Association between glycemic control and short-term healthcare costs among commercially insured diabetes patients in the United States

Abstract Objectives: Glycemic control, measured by HbA(1c), is well known to be a risk marker for long-term costly diabetes-related complications. The relationship between HbA(1c) and short-term costs is unclear. This study investigates how HbA(1c) is correlated to short-term diabetes-related medical expenses. Methods: Patients with diabetes with an HbA(1c) reading ≥6% between April and September 2007 were identified from a large US managed-care organization. Healthcare utilization data was obtained during the subsequent 12-month period. Multivariate analyses were performed to estimate the correlation between HbA(1c) and diabetes-related healthcare costs. Results: In all, 34,469 and 1,837 patients with type 2 and type 1 diabetes, respectively, were identified with an HbA(1c) reading ≥6% (mean HbA(1c): 7.4% and 7.9%). The majority of patients with type 1 diabetes were treated with insulin, while most patients with type 2 diabetes were treated with metformin. The multivariate analysis showed that several characteristics, including HbA(1c), significantly correlate with diabetes-related medical costs for both patients with type 1 and type 2 diabetes. A 1-percentage-point increase in HbA(1c) will, on average, lead to a 6.0% and 4.4% increase in diabetes-related medical costs for type 1 and type 2 diabetes, respectively. This corresponds to an annual cost increase of $445 and $250 for patients with type 1 and type 2 diabetes, respectively. Limitations: Retrospective data analyses inherently associated with selection bias which can only partly be adjusted by statistical techniques. Furthermore, the study population is not necessarily representative of the general population and there can be isolated coding or data errors in the dataset. Conclusions: These results suggest that tighter glycemic control is associated with short-term cost benefits for patients with diabetes. This supplements conventional wisdom that HbA(1c) affects risk of long-term complications and long-term costs.     

Predictors of glycemic control and diabetes-related costs among type 2 diabetes patients initiating therapy with liraglutide in the United States

Objective:

Liraglutide has been shown to significantly improve glycemic control and reduce body weight while minimizing the risk of hypoglycemia in adult patients with type 2 diabetes (T2D). This study aimed to identify characteristics that predict clinical and economic outcomes associated with liraglutide therapy in clinical practice in the US.

Methods:

Using the Truven Health MarketScan Laboratory Database, glycemic control (A1C <7%) and diabetes-related costs were evaluated in T2D patients initiating liraglutide between January 1, 2010 and June 30, 2012. Patients were required to have ≥1 post-index claim for liraglutide and A1C values at baseline and 6 months follow-up. All valid values of baseline A1C were included. Patients previously treated with GLP-1 receptor agonist(s) or insulin, or with evidence of type 1 diabetes, pregnancy, or gestational diabetes during the study period were excluded. Multivariable regression models were used to identify predictors of glycemic control and diabetes-related costs.

Results:

Of 417 patients newly treated with liraglutide, 54.0% achieved glycemic control (A1C <7%) during follow-up. Factors associated with increased odds of glycemic control during follow-up were: being female, POS/EPO health plan type, baseline A1C, early liraglutide initiation (0–1 prior oral anti diabetics [OADs] vs ≥2), adherence to liraglutide (defined as the proportion of days covered [PDC]), and diabetic retinopathy. Being female, earlier liraglutide initiation (0–1 prior OADs), and higher patient share of liraglutide costs were associated with significantly lower diabetes-related costs during follow-up. Factors associated with significantly higher post-index diabetes-related costs were: higher baseline A1C, baseline use of sulfonylureas, and diabetic retinopathy.

Conclusions:

Within this commercially-insured population of T2D patients treated with liraglutide, gender, baseline A1C, early liraglutide initiation (0–1 prior OADs), diabetic retinopathy, better adherence, and patient share of liraglutide costs were associated with increased odds of achieving glycemic control and the odds of having higher or lower diabetes-related costs.     

Association between provider specialty and healthcare costs and glycemic control for patients with diabetes

Aims: To analyze the association between provider, healthcare costs, and glycemic control for patients with diabetes mellitus (DM).

Materials and methods: This cross-sectional study identified adults with type 1 or 2?DM (T1D, T2D) in the Optum database. The main independent variable was provider (endocrinologist or primary care). Regression analysis compared total medical and pharmacy costs, adjusting for health status and other patient differences, by provider.

Results: For all patients, HbA1C improvement was greater, and medical costs significantly lower with an endocrinologist rather than a primary care provider. The largest HbA1C improvement (4%) occurred for insulin-dependent patients seen by endocrinologists. Significant medical savings with endocrinologist management occurred within the Medicare Advantage population in every sub-group of patients, with 14% lower costs ($4,767) for patients with T1D, 11% lower costs ($3,160) for patients with macro- and microvascular complications, and 10% lower costs ($2,237) for insulin-dependent patients. Within the commercial insurance population, medical costs were reduced by ≥9% in every sub-group of patients, with a 20% reduction ($8,450) for patients with micro- and macrovascular complications. Overall total costs (medical and pharmacy) were 8% ($1,541) higher for patients receiving endocrinologist rather than primary care, although endocrinologist care resulted in a 9% reduction (–$3,710) in costs for Medicare Advantage patients with T1D. Total medical costs (excluding pharmacy costs) may be a more accurate indicator of costs associated with patients in various stages of DM.

Limitations: There was insufficient data to develop risk-adjustment payments for pharmacy costs based on disease severity. The cross-sectional design identifies associations and not cause–effect relationships.

Conclusion: DM management by an endocrinologist was associated with greater HbA1C improvement and significantly lower medical costs. Total costs were higher with an endocrinologist, but for patients with T1D lower costs were seen, ranging from 2–9% regardless of insurance type.     

Retrospective study comparing healthcare costs and utilization between commercially insured patients with type 2 diabetes mellitus who are newly initiating exenatide once weekly or liraglutide in the United States

Abstract

Objective:

To compare healthcare costs and utilization between commercially insured patients with type 2 diabetes mellitus (T2DM) in the United States newly initiating exenatide once weekly (QW) or liraglutide.     

Healthcare resource utilization among commercially insured patients with cold agglutinin disease in the United States

Abstract

Aims: Cold agglutinin disease (CAD) is a rare subtype of autoimmune hemolytic anemia associated with increased thromboembolism risk and early mortality. Healthcare resource utilization (HRU) in CAD has not been reported. We aimed to compare HRU of patients with CAD with a matched non-CAD cohort in the United States.

Materials and methods: Patients with CAD were identified from 2006 to 2016 in the Optum-Humedica database using CAD terms in clinical notes and hematologist review. Patients were required to have Integrated Delivery Network records and ≥6 months’ follow-up before and after the first CAD mention date (index date). Patients with CAD were matched to a non-CAD cohort based on demographics. Multivariate analyses assessed inpatient hospitalizations, outpatient visits, emergency room visits, and transfusion use between cohorts 6 months before and 12 months after the index date.

Results: Of 814 patients with CAD, 410 met inclusion criteria and were matched to 3,390 patients without CAD. Mean age of patients with CAD was 68.0 years; approximately 62% were female. In the 12 months after the index date, mean inpatient hospitalizations (0.83 vs. 0.25), outpatient visits (17.26 vs. 6.77), emergency room visits (0.55 vs. 0.32), and transfusion days (1.05 vs. 0.05) were higher for patients with CAD than the matched non-CAD cohort (all p?<?.0001). Similarly, in the 6 months before the index date, patients with CAD had higher HRU than matched patients without CAD for all measures evaluated.

Limitations: Results of this study are based on patient information from the Optum-Humedica database, which is limited to commercially insured patients and may not represent the overall CAD population.

Conclusions: CAD places a substantial burden on patients and healthcare systems. In addition, the high HRU for patients with CAD observed in the 6 months before diagnosis indicates that disease awareness and better diagnostic practices may be needed.     

Healthcare resource utilization among patients diagnosed with idiopathic pulmonary fibrosis in the United States

Abstract

Objectives:

Few studies have characterized healthcare resource utilization among patients with idiopathic pulmonary fibrosis. The objective of this study is to assess healthcare resource utilization among patients with idiopathic pulmonary fibrosis as compared to members without this condition.

Methods:

Patients newly diagnosed with idiopathic pulmonary fibrosis were identified from a national administrative claims database (2006–2011) as having ≥2 claims with idiopathic fibrosing alveolitis, or ≥1 claim with idiopathic fibrosing alveolitis and ≥1 claim with post-inflammatory pulmonary fibrosis (earliest claim with idiopathic fibrosing alveolitis denoted the index date), a procedure of lung biopsy or high-resolution computed tomography within ±90 days of the index date, 12-month pre-index continuous enrollment, plus ≥2 confirmatory idiopathic fibrosing alveolitis diagnoses after the procedure. For each idiopathic pulmonary fibrosis patient, three members without the condition were matched by age/gender/region/payer type. Demographic/clinical characteristics were measured during the 1-year pre-index period. Healthcare resource utilization was assessed by quarter during 1-year pre- and post-index periods. Generalized estimating equation models controlling for patient characteristics were constructed to estimate adjusted post-index healthcare resource utilization.

Results:

In total, 1735 patients with idiopathic pulmonary fibrosis and 5205 without (mean age?=?71.5 years; 46.1% female) were included. Adjusted results revealed idiopathic pulmonary fibrosis patients were more likely to use healthcare resources than members without the condition 1-year post-index (number of hospitalizations, emergency room visits, and outpatients visits: 0.63 vs 0.31, 0.62 vs 0.48, and 5.7 vs 3.1 per person-year, respectively).

Conclusions:

Healthcare resource utilization is considerably higher among patients with idiopathic pulmonary fibrosis than members without the condition. Effective treatments for patients with idiopathic pulmonary fibrosis are needed to help reduce burden of healthcare resource use.     

Direct medical costs of treatment in newly-diagnosed high-grade glioma among commercially insured US patients

Aim: This analysis assessed the direct medical costs of newly-diagnosed, temozolomide (TMZ)-treated glioblastoma (GBM) from the perspective of a US commercial setting.

Materials and methods: The analysis included subjects identified from the IMS PharMetrics LifeLink Plus? claims database from January 1, 2008 to August 31, 2014 who were ≥18 years of age, had ≥1 malignant brain cancer diagnosis, had brain surgery ≤90 days prior to TMZ initiation, had TMZ treatment, and were continuously enrolled for ≥12 months pre-diagnosis and ≥1 month post-diagnosis. Per-patient per-month (PPPM) and cumulative costs from 3 months pre-diagnosis to various post-diagnosis follow-up time points were calculated. Multivariable analyses were used to estimate adjusted mean cost and identify contributors of cost.

Results: The study included 2,921 subjects (median age?=?56 years; 60% male). After diagnosis, the median (interquartile range, IQR) number of inpatient, emergency department, and outpatient visits were 2 (1–4), 1 (1–3), and 19 (13–27); median (IQR) length of stay per hospitalization was 5 (3–9) days. Mean total cumulative costs per patient from 3 months pre-diagnosis to 12 months and to 5 years post-diagnosis were $201,749 (197,490–206,024) and $268,031 (262,877–274,416). Mean (SD) PPPM costs were $818 (1,128) and $7,394 (8,676) pre- and post-GBM diagnosis, respectively. The variables most predictive of cumulative costs included radiation therapy (+$81,732), ≥2 weeks of hospitalization (+$49,629), and ≥7 MRI scans (+$40,105).

Conclusions: The direct medical costs of newly-diagnosed, TMZ-treated GBM in commercially insured patients are substantial, with estimated total cumulative costs of $268,031.     

The economic burden of brain metastasis among lung cancer patients in the United States

Objective:

Brain metastases among lung cancer patients can impair cognitive and functional ability, complicate care, and reduce survival. This study focuses on the economic burden of brain metastasis in lung cancer—direct healthcare costs to payers and indirect costs to patients, payers, and employers—in the US.

Methods:

Retrospective study using claims data from over 60 self-insured Fortune 500 companies across all US census regions (January 1999–March 2013). Adult, non-elderly lung cancer patients with brain metastasis were evaluated over two study periods: (1) pre-diagnosis (≤30 days prior to first observed lung cancer diagnosis to ≤30 days prior to first-observed brain metastasis diagnosis) and (2) post-diagnosis (≤30 days prior to first observed brain metastasis diagnosis to end of continuous eligibility or observation).

Outcome measures:

Healthcare costs to payers and resource utilization, salary loss to patients, disability payouts for payers, and productivity loss to employers.

Results:

A total of 132 patients were followed for a median of 8.4 and 6.6 months in the pre- and post-diagnosis periods, respectively. At diagnosis of brain metastasis, 21.2% of patients were on leave of absence and 6.1% on long-term disability leave. Substantial differences were observed in the pre- vs post-diagnosis periods. Specifically, patients incurred much greater healthcare utilization in the post-diagnosis period, resulting in $25,579 higher medical costs per-patient-per-6-months (PPP6M). During this period, patients missed significantly more work days, generating an incremental burden of $2853 PPP6M in salary loss for patients, $2557 PPP6M in disability payments for payers, and $4570 PPP6M in productivity loss for employers.

Limitations:

Type of primary lung cancer and extent of brain metastasis could not be assessed in the data. The analysis was also limited to patients with comprehensive disability coverage.

Conclusions:

Development of brain metastasis among lung cancer patients is associated with a substantial economic burden to payers, patients, and employers.     

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.     

Treatment patterns,healthcare resource utilization,and costs in patients with acute myeloid leukemia in commercially insured and Medicare populations

Objective: To describe the setting, duration, and costs of induction and consolidation chemotherapy for adults with newly-diagnosed acute myeloid leukemia (AML), who are candidates for standard induction chemotherapy, in the US.

Methods: Adults newly-diagnosed with AML who received standard induction chemotherapy in an inpatient setting were identified from the Truven Health Analytics MarketScan (2006–2015) and SEER-Medicare (2007–2011) databases. Patients were observed from induction therapy start to the first of hematopoietic stem cell transplant, 180 days after induction discharge, health plan enrollment/data availability end, or death. Induction and consolidation chemotherapy were identified using Diagnosis-Related Group codes (chemotherapy with acute leukemia) or procedure codes for AML chemotherapy administration. AML treatment episode setting (inpatient or outpatient), duration, and costs (2015 USD, payers’ perspective) were described for commercially insured patients and Medicare beneficiaries.

Results: In total, 459 commercially insured patients and 563 Medicare beneficiaries (mean age?=?54 and 66 years; 53% and 54% male; respectively) were identified. For induction therapy, mean costs were $145,189 for commercially insured patients and $85,734 for Medicare beneficiaries, and median inpatient duration was 31 days (both). Following induction, 64% of commercially insured patients and 53% of Medicare beneficiaries had ≥1 consolidation cycle; 75% and 65% of consolidation cycles were in an inpatient setting, respectively. For consolidation cycles, in the inpatient setting, mean costs were $28,137 for commercially insured patients and $28,843 for Medicare beneficiaries, median cycle duration was 6 days (both); in the outpatient setting, mean costs were $11,271 for commercially insured patients and $5,803 Medicare beneficiaries, median duration was 5 days (both).

Limitations: Granular information on chemotherapy type administered was unavailable.

Conclusions: This is the first exploratory study providing a complete picture of recent AML treatment patterns and management costs among commercially insured patients and Medicare beneficiaries. There is substantial heterogeneity in the management and costs of AML.     

Treatment patterns and resource utilization and costs among patients with pulmonary arterial hypertension in the United States

Abstract

Objective:

To explore treatment patterns and resource utilization and cost for subjects with pulmonary arterial hypertension (PAH).

Research design:

Retrospective claims database analysis of 706 patients with PAH enrolled in a large, geographically diverse US managed-care organization.

Results:

In the final sample of PAH patients treated with bosentan (n?=?251) or sildenafil (n?=?455), average age was 57 years, 86% of patients were commercially insured, and 52% of patients were male. Gender distribution varied significantly across subgroups, with a lower proportion of males in the bosentan (30%) subgroup compared with the sildenafil group (64%) (p?<?0.001). Average baseline Charlson comorbidity score was 2.4. Average numbers of fills per month were 0.8 and 0.4 for bosentan and sildenafil patients, respectively (p?<?0.001). Over 80% of patients received only one PAH treatment in the first 90 days following the index date, with 28% of bosentan and 13% of sildenafil patients receiving combination therapy (p?<?0.001). Over one-third of bosentan patients and one-quarter of sildenafil patients experienced a dose increase in the follow-up period (p?=?0.009). Sixteen percent of sildenafil patients experienced a dose decrease in the follow-up period, while a smaller proportion of patients receiving bosentan (4%) experienced a dose decrease (p?<?0.001). On average, number of PAH-related per subject per month (PSPM) inpatient stays and emergency department visits and PSPM length of inpatient stays were statistically similar between the subgroups. PAH-related PSPM healthcare costs were high for both subgroups, with average monthly costs of $5,332 and $3,632 among bosentan and sildenafil patients, respectively (p?=?0.003). Differences in total costs were driven mainly by differences in pharmacy expenditures.

Conclusions:

Of the oral agents approved for treating PAH at the time of this study, sildenafil was most commonly prescribed as index therapy and was also associated with the lowest costs, largely due to significantly lower pharmacy costs. This study is characterized by limitations inherent to claims database analyses, such as the potential for coding errors and lack of information on whether a drug was taken as prescribed. Furthermore, PAH severity (WHO functional class) was not assessed.     

Drug wastage and costs to the healthcare system in the care of patients with non-small cell lung cancer in the United States

Background: Lung cancer is one of the most prevalent cancers in the US. This study was designed to evaluate the actual drug wastage and cost to the healthcare system using patient-level retrospective observational electronic medical record (EMR) data from a cohort of lung cancer patients in the US.

Methods: Data from the Flatiron Health advanced non-small cell lung cancer (NSCLC) cohort was used for this study. Drug administered amount (in mg) was used to determine an optimal set of available vial sizes to minimize waste. Drug wastage was defined as the difference between the drug amount in the optimal set of vials and the administered amount. Wholesale acquisition costs were used to value the cost of drugs, with and without vial sharing assumptions. The amount and cost of waste were quantified over the 2-year study period (January 2015–December 2016).

Results: There were 8,467 eligible patients included in this study, providing data from 103,826 unique drug administrations across multiple lines of therapy. Overall wastage was 4.37% of the total medication used to care for patients. While costs per administration were low, the total cost of wastage for the study population represented $16,630,112 across the 2-year study period. Assuming that vial sharing occurred at the site level slightly reduced waste to 3.74% (reducing costs to $15,953,212 over 2 years).

Conclusions: Drug wastage is an important concern and has implications on healthcare costs in NSCLC. Evaluation of these real-world data suggest that pharmacists and physicians are able to reduce drug wastage by optimizing vial combinations and sharing vials among patients. Even small amounts of reduction in wastage could be useful in reducing healthcare costs in the US; however, caution is needed with drug rounding efforts to ensure patients do not receive a sub-optimal dose of medication.     

Treatment patterns and healthcare resource utilization and costs in heavy menstrual bleeding: a Japanese claims database analysis

Aims: Heavy menstrual bleeding (HMB) is a highly prevalent condition, characterized by excessive menstrual blood loss and cramping, that interferes with activities of daily life. The aim of this study was to investigate treatment patterns in HMB in Japan, and to assess healthcare resource utilization and costs among women newly-diagnosed with the condition.

Materials and methods: This study retrospectively analyzed health insurance data available in the Japan Medical Data Center (JMDC) database on women aged 18–49 years who were newly-diagnosed with primary or secondary HMB. Treatment patterns were analyzed, and healthcare utilization and costs were evaluated and compared to matched controls.

Results: The study included a total of 635 patients, 210 with primary HMB and 425 with secondary HMB. In the primary HMB cohort, 60.0% of patients received one or more pharmacological or surgical treatments, compared with 76.2% in the secondary HMB cohort. The most commonly prescribed medications in all patients were hemostatic agents (28.7%), traditional Chinese medicine (TCM) (12.1%), and low-dose estrogen progestins (LEPs) (10.1%). After adjustment for patient baseline characteristics, healthcare costs were 1.93-times higher in primary HMB cases (p?<?.0001) and 4.44-times higher in secondary HMB cases (p?<?.0001) vs healthy controls. Outpatient care was the main cost driver.

Limitations: The main limitations of this study are related to its retrospective nature, and the fact that only reimbursed medications were captured in the source database.

Conclusions: A substantial proportion of HMB patients did not receive the recommended treatments. Healthcare costs were considerably increased in the presence of an HMB diagnosis.     

Annual costs of tumor necrosis factor inhibitors using real-world data in a commercially insured population in the United States

Abstract

Objective:

To calculate annual cost per treated patient of tumor necrosis factor (TNF) inhibitors etanercept, adalimumab, and infliximab for common approved indications, based on actual TNF-inhibitor use in clinical practice.

Methods:

Adults with ≥1 claim for etanercept, adalimumab, or infliximab between January 2005 and March 2009 were identified from the IMS LifeLink? Health Plan Claims Database. Patients new to therapy or continuing therapy (i.e., a prior claim for a TNF-inhibitor) were analyzed separately. Included patients had been enrolled from 180 days before the first TNF-inhibitor claim (index date) through 360 days after the index date and had a diagnosis during the pre-index period for rheumatoid arthritis, psoriasis, psoriatic arthritis, or ankylosing spondylitis. Patients with Crohn’s disease, ulcerative colitis, or juvenile idiopathic arthritis were excluded. Annual costs were calculated using wholesale acquisition costs for the TNF-inhibitor and Medicare Physician Fee Schedule for drug administration. Costs from restarting or switching TNF-inhibitor therapy during the first year were included.

Results:

A total of 27,704 patients (11,528 new, 16,176 continuing) had claims for etanercept, adalimumab, or infliximab, most commonly (65%) for treatment of rheumatoid arthritis. The most commonly used agent was etanercept (14,777 patients; 53%), followed by adalimumab (6862 patients; 25%) and infliximab (6065 patients; 22%). Annual cost per treated patient was etanercept $14,873, adalimumab $17,766, and infliximab $21,256 across all indications. Annual cost per treated patient by disease was (etanercept/adalimumab/infliximab): rheumatoid arthritis ($14,314/$17,700/$20,390), psoriasis ($17,182/$17,682/$23,935), psoriatic arthritis ($15,030/$18,483/$24,974), and ankylosing spondylitis ($14,254/$16,925/$23,056). New and continuing patients showed similar results, with etanercept having the lowest costs.

Limitations:

This analysis is limited to three TNF-inhibitors and a US managed-care population.

Conclusions:

Based on this analysis of real-world use of TNF-inhibitors among patients in nationwide clinical practice settings, the annual TNF-inhibitor cost per treated patient was lowest for etanercept across all indications.     

Treatment patterns and predictors of costs among patients with migraine: evidence from the United States medical expenditure panel survey

Abstract

Aim: Within a treated migraine population, to evaluate if the sub-group meeting criteria for high disease-specific total costs is significantly different to the sub-group with medium and/or low-costs, and to identify the associated risk factors.

Methods: Data from the Household Component of Medical Expenditure Panel Survey (MEPS-HC, 2008–2012), a nationally representative survey of non-institutionalized civilians in the US, were analyzed. Key inclusion criteria were migraine diagnosis (ICD-9 code: 346.XX) and prescribed treatment for migraine. Patients were categorized into high (>top 10th percentile), low (<bottom 10th percentile), and medium (between high and low) cost sub-groups per migraine-specific total costs. Logistic regression models were applied to identify predictors of high vs medium and medium vs low-costs. Preventive eligibility, defined as (i) past/current use of migraine preventives or (ii) overuse of acute medications, was compared to non-preventive eligibility.

Results: Within the treated migraine cohort (n?=?1,735), the mean age was 39?years, 80% were female, and the majority were in the medium-cost sub-group (n?=?1,360) (low-cost n?=?190, high-cost n?=?195). Significant predictors of high vs medium-costs were low SF-12 Physical Composite Scores (OR?=?0.95; 95% CI?=?0.92–0.97), low SF-6D health utility index scores (OR?=?0.019; 95% CI?=?0.002–0.193), preventive eligibility-i (OR?=?0.019; 95% CI?=?0.002–0.193), and preventive-eligibility-ii (OR?=?3.10; 95% CI?=?1.62–5.91). Statistically significant (p?<?0.05) predictors of medium vs low-costs included anxiety, Fleishman score, preventive-eligible-i, and preventive-eligible-ii.

Conclusions: Among patients treated for migraine, distinct characteristics, including patient-functioning measures and comorbidities, are predictive of high vs medium-costs, and medium vs low-costs. Preventive eligibility is a predictor of being in the higher cost sub-groups; however, preventive treatments that improve functioning and reduce acute medication use have the potential to reduce migraine-specific costs.

Limitations: The results are limited to a population that is diagnosed and treated for migraine. Over-the-counter medication use, and migraine headache frequency and severity were not captured.     

Glycemic control among patients with type 2 diabetes who initiate basal insulin: a retrospective cohort study

Objective:

To examine changes in glycemic control for patients with type 2 diabetes mellitus (T2DM) after initiation of basal insulin and factors associated with improved glycemic control.

Methods:

An analysis of retrospective medical records of patients with T2DM was examined using Humedica’s electronic medical records database (January 2007–August 2012). Patients with T2DM, initiating basal insulin, age ≥21 years, with a recorded HbA1c test in both the 1 year prior and the 2 years post-initiation were included. A multivariate regression examined factors associated with changes in glycemic control. Logistic regressions examined factors associated with improvements or worsening of glycemic control, compared to relatively unchanged glycemic control.

Results:

Many (14,457) individuals met the inclusion–exclusion criteria. Multivariate analyses revealed that older age (p?p?p?=?0.0138), and higher household income (p?=?0.0065) were associated with improved glycemic control. Patients diagnosed with comorbid peripheral vascular disease (p?=?0.0072), cancer (p?=?0.0019), obesity (p?=?0.0002), moderate (p?=?0.0103), and severe chronic kidney disease (p?p?=?0.0075) in the pre-period were found to have significantly improved glycemic control in the post-period. Use of prandial insulin (p?=?0.0087), pre-mix insulin (p?=?0.0003) in the pre-period, a higher pre-period HbA1c score (p?p?Limitations:

Analyses rely on electronic medical records which cannot capture patient healthcare utilization occurring outside of the data capture system. Analyses do not control for insulin dosage or type of basal insulin prescribed.

Conclusions:

Among patients with T2DM treated with basal insulin, a number of factors may influence glycemic outcomes. These findings suggest a role for a more personalized approach to the treatment of patients with T2DM.     

Factors associated with increased healthcare costs in Medicare Advantage patients with type 2 diabetes enrolled in a large representative health insurance plan in the US

Abstract

Aim:

The objective of this study was to apply quantile regression (QR) methodology to a population from a large representative health insurance plan with known skewed healthcare utilization attributes, co-morbidities, and costs in order to identify predictors of increased healthcare costs. Further, this study provides comparison of the results to those obtained using ordinary least squares (OLS) regression methodology.

Methods:

Members diagnosed with Type 2 Diabetes and with 24 months of continuous enrollment were included. Baseline patient demographic, clinical, consumer/behavioural, and cost characteristics were quantified. Quantile regression was used to model the relationship between the baseline characteristics and total healthcare costs during the follow-up 12 month period.

Results:

The sample included 83,705 patients (mean age?=?70.6 years, 48% male) residing primarily in the southern US (78.1%); 81.2% of subjects were on oral-only anti-diabetic therapy. Co-morbid conditions included nephropathy (43.5%), peripheral artery disease (26.4%), and retinopathy (18.0%). Variables with the strongest relationship with costs during the follow-up period included outpatient visits, ER visits, inpatient visits, and Diabetes Complications Severity Index score during the baseline period. In the top cost quantiles, each additional glycohemoglobin (HbA1c) test was associated with cost savings ($1400 in the 98th percentile). Stage 4 and Stage 5 chronic kidney disease were associated with an incremental cost increase of $33,131 and $106,975 relative to Stage 1 or no CKD in the 98th percentile ($US).

Conclusions:

These results demonstrate that QR provides additional insight compared to traditional OLS regression modeling, and may be more useful for informing resource allocation to patients most likely to benefit from interventions. This study highlights that the impact of clinical and demographic characteristics on the economic burden of the disease vary across the continuum of healthcare costs. Understanding factors that drive costs on an individual patient level provide important insights that will help in ameliorating the clinical, humanistic, and economic burden of diabetes.     

Kidney involvement in tuberous sclerosis complex: the impact on healthcare resource use and costs

Abstract

Objective:

Tuberous sclerosis complex (TSC) is associated with non-malignant kidney lesions—angiomyolipomata—that may be associated with chronic kidney disease (CKD). This study investigated the relationship between renal angiomyolipomata and CKD in TSC, including the impact on healthcare resource utilization (HCRU) and costs.