Cost-Effectiveness Modeling of Prostate-Specific Membrane Antigen Positron Emission Tomography with Piflufolastat F 18 for the Initial Diagnosis of Patients with Prostate Cancer in the United States.

BACKGROUND AND OBJECTIVES: Piflufolastat F 18 is a novel prostate-specific membrane antigen (PSMA)-targeted positron emission tomography (PET) radiotracer that is superior to standard of care (SOC) imaging for the initial staging of prostate cancer and the detection of biochemical recurrence. As piflufolastat F 18 has been approved in the United States (US) for this indication, this modeling study assessed the cost effectiveness of piflufolastat F 18 versus fluciclovine F-18, gallium68-PSMA-11 (PSMA 11), and SOC imaging (a mix of bone scans, computed tomography, and magnetic resonance imaging) for the diagnosis and staging of prostate cancer from a US healthcare system perspective. PERSPECTIVE: A US third-party payer perspective was used, which for this population reflects a mix of commercial and Medicare, considering only direct healthcare costs. SETTING: This study utilized a tertiary healthcare setting. METHODS: A decision tree was used to map the diagnostic/treatment pathway, consisting of the proportion of patients with local, regional, distant, or no disease; prostate-specific antigen (PSA) ≤ 1.0 or > 1.0; and accuracy of imaging modalities. A Markov model predicted the long-term outcomes of disease progression according to treatment decisions. Inputs to the model were informed by data from the OSPREY and CONDOR clinical trials, public data, and the literature. Treatment mix included active surveillance, radiation therapy, prostatectomy, androgen deprivation therapy (ADT), and radiation therapy + ADT, informed by expert opinion. Outcomes included life-years (LY), quality-adjusted life-years (QALY), and the incremental cost-effectiveness ratio (ICER). All costs were reported in 2021 US dollars, using the US Bureau of Labor Statistics Consumer Price Index. A willingness-to-pay (WTP) threshold of $150,000 was considered cost effective, consistent with the upper range used as the standard for price benchmarks by the Institute for Clinical and Economic Review. The robustness of the base-case results was assessed in deterministic and probabilistic sensitivity analyses. RESULTS: Over a lifetime horizon, piflufolastat F 18 had the greatest effectiveness in terms of LYs (6.80) and QALYs (5.33); for the comparators, LYs ranged from 6.58 (SOC) to 6.76 (PSMA 11) and QALYs ranged from 5.12 (SOC) and 5.30 (PSMA 11). Piflufolastat F 18 was more cost effective compared with fluciclovine F 18, PSMA 11, and SOC, with ICERs of $21,122, $55,836, and $124,330 per QALY gained, respectively. Piflufolastat F 18 was associated with the greatest net monetary benefit ($627,918) compared with the other options at a WTP threshold of $150,000. The results of the deterministic and probabilistic sensitivity analyses supported the robustness of the base-case results. CONCLUSIONS: This study suggests that piflufolastat F 18 is a cost-effective diagnostic option for men with prostate cancer in the US, with higher associated LY, QALY, and greater net monetary benefit than fluciclovine F 18, PSMA 11, and SOC imaging.

Outcomes and resource use of patients with large hemispheric infarction and cerebral edema: analysis of real-world data.

OBJECTIVE: Large hemispheric infarction (LHI) is associated with a high likelihood of the evolution of life-threatening edema. Few studies have assessed real-world clinical outcomes and management strategies among patients with LHI. The objective of this study was to describe the management, in-hospital outcomes, and direct healthcare resource burden of patients with LHI, as well as those of patients with subsequent cerebral edema. METHODS: This observational, retrospective cohort study analyzed de-identified data from US adult patients using the IBM MarketScan Hospital Drug Database (Q4-2015 to Q4-2017). Patients were included in the "Possible LHI" or the "Other Ischemic Strokes" cohorts using ICD-10 diagnosis codes. Patients with possible LHI were further categorized into "LHI with Edema" and "LHI without Edema" subgroups using diagnosis and procedure codes. Select clinical and economic outcomes were compared between cohorts and subgroups using multivariable regressions. RESULTS: Of 79,201 eligible encounters with ischemic strokes, 11,772 unique patients were assigned to the Possible LHI cohort while 67,429 were assigned to the Other Ischemic Strokes cohort. Among patients with possible LHI, 869 (7%) were assigned to the LHI with Edema subgroup and 10,903 (93%) were assigned to the LHI without Edema subgroup. Patients in the Possible LHI cohort had longer hospital stays (mean difference [MD] [95%CI] = 2.6 [2.4;2.8] days), higher total facility charges (MD [95%CI] = $28,656 [26,794;30,524]), and higher odds of death (odds ratio [95%CI] = 2.2 [2.0;2.4]) than the Other Ischemic Strokes cohort. Among patients with possible LHI, the incremental clinical and resource burden was further exacerbated in the subgroup of patients with edema (hospital days: MD [95%CI] = 5.0 [3.9;6.2] days; total facility charges: MD [95%CI] = $59,585 [50,816;67,583]; mortality: odds ratio [95%CI] = 10.3 [8.5;12.4]). CONCLUSIONS: Among patients with ischemic strokes, LHI was associated with increased clinical management and direct healthcare resource burden in real-world hospital settings. The burden was substantially increased among patients who developed cerebral edema.

Cost-per-remitter with esketamine nasal spray versus standard of care for treatment-resistant depression.

Aim: Estimate the cost-per-remitter with esketamine nasal spray plus an oral antidepressant (ESK + oral AD) versus oral AD plus nasal placebo (oral AD + PBO) among patients with treatment-resistant depression. Patients & methods: An Excel-based model was developed to estimate the cost-per-remitter for ESK + oral AD versus oral AD + PBO over 52 weeks from multiple US payer perspectives. Clinical end points and cost inputs were derived from clinical trials and the literature, respectively. Results: Under the base-case scenario, the cost-per-remitter for ESK + oral AD and oral AD + PBO were as follows: Commercial: US$85,808 versus US$100,198; Medicaid: US$76,236 versus US$96,067; Veteran's Affairs: US$77,765 versus US$104,519; and Integrated Delivery Network: US$103,924 versus US$142,766. Conclusion: The findings suggest that ESK + oral AD is a cost-efficient alternative treatment for treatment-resistant depression compared with oral AD + PBO.

Lay abstract The US FDA recently approved esketamine nasal spray plus an oral antidepressant (AD) as a new treatment for adults with treatment-resistant depression. We developed an Excel-based model to understand whether esketamine + oral AD treatment offers better value for the money spent, compared with treatment with oral AD alone. We find that the higher annual costs of esketamine + oral AD treatment are more than offset by the better clinical outcomes achieved with this treatment. Specifically, in a given year, more people treated with esketamine + oral AD versus oral AD alone achieved and remained in remission, and as a result, they incurred fewer other medical costs.

Disease severity at the time of initial cognitive assessment is related to prior health-care resource use burden.

INTRODUCTION: Research has shown increased health-care resource use (HRU) among patients with Alzheimer's disease and related disorders (ADRD) well before diagnosis, but the degree to which HRU is correlated with disease severity at the time of initial assessment is not well documented. METHODS: Retrospective analysis of linked medical records and claims data for three cohorts: mild ADRD (first [index] Mini-Mental State Examination [MMSE] ≥20), moderate/severe ADRD (index MMSE < 20), controls without cognitive impairment. HRU during the pre-index year was compared using multivariate regressions. RESULTS: ADRD cohorts had significantly (P < .01) higher HRU than controls. Compared to mild ADRD patients, moderate/severe ADRD patients had higher rates of hospitalizations (relative risk [RR]: 1.57), emergency department visits (RR: 1.36), potentially avoidable hospitalizations (RR: 1.72), and accidental falls (RR: 1.58). DISCUSSION: HRU before initial assessment increases with disease severity at the time of assessment, highlighting the need for timely evaluation and improved management in the earliest stages of ADRD.

Temporal and Geographic Variation in the Incidence of Alzheimer's Disease Diagnosis in the US between 2007 and 2014.

OBJECTIVES: Our aim was to describe the incidence of Alzheimer's disease (AD) in the United States, overall and by geographic region. DESIGN: We conducted retrospective analyses of administrative claims data for a 5% random sample of US Medicare beneficiaries aged 65 years or older. AD incidence, defined as a diagnosis for AD (International Classification of Disease, Ninth Revision, Clinical Modification code 331.0×) in a given year, with no AD diagnosis in the beneficiary's entire medical history, was estimated for each calendar year between 2007 and 2014. Beneficiaries were required to be enrolled in Medicare for the calendar year of evaluation as well as the preceding 12 months. In addition, a cross-sectional assessment of geographic variation in AD incidence was conducted for 2014. For each population area (specifically, core-based statistical area, as defined by the US Census Bureau), AD incidence was estimated overall, as well as adjusted for differences in underlying patient demographics and metrics of access to care and quality of care. Changes in AD incidence from 2007 were also estimated. SETTING: US fee-for-service Medicare. PARTICIPANTS: US Medicare beneficiaries aged 65 years or older with no history of AD. RESULTS: Overall, the diagnosed incidence of AD decreased over time, from 1.53% in 2007 to 1.09% in 2014; trends were similar for most population areas. In 2014, the rates of AD incidence ranged from 0% to more than 3% across population areas, with the highest observed incidence rates in areas of the Midwest and the South. Statistical models explain little of the geographic variation, although following adjustment, the incidence rates increased the most (in relative terms) in rural areas of western states. CONCLUSION: Our findings are consistent with previously reported estimates of incidence of AD in the United States and its recent declining trend. Additionally, the study highlights the considerable geographic variation in the incidence of AD in the United States and suggests that further research is needed to better understand the determinants of this geographic variation. J Am Geriatr Soc 68:346-353, 2020.

Economic and clinical benefits of early identification of acute kidney injury using a urinary biomarker.

Purpose: To evaluate the budget impact of adding a diagnostic test of tissue inhibitor of metalloproteinase 2 and insulin-like growth factor binding protein 7 ([TIMP-2]·[IGFBP7]), which identifies patients at risk of moderate-to-severe acute kidney injury (AKI), to the current standard of care (SOC) in a hospital setting.Materials and methods: A budget impact model (2017 USD) was developed from the perspective of a hypothetical US hospital system serving 10,000 inpatients annually. The model estimated the impact of assessing the risk of AKI using SOC vs a combination of SOC and the US Food and Drug Administration-approved assay [TIMP-2]·[IGFBP7] over a 1-year period. Potential cost implications were assessed using estimates for payer mix among patients, diagnostic efficacy, and patient healthcare resource utilization. The model also considered provider adoption rates and the estimated costs of [TIMP-2]·[IGFBP7].Results: Compared to SOC alone, adding [TIMP-2]·[IGFBP7] to SOC was associated with a $1,855 reduction in uncompensated care per patient tested, which, after accounting for the additional costs of the test ($277), resulted in net savings of $1,578 per patient tested. The findings were robust to input parameter variations, as demonstrated by deterministic and probabilistic sensitivity analyses. In the probabilistic sensitivity analyses, net cost savings to the hospital ranged from $50,308-$3,971,514, or $101-$7,943 per tested patient (mean = $1,710; 95% confidence interval = $1,691-$1,729).Conclusions: The introduction of [TIMP-2]·[IGFBP7] as a novel tool in the identification of AKI risk may result in considerable cost savings from a hospital perspective under this model's base-case assumptions. Further prospective studies are needed to confirm these findings in a real-world setting.Key points for decision makersAn economic model was constructed to determine the budget impact of adding a diagnostic test ([TIMP-2]·[IGFBP7]), which identifies patients at risk of moderate-to-severe acute kidney injury, to the current standard of care (SOC) in a hospital setting.According to the present model, the use of [TIMP-2]·[IGFBP7] to identify acute kidney injury risk may reduce costs for hospitals by ∼$1,578 per patient tested.

The Economic Burden of Abuse of Prescription Opioids: A Systematic Literature Review from 2012 to 2017.

BACKGROUND: Abuse of prescription opioids [opioid use disorder (OUD), poisoning, and fatal and non-fatal overdose] is a public health and economic challenge that is associated with considerable morbidity and mortality in the USA and globally. OBJECTIVE: To systematically review and summarize the health economics literature published over the last 5 years that describes the economic burden of abuse of prescription opioids. METHODS: Findings from searches of databases including MEDLINE, Embase, and Cochrane CENTRAL as well as hand searches of multiple conference abstracts were screened against predefined inclusion criteria to identify studies reporting cost and healthcare resource utilization (HRU) data associated with abuse of prescription opioids. RESULTS: A total of 49 unique studies were identified. Most of the studies examined direct costs and HRU, which were substantially higher for abusers of prescription opioids than non-abuser controls in several matched cohort analyses (US$20,343-US$28,718 vs US$9716-US$14,079 for mean direct combined annual healthcare costs reported in 6 studies). Although only a small number of studies reported indirect costs, these findings suggest a high societal burden related to productivity losses, absenteeism, morbidity, and mortality among those who abuse opioids. Studies of medication-assisted treatment demonstrated that factors such as adherence, dose, formulation (film or tablet), and relapse during treatment, were associated with direct costs and HRU among treated patients. CONCLUSIONS: This systematic literature review shows that abuse of prescription opioids is characterized by substantial direct healthcare costs, medical utilization, and related societal costs. Future research should further investigate the indirect costs of opioid abuse.

One-Year Effect of the Medicare Annual Wellness Visit on Detection of Cognitive Impairment: A Cohort Study.

OBJECTIVES: To examine the effect of the Medicare Annual Wellness Visit (AWV) on the detection of cognitive impairment and on follow-up cognitive care for older adults. DESIGN: Retrospective matched-cohort study. SETTING: United States. PARTICIPANTS: A 5% random sample of fee-for-service Medicare beneficiaries continuously enrolled for 12 months before and after an index ambulatory visit occurring from 2011 to 2013 with no claims evidence of cognitive impairment before index. MEASUREMENTS: Outcomes include 12-month post-index visit claims-based measurements of cognitive impairment, including new Alzheimer's disease and related dementia (ADRD) diagnoses; medications for ADRD; and cognitive care-related diagnostic examination such as neurobehavioral testing, brain imaging, and blood tests for thyroid-stimulating hormone (TSH), serum B12, folate, and syphilis. We also measured changes in burden of anticholinergic medication. RESULTS: There were no clinically relevant differences between the AWV and control groups in the rates of incident ADRD diagnoses (6.16% vs 6.86%, p<.001) and initiation of ADRD medications (1.00% vs 1.08%, p=.15), although there were differences favoring the AWV group in rates of TSH (39.80% vs 28.36%, p<.001), B12 (9.41% vs 6.97%, p<.001), folate (4.76% vs 3.72%, p<.001), and neurobehavioral (0.75% vs 0.55%, p<.001) testing. CONCLUSIONS: Although the AWV is correlated with an increase in some measures of cognitive care, such as laboratory testing for reversible causes of cognitive impairment, it does not appear to substantially increase recognition of undetected ADRD.

Opioid Abuse: A Detailed Examination of Cost Drivers over a 24-Month Follow-up Period.

BACKGROUND: Previous work has documented the considerable economic burden associated with opioid abuse, dependence, and overdose/poisoning (hereafter, "abuse"). Recent analyses have provided insights into the trajectory and drivers of the excess costs of abuse both before and after diagnosis, showing the important role of other substance abuse, mental health issues, and painful conditions. OBJECTIVE: To build on the recently published study by Kirson et al. (2017) and extend its findings by (a) evaluating the trajectory of excess costs of abuse for an additional year after an incident abuse diagnosis and (b) exploring the diagnosis-level drivers of excess costs over time in greater detail. METHODS: Using administrative medical and pharmacy claims, which included payment amounts, for beneficiaries covered by large self-insured companies throughout the United States, abusers were matched to controls using the same methods as in Kirson et al. Excess health care costs were assessed over a 24-month follow-up period, which comprised the 6 months before the initial abuse diagnosis and the 18 months after. Drivers of excess costs were then evaluated by diagnosis (grouped at the 3-digit ICD-9-CM level). RESULTS: This study analyzed 9,345 matched pairs of abusers and non-abusers. Similar to the previous study, mean per-patient excess health care costs were found to rise considerably leading up to and shortly after the incident diagnosis of abuse, reaching $15,764 over the first half of the follow-up period. Over the newly extended follow-up period (months 6 to 18 after diagnosis), excess costs remained elevated ($7,346) and did not return to baseline levels. Over time, an increasing share of excess costs was observed for outpatient services and prescription drug use, relative to acute care settings. A detailed examination of cost drivers suggested elevated costs in several clinical categories (e.g., gastrointestinal, respiratory conditions) beyond those previously identified. CONCLUSIONS: This research finds that the excess medical costs of abuse extend for at least 1 more year than previously documented, reflecting the need for considerable follow-up care over time. The identification of several other clinical categories with elevated excess costs suggests important areas for future research into the interaction of opioid abuse with the management of other conditions. DISCLOSURES: This study was funded by Purdue Pharma. Howard was an employee of Purdue Pharma at the time that this study was conducted. Kirson, Scarpati, Jia, and Wen are employees of Analysis Group, which received funding from Purdue Pharma to conduct this study. Study concept and design were contributed by Kirson, Scarpati, and Howard, along with Jia and Wen. Jia and Wen took the lead in data collection, with assistance from Scarpati and Kirson. Data interpretation was performed by Scarpati, Kirson, and Howard, with assistance from Jia and Wen. The manuscript was written and revised by Scarpati, Kirson, and Howard.

Drivers of excess costs of opioid abuse among a commercially insured population.

OBJECTIVES: To replicate and extend a recently published analysis of the drivers of excess costs of opioid abuse. STUDY DESIGN: Retrospective data analysis using de-identified claims data from the Truven MarketScan Commercial Claims and Encounter database. METHODS: Medical and prescription drug claims from beneficiaries covered by large self-insured US companies were used to select patients with incident diagnoses of opioid abuse between 2012 and 2015. Two cohorts, abusers and nonabusers, were matched using propensity score methods. Excess healthcare costs were estimated over a 6-month baseline period and 12-month follow-up period. Cost drivers were assessed by diagnosis (3-digit International Classification of Diseases, Ninth Revision, Clinical Modification groupings) and place of service. RESULTS: The analysis included 73,714 matched pairs of abusers and nonabusers. Relative to nonabusers, abusers had considerably higher annual healthcare costs of $10,989 per patient, or $1.98 per member per month. Excess costs were similar, yet lower, than the previous analysis using another commercial claims database. In both analyses, a ramp-up in excess costs was observed prior to the incident abuse diagnosis, followed by a decline post diagnosis, although not to baseline levels. Key drivers of excess costs in the 2 studies included opioid use disorders, nonopioid substance misuse, and painful and mental health conditions. From 2010 to 2014, the prevalence of diagnosed opioid abuse doubled, with incidence rates exhibiting an increasing, though flatter, trend than earlier in the period. CONCLUSIONS: Opioid abuse imposes a considerable economic burden on payers. Many abusers have complex healthcare needs and may require care beyond that which is required to treat opioid abuse. These results are robust and consistent across different data sources.

The Economic Burden of Opioid Abuse: Updated Findings.

BACKGROUND: Opioid pain relievers can be highly effective in providing relief for patients suffering from pain. At the same time, prescription opioid abuse, dependence, overdose, and poisoning (hereinafter "abuse") have become a national public health concern. Opioid abuse is also costly: previous estimates of the annual excess costs of opioid abuse to payers range from approximately $10,000 to $20,000 per patient. OBJECTIVES: To (a) provide a comprehensive, current estimate of the economic burden of opioid abuse to commercial payers and (b) explore the drivers of these excess costs of abuse. METHODS: Administrative claims from beneficiaries covered by large self-insured companies throughout the United States were used to identify patients diagnosed with opioid abuse, dependence, and overdose/poisoning ("abuse") between 2012 and 2015. Sample selection criteria identified patients most likely to be misusing opioids. Abusers and nonabuser controls were matched using propensity scores. Excess health care costs were assessed over the 18-month study period. Drivers of excess costs were then evaluated by place of service and medical condition (identified as 3-digit ICD-9-CM groupings). RESULTS: 9,342 matched abuser/nonabuser pairs were analyzed. Relative to nonabusers, abusers had significantly higher annual health care resource utilization, leading to $14,810 in per-patient incremental annual health care costs. Excess costs began accumulating 5 months before the formal, incident diagnosis of abuse, driven by alcohol and nonopioid substance abuse. Major drivers of excess costs of abuse included opioid and other substance abuse disorders, mental health conditions, and painful conditions. Many patients had diagnoses for other substance abuse that predated their opioid abuse diagnoses. CONCLUSIONS: Opioid abuse imposes a substantial economic burden on payers and often occurs in the context of other substance abuse. Poly-substance abuse often precedes the diagnosis of opioid abuse. DISCLOSURES: This study was funded by Purdue Pharma. Mayne is an employee of Purdue Pharma. Kirson, Scarpati, and Birnbaum are employees of Analysis Group, which received funding from Purdue Pharma to conduct this study. Enloe and Dincer were employees of Analysis Group at the time this research was conducted. Study concept and design were contributed by Kirson, Birnbaum, Mayne, and Scarpati, along with Enloe and Dincer. Enloe and Dincer took the lead in data collection, along with Birnbaum and assisted by Kirson and Scarpati. Data interpretation was performed by all the authors. The manuscript was written and revised by Kirson and Scarpati, along with Mayne and Birnbaum.

Assessing the economic burden of Alzheimer's disease patients first diagnosed by specialists.

BACKGROUND: It is not known if there is a differential impact on Alzheimer's disease (AD) diagnosis and outcomes if/when patients are diagnosed with cognitive decline by specialists versus non-specialists. This study examined the cost trajectories of Medicare beneficiaries initially diagnosed by specialists compared to similar patients who received their diagnosis in primary care settings. METHODS: Patients with ≥2 claims for AD were selected from de-identified administrative claims data for US Medicare beneficiaries (5 % random sample). The earliest observed diagnosis of cognitive decline served as the index date. Patients were required to have continuous Medicare coverage for ≥12 months pre-index (baseline) and ≥12 months following the first AD diagnosis, allowing for up to 3 years from index to AD diagnosis. Time from index date to AD diagnosis was compared between those diagnosed by specialists (i.e., neurologist, psychiatrist, or geriatrician) versus non-specialists using Kaplan-Meier analyses with log-rank tests. Patient demographics, Charlson Comorbidity Index (CCI) during baseline, and annual all-cause medical costs (reimbursed by Medicare) in baseline and follow-up periods were compared across propensity-score matched cohorts. RESULTS: Patients first diagnosed with cognitive decline by specialists (n = 2593) were younger (78.8 versus 80.8 years old), more likely to be male (40 % versus 34 %), and had higher CCI scores and higher medical costs at baseline than those diagnosed by non-specialists (n = 13,961). However, patients diagnosed by specialists had a significantly shorter time to AD diagnosis, both before and after matching (mean [after matching]: 3.5 versus 4.6 months, p < 0.0001). In addition, patients diagnosed by specialists had significantly lower average total all-cause medical costs in the first 12 months after their index date, a finding that persisted after matching ($19,824 versus $25,863, p < 0.0001). Total per-patient annual medical costs were similar for the two groups starting in the second year post-index. CONCLUSIONS: Before and after matching, patients diagnosed by a specialist had a shorter time to AD diagnosis and incurred lower costs in the year following the initial cognitive decline diagnosis. Differences in costs converged during subsequent years. This suggests that seeking care from specialists may yield more timely diagnosis, appropriate care and reduced costs among those with cognitive decline.

Excess Costs Associated with Possible Misdiagnosis of Alzheimer's Disease Among Patients with Vascular Dementia in a UK CPRD Population.

BACKGROUND: Prior diagnosis of Alzheimer's disease (AD) among patients later diagnosed with vascular dementia (VaD) has been associated with excess costs, suggesting potential benefits of earlier rule-out of AD diagnosis. OBJECTIVE: To investigate whether prior diagnosis with AD among patients with VaD is associated with excess costs in the UK. METHODS: Patients with a final VaD diagnosis, continuous data visibility for≥6 months prior to index date, and linkage to Hospital Episode Statistics data were retrospectively selected from de-identified Clinical Practice Research Datalink data. Patients with AD diagnosis before a final VaD diagnosis were matched to similar patients with no prior AD diagnosis using propensity score methods. Annual excess healthcare costs were calculated for 5 years post-index, stratified by time to final diagnosis. RESULTS: Of 9,311 patients with VaD, 508 (6%) had prior AD diagnosis with a median time to VaD diagnosis exceeding 2 years from index date. Over the entire follow-up period, patients with prior AD diagnosis had accumulated healthcare costs that were approximately GBP2,000 higher than those for matched counterparts (mostly due to higher hospitalization costs). Cost differentials peaked particularly in the period including the final VaD diagnosis, with excess costs quickly declining thereafter. CONCLUSION: Potential misdiagnosis of AD among UK patients with VaD resulted in substantial excess costs. The decline in excess costs following a final VaD diagnosis suggests potential benefits from earlier rule-out of AD.

Basal insulin persistence, associated factors, and outcomes after treatment initiation among people with type 2 diabetes mellitus in the US.

OBJECTIVE: To assess basal insulin persistence, associated factors, and economic outcomes for insulin-naïve people with type 2 diabetes mellitus (T2DM) in the US. RESEARCH DESIGN AND METHODS: People aged ≥18 years diagnosed with T2DM initiating basal insulin between April 2006 and March 2012 (index date), no prior insulin use, and continuous insurance coverage for 6 months before (baseline) and 24 months after index date (follow-up period) were selected using de-identified administrative claims data in the US. Based on whether there were ≥30 day gaps in basal insulin use in the first year post-index, patients were classified as continuers (no gap), interrupters (≥1 prescription after gap), and discontinuers (no prescription after gap). MAIN OUTCOME MEASURES: Factors associated with persistence - assessed using multinomial logistic regression model; annual healthcare resource use and costs during follow-up period - compared separately between continuers and interrupters, and continuers and discontinuers. RESULTS: Of the 19,110 people included in the sample (mean age: 59 years, ∼60% male), 20% continued to use basal insulin, 62% had ≥1 interruption, and 18% discontinued therapy in the year after initiation. Older age, multiple antihyperglycemic drug use, and injectable antihyperglycemic use during baseline were associated with significantly higher likelihoods of continuing basal insulin. Relative to interrupters and discontinuers, continuers had fewer emergency department visits, shorter hospital stays, and lower medical costs (continuers: $10,890, interrupters: $13,674, discontinuers: $13,021), but higher pharmacy costs (continuers: $7449, interrupters: $5239, discontinuers: $4857) in the first year post-index (p < 0.05 for all comparisons). Total healthcare costs were similar across the three cohorts. Findings for the second year post-index were similar. CONCLUSIONS: The majority of people in this study interrupted or discontinued basal insulin treatment in the year after initiation; and incurred higher medical resource use and costs than continuers. The findings are limited to the commercially insured population in the US. In addition, persistence patterns were assessed using administrative claims as opposed to actual medication-taking behavior and did not account for measures of glycemic control. Further research is needed to understand the reasons behind basal insulin persistence and the implications thereof, to help clinicians manage care for T2DM more effectively.

Characteristics of High-Cost Patients Diagnosed with Opioid Abuse.

BACKGROUND: Prescription opioid abuse is associated with substantial economic burden, with estimates of incremental annual per-patient health care costs of diagnosed opioid abuse exceeding $10,000 in prior literature. A subset of patients diagnosed with opioid abuse has disproportionately high health care costs, but little is known about the characteristics of these patients.  OBJECTIVE: To describe the characteristics of a subset of patients diagnosed with opioid abuse with disproportionately high health care costs to assist physicians and managed care organizations in targeting interventions at the costliest patients. METHODS: This retrospective claims data analysis identified patients aged 12 to 64 years diagnosed with opioid abuse/dependence in the OptumHealth Reporting and Insights medical and pharmacy claims database, Quarter 1 (Q1) 1999-Q1 2012. Inclusion criteria required that patients had a diagnosis of opioid abuse during or after Q1 2006, no prior diagnoses of opioid abuse, and continuous non-HMO coverage over an 18-month study period. The study period comprised a 12-month observation period centered on the date of the first opioid abuse diagnosis (index date) and a 6-month baseline period immediately preceding the observation period. Patients in the top 20% of total health care costs in the observation period were classified as "high-cost patients," and the remaining patients were classified as "lower-cost patients." Patient characteristics, comorbidities, health care resource use, and health care costs were compared between high-cost patients and lower-cost patients using chi-square tests for dichotomous variables and Wilcoxon rank-sum tests for continuous variables. In addition, multivariate regression was used to assess the relationship between patient characteristics in the baseline period and total health care costs in the observation period among all patients diagnosed with opioid abuse.  RESULTS: 9,291 patients diagnosed with opioid abuse met the inclusion criteria. The 20% of patients classified as high-cost patients accounted for approximately two thirds of the total health care costs of patients diagnosed with opioid abuse. Compared with lower-cost patients, high-cost patients were older (42.5 vs. 36.1; P less than 0.001) and more likely to be female (55.9% vs. 42.9%; P less than 0.001). They had a higher comorbidity burden at baseline, as reflected in the Charlson Comorbidity Index (0.8 vs. 0.2; P less than 0.001), and rates of conditions such as chronic pulmonary disease (12.9% vs. 5.6%; P less than 0.001) and mild/moderate diabetes (8.4% vs. 3.4%; P less than 0.001). High-cost patients also had higher rates of nonopioid substance abuse diagnoses (12.4% vs. 8.9%; P less than 0.001) and psychotic disorders (26.5% vs. 13.6%; P less than 0.001). In the observation period, high-cost patients continued to have higher rates of nonopioid substance abuse diagnoses (53.0% vs. 47.2%; P less than 0.001) and psychotic disorders (67.1% vs. 47.5%; P less than 0.001). In addition, they had greater medical resource use across all places of service (i.e., inpatient, emergency department, outpatient, drug/alcohol rehabilitation facility, and other) compared with lower-cost patients. The mean observation period health care costs of high-cost patients was $89,177 compared with $11,653 for lower-cost patients (P less than 0.001). High-cost patients had higher medical costs linked to claims with an opioid abuse diagnosis in absolute terms, but the share of total medical costs attributed to such claims was lower among high-cost patients than among lower-cost patients. While many baseline characteristics were found to have a statistically significant (P less than 0.05) association with observation period health care costs, only 27.3% of the variation in observation period health care costs was explained by patient characteristics in the baseline period. CONCLUSIONS: This study found that the costliest patients diagnosed with opioid abuse had high rates of preexisting and concurrent chronic comorbidities and mental health conditions, suggesting potential indicators for targeted intervention and a need for greater awareness and screening of comorbid conditions. Opioid abuse may exacerbate existing conditions and make it difficult for patients to adhere to treatment plans for those underlying conditions. Baseline patient characteristics explained only a small share of the variation in observation period health care costs, however. Future research should explore the degree to which other factors not captured in administrative claims data (e.g., severity of abuse) can explain the wide variation in health care costs among opioid abusers.

Medical costs of Alzheimer's disease misdiagnosis among US Medicare beneficiaries.

INTRODUCTION: Recent developments in diagnostic technology can support earlier, more accurate diagnosis of non-Alzheimer's disease (AD) dementias. METHODS: To evaluate potential economic benefits of early rule-out of AD, annual medical resource use and costs for Medicare beneficiaries potentially misdiagnosed with AD prior to their diagnosis of vascular dementia (VD) or Parkinson's disease (PD) were compared with that of similar patients never diagnosed with AD. RESULTS: Patients with prior AD diagnosis used substantially more medical services every year until their VD/PD diagnosis, resulting in incremental annual medical costs of approximately $9,500-$14,000. However, following their corrected diagnosis, medical costs converged with those of patients never diagnosed with AD. DISCUSSION: The observed correlation between timing of correct diagnosis and subsequent reversal in excess costs is strongly suggestive of the role of misdiagnosis of AD - rather than AD comorbidity - in this patient population. Our findings suggest potential benefits from earlier, accurate diagnosis.

The Burden of Undiagnosed Opioid Abuse Among Commercially Insured Individuals.

OBJECTIVES: Estimate the prevalence and healthcare costs of undiagnosed opioid abuse among commercially insured individuals. STUDY DESIGN: Retrospective analysis of de-identified pharmacy and medical claims data and publicly-available survey data (no IRB approval required). METHODS: This study focused on commercially insured individuals. Rates of prescription pain-reliever abuse/dependence ("abuse") among individuals ages ≥12 were calculated using National Survey on Drug Use and Health (NSDUH) public-use data for 2006-2011 and assumed to capture both diagnosed and undiagnosed opioid abuse. Rates of undiagnosed opioid abuse were calculated as the difference between NSDUH rates and published rates of diagnosed opioid abuse. OptumHealth Reporting and Insights claims data were used to estimate the healthcare costs of undiagnosed abuse. Diagnosed abusers ages 12-64 were identified using ICD-9-CM diagnosis codes for opioid abuse/dependence. Pre-diagnosis costs were assumed to be a proxy for undiagnosed opioid abuse costs. The ratio of undiagnosed to diagnosed abuse costs was calculated as the ratio of annual per-patient healthcare costs between pre-diagnosis and post-diagnosis periods. RESULTS: While rates of diagnosed opioid abuse among commercially insured individuals increased from 0.07% in 2006 to 0.19% in 2011, rates of undiagnosed abuse decreased from 0.42% to 0.38% over the same time period. Annual per-patient healthcare costs of undiagnosed abusers were 69.2% of those of diagnosed abusers. CONCLUSIONS: Per-patient healthcare costs of undiagnosed abusers among the commercially insured are estimated to be lower than those of diagnosed abusers. However, the higher prevalence of undiagnosed opioid abuse implies that undiagnosed abuse represents a substantial burden to commercial payers.

Medical resource use and costs among pain patients with potential opioid-tolerability issues.

OBJECTIVE: To estimate excess medical resource use and costs associated with prescription opioid (RxO) tolerability issues. DESIGN: This was an observational, retrospective analysis of deidentified administrative claims data. SETTING: The study included commercially insured patients treated in different healthcare settings captured in the Truven MarketScan claims database. PATIENTS: Patients aged 18-64 years initiating treatment with an RxO (index) and continuously treated with pain relievers over a 6-month period were selected. "Switchers" were patients who discontinued their index RxO and switched to non-RxO pain relievers < 30 days post-index, and whose last pain reliever in the 6-month follow-up period was not an RxO. Such switching was considered a proxy for RxO-tolerability issues. "Continuous RxO users" were patients who remained on the index RxO for the follow-up period. Switchers and continuous RxO users were matched 1:1 on propensity score, baseline medical costs, index RxO days supply, and short-/long-acting index RxO. MAIN OUTCOME MEASURES: Six-month follow-up medical resource use and costs were compared between matched switchers and continuous RxO users. RESULTS: A total of 10,704 pairs of switchers and continuous RxO users were matched. In the 6-month follow-up period, switchers had more outpatient (7.5 vs 6.8; p < 0.001) and inpatient (0.05 vs 0.04; p = 0.002) visits and longer inpatient stays (0.26 days vs 0.19; p = 0.006) compared to continuous RxO users. Switchers also had higher total medical costs ($4,522 vs $3,657; p < 0.001). CONCLUSIONS: Switchers incur greater medical resource use and costs than similar patients continuously treated with their index RxO.

The economic burden of diagnosed opioid abuse among commercially insured individuals.

The abuse of prescription opioids imposes a substantial public health and economic burden. Recent research using administrative claims data has substantiated the prevalence and cost of opioid abuse among commercially insured individuals. Although administrative claims data are readily available and have been used to effectively answer research questions about the burden of illness for many different conditions, an important issue is the reliability, replicability, and generalizability of estimates derived from different databases. Therefore, this study sought to assess whether the findings of a recently published study of opioid abuse in a commercial claims database (original analysis) could be replicated in a different commercial claims database. The original analysis, which analyzed the prevalence and excess health care costs of diagnosed opioid abuse in the OptumHealth Reporting and Insights Database, was replicated by applying the same approach to the Truven MarketScan Commercial Claims and Encounters Database (replication analysis). In the replication analysis, the prevalence of diagnosed opioid abuse increased steadily from 15.8 diagnosed opioid abusers per 10,000 in 2009, to 26.6 diagnosed opioid abusers per 10,000 in 2012. Although the prevalence of diagnosed opioid abuse was higher than reported in the original analysis, the trend of increasing prevalence over time was consistent across analyses. Additionally, diagnosed abusers had excess annual per patient health care costs of $11,376 in the replication analysis, which was consistent with the excess annual per patient health care costs of diagnosed abuse of $10,627 reported in the original analysis. The replication analysis also found an upward trend in the prevalence of diagnosed opioid abuse over time and substantial excess annual per patient health care costs of diagnosed opioid abuse among commercially insured individuals, suggesting that these findings are generalizable to other commercially insured populations.