scholarly journals Persistence of High-Need Status Over Time Among Fee-for-Service Medicare Beneficiaries

2020 ◽  
pp. 107755871990121
Author(s):  
Tamra Keeney ◽  
Nina R. Joyce ◽  
David J. Meyers ◽  
Vincent Mor ◽  
Emmanuelle Belanger
Keyword(s):  
Claims Data ◽  
National Level ◽  
Demographic Characteristics ◽  
Administrative Claims ◽  
Fee For Service ◽  
Medicare Beneficiaries ◽  
Longitudinal Patterns ◽  
Poor Outcomes ◽  
Longitudinal Variability ◽  
Over Time

Although administrative claims data can be used to identify high-need (HN) Medicare beneficiaries, persistence in HN status among beneficiaries and subsequent variation in outcomes are unknown. We use national-level claims data to classify Fee-for-Service (FFS) Medicare beneficiaries as HN annually among beneficiaries continuously enrolled between 2013 and 2015. To examine persistence of HN status over time, we categorize longitudinal patterns in HN status into being never, newly, transiently, and persistently HN and examine differences in patients’ demographic characteristics and outcomes. Among survivors, 23% of beneficiaries were HN at any time—4% persistently HN, 13% transiently HN, and 6% newly HN. While beneficiaries who were persistently HN had higher mortality, utilization, and expenditures, classification as HN at any time was associated with poor outcomes. These findings demonstrate longitudinal variability of HN status among FFS beneficiaries and reveal the pervasiveness of poor outcomes associated with even transitory HN status over time.

scholarly journals Patterns of Long-Term Prescription Opioid Use Among Older Adults in the United States: A Study of Medicare Administrative Claims Data

2020 ◽  
Vol 1;24 (1;1) ◽  
pp. 31-40
Keyword(s):  
Older Adults ◽  
Claims Data ◽  
The United States ◽  
Prescription Opioid ◽  
Administrative Claims ◽  
Medicare Beneficiaries ◽  
Opioid Use ◽  
Opioid Prescription ◽  
Administrative Claims Data

BACKGROUND: Long-term opioid therapy was prescribed with increasing frequency over the past decade. However, factors surrounding long-term use of opioids in older adults remains poorly understood, probably because older people are not at the center stage of the national opioid crisis. OBJECTIVES: To estimate the annual utilization and trends in long-term opioid use among older adults in the United States. STUDY DESIGN: Retrospective cohort study. SETTING: Data from Medicare-enrolled older adults. METHODS: This study utilized a nationally representative sample of Medicare administrative claims data from the years 2012 to 2016 containing records of health care services for more than 2.3 million Medicare beneficiaries each year. Medicare beneficiaries who were 65 years of age or older and who were enrolled in Medicare Parts A, B, and D, but not Part C, for at least 10 months in a year were included in the study. We measured annual utilization and trends in new long-term opioid use episodes over 4 years (2013–2016). We examined claims records for the demographic characteristics of the eligible individuals and for the presence of chronic non-cancer pain (CNCP), cancer, and other comorbidities. RESULTS: From 2013 to 2016, administrative claims of approximately 2.3 million elderly Medicare beneficiaries were analyzed in each year with a majority of them being women (~56%) and white (~82%) with a mean age of approximately 75 years. The proportion of all eligible beneficiaries with at least one new opioid prescription increased from 6.64% in 2013, peaked at 10.32% in 2015, and then decreased to 8.14% in 2016. The proportion of individuals with long-term opioid use among those with a new opioid prescription was 12.40% in 2013 and 10.20% in 2016. Among new long-term opioid users, the proportion of beneficiaries with a cancer diagnosis during the study years increased from 13.30% in 2013 to 15.67% in 2016, and the proportion with CNCP decreased from 30.25% in 2013 to 27.36% in 2016. Across all years, long-term opioid use was consistently high in the Southern states followed by the Midwest region. LIMITATIONS: This study used Medicare fee-for-service administrative claims data to capture prescription fill patterns, which do not allow for the capture of individuals enrolled in Medicare Advantage plans, cash prescriptions, or for the evaluation of appropriateness of prescribing, or the actual use of medication. This study only examined long-term use episodes among patients who were defined as opioid-naive. Finally, estimates captured for 2016 could only utilize data from 9 months of the year to capture 90-day long-term-use episodes. CONCLUSIONS: Using a national sample of elderly Medicare beneficiaries, we observed that from 2013 to 2016 the use of new prescription opioids increased from 2013 to 2014 and peaked in 2015. The use of new long-term prescription opioids peaked in 2014 and started to decrease from 2015 and 2016. Future research needs to evaluate the impact of the changes in new and long-term prescription opioid use on population health outcomes. KEY WORDS: Long-term, opioids, older adults, trends, Medicare, chronic non-cancer pain, cancer, cohort study

Accurate Medication Adherence Measurement Using Administrative Data for Frequently Hospitalized Patients

2020 ◽  
pp. 001857872091855
Author(s):  
Rafia S. Rasu ◽  
Suzanne L. Hunt ◽  
Junqiang Dai ◽  
Huizhong Cui ◽  
Milind A. Phadnis ◽  
...  
Keyword(s):  
Medication Adherence ◽  
Hospital Stay ◽  
Claims Data ◽  
Medication Possession Ratio ◽  
The United States ◽  
Hospital Length ◽  
Hospital Length Of Stay ◽  
Administrative Claims ◽  
P2y12 Inhibitors ◽  
Over Time

Background: Pharmacy administrative claims data remain an accessible and efficient source to measure medication adherence for frequently hospitalized patient populations that are systematically excluded from the landmark drug trials. Published pharmacotherapy studies use medication possession ratio (MPR) and proportion of days covered (PDC) to calculate medication adherence and usually fail to incorporate hospitalization and prescription overlap/gap from claims data. To make the cacophony of adherence measures clearer, this study created a refined hospital-adjusted algorithm to capture pharmacotherapy adherence among patients with end-stage renal disease (ESRD). Methods: The United States Renal Data System (USRDS) registry of ESRD was used to determine prescription-filling patterns of those receiving new prescriptions for oral P2Y12 inhibitors (P2Y12-I) between 2011 and 2015. P2Y12-I-naïve patients were followed until death, kidney transplantation, discontinuing medications, or loss to follow-up. After flagging/censoring key variables, the algorithm adjusted for hospital length of stay (LOS) and medication overlap. Hospital-adjusted medication adherence (HA-PDC) was calculated and compared with traditional MPR and PDC methods. Analyses were performed with SAS software. Results: Hospitalization occurred for 78% of the cohort (N = 46 514). The median LOS was 12 (interquartile range [IQR] = 2-34) days. MPR and PDC were 61% (IQR = 29%-94%) and 59% (IQR = 31%-93%), respectively. After applying adjustments for overlapping coverage days and hospital stays independently, HA-PDC adherence values changed in 41% and 52.7% of the cohort, respectively. When adjustments for overlap and hospital stay were made concurrently, HA-PDC adherence values changed in 68% of the cohort by 5.8% (HA-PDC median = 0.68, IQR = 0.31-0.93). HA-PDC declined over time (3M-6M-9M-12M). Nearly 48% of the cohort had a ≥30 days refill gap in the first 3 months, and this increased over time ( P < .0001). Conclusions: Refill gaps should be investigated carefully to capture accurate pharmacotherapy adherence. HA-PDC measures increased adherence substantially when adjustments for hospital stay and medication refill overlaps are made. Furthermore, if hospitalizations were ignored for medications that are included in Medicare quality measures, such as Medicare STAR program, the apparent reduction in adherence might be associated with lower quality and health plan reimbursement.

scholarly journals Trends in outpatient antibiotic use and prescribing practice among US older adults, 2011-15: observational study

BMJ ◽  
2018 ◽  
pp. k3155 ◽  
Author(s):  
Scott W Olesen ◽  
Michael L Barnett ◽  
Derek R MacFadden ◽  
Marc Lipsitch ◽  
Yonatan H Grad
Keyword(s):  
Older Adults ◽  
Observational Study ◽  
Inappropriate Prescribing ◽  
Temporal Trends ◽  
Antibiotic Use ◽  
Antibiotic Prescribing ◽  
Administrative Claims ◽  
Fee For Service ◽  
Medicare Beneficiaries ◽  
Prescribing Practice

AbstractObjectiveTo identify temporal trends in outpatient antibiotic use and antibiotic prescribing practice among older adults in a high income country.DesignObservational study using United States Medicare administrative claims in 2011-15.SettingMedicare, a US national healthcare program for which 98% of older adults are eligible.Participants4.5 million fee-for-service Medicare beneficiaries aged 65 years old and older.Main outcome measurementsOverall rates of antibiotic prescription claims, rates of potentially appropriate and inappropriate prescribing, rates for each of the most frequently prescribed antibiotics, and rates of antibiotic claims associated with specific diagnoses. Trends in antibiotic use were estimated by multivariable regression adjusting for beneficiaries’ demographic and clinical covariates.ResultsThe number of antibiotic claims fell from 1364.7 to 1309.3 claims per 1000 beneficiaries per year in 2011-14 (adjusted reduction of 2.1% (95% confidence interval 2.0% to 2.2%)), but then rose to 1364.3 claims per 1000 beneficiaries per year in 2015 (adjusted reduction of 0.20% over 2011-15 (0.09% to 0.30%)). Potentially inappropriate antibiotic claims fell from 552.7 to 522.1 per 1000 beneficiaries over 2011-14, an adjusted reduction of 3.9% (3.7% to 4.1%). Individual antibiotics had heterogeneous changes in use. For example, azithromycin claims per beneficiary decreased by 18.5% (18.2% to 18.8%) while levofloxacin claims increased by 27.7% (27.2% to 28.3%). Azithromycin use associated with each of the potentially appropriate and inappropriate respiratory diagnoses decreased, while levofloxacin use associated with each of those diagnoses increased.ConclusionAmong US Medicare beneficiaries, overall antibiotic use and potentially inappropriate use in 2011-15 remained steady or fell modestly, but individual drugs had divergent changes in use. Trends in drug use across indications were stronger than trends in use for individual indications, suggesting that guidelines and concerns about antibiotic resistance were not major drivers of change in antibiotic use.

scholarly journals Transgender Medicare Beneficiaries and Chronic Conditions: Exploring Fee-for-Service Claims Data

LGBT Health ◽  
2017 ◽  
Vol 4 (6) ◽  
pp. 404-411 ◽  
Author(s):  
Christina N. Dragon ◽  
Paul Guerino ◽  
Erin Ewald ◽  
Alison M. Laffan
Keyword(s):  
Chronic Conditions ◽  
Claims Data ◽  
Fee For Service ◽  
Medicare Beneficiaries

scholarly journals Comparing Survey-Based Frailty Assessment to Medicare Claims in Predicting Health Outcomes and Utilization in Medicare Beneficiaries

2019 ◽  
Vol 32 (7-8) ◽  
pp. 764-777
Author(s):  
Shannon Wu ◽  
John Mulcahy ◽  
Judith D. Kasper ◽  
Hong J. Kan ◽  
Jonathan P. Weiner
Keyword(s):  
Administrative Data ◽  
Health Care Providers ◽  
Risk Measures ◽  
Administrative Claims ◽  
Fee For Service ◽  
Medicare Beneficiaries ◽  
Care Providers ◽  
Multivariable Logistic Regression Model ◽  
Management Interventions ◽  
C Statistic

Objectives: To assess two models for the prediction of health utilization and functions using standardized in-person assessments of frailty and administrative claims-based geriatric risk measures among Medicare fee-for-service beneficiaries aged 65 years and above. Methods: Outcomes of hospitalizations, death, and functional help were investigated for participants in the 2011 National Health and Aging Trends Study. For each outcome, multivariable logistic regression model was used to investigate claims-based geriatric risk and survey-based frailty. Results: Both claims-based and survey-based models showed moderate discrimination. The c-statistic of the standardized frailty models ranged from 0.67 (for any hospitalization) to 0.84 (for any IADL [instrumental activities of daily living] help). Models using administrative data ranged from 0.71 (for any hospitalization) to 0.81 (for any IADL help). Discussion: Models based on existing administrative data appear to be as discriminate as survey-based models. Health care providers and insurance plans can effectively apply existing data resources to help identify high-risk individuals for potential care management interventions.

Characteristics of Medicare Beneficiaries With Intellectual or Developmental Disabilities

2019 ◽  
Vol 57 (5) ◽  
pp. 405-420 ◽  
Author(s):  
Amanda Reichard ◽  
Elsa Haile ◽  
Andrew Morris
Keyword(s):  
Developmental Disabilities ◽  
Health Outcomes ◽  
High Rate ◽  
Administrative Claims ◽  
Fee For Service ◽  
Medicare Beneficiaries ◽  
Physical And Mental Health ◽  
Critical Gap ◽  
Health Care Coordination ◽  
Disability Group

Gaps in knowledge and systematic tracking of the prevalence of intellectual and developmental disabilities (IDD) and characteristics that may affect the health of this disability group limits our ability to address the health disparities they experience in comparison to people without disability. The purpose of this study is to begin to fill one relevant critical gap in knowledge: understanding the demographics and health outcomes of adults with IDD who receive services under Medicare Fee-for-Service (FFS), many of who are also eligible for Medicaid. Using 2016 Medicare administrative claims, we examined the prevalence and characteristics of five diagnosis groups of IDD, in those under 65 and those 65 and over, as well as their health outcomes. We found that the IDD Medicare FFS group had high prevalence rates for chronic physical and mental health conditions, overuse of emergency departments, and high rate of 30-day readmission. These findings highlight the need for evidence-based health care coordination, improved and increased public health interventions, and continued surveillance.

scholarly journals Validation of a Parkinson Disease Predictive Model in a Population-Based Study

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Irene M. Faust ◽  
Brad A. Racette ◽  
Susan Searles Nielsen
Keyword(s):  
Parkinson Disease ◽  
Predictive Model ◽  
Sensitivity And Specificity ◽  
Claims Data ◽  
Cox Regression ◽  
Control Sample ◽  
Population Based ◽  
Case Control ◽  
Administrative Claims ◽  
Medicare Beneficiaries

Parkinson disease (PD) has a relatively long prodromal period that may permit early identification to reduce diagnostic testing for other conditions when patients are simply presenting with early PD symptoms, as well as to reduce morbidity from fall-related trauma. Earlier identification also could prove critical to the development of neuroprotective therapies. We previously developed a PD predictive model using demographic and Medicare claims data in a population-based case-control study. The area under the receiver-operating characteristic curve (AUC) indicated good performance. We sought to further validate this PD predictive model. In a randomly selected, population-based cohort of 115,492 Medicare beneficiaries aged 66–90 and without PD in 2009, we applied the predictive model to claims data from the prior five years to estimate the probability of future PD diagnosis. During five years of follow-up, we used 2010–2014 Medicare data to determine PD and vital status and then Cox regression to investigate whether PD probability at baseline was associated with time to PD diagnosis. Within a nested case-control sample, we calculated the AUC, sensitivity, and specificity. A total of 2,326 beneficiaries developed PD. Probability of PD was associated with time to PD diagnosis (p<0.001, hazard ratio = 13.5, 95% confidence interval (CI) 10.6–17.3 for the highest vs. lowest decile of probability). The AUC was 83.3% (95% CI 82.5%–84.1%). At the cut point that balanced sensitivity and specificity, sensitivity was 76.7% and specificity was 76.2%. In an independent sample of additional Medicare beneficiaries, we again applied the model and observed good performance (AUC = 82.2%, 95% CI 81.1%–83.3%). Administrative claims data can facilitate PD identification within Medicare and Medicare-aged samples.

scholarly journals Use of Medicare Claims to Rank Hospitals by Surgical Site Infection Risk following Coronary Artery Bypass Graft Surgery

2011 ◽  
Vol 32 (8) ◽  
pp. 775-783 ◽  
Author(s):  
Susan S. Huang ◽  
Hilary Placzek ◽  
James Livingston ◽  
Allen Ma ◽  
Fallon Onufrak ◽  
...  
Keyword(s):  
Coronary Artery ◽  
Surgical Site Infection ◽  
Coronary Artery Bypass ◽  
Claims Data ◽  
Artery Bypass ◽  
Bypass Graft ◽  
Fee For Service ◽  
Site Infection ◽  
Medicare Beneficiaries ◽  
Assess Quality

Objective.To evaluate whether longitudinal insurer claims data allow reliable identification of elevated hospital surgical site infection (SSI) rates.Design.We conducted a retrospective cohort study of Medicare beneficiaries who underwent coronary artery bypass grafting (CABG) in US hospitals performing at least 80 procedures in 2005. Hospitals were assigned to deciles by using case mix–adjusted probabilities of having an SSI-related inpatient or outpatient claim code within 60 days of surgery. We then reviewed medical records of randomly selected patients to assess whether chart-confirmed SSI risk was higher in hospitals in the worst deciles compared with the best deciles.Participants.Fee-for-service Medicare beneficiaries who underwent CABG in these hospitals in 2005.Results.We evaluated 114,673 patients who underwent CABG in 671 hospitals. In the best decile, 7.8% (958/12,307) of patients had an SSI-related code, compared with 24.8% (2,747/11,068) in the worst decile (P<.001). Medical record review confirmed SSI in 40% (388/980) of those with SSI-related codes. In the best decile, the chart-confirmed annual SSI rate was 3.2%, compared with 9.4% in the worst decile, with an adjusted odds ratio of SSI of 2.7 (confidence interval, 2.2–3.3; P<.001) for CABG performed in a worst-decile hospital compared with a best-decile hospital.Conclusions.Claims data can identify groups of hospitals with unusually high or low post-CABG SSI rates. Assessment of claims is more reproducible and efficient than current surveillance methods. This example of secondary use of routinely recorded electronic health information to assess quality of care can identify hospitals that may benefit from prevention programs.

Sign in / Sign up

Export Citation Format

Share Document