The economic burden of switching targeted disease-modifying anti-rheumatic drugs among rheumatoid arthritis patients

Aims: To estimate real world healthcare costs and resource utilization of rheumatoid arthritis (RA) patients associated with targeted disease modifying anti-rheumatic drugs (tDMARD) switching in general and switching to abatacept specifically.

Materials and methods: RA patients initiating a tDMARD were identified in IMS PharMetrics Plus health insurance claims data (2010–2016), and outcomes measured included monthly healthcare costs per patient (all-cause, RA-related) and resource utilization (inpatient stays, outpatient visits, emergency department [ED] visits). Generalized linear models were used to assess (i) average monthly costs per patient associated with tDMARD switching, and (ii) among switchers only, costs of switching to abatacept vs tumor necrosis factor inhibitors (TNFi) or other non-TNFi. Negative binomial regressions were used to determine incident rate ratios of resource utilization associated with switching to abatacept.

Results: Among 11,856 RA patients who initiated a tDMARD, 2,708 switched tDMARDs once and 814 switched twice (to a third tDMARD). Adjusted average monthly costs were higher among patients who switched to a second tDMARD vs non-switchers (all-cause: $4,785 vs $3,491, p?p?p?p?=?.021), and numerically lower all-cause costs ($4,444 vs $4,741, p?=?0.188). Switchers to TNFi relative to abatacept had more frequent inpatient stays after switch (incidence rate ratio (IRR) = 1.85, p?=?.031), and numerically higher ED visits (IRR = 1.32, p?=?.093). Outpatient visits were less frequent for TNFi switchers (IRR = 0.83, p?Limitations and conclusions: Switching to another tDMARD was associated with higher healthcare costs. Switching to abatacept, however, was associated with lower RA-related costs, fewer inpatient stays, but more frequent outpatient visits compared to switching to a TNFi.     

Major bleeding risk and healthcare economic outcomes of non-valvular atrial fibrillation patients newly-initiated with oral anticoagulant therapy in the real-world setting

Aims: This study compared the risk for major bleeding (MB) and healthcare economic outcomes of patients with non-valvular atrial fibrillation (NVAF) after initiating treatment with apixaban vs rivaroxaban, dabigatran, or warfarin.

Methods: NVAF patients who initiated apixaban, rivaroxaban, dabigatran, or warfarin were identified from the IMS Pharmetrics Plus database (January 1, 2013–September 30, 2015). Propensity score matching (PSM) was used to balance differences in patient characteristics between study cohorts: patients treated with apixaban vs rivaroxaban, apixaban vs dabigatran, and apixaban vs warfarin. Risk of hospitalization and healthcare costs (all-cause and MB-related) were compared between matched cohorts during the follow-up.

Results: During the follow-up, risks for all-cause (hazard ratio [HR]?=?1.44, 95% confidence interval [CI]?=?1.2–1.7) and MB-related (HR?=?1.57, 95% CI?=?1.0–2.4) hospitalizations were significantly greater for patients treated with rivaroxaban vs apixaban. Adjusted total all-cause healthcare costs were significantly lower for patients treated with apixaban vs rivaroxaban ($3,950 vs $4,333 per patient per month [PPPM], p?=?.002) and MB-related medical costs were not statistically significantly different ($100 vs $233 PPPM, p?=?.096). Risk for all-cause hospitalization (HR?=?1.98, 95% CI?=?1.6–2.4) was significantly greater for patients treated with dabigatran vs apixaban, although total all-cause healthcare costs were not statistically different. Risks for all-cause (HR?=?2.22, 95% CI?=?1.9–2.5) and MB-related (HR?=?2.05, 95% CI?=?1.4–3.0) hospitalizations were significantly greater for patients treated with warfarin vs apixaban. Total all-cause healthcare costs ($3,919 vs $4,177 PPPM, p?=?.025) and MB-related medical costs ($96 vs $212 PPPM, p?=?.026) were significantly lower for patients treated with apixaban vs warfarin.

Limitations: This retrospective database analysis does not establish causation.

Conclusions: In the real-world setting, compared with rivaroxaban and warfarin, apixaban is associated with reduced risk of hospitalization and lower healthcare costs. Compared with dabigatran, apixaban is associated with lower risk of hospitalizations.     

Impact of completing chronic hepatitis C (CHC) treatment on post-therapy healthcare cost

Background:

Chronic hepatitis C (CHC) is associated with significant economic burden. This study evaluated the healthcare cost alleviation associated with treatment of CHC.

Methods:

Health insurance claims from 60 self-insured US companies were analyzed (01/2001–03/2012). Adult patients with ≥1 CHC diagnosis (ICD-9-CM: 070.44, 070.54), initiating interferon, and with ≥2 dispensings and with ≥48 weeks of follow-up were selected. Patients diagnosed with HIV or who completed only 24 weeks of interferon therapy (a surrogate for CHC genotypes 2 and 3) were excluded from the study. Interferon users were categorized into complete and discontinued therapy cohorts. During the post–48-week treatment period, cohorts were compared for healthcare resource utilization using rate ratios (RRs), as well as healthcare costs using per-patient per-year (PPPY) cost differences.

Results:

A total of 1017 patients who completed and 953 patients who discontinued interferon therapy were identified. Relative to the discontinued therapy cohort, the completed therapy cohort had significantly fewer hospitalizations (RR [95% CI]?=?0.74 [0.68, 0.81], p?p?p?=?0.039), which translated into significantly lower total healthcare costs PPPY (cost difference [95% CI]?=?$4540 [1570, 7680], p?=?0.004) and hospitalization costs (cost difference [95% CI]?=?$3039 [1140, 5248], p?=?0.002). Non–CHC-related costs accounted for 55% and CHC-related costs for 45% of the all-cause cost difference between cohorts.

Limitations:

Claims data may have contained inaccuracies, and genotypes of patients with CHC could not be confirmed. The study consisted of privately insured individuals and may not be generalizable to the entire CHC population.

Conclusion:

Compared to discontinued therapy patients, CHC patients who completed interferon therapy and presumably had a higher rate of achieving SVR were found to have lower levels of healthcare resource utilization and costs post-therapy. The reduction was primarily in costs associated with non–HCV-related comorbidities.     

Healthcare costs in patients with advanced non-small cell lung cancer and disease progression during targeted therapy: a real-world observational study

Aims: To assess healthcare costs during treatment with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) and following disease progression in patients with advanced non-small cell lung cancer (NSCLC).

Methods: A retrospective analysis of medical records of US community oncology practices was conducted. Eligible patients had advanced NSCLC (stage IIIB/IV) diagnosed between January 1, 2008 and January 1, 2015, initiated treatment with erlotinib or afatinib (first-line or second-line), and had disease progression. Monthly Medicare-paid costs were evaluated during the TKI therapy period and following progression.

Results: The study included 364 patients. The total mean monthly cost during TKI therapy was $20,106 (95% confidence interval [CI]?=?$16,836–$23,376), of which 47.0% and 42.4% represented hospitalization costs and anti-cancer therapy costs, respectively. Following progression on TKI therapy (data available for 316 patients), total mean monthly cost was $19,274 (95% CI?=?$15,329–$23,218), and was higher in the 76.3% of patients who received anti-cancer therapy following progression than in the 23.7% of those who did not ($20,490 vs $15,364; p?<?.001). Among patients who received it, anti-cancer therapy ($11,198; 95% CI?=?$7,102–$15,295) represented 54.7% of total mean monthly cost. Among patients who did not receive anti-cancer therapy, hospitalization ($13,829; 95% CI?=?$4,922–$22,736) represented 90.0% of total mean monthly cost. Impaired performance status and brain metastases were significant predictors of increased cost during TKI therapy.

Limitations: The study design may limit the generalizability of findings.

Conclusions: Healthcare costs during TKI treatment and following progression appeared to be similar and were largely attributed to hospitalization and anti-cancer therapy. Notably, almost one-quarter of patients did not receive anti-cancer therapy following progression, potentially indicating an unmet need; hospitalization was the largest cost contributor for these patients. Additional effective targeted therapies are needed that could prolong progression-free survival, leading to fewer hospitalizations for EGFR mutation-positive patients.     

A comparison of treatment patterns,healthcare resource utilization,and costs among young adult Medicaid beneficiaries with schizophrenia treated with paliperidone palmitate or oral atypical antipsychotics in the US

Abstract

Background: Much of the burden associated with schizophrenia is attributed to its early onset and chronic nature. Treatment with once monthly paliperidone palmitate (PP1M) is associated with lower healthcare utilization and better adherence as compared to oral atypical antipsychotics (OAAs). This study aimed to evaluate real-world effectiveness of PP1M and OAA therapies among US-based adult Medicaid patients with schizophrenia, overall and among young adults aged 18–35 years.

Methods: Adult patients with a diagnosis of schizophrenia and at least two claims for PP1M or OAA between January 1, 2010 and December 31, 2014 were selected from the IBM Watson Health MarketScan Medicaid Database. Treatment patterns and healthcare resource utilization and costs were compared between PP1M and OAA treatment groups following inverse probability of treatment (IPT) weighting to adjust for potential differences. Utilization and cost outcomes were estimated using OLS and weighted Poisson regression models.

Results: After IPT weighting, the young adult PP1M and OAA cohorts were comprised of 3,095 and 3,155 patients, respectively. PP1M patients had a higher duration of continuous treatment exposure (168.2 vs 132.5 days, p?=?.004) and better adherence on the index medication (proportion of days covered ≥80%: 19.0% vs 17.1%, p?<?.049). Young adults treated with PP1M were 37% less likely to have an all-cause inpatient admission (odds ratio [OR]?=?0.63, 95% confidence interval [CI]?=?0.53–0.74) and 33% less likely to have an ER visit (OR?=?0.67, 95% CI?=?0.55–0.81) compared to OAA young adult patients, but 27% more likely to have an all-cause outpatient office visit (OR?=?1.27, 95% CI?=?1.02–1.56). PP1M patients incurred significantly lower medical costs as compared to OAA patients.

Conclusions: Medicaid patients with schizophrenia treated with PP1M have higher medication adherence and have fewer hospitalizations as compared to patients treated with OAAs. PP1M may lead to reduced healthcare utilization and improved clinical outcomes.     

Using observational analysis of multiple sclerosis relapse to design outcomes-based contracts for disease-modifying drugs: a feasibility assessment

Abstract

Objective:

To assess predictors and costs of multiple sclerosis (MS) relapse, a potential outcome measure in payer-manufacturer risk-sharing agreements for disease-modifying drugs (DMDs).

Methods:

A retrospective cohort analysis of medical/pharmacy claims was used. Study patients had ≥1 DMD (interferon beta, glatiramer, natalizumab) claim, without DMD claims in a 6-month pre-period before DMD initiation; were aged 18–64 years and continuously enrolled from the pre-period through a 24-month post-period; and had ≥2 MS medical claims during the 30-month study period. Post-period relapse cohorts included: (1) severe (hospitalization with MS diagnosis); (2) moderate (outpatient services including intravenous methylprednisolone); and (3) none. Poisson regression modeled severe relapse frequency, logistic regression modeled ≥1 severe relapse, and generalized linear modeling predicted healthcare costs. Tested predictors included demographics, insurance type, index DMD, pre-period health status, and DMD medication possession ratio (MPR).

Results:

Severe relapse was experienced by 14.5% and moderate relapse by 13.8% of 2291 patients. In logistic regression, severe relapse was predicted by plan type; age (odds ratio [OR]?=?1.018, 95% confidence interval [CI]?=?1.005–1.031); pre-period Charlson Comorbidity Index (OR?=?1.307, 95% CI?=?1.166–1.464); pre-period proxy measure indicating impaired activities of daily living (OR?=?1.470, 95% CI?=?1.134–1.905); pre-period MS hospitalization (OR?=?2.174, 95% CI?=?1.537–3.074); and DMD non-adherence (MPR OR?=?0.101, 95% CI?=?0.068–0.151). Poisson regression results were similar. Predicted mean [standard deviation] all-cause healthcare expenditures were tripled for patients with severe compared with moderate relapse ($48,173 [$8665] and $13,334 [$1929], respectively).

Limitations:

Commercially insured patients from a single payer; use may have been inconsistent with approved indications; proxy relapse measure may have misclassified patients.

Conclusions:

Severe MS relapses requiring hospitalization, although affecting less than 15% of patients initiating DMD treatment, are associated with high medical costs. The only actionable predictor of severe relapse identified in observational analysis was MPR, raising questions about the feasibility of using observational data to guide outcomes-based contracting.     

Switching of biologic disease modifying anti-rheumatic drugs in patients with rheumatoid arthritis in a real world setting

Objectives:

This study examined total healthcare costs and rates of patients with rheumatoid arthritis (RA) who switch biologic disease-modifying anti-rheumatic drug (bDMARD) therapy in a real world setting.

Methods:

A retrospective longitudinal analysis was conducted in patients with RA using IMS PharMetrics Plus database from 1/1/2004 to 3/31/2010. The first-line cohort included patients newly initiated on abatacept or the tumor necrosis factor-alpha inhibitors (anti-TNFs) adalimumab, etanercept, or infliximab, with 12 months of continuous follow-up. The second-line cohort included patients initiating a bDMARD with evidence of a different bDMARD within the previous 2 years and with 12 months of continuous follow-up. Switching was defined as a different bDMARD claim within a 200% gap in days supply from the previous bDMARD claim. Non-switchers stayed on their bDMARD in the follow-up period. Monthly total healthcare costs for switchers and non-switchers and rates of bDMARD switching were examined. Switch rates for each bDMARD were also compared.

Results:

First-line switchers had significantly higher monthly total healthcare costs after the switch than non-switchers ($3759 vs $2343; p?p?Limitations:

There are no clinical data available in this database and, therefore, this study did not examine the clinical drivers of healthcare costs and switch rates.

Conclusions:

Monthly total healthcare costs were higher for bDMARD switchers following the switch compared to non-switchers. Patients on abatacept switched less frequently than patients on anti-TNFs. This study highlights the need to identify patients who are likely to switch in order to ensure they receive the appropriate therapy which may improve outcomes and decrease healthcare costs.     

Real-world comparison of all-cause hospitalizations,hospitalizations due to stroke and major bleeding,and costs for non-valvular atrial fibrillation patients prescribed oral anticoagulants in a US health plan

Aims: To compare the risk of all-cause hospitalization and hospitalizations due to stroke/systemic embolism (SE) and major bleeding, as well as associated healthcare costs for non-valvular atrial fibrillation (NVAF) patients initiating apixaban, dabigatran, rivaroxaban, or warfarin.

Materials and methods: NVAF patients initiating apixaban, dabigatran, rivaroxaban, or warfarin were selected from the OptumInsight Research Database from January 1, 2013–September 30, 2015. Propensity score matching (PSM) was performed between apixaban and each oral anticoagulant. Cox models were used to estimate the risk of stroke/SE and major bleeding. Generalized linear and 2-part models were used to compare healthcare costs.

Results: Of the 47,634 eligible patients, 8,328 warfarin-apixaban pairs, 3,557 dabigatran-apixaban pairs, and 8,440 rivaroxaban-apixaban pairs were matched. Compared to apixaban, warfarin patients were associated with a significantly higher risk of all-cause (hazard ratio [HR]?=?1.30; 95% confidence interval [CI]?=?1.21–1.40) as well as stroke/SE-related (HR?=?1.60; 95% CI?=?1.23–2.07) and major bleeding-related (HR?=?1.95; 95% CI?=?1.60–2.39) hospitalization; rivaroxaban patients were associated with a higher risk of all-cause (HR?=?1.15; 95% CI?=?1.07–1.24) and major bleeding-related hospitalization (HR?=?1.71; 95% CI?=?1.39–2.10); and dabigatran patients were associated with a higher risk of major bleeding hospitalization (HR?=?1.46, 95% CI?=?1.02–2.10). Warfarin patients had significantly higher major bleeding-related and total all-cause healthcare costs compared to apixaban patients. Rivaroxaban patients had significantly higher major bleeding-related costs compared to apixaban patients. No significant results were found for the remaining comparisons.

Limitations: No causal relationships can be concluded, and unobserved confounders may exist in this retrospective database analysis.

Conclusions: This study demonstrated a significantly higher risk of hospitalization (all-cause, stroke/SE, and major bleeding) associated with warfarin, a significantly higher risk of major bleeding hospitalization associated with dabigatran or rivaroxaban, and a significantly higher risk of all-cause hospitalization associated with rivaroxaban compared to apixaban. Lower major bleeding-related costs were observed for apixaban patients compared to warfarin and rivaroxaban patients.     

Subcutaneous vs intravenous rituximab in patients with non-Hodgkin lymphoma: a time and motion study in the United Kingdom

Objective:

Rituximab is part of standard therapy for many non-Hodgkin lymphoma (NHL) patients, and is usually administered as an intravenous (IV) infusion. A formulation for subcutaneous (SC) injection will be available from June 2014. A time and motion study was conducted to investigate the staff time and costs associated with administration of SC and IV rituximab.

Research design and methods:

The time and motion study was conducted in three UK centers alongside a phase III trial of SC rituximab in patients with NHL (ClinicalTrials.gov identifier NCT01461928). Active healthcare professional (HCP) time spent on the preparation and administration of IV and SC rituximab was recorded and used to calculate the associated costs.

Results:

Total active HCP time associated with administration of IV rituximab was 223.3?min (95% CI?=?218.0–228.7), vs 48.5?min (95% CI?=?45.5–51.6) for SC rituximab, a saving of 174.8?min (95% CI?=?172.5–177.1) per session. Patient time in the treatment room was 263.8?min (95% CI?=?236.6–294.3) for IV rituximab and 70.0?min (95% CI?=?57.1–87.2) for SC rituximab, per session. The SC formulation reduced total mean staff costs by £115.17 (95% CI?=?98.95–136.93) per session. Differing monitoring scenarios during infusion consistently showed time and cost savings for SC rituximab.

Limitations:

Study limitations include the non-interventional design and lack of statistical power, and the investigational nature of SC rituximab. The data collected did not account for patient and center characteristics and variability on active HCP time.

Conclusions:

SC rituximab was associated with reduced active HCP time and costs vs IV rituximab, as well as reduced patient time in the treatment room. Switching from IV to SC rituximab could increase treatment room capacity and patient throughput, as well as improving the patient experience.     

The association of pain interference and opioid use with healthcare utilization and costs,and wage loss among adults with osteoarthritis in the United States

Abstract

Aim: To examine associations of opioid use and pain interference with activities (PIA), healthcare resource utilization (HRU) and costs, and wage loss in noninstitutionalized adults with osteoarthritis in the United States (US).

Methods: Adults with osteoarthritis identified from the Medical Expenditure Panel Survey for 2011/2013/2015 were stratified by no-opioid use with no/mild PIA, no-opioid use with moderate/severe PIA, opioid use with no/mild PIA, and opioid use with moderate/severe PIA. Outcomes included annualized total HRU, direct healthcare costs, and wage loss. Multivariable regression analyses were used for comparisons versus no-opioid use with no/mild PIA (referent). The counterfactual recycled prediction method estimated incremental costs. Results reflect weighted nationally representative data.

Results: Of 4,921 participants (weighted n?=?20,785,007), 46.5% had no-opioid use with no/mild PIA; 23.2% had no-opioid use with moderate/severe PIA; 9.6% had opioid use with no/mild PIA; and 20.7% had opioid use with moderate/severe PIA. Moderate/severe PIA and/or opioid use were associated with significantly higher HRU and associated costs, and wage loss. Relative to adults with no/mild PIA, opioid users with moderate/severe PIA were more likely to have hospitalizations, specialist visits, and emergency room visits (all p?<?.001). Relative to the referent, opioid use with no/mild PIA had higher per-patient incremental annual total healthcare costs ($11,672, 95% confidence interval [CI]?=?$11,435–$11,909) and wage loss ($1,395, 95% CI?=?$1,376–$1,414) as did opioid use with moderate/severe PIA ($13,595, 95% CI?=?$13,319–$13,871; and $2,331, 95% CI?=?$2,298–$2,363) (all p?<?.001). Compared with the referent, estimated excess national total healthcare costs/lost wages were $23.3 billion/$1.3 billion for opioid use with no/mild PIA, and $58.5 billion/$2.2 billion for opioid use with moderate/severe PIA.

Limitations: Unobservable/unmeasured factors that could not be accounted for.

Conclusions: Opioid use with moderate/severe PIA had significantly higher HRU, costs, and wage loss; opioid use was more relevant than PIA to the economic burden. These results suggest unmet needs for alternative pain management strategies.     

Healthcare resource utilization and direct costs associated with frequent nausea in episodic migraine: results from the American Migraine Prevalence and Prevention (AMPP) Study

Abstract

Background:

Nausea is a common migraine symptom that is associated with impaired quality-of-life and functional disability. In this study, population-based data were used to elucidate the relationship between nausea frequency and headache-related healthcare utilization and costs in persons with migraine.

Research design and methods:

Participants with episodic migraine who completed the 2009 American Migraine Prevalence and Prevention (AMPP) Study survey rated their headache-related nausea as occurring never, rarely, <half the time, or ≥half the time with their headaches, and completed questions on symptom frequency and healthcare resource utilization.

Main outcomes measures:

Ordinal logistic regression models were used to assess the association between nausea frequency and headache-related healthcare utilization. Healthcare cost equivalents were calculated.

Results:

Among the 6488 respondents with episodic migraine, the number of respondents observed across headache-related nausea frequency strata were 6.9% for never, 14.5% for rarely, 29.1% for <half the time, and 49.5% for ≥half the time. In unadjusted models, the odds of having ≥1 healthcare encounter for headache in the preceding year increased with frequency of nausea for primary care/obstetrics-gynecology visits (OR?=?1.41; 95% CI?=?1.30–1.52, p?<?0.001), nurse practitioner/physician assistant visits (OR?=?1.52; 95% CI?=?1.25–1.85, p?<?0.001), neurology/headache clinic visits (OR?=?1.33, 95% CI?=?1.18–1.51, p?<?0.001), pain clinic visits (OR?=?1.31, 95% CI?=?1.01–1.71, p?<?0.05), emergency department visits (OR?=?1.85; 95% CI?=?1.56–2.19, p?<?0.01), and overnight hospital stays (OR?=?1.50, 92% CI?=?1.12–2.00, p?<?0.01). The odds of having ≥1 lifetime CT scan or MRI also increased with the frequency of nausea (p?<?0.001 for both). Results remained significant in these analyses when controlling for sociodemographics and overall symptom severity except in the case of pain clinic visits (p?<?0.107). Visits for Mental Health and visits for Chiropractic/Alternative care did not differ significantly by nausea group in unadjusted or adjusted models. Mean estimated direct headache-related healthcare cost equivalents per person per year generally increased with increasing headache-related nausea frequency across categories of healthcare utilization. Average per person healthcare cost for nausea ≥half the time vs nausea never was $179 and $49 yearly for outpatient services, $183 vs $20 yearly for overnight hospital stays, and $314 vs $257 for lifetime diagnostic services/imaging.

Conclusions:

Direct costs of migraine increase with increasing frequency of migraine-associated nausea. Both frequency and severity of headache-related nausea should be monitored as part of ongoing care of persons with migraine. Headache-related nausea, like headache pain, should be considered an area of central concern during clinical, diagnostic, and treatment optimization assessments.

Study limitations:

This study relied on self-reported headache frequency and healthcare costs which are subject to recall bias and under-reporting; however, reporting bias is unlikely to be different as a function of nausea frequency. In addition, medication use costs and indirect costs (which may be higher than direct costs for migraine) were not assessed.     

Comparison of second-generation antipsychotic treatment on psychiatric hospitalization in Medicaid beneficiaries with bipolar disorder

Abstract

Objective:

To compare second-generation antipsychotics on time to and cost of psychiatric hospitalization in Medicaid beneficiaries with bipolar disorder.

Methods:

Retrospective study using healthcare claims from 10 US state Medicaid programs. Included beneficiaries were aged 18–64, initiated a single second-generation antipsychotic (aripiprazole, olanzapine, quetiapine, risperidone, or ziprasidone) between 1/1/2003–6/30/2008 (initiation date?=?index), and had a medical claim with an ICD-9-CM diagnosis code for bipolar disorder. A 360-day post-index period was used to measure time to and costs of psychiatric hospitalization (inpatient claims with a diagnosis code for a mental disorder [ICD-9-CM 290.xx–319.xx] in any position). Cox proportional hazards models and Generalized Linear Models compared time to and costs of psychiatric hospitalization, respectively, in beneficiaries initiating aripiprazole vs each other second-generation antipsychotic, adjusting for beneficiaries’ baseline characteristics.

Results:

Included beneficiary characteristics: mean age 36 years, 77% female, 80% Caucasian, aripiprazole (n?=?2553), mean time to psychiatric hospitalization or censoring?=?85 days; olanzapine (n?=?4702), 81 days; quetiapine (n?=?9327), 97 days; risperidone (n?=?4377), 85 days; ziprasidone (n?=?1520), 82 days. After adjusting for baseline characteristics, time to psychiatric hospitalization in beneficiaries initiating aripiprazole was longer compared to olanzapine (hazard ratio [HR]?=?1.52, p?<?0.001), quetiapine (HR?=?1.40, p?<?0.001), ziprasidone (HR?=?1.33, p?=?0.032), and risperidone, although the latter difference did not reach significance (HR?=?1.18, p?=?0.13). The adjusted costs of psychiatric hospitalization in beneficiaries initiating aripiprazole were significantly lower compared to those initiating quetiapine (incremental per-patient per-month difference?=?$42, 95% CI?=?$16–66, p?<?0.05), but not significantly lower for the other comparisons.

Limitations:

This study was based on a non-probability convenience sample of the Medicaid population. Analyses of administrative claims data are subject to coding and classification error.

Conclusions:

Medicaid beneficiaries with bipolar disorder initiating aripiprazole had significantly longer time to psychiatric hospitalization than those initiating olanzapine, quetiapine, or ziprasidone, and significantly lower adjusted costs for psychiatric hospitalization than those initiating quetiapine.     

Predictors for total hospital and cardiology cost claims among patients with atrial fibrillation initiating dabigatran or acenocoumarol in The Netherlands

Aims: The prevalence of atrial fibrillation (AF) has increased over the past years due to aging of the population, and healthcare costs associated with AF reflect a significant financial burden. The aim of this study was to explore predictors for the real-world AF-related in-hospital costs in patients that recently initiated anticoagulation with acenocoumarol or dabigatran.

Methods: Predictors for claimed total hospital care costs and cardiology costs in AF patients were explored by using hospital financial claims data from propensity score matched patient groups in a large Dutch community hospital. This study analyzed the total dataset (n?=?766) and carried out a secondary analysis for all matched pairs of anticoagulation naïve AF patients (n?=?590) by ordinal regression.

Results: Dabigatran was a predictor for significantly lower cardiology and total hospital care costs (Odds Ratio [OR]?=?0.43, 95% confidence interval (CI)?=?0.33–0.57; and OR?=?0.60, 95% CI?=?0.46–0.79, respectively). Female gender was a predictor for lower total hospital care costs. Predictors for an increase in total hospital care costs were the occurrence of stroke or systemic embolism, major bleeding, and minor bleeding. The costs predictors were comparable when limiting the analysis to patients that were anticoagulation naïve. Age and CHA₂DS₂-VASc were not predictors for either cardiology or total hospital care costs in both analyses.

Conclusion: Dabigatran treatment was as a predictor for lower cardiology costs and lower total hospital care costs in AF patients that initiated oral anticoagulation.