Dataset Information

Hospital Prescribing of Opioids to Medicare Beneficiaries.

ABSTRACT: Use of opioids during and shortly after an acute hospitalization is warranted in some clinical settings. However, given the potential of opioids for short-term adverse events and long-term physiologic tolerance, it is important to understand the frequency of opioid prescribing at hospital discharge, hospital variation, and patient and hospital factors associated with opioid prescribing, which is currently unknown in the United States.To estimate the frequency of opioid prescribing at hospital discharge among Medicare beneficiaries without an opioid prescription claim 60 days prior to hospitalization; to document hospital variation in prescribing; and to analyze patient and hospital factors associated with prescribing, including hospital average performance on pain-related Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) measures.Analysis of pharmacy claims of a 20% random sample of Medicare beneficiaries hospitalized in 2011 without an opioid prescription claim in the 60 days before hospitalization.Our main outcome was a new opioid claim within 7 days of hospital discharge. We estimated a multivariable linear probability model of patient factors associated with new opioid use and described hospital variation in adjusted rates of new opioid use. In multivariable linear regression analysis, we also analyzed hospital factors associated with average adjusted new opioid use at the hospital level, including the percentage of each hospital's patients who reported that their pain during hospitalization was always well controlled in the 2011 HCAHPS surveys.Among 623?957 hospitalizations, 92?882 (14.9%) were associated with a new opioid claim. Among those hospitalizations with an associated opioid claim within 7 days of hospital discharge, 32?731 (42.5%) of 77?092 were associated with an opioid claim after 90 days postdischarge. Across 2512 hospitals, the average adjusted rate of new opioid use within 7 days of hospitalization was 15.1% (interquartile range, 12.3%-17.4%; interdecile range, 10.5%-20.0%). A hospital's adjusted rate of new opioid use was modestly positively associated with the percentage of its inpatients reporting that their pain was always well managed (increase from 25th to the 75th percentile in the HCAHPS measure was associated with an absolute increase in new opioid use of 0.89 percentage points or a relative increase of 6.0%; P?

SUBMITTER: Jena AB

PROVIDER: S-EPMC4955877 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Hospital Prescribing of Opioids to Medicare Beneficiaries.

Jena Anupam B AB Goldman Dana D Karaca-Mandic Pinar P

JAMA internal medicine 20160701 7

<h4>Importance</h4>Use of opioids during and shortly after an acute hospitalization is warranted in some clinical settings. However, given the potential of opioids for short-term adverse events and long-term physiologic tolerance, it is important to understand the frequency of opioid prescribing at hospital discharge, hospital variation, and patient and hospital factors associated with opioid prescribing, which is currently unknown in the United States.<h4>Objective</h4>To estimate the frequency ...[more]

PMID: 27294595

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Project description:ImportanceContemporary national clinical practice guidelines recommend direct-acting oral anticoagulants (DOACs) as the first-line anticoagulant strategy over warfarin for most indications, especially among older individuals with an elevated bleeding risk.ObjectiveTo evaluate anticoagulant prescribing and DOAC uptake by US clinicians in the Medicare population.Design, setting, and participantsThis retrospective cohort study included all US clinicians with more than 10 Medicare oral anticoagulant prescription claims, who were included in the national Medicare Provider Utilization and Payment Data (2013-2018). Data analyses were conducted between October 2020 and October 2021.ExposuresDOAC prescription in 2013.Main outcomes and measuresClinicians were categorized based on 2013 prescribing as solely prescribing warfarin, DOAC, or both, and their temporal trajectories of proportionate DOAC use were examined.ResultsThe analysis included 325 666 unique clinicians with more than 10 oral anticoagulant prescriptions between 2013 and 2018 (26 620 [8.2%] cardiologists, 85 563 [26.3%] internal medicine physicians, 84 369 [25.9%] family medicine physicians, and 81 161 [24.9%] advanced practice clinicians, including nurse practitioners and physician assistants). In 2013, among 91 837 prescribers, 54 501 (59.3%) prescribed only warfarin, 1918 (2.1%) prescribed only a DOAC, and 35 418 (38.6%) prescribed both. During the study period, the number of clinicians prescribing DOACs increased, but 19% continued to prescribe only warfarin in 2018. While 359 cardiologists prescribing anticoagulants (1.6%) were warfarin-only prescribers, 10 414 (20.0%) and 6296 (12.6%) of family and internal medicine physicians also prescribed only warfarin, respectively. Clinicians prescribing only warfarin in 2013 had lower proportionate DOAC use throughout the study compared with 2013 DOAC prescribers, which represents a median (IQR) of 41.9% (20.3%-61.9%) of their anticoagulant prescriptions in 2018 vs 67.0% (49.9%-82.8%) for DOAC prescribers.Conclusions and relevanceDespite the increase in DOAC use among Medicare beneficiaries, many clinicians in this study continued to use warfarin as their predominant or only anticoagulant instead of DOACs. There is a need to address barriers to the uptake of these medications to realize their potential benefits for patients.

Project description:OBJECTIVE:To use patient-level clinical variables to develop and validate a parsimonious model to predict hospital readmissions from home healthcare (HHC) in Medicare fee-for-service beneficiaries. DESIGN:Retrospective analysis using multivariable logistic regression and gradient boosting machine (GBM) learning to develop and validate a predictive model. SETTING/PARTICIPANTS/MEAUREMENTS:A 5% national sample of patients, aged 65?years or older, with Medicare fee-for-service who received skilled HHC services within 5 days of hospital discharge in 2012 (n = 43 407). Multiple data sets were merged, including Medicare Outcome and Assessment Information Set, Home Health Claims, Medicare Provider Analysis and Review, and Master Beneficiary Summary Files, to extract patient-level variables from the first HHC visit after discharge and measure 30-day readmission outcomes. RESULTS:Among 43 407 patients with inpatient hospitalizations followed by HHC, 14.7% were readmitted within 30?days. Of the 53 candidate variables, seven remained in the final model as individually predictive of outcome: Elixhauser comorbidity index, index hospital length of stay, urinary catheter presence, patient status (ie, fragile health with high risk of complications or serious progressive condition), two or more hospitalizations in prior year, pressure injury risk or presence, and surgical wound presence. Of interest, surgical wounds, either from a total hip or total knee arthroplasty procedure or another surgical procedure, were associated with fewer readmissions. The optimism-corrected c-statistics for the full model and parsimonious model were 0.67 and 0.66, respectively, indicating fair discrimination. The Brier score for both models was 0.120, indicating good calibration. The GBM model identified similar predictive variables. CONCLUSION:Variables available to HHC clinicians at the first postdischarge HHC visit can predict readmission risk and inform care plans in HHC. Future analyses incorporating measures of social determinants of health, such as housing instability or social support, have the potential to enhance prediction of this outcome. J Am Geriatr Soc 67:2505-2510, 2019.

Project description:ImportanceA growing proportion of the population is enrolling in Medicare Advantage (MA), which typically offers additional benefits compared with traditional Medicare (TM).ObjectiveTo determine whether frailty and frailty trajectories differ between MA enrollees and TM enrollees.Design, setting, and participantsThis retrospective cohort study used data from the National Health and Aging Trends Study (2015-2016). Analyses were conducted from August 2023 to March 2024. Participants were community-dwelling Medicare beneficiaries aged 65 years and older.ExposureEnrollment in MA vs TM.Main outcomes and measuresFrailty was calculated by a frailty index (FI) (range, 0-1, with higher values indicating greater frailty) and the Fried Frailty Phenotype (FFP) score (range, 0-5, with higher values indicating greater frailty). Physical performance, including Short Physical Performance Battery (SPPB) score (range, 0-12, with higher values indicating better performance), and gait speed (meters per second) were measured. The primary outcome was the difference in FI and FFP scores from the 2015 baseline assessment to the 2016 follow-up assessment. Secondary outcomes include the 1-year changes in SPPB and gait speed.ResultsThe final cohort consisted of 7063 participants (2775 [23.1%] aged >80 years; 4040 [54.7%] female), representing a sample of the 38.8 million beneficiaries. There were 2583 (35.0%) MA enrollees (13.6 million) and 4480 (65.0%) TM enrollees (25.2 million). At baseline, the FI score was similar between MA and TM enrollees (mean [SD], 0.22 [0.15] vs 0.21 [0.14]), although MA enrollees had worse phenotypic frailty (496 participants [15.2%] vs 811 participants [13.7%] considered frail by FFP score), SPPB scores (mean [SD], 6.91 [3.34] vs 7.21 [3.27]), and gait speed (0.79 [0.24] m/s vs 0.82 [0.23] m/s) than TM enrollees. One year later, there were no differences between MA and TM enrollees in the 1-year change in FI score (mean [SD], 0.016 [0.071] vs 0.014 [0.066]; adjusted mean difference, 0.001 [95% CI, -0.004 to 0.005]), FFP score (mean [SD], 0.017 [1.004] vs 0.007 [0.958]; adjusted mean difference, -0.009 [95% CI, -0.067 to 0.049]), SPPB score (mean [SD], -0.144 [2.064] vs -0.211 [1.968]; adjusted mean difference, 0.068 [95% CI, -0.076 to 0.212]), and gait speed (mean [SD], -0.0160 [0.148] m/s vs -0.007 [0.148] m/s; adjusted mean difference, -0.010 m/s [95% CI, -0.067 to 0.049 m/s]).Conclusions and relevanceIn this cohort study of Medicare beneficiaries from 2015, MA enrollees experienced similar declines in frailty over 1 year compared with TM enrollees. Future work should examine whether the specific types of services covered by health insurance can impact frailty and health trajectories for older adults.

Project description:Importance:Although there are many pharmacologic alternatives to opioids, it is unclear whether the structure of Medicare Part D formularies discourages use of the alternatives. Objectives:To quantify the coverage of opioid alternatives and prevalence of prior authorization, step therapy, quantity limits, and tier placement for these drugs, and test whether these formulary exclusions and restrictions are associated with increased opioid prescribing to older adults at the county level. Design, Setting, and Participants:County fixed-effect models were estimated using a panel of counties across the 50 US states and the District of Columbia over calendar years 2015 and 2016. Data analysis was conducted from July 1 to September 23, 2019. The sample included 2721 counties in 2015 and 2671 counties in 2016 with sufficient data on Medicare Part D formulary design and opioid prescribing. Main Outcomes and Measures:County-level opioid prescribing rate (number of opioid claims divided by the number of overall claims) and counts of excluded opioid alternatives and opioid alternatives with prior authorization, step therapy, quantity limits, and high-tier placements. Results:A total of 30 nonopioid analgesics were examined across 28 997 Medicare plans in 2015 and 30 390 plans in 2016. Medicare plans did not cover a mean of 7% of these drugs (interquartile range, 10%; lower to upper limit, 0%-23%). Among covered nonopioids, prior authorization and step therapy were uncommon, with fewer than 5% affected by prior authorization and 0% by step therapy. However, 13% of covered nonopioids had quantity limits (interquartile range, 10%; lower to upper limit, 0%-31%) and 22% were in high-cost tiers (interquartile range, 38%; lower to upper limit, 0%-50%). Increases in the number of nonopioids excluded on Medicare plans in a county were associated with increased opioid prescribing (effect size relative to mean, 2.2%-3.7%; P = .004). Conversely, increases in the number of opioids not covered on Medicare plans in a county was found to be associated with decreased opioid prescribing (effect size relative to mean, 0.8%-1.5%; P = .02). None of the utilization management strategies (prior authorization, step therapy, and quantity limits) examined or high-cost tier placements of nonopioids were associated with increased opioid prescribing. Conclusions and Relevance:Lack of Medicare coverage for pharmacologic alternatives to opioids may be associated with increased opioid prescribing.

Project description:BackgroundPrescribing of medications with anticholinergic properties in older nursing home residents is relatively common, despite an association with an increased risk for falls, delirium, and other outcomes. Few studies have investigated what factors influence different levels of prescribing of these agents.ObjectivesThe primary objective was to identify factors associated with low- and high-level anticholinergic burden in nursing home residents. A secondary objective was to examine in detail the contribution of different medications to low versus high burden to aid in determining which drugs to target in interventions.MethodsThis was a retrospective, cross-sectional analysis of a national sample of 2009-2010 Medicare Part A and B claims, Part D prescription drug events, and Minimum Data Set (MDS) v2.0 assessments. The cohort included 4730 Medicare beneficiaries aged ≥ 65 years with continuous Medicare Parts A, B, and D enrollment, admitted for non-skilled stays of ≥ 14 days between 1 January 2010 and 30 September 2010. Anticholinergic burden was defined using the Anticholinergic Cognitive Burden (ACB) scale. Medication scores were summed at the patient level and categorized as high (score ≥ 3), low (score 1-2), or none. Baseline predisposing factors (age, sex, race/ethnicity), enabling factors (prior year hospitalization, emergency department, primary care, specialist visits; region; Medicaid/low-income subsidy), and medical need factors (dementia severity, anti-dementia medication, Charlson co-morbidity index [CCI], select comorbidities) were evaluated for association with anticholinergic burden using multinomial logistic regression.ResultsOverall, 29.6% of subjects had a high anticholinergic burden and 35.2% had a low burden. High burden was most often (72%) due to one highly anticholinergic medication rather than a cumulative effect. In adjusted analyses, factors associated with increased risk of both low and high anticholinergic burden included comorbidity, antidementia medication, depression, hypertension, and prior year hospitalization. Older age was associated with decreased odds of high anticholinergic burden. Urinary incontinence and prior year specialist visit were associated with increased odds of high anticholinergic burden. Severe and nonsevere dementia were associated with decreased odds of low burden but increased odds of high burden.ConclusionAlmost two-thirds of nursing home patients have some degree of anticholinergic burden. Several medical need variables are significantly associated with increased risk for low and high anticholinergic burden. Interventions should be developed to optimize prescribing for residents at increased risk of receiving medications with anticholinergic properties. Future study is needed to evaluate the difference in the risk of adverse outcomes associated with various levels of anticholinergic burden.

Dataset Information

Hospital Prescribing of Opioids to Medicare Beneficiaries.

Publications

Hospital Prescribing of Opioids to Medicare Beneficiaries.

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