The impact of telemental health use on healthcare costs among commercially insured adults with mental health conditions.
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ABSTRACT: Objective
To determine the impact of telemental health (TMH) use on total healthcare costs and mental health (MH)-related costs paid by a third party among adults with mental health conditions (MHC).Method
This study employed a pre-post design with a non-equivalent control group. The cohort comprised adults with MHCs identified using diagnosis codes from de-identified claims data of the Optum Clinformatics DataMart (2010 January 01 to 2017 June 30). We identified mental health (MH) service users and TMH users (N = 348) based on procedure codes. Non-users (N = 238,595) were defined as those who only used in-person MH services. A Difference-in-Differences (DID) analysis was performed within a multivariable two-part model (TPM) framework to examine the impact of TMH use on adjusted standardized costs (2018 US $) of all healthcare services and MH services. Patient-level and state-level factors were adjusted in TPM.Results
TMH use was associated with significantly higher MH-related costs [Marginal effect = $461.3, 95% confidence interval: $142.4-$780.2] and an excess of $370 increase in MH-related costs at follow-up as compared to baseline. However, TMH use was not associated with an increase in total third-party healthcare costs nor with changes in total costs from baseline to follow-up.Conclusions
Despite having a higher likelihood of MH services use and MH-related costs, TMH users did not have higher total costs as compared to adults using only in-person MH services. Our findings suggest that TMH can increase access to MH care without increasing total healthcare costs among adults with MHC. Future studies exploring whether TMH use can lead to cost-savings over a longer period are warranted.
SUBMITTER: Zhao X
PROVIDER: S-EPMC7535072 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionInsomnia diagnosis has been associated with a significant clinical and economic burden on patients and healthcare systems. This study examined changes in healthcare resource use (HCRU) and costs in insomnia patients before and after initiation of suvorexant treatment.MethodsThis retrospective cohort study analyzed Optum Clinformatics Data Mart claims data (Jan 2010-Dec 2018). Patients with ≥ 2 insomnia diagnosis claims and ≥ 1 prescription for suvorexant were included. Prevalent and incident insomnia patients were analyzed separately. The change in the trends of HCRU and costs were examined for 12 months before and 12 months after suvorexant initiation. An interrupted time series (ITS) analysis was conducted to assess the level and slope changes. Subgroups of patients with mental health comorbidities were examined.ResultsThe study included 18,919 and 5939 patients in the prevalent and incident insomnia cohorts, respectively. For the prevalent cohort, mean (SD) age was 64.5 (14.1) years, 65% were female, 74% had Medicare Advantage coverage, and 61% had a Charlson comorbidity index score ≥ 1. Characteristics for the incident cohort were similar. The ITS results suggested that the trend for monthly total healthcare cost (THC) was increasing before suvorexant initiation (US$52.51 in the prevalent cohort, $74.93 in incident insomnia cohort), but, after suvorexant initiation, the monthly total cost showed a decreasing trend in both cohorts. The decrease in slope for THC after suvorexant initiation were $72.66 and $112.07 per month in the prevalent and incident cohorts, respectively. The monthly trends in HCRU rates also decreased. The subgroup analysis showed that decreases were 1.5-3 times greater for patients with mental health comorbidities.ConclusionsIn this real-world study, suvorexant initiation was associated with immediate and continued decreases in HCRU and costs in insomnia patients. Further research is needed to understand the effect of suvorexant initiation on direct medical costs as well as costs associated with lost productivity in other real-world settings.
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Project description:PurposeHealth plan disenrollment occurs frequently in commercial insurance claims databases. If individuals who disenroll are different from those who remain enrolled, informative censoring may bias descriptive statistics as well as estimates of causal effect. We explored whether patterns of disenrollment varied by patient or health plan characteristics.MethodsIn a large cohort of commercially insured adults (2007-2013), we examined two primary outcomes: (a) within-year disenrollment between January 1 and December 30, which was considered to occur due to patient disenrollment from the health plan, and (b) end-of-year disenrollment on December 31, which was considered to occur due to either patient disenrollment from the health plan or withdrawal of the entire health plan from the commercial insurance database. In yearly cohorts, we identified factors independently associated with disenrollment by using log-binomial regression models to estimate risk ratios (RR) and 95% confidence intervals (CI).ResultsAmong 2 053 100 unique patient years, the annual proportion of within-year disenrollment remained steady across years (range, 13% to 14%) whereas the annual proportion of end-of-year disenrollment varied widely (range, 8% to 26%). Independent predictors of within-year disenrollment were related to health status, including age, comorbidities, frailty, hospitalization, emergency room visits, use of durable medical equipment, use of preventive care, and use of prescription medications. In contrast, independent predictors of end-of-year disenrollment were related to health plan characteristics including insurance plan type and geographic characteristics.ConclusionsDifferential risk of disenrollment suggests that analytic approaches to address selection bias should be considered in studies using commercial insurance databases.
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Project description:BackgroundFew studies have estimated the real-world economic burden such as all-cause and follicular lymphoma (FL)-related costs and health care resource utilization (HCRU) in patients with FL.ObjectivesThis study evaluated outcomes in patients who were newly initiated with FL indicated regimens by line of therapy with real-world data.MethodsA retrospective study was conducted among patients with FL from MarketScan® databases between January 1, 2010 and December 31, 2013. Patients were selected if they were ≥18 years old when initiated on a FL indicated therapy, had at least 1 FL-related diagnosis, ≥1 FL commonly prescribed systemic anti-cancer therapy after diagnosis, and did not use any FL indicated regimen in the 24 months prior to the first agent. These patients were followed up at least 48 months and the outcomes, including the distribution of regimens by line of therapy, the treatment duration by line of therapy, all-cause and FL-related costs, and HCRU by line of therapy were evaluated.ResultsThis study identified 598 patients who initiated FL indicated treatment. The average follow-up time was approximately 5.7 years. Of these patients, 50.2% (n=300) were female, with a mean age of 60.7 years (SD=13.1 years) when initiating their treatment with FL indicated regimens. Overall, 598 (100%) patients received first-line therapy, 180 (43.6%) received second-line therapy, 51 received third-line therapy, 21 received fourth-line therapy, and 10 received fifth-line therapy. Duration of treatment by each line of therapy was 370 days, 392 days, 162 days, 148 days, and 88 days, respectively. The most common first-line regimens received by patients were rituximab (n=201, 33.6%), R-CHOP (combination of rituximab, cyclophosphamide, doxorubicin hydrochloride [hydroxydaunomycin]; n=143, 24.0%), BR (combination of bendamustine and rituximab; n=143, 24.0%), and R-CVP (combination of rituximab, cyclophosphamide, vincristine, and prednisone; n=71, 11.9%). The most common second-line treatment regimens were (N=180): rituximab (n=78, 43.3%) and BR (n=41, 22.8%). Annualized all-cause health care costs per patient ranged from US$97 141 (SD: US$144 730) for first-line to US$424 758 (SD: US$715 028) for fifth-line therapy.ConclusionsThe primary regimens used across treatment lines conform to those recommended by the National Comprehensive Cancer Network clinical practice guidelines. The economic burden for patients with FL is high and grows with subsequent lines of therapy.
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Project description:IntroductionThere are limited data on treatment patterns, adverse events (AEs), and economic burden in younger, commercially insured patients treated for mantle cell lymphoma (MCL).MethodsAdults with ≥1 treatment for MCL between 1 November 2013-31 December 2017 were identified from IQVIA Real-World Data Adjudicated Claims-US; index date was first treatment. Patients carried ≥1 MCL diagnosis, were newly treated, and were enrolled continuously for ≥12 months prior to and ≥30 days following index. Patients receiving the four most common MCL regimens were included. Measures included frequency of incident AEs, resource use, and costs overall and by number of AEs. Adjusted logistic regression and generalized linear modeling evaluated risk of hospitalization and all-cause costs per patient per month (PPPM).ResultsTwo thousand five hundred and nine treated patients had a drug-specific code and were classified to a specific treatment regimen. Of those patients, 1785 patients received at least one of the four most commonly used MCL regimens (R-CHOP, rituximab monotherapy, B-R, and ibrutinib) at some point over follow-up (median 23 months). R-CHOP was the most common regimen observed in the first line (26%), followed by rituximab monotherapy (19%), B-R (15%), and ibrutinib (5%). The median age was 57 years; median Charlson Comorbidity Index was 0. Among patients receiving the four most common regimens, 63% of patients experienced ≥1 incident AE (R-CHOP 77%, B-R 58%, and ibrutinib 52%). An increasing number of incident AEs was associated with increased hospitalization risk (odds ratio = 2.4; 95% Confidence Interval [CI] 2.1-2.7) and increased mean costs PPPM (cost ratio = 1.1; 95% CI 1.1-1.2).DiscussionThis is the largest study describing treatment patterns and clinical and economic impact of MCL treatment. The most common regimens were R-CHOP, rituximab monotherapy, B-R, and ibrutinib. The majority of treated patients experienced at least one incident AE, with hospitalization risk and all-cause costs increasing as the number of AEs increased.
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Project description:Background/objectivesBenzodiazepines (BZDs) are widely prescribed to older adults. Although prescribing has declined in the U.S. Department of Veterans Affairs (VA), Medicare introduced BZD coverage in 2013. It is unknown whether declines in the VA have been widespread among older adults in the United States.DesignObservational study in traditional fee-for-service Medicare, commercial insurance, and the VA.SettingUnited States, 2013-2017.ParticipantsAdults aged 55 and older in traditional Medicare (234,290,693 person-months), commercial insurance (337,827,125 person-months), and the VA (256,590,369 person-months).Measurements(1) Change in BZD and BZD-opioid co-prescribing modeled by Poisson regression over time; and (2) standardized ratios of BZD and BZD-opioid co-prescribing, using Medicare as the reference.ResultsFrom April 2013 to December 2017, the monthly percentage of adults aged 55 and older who received BZDs fell from 10.4% to 9.3% in Medicare, 6.6% to 6.5% in commercial insurance, and 5.7% to 3.0% in the VA. Monthly BZD-opioid co-prescribing over the same time fell from 4.0% to 3.0% in Medicare, 2.3% to 2.0% in commercial, and 2.2% to .6% for the VA. Age- and sex-adjusted rates of decline for BZD and BZD-opioid co-prescribing were statistically significant for all systems. Annual BZD rate reductions were .98 (Medicare), .99 (commercial), and .87 (VA; P < .001 for all); co-prescribing rate reductions were .95, .99, and .75 (P < .001 for all). Using standardized ratios accounting for demographic and clinical characteristics, both prescribing and co-prescribing were lowest for the VA relative to Medicare (standardized BZD ratio = .40; 95% confidence interval [CI] = .39-.40; standardized BZD-opioid co-prescribing ratio = .35; 95% CI = .35-.35). Prescribing in commercial insurance was also lower (BZD = .65; 95% CI = .65-.65; BZD-opioid co-prescribing = .65; 95% CI = .65-.65).ConclusionBZD prescribing has declined much more to older adults receiving care through the VA than Medicare or commercial insurance. Other systems may learn from strategies implemented in the VA.
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Project description: Not available
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Project description:BackgroundInfections with Histoplasma can range from asymptomatic to life-threatening acute pulmonary or disseminated disease. Histoplasmosis can be challenging to diagnose and is widely underrecognized. We analyzed insurance claims data to better characterize histoplasmosis testing and treatment practices and its burden on patients.MethodsWe used the IBM MarketScan Research Databases to identify patients with histoplasmosis (International Classification of Diseases, Ninth Revision, Clinical Modification codes 115.00-115.99) during 2012-2014. We analyzed claims in the 3 months before to the 1 year after diagnosis and examined differences between patients with probable (hospitalized or >1 outpatient visit) and suspected (1 outpatient visit) histoplasmosis.ResultsAmong 1935 patients (943 probable, 992 suspected), 54% had codes for symptoms or findings consistent with histoplasmosis and 35% had ≥2 healthcare visits in the 3 months before diagnosis. Overall, 646 (33%) had any fungal-specific laboratory test: histoplasmosis antibody test (n = 349 [18%]), Histoplasma antigen test (n = 349 [18%]), fungal smear (n = 294 [15%]), or fungal culture (n = 223 [12%]); 464 (24%) had a biopsy. Forty-nine percent of probable patients and 10% of suspected patients were prescribed antifungal medication in the outpatient setting. In total, 19% were hospitalized. Patients' last histoplasmosis-associated healthcare visits occurred a median of 6 months after diagnosis.ConclusionsSome histoplasmosis patients experienced severe disease, apparent diagnostic delays, and prolonged illness, whereas other patients lacked symptoms and were likely diagnosed incidentally (eg, via biopsy). Low rates of histoplasmosis-specific testing also suggest incidental diagnoses and low provider suspicion, highlighting the need for improved awareness about this disease.
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Project description:ObjectivesThe healthcare burden associated with porphyria remains unevaluated despite the associated increased risks of morbidity and mortality. We aimed to assess the healthcare utilization and cost burdens of porphyria in the United States (US) using real-world claims data.MethodsWe performed a case-control analysis of adults in the Truven Health MarketScan® Commercial Claims database (2010-2015). Using propensity scores, 2788 porphyria cases were matched 1:1 to porphyria-free controls with chronic liver disease. Total and service-specific parameters were quantified for the 12 months before porphyria diagnosis versus the 12 months after diagnosis and over the 12 months following a randomly selected date for controls. Wilcoxon signed rank tests and McNemar tests were used to examine incremental differences in burden between cases and controls. Adjusted multivariable generalized linear regression models were used to compare healthcare burdens for cases versus controls.ResultsRelative to the 12 months before porphyria diagnosis, the following 12 months had more claims per patient (35.94 vs 39.67; p < 0.0001) and increased per-patient healthcare costs (US$21,308 vs US$27,270; p < 0.0001). Porphyria cases incurred US$7839 more in total unadjusted costs compared with controls in the 12 months after index date. Compared with controls, cases also had more claims (39.67 vs 34.81), primarily due to inpatient admissions (1.80 vs 0.78) and outpatient visits (21.41 vs 17.98). Cases also had higher healthcare costs for inpatient admissions (US$8882 vs US$4674) and outpatient visits (US$12,378 vs US$9801).ConclusionPorphyria is associated with significant healthcare costs and utilization burdens driven by increased inpatient admissions, outpatient visits, and pharmaceutical claims.
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