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With increasing rates of opioid overdoses in the US, a surveillance tool to identify high-risk patients may help facilitate early intervention. To develop an algorithm to predict overdose using routinely-collected healthcare databases. Within a US commercial claims database (2011-2015), patients with ≥1 opioid prescription were identified. Patients were randomly allocated into the training (50%), validation (25%), or test set (25%). For each month of follow-up, pooled logistic regression was used to predict the odds of incident overdose in the next month based on patient history from the preceding 3-6 months (time-updated), using elastic net for variable selection. As secondary analyses, we explored whether using simpler models (few predictors, baseline only) or different analytic methods (random forest, traditional regression) influenced performance. We identified 5,293,880 individuals prescribed opioids; 2,682 patients (0.05%) had an overdose during follow-up (mean: 17.1 months). On average, patients who overdosed were younger and had more diagnoses and prescriptions. The elastic net model achieved good performance (c-statistic 0.887, 95% CI 0.872-0.902; sensitivity 80.2, specificity 80.1, PPV 0.21, NPV 99.9 at optimal cutpoint). It outperformed simpler models based on few predictors (c-statistic 0.825, 95% CI 0.808-0.843) and baseline predictors only (c-statistic 0.806, 95% CI 0.787-0.26). Different analytic techniques did not substantially influence performance. In the final algorithm based on elastic net, the strongest predictors were age 18-25 years (OR: 2.21), prior suicide attempt (OR: 3.68), opioid dependence (OR: 3.14). We demonstrate that sophisticated algorithms using healthcare databases can be predictive of overdose, creating opportunities for active monitoring and early intervention.

Medicare insurance claims may provide an efficient means to ascertain follow-up of older participants in clinical research. We sought to determine the accuracy and completeness of claims- versus site-based follow-up with clinical event committee (+CEC) adjudication of cardiovascular outcomes. We performed a retrospective study using linked Medicare and Duke Database of Clinical Trials data. Medicare claims were linked to clinical data from 7 randomized cardiovascular clinical trials. Of 52,476 trial participants, linking resulted in 5,839 (of 10,497 linkage-eligible) Medicare-linked trial participants with fee-for-service A and B coverage. Death, myocardial infarction (MI), stroke, and revascularization incidences were compared using Medicare inpatient claims only, site-reported events (+CEC) only, or a combination of the 2. Randomized treatment effects were compared as a function of whether claims-based, site-based (+CEC), or a combined system was used for event detection. Among the 5,839 study participants, the annual event rates were similar between claims- and site-based (+CEC) follow-up: death (overall rate 5.2% vs 5.2%; adjusted κ 0.99), MI (2.2% vs 2.3%; adjusted κ 0.96), stroke (0.7% vs 0.7%; adjusted κ 0.99), and any revascularization (7.4% vs 7.9%; adjusted κ 0.95). Of events detected by claims yet not reported by CEC, a minority were reported by sites but negatively adjudicated by CEC (39% of MIs and 18% of strokes). Differences in individual case concordance led to higher event rates when claims- and site-based (+CEC) systems were combined. Randomized treatment effects were similar among the 3 approaches for each outcome of interest. Claims- versus site-based (+CEC) follow-up identified similar overall cardiovascular event rates despite meaningful differences in the events detected. Randomized treatment effects were similar using the 2 methods, suggesting claims data could be used to support clinical research leveraging routinely collected data. This approach may lead to more effective evidence generation, synthesis, and appraisal of medical products and inform the strategic approaches toward the National Evaluation System for Health Technology.

BACKGROUND:The most used score to measure comorbidity is the Charlson index. Its application to a health care administrative database including International Classification of Diseases, 10th edition (ICD-10) codes, medical procedures, and medication required studying its properties on survival. Our objectives were to adapt the Charlson comorbidity index to the French National Health Insurance database to predict 1-year mortality of discharged patients and to compare discrimination and calibration of different versions of the Charlson index. METHODS:Our cohort included all adults discharged from a hospital stay in France in 2010 registered in the French National Health Insurance general scheme. The pathologies of the Charlson index were identified through ICD-10 codes of discharge diagnoses and long-term disease, specific medical procedures, and reimbursement of specific medications in the past 12 months before inclusion. RESULTS:We included 6,602,641 subjects at the date of their first discharge from medical, surgical, or obstetrical department in 2010. One-year survival was 94.88%, decreasing from 98.41% for Charlson index of 0–71.64% for Charlson index of ≥5. With a discrimination of 0.91 and an appropriate calibration curve, we retained the crude Cox model including the age-adjusted Charlson index as a 4-level score. CONCLUSIONS:Our study is the first to adapt the Charlson index to a large health care database including >6 million of inpatients. When mortality is the outcome, we recommended using the age-adjusted Charlson index as 4-level score to take into account comorbidities.

Background Use of administrative claims from multiple sources for research purposes is challenged by the lack of consistency in the structure of the underlying data and definition of data across claims data providers. This paper evaluates the impact of applying a standardized revenue code-based logic for defining inpatient encounters across two different claims databases. Methods We selected members who had complete enrollment in 2012 from the Truven MarketScan Commercial Claims and Encounters (CCAE) and the Optum Clinformatics (Optum) databases. The overall prevalence of inpatient conditions in the raw data was compared to that in the common data model (CDM) with the standardized visit definition applied. Results In CCAE, 87.18% of claims from 2012 that were classified as part of inpatient visits in the raw data were also classified as part of inpatient visits after the data were standardized to CDM, and this overlap was consistent from 2006 to 2011. In contrast, Optum had 83.18% concordance in classification of 2012 claims from inpatient encounters before and after standardization, but the consistency varied over time. The re-classification of inpatient encounters substantially impacted the observed prevalence of medical conditions occurring in the inpatient setting and the consistency in prevalence estimates between the databases. On average, before standardization, each condition in Optum was 12% more prevalent than that same condition in CCAE; after standardization, the prevalence of conditions had a mean difference of only 1% between databases. Amongst 7,039 conditions reviewed, the difference in the prevalence of 67% of conditions in these two databases was reduced after standardization. Conclusions In an effort to improve consistency in research results across database one should review sources of database heterogeneity, such as the way data holders process raw claims data. Our study showed that applying the Observational Medical Outcomes Partnership (OMOP) CDM with a standardized approach for defining inpatient visits during the extract, transfer, and load process can decrease the heterogeneity observed in disease prevalence estimates across two different claims data sources.

Purpose The objective of this study was to evaluate the overall incidence and total burden of successful litigation relating to the management of spinal disease across the National Health Service (NHS) in England. Methods The study design comprised a retrospective review of the NHS Litigation Authority (NHSLA) database, retrieving all successful claims relating to spinal disease between 2002 and 2010—a total of 235 (144 acute, 91 elective). Results The general trend for successful claims with relation to spinal surgery has actually been decreasing steadily over the last few years. The total value of these claims during the period was £60.5 million, comprising £42.8 million (£28.6 million relating to acute diagnoses, £16.1 million for elective) in damages and £17.7 million in legal costs (31% relating to NHS legal costs, the remainder claimants costs). Conclusions Spinal litigation remains a source of significant cost to the NHS. The complexity of resolving these cases is reflected in the associated legal costs.

Hospitals can leverage their position between the ultimate buyers and sellers of drugs to retain a substantial share of insurer pharmaceutical expenditures. In this study, we used 2020-2021 national Blue Cross Blue Shield claims data regarding patients in the United States who had drug-infusion visits for oncologic conditions, inflammatory conditions, or blood-cell deficiency disorders. Markups of the reimbursement prices were measured in terms of amounts paid by Blue Cross Blue Shield plans to hospitals and physician practices relative to the amounts paid by these providers to drug manufacturers. Acquisition-price reductions in hospital payments to drug manufacturers were measured in terms of discounts under the federal 340B Drug Pricing Program. We estimated the percentage of Blue Cross Blue Shield drug spending that was received by drug manufacturers and the percentage retained by provider organizations. The study included 404,443 patients in the United States who had 4,727,189 drug-infusion visits. The median price markup (defined as the ratio of the reimbursement price to the acquisition price) for hospitals eligible for 340B discounts was 3.08 (interquartile range, 1.87 to 6.38). After adjustment for drug, patient, and geographic factors, price markups at hospitals eligible for 340B discounts were 6.59 times (95% confidence interval [CI], 6.02 to 7.16) as high as those in independent physician practices, and price markups at noneligible hospitals were 4.34 times (95% CI, 3.77 to 4.90) as high as those in physician practices. Hospitals eligible for 340B discounts retained 64.3% of insurer drug expenditures, whereas hospitals not eligible for 340B discounts retained 44.8% and independent physician practices retained 19.1%. This study showed that hospitals imposed large price markups and retained a substantial share of total insurer spending on physician-administered drugs for patients with private insurance. The effects were especially large for hospitals eligible for discounts under the federal 340B Drug Pricing Program on acquisition costs paid to manufacturers. (Funded by Arnold Ventures and the National Institute for Health Care Management.).

International norms and ethical standards have suggested that compensation for research-related injury should be provided to injured research volunteers. However, statistical data of incidence of compensation claims and the rate of awarding them have been rarely reported. Questionnaire surveys were sent to pharmaceutical companies and medical institutions, focusing on industry-initiated clinical trials aiming at new drug applications (NDAs) on patient volunteers in Japan. With the answers from pharmaceutical companies, the incidence of compensation was 0.8%, including 0.06% of monetary compensation. Of the cases of compensation claims, 99% were awarded. In turn, with the answers from medical institutions, the incidence of compensation was 0.6%, including 0.4% of serious but not death cases, and 0.04% of death cases. Furthermore, most claims for compensation were initiated by medical institutions, rather than by the patients. On the other hand, with the answers from clinical trial volunteers, 3% of respondents received compensations. These compensated cases were 25% of the injuries which cannot be ruled out from the scope of compensation. Our study results demonstrated that Japanese pharmaceutical companies have provided a high rate of compensation for clinical trial-related injuries despite the possibility of overestimation. In the era of global clinical development, our study indicates the importance of further surveys to find each country's compensation policy by determining how it is being implemented based on a survey of the actual status of compensation coming from statistical data.

Only a small proportion of people with a substance use disorder (SUD) receive treatment. The shortage of SUD treatment providers, particularly in rural areas, is an important driver of this treatment gap. Telemedicine could be a means of expanding access to treatment. However, several key regulatory and reimbursement barriers to greater use of telemedicine for SUD (tele-SUD) exist, and both Congress and the states are considering or have recently passed legislation to address them. To inform these efforts, we describe how tele-SUD is being used. Using claims data for 2010-17 from a large commercial insurer, we identified characteristics of tele-SUD users and examined how tele-SUD is being used in conjunction with in-person SUD care. Despite a rapid increase in tele-SUD over the study period, we found low use rates overall, particularly relative to the growth in telemental health. Tele-SUD is primarily used to complement in-person care and is disproportionately used by those with relatively severe SUD. Given the severity of the opioid epidemic, low rates of tele-SUD use represent a missed opportunity. As tele-SUD becomes more available, it will be important to monitor closely which tele-SUD delivery models are being used and their impact on access and outcomes.

This article quantifies the prevalence of claim denials in Medicare Advantage (MA), along with their direct impact on provider revenue. Employing medical claims data from multiple MA plans, covering 30 percent of the entire MA market in 2019, our study found claim denial rates of 17 percent as a share of initial claim submissions. We also found that 57 percent of all claim denials were ultimately overturned. We calculated that denials resulted in a 7 percent net reduction in provider MA revenue, based on the dollar-weighted share of claim denials that were not overturned. However, the indirect impact of denials could be even greater than this direct effect that we measured. This article points to the important role that claim denials play in reducing MA spending and in driving outcome differences between MA and traditional Medicare. However, our analysis did not weigh the cost-saving benefits of claim denials against potential downsides.

Insurance claim denials are a common source of administrative burden, especially for patients with private health insurance. Contesting denied claims requires considerable investment from physicians and patients or caregivers, including both institutional knowledge of health policies and billing practices and the means to engage in reconciliation. We used a novel national data set comprising remittance data and patient demographics to describe disparities in the rates of seeking and receiving claim denial corrections across demographic and socioeconomic dimensions. We found that patients from historically disadvantaged racial and ethnic groups or with low household incomes experienced the largest burdens from claim denials. Patients with household incomes less than $50,000 annually were least likely to have denied claims contested and, conditionally, have cost-sharing obligations reduced. Racial minority patients were more likely than non-Hispanic White patients to have cost-sharing obligations reduced but achieved lower mean savings per successfully contested denial. Policy makers working to promote equitable health care access should make available more resources for contesting and rectifying administrative errors and enact policies to prevent billing errors and consequent claim denials.