide, liraglutide, semaglutide) using a dataset that links electronic prescribing with health insurance claims.

DESIGN AND PARTICIPANTS: A retrospective cohort design using data of adult patients from a large health system who had at least one prescription order for a SGLT2i or GLP-1 agonist between 2012 and 2019. We used mixed-effects multivariable logistic regression to determine associations between sociodemographic, clinical, and provider variables and primary nonadherence.

MAIN MEASURES: Primary medication nonadherence, defined as no dispensed claim within 30 days of an electronic prescription order for any drug within each medication class.

KEY RESULTS: The cohort included 5146 patients newly prescribed a SGLT2i or GLP-1 agonist. The overall incidence of 30-day primary medication nonadherence was 31.8% (1637/5146). This incidence rate was 29.8% (n = 726) and 33.6% (n = 911) among those initiating a GLP-1 agonist and SGLT2i, respectively. Age ≥ 65 (aOR 1.37 (95% CI 1.09 to 1.72)), Black race vs White (aOR 1.29 (95% CI 1.02 to 1.62)), diabetic nephropathy (aOR 1.31 (95% CI 1.02 to 1.68)), and hyperlipidemia (aOR 1.18 (95% CI 1.01 to 1.39)) were associated with a higher odds of primary nonadherence. Female sex (aOR 0.86 (95% CI 0.75 to 0.99)), peripheral artery disease (aOR 0.73 (95% CI 0.56 to 0.94)), and having the index prescription ordered by an endocrinologist vs a primary care provider (aOR 0.76 (95% CI 0.61 to 0.95)) were associated with lower odds of primary nonadherence.

CONCLUSIONS: One third of patients prescribed SGLT2i or GLP-1 agonists in this sample did not fill their prescription within 30 days. Black race, male sex, older age, having greater baseline comorbidities, and having a primary care provider vs endocrinologist prescribe the index drug were associated with higher odds of primary nonadherence. Interventions targeting medication adherence for these newer drugs must consider primary nonadherence as a barrier to optimal clinical care.

OBJECTIVES: Limited information is available regarding provider- and patient panel-level factors associated with primary care provider (PCP) adoption/prescribing of medication for opioid use disorder (MOUD).

METHODS: We assessed a retrospective cohort from 2015 to 2018 within the Pennsylvania Medicaid Program. Participants included PCPs who were Medicaid providers, with no history of MOUD provision, and who treated ≥10 Medicaid enrollees annually. We assessed initial MOUD adoption, defined as an index buprenorphine/buprenorphine-naloxone or oral/extended release naltrexone fill and sustained prescribing, defined as ≥1 MOUD prescription(s) for 3 consecutive quarters from the PCP. Independent variables included provider- and patient panel-level characteristics.

RESULTS: We identified 113 rural and 782 urban PCPs who engaged in initial adoption and 36 rural and 288 urban PCPs who engaged in sustained prescribing. Rural/urban PCPs who issued increasingly larger numbers of antidepressant and antipsychotic medication prescriptions had greater odds of initial adoption and sustained prescribing (P < 0.05) compared to those that did not prescribe these medications. Further, each additional patient out of 100 with opioid use disorder diagnosed before MOUD adoption increased the adjusted odds for initial adoption 2% to 4% (95% confidence interval [CI] = 1.01-1.08) and sustained prescribing by 4% to 7% (95% CI = 1.01-1.08). New Medicaid providers in rural areas were 2.52 (95% CI = 1.04-6.11) and in urban areas were 2.66 (95% CI = 1.94, 3.64) more likely to engage in initial MOUD adoption compared to established PCPs.

CONCLUSIONS: MOUD prescribing adoption was concentrated among PCPs prescribing mental health medications, caring for those with OUD, and new Medicaid providers. These results should be leveraged to test/implement interventions targeting MOUD adoption among PCPs.

BACKGROUND AND AIMS: The time lag encountered when accessing health-care data is one major barrier to implementing opioid overdose prediction measures in practice. Little is known regarding how one's opioid overdose risk changes over time. We aimed to identify longitudinal patterns of individual predicted overdose risks among Medicaid beneficiaries after initiation of opioid prescriptions.

DESIGN, SETTING AND PARTICIPANTS: A retrospective cohort study in Pennsylvania, USA among Pennsylvania Medicaid beneficiaries aged 18-64 years who initiated opioid prescriptions between July 2017 and September 2018 (318 585 eligible beneficiaries (mean age = 39 ± 12 years, female = 65.7%, White = 62.2% and Black = 24.9%).

MEASUREMENTS: We first applied a previously developed and validated machine-learning algorithm to obtain risk scores for opioid overdose emergency room or hospital visits in 3-month intervals for each beneficiary who initiated opioid therapy, until disenrollment from Medicaid, death or the end of observation (December 2018). We performed group-based trajectory modeling to identify trajectories of these predicted overdose risk scores over time.

FINDINGS: Among eligible beneficiaries, 0.61% had one or more occurrences of opioid overdose in a median follow-up of 15 months. We identified five unique opioid overdose risk trajectories: three trajectories (accounting for 92% of the cohort) had consistent overdose risk over time, including consistent low-risk (63%), consistent medium-risk (25%) and consistent high-risk (4%) groups; another two trajectories (accounting for 8%) had overdose risks that substantially changed over time, including a group that transitioned from high- to medium-risk (3%) and another group that increased from medium- to high-risk over time (5%).

CONCLUSIONS: More than 90% of Medicaid beneficiaries in Pennsylvania USA with one or more opioid prescriptions had consistent, predicted opioid overdose risks over 15 months. Applying opioid prediction algorithms developed from historical data may not be a major barrier to implementation in practice for the large majority of individuals.

STUDY OBJECTIVE: High prescribers of antibiotics and opioids are an important target for stewardship interventions. The goal of this study was to assess the association between high antibiotic and high opioid prescribing by provider type.

DESIGN: A national cross-sectional study.

SETTING: 2015-2017 Department of Veterans Affairs (VA) electronic health record data.

POPULATION: Prescribers were identified as dentists (2017: n = 1346) and medical providers (physicians n = 23,072; advanced practice providers [APP] n = 7705; and other providers [pharmacists/chiropractors] n = 3674) (2017: n = 34,451).

MEASUREMENTS: High prescribing was defined as being in the top 25% of visit-based rates of antibiotic or opioid prescribing (number of prescriptions/number of dental or medical visits). Multivariable random effects logistic regression with clustering by facility was used to assess the adjusted association between high antibiotic and opioid prescribing.

RESULTS: Medical providers prescribed 4,348,670 antibiotic and 10,256,706 opioid prescriptions; dentists prescribed 277,170 antibiotic and 124,103 opioid prescriptions. Among all high prescribers of antibiotics, 40% were also high prescribers of opioids as compared to 18% of those who were not high antibiotic prescribers (p < 0.0001). High prescribing of antibiotics was associated with high prescribing of opioids in medical providers (adjusted odds ratio [aOR] = 2.87, 95% confidence interval [CI] = 2.72-3.04) and dentists (aOR = 8.40, 95% CI 6.00-11.76). Older provider age, specific US geographic regions, and lower VA facility complexity and rurality were also associated with high opioid prescribing by medical providers. In dentists, younger provider age, male gender, specific regions of the United States, and lower number of dentists in a facility were associated with high opioid prescribing. At the facility level, high dental prescribers of antibiotics or opioids were not at the same facilities as high medical prescribers, respectively (p < 0.0001).

CONCLUSIONS: High antibiotic prescribing was associated with high opioid prescribing. Thus, stewardship interventions targeting both medication classes may have higher impact to efficiently reduce prescribing of medications with high public health impact. Provider-targeted interventions are needed to improve antibiotic and opioid prescribing in both dentists and medical providers.

BACKGROUND: The drug supply chain is global and at risk of disruption and subsequent drug shortages, especially during unanticipated events.

OBJECTIVE: Our objective was to determine the impact of coronavirus disease 2019 (COVID-19) on drug purchases overall, by class, and for specific countries.

METHODS: A cross-sectional time series analysis of country-level drug purchase data from August 2014 to August 2020 from IQVIA MIDAS was conducted. Standardized units per 100 population and percentage increase in units purchased were assessed from 68 countries and jurisdictions in March 2020 (when the World Health Organization declared COVID-19 a pandemic). Analyses were compared by United Nations development status and drug class. Autoregressive integrated moving average models tested the significance of changes in purchasing trends.

RESULTS: Before COVID-19, standardized medication units per 100 population ranged from 3990 to 4760 monthly. In March 2020, there was a global 15% increase in units of drugs purchased to 5309.3 units per 100 population compared with the previous year; the increase was greater in developed countries (18.5%; P < 0.001) than in developing countries (12.8%; P < 0.0001). After the increase in March 2020, there was a correction in the global purchase rate decreasing by 4.7% (April to August 2020 rate, 21,334.6/100 population; P < 0.001). Globally, we observed high purchasing rates and large changes for respiratory medicines such as inhalers and systemic adrenergic drugs (March 2020 rate, 892.7/100 population; change from 2019, 28.5%; P < 0.001). Purchases for topical dermatologic products also increased substantially (42.2%), although at lower absolute rates (610.0/100 population in March 2020; P < 0.0001). Interestingly, purchases for systemic anti-infective agents (including antiviral drugs) increased in developing countries (11.3%; P < 0.001), but decreased in developed countries (1.0%; P = 0.06).

CONCLUSION: We observed evidence of global drug stockpiling in the early months of the COVID-19 pandemic, especially among developed countries. Actions toward equitable distribution of medicines through a resilient drug supply chain should be taken to increase global response to future unanticipated events, such as pandemics.