Medicare characteristics, treatment, cost and survival in triple class exposed relapsed or refractory multiple myeloma.

Background: This study describes real-world treatment patterns of Medicare beneficiaries with relapsed or refractory multiple myeloma (RRMM) who are triple class exposed (TCE). Materials & methods: Retrospective analysis of Medicare fee for service claims to identify a cohort age >65 with RRMM + TCE, 1 January 2016 to 30 June 2019. Outcomes: Initiation of a new treatment regimen (TCE1), healthcare resource utilization, cost and mortality. Results: Of 5395 patients with RRMM + TCE, 1672 (31.0%) initiated a new therapy (TCE1). During TCE1, 97 TCE1 drug combinations were observed and RRMM treatments were the largest cost driver. Median time to TCE1 discontinuation was 3.3 months. Few patients received subsequent treatment and 41.3% of study patients died. Conclusion: There is no clear standard-of-care for Medicare patients with RRMM + TCE and prognosis remains poor.

This research study describes outcomes in older Medicare patients with relapse or refractory multiple myeloma (RRMM) who failed three different classes of treatment (triple class exposed [TCE]) between 2016 and 2019. The authors utilized data from Medicare to follow patients who started a new treatment after TCE (this group was labeled 'TCE1'), and this article describes their cancer treatment, hospitalizations, emergency department visits, physician visits, costs of care, and length of survival. The authors identified 5395 Medicare patients with RRMM + TCE during the study period, of which 1672 (31.0%) started a new therapy and were considered TCE1. Patients were 75.6 years old, on average, when they started TCE1 treatment. The authors observed 97 different TCE1 drug combinations, and 50% of patients discontinued TCE1 treatment within 3 months. Few patients received additional treatment, and 41.3% of study patients died during the study period. More than 90% of healthcare costs were related to cancer care (rather than management of other conditions). There is no clear standard-of-care for older Medicare patients with RRMM + TCE, and prognosis remains poor.

The Increased Clinical and Economic Burden of Hyperkalemia in Medicare Patients Admitted to Long-Term Care Settings.

INTRODUCTION: Older patients are at increased risk for hyperkalemia (HK). This study describes the prevalence, recurrence, and clinical and economic burden of HK in Medicare patients admitted to a long-term care (LTC) setting. METHODS: Retrospective cohort study using 100% Medicare Fee-for-Service (FFS) claims identified patients aged ≥ 65 years with index admission between 2017 and 2019 to a LTC setting (skilled nursing, home health, inpatient rehabilitation, or long-term acute care). Beneficiaries were required to have 12 months continuous medical and pharmacy coverage prior to index LTC admission and ≥ 30 days after LTC discharge (follow-up). Patient characteristics, healthcare resource utilization, and costs were assessed. HK was defined as ICD-10 diagnosis code E87.5 in any claim position or Medicare Part D fill for oral potassium binder. RESULTS: Of 4,562,231 patients with a LTC stay, the prevalence of HK was 14.7% over the full study period (pre-index, index stay, and follow-up). Excluding those with HK only during the follow-up period resulted in 4,081,103 patients. Of these, 290,567 (7.1%) had HK and 3,790,536 (92.9%) did not have HK during or within 14 days prior to index LTC stay. The HK recurrence rate during index stay and follow-up was 48.3%. Unmatched HK versus non-HK patients were more often male (43.0% vs. 35.4%), Black (13.5% vs. 8.0%), dual eligible for Medicaid (34.2% vs. 25.0%), with higher mean Charlson Comorbidity Index scores (6.2 vs. 3.9) (all p < 0.0001). After propensity matching, HK patients were 2.2 times more likely to be hospitalized, with higher mortality (30.8% vs. 21.5%) and higher total healthcare costs during both index stay (US$26,520 vs. $18,021; p < 0.0011) and follow-up ($57,948 vs. $41,744 (p < 0.0011) versus matched non-HK patients. CONCLUSION: Prevalence and recurrence of HK was high among LTC patients, and HK was associated with significantly greater clinical and economic burden during and post-LTC.

Hyperkalemia is a serious medical condition commonly occurring in nursing home residents. It is characterized by abnormally high blood levels of potassium that if untreated can be life-threatening. High levels of potassium can be the result of kidney disease and inability to remove potassium from the bloodstream; eating foods high in potassium; and/or taking medications that interfere with the kidney's ability to remove potassium from the bloodstream. Older patients who have chronic kidney disease, heart failure, diabetes, and high blood pressure are at particularly high risk for hyperkalemia. Management is difficult as it requires reducing intake of foods high in potassium, adjusting medications that cause hyperkalemia, and potentially treating with oral potassium binders to reduce potassium blood levels. This study focused on the clinical outcomes, healthcare services use, and costs incurred by Medicare beneficiaries 65 years and older admitted to long-term care, where the occurrence of hyperkalemia is often high yet unrecognized. Patients with a diagnosis of hyperkalemia immediately before and during admission to long-term care or after discharge had an increased rate of death compared with patients without a hyperkalemia diagnosis. Hyperkalemia patients also had more hospitalizations and visits to the Emergency Department and outpatient facilities, resulting in higher total medical costs. Total costs for hyperkalemia patients were highest for those with chronic kidney disease, heart failure, and diabetes.

Risk factors and costs associated with 30-day readmissions following alcohol-related hospitalizations in the United States from 2010 to 2015.

Patients with alcohol-related diagnoses at initial hospitalization are at high risk of 30-day readmission. Understanding risk factors for 30-day readmission among these patients may help to identify those who would benefit from efforts to reduce risk of readmission. The Nationwide Readmissions Database was used to estimate 30-day all-cause readmissions among United States patients with an alcohol-related index hospitalization and to evaluate risk factors and costs associated with these readmissions. Included patients were 18 years of age or older at initial hospitalization, had an alcohol-related primary diagnosis (based on ICD-9-CM codes), and were discharged between 2010 and 2015. They were followed for 30 days after initial hospitalization within the calendar year to identify all-cause readmissions. A logistic regression analysis assessed the association between risk factors and 30-day readmission. Average costs of initial admissions and readmissions were estimated. Among 113,931,723 adult index hospitalizations, 1,124,228 had alcohol-related diagnoses. Patients had a mean age of 49 years, 73% were male, and 45% had public insurance coverage. The annual rate of 30-day readmissions among patients with index alcohol-related hospitalizations increased from 119 readmissions per 1000 admissions in 2010 to 140 per 1000 in 2015, while the rate of readmissions among patients with all-cause hospitalizations declined from 103 to 98 per 1000. The regression analysis suggested that age, male sex, comorbid conditions, discharge against medical advice, admission to large and teaching hospitals, and Medicaid vs. non-Medicaid payment were all risk factors for 30-day readmission. Mean costs of initial alcohol-related hospitalizations were greater among those with a 30-day readmission than without a 30-day readmission, and the mean cost of 30-day readmission was even greater. Mitigating the upward trend in rates of readmission following alcohol-related initial hospitalizations may be addressed through better identification of high-risk patients who are admitted with an alcohol-related diagnosis and greater use of existing evidence-based psychosocial and pharmacotherapy treatment methods.

The economic burden of kidney graft failure in the United States.

Despite improvements in outcomes for kidney transplant recipients in the past decade, graft failure continues to impose substantial burden on patients. However, the population-wide economic burden of graft failure has not been quantified. This study aims to fill that gap by comparing outcomes from a simulation model of kidney transplant patients in which patients are at risk for graft failure with an alternative simulation in which the risk of graft failure is assumed to be zero. Transitions through the model were estimated using Scientific Registry of Transplant Recipients data from 1987 to 2017. We estimated lifetime costs, overall survival, and quality-adjusted life-years (QALYs) for both scenarios and calculated the difference between them to obtain the burden of graft failure. We find that for the average patient, graft failure will impose additional medical costs of $78 079 (95% confidence interval [CI] $41 074, $112 409) and a loss of 1.66 QALYs (95% CI 1.15, 2.18). Given 17 644 kidney transplants in 2017, the total incremental lifetime medical costs associated with graft failure is $1.38B (95% CI $725M, $1.98B) and the total QALY loss is 29 289 (95% CI 20 291, 38 464). Efforts to reduce the incidence of graft failure or to mitigate its impact are urgently needed.

The long-term social value of granulocyte colony-stimulating factors.

OBJECTIVES: Febrile neutropenia (FN) is a life-threatening complication of chemotherapy that can lead to hospitalizations, chemotherapy dose reductions or delays, and mortality. Granulocyte colony-stimulating factor (G-CSF) prophylaxis reduces the incidence of FN, enabling patients to undergo and remain on myelosuppressive chemotherapy. We estimate the benefits of continuing current G-CSF use patterns and an alternative that aligns prophylactic G-CSF use with guideline recommendations. STUDY DESIGN: Using The Health Economics Medical Innovation Simulation microsimulation, we estimated lifetime social value (SV) of prophylactic G-CSF for a nationally representative US population with breast, lung, and gynecological cancers and non-Hodgkin lymphoma. METHODS: SV estimates included the cost of G-CSF, FN, chemotherapy relative dose intensity (RDI) less than 85% (RDI<85%), medical spending, and deaths for 3 scenarios: current use (current G-CSF use), targeted use (100% G-CSF use among patients with high FN risk), and reduced use (current G-CSF use reduced by 20% across all FN risk categories). RESULTS: Over 10 years, current use, compared with no G-CSF use, would decrease cases of FN by 3.3 million, prevent 354,000 cases of RDI<85%, and generate $96 billion in SV. Compared with current use, targeted use would decrease cases of FN by an additional 3.3 million, prevent 355,000 more cases of RDI<85%, and generate another $119 billion in SV. Reduced use would increase FN and RDI<85%, lowering SV by $18 billion compared with current use. CONCLUSIONS: Current use of G-CSF prophylaxis would provide $96 billion in SV over the next 10 years. Targeting G-CSF prophylaxis to align with guidelines would more than double SV, highlighting the substantial value of appropriate FN risk assessment and targeted G-CSF prophylaxis.

Using Information on Patient Adherence to Antipsychotic Medication to Understand Their Adherence to Other Medications.

PURPOSE: To assess how patient adherence to atypical antipsychotic medications is associated with adherence to concurrently used medications that treat other serious mental illnesses (SMIs), type-2 diabetes, or hypertension. METHODS: Among patients who had been diagnosed with an SMI (i.e., bipolar disorder, major depressive disorder, or schizophrenia) in the previous year, we used health-insurance claims data to measure adherence based on medication fills. Patients diagnosed with an SMI were required to have 1) a prescription for an atypical oral antipsychotic, and 2) another SMI therapy or oral anti-diabetic or antihypertensive agent in the same year. The patient's concurrent adherence to an antipsychotic and one of 23 other medications was measured by the proportion of days covered (PDC) over a one-year period. Patients were considered adherent when the PDC was ≥ 80%. The strength of the association between their atypical antipsychotic adherence and their concurrent medication adherence was evaluated using the following metrics: accuracy, positive predictive value (PPV), and negative predictive value (NPV). RESULTS: The average (standard deviation) age of patients (N = 129,614) was 44.8 (14.8) years and 62.2% of patients were female. The median accuracy based on atypical antipsychotic adherence to the other 23 medications was 67% (range, 55-71%; statistically different from 50% accuracy in all cases, P < 0.001). Accuracy was higher than physician predictions of adherence from previous studies (53%). The negative predictive value of antipsychotic adherence (75%; range, 62-88%) was generally higher than the PPV (62%; range, 43-67%; all, P < 0.001). CONCLUSION: Information on patient adherence to antipsychotics provides significant insight into adherence to other medications often used by patients with SMI. Because NPV is higher than PPV, adherence to antipsychotics is likely to be a necessary but not sufficient condition for patients with SMI regarding adherence to non-SMI medications.

Association Between State Medicaid Eligibility Thresholds and Deaths Due to Substance Use Disorders.

Importance: The United States is currently facing an epidemic of deaths related to substance use disorder (SUD), with totals exceeding those due to motor vehicle crashes and gun violence. The epidemic has led to decreased life expectancy in some populations. In recent years, Medicaid eligibility has expanded in some states, and the association of this expansion with SUD-related deaths is yet to be examined. Objective: To examine the association between eligibility thresholds for state Medicaid coverage and SUD-related deaths. Design, Setting, and Participants: Economic evaluation study using a retrospective analysis of state-level data between 2002 and 2015 to determine the association between the Medicaid eligibility threshold and SUD-related deaths, controlling for other relevant policies, state socioeconomic characteristics, fixed effects, and a time trend. Policy variables were lagged by 1 year to allow time for associations to materialize. Data were collected and analyzed from 2016 to 2017. Exposures: The policy of interest was the state Medicaid eligibility threshold, ie, the highest allowed income that qualifies a person for Medicaid, expressed as a percentage of the federal poverty level. State policies related to mental health, overdose treatment, and law enforcement of drug crimes were included as controls. Main Outcomes and Measures: The primary outcome was number of SUD-related deaths, obtained from data provided by the Centers for Disease Control and Prevention. Results: Across 700 state-year observations, the mean (SD) number of SUD-related deaths was 21.15 (6.05) per 100 000 population. Between 2002 and 2015, the national SUD-related death rate increased from 16.0 to 27.5 per 100 000, while the average Medicaid eligibility threshold increased from 87.2% to 97.1% of the federal poverty level. Over this period, every 100-percentage point increase in the Medicaid eligibility threshold (eg, from 50% to 150% of the federal poverty level) was associated with 1.373 (95% CI, -2.732 to -0.014) fewer SUD-related deaths per 100 000 residents, a reduction of 6.50%. In the 22 states with net contractions in eligibility thresholds between 2005 and 2015, an estimated increase of 570 SUD-related deaths (95% CI, -143 to 1283) occurred. In the 28 states that increased eligibility thresholds, an estimated 1045 SUD-related deaths (95% CI, -209 to 2299) may have been prevented. Conclusions and Relevance: These findings suggest that the overall increase in SUD-related deaths between 2002 and 2015 may have been greater had the average eligibility threshold for Medicaid not increased over this period. Broader eligibility for Medicaid coverage may be one tool to help reduce SUD-related deaths.

Short-term budget affordability of hepatitis C treatments for state Medicaid programs.

BACKGROUND: With some Medicaid state programs still restricting patient access to hepatitis C (HCV) treatment, it is important to demonstrate how states could expand treatment access to a broader Medicaid population and balance short-term budget concerns. METHODS: We used the HCV Transmission and Progression (TaP) Markov model to quantify the impact of removing restrictions to HCV treatment access on the infected populations, expenditures, and net social value for the North Carolina (NC), Oregon (OR), and Wisconsin (WI) Medicaid programs. Four HCV treatment access scenarios were modeled: 1) Baseline: Patients were treated according to Medicaid disease severity and sobriety requirements in 2015; 2) Remove Sobriety Restrictions: Disease severity restrictions were maintained, but people who inject drugs (PWID) were given access to treatment; 3) Treat Early: All patients, except for PWIDs, regardless of disease severity, were eligible for treatment and the diagnosis rate increased from 50 to 66%; and 4) Remove Access Restrictions: all patients, regardless of disease severity and sobriety, were eligible for treatment. Our key model outputs were: number of infected Medicaid beneficiaries, HCV-related medical and treatment expenditures, total social value, and state Medicaid spending over 10 years. RESULTS: Across all three states, removing access restrictions resulted in the greatest benefits over 10 years (net social value relative to baseline = $408 M in NC; $408 M in OR; $271 M in WI) and the smallest infected population (5200 in NC; 2000 in OR; 614 in WI). Reduced disease transmission resulted in lower health care expenditures (-$66 M in NC; -$50 M in OR; -$54 M in WI). All of the expanded treatment access policies achieved break-even costs-where total treatment and health care expenditures fell below those of Baseline-in 4 to 8 years. Removing access restrictions yielded the greatest improvement in social value (net of medical expenditures and treatment costs, QALYs valued at $150 K per QALY). CONCLUSIONS: While increasing treatment access in Medicaid will raise short-term costs, it will also provide clear benefits relatively quickly by saving money and improving health within a 10-year window. Patients and taxpayers would benefit by considering these gains and taking a more expansive and long-term view of HCV treatment policies.

Medication Adherence Patterns Among Patients with Multiple Serious Mental and Physical Illnesses.

INTRODUCTION: Patients with mental and physical health conditions are complex to treat and often use multiple medications. It is unclear how adherence to one medication predicts adherence to others. A predictive relationship could permit less expensive adherence monitoring if overall adherence could be predicted through tracking a single medication. METHODS: To test this hypothesis, we examined whether patients with multiple mental and physical illnesses have similar adherence trajectories across medications. Specifically, we conducted a retrospective cohort analysis using health insurance claims data for enrollees who were diagnosed with a serious mental illness, initiated an atypical antipsychotic, as well as an SSRI (to treat serious mental illness), biguanides (to treat type 2 diabetes), or an ACE inhibitor (to treat hypertension). Using group-based trajectory modeling, we estimated adherence patterns based on monthly estimates of the proportion of days covered with each medication. We measured the predictive value of the atypical antipsychotic trajectories to adherence predictions based on patient characteristics and assessed their relative strength with the R-squared goodness of fit metric. RESULTS: Within our sample of 431,591 patients, four trajectory groups were observed: non-adherent, gradual discontinuation, stop-start, and adherent. The accuracy of atypical antipsychotic adherence for predicting adherence to ACE inhibitors, biguanides, and SSRIs was 44.5, 44.5, and 49.6%, respectively (all p < 0.001 vs. random). We also found that information on patient adherence patterns to atypical antipsychotics was a better predictor of patient adherence to these three medications than would be the case using patient demographic and clinical characteristics alone. CONCLUSION: Among patients with multiple chronic mental and physical illnesses, patterns of atypical antipsychotic adherence were useful predictors of adherence patterns to a patient's adherence to ACE inhibitors, biguanides, and SSRIs. FUNDING: Otsuka Pharmaceutical Development & Commercialization, Inc.