Clinical validation of a cell-free DNA fragmentome assay for augmentation of lung cancer early detection.

Lung cancer screening via annual low-dose computed tomography (LDCT) has poor adoption. We conducted a prospective case-control study among 958 individuals eligible for lung cancer screening to develop a blood-based lung cancer detection test that when positive is followed by an LDCT. Changes in genome-wide cell-free DNA (cfDNA) fragmentation profiles (fragmentomes) in peripheral blood reflected genomic and chromatin characteristics of lung cancer. We applied machine learning to fragmentome features to identify individuals who were more or less likely to have lung cancer. We trained the classifier using 576 cases and controls from study samples, and then validated it in a held-out group of 382 cases and controls. The validation demonstrated high sensitivity for lung cancer, and consistency across demographic groups and comorbid conditions. Applying test performance to the screening eligible population in a five-year model with modest utilization assumptions suggested the potential to prevent thousands of lung cancer deaths.

Value of next generation sequencing (NGS) testing in advanced cancer patients.

OBJECTIVE: The availability of targeted therapies for oncology patients is increasing. Available genomic tests to identify treatment-eligible patients include single gene tests and gene panel tests, including the whole-exome, whole-transcriptome OncoExTra test. We assessed the costs and clinical benefits of test choice. METHODS: A Microsoft Excel-based model was developed to evaluate test choice in patients with advanced/metastatic non-small cell lung cancer (NSCLC), breast, prostate, and colorectal cancer. Treatment pathways were based on NCCN guidelines and medical expert opinion. Inputs were derived from published literature. Annual economic results and lifetime clinical results with OncoExTra testing were projected per-tested-patient and compared with single gene testing and no testing. Separately, results were estimated for a US health plan without the OncoExTra test and with its use in 5% of patients. RESULTS: Compared with no genomic testing, OncoExTra test use increased costs by $4,915 per patient; however, 82%-92% of individuals across tumour types were identified as eligible for targeted therapy or a clinical trial. Compared with single gene testing, OncoExTra test use decreased costs by $9,966 per-patient-tested while increasing use of approved or investigational targeted therapies by 20%. When considering a hypothetical health plan with 1 million members, 858 patients were eligible for genomic testing. Using the OncoExTra test in 5% of those eligible, per-member per-month costs decreased by $0.003, ranging from cost-savings of $0.026 in NSCLC patients to a $0.009 increase in prostate cancer patients. Cost-savings were driven by reduced treatment costs with increased clinical trial enrolment and reduced direct and indirect medical costs associated with targeted treatments. LIMITATIONS: Limitations include the required simplifications in modelling complex conditions that may not fully reflect evolving real-world testing and treatment patterns. CONCLUSIONS: Compared to single-gene testing, results indicate that using next generation sequencing test such as OncoExTra identified more actionable alterations, leading to improved outcomes and reduced costs.

Reduced mortality, complications, and economic burden among medicare beneficiaries receiving influenza antivirals.

INTRODUCTION: Antiviral therapy may be underutilized in patients at high risk for increased clinical and economic burden (e.g. older adults). We aimed to examine the benefits associated with antiviral treatment of seasonal influenza among treated and untreated Medicare beneficiaries. METHODS: This retrospective study of Medicare Claims Research Identifiable Files identified patients ≥66 years old with an influenza diagnosis in outpatient setting between October 2016-March 2019 (flu seasons 2016-2018). Index date defined as date of first claim with influenza diagnosis; baseline as the 12 months pre-index. Treated patients received antivirals ≤2 days from index. Untreated patients had no antivirals ≤6 months post-index. Treated/untreated patients were 1:1 propensity score matched. Outcomes (death, all-cause and respiratory-related healthcare resource utilization [HCRU] and costs) were assessed until death or up to 6 months post-index. Descriptive statistics were reported; Kaplan-Meier estimation was used for survival over time. RESULTS: Among 116,901 matched patient pairs, all-cause mortality within 6 months from index diagnosis was 1.6% among treated versus 4.3% among untreated patients. Rates (treated versus untreated) of all-cause inpatient hospitalizations during follow-up were 13.9% versus 22.7% and respiratory-related hospitalizations were 4.2% versus 9.0%. Mean (SD) total all-cause and respiratory-related costs were $9,830 ($18,616.0) and $900 ($4016.4) among the treated, respectively, versus $13,207 ($24,405.1) and $2,024 ($7,623.7) among untreated, respectively. All differences were statistically significant (p < 0.001). CONCLUSIONS: Lack of antiviral treatment is associated with increased mortality, HCRU, and economic burden in older Medicare beneficiaries with seasonal influenza. Future research should investigate whether the choice of antivirals affects influenza burden.

Previous studies have shown that antiviral drugs help prevent flu-related complications and lower healthcare utilization and costs. However, these previous studies have focused on working aged people with existing health problems. Our study looks at how antiviral treatment can lower the health and financial burden caused by the flu in older adults. Using a Medicare claims database from the 2016­2018 flu season, we identified 116,901 matched (treated versus untreated) patient pairs. All-cause mortality within 6 months from the index diagnosis (defined as the first claim with a flu diagnosis) was 1.6% among treated versus 4.3% among untreated patients. Rates (treated versus untreated) of all-cause inpatient hospitalizations during follow-up (defined as 6 months after the index diagnosis date) were 13.9% versus 22.7% and respiratory-related hospitalizations were 4.2% versus 9.0%. Mean total all-cause and respiratory-related costs were $9,830 and $900 among the treated, respectively, versus $13,207 and $2,024 among untreated, respectively. All differences were statistically significant (p < 0.001). This analysis of older adults with the flu found that prompt antiviral treatment is associated with lower rates of mortality and acute complications, reduced hospitalization, and lower healthcare costs. Use of antiviral treatment for patients at high risk of flu, such as older adults, is warranted.

In-hospital mortality in amyloid light chain amyloidosis: analysis of the Premier Healthcare Database.

Aim: Describe the clinical and economic burden of hospitalizations for amyloid light chain (AL) amyloidosis. Materials & methods: This retrospective analysis used nationally representative hospital discharge data (2017-2020) to report discharge status, resource use and costs for hospitalizations among patients with AL amyloidosis. Results: Of 1341 patients identified, 92% were discharged alive and 8% experienced in-hospital death. Compared with the average US hospital stay during 2017-2019 (4.7 days, mean costs of $13,046 and mean charges of $54,496), hospital stays for AL amyloidosis were longer and costlier (9.7 days, $27,098.61, $111,233.91), especially in patients with in-hospital death (12.2 days, $44,966, $182,338.18). Conclusion: AL amyloidosis is associated with significant clinical and economic burden.

Medication Adherence and Healthcare Utilization in Relapsing-Remitting Multiple Sclerosis Patients Using Teriflunomide.

Purpose: Multiple sclerosis (MS) is a costly, immune-mediated disease of the central nervous system. Most patients have relapsing-remitting MS (RRMS) for which disease-modifying therapies (DMTs) provide an effective treatment option by reducing relapse rates. However, adherence to DMTs is suboptimal. This study examines the association between adherence to teriflunomide and clinical and healthcare utilization outcomes. Patients and Methods: Patients with RRMS who started treatment with teriflunomide between 1/1/2018 and 12/31/2019 were analyzed using IQVIA PharMetrics® Plus data. RRMS patients were identified via diagnosis codes and treatment types; the first prescription date for teriflunomide was the index date. Highly and poorly adherent patients were identified based on the proportion of days covered (PDC) post-index (PDC ≥0.8 and PDC ≤0.5, respectively). Patient demographics, clinical characteristics, healthcare utilization during the year pre- and post-index, and relapse rate post-index were reported descriptively. Outcomes were compared between highly and poorly adherent patients through logistic regression. Models were adjusted for demographics, comorbidities, and utilization measures during the baseline period. Results: Among the 922 RRMS patients identified, 534 (57.9%) were highly adherent to teriflunomide, while 249 (27.0%) had PDC ≤0.5. The two groups were not statistically different in terms of demographic characteristics and comorbidities; however, poorly adherent patients were more likely to have emergency department (ED) or inpatient visits during baseline (36.9% versus 26.8%, P=0.004; 17.3% versus 10.9%, P=0.013, respectively). Unadjusted results suggested lower likelihood of both relapses and utilization during follow-up among highly adherent patients compared to poorly adherent patients. Adjusted results confirmed that high adherence was associated with decreased likelihood of post-index relapses, ED utilization, and inpatient utilization (OR [95% CI]: 0.55 [0.39-0.76], 0.49 [0.34-0.71], and 0.51 [0.27-0.97], respectively) even after controlling for baseline utilization. Conclusion: High adherence to teriflunomide was found to be associated with fewer relapses and lower healthcare utilization among patients with RRMS.

Diagnostic amyloid light chain amyloidosis hospitalizations associated with high acuity and cost: analysis of the Premier Healthcare Database.

Aim: Estimate the frequency and costs of diagnostic admissions among hospitalized patients with amyloid light chain (AL) amyloidosis. Materials & methods: This retrospective analysis used nationally representative hospital discharge data from 2017 to 2020 to report resource use and cost for hospitalizations during which AL amyloidosis was diagnosed. Results: Of 1341 admissions, 17.6% were diagnostic. Bone marrow (79.5%) and kidney (44.9%) biopsies were the most common qualifying biopsies. Diagnostic hospitalizations had longer length of stay (14.5 vs 8.4 days; p < 0.001) and higher cost ($40,052 [USD] vs $24,360; p < 0.001) than nondiagnostic ones. Conclusion: Diagnostic admissions are more likely to be urgent/emergent, require longer stays and have higher costs compared with hospitalizations in known AL amyloidosis patients. Improved diagnostic pathways toward early diagnosis are needed.

Estimating Productivity Loss from Breast and Non-Small-Cell Lung Cancer among Working-Age Patients and Unpaid Caregivers: A Survey Study Using the Multiplier Method.

Background. Traditional approaches to capturing health-related productivity loss (e.g., the human capital method) focus only on the foregone wages of affected patients, overlooking the losses caregivers can incur. This study estimated the burden of productivity loss among breast cancer (BC) and non-small-cell lung cancer (NSCLC) patients and individuals caring for such patients using an augmented multiplier method. Design. A cross-sectional survey of BC and NSCLC patients and caregivers measured loss associated with time absent from work (absenteeism) and reduced effectiveness (presenteeism). Respondents reported pre- and postcancer diagnosis income, hours worked, and time to complete tasks. Exploratory multivariable analyses examined correlations between respondents' clinical/demographic characteristics-including industry of employment-and postdiagnosis productivity. Results. Of 204 patients (104 BC, 100 NSCLC) and 200 caregivers (100 BC, 100 NSCLC) who completed the survey, 319 participants (162 BC, 157 NSCLC) working ≥40 wk/y prediagnosis were included in the analysis. More than one-third of the NSCLC (33%) and BC (43%) patients left the workforce postdiagnosis, whereas only 15% of caregivers did. The traditional estimate for the burden of productivity loss was 66% lower on average than the augmented estimate (NSCLC patients: 60%, BC patients: 69%, NSCLC caregivers: 59%, and BC caregivers: 73%). Conclusions. Although patients typically experience greater absenteeism, productivity loss incurred by caregivers is also substantial. Failure to account for such impacts can result in substantial underestimation of productivity gains novel cancer treatments may confer by enabling patients and caregivers to remain in the workforce longer. Our results underscore the importance of holistic approaches to understanding this impact on both patients and their caregivers and accounting for such considerations when making decisions about treatment and treatment value. Highlights: Cancer can have a profound impact on productivity. This study demonstrates how the disease affects not only patients but also the informal or unpaid individuals who care for patients.An augmented approach to calculating health-related productivity loss suggests that productivity impacts are much larger than previously understood.A more comprehensive understanding of the economic burden of cancer for both patients and their caregivers suggests the need for more support in the workplace for these individuals and a holistic approach to accounting for these impacts in treatment decision making.

Biologic Initiation Rate in Systemic-Naïve Psoriatic Arthritis Patients Starting Treatment with Apremilast vs Methotrexate: 1-Year Retrospective Analysis of a US Claims Database.

Purpose: To compare the rate of biologic initiation after commencing treatment with apremilast (APR) vs methotrexate (MTX), in systemic-naïve patients with psoriatic arthritis (PsA). Patients and Methods: Systemic-naïve patients with PsA who started treatment with either APR or MTX between 01/01/2015 and 12/31/2018 were analyzed using claims data from the IBM® MarketScan® Commercial and Medicare Supplemental databases (2014-2019). PsA patients were identified via diagnosis codes; the first prescription date for APR or MTX was the index date. Patient demographics, clinical characteristics, healthcare utilization during the year pre-index (baseline) and the year post-index (follow-up), and median time to biologic initiation were reported descriptively. The rates and risk of biologic initiation during follow-up were compared between APR and MTX users by logistic and Cox regressions, respectively. Models were adjusted for demographics, clinical and utilization measures during the baseline period. Results: A total of 2116 patients with PsA newly treated with APR (n = 534) or MTX (n = 1582) were identified. Mean age was similar (50.5 vs 50.4; P = 0.938), and proportion of females was higher for APR vs MTX users (59.4% vs 54.0%; P = 0.031). Mean time to biologic initiation among patients who initiated during follow-up was 194.1 vs 138.7 days between APR vs MTX users (P < 0.001). After adjusting for confounders, the likelihood of biologic initiation was 58% lower (OR, 0.42 [95% CI, 0.32-0.54]; P < 0.001) with APR, with a significantly lower predicted rate of biologic initiation among APR users when compared to MTX users during follow-up (20.0% [95% CI, 16.6-23.9%] vs 37.5% [95% CI, 35.0-40.1%]). Additionally, APR users had a lower risk of biologic initiation than MTX users (HR, 0.46 [95% CI, 0.37-0.57]; P < 0.001) during the 1-year follow-up. Conclusion: Systemic-naïve patients with PsA have a lower rate of, and longer time to, biologic initiation over one-year following APR initiation, compared to those initiating MTX.

Measuring the Value Healthy Individuals Place on Generous Insurance Coverage of Severe Diseases: A Stated Preference Survey of Adults Diagnosed With and Without Lung Cancer.

OBJECTIVES: To compare the ex ante willingness to pay (WTP) of healthy individuals for generous insurance coverage of novel lung cancer treatments to the WTP for coverage of such treatment among individuals with lung cancer. METHODS: A survey was administered to 2 cohorts of US adults: (1) healthy individuals without cancer and (2) individuals diagnosed with lung cancer. A multiple random staircase survey design was used to elicit respondent WTP for coverage of novel lung cancer therapy associated with survival gains. RESULTS: Of the 84 937 healthy individuals invited, 300 completed the survey. Of the 36 249 in the lung cancer cohort invited, 250 completed the survey. Mean age by cohort was 50.0 (SD 14.6) and 48.4 (SD 16.8) years, and 55.2% and 47.2% were female, respectively. Respondents in the healthy and lung cancer cohorts were willing to pay $97.52 (95% confidence interval (CI) $89.89-$105.15) and $22 304 (95% CI $20 194-$24 414) per month, respectively, for coverage of a novel therapy providing 5-year survival of 15% versus standard-of-care therapy with a 5-year survival of 4%. After accounting for the likelihood that healthy individuals are diagnosed with lung cancer in the future, we estimated that 89.8% of the total value of new lung cancer treatments comes from the WTP healthy individuals place on generous insurance coverage. CONCLUSIONS: Total societal willingness to pay for lung cancer is much higher than conventionally thought, as most healthy individuals are risk-averse and highly value having lung cancer treatments available to them in the future.

Does knowledge of patient non-compliance change prescribing behavior in the real world? A claims-based analysis of patients with serious mental illness.

BACKGROUND: New digital technologies offer providers the promise of more accurately tracking patients' medication adherence. It is unclear, however, whether access to such information will affect provider treatment decisions in the real world. METHODS: Using prescriber-reported information on patient non-compliance from health insurance claims data between 2008 and 2014, we examined whether prescribers' knowledge of non-compliance was associated with different prescribing patterns for patients with serious mental illness (SMI). We examined patients who initiated an oral atypical antipsychotic, but were later objectively non-adherent to this treatment, defined as proportion of days covered (PDC) <0.8. We examined how a physician's awareness of patient non-compliance (ICD-9 diagnosis code: V15.81) was correlated with the physician's real-world treatment decisions for that patient. Treatment decisions studied included the share of patients who increased antipsychotic dose, augmented treatment, switched their antipsychotic, or used a long-acting injectable (LAI). RESULTS: Among the 286,249 patients with SMI who initiated an antipsychotic and had PDC <0.8, 4,033 (1.4%) had documented non-compliance. When prescribers documented non-compliance, patients were more likely to be switched to another antipsychotic (32.8% vs 24.7%, P<0.001), have their dose increased (24.4% vs 22.1%, P=0.004), or receive an LAI (0.09% vs 0.04%, P=0.008), but were less likely to have augmented therapy with another antipsychotic (1.1% vs 1.3%, P=0.035) than patients without documented non-compliance. CONCLUSION: Among SMI patients with documented non-compliance, the frequency of dose, medication switches, and LAI use were higher and augmentation was lower compared to patients without documented non-compliance. Access to adherence information may help prescribers more rapidly switch ineffective medications as well as avoid unnecessary medication augmentation.

The potential value of rapid, cloud-enabled onsite testing for the diagnosis of rheumatoid arthritis in the United States.

AIMS: Improvements in information technology have granted the recent development of rapid, cloud-enabled, onsite laboratory testing for rheumatoid arthritis (RA). This study aims to quantify the value to payers of such technologies. MATERIALS AND METHODS: To calculate the value of rapid, cloud-enabled, onsite laboratory testing to diagnose RA relative to traditional, centralized laboratory testing, an Excel-based decision tree model was created that simulated potential cost-savings to payers who cover routine evaluations of RA patients in the US. First, a conceptual framework was created to identify the value components of rapid, cloud-enabled onsite testing. Second, value associated with patient time savings, savings on visit fees, change in treatment costs, and QALY improvements was measured, leveraging existing literature and information from an observational study. Lastly, these value components were combined to estimate the total incremental value accruing to payers per patient-year relative to centralized laboratory testing. RESULTS: Rapid, cloud-enabled, onsite testing is estimated to save one office and 1.81 laboratory visits during the evaluation period for the average patient. Results from an observational study found that rapid, cloud-enabled testing increased the likelihood of completing diagnostic orders from 84.5% to 97%, resulting in an increased probability of early treatment (3.5 percentage points) with disease-modifying anti-rheumatic drugs among patients eligible for treatment. The combined total value was $5,648 per evaluated patient-year. This value is primarily attributed to health benefits of early treatment ($5,048), fewer visit payments ($459), and patient time savings due to fewer office ($216) and laboratory visits ($255). LIMITATIONS AND CONCLUSIONS: Data on the impact of rapid, cloud-enabled, onsite testing on patient health, care delivery, and clinical decision-making is scarce. More robust real-world data would confirm the validity of our model. Rapid, cloud-enabled, onsite testing has the potential to generate significant value to payers.

Estimated prevalence of undiagnosed atrial fibrillation in the United States.

INTRODUCTION: As atrial fibrillation (AF) is often asymptomatic, it may remain undiagnosed until or even after development of complications, such as stroke. Consequently the observed prevalence of AF may underestimate total disease burden. METHODS: To estimate the prevalence of undiagnosed AF in the United States, we performed a retrospective cohort modeling study in working age (18-64) and elderly (≥65) people using commercial and Medicare administrative claims databases. We identified patients in years 2004-2010 with incident AF following an ischemic stroke. Using a back-calculation methodology, we estimated the prevalence of undiagnosed AF as the ratio of the number of post-stroke AF patients and the CHADS2-specific stroke probability for each patient, adjusting for age and gender composition based on United States census data. RESULTS: The estimated prevalence of AF (diagnosed and undiagnosed) was 3,873,900 (95%CI: 3,675,200-4,702,600) elderly and 1,457,100 (95%CI: 1,218,500-1,695,800) working age adults, representing 10.0% and 0.92% of the respective populations. Of these, 698,900 were undiagnosed: 535,400 (95%CI: 331,900-804,400) elderly and 163,500 (95%CI: 17,700-400,000) working age adults, representing 1.3% and 0.09% of the respective populations. Among all undiagnosed cases, 77% had a CHADS2 score ≥1, and 56% had CHADS2 score ≥2. CONCLUSIONS: Using a back-calculation approach, we estimate that the total AF prevalence in 2009 was 5.3 million of which 0.7 million (13.1% of AF cases) were undiagnosed. Over half of the modeled population with undiagnosed AF was at moderate to high risk of stroke.

Regional disparities in the quality of stroke care.

BACKGROUND AND PURPOSE: There is widespread geographic variation in healthcare quality, but we often lack clear strategies for improving quality in underserved areas. This study characterized geographic disparities in stroke care quality to assess whether improved access to neurological services has the potential to bridge the care quality gap, particularly in terms of alteplase (rt-PA) administration. METHODS: This was a retrospective study using quality performance data from the 2015 Hospital Compare database linked to information on certification status from the Joint Commission and information on local access to neurological services from the Area Health Resources File. We used these data to compare stroke care quality according to geographic area, certification, and neurologist access. RESULTS: Non-metropolitan hospitals performed worse than metropolitan hospitals on all assessed stroke care quality measures. The most prevalent disparity occurred in the use of rt-PA for eligible patients (52.2% versus 82.7%, respectively). Certified stroke centers in every geographic designation provided higher quality of care, whereas large variation was observed among non-certified hospitals. Regression analyses suggested that improvements in hospital certification or access to neurologists were associated with absolute improvements of 44.9% and 21.3%, respectively, in the percentage of patients receiving rt-PA. CONCLUSIONS: The large quality gap in stroke care between metropolitan and non-metropolitan areas could be at least partly addressed through improved procedural efforts by stroke center certification increasing the supply of neurological services, (i.e. through training and hiring new neurologists) or by adopting decision support systems such as telemedicine.

The role of imperfect surrogate endpoint information in drug approval and reimbursement decisions.

Approval of new drugs is increasingly reliant on "surrogate endpoints," which correlate with but imperfectly predict clinical benefits. Proponents argue surrogate endpoints allow for faster approval, but critics charge they provide inadequate evidence. We develop an economic framework that addresses the value of improvement in the predictive power, or "quality," of surrogate endpoints, and clarifies how quality can influence decisions by regulators, payers, and manufacturers. For example, the framework shows how lower-quality surrogates lead to greater misalignment of incentives between payers and regulators, resulting in more drugs that are approved for use but not covered by payers. Efficient price-negotiation in the marketplace can help align payer incentives for granting access based on surrogates. Higher-quality surrogates increase manufacturer profits and social surplus from early access to new drugs. Since the return on better quality is shared between manufacturers and payers, private incentives to invest in higher-quality surrogates are inefficiently low.

Undertreatment of osteoporosis and the role of gastrointestinal events among elderly osteoporotic women with Medicare Part D drug coverage.

OBJECTIVES: To examine the rate of osteoporosis (OP) undertreatment and the association between gastrointestinal (GI) events and OP treatment initiation among elderly osteoporotic women with Medicare Part D drug coverage. METHODS: This retrospective cohort study utilized a 20% random sample of Medicare beneficiaries. Included were women ≥66 years old with Medicare Part D drug coverage, newly diagnosed with OP in 2007-2008 (first diagnosis date as the index date), and with no prior OP treatment. GI event was defined as a diagnosis or procedure for a GI condition between OP diagnosis and treatment initiation or at the end of a 12-month follow-up, whichever occurred first. OP treatment initiation was defined as the use of any bisphosphonate (BIS) or non-BIS within 1 year postindex. Logistic regression, adjusted for patient characteristics, was used to model the association between 1) GI events and OP treatment initiation (treated versus nontreated); and 2) GI events and type of initial therapy (BIS versus non-BIS) among treated patients only. RESULTS: A total of 126,188 women met the inclusion criteria: 72.1% did not receive OP medication within 1 year of diagnosis and 27.9% had GI events. Patients with a GI event were 75.7% less likely to start OP treatment (odds ratio [OR]=0.243; P<0.001); among treated patients, patients with a GI event had 11.3% lower odds of starting with BIS versus non-BIS (OR=0.887; P<0.001). CONCLUSION: Among elderly women newly diagnosed with OP, only 28% initiated OP treatment. GI events were associated with a higher likelihood of not being treated and, among treated patients, a lower likelihood of being treated with BIS versus non-BIS.

Economic Burden of Undiagnosed Nonvalvular Atrial Fibrillation in the United States.

Atrial fibrillation (AF) may be clinically silent and therefore undiagnosed. To date, no estimates of the direct medical cost of undiagnosed AF exist. We estimated the United States (US) incremental cost burden of undiagnosed nonvalvular AF nationally using administrative claims data. To calculate the incremental costs of undiagnosed AF, we compared annual medical costs (in 2014 US Dollars) for patients with AF compared to propensity-matched controls and multiplied this by estimates of undiagnosed AF prevalence derived from the same data sources. The study population included US residents aged ≥18 years with 24 months of continuous enrollment drawn from 2 large administrative claims databases. Mean per capita medical spending for patients with AF aged from 18 to 64 year was $38,861 (95% confidence interval [CI] $35,781 to $41,950) compared to $28,506 (95% CI $28,409 to $28,603) for similar patients without AF (incremental cost difference $10,355, p <0.001); total spending for patients aged ≥65 years with AF was $25,322 (95% CI $25,049 to $25,595) compared to $21,706 (95% CI $21,563 to $21,849) for similar patients without AF (incremental cost difference $3,616, p <0.001). Using estimates of the US prevalence of undiagnosed AF (596,000) drawn from the same data, we estimated that the US incremental cost burden of undiagnosed nonvalvular AF is $3.1 billion (95% CI $2.7 to $3.7 billion). In conclusion, the direct medical costs for patients with undiagnosed AF are greater than patients with similar observable characteristics without AF and strategies to identify and treat patients with undiagnosed AF could lead to sizable reductions in stroke sequelae and associated costs.

Identifying patients at risk for high medical costs and good candidates for obesity intervention.

PURPOSE: To develop a risk-scoring tool to identify in a base year patients likely to have high medical spending in the subsequent year and to understand the role obesity and obesity reduction may play in mitigating this risk. DESIGN: Cross-sectional analysis, using commercial claims and health risk assessment data. SETTING: United States, 2004-2009. SUBJECTS: Panel of 192,750 person-year observations from 116,868 unique working-age employees of large companies. MEASURES: Probability of high medical expenses (80th percentile or above) in the following year; adjusted body mass index (BMI). ANALYSIS: Generate risk scores by modeling the likelihood of high next-year expenses as a function of base-year age, sex, medical utilization, comorbidities, and BMI. Estimate the effect of simulated bariatric intervention on patient risk scores. RESULTS: Individuals with higher BMI were more likely to be categorized in the very high risk group, in which the average annual medical expense was $8621. A weight-loss intervention transitioning a patient to the next lower obesity class was predicted to reduce this risk by 1.5% to 27.4%-comparable to hypothetically curing a patient of depression or type 2 diabetes. CONCLUSION: A logistic model was used to capture the effect of BMI on the risk of high future medical spending. Weight-loss interventions for obese patients may generate significant savings by reducing this risk.