Healthcare costs and resource utilization in patients with severe aplastic anemia in the US

Abstract

Purpose: This study aimed to evaluate the healthcare resource utilization (HCRU) and costs for patients with severe aplastic anemia (SAA) using US claims data.

Methods: This retrospective, observational database study analyzed claims data from the Truven MarketScan databases. SAA patients aged ≥2?years identified between 2014 and 2017 who were continuously enrolled for 6?months before their first SAA treatment or blood transfusion, with a ≥6-month follow-up, were included. Baseline demographics and comorbidities were evaluated. Monthly all-cause and SAA-related HCRU and direct costs in the follow-up period were analyzed and differences were presented for all patients and across age groups.

Results: With an average follow-up period of 21.5?months, 939 patients were included in the study. Monthly all-cause and SAA-related HCRU [mean (SD)] were 1.65 days (2.61 days) and 0.18 days (0.70 days) for length of stay, 0.18 (0.23) and 0.01 (0.04) for hospital admissions, 0.25 (0.30) and 0.02 (0.07) for ER visits, 2.24 (1.40) and 0.46 (0.99) for office visits, and 2.90 (2.64) and 0.55 (1.31) for outpatient visits, respectively. On average, SAA patients received 0.15 (0.57) blood transfusions per month. Mean monthly all-cause direct costs were $28,280 USD ($36,127) [US dollars, mean (SD)]. Direct costs related to admissions were $11,433 USD (SD $25,040), followed by $624 USD ($1,703) for ER visits, $528 USD ($694) for office visits, $7,615 USD ($13,273) for outpatient visits, and $5,998 USD ($11,461) for pharmacy expenses. Monthly SAA-related direct costs averaged $7,884 USD (SD $16,254); of these costs, $1,608 USD ($7,774) were from admissions, $47 USD ($257) from ER visits, $127 USD ($374) from office visits, $1,462 USD ($4,994) from outpatient visits, and $4,451 USD ($10,552) from pharmacy expenses.

Conclusion: SAA is associated with high economic burden, with costs comparable to blood malignancies, implying that US health plans should consider appropriately managing SAA while constraining the total healthcare costs when making formulary decisions.     

The economic burden of psoriasis with high comorbidity among privately insured patients in the United States

Objective: To evaluate the impact of comorbidities on healthcare resource use (HRU), and direct and indirect work-loss-related costs in psoriasis patients.

Methods: Adults with psoriasis (≥2 diagnoses, the first designated as the index date) and non-psoriasis controls (no psoriasis diagnoses, randomly generated index date) were identified in a US healthcare claims database of privately-insured patients (data between January 2010 and March 2017 were used). Psoriasis patients were stratified based on the number of psoriasis-related comorbidities (0, 1–2, or ≥3) developed during the 12?months post-index. All outcomes were evaluated during the follow-up period, spanning the index date until the end of continuous health plan eligibility or data cut-off. HRU and costs per-patient-per-year (PPPY) were compared in psoriasis and non-psoriasis patients with ≥12?months of follow-up.

Results: A total of 9,078 psoriasis (mean age?=?44?years, 51% female) and 48,704 non-psoriasis (mean age?=?41?years, 50% female) patients were selected. During the 12?months post-index, among psoriasis vs non-psoriasis patients, 71.0% vs 83.0% developed no psoriasis-related comorbidities, 26.3% vs 16.0% developed 1–2, and 2.6% vs 1.0% developed ≥3 psoriasis-related comorbidities. Compared to non-psoriasis patients, psoriasis patients had more HRU including outpatient visits (incidence rate ratios [IRRs]?=?1.52, 2.03, and 2.66 for 0, 1–2, and ≥3 comorbidities, respectively [all p?p?p?p?Conclusions: HRU and cost burden of psoriasis are substantial, and increase with the development of psoriasis-related comorbidities.     

Healthcare costs in psoriasis and psoriasis sub-groups over time following psoriasis diagnosis

Aims: To quantify healthcare costs in patients with psoriasis overall and in psoriasis patient sub-groups, by level of disease severity, presence or absence of psoriatic arthritis, or use of biologics.

Methods: Administrative data from Truven Health Analytics MarketScan Research Database were used to select adult patients with psoriasis from January 2009 to January 2014. The first psoriasis diagnosis was set as the index date. Patients were required to have ≥6 months of continuous enrollment with medical and pharmacy benefits pre-index and ≥12 months post-index. Patients were followed from index until the earliest of loss to follow-up or study end. All-cause healthcare costs and outpatient pharmacy costs were calculated for the overall psoriasis cohort and for the six different psoriasis patient sub-groups: (a) patients with moderate-to-severe disease and mild disease, (b) patients with psoriatic arthritis and those without, and (c) patients on biologics and those who are not. Costs are presented per-patient-per-year (PPPY) and by years 1, 2, 3, 4, and 5 of follow-up, expressed in 2014?US dollars.

Results: A total of 108,790 psoriasis patients were selected, with a mean age of 46.0 years (52.7% females). Average follow-up was 962 days. All-cause healthcare costs were $12,523 PPPY. Outpatient pharmacy costs accounted for 38.6% of total costs. All-cause healthcare costs were highest for patients on biologics ($29,832), then for patients with psoriatic arthritis ($23,427) and those with moderate-to-severe disease ($21,481). Overall, all-cause healthcare costs and outpatient pharmacy costs presented an upward trend over a 5-year period.

Conclusions: Psoriasis is associated with significant economic burden, which increases over time as the disease progresses. Patients with moderate-to-severe psoriasis, those with psoriatic arthritis, or use of biologics contributes to higher healthcare costs. Psoriasis-related pharmacy expenditure is the largest driver of healthcare costs in patients with psoriasis.     

Societal burden of cluster headache in the United States: a descriptive economic analysis

Aim: To estimate direct and indirect costs in patients with a diagnosis of cluster headache in the US.

Methods: Adult patients (18–64 years of age) enrolled in the Marketscan Commercial and Medicare Databases with ≥2 non-diagnostic outpatient (≥30 days apart between the two outpatient claims) or ≥1 inpatient diagnoses of cluster headache (ICD-9-CM code 339.00, 339.01, or 339.02) between January 1, 2009 and June 30, 2014, were included in the analyses. Patients had ≥6 months of continuous enrollment with medical and pharmacy coverage before and after the index date (first cluster headache diagnosis). Three outcomes were evaluated: (1) healthcare resource utilization, (2) direct healthcare costs, and (3) indirect costs associated with work days lost due to absenteeism and short-term disability. Direct costs included costs of all-cause and cluster headache-related outpatient, inpatient hospitalization, surgery, and pharmacy claims. Indirect costs were based on an average daily wage, which was estimated from the 2014?US Bureau of Labor Statistics and inflated to 2015 dollars.

Results: There were 9,328 patients with cluster headache claims included in the analysis. Cluster headache-related total direct costs (mean [standard deviation]) were $3,132 [$13,396] per patient per year (PPPY), accounting for 17.8% of the all-cause total direct cost. Cluster headache-related inpatient hospitalizations ($1,604) and pharmacy ($809) together ($2,413) contributed over 75% of the cluster headache-related direct healthcare cost. There were three sub-groups of patients with claims associated with indirect costs that included absenteeism, short-term disability, and absenteeism?+?short-term disability. Indirect costs PPPY were $4,928 [$4,860] for absenteeism, $803 [$2,621] for short-term disability, and $3,374 [$3,198] for absenteeism?+?disability.

Conclusion: Patients with cluster headache have high healthcare costs that are associated with inpatient admissions and pharmacy fulfillments, and high indirect costs associated with absenteeism and short-term disability.     

Adherence to iron chelation therapy and associated healthcare resource utilization and costs in Medicaid patients with sickle cell disease and thalassemia

Background:

Sub-optimal patient adherence to iron chelation therapy (ICT) may impact patient outcomes and increase cost of care. This study evaluated the economic burden of ICT non-adherence in patients with sickle cell disease (SCD) or thalassemia.

Methods:

Patients with SCD or thalassemia were identified from six state Medicaid programs (1997–2013). Adherence was estimated using the medication possession ratio (MPR) of ≥0.80. All-cause and disease-specific resource utilization per-patient-per-month (PPPM) was assessed and compared between adherent and non-adherent patients using adjusted incidence rate ratios (aIRR). All-cause and disease-specific healthcare costs were computed using mean cost PPPM. Regression models adjusting for baseline characteristics were used to compare adherent and non-adherent patients.

Results:

A total of 728 eligible patients treated with ICT in the SCD cohort, 461 (63%) adherent, and 218 in the thalassemia cohort, 137 (63%) adherent, were included in this study. In SCD patients, the adjusted rate of all-cause outpatient visits PPPM was higher in adherent patients vs non-adherent patients (aIRR [95% CI]: 1.05 [1.01–1.08], p?<?0.0001). Conversely, adherent patients incurred fewer all-cause inpatients visits (0.87 [0.81–0.94], p?<?0.001) and ER visits (0.86 [0.78–0.93], p?<?0.001). Similar trends were observed in SCD-related resource utilization rates and in thalassemia patients. Total all-cause costs were similar between adherent and non-adherent patients, but inpatient costs (adjusted cost difference?=??$1530 PPPM, p?=?0.0360) were lower in adherent patients.

Conclusion:

Patients adherent to ICT had less acute care need and lower inpatient costs than non-adherent patients, although they had more outpatient visits. Improved adherence may be linked to better disease monitoring and has the potential to avoid important downstream costs associated with acute care visits and reduce the financial burden on health programs and managed care plans treating SCD and thalassemia patients.     

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.     

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.     

Clinical comorbidities,treatment patterns,and direct medical costs of patients with osteoarthritis in usual care: a retrospective claims database analysis

Abstract

Objective:

Comorbidities and resource utilization among patients with osteoarthritis (OA) in clinical practice have been infrequently characterized. The purpose of this study was to examine comorbidities, pain-related pharmacotherapy, and direct medical costs of patients with OA in clinical practice.

Method:

This retrospective cohort analysis used medical and pharmacy claims data from the LifeLink? Database. OA patients (ICD-9-CM codes 715.XX) were matched (age, gender, and region) with individuals without OA. Comorbidities, pain-related pharmacotherapy, and direct medical costs (pharmacy, outpatient, inpatient, total) were examined for the calendar year 2008.

Results:

The sample consisted of 112,951 OA patients and 112,951 controls (mean age: 56.9 [SD?=?9.5] years; 62% female). Relative to controls, OA patients were significantly more likely (p?<?0.0001) to have comorbidities, including musculoskeletal (84.3 vs. 37.1%) and neuropathic pain (22.0 vs. 6.1%) conditions, depression (12.4 vs. 6.4%), anxiety (6.6 vs. 3.5%), and sleep disorders (11.9 vs. 4.2%). OA patients were significantly more likely (p?<?0.0001) to receive pain-related medications, including opioids (40.7 vs. 17.1%), NSAIDs (37.1 vs. 11.5%), tramadol (9.8 vs. 1.8%), and adjunctive medications for treating depression, anxiety, and insomnia. Mean [SD] total direct medical costs were more than two times higher among OA patients ($12,905 [$21,884] vs. $5099 [$13,855]; p?<?0.001) and median costs were more than three times higher ($6188 vs. $1879; p?<?0.0001). Study limitations include potential errors in coding and recording; overestimation of the comorbidity burden; inability to link condition of interest, OA, with prescribed medications; and possible underestimation of the true costs of OA, because indirect costs were not considered and the direct costs were from a third party payer (commercial insurance) perspective.

Conclusion:

The patient burden of OA was characterized by a high prevalence of comorbidities. The payer burden was also substantial, with significantly greater use of pain-related and adjunctive medications, and higher direct medical costs.     

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.     

Healthcare resource utilization and costs associated with venous thromboembolism recurrence in patients with cancer

Abstract

Objective: Patients with cancer are at high risk for developing primary but also recurrent venous thromboembolism (VTE). This study examined healthcare utilization (HRU) and costs related to VTE recurrence among cancer patients.

Methods: Medical and pharmacy claims from the Humana Database were used to compare HRU (outpatient visits, emergency room visits, hospitalizations, and hospitalization days) and healthcare costs among cancer patients with a single VTE event (between 01/2013 and 06/2015) and those with recurrent VTE during the follow-up period (from initiation of anticoagulant therapy until end of eligibility or data availability). All-cause and VTE-related HRU and costs were evaluated using Poisson regression, and healthcare costs were compared using mean differences reported as per-patient-per-year (PPPY).

Results: Of 2,428 newly diagnosed cancer patients who developed VTE, 413 (17.1%) experienced recurrent VTE during the follow-up period (mean = 9 months). Patients with recurrent VTE had higher all-cause and VTE-related HRU and costs compared to those without recurrence. Patients with recurrent VTE also had over 3.19-times more VTE-related hospitalizations (RR [95% CI]?=?3.19 [2.93–3.47]), and 3.88-times more VTE-related hospitalization days (RR [95% CI]?=?3.88 [3.74–4.02]) than patients without a VTE recurrence. Total VTE-related healthcare costs were $39,641 PPPY among patients with recurrent VTE, $29,142 higher compared to those without recurrence ($10,499 PPPY). This difference was mainly driven by hospitalization costs.

Conclusion: Recurrent VTE among cancer patients is associated with significant HRU and healthcare costs, notably hospitalizations. Strategies to reduce VTE recurrence in patients with cancer can contribute to reducing healthcare cost.     

Economic burden associated with inadequate antidepressant medication management among patients with depression and known cardiovascular diseases: insights from a United States–based retrospective claims database analysis

Abstract

Aims: The current study examined the association between insufficient major depressive disorder (MDD) care and healthcare resource use (HCRU) and costs among patients with prior myocardial infarction (MI) or stroke.

Methods: This was a retrospective study conducted using the MarketScan Claims Database (2010–2015). The date of the first MI/stroke diagnosis was defined as the cardiovascular disease (CVD) index date and the first date of a subsequent MDD diagnosis was the index MDD date. Adequacy of MDD care was assessed during the 90 days following the index MDD date (profiling period) using 2 measures: dosage adequacy (average fluoxetine equivalent dose of ≥20?mg/day for nonelderly and ≥10?mg/day for elderly patients) and duration adequacy (measured as the proportion of days covered of 80% or higher for all MDD drugs). Study outcomes included all-cause and CVD-related HCRU and costs which were determined from the end of the profiling period until the end of study follow-up. Propensity-score adjusted generalized linear models (GLMs) were used to compare patients receiving adequate versus inadequate MDD care in terms of study outcomes.

Results: Of 1,568 CVD patients who were treated for MDD, 937 (59.8%) were categorized as receiving inadequate MDD care. Results from the GLMs suggested that patients receiving inadequate MDD care had 14% more all-cause hospitalizations, 4% more all-cause outpatient visits, 17% more CVD-related outpatient visits, 13% more CVD-related emergency room (ER) visits, higher per patient per year CVD-related hospitalization costs ($21,485 vs. $17,756), higher all-cause outpatient costs ($2,820 vs. $2,055), and higher CVD-related outpatient costs ($520 vs. $434) compared to patients receiving adequate MDD care.

Limitations: Clinical information such as depression severity and frailty, which are potential predictors of adverse CVD outcomes, could not be ascertained using administrative claims data.

Conclusions: Among post-MI and post-stroke patients, inadequate MDD care was associated with a significantly higher economic burden.     

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.