Prescription Count Research Articles

Impact of Live Training on Medication Errors in a Community-Based Pharmacy Setting.

To compare community-based pharmacy medication errors before and after a one-hour live interactive training session for both pharmacists and technicians. A one group pre-post intervention design study was conducted in 20 community-based pharmacies in a district of a large national community pharmacy chain. A one-hour live, interactive session was developed based on incident reports and medication error trends including medication error definition, ways in which medication errors occur, strategies for mitigating errors, information about human error, and methods and habits to improve patient safety. At least 50% of full-time staff for each of the 20 pharmacies were required to attend a training session between December 1, 2017-January 15, 2018. Participants completed a demographics survey documenting gender, age, credentials, number of years of experience, and years of service with the company. Pharmacies were categorized as low, medium or high volume based on prescription count. Medication errors were compared six months pre- and post-live education session. Data were analyzed using SAS version 9.4. One hundred and thirty- five errors and 111 errors were reported pre-and post-live training (mean 6.85 and 5.55, p < 0.301), respectively. Nine pharmacies were low, eight medium, and three high volume with the mean number of medication errors reported pre- and post-live training; low 4.33 vs 4.11 p<0.478, medium 9.37 vs 6.87 p<0.443, and high 7.66 vs 6.33 p<0.593, respectively. Sixty pharmacy staff (34 pharmacists, 26 technicians) attended one of the live training sessions; 73% female; most frequently reported age range 35-50 years; 23 Doctor of Pharmacy, 11 Bachelor of Science in Pharmacy, and 26 Certified Technician; and average number of years' experience was 13.6 and average service with the company was 8.6 years. A live training session for both pharmacists and technicians did not significantly decrease medication errors, but could be incorporated as an element of a medication safety program. It should be considered for implementation in other districts of this large national pharmacy chain as a part of an improved patient safety effort.

Opioid Dependence Subsequent to Exposure to Prescription Opioids

To determine whether the length, dose, and/or frequency of opioid prescriptions correlates with the subsequent diagnosis of opioid use disorder (OUD) among Medicaid enrollees and if there are higher odds of developing opioid dependence after receiving opioid prescriptions for dental procedures versus medical procedures.Our design was a nested case‐control in a cohort of continuously enrolled, opioid‐naïve (no opioid prescription for 1 year before the first prescription of opioid) Medicaid enrollees with at least one opioid prescription between January 1, 2013, and December 31, 2017, in IBM Watson Health’s MarketScan Medicaid database. The cases were defined as enrollees with diagnosed opioid use disorder, and controls were drawn from the same population who were not diagnosed with OUD. They were matched (up to 1:2) by age, sex, race, baseline pain diagnosis, number of Elixhauser comorbidities, and similar exposure time for prescription opioids. Outcome variable was the diagnosis of OUD, and the predictor variables were cumulative length of opioid prescriptions, morphine milligram equivalent (MME) dose, and frequency of opioids. The correlation was explored through multivariate logistic regression, and the model was re‐adjusted for baseline matching characteristics.The study population is opioid‐naïve Medicaid enrollees with at least one opioid prescription between January 1, 2013, and December 31, 2017, in IBM Watson Health’s MarketScan Medicaid database.Among a matched cohort of 1051 cases and 2053 controls, odds of OUD increased significantly for prescription count of 2‐3 (OR = 1.3, CI = 1.1‐1.6), 4‐5 days (OR = 2.0, CI = 1.4‐2.8), and above 6 (OR = 5.1, CI = 3.3‐7.8), compared to one prescription. Odds of OUD increased significantly for cumulative prescription length of 31‐60 days (OR = 1.8, CI = 1.3‐2.3), 61‐90 days (OR = 2.9, CI = 1.5‐5.6), and above 91 days (OR = 10.1, CI = 5.0‐20.4), compared to 5 days or less. Odds of OUD for average prescription length of 16‐30 days (OR = 1.9, CI = 1.3‐2.5) were significantly more compared to 5 days or less. Odds of OUD increased significantly for cumulative MME dose of 120‐180 (OR = 1.7, CI = 1.2‐2.3), and for 180 and above (OR = 4.1, CI = 2.8‐5.8), compared less than or equal to 20. Odds of OUD for average MME dose of 91 and above (OR = 1.9, CI = 1.2‐3.0) were significantly more compared less than or equal to 20. Moreover, enrollees who received opioid prescription for dental procedure were less likely (OR = 0.5, CI = 0.4‐0.7) to develop OUD then who received prescriptions for medical procedures.The study concluded that when number of prescriptions, days supplied, and morphine milligram equivalent dose go up, the odds of developing OUD increases significantly. Therefore a quantitative association between prescription opioid exposure and subsequent dependence in established. Moreover, the odds of developing OUD are less for prescriptions received after dental procedures compared to medical procedures.The study informs the opioid prescribing and opioid‐prescribing guidelines for clinical practice.DentaQuest Partnership for Oral Health Advancement.

Dispensing patterns of emergency medicines prescribed by Australian dentists from 1992 to 2018 – a pharmacoepidemiology study

As the population ages, dentists are likely to encounter medical emergencies due to metabolic factors and polypharmacy. To date, there have been no documented studies in Australia that have analysed the prescription rate of Pharmaceutical Benefits Scheme (PBS)-funded emergency medicines for dentists. Therefore, this pharmacoepidemiology study aims to describe the dispensing patterns of emergency medicines as prescribed by dental practitioners, related to medicines covered by the Australian PBS system. Data on dental medications used for emergencies, under the PBS, from 1992 to 2018, were accessed. Cumulative dispensing counts were calculated. Data on medications that were not utilised were also collected in the form of the crude cumulative count. Out of the 56 medications on the dental PBS schedule, eight were utilised for medical emergencies, with a total of 432 prescriptions on a national level, over 27years. The commonly utilised lifesaving medicines of adrenaline, glucagon, as well as glyceryl trinitrate, had a total prescription count of 147, 88 and 27 respectively. Medicines used for opiate overdose; naloxone, had a total prescription count of one. Only one medicine (benztropine injection) for medical emergencies had a prescription count of 0. This study highlights the dispensing patterns of medicines prescribed by dentists for emergency scenarios. Although this study did not assess the appropriateness of use of the emergency medicines, further investigation may be required to ensure the future safety of patients when encountering emergency scenarios.

Outpatient Pharmacy Prescriptions During the First Year Following Serious Combat Injury: A Retrospective Analysis.

Limited research has analyzed the full range of outpatient medication prescription activity following serious combat injury. The objectives of this study were to describe (1) outpatient medication prescriptions and refills during the first 12months after serious combat injury, (2) longitudinal changes in medication prescriptions during the first-year postinjury, and (3) patient characteristics associated with outpatient prescriptions. This was a retrospective analysis of existing health and pharmacy data for a random sample of U.S. service members who sustained serious combat injuries in the Iraq and Afghanistan conflicts, 2010-2013 (n=381). Serious injury was defined by an Injury Severity Score (ISS) of 9 or greater. These patients typically participate in military rehabilitation programs (eg, amputation care) where prescription medications are essential. Data sources were the Expeditionary Medical Encounter Database for injury-specific data, the Pharmacy Data Transaction Service for outpatient medication prescriptions and refills, and the Military Health System Data Repository for diagnostic codes of pain and psychological disorders. Military trauma nurses reviewed casualty records to identify types of injuries. Using the American Hospital Formulary Service Pharmacologic-Therapeutic Classification system, clinicians identified 13 categories of prescription medications (eg, opioid, psychotherapeutic, immunologic) for analysis. Multivariable negative binomial and logistic regression analyses evaluated significant associations between independent variables (eg, blast injury, traumatic brain injury [TBI], ISS, limb amputation, diagnoses of chronic pain, or psychological disorders) and prescription measures (ie, number or category of medication prescriptions). We also describe longitudinal changes in prescription activity postinjury across consecutive quarterly intervals (91days) during the first-year postinjury. During the first-year postinjury, patients averaged 61 outpatient prescriptions, including all initial prescriptions and refills. They averaged eight different categories of medications, primarily opioid, immunologic, gastrointestinal/genitourinary, central nervous system (CNS), nonopioid analgesic, and psychotherapeutic medications (representing 82% of prescriptions) during the first year. Prescription activity generally declined across quarters. There was still substantial prescription activity during the fourth quarter, as 79% of patients had at least one prescription. From 39 to 49% of patients had fourth-quarter prescriptions for opioid, CNS, or psychotherapeutic medications. Longitudinally, we found that 24-34% of patients had an opioid, CNS, or psychotherapeutic prescription during each of the final three quarters. In multivariable analysis, ISS, limb amputation (particularly bilateral amputation), and diagnoses of chronic pain and post-traumatic stress disorder (PTSD) were associated with significantly higher counts of individual and multiple medication prescriptions. TBI was associated with significantly lower numbers of prescriptions for certain medications. This is one of the first studies to provide a systematic analysis of outpatient medication prescriptions following serious combat injury. The results indicate substantial prescription activity from multiple medication categories throughout the first-year postinjury. Diagnoses of chronic pain, PTSD, and limb amputation and ISS were associated with significantly higher counts of prescriptions overall and more prescription medication categories. This study provides initial evidence to better understand medication prescription activity following serious combat injury. The results inform future research on medication prescription practices and planning for rehabilitation.

Association between quality-of-care indicators for HIV infection and healthcare resource utilization and costs.

Multiple care quality indicators for HIV infection exist but few studies examine their impact on health outcomes. This study assessed which HIV care quality indicators were associated with healthcare resource utilization and costs. Retrospective analysis of Texas Medicaid claims data (01 January 2012 to 31 September 2016). Included patients had at least two HIV-related medical claims during the identification period (01 July 2012 to 31 August 2014) (index = date of first HIV claim), were 18-62 years at index, and were continuously enrolled in the 6-month pre-index and 1-year post-index periods. Dependent variables included emergency department (ED) visits, inpatient hospitalizations, prescription count, and all-cause healthcare costs. Independent variables included CD4 cell count monitoring, syphilis, chlamydia, gonorrhea, hepatitis B, hepatitis C, and tuberculosis screenings, influenza and pneumococcal vaccinations, retention in care, and HAART initiation. Covariates included age, chronic hepatitis C virus infection, AIDS diagnosis, sex, and baseline healthcare cost. The study objective was addressed using generalized linear modeling. CD4 cell count monitoring and HAART initiation were significantly associated with reduced emergency department visits (P < 0.0001 for each). Influenza vaccination was significantly associated with reduced inpatient hospitalization (P < 0.0001). CD4 cell count monitoring (P < 0.0001), TB screening (P = 0.0006), influenza vaccination (P < 0.0001), and HAART initiation (P < 0.0001) were significantly associated with increase prescription claims. CD4 cell count monitoring, TB screening, and HAART initiation (P < 0.0001 for each) were significantly associated with all-cause healthcare costs. HAART may reduce use of emergency care services as early as 1 year following initiation.

Spending on World Health Organization essential medicines in Medicare Part D, 2011-15: retrospective cost analysis

ObjectivesTo characterize the trends, drivers, and potential modifiers of increased spending by US Medicare beneficiaries on medicines deemed essential by the World Health Organization.DesignRetrospective cost analysis of Medicare Part D...

Use of a medication-based risk adjustment index to predict mortality among veterans dually-enrolled in VA and medicare

BackgroundThere is systemic undercoding of medical comorbidities within administrative claims in the Department of Veterans Affairs (VA). This leads to bias when applying claims-based risk adjustment indices to compare outcomes between VA and non-VA settings. Our objective was to compare the accuracy of a medication-based risk adjustment index (RxRisk-VM) to diagnostic claims-based indices for predicting mortality. MethodsWe modified the RxRisk-V index (RxRisk-VM) by incorporating VA and Medicare pharmacy and durable medical equipment claims in Veterans dually-enrolled in VA and Medicare in 2012. Using the concordance (C) statistic, we compared its accuracy in predicting 1 and 3-year all-cause mortality to the following models: demographics only, demographics plus prescription count, or demographics plus a diagnostic claims-based risk index (e.g., Charlson, Elixhauser, or Gagne). We also compared models containing demographics, RxRisk-VM, and a claims-based index. ResultsIn our cohort of 271,184 dually-enrolled Veterans (mean age = 70.5 years, 96.1% male, 81.7% non-Hispanic white), RxRisk-VM (C = 0.773) exhibited greater accuracy in predicting 1-year mortality than demographics only (C = 0.716) or prescription counts (C = 0.744), but was less accurate than the Charlson (C = 0.794), Elixhauser (C = 0.80), or Gagne (C = 0.810) indices (all P < 0.001). Combining RxRisk-VM with claims-based indices enhanced its accuracy over each index alone (all models C ≥ 0.81). Relative model performance was similar for 3-year mortality. ConclusionsThe RxRisk-VM index exhibited a high level of, but slightly less, accuracy in predicting mortality in comparison to claims-based risk indices. ImplicationsIts application may enhance the accuracy of studies examining VA and non-VA care and enable risk adjustment when diagnostic claims are not available or biased. Level of evidenceLevel 3.

Trends in Treatment and Spending for Patients Receiving Outpatient Treatment of Depression in the United States, 1998-2015

After marked increases from 1987 to 1997, trends in depression treatment in the United States increased modestly from 1998 to 2007. However, multiple policy changes that expanded insurance coverage for mental health conditions may have shifted these trends again since 2007. To examine national trends in outpatient treatment of depression from 1998 to 2015, with particular focus on 2007 to 2015. This analysis of the use of health services and spending for treatment of depression in the United States assessed data from the 1998 (n = 22 953), 2007 (n = 29 370), and 2015 (n = 33 893) Medical Expenditure Panel Surveys (MEPSs). Participants included respondent households to the nationally representative survey. Data were analyzed from June 15 through December 18, 2018. Rates of outpatient and pharmaceutical treatment of depression; counts of outpatient visits, psychotherapy visits, and prescriptions; and expenditures. The analysis included 86 216 individuals from the 1998, 2007, and 2015 MEPSs. Respondents' mean (SD) age was 37.2 (22.7) years; 45 086 (52.3%) were female, 24 312 (28.2%) were Hispanic, 15 463 (17.9%) were black, and 62 926 (72.9%) were white. Rates of outpatient treatment of depression increased from 2.36 (95% CI, 2.12-2.61) per 100 population in 1998 to 3.47 (95% CI, 3.16-3.79) per 100 population in 2015. The proportion of respondents who were treated for depression using psychotherapy decreased from 53.7% (95% CI, 48.3%-59.1%) in 1998 to 43.2% (95% CI, 39.0%-47.4%) in 2007 and then increased to 50.4% (95% CI, 46.0%-54.9%) in 2015, whereas the proportion receiving pharmacotherapy remained steady at 81.9% (95% CI, 77.9%-85.9%) in 1998, 82.4% (95% CI, 79.3%-85.4%) in 2007, and 80.8% (95% CI, 77.9%-83.7%) in 2015. After adjusting for inflation using 2015 US dollars, prescription expenditures for these individuals decreased from $848 (95% CI, $713-$984) per year in 1998 to $603 (95% CI, $484-$722) per year in 2015, whereas the mean number of prescriptions decreased from 7.64 (95% CI, 6.61-8.67) in 1998 to 7.03 (95% CI, 6.51-7.56) in 2015. National expenditures for outpatient treatment of depression increased from $12 430 000 000 in 1997 to $15 554 000 000 in 2007 and then to $17 404 000 000 in 2015, consistent with a slowing growth in national outpatient expenditures for depression. The percentage of this spending that came from self-pay (uninsured) individuals decreased from 32% in 1998 to 29% in 2007 and then to 20% in 2015. This decrease was largely associated with increasing Medicaid coverage, because the percentage of this spending covered was 19% in 1998, 15% in 2007, and 36% in 2015. Recent policy changes that increased insurance coverage for depression may be associated with reduced uninsured burden and with modest increases in the prevalence of and overall spending for outpatient treatment of depression. The lower-than-expected rate of treatment suggests that substantial barriers remain to individuals receiving treatment for their depression.

Impact of hydrocodone reclassification on analgesic prescribing in the Veterans Health Administration.

The impact of hydrocodone reclassification on analgesic prescribing in the Veterans Health Administration (VHA) was quantified. In this retrospective observational study, the volume of opioid medication dispensed was calculated quarterly from October 2011 to September 2015 using national VHA administrative data. Four volume measures were examined (prescription count, tablets dispensed, days' supply dispensed, and unique patients) for 4 opioid groups: hydrocodone combination products (HCPs), other opioid combination products, tramadol, and single-agent Schedule II opioids. HCP prescription count was further tabulated within longitudinal course of receipt groups: short-term, intermediate-term, and long-term. The initiation frequency of alternative analgesic pharmacotherapy, including opioid and nonopioid medications, was assessed among patients who discontinued long-term HCP receipt at reclassification. HCP prescriptions declined by 172,535 (19.4%) in the quarter after reclassification, whereas other opioid categories remained unchanged. The number of HCP prescriptions decreased by 10.7% among patients with short-term opioid receipt, and by 23.3% and 19.4% for intermediate- and long-term receipt groups, respectively. Among 13,416 individuals who discontinued receipt of long-term HCPs, replacement analgesics were not identified in 8,055 (60.0%) patients, whereas prescriptions for alternative opioids were observed in 3,557 (26.5%) and nonopioids in 2,753 (20.5%). HCP dispensing in VHA declined by 19.4% in the quarter after reclassification, which was driven largely by patients receiving long-term therapy. More than 13,000 veterans discontinued receipt of long-term HCP therapy after reclassification and the majority did not receive a replacement analgesic through VHA.

Associations between implementation of Project Lazarus and opioid analgesic dispensing and buprenorphine utilization in North Carolina, 2009\u20132014

BackgroundProject Lazarus (PL) is a seven-strategy, community-coalition-based intervention designed to reduce opioid overdose and dependence. The seven strategies include: community education, provider education, hospital emergency department policy change, diversion control, support programs for patients with pain, naloxone policies, and addiction treatment expansion. PL was originally developed in Wilkes County, NC. It was made available to all counties in North Carolina starting in March 2013 with funding of up to $34,400 per county per year. We examined the association between PL implementation and 1) overall dispensing rate of opioid analgesics, and 2) utilization of buprenorphine. Buprenorphine is often used in connection with medication assisted treatment (MAT) for opioid dependence.MethodsObservational interrupted time series analysis of 100 counties over 2009–2014 (n = 7200 county-months) in North Carolina. The intervention period was March 2013–December 2014. 74 of 100 counties implemented the intervention. Exposure data sources comprised process surveys, training records, Prescription Drug Monitoring Program (PDMP) data, and methadone treatment program quality data. Outcomes were PDMP-derived counts of opioid prescriptions and buprenorphine patients. Incidence Rate Ratios were estimated with adjusted GEE Poisson regression models of all seven PL strategies.ResultsIn adjusted models, diversion control efforts were positively associated with increased dispensing of opioid analgesics (IRR: 1.06; 95% CI: 1.03, 1.09). None of the other PL strategies were associated with reduced prescribing of opioid analgesics. Support programs for patients with pain were associated with a non-significant decrease in buprenorphine utilization (IRR: 0.93; 95% CI: 0.85, 1.02), but addiction treatment expansion efforts were associated with no change in buprenorphine utilization (IRR: 0.98; 95% CI: 0.91, 1.06).ConclusionsImplementation of PL strategies did not appreciably reduce opioid dispensing and did not increase buprenorphine utilization. These results are consistent with previous findings of limited impact of PL strategies on overdose morbidity and mortality. Future studies should analyze the uptake of MAT using a more expansive view of institutional barriers, treating community coalition activity around MAT as an effect modifier.

PHP54 - Defining Polypharmacy As A Count Of Medications: What is the Optimal Cut-Point?

Polypharmacy is a growing health concern that is prevalent among patients with multiple chronic conditions. However, the term “polypharmacy” is inconsistently defined in the literature. We seek to measure the relationship between prescription medication count and self-reported health, and to determine if an optimal cut-point for count of medications exists to define polypharmacy. Retrospective cohort study of adults 18+ using the 2014-2015 Medical Expenditure Panel Survey (n=8,995). The main exposure variable was prescription count defined as the number of unique therapeutic prescription drug classes taken during the baseline year. The outcome was functional (physical and mental) health captured through the Short Form 12 (SF-12). To identify inflection points in the data, we employed locally weighted smoothing (LOESS) in scatterplots. We employed Generalized Additive Models (GAM), allowing modeling non-linearity of the functional health trajectory across prescription count, and controlled for age, race, sex, insurance status, and multi-morbidity. Population-level weights were applied to provide national estimates. 69% of US adults are prescribed at least one drug in 2014, with 55%, 26%, and 13% taking two, five, and eight unique therapeutic drugs, respectively. Prescription medication count was inversely associated with physical health (β =-0.37 , 95% CI:[-0.46, -0.26]), but not mental health (β = -0.06, 95% CI: [-0.16, 0.05]). Loess curves show a mostly linear relationship between health and prescription count, with no clear inflection points. We identify that a cubic GAM model reflects the trajectory (p=0.05), and explains 22.8% of total variance of functional health at follow-up. Higher number of prescription count is associated with poorer health as expected. However, the data do not show any obvious break point that would justify operationalizing polypharmacy at a specific number of medications (e.g. 5 or more medications). The association varies greatly by underlying personal contextual factors (e.g. age, race-ethnicity).

Stated Pain Levels, Opioid Prescription Volume, and Chronic Opioid Use Among United States Army Soldiers.

The use of opioids has increased drastically over the past few years and decades. As a result, concerns have mounted over serious outcomes associated with chronic opioid use (COU), including dependency and death. A greater understanding of the factors that are associated with COU will be critical if prescribers are to navigate potentially competing objectives to provide compassionate care, while reducing the overall opioid use problem. In this study, we study pain levels and opioid prescription volumes and their effects on the risk of COU.This study leveraged passive data sources that support automated decision support systems (DSSs) currently employed in a large military population. The models presented compute monthly, person-specific, adjusted probability of subsequent COT and could potentially provide critical decision support for clinicians engaged in pain management. The study population included all outpatient presentations at military medical facilities worldwide among active duty United States Army soldiers during July 2011 to September 2014 (17,664,006 encounters; population N = 552,193). We conducted a retrospective cohort study of this population and employed longitudinal data and a discrete time multivariable logistic regression model to compute COT probability scores. The contribution of pain scores and opioid prescription quantities to the probability of COT represented analytic foci. There were 13,891 subjects (2.5%) who experienced incident COT during the observed time period. Statistically significant interactions between pain scores and prescription quantity were present, in addition to effects of multiple other control variables. Counts of monthly opioid prescriptions and maximum stated pain scores per month were each positively associated with COT. A wide range in individual COT risk scores was evident. The effect of prescription volume on the COT risk was larger than the effect of the pain score, and the combined effect of larger pain scores and increased prescription quantity was moderated by the interaction term. The results verified that passive data on the US Army can support a robust COT risk computation in this population. The individual, adjusted risk level requires statistical analyses to be fully understood. Because the same data sources drive current military DSSs, this work provides the potential basis for new, evidence-based decision support resources for military clinicians. The strong, independent impact of increasing opioid prescription counts on the COT risk reinforces the importance of exploring alternatives to opioids in pain management planning. It suggests that changing provider behavior through enhanced decision support could help reduce COT rates.

Do primary care providers who prescribe more opioids have higher patient panel satisfaction scores?

Objectives:Opioid prescribing in the United States has tripled since 1999. At the same time, there has been increasing attention to patient satisfaction. It has been suggested that providers concerned about patient satisfaction may be more likely to treat pain with opioids. We examined primary care providers’ opioid prescribing practices to determine if higher provider opioid prescribing was associated with higher patient satisfaction.Methods:For 77 primary care providers, we compared each provider’s opioid prescription count and amount prescribed to each provider’s patient panel satisfaction measures. Satisfaction measures were obtained from surveys following office visits and consisted of Likert-type scale answers concerning satisfaction for pain management and other provider satisfaction domains. Satisfaction surveys were generated independent of patient complaint of pain and had the aim of overall assessment of patient satisfaction with the provider and the healthcare system. We assessed the correlation between opioid prescribing and patient panel pain management satisfaction using linear regression models with and without adjustment for patient complexity.Results:We observed no statistically significant correlation between patient panel satisfaction with their provider and the quantity of opioids that the provider prescribed (R2 = 0.006; p = 0.52). There was also no correlation between patient panel satisfaction and the number of opioid prescriptions written by their provider (R2 = 0.005; p = 0.54). Additional multivariate analysis after adjusting for patient complexity also demonstrated no correlation of pain management satisfaction with opioids prescribed. Although the quantity of opioid prescriptions was not correlated with pain management satisfaction, several other patient satisfaction measures correlated significantly with pain management satisfaction.Conclusion:Primary care providers with a greater rate of opioid prescribing did not have higher patient panel satisfaction scores for pain management. In primary care, providers who want to improve patient satisfaction should focus on other components of patient care besides opioid-based pain management.

The lack of a relationship between physician payments from drug manufacturers and Medicare claims for abiraterone and enzalutamide.

Interactions between industry and prescribers have raised concerns regarding conflicts of interest. To the best of the authors' knowledge, quantitative data measuring these interactions have been limited until recently. In the current study, the authors sought to determine whether an association exists between industry payments and prescriber behavior with regard to abiraterone and enzalutamide. Two Centers for Medicare and Medicaid Services databases were combined to analyze oncologists and urologists who received industry payments and/or prescribed abiraterone and enzalutamide. Correlation analysis was constructed on prescription count and industry payments. Multivariable median regression examined predictors of change in prescription count per dollar of industry payment. Stratifying prescribers by quantile evaluated threshold effects on prescribers. The number of prescriptions was similar between prescribers who did and those who did not receive industry payment for both drugs. The median industry payment amount to prescribers differed between prescribers and nonprescribers for abiraterone ($72 vs $56) and enzalutamide ($59 vs $31). Although no statistical association was found to exist between industry payment amount and prescription count for abiraterone prescribers, an association was found to exist for enzalutamide prescribers (rho = 0.31). A small change was found with regard to prescription count per dollar of industry payment for abiraterone (0.0007 prescriptions) and enzalutamide (0.0006 prescriptions). The amount of industry payment needed to predict one additional prescription was found to be lower in the fourth and fifth quantiles compared with the first through third quantiles. No difference in prescription count was found to exist between prescribers who received industry payments and those who did not. A positive correlation was noted between industry payments and prescription count for enzalutamide. Ease of adoption may affect differences between the 2 drugs. Cancer 2017;123:4356-62. © 2017 American Cancer Society.

Variations in antibiotic use for respiratory tract infections

ABSTRACT&#x0D; ObjectivesAntibiotic resistance is a significant public health issue, driven in large part by selection pressure induced by antibiotic use. Despite knowledge that a reduction in inappropriate antibiotic use is important, significant and sustained behaviour change has remained difficult to achieve. Previous studies have suggested that prescribing decisions vary with patient comorbidities and age, as well as the physician’s age, claim volume, specialty, and continuity of care with the particular patient. Regional level variation has also been reported. The goal of this study is to explore variations in antibiotic prescribing for respiratory tract infections (RTIs) at the levels of patients, physicians, and regions.&#x0D; ApproachWe used data on fee-for-service physician visits from the universal Medical Services Plan (MSP) for all residents of British Columbia, Canada from 2002 to 2012. We identified a cohort of patient visits for RTI (ICD-9 codes 460-466, 480, or 487). We derived measures of healthcare use and comorbidities at the patient level, and measures of physician claim volume and frequency of respiratory tract infection management, at the level of the physician. We used data on antibiotics filled by individuals, the number of all medications filled by individuals each year, and counts of prescriptions written by physicians (and filled) by month, from the provincial drug insurance database. We linked antibiotic prescriptions to physician visits by patient and prescriber as antibiotics dispensed within 5 days after the RTI visit. We calculated measures of regional population distributions. We used data on meteorological temperature readings assigned to each region, for each day, and calculated 28-day moving averages. We linked data on patient demographics, physician demographics, and hospitalizations to our dataset. Our analysis will use hierarchical generalized linear mixed models (GLMMs) with logit link to account for the clustering effects of patients among physicians and regions, to model the odds of an antibiotic prescription being dispensed. Measures of variation will be discussed.&#x0D; ResultsBetween April 1, 2005 and March 31, 2012, there were over 10.5 million visits by nearly 3 million individuals, served by over 8000 physicians in 88 regions. Antibiotics were prescribed in 37% of all visits.&#x0D; ConclusionThese are preliminary results, with full analytic results available in the coming months. These results will have implications for better understanding the extent of variations in antibiotic prescribing, and some of the drivers of these variations, as well as the potential to inform ongoing efforts to improve the appropriateness of antibiotic use.

Pharmacy use by dual-eligible non-elderly veterans with private healthcare insurance.

BackgroundUtilization of private sector healthcare services among dual enrolled veterans with private healthcare insurance plans (PHIP) has not been well-characterized. Concurrent use of Veterans Health Administration (VHA) and non-VHA pharmacies may increase risk for adverse outcomes. Thus, the objectives of this study were to determine the extent to which dual VHA-PHIP enrollees obtain medications through VHA and non-VHA pharmacies and to characterize medications obtained through non-VHA pharmacies.MethodsThis observational study used merged administrative data from VHA and a predominant regional PHIP to select veterans < 65 years of age, residing in two Midwestern US states, and simultaneously enrolled in both VHA and the PHIP during fiscal years (FY) 2001–2010. Primary outcome measures included counts of prescriptions dispensed from VHA and non-VHA pharmacies, and frequencies of medications dispensed by non-VHA pharmacies based on PHIP claims.ResultsOf 5783 veterans who filled ≥ 1 prescription in FY10, 2935 (50.8 %) used non-VHA pharmacies exclusively, 1165 (20.2 %) used VHA pharmacies exclusively and 1683 (29.1 %) were dual users. Health services utilization was higher for dual users compared to exclusive users of either VHA or non-VHA pharmacies across multiple measures, including total prescriptions, outpatient encounters, and inpatient admissions. The most common medications dispensed by non-VHA pharmacies, by proportion of veterans treated, were hydrocodone (20.9 %), amoxicillin (18.5 %), simvastatin (17.5 %), azithromycin (17.4 %), and lisinopril (15.1 %). Antidepressants comprised 3 of 10 most common medications dispensed by VHA, but none of the most common medications dispensed to exclusive non-VHA pharmacy users.ConclusionsOur findings align with VHA-Medicare dual enrolled veterans where only a minority of veterans used VHA services exclusively. Younger veterans relied disproportionately on VHA for mental health medications.

Trends in Opioid Analgesic-Prescribing Rates by Specialty, U.S., 2007-2012.

Opioid analgesic prescriptions are driving trends in drug overdoses, but little is known about prescribing patterns among medical specialties. We conducted this study to examine the opioid-prescribing patterns of the medical specialties over time. IMS Health's National Prescription Audit (NPA) estimated the annual counts of pharmaceutical prescriptions dispensed in the U.S. during 2007-2012. We grouped NPA prescriber specialty data by practice type for ease of analysis, and measured the distribution of total prescriptions and opioid prescriptions by specialty. We calculated the percentage of all prescriptions dispensed that were opioids, and evaluated changes in that rate by specialty during 2007-2012. The analysis was conducted in 2013. In 2012, U.S. pharmacies and long-term care facilities dispensed 4.2 billion prescriptions, 289 million (6.8%) of which were opioids. Primary care specialties accounted for nearly half of all dispensed opioid prescriptions. The rate of opioid prescribing was highest for specialists in pain medicine (48.6%); surgery (36.5%); and physical medicine/rehabilitation (35.5%). The rate of opioid prescribing rose during 2007-2010 but leveled thereafter as most specialties reduced opioid use. The greatest percentage increase in opioid-prescribing rates during 2007-2012 occurred among physical medicine/rehabilitation specialists (+12.0%). The largest percentage drops in opioid-prescribing rates occurred in emergency medicine (-8.9%) and dentistry (-5.7%). The data indicate diverging trends in opioid prescribing among medical specialties in the U.S. during 2007-2012. Engaging the medical specialties individually is critical for continued improvement in the safe and effective treatment of pain.

Factors associated with treatment of women with osteoporosis or osteopenia from a national survey

BackgroundHealth outcomes could be improved if women at high risk for osteoporotic fracture were matched to effective treatment. This study determined the extent to which treatment for osteoporosis/osteopenia corresponded to the presence of specific risk factors for osteoporotic fracture.MethodsThis retrospective analysis of the United States 2007 National Health and Wellness Survey included women age ≥ 40 years who reported having a diagnosis of osteoporosis (69% of 3276) or osteopenia (31% of 3276). Patients were stratified by whether they were or were not taking prescription treatment for osteoporosis/osteopenia. Using 34 patient characteristics as covariates, logistic regression was used to determine factors associated with treatment.ResultsCurrent prescription treatment was reported by 1800 of 3276 (54.9%) women with osteoporosis/osteopenia. The following factors were associated with receiving prescription treatment: patient-reported diagnosis of osteoporosis (versus osteopenia); previous bone mineral density test; ≥ 2 fractures since age 50; older age; lower body mass index; better physical functioning; postmenopausal status; family history of osteoporosis; fewer comorbidities; prescription insurance coverage; higher total prescription count; higher ratio of prescription costs to monthly income; higher income; single status; previous visit to a rheumatologist or gynecologist; and 1 or 2 outpatient visits to healthcare provider (vs. none) in the prior 6 months. Glucocorticoid, tobacco, and daily alcohol use were risk factors for fracture that were not associated with treatment.ConclusionsThere is a mismatch between those women who could benefit from treatment for osteoporosis and those who are actually treated. For example, self-reported use of glucocorticoids, tobacco, and alcohol were not associated with prescription treatment of osteoporosis. Other clinical and socioeconomic factors were associated with treatment (e.g. prescription drug coverage and higher income) or not (e.g. comorbid osteoarthritis and anxiety) and could be opportunities to improve care.

Relationship between leukotriene-modifying agent prescriptions dispensed and rate of suicide deaths by county in the US.

Background:The US Food and Drug Administration has issued warnings about a potential link between leukotriene receptor-modifying agents (LTMA) and suicide. These warnings are based on case reports and there is controversy about the association. While spontaneous reporting of suicide-related events attributed to LTMA has risen dramatically, these data may be biased by the warnings. The objective of this study was to explore the relationship between LTMA and suicide deaths using event data preceding the Food and Drug Administration warnings.Methods:We conducted a mixed-effects Poisson regression analysis of the association between LTMA prescriptions dispensed and suicide deaths at the county level. Counts of suicide deaths in each US county, stratified by race, age group, gender, and year were obtained from the National Center for Health Statistics for the period January 1, 1999 to December 31, 2006. Counts of LTMA prescriptions dispensed in each US county were obtained from IMS Health Incorporated. The model estimated the overall suicide rate conditional on LTMA use, adjusted for age, gender, race, year, and antidepressant utilization. We also assessed the intracounty and intercounty associations.Results:There were 249,872 suicides in the US between 1999 and 2006, and the annual suicide rate ranged from 11.17 to 11.92 per 100,000 population. There were 118.63, 11.68, and 0.12 million prescriptions dispensed for montelukast, zafirlukast, and zileuton, respectively, between 1999 and 2006. The mean rate of LTMA prescriptions dispensed by county was 42.91 (95% confidence interval [CI] 42.78–43.04), 4.82 (95% CI 4.81–4.84), and 0.05 (95% CI 0.05–0.05) per 1000 for montelukast, zafirlukast, and zileuton, respectively. We found a negative within-county association between the rate of total LTMA prescriptions dispensed and the suicide rate by county (P = 0.0296). This association was primarily driven by montelukast.Conclusion:Our results, while subject to certain limitations, provide preliminary evidence that the association between LTMA and suicide could be different (ie, reduced risk) than that which might be anticipated based on previous warnings. Patient-level research is needed to understand more clearly the association between LTMA and suicide.

Change of Selection to Antihypertensive Drugs in Hypertensive Patients with Diabetes Mellitus: In Pohang · Gyeongju Primary Care Research Network

Background: Angiotensin converting enzyme inhibitors (ACEIs) or Angiotensin II type 1 receptor blockers (ARBs) are drugs for hypertensive patients with diabetes mellitus. But prescription rate in 2005 year study of Pohang · Gyeongju area was only 30.8%. Therefore, a study on the change of prescription rate in the same area after 3 years was done. Methods: During three months from January 2008, 152 hypertensive patients with diabetes mellitus on their prescribed antihypertensive medications by 9 family physicians in visiting order were analyzed. After the analysis, the infl uencing factors for such prescriptions were ascertained by directly visiting each physicians who prescribed them. Results: A regimen of 16 antihypertensive agents were prescribed by these family physicians. Prescription count of ACEIs or ARBs was 101 cases (66.4%). ACEIs single therapy was 19 cases (12.5%), ACEIs combination therapy was 7 cases (4.6%), ARBs single therapy was 31 cases (20.4%) and ARBs combination therapy was 44 cases (28.9%). The ACEIs or ARBs which were selected by physicians that followed compelling indication was 5 (55.6%), reduce pressure effect was 3 (33.3%) and public relations of new medicine was 1 (11.1%). Conclusion: In prescribing antihypertensive agents for patients with diabetes mellitus, selection of ACEIs or ARBs was increased from 30.8% to 66.4%. Education of recommended standard by participating in such study and developing of excellent new medicines may increase such change.