Hospital Prices for Physician-Administered Drugs for Patients with Private Insurance.

BACKGROUND: Hospitals can leverage their position between the ultimate buyers and sellers of drugs to retain a substantial share of insurer pharmaceutical expenditures. METHODS: 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. RESULTS: 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%. CONCLUSIONS: 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.).

Influence of incomplete death information on cumulative risk estimates in US claims data.

Administrative claims databases often do not capture date or fact of death, so studies using these data may inappropriately treat death as a censoring event-equivalent to other withdrawal reasons-rather than a competing event. We examined 1-, 3-, and 5-year inverse-probability-of-treatment weighted cumulative risks of a composite cardiovascular outcome among 34 527 initiators of telmisartan (exposure) and ramipril (referent), who were aged ≥55 years, in Optum (United States) claims data from 2003 to 2020. Differences in cumulative risks of the cardiovascular endpoint due to censoring of death (cause-specific), as compared with treating death as a competing event (subdistribution), increased with greater follow-up time and older age, where event and mortality risks were higher. Among ramipril users, 5-year cause-specific and subdistribution cumulative risk estimates per 100, respectively, were 16.4 (95% CI, 15.3-17.5) and 16.2 (95% CI, 15.1-17.3) among ages 55-64 (difference = 0.2) and were 43.2 (95% CI, 41.3-45.2) and 39.7 (95% CI, 37.9-41.4) among ages ≥75 (difference = 3.6). Plasmode simulation results demonstrated the differences in cause-specific versus subdistribution cumulative risks to increase with increasing mortality rate. We suggest researchers consider the cohort's baseline mortality risk when deciding whether real-world data with incomplete death information can be used without concern. This article is part of a Special Collection on Pharmacoepidemiology.

The clinical outcomes and healthcare resource utilization in IgG4-related disease: a claims-based analysis of commercially insured adults in the United States.

OBJECTIVES: IgG4-related disease (IgG4-RD) can affect nearly any organ and is often treated with glucocorticoids, which contribute to organ damage and toxicity. Comorbidities and healthcare utilization in IgG4-RD are poorly understood. METHODS: We conducted a cohort study using claims data from a US managed care organization. Incident IgG4-RD cases were identified using a validated algorithm; general population comparators were matched by age, sex, race/ethnicity and index date. The frequency of 21 expert-defined clinical outcomes associated with IgG4-RD or its treatment and healthcare-associated visits and costs were assessed 12 months before and 36 months after the index date (date of earliest IgG4-RD-related claim). RESULTS: There were 524 cases and 5240 comparators. Most cases received glucocorticoids prior to (64.0%) and after (85.1%) the index date. Nearly all outcomes, many being common glucocorticoid toxicities, occurred more frequently in cases vs comparators. During follow-up, the largest differences between cases and comparators were seen for gastroesophageal reflux disease (prevalence difference: +31.2%, P < 0.001), infections (+17.3%, P < 0.001), hypertension (+15.5%, P < 0.01) and diabetes mellitus (+15.0%, P < 0.001). The difference in malignancy increased during follow-up from +8.8% to +12.5% (P < 0.001). Some 17.4% of cases used pancreatic enzyme replacement therapy during follow-up. Over follow-up, cases were more often hospitalized (57.3% vs 17.2%, P < 0.01) and/or had an emergency room visit (72.0% vs 36.7%, P < 0.01); all costs were greater in cases than comparators. CONCLUSIONS: Patients with IgG4-RD are disproportionately affected by adverse outcomes, some of which may be preventable or modifiable with vigilant clinician monitoring. Glucocorticoid-sparing treatments may improve these outcomes.

Outcomes of Warfarin Home INR Monitoring vs Office-Based Monitoring: a Retrospective Claims-Based Analysis.

BACKGROUND: Home INR testing (patient self-testing) is feasible and effective for warfarin patients but little is known about real-world differences in outcomes for patients using PST versus laboratory-based INR monitoring. OBJECTIVE: To compare the safety/efficacy of patient self-testing of real-world warfarin therapy versus office/lab-based monitoring of therapy. DESIGN/SETTING/PARTICIPANTS/EXPOSURE: A retrospective claims-based analysis of warfarin patients enrolled in the MarketScan® Commercial Claims and Encounters and Medicare databases between January 1, 2013, and March 30, 2020. Stratification was based on INR testing method: patient self-testing versus testing at physicians' offices/local laboratory. The probability of adverse events in each cohort was determined after adjusting for demographic and baseline clinical characteristics using a repeated measures analysis. MAIN MEASURES: Rates of all adverse events: deep venous thrombosis, pulmonary embolism, bleeding, and stroke. A secondary outcome of interest was emergency department visits. KEY RESULTS: A total of 37,837 patients were included in the analysis: 1592 patients in the patient self-testing group and 36,245 in the office-based therapy group. After adjusting for demographic and baseline clinical characteristics, patients in the office-based group had statistically significantly higher rates of all adverse events (incidence rate ratio [IRR]=2.07, 95% CI [1.82, 2.36]), and specific adverse events including thromboembolism (IRR=4.38, 95% CI [3.29, 5.84]), major bleed (IRR=1.45, 95% CI [1.28, 1.64]), and stroke (IRR=1.30, 95% CI [1.05, 1.61]) than patients in the patient self-testing group. Office-based patients also had a statistically significant higher rate of emergency department visits than patient self-testing patients (IRR = 1.65, 95% CI [1.47, 1.84]). CONCLUSIONS/RELEVANCE: This analysis of real-world claims data shows lower rates of stroke, thromboembolism, and major bleeding, as well as fewer emergency department visits, with patient self-testing compared to office-based/lab INR monitoring. Our finding that PST is safe and effective among current users suggests that more patients may benefit from its use.

Myelofibrosis and anemia: A German claims data analysis to describe epidemiology and current treatment.

OBJECTIVES: There is limited data on the incidence, prevalence, and treatments for myelofibrosis (MF) in Germany. This retrospective study examined claims data from 3.3 million insured individuals, spanning from 2010 to 2021. METHODS: Four sensitivity scenarios were explored to identify cases of MF. Point prevalence and cumulative incidence of MF were determined as of December 31, 2021, and within 2021, respectively. A cross-sectional analysis used the main scenario definition of MF to identify cases and evaluate the period prevalence of patients receiving treatment for symptoms and/or splenomegaly, including first-line (1L) Janus kinase inhibitor (JAKi), second-line, or further (2L+) MF-related treatment therapies during 2021. The prevalence of anemia treatment was also reported. RESULTS: The estimated standardized point prevalence of MF on December 31, 2021, was 9.9-12.4 cases per 100 000 persons, and cumulative incidence in 2021 was 1.2-1.8 cases per 100 000 persons. Standardized period prevalence in 2021 for MF patients receiving 1L JAKi and/or 2L+ MF-related treatment was 4.0 cases per 100 000. Among these patients, 47.1%-53.7% required treatment for anemia, resulting in a period prevalence of 1.9-2.2 cases per 100 000 individuals. CONCLUSION: The data reveal gaps in MF treatments and the need to improve patient quality of life.

Cumulative incidence of cardiac surgery associated with exposure to benfluorex: A retrospective analysis based on compensation claims data.

Data on retrospective compensation claims for injuries caused by pharmaceutical drugs are prone to selection and reporting biases. Nevertheless, this case study of the antidiabetic drug benfluorex shows that such data can be used to estimate the cumulative incidence of drug-related injury, and to provide insights into its epidemiology. To this end, we develop a modelling framework for under-reporting of retrospective claims for compensation arising from drug damage. The model involves a longitudinal component related to attrition of cases over time, and a cross-sectional component related to incomplete reporting. We apply this model to cardiac valve surgery necessitated by exposure to benfluorex. Benfluorex was marketed in France between 1976 and 2009, when it was withdrawn because it caused valvular heart disease. A scandal erupted in 2010 over the scale of the damage caused by the drug. Since then, no further estimates of cumulative incidence have been published, though thousands of claims for compensation have been processed. The analysis combines compensation claims data and sociological survey data on benfluorex users, together with data on benfluorex sales and duration of treatment. We find a threshold of toxicity at about 6 months' exposure, and that at least 1690 individuals (95% CI 1290 to 2320) needed heart surgery to replace or repair valves damaged by exposure to benfluorex in France: a cumulative incidence of 3.68 per 10,000 (95% CI 2.68 to 5.34) benfluorex users or 3.22 per 10,000 (95% CI 2.48 to 4.39) person-years at risk above the exposure threshold. While these findings are tentative, they are consistent with those obtained previously using very different methods.

A Claims-Based Method for Identification and Characterization of Practicing Interventional Radiologists.

PURPOSE: To propose a research method for identifying "practicing interventional radiologists" using 2 national claims data sets. MATERIALS AND METHODS: The 2015-2019 100% Medicare Part B data and 2015-2019 private insurance claims from Optum's Clinformatics Data Mart (CDM) database were used to rank-order radiologists' interventional radiology (IR)-related work as a percentage of total billed work relative value units (RVUs). Characteristics were analyzed at various threshold percentages. External validation used Medicare self-designated specialty with Society of Interventional Radiology (SIR) membership records; Youden index evaluated sensitivity and specificity. Multivariate logistic regression assessed practicing IR characteristics. RESULTS: In the Medicare data, above a 10% IR-related work threshold, only 23.8% of selected practicing interventional radiologists were designated as interventional radiologists; above 50% and 90% thresholds, this percentage increased to 42.0% and 47.5%, respectively. The mean percentage of IR-related work among practicing interventional radiologists was 45%, 84%, and 96% of total work RVUs for the 10%, 50%, and 90% thresholds, respectively. At these thresholds, the CDM practicing interventional radiologists included 21.2%, 35.2%, and 38.4% designated interventional radiologists, and evaluation and management services comprised relatively more total work RVUs. Practicing interventional radiologists were more likely to be males, metropolitan, and earlier in their careers than other radiologists at all thresholds. CONCLUSIONS: Most radiologists performing IR-related work are designated in claims data as diagnostic radiologists, indicating insufficiency of specialty designation for IR identification. The proposed method to identify practicing interventional radiologists by percent IR-related work effort could improve generalizability and comparability across claims-based IR studies.

Comparison of two propensity score-based methods for balancing covariates: the overlap weighting and fine stratification methods in real-world claims data.

BACKGROUND: Two propensity score (PS) based balancing covariate methods, the overlap weighting method (OW) and the fine stratification method (FS), produce superb covariate balance. OW has been compared with various weighting methods while FS has been compared with the traditional stratification method and various matching methods. However, no study has yet compared OW and FS. In addition, OW has not yet been evaluated in large claims data with low prevalence exposure and with low frequency outcomes, a context in which optimal use of balancing methods is critical. In the study, we aimed to compare OW and FS using real-world data and simulations with low prevalence exposure and with low frequency outcomes. METHODS: We used the Texas State Medicaid claims data on adult beneficiaries with diabetes in 2012 as an empirical example (N = 42,628). Based on its real-world research question, we estimated an average treatment effect of health center vs. non-health center attendance in the total population. We also performed simulations to evaluate their relative performance. To preserve associations between covariates, we used the plasmode approach to simulate outcomes and/or exposures with N = 4,000. We simulated both homogeneous and heterogeneous treatment effects with various outcome risks (1-30% or observed: 27.75%) and/or exposure prevalence (2.5-30% or observed:10.55%). We used a weighted generalized linear model to estimate the exposure effect and the cluster-robust standard error (SE) method to estimate its SE. RESULTS: In the empirical example, we found that OW had smaller standardized mean differences in all covariates (range: OW: 0.0-0.02 vs. FS: 0.22-3.26) and Mahalanobis balance distance (MB) (< 0.001 vs. > 0.049) than FS. In simulations, OW also achieved smaller MB (homogeneity: <0.04 vs. > 0.04; heterogeneity: 0.0-0.11 vs. 0.07-0.29), relative bias (homogeneity: 4.04-56.20 vs. 20-61.63; heterogeneity: 7.85-57.6 vs. 15.0-60.4), square root of mean squared error (homogeneity: 0.332-1.308 vs. 0.385-1.365; heterogeneity: 0.263-0.526 vs 0.313-0.620), and coverage probability (homogeneity: 0.0-80.4% vs. 0.0-69.8%; heterogeneity: 0.0-97.6% vs. 0.0-92.8%), than FS, in most cases. CONCLUSIONS: These findings suggest that OW can yield nearly perfect covariate balance and therefore enhance the accuracy of average treatment effect estimation in the total population.

Greater need for treatment optimization in patients with epilepsy initiating adjunctive therapy: Results of a retrospective claims analysis of antiseizure medication drug load in the United States.

BACKGROUND: This retrospective, observational study used US claims data to assess changes in antiseizure medication (ASM) drug load for a cohort of patients with epilepsy. METHODS: Adults (≥18 years) with a diagnosis of epilepsy (ICD-10 code G40.xxx) who started new adjunctive ASM treatment with one of 4 branded (brivaracetam, eslicarbazepine, lacosamide, perampanel) or 4 unbranded (carbamazepine, lamotrigine, levetiracetam, topiramate) ASMs between January 1, 2016 and December 31, 2020 were identified from IBM MarketScan® research databases (primary study population). Patients must have been continuously enrolled 360 days before the start of the new ASM (eligibility period). Follow-up was from the start of new ASM until Day 540 (∼18 months). The primary endpoint was concomitant ASM drug load, which included all ASMs except the new (comparator) ASM. A sensitivity analysis population included adults with epilepsy who were continuously enrolled for ≥ 180 days during at least one calendar year in the study period (2016-2020), whether or not the comparator ASM was new or existing during that period. Total ASM drug load, which included comparator ASM and concomitant ASMs, was assessed in the sensitivity analysis population. RESULTS: In total, 21,332 patients were included in the primary study population, of which 5767 initiated branded ASMs and 15,565 initiated unbranded ASMs. A total of 392,426 patients were included in the sensitivity analysis population during at least one calendar year 2016-2020. Concomitant ASM drug load increased in the 360 days prior to new ASM start and slightly declined thereafter. Mean concomitant ASM drug load for the primary population was 1.6 (SD 1.8) at new ASM start. Concomitant drug load was higher among those starting branded ASM comparators compared to those starting unbranded comparators. Mean total ASM drug load for patients increased over time and was approximately double for patients exposed to branded ASMs (mean range 2.1 to 2.7) compared to that of patients exposed to any unbranded ASM (mean range 1.0 to 1.3). CONCLUSION: Concomitant ASM drug load increased prior to addition of new ASM, with higher increases observed among patients starting branded vs unbranded ASMs, followed by slight decreases thereafter. Total drug load increased linearly among all patients. These findings underscore the need for ongoing ASM regimen evaluation and treatment optimization in patients with epilepsy.

Seizure clusters, treatment patterns, and healthcare resource utilization in patients with epilepsy: A Wisconsin-based claims analysis.

BACKGROUND: Seizure clusters are underresearched and associated with adverse outcomes in patients with epilepsy. This study was a noninterventional, retrospective claims-based analysis using the Wisconsin Health Information Organization (WHIO) All-Payer Claims Database to characterize the epilepsy population in Wisconsin, with a focus on prevalence, treatment patterns, and healthcare resource utilization (HCRU) in patients with seizure clusters prior to the introduction of nasal spray rescue medications. This timeframe allows characterization of a historical baseline for future comparisons with newer treatments. METHODS: Four cohorts were defined: (1) all-epilepsy (all patients with epilepsy); and subcohorts of: (2) patients receiving a monotherapy antiseizure medication (ASM); (3) patients receiving ASM polytherapy; and (4) patients treated for seizure clusters (ie, those taking rescue medications and ≥ 1 ASM). Primary outcomes were HCRU over a 12-month follow-up period, which were descriptively analyzed. RESULTS: Between 2017 and 2019, 16,384 patients were included in the all-epilepsy cohort; 11,688 (71.3 %) were on monotherapy, 3,849 (23.5 %) were on polytherapy, and 526 (3.2 %) were treated for seizure clusters. Twelve-month retentions to the ASM treatments were 46.7 % (7,895/16,904) in the all-epilepsy cohort, and 40.0 % (4,679/11,688) and 40.1 % (1,544/3,849) in the monotherapy and polytherapy subcohorts, respectively. Rescue medication prescriptions were obtained 1,029 times by the 526 patients in the treated seizure cluster subcohort, with infrequent refill rates (mean 1.6-1.9 times/year). A higher proportion of patients in the treated seizure cluster subcohort had epilepsy-related outpatient visits (89.7 %), other visits (71.3 %), and hospitalizations (25.3 %) than patients in the monotherapy (72.2 %, 50.2 %, 19.3 %, respectively) and polytherapy (83.3 %, 63.3 %, 22.8 %, respectively) subcohorts. Mean (standard deviation) all-cause ($114,717 [$231,667]) and epilepsy-related ($76,134 [$204,930]) costs over 12 months were higher in the treated seizure cluster subcohort than the monotherapy ($89,324 [$220,181] and $30,745 [$145,977], respectively) and polytherapy ($101,506 [$152,931] and $49,383 [$96,285], respectively) subcohorts. CONCLUSIONS: Patients treated for seizure clusters incurred higher all-cause and epilepsy-related costs and epilepsy-related HCRU than other subcohorts and had infrequent rescue medication refills. The findings of this analysis highlight the need for appropriate treatment for those patients with epilepsy experiencing seizure clusters. The effect of newer rescue medications to alter these findings will be explored in a follow-up study. Regardless, specialist providers with expertise in treating refractory epilepsy and seizure cluster patients may help to reduce the burden of seizure clusters.

The FDA Sentinel Real World Evidence Data Enterprise (RWE-DE).

PURPOSE: The US Food and Drug Administration's Sentinel Innovation Center aimed to establish a query-ready, quality-checked distributed data network containing electronic health records (EHRs) linked with insurance claims data for at least 10 million individuals to expand the utility of real-world data for regulatory decision-making. METHODS: In this report, we describe the resulting network, the Real-World Evidence Data Enterprise (RWE-DE), including data from two commercial EHR-claims linked assets collectively termed the Commercial Network covering 21 million lives, and four academic partner institutions collectively termed the Development Network covering 4.5 million lives. RESULTS: We discuss provenance and completeness of the data converted in the Sentinel Common Data Model (SCDM), describe patient populations, and report on EHR-claims linkage characterization for all contributing data sources. Further, we introduce a standardized process to store free-text notes in the Development Network for efficient retrieval as needed. CONCLUSIONS: Finally, we outline typical use cases for the RWE-DE where it can broaden the reach of the types of questions that can be addressed by the Sentinel system.

Agreement of Medication Information Derived From EHR Data Compared to Medicare Insurance Claims: An Analysis of Biologic Disease-Modifying Antirheumatic Drugs.

PURPOSE: Few studies have reported the agreement between medication information derived from ambulatory EHR data compared to administrative claims for high-cost specialty drugs. We used data from a national EHR-enabled registry, the Rheumatology Informatics System for Effectiveness (RISE), with linked Medicare claims in a population of patients with rheumatoid arthritis (RA) to investigate variations in agreement for different biologic disease-modifying agents (bDMARDs) between two data sources (RISE EHR data vs. Medicare claims), categorized by drug, route of administration, and patient insurance factors (dual eligibility). METHODS: Patients ≥ 65 years old, with ≥ 2 visits in RISE with RA ICD codes ≥ 30 days apart, and continuous enrollment in Medicare Parts B and D in 2017-2018 were included. We classified patients as bDMARD users or nonusers in Medicare claims or EHR data in 2018, and we calculated sensitivity, specificity, positive predicted value (PPV), and negative predicted value (NPV) of EHR data for identifying bDMARD users, using Medicare as the reference standard. We also calculated these metrics after stratifying by clinic-administered (Part B) versus. pharmacy-dispensed (Part D) bDMARDs and by patient dual-eligibility. RESULTS: A total of 26 097 patients were included in the study. Using Medicare claims as the reference standard, EHR data had a sensitivity of 75.0%-90.8% for identifying patients with the same medication and route. PPV for Part B bDMARDs was higher compared with Part D bDMARDs (range 94.3%-97.3% vs. 51.0%-69.6%). We observed higher PPVs for Part D bDMARDs among patients who were dual-eligible (range 82.4%-95.1%). CONCLUSION: The risk of misclassification of drug exposure based on EHR data sources alone is small for Medicare Part B bDMARDs but could be as high as 50% for Part D bDMARDs, in particular for patients who are not dually eligible for Medicare and Medicaid.

Evaluation of Medication Adherence Among Prevalent Users in Hypertension, Dyslipidemia, and Diabetes Using Health Insurance Claims: A Population-Based Cohort Study in Japan.

PURPOSE: Hypertension (HT), dyslipidemia (DL), and diabetes mellitus (DM) are major risk factors for cardiovascular diseases. Despite the wide availability of medications to reduce this risk, poor adherence to medications remains an issue. The aim of this study is to evaluate medication adherence of prevalent users in these disease medications (HT, DL, DM) using claims data. Factors associated with non-adherence were also examined. METHODS: Of 7538 participants of the Tsuruoka Metabolomics Cohort Study, 3693 (HT: 2702, DL: 2112, DM: 661) were identified as prevalent users of these disease medications. Information on lifestyle was collected through a questionnaire. Adherence was assessed by a proportion of days covered (PDC) and participants with PDC ≥0.8 were defined as adherent. Predictors of non-adherence were determined by performing multivariable logistic regression. RESULTS: Medication adherence differed by treatment status. Among those without comorbidities, those with HT-only showed the highest adherence (90.2%), followed by those with DM-only (81.2%) and those with DL-only (80.8%). Factors associated with non-adherence in each medication group were skipping breakfast and poor understanding of medications among those with HT medications, females, having comorbidities, having a history of heart disease, and drinking habit among those with DL medications, and good sleep quality and skipping breakfast among those with DM medications. CONCLUSION: While participants showed high medication adherence, differences were observed across medication groups. The identified predictors of non-adherence could help target those in need of adherence support.

Validation Study of the Claims-Based Algorithm Using the International Classification of Diseases Codes to Identify Patients With Coronavirus Disease in Japan From 2020 to 2022: The VENUS Study.

PURPOSE: We validated claims-based algorithms using the International Classification of Diseases, Tenth Revision (ICD-10) to identify patients with the first-ever coronavirus disease (COVID-19) onset between May 2020 and August 2022. METHODS: The study cohort was comprised of residents of one municipality enrolled in a public insurance program. This study used data provided by the municipality, including residents' insurer-based medical claims data linked to the Health Center Real-time Information-Sharing System (HER-SYS). The HER-SYS data included positive results from COVID-19 tests and were used as reference standards. Claims-based algorithms #1 and #2 were U07.1, B34.2, with and without suspicious diagnoses, respectively. Claims-based algorithms #3 and #4 were U07.1 with and without suspicious diagnoses, respectively. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each algorithm. RESULTS: The study cohort included 165 038 residents, including 13 402 residents were the reference standard. For the entire period, the sensitivity, specificity, PPV, and NPV were 55.7% (95% confidence interval: 54.8%-56.5%), 65.4% (65.2%-65.6%), 11.5% (11.3%-11.8%), and 98.9% (98.8%-99.0%) for Algorithm #1, and 67.0% (66.2%-67.8%), 88.1% (87.9%-88.3%), 31.6% (31.1%-32.2%), and 97.8% (97.7%-97.8%) for Algorithm #2, and 52.9% (52.0%-53.7%), 67.1% (66.9%-67.3%), 11.5% (11.2%-11.8%), and 98.3% (98.3%-98.4%) for Algorithm #3, 62.6% (61.8%-63.4%), 88.5% (88.3%-88.7%), 30.9% (30.3%-31.4%), and 97.3% (97.2%-97.4%) for Algorithm #4, respectively. CONCLUSIONS: Our study showed that the validity of claims-based algorithms consisting of COVID-19-related ICD-10 codes to identify patients with first-onset COVID-19 is limited.

Validity of Self-reported Helicobacter pylori Eradication Treatment From Questionnaire and Interview Surveys of the JPHC-NEXT Study: Comparison With Prescription History From Insurance Claims Data.

BACKGROUND: We aimed to evaluate the validity of self-administered questionnaire surveys and face-to-face interview surveys for the detection of Helicobacter pylori eradication therapy. METHODS: Participants were a cohort, aged 40-74 years, living in three different locations of Japan, who took part in the baseline survey (2011-2012) of the Japan Public Health Center-based Prospective Study for the Next Generation (JPHC-NEXT). Five years after the baseline survey, a questionnaire and interview survey were independently conducted to determine the history of Helicobacter pylori eradication treatment over the 5-year period. Prescription of Helicobacter pylori eradication medications in national insurance claims data from the baseline survey to the 5-year survey was used as a reference standard. RESULTS: In total, 15,760 questionnaire surveys and 8,006 interview surveys were included in the analysis. There were 3,471 respondents to the questionnaire and 2,398 respondents to the interview who reported having received Helicobacter pylori eradication treatment within the past 5 years. Comparison of the questionnaire survey to national insurance claims data showed a sensitivity of 95.1% (2,213/2,328), specificity of 90.6% (12,174/13,432), positive predictive value of 63.8% (2,213/3,471), negative predictive value of 99.1% (12,174/12,289), and Cohen's Kappa value of 0.71. Respective values of the interview survey were 94.4% (1,694/1,795), 88.7% (5,507/6,211), 70.6% (1,694/2,398), 98.2% (5,507/5,608), and 0.74. CONCLUSION: Both the questionnaire and the interview showed high sensitivity, high specificity, and good agreement with the insurance claim prescriptions data. Some participants may have received eradication treatment without going through the public insurance claim database, resulting in a low positive predictive value.

Development and Validation of Claims-based Algorithms for Identifying Hospitalized Patients With COVID-19 and Their Severity in 2020 and 2021.

BACKGROUND: This study aimed to develop and validate claims-based algorithms for identifying hospitalized patients with coronavirus disease 2019 (COVID-19) and disease severity. METHODS: We used claims data including all patients at the National Center for Global and Medicine Hospital between January 1, 2020, and December 31, 2021. The claims-based algorithms for three statuses with COVID-19 (hospitalizations, moderate or higher status, and severe status) were developed using diagnosis codes (International Classification of Diseases, 10th revision code: U07.1, B34.2) and relevant medical procedure code. True cases were determined using the COVID-19 inpatient registry and electronic health records. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each algorithm at 6-month intervals. RESULTS: Of the 75,711 total patients, the number of true cases was 1,192 for hospitalizations, 622 for moderate or higher status, and 55 for severe status. The diagnosis code-only algorithm for hospitalization had sensitivities 90.4% to 94.9% and PPVs 9.3% to 19.4%. Among the algorithms consisting of both diagnosis codes and procedure codes, high sensitivity and PPV were observed during the following periods: 93.9% and 97.1% for hospitalization (January-June 2021), 90.4% and 87.5% for moderate or higher status (July-December 2021), and 92.3% and 85.7% for severe status (July-December 2020), respectively. Almost all algorithms had specificities and NPVs of approximately 99%. CONCLUSION: The diagnosis code-only algorithm for COVID-19 hospitalization showed low validity throughout the study period. The algorithms for hospitalizations, moderate or higher status, and severe status with COVID-19, consisting of both diagnosis codes and procedure codes, showed high validity in some periods.

Trends in Telerehabilitation Utilization in the United States 2020-2021.

OBJECTIVE: To examine telerehabilitation utilization in the United States (US) during the first 2 years of the pandemic. DESIGN: We performed a retrospective analysis of outpatient insurance claims from the IBM MarketScan Commercial Claims and Encounters Database to identify the number and proportion of patients using telerehabilitation from 2020 to 2021. Telerehabilitation was identified based on the presence of specific code modifiers and place of service. SETTING: Retrospective claims analysis. PARTICIPANTS: Individuals living in the United States with employer-sponsored insurance plans using outpatient physical or occupational therapy (PT/OT) (N=2,007,524). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE: Number and proportion of outpatient PT/OT visits completed via telerehabilitation. RESULTS: We identified 21,026,608 PT/OT visits among 2,007,524 patients. Overall, 49,974 (2.5%) patients received ≥1 telerehabilitation visit during the specified timeframe. We observed trends in utilization over time, with utilization peaking in April 2020 when 10.9% of all PT/OT visits were conducted by telerehabilitation. We also observed geographic trends with lower rates of utilization identified in rural areas. State-by-state utilization rates ranged from 10.4% (California) to 0.3% (Wyoming). CONCLUSION: Telerehabilitation may be underutilized as a means of improving access to PT/OT, especially in rural areas of the country. Further research is needed to examine contributing factors to low observed utilization rates, such as provider and patient perceptions of telerehabilitation.

Characteristics of pediatric patients claimed with acute upper respiratory infection during otorhinolaryngology consultations: A descriptive study of a large Japanese medical claims database.

This study aimed to clarify other diseases claimed simultaneously with acute upper respiratory infection (URI), antibiotic prescriptions, and examinations associated with infectious diseases in pediatric patients with acute URI insurance claims at otorhinolaryngology outpatient visits. Pediatric patients who visited an otolaryngology department between 2019 and 2021 and were definitively diagnosed with URI were selected using a large Japanese medical claims database. Patient backgrounds, antibiotic use, and examinations were descriptively evaluated. In total, 8010 patients were included in the analysis. The median number (interquartile range) of diseases claimed in the same month as acute URI was 4 (3-6). Only 519 (6.5 %) patients were claimed as acute URI alone. Regardless of the prescription of antibiotics, the most commonly redundantly claimed disease in these patients was allergic rhinitis, followed by acute bronchitis, acute sinusitis, and earwax impaction. The frequently prescribed antibiotics were third-generation cephalosporins, macrolides, and penicillins with extended-spectrum, including amoxicillin which was recommended by the Japanese manual; the proportion of patients with examinations was low (2.9-21.7 %). Among patients with acute URI, diagnoses requiring antibiotics were also claimed; therefore, when evaluating acute URI using the Japanese medical claims database, care must be taken in patient selection. Moreover, the implementation rate of examinations necessary for diagnosis was low, so there is an urgent need to develop an environment where examinations can be conducted in outpatient settings.

Type 2 diabetes in the employed population: do rates and trends differ among nine occupational sectors? An analysis using German health insurance claims data.

BACKGROUND: Socioeconomic inequalities in type 2 diabetes (T2D) are well established in the literature. However, within the background of changing work contexts associated with digitalization and its effect on lifestyle and sedentary behavior, little is known on T2D prevalence and trends among different occupational groups. This study aims to examine occupational sector differences in T2D prevalence and trends thereof between 2012 and 2019. METHODS: The study was done on 1.683.644 employed individuals using data from the German statutory health insurance provider in Lower Saxony, the "Allgemeine Ortskrankenkasse Niedersachsen" (AOKN). Predicted probabilities for T2D prevalence in four two-year periods between 2012 and 2019 were estimated based on logistic regression analyses for nine occupational sectors. Prevalence ratios were calculated to illustrate the effect of time period on the prevalence of T2D among the nine occupational sectors. Analyses were stratified by gender and two age groups. RESULTS: Results showed differences among occupational sectors in the predicted probabilities for T2D. The occupational sectors "Transport, logistics, protection and security" and "Health sector, social work, teaching & education" had the highest predicted probabilities, while those working in the sector "Agriculture" had by far the lowest predicted probabilities for T2D. Over all, there appeared to be a rising trend in T2D prevalence among younger employed individuals, with gender differences among occupational sectors. CONCLUSION: The study displayed different vulnerability levels among occupational sectors with respect to T2D prevalence overall and for its rising trend among the younger age group. Specific occupations within the vulnerable sectors need to be focused upon in further research to define specific target groups to which T2D prevention interventions should be tailored.

Burden of vaccine-preventable diseases in adults (50+) in the United States: a retrospective claims analysis.

BACKGROUND: In adults aged 50 + years, vaccine-preventable diseases (VPDs) pose a significant health burden and can lead to additional 'downstream effects' of infection beyond the acute phase e.g., increasing the risk for non-communicable disease and exacerbating chronic conditions. The aim was to understand and quantify the burden of VPD downstream effects in hospitalised adults in the United States. METHODS: This retrospective observational study analysed hospitalisation claims data (2016-2019) with 1-year follow-up, in adults with a VPD diagnosis versus matched controls (using Optum's de-identified Clinformatics Data Mart Database). Outcomes included mortality; increase in Charlson Comorbidity Index (CCI) score; new diagnosis of comorbidities; and loss of independence (defined by need for home health/home care and/or move to long-term facility). RESULTS: Mortality was significantly increased in VPD cases versus controls at 30-day (risk ratio [RR] of 4.08 [95% CI 3.98-4.18]) and 1-year follow-up (RR 2.76 [2.73-2.80]). Over a 1-year follow-up period, morbidity increased following VPD hospitalisation: 65-86% of VPD cases had new comorbidities diagnosed (versus 13-41% of controls); with a significantly higher mean increase in CCI score versus baseline (3.23 in VPD cases versus 0.89 in controls, p < 0.001). Adults were observed to experience a worsening of their health status and were less likely to return to their original health state. In addition, 41% of VPD cases had a loss of independence following hospitalisation versus 12% of controls; as seen by an increased need for home assistance (in 25% versus 9% of controls) and/or a move to a long-term care facility (in 29% versus 6% of controls). CONCLUSIONS: This analysis suggests that VPD hospitalised cases suffer significantly worse clinical outcomes than controls, with downstream effects that include increased mortality and morbidity, and greater loss of independence. Evidence on potential downstream effects of infection is relatively new, and this additional burden is generally not considered in vaccine decision-making. More research is needed to disentangle the effect of VPDs on new comorbidities versus the natural course of the condition. Increasing awareness among adults, healthcare providers and decision makers could help to increase adult vaccination coverage, and reduce the clinical burden of VPDs.