Large-scale real-world data analyses of cancer risks among patients with rheumatoid arthritis.

Rheumatoid arthritis (RA) affects 24.5 million people worldwide and has been associated with increased cancer risks. However, the extent to which the observed risks are related to the pathophysiology of rheumatoid arthritis or its treatments is unknown. Leveraging nationwide health insurance claims data with 85.97 million enrollees across 8 years, we identified 92 864 patients without cancers at the time of rheumatoid arthritis diagnoses. We matched 68 415 of these patients with participants without rheumatoid arthritis by sex, race, age and inferred health and economic status and compared their risks of developing all cancer types. By 12 months after the diagnosis of rheumatoid arthritis, rheumatoid arthritis patients were 1.21 (95% confidence interval [CI] [1.14, 1.29]) times more likely to develop any cancer compared with matched enrollees without rheumatoid arthritis. In particular, the risk of developing lymphoma is 2.08 (95% CI [1.67, 2.58]) times higher in the rheumatoid arthritis group, and the risk of developing lung cancer is 1.69 (95% CI [1.32, 2.13]) times higher. We further identified the five most commonly used drugs in treating rheumatoid arthritis, and the log-rank test showed none of them is implicated with a significantly increased cancer risk compared with rheumatoid arthritis patients without that specific drug. Our study suggested that the pathophysiology of rheumatoid arthritis, rather than its treatments, is implicated in the development of subsequent cancers. Our method is extensible to investigating the connections among drugs, diseases and comorbidities at scale.

Confederated learning in healthcare: Training machine learning models using disconnected data separated by individual, data type and identity for Large-Scale health system Intelligence.

BACKGROUND: A patient's health information is generally fragmented across silos because it follows how care is delivered: multiple providers in multiple settings. Though it is technically feasible to reunite data for analysis in a manner that underpins a rapid learning healthcare system, privacy concerns and regulatory barriers limit data centralization for this purpose. OBJECTIVES: Machine learning can be conducted in a federated manner on patient datasets with the same set of variables but separated across storage. But federated learning cannot handle the situation where different data types for a given patient are separated vertically across different organizations and when patient ID matching across different institutions is difficult. We call methods that enable machine learning model training on data separated by two or more dimensions "confederated machine learning", which we aim to develop in this study. METHODS: We propose and evaluate confederated learning for training machine learning models to stratify the risk of several diseases among silos when data are horizontally separated by individual, vertically separated by data type, and separated by identity without patient ID matching. The confederated learning method can be intuitively understood as a distributed learning method with representation learning, generative model, imputation method and data augmentation elements. RESULTS: Our confederated learning method achieves AUCROC (Area Under The Curve Receiver Operating Characteristics) of 0.787 for diabetes prediction, 0.718 for psychological disorders prediction, and 0.698 for Ischemic heart disease prediction using nationwide health insurance claims. CONCLUSION: Our proposed confederated learning method successfully trained machine learning models on health insurance data separated by two or more dimensions.

Cognitive impairment and edentulism among older adults: an observational study using claims data.

BACKGROUND: The scientific link between mastication strength and cognitive function has not yet been strongly corroborated in population studies. Utilizing large-scale claims, we aim to investigate the association between edentulism and cognitive impairment in older American adults. METHODS: Using de-identified claims from a commercial insurer from 2015-2019, we conducted a retrospective cohort study using multilevel regression models to evaluate the association between denture status and clinically diagnosed cognitive impairment. Secondary analysis included symptomatic cognitive impairment in the outcome. RESULTS: Adjusting for individual-level risk factors, denture status was significantly associated with clinical cognitive impairment with odds ratios of 1.13 (95%CI: 1.02-1.25) and 1.26, (95%CI: 1.09-1.45) for complete dentures on one or both jaws, respectively. Including symptomatic cognitive impairment in the analysis did not substantially change our fundamental findings. CONCLUSION: Prevention and treatment of oral diseases should be considered a key component in preserving the overall wellness of older adults.

Cost Savings Without Increased Risk of Respiratory Hospitalization for Preterm Children after the 2014 Palivizumab Policy Update.

OBJECTIVE: Our objective was to compare rates of hospitalizations for respiratory illnesses in preterm and full-term (FT) children for 4 years before and after the 2014 update to the American Academy of Pediatrics (AAP) respiratory syncytial virus (RSV) immunoprophylaxis guidance, which restricted eligibility among infants born at 29 to 34 weeks in the first winter and all preterm infants in the second winter after neonatal discharge. STUDY DESIGN: We conducted pre-post and interrupted time series analyses on claims data from a commercial national managed care plan. We compared the number of RSV and all respiratory hospital admissions in the first and second RSV seasons after neonatal discharge among a cohort of preterm children, regardless of palivizumab status, in the 4 years before and after the implementation of the 2014 palivizumab eligibility change. A FT group was included for reference. RESULTS: The cohort included 821 early preterm (EP, <29 weeks), 4,790 moderate preterm (MP, 29-34 weeks), and 130,782 FT children. Palivizumab use after the policy update decreased among MP children in the first and second RSV seasons after neonatal discharge, without any change in the odds of hospitalization with RSV or respiratory illness. For the EP group, there was no change in the rate of palivizumab or the odds of hospitalization with RSV or respiratory illness after the policy update. For the FT group, there was a slight decrease in odds of hospitalization post-2014 after the policy update. The interrupted time series did not reveal any secular trends over time in hospitalization rates among preterm children. Following the policy change, there were cost savings for MP children in the first and second RSV seasons, when accounting for the cost of hospitalizations and the cost of palivizumab. CONCLUSION: Hospitalizations for RSV or respiratory illness did not increase, and cost savings were obtained after the implementation of the 2014 AAP palivizumab prophylaxis policy. KEY POINTS: · Palivizumab use decreased among children born moderate preterm (29 to34 weeks) after the 2014 palivizuamb policy update.. · There was no change in odds of hospitalization with respiratory syncitial virus or respiratory illness among preterm infants after the policy update when compared to before.. · There were cost savings, when accounting for the cost of hospitalizations and the cost of palivizumab, after the policy update among children born moderate preterm..

Association of a Clinician's Antibiotic-Prescribing Rate With Patients' Future Likelihood of Seeking Care and Receipt of Antibiotics.

BACKGROUND: One underexplored driver of inappropriate antibiotic prescribing for acute respiratory illnesses (ARI) is patients' prior care experiences. When patients receive antibiotics for an ARI, patients may attribute their clinical improvement to the antibiotics, regardless of their true benefit. These experiences, and experiences of family members, may drive whether patients seek care or request antibiotics for subsequent ARIs. METHODS: Using encounter data from a national United States insurer, we identified patients <65 years old with an index ARI urgent care center (UCC) visit. We categorized clinicians within each UCC into quartiles based on their ARI antibiotic prescribing rate. Exploiting the quasi-random assignment of patients to a clinician within an UCC, we examined the association between the clinician's antibiotic prescribing rate to the patients' and their spouses' rates of ARI antibiotic receipt in the subsequent year. RESULTS: Across 232,256 visits at 736 UCCs, ARI antibiotic prescribing rates were 42.1% and 80.2% in the lowest and highest quartile of clinicians, respectively. Patient characteristics were similar across the four quartiles. In the year after the index ARI visit, patients seen by the highest-prescribing clinicians received more ARI antibiotics (+3.0 fills/100 patients (a 14.6% difference), 95% CI 2.2-3.8, P < 0.001,) versus those seen by the lowest-prescribing clinicians. The increase in antibiotics was also observed among the patients' spouses. The increase in patient ARI antibiotic prescriptions was largely driven by an increased number of ARI visits (+5.6 ARI visits/100 patients, 95% CI 3.6-7.7, P < 0.001), rather than a higher antibiotic prescribing rate during those subsequent ARI visits. CONCLUSIONS: Receipt of antibiotics for an ARI increases the likelihood that patients and their spouses will receive antibiotics for future ARIs.

Impact of Direct to Consumer Store-and-Forward Teledermatology on Access to Care, Satisfaction, Utilization, and Costs in a Commercial Health Plan Population.

PURPOSE: Store-and-forward teledermatology can improve access to dermatology by enabling asynchronous consults. This study assesses it on access, satisfaction, utilization, and costs in a commercial health plan setting. METHODOLOGY: In this prospective observational study with matched control, 47,411 individuals were provided access to teledermatology services staffed by board-certified, licensed dermatologists for 6 months. Two hundred forty-three individuals used the service. One hundred fifty-two participants successfully matched to similar users of in-person services for comparison. Average number of dermatology-related visits and dermatology-related costs in 30, 60, and 90 days postvisit, most frequent diagnoses, time to consult, patient satisfaction, and number of procedures were measured. RESULTS: Average time to consult for the teledermatology group was 16.31 h. Patient satisfaction was 4.38/5. Total dermatology utilization in the postvisit period for the teledermatology and the control groups respectively was 9 and 21 visits at 30 days (p = 0.074), 15 and 46 visits at 60 days (p = 0.005), and 26 and 74 at 90 days (p = 0.001). The dermatology-related spend for the teledermatology and control groups, respectively, was $59 and $113 on the day of the initial consult (p < 0.01), $70 and $202 for 30 days (p = 0.03), $78 and $ 221 for 60 days (p = 0.02), and $86 and $307 for 90 days (p = 0.08) following initial visit. Total number of procedures conducted in the control group at the index visit was 26. In the postvisit period, the total number of procedures in the study and control groups, respectively, were 5 and 15 at 30 days (p = 0.053), 10 and 26 at 60 days (p = 0.088), and 14 and 32 at 90 days (p = 0.082). CONCLUSIONS: Teledermatology services are accessible within hours and associated with high patient satisfaction. There is no evident increased utilization or costs postvisit.

Fecal microbiota transplantation and Clostridioides difficile infection among privately insured patients in the United States.

BACKGROUND: Clostridioides difficile infection (CDI) may be rising in severity in the US over the past decade and its treatment landscape is changing given the recent adoption of fecal microbiota transplantation (FMT) METHODS: We built a retrospective observational cohort using a database of a national care-plan containing medical claims of over 50 million individuals between 2008 and 2019. We used International Classification of Disease (ICD) and prescription data to identify patients with CDI. We estimated trends in disease burden and FMT use, and evaluated complications post FMT using a phenome-wide association approach. RESULTS: We identified 38,396 patients with CDI; the median age was 60 years (IQR 45-74) and 60% were female (n = 23,374). The rate of CDI increased from 33.4 to 69.46 cases per 100,000 person-years between 2008 and 2015, and stabilized from 2015 to 2019 (increase of 4.77 cases per 100,000 person-years per year, 95% CI 3.55-5.98 prior to 2015 vs. 2.01 95% CI - 10.16 to 14.18 after 2015). Of the 7715 patients with recurrent CDI, 407 patients (5%) underwent FMT. Gastrointestinal complications were increased within 1 month post FMT (OR 99.60, p < 0.001). Sepsis was identified in two individuals (0.49% 95% CI 0.05-1.7%) within the first month post FMT. The risk of CDI recurrence significantly decreased post FMT compared with anti-CDI antibiotics in the multivariable model (raw-recurrence rate 9.8% vs 36%, aOR = 0.21, 95% CI 0.12-0.53, p < 0.001). CONCLUSION: We show that FMT is strongly associated with a decrease in CDI recurrence compared with the usual care with generally mild complications for up to 2 years.

Large-scale real-world data analysis identifies comorbidity patterns in schizophrenia.

Schizophrenia affects >3.2 million people in the USA. However, its comorbidity patterns have not been systematically characterized in real-world populations. To address this gap, we conducted an observational study using a cohort of 86 million patients in a nationwide health insurance dataset. We identified participants with schizophrenia and those without schizophrenia matched by age, sex, and the first three digits of zip code. For each phenotype encoded in phecodes, we compared their prevalence in schizophrenia patients and the matched non-schizophrenic participants, and we performed subgroup analyses stratified by age and sex. Results show that anxiety, posttraumatic stress disorder, and substance abuse commonly occur in adolescents and young adults prior to schizophrenia diagnoses. Patients aged 60 and above are at higher risks of developing delirium, alcoholism, dementia, pelvic fracture, and osteomyelitis than their matched controls. Type 2 diabetes, sleep apnea, and eating disorders were more prevalent in women prior to schizophrenia diagnosis, whereas acute renal failure, rhabdomyolysis, and developmental delays were found at higher rates in men. Anxiety and obesity are more commonly seen in patients with schizoaffective disorders compared to patients with other types of schizophrenia. Leveraging a large-scale insurance claims dataset, this study identified less-known comorbidity patterns of schizophrenia and confirmed known ones. These comorbidity profiles can guide clinicians and researchers to take heed of early signs of co-occurring diseases.

Association of Postsurgical Opioid Refills for Patients With Risk of Opioid Misuse and Chronic Opioid Use Among Family Members.

Importance: The US health care system is experiencing a sharp increase in opioid-related adverse events and spending, and opioid overprescription may be a key factor in this crisis. Ambient opioid exposure within households is one of the known major dangers of overprescription. Objective: To quantify the association between the postsurgical initiation of prescription opioid use in opioid-naive patients and the subsequent prescription opioid misuse and chronic opioid use among opioid-naive family members. Design, Setting, and Participants: This cohort study was conducted using administrative data from the database of a US commercial insurance provider with more than 35 million covered individuals. Participants included pairs of patients who underwent surgery from January 1, 2008, to December 31, 2016, and their family members within the same household. Data were analyzed from January 1 to November 30, 2018. Exposures: Duration of opioid exposure and refills of opioid prescriptions received by patients after surgery. Main Outcomes and Measures: Risk of opioid misuse and chronic opioid use in family members were calculated using inverse probability weighted Cox proportional hazards regression models. Results: The final cohort included 843 531 pairs of patients and family members. Most pairs included female patients (445 456 [52.8%]) and male family members (442 992 [52.5%]), and a plurality of pairs included patients in the 45 to 54 years age group (249 369 [29.6%]) and family members in the 15 to 24 years age group (313 707 [37.2%]). A total of 3894 opioid misuse events (0.5%) and 7485 chronic opioid use events (0.9%) occurred in family members. In adjusted models, each additional opioid prescription refill for the patient was associated with a 19.2% (95% CI, 14.5%-24.0%) increase in hazard of opioid misuse in family members. The risk of opioid misuse appeared to increase only in households in which the patient obtained refills. Family members in households with any refill had a 32.9% (95% CI, 22.7%-43.8%) increased adjusted hazard of opioid misuse. When patients became chronic opioid users, the hazard ratio for opioid misuse among family members was 2.52 (95% CI, 1.68-3.80), and similar patterns were found for chronic opioid use. Conclusions and Relevance: This cohort study found that opioid exposure was a household risk. Family members of a patient who received opioid prescription refills after surgery had an increased risk of opioid misuse and chronic opioid use.

Multi-PheWAS intersection approach to identify sex differences across comorbidities in 59 140 pediatric patients with autism spectrum disorder.

OBJECTIVE: To identify differences related to sex and define autism spectrum disorder (ASD) comorbidities female-enriched through a comprehensive multi-PheWAS intersection approach on big, real-world data. Although sex difference is a consistent and recognized feature of ASD, additional clinical correlates could help to identify potential disease subgroups, based on sex and age. MATERIALS AND METHODS: We performed a systematic comorbidity analysis on 1860 groups of comorbidities exploring all spectrum of known disease, in 59 140 individuals (11 440 females) with ASD from 4 age groups. We explored ASD sex differences in 2 independent real-world datasets, across all potential comorbidities by comparing (1) females with ASD vs males with ASD and (2) females with ASD vs females without ASD. RESULTS: We identified 27 different comorbidities that appeared significantly more frequently in females with ASD. The comorbidities were mostly neurological (eg, epilepsy, odds ratio [OR] > 1.8, 3-18 years of age), congenital (eg, chromosomal anomalies, OR > 2, 3-18 years of age), and mental disorders (eg, intellectual disability, OR > 1.7, 6-18 years of age). Novel comorbidities included endocrine metabolic diseases (eg, failure to thrive, OR = 2.5, ages 0-2), digestive disorders (gastroesophageal reflux disease: OR = 1.7, 6-11 years of age; and constipation: OR > 1.6, 3-11 years of age), and sense organs (strabismus: OR > 1.8, 3-18 years of age). DISCUSSION: A multi-PheWAS intersection approach on real-world data as presented in this study uniquely contributes to the growing body of research regarding sex-based comorbidity analysis in ASD population. CONCLUSIONS: Our findings provide insights into female-enriched ASD comorbidities that are potentially important in diagnosis, as well as the identification of distinct comorbidity patterns influencing anticipatory treatment or referrals. The code is publicly available (https://github.com/hms-dbmi/sexDifferenceInASD).

Variation in dental services by rurality among privately insured adults in the United States.

OBJECTIVES: Rurality is associated with reduced dental access and worse oral health outcomes. It is unknown whether there is variation in dental services received by rural adults who visit a dentist. METHODS: This was a retrospective analysis of claims data from a large private insurer. All individuals who had at least one dental visit in 2018 were included. Patient demographics, whether or not a patient's ZIP code was rural as defined by the Federal Office of Rural Health Policy, as well as ZIP code demographics were collected. Differences in the frequency of dental services received were evaluated using χ2 tests. Multilevel logistic regressions were used to evaluate the individual and ZIP code-level correlates of receiving a preventive dental procedure, a tooth extraction, or a denture-related dental procedure. RESULTS: Rates of preventive, oral and maxillofacial surgery, and denture-related procedures were higher among rural adults. Accounting for individual age and gender, and ZIP code average income and dentist density, rural dwellers were more likely to receive a preventive procedure [odds ratio (OR) 1.15, P < 0.0001] or tooth extraction (OR 1.08, P < 0.0001), and less likely to have a denture-related procedure (OR 0.94, P = 0.015) compared to nonrural dwellers. Female gender was the strongest predictor of receiving a preventive procedure (OR 1.30, P < 0.0001). CONCLUSIONS: Even among privately insured individuals with known access to dental care, rurality was associated with significant differences in the frequency of various dental procedures. Rural dental patients may have higher needs for oral surgical procedures, even when they have access to preventive care.

Medication utilization in children born preterm in the first two years of life.

OBJECTIVE: To compare medications dispensed during the first 2 years in children born preterm and full-term. STUDY DESIGN: Retrospective analysis of claims data from a commercial national managed care plan 2008-2019. 329,855 beneficiaries were enrolled from birth through 2 years, of which 25,408 (7.7%) were preterm (<37 weeks). Filled prescription claims and paid amount over 2 years were identified. RESULTS: In preterm children, the number of filled prescriptions was 1.4 times and cost was 3.8 times that of full-term children. Number and cost of medications were inversely related to gestational age. Differences peak at 4-9 months and resolve by 19 months after discharge. Palivizumab, ranitidine, albuterol, lansoprazole, budesonide, and prednisolone had the greatest differences in utilization. CONCLUSION: Prescription medication utilization among preterm children under 2 years is driven by palivizumab, anti-reflux, and respiratory medications, despite little evidence regarding efficacy for many medications and concern for harm with certain classes.

Measuring health-care delays among privately insured patients with tuberculosis in the USA: an observational cohort study.

BACKGROUND: A high index of suspicion is needed to initiate appropriate testing for tuberculosis due to its protean symptoms, yet health-care providers in low-incidence settings are becoming less familiar with the disease as rates decline. We aimed to estimate delays in tuberculosis diagnosis and treatment at the US national level between 2008 and 2016. METHODS: In this retrospective observational cohort study, we repurposed private insurance claims data provided by Aetna (Connecticut, USA), to measure health-care delays in tuberculosis diagnosis in the USA in 2008-16. Active tuberculosis was determined by diagnosis codes and the filling of anti-tuberculosis treatment prescriptions. Health-care delays were defined as the duration between the first health-care visit for a tuberculosis symptom and the initiation of anti-tuberculosis treatment. We assessed if delays varied over time, and by patient and system variables, using multivariable regression. We estimated household tuberculosis transmission and respiratory complications after treatment initiation. FINDINGS: We confirmed 738 active tuberculosis cases (incidence 1·45 per 100 000 person-years) with a median health-care delay of 24 days (IQR 10-45). Multivariable regression analysis showed that longer delays were associated with older age (8·4% per 10 year increase [95% CI 4·0 to 13·1]; p<0·0086) and non-HIV immunosuppression (19·2% [15·1 to 60·0]; p=0·0432). Presenting with three or more symptoms was associated with a shorter delay (-22·5% [-39·1 to -2·0]; p=0·0415), relative to presenting with one symptom, as did use of chest imaging (-24·9% [-37·9 to -8·9]; p<0·0098), tuberculosis nucleic acid amplification tests (-19·2% [-32·7 to -3·1]; p=0·0241), and care by a tuberculosis specialist provider (-17·2% [-33·1 to -22·3]; p<0·0087). Longer delays were associated with an increased rate of respiratory complications even after controlling for patient characteristics, and an increased rate of secondary tuberculosis among dependents. INTERPRETATION: In the USA, the median health-care delay for privately insured patients with tuberculosis exceeds WHO-recommended levels of 21 days (3 weeks). The results suggest the need for health-care provider education on best practices in tuberculosis diagnosis, including the use of molecular tests and the maintenance of a high index of suspicion for the disease. FUNDING: US National Institutes of Health.

Real-world data analyses unveiled the immune-related adverse effects of immune checkpoint inhibitors across cancer types.

Immune checkpoint inhibitors have demonstrated significant survival benefits in treating many types of cancers. However, their immune-related adverse events (irAEs) have not been systematically evaluated across cancer types in large-scale real-world populations. To address this gap, we conducted real-world data analyses using nationwide insurance claims data with 85.97 million enrollees across 8 years. We identified a significantly increased risk of developing irAEs among patients receiving immunotherapy agents in all seven cancer types commonly treated with immune checkpoint inhibitors. By six months after treatment initialization, those receiving immunotherapy were 1.50-4.00 times (95% CI, lower bound from 1.15 to 2.16, upper bound from 1.69 to 20.36) more likely to develop irAEs in the first 6 months of treatment, compared to matched chemotherapy or targeted therapy groups, with a total of 92,858 patients. The risk of developing irAEs among patients using nivolumab is higher compared to those using pembrolizumab. These results confirmed the need for clinicians to assess irAEs among cancer patients undergoing immunotherapy as part of management. Our methods are extensible to characterizing the effectiveness and adverse effects of novel treatments in large populations in an efficient and economical fashion.

Dental Services Utilization by Rurality Among Privately Insured Children in the United States.

Purpose: The purpose of this study was to determine differences in dental services received between rural and urban residents in a national sample of children with private insurance. Methods: This was a retrospective study of deidentified claims data from a major national private insurer. Children younger than 18 years of age enrolled throughout 2018 and who had at least one visit to the dentist that year were included. Differences in the frequency of dental procedures received were determined by chi-square tests. Multilevel logistic regression was used to evaluate the effect of individual-level and ZIP Code-level covariates, including rurality, on the odds of receiving a preventive dental service or having a tooth extracted. Results: A total of 603,064 children, with an average age of 10.2±4.4 (standard deviation) years, visited a dentist, and 6.52 percent lived in a rural area. In a multilevel logistic regression correcting for patient age, patient gender, ZIP Code average income, and dental provider density, rurality was positively associated with receiving a tooth extraction (odds ratio [OR] equals 1.06; P<0.001) and negatively associated with receiving a preventive service (OR equals 0.85; P<0.001). Female gender was a negative predictor of preventive services and a predictor of having a tooth extracted. Conclusion: Children living in rural areas had reduced rates of preventive dental care and higher rates of tooth extraction than their nonrural counterparts.

Association of income inequality with orthodontic treatment use.

BACKGROUND: Income inequality has been associated with worse oral health outcomes and reduced dental care use. It is unknown whether income inequality may motivate people to seek orthodontic treatment. METHODS: This was a logistic mixed-effects model of deidentified claims from a private insurer in the United States with enrolled members having at least 1 orthodontic visit in the calendar year as the dependent variable. Total number of dental visits, age, and sex were individual-level covariates. Median household income, Gini coefficient, female population proportion, number of practicing dentists and orthodontists, population size, and population density were zip code-level covariates. RESULTS: A total of 1,860,709 people had at least 1 orthodontic claim. Adjusting for population demographics, the Gini index was significantly positively associated with orthodontic use for children but not for adults (odds ratio, 1.69 for children; P < .0001). Being female was the strongest predictor of orthodontic use for adults and was a significant predictor of use for children (odds ratio, 1.50 and 1.45, respectively; P < .0001). CONCLUSIONS: The Gini index is associated with orthodontic use in children in a privately insured population. Individual characteristics are more predictive of orthodontic use among privately insured adults. PRACTICAL IMPLICATIONS: Demographic and economic traits of communities can affect oral health care use; effects on orthodontic use may be more dramatic than on other forms of oral health care.

Autoimmune Effects of Lung Cancer Immunotherapy Revealed by Data-Driven Analysis on a Nationwide Cohort.

The autoimmune adverse effects of lung cancer immunotherapy are not fully understood at the population level. Using observational data from commercial health insurance claims, we compared autoimmune diseases risk of immune checkpoint inhibitors (including pembrolizumab and nivolumab) and that of chemotherapy using the matching method. By 6 months after treatment initialization, the cumulative incidence of new autoimmune diseases among patients receiving immunotherapy was 13.13% (95% confidence interval (CI), 10.79-15.50%) and that of the matched chemotherapy patients was 6.65% (95% CI, 5.79-7.50%), constituting a hazard ratio (HR) of 1.97 (95% CI, 1.58-2.48). Both pembrolizumab (HR = 2.06 (95% CI, 1.20-3.65), P = 0.0032) and nivolumab (HR = 1.76 (95% CI, 1.39-2.24), P < 0.0001) were associated with higher risks of developing autoimmune diseases, especially for hypothyroidism (P < 0.0001). Our findings suggest the need to monitor autoimmune side effects of immunotherapy.

Estimates of healthcare spending for preterm and low-birthweight infants in a commercially insured population: 2008-2016.

The growth in healthcare spending is an important topic in the United States, and preterm and low-birthweight infants have some of the highest healthcare expenditures of any patient population. We performed a retrospective cohort study of spending in this population using a large, national claims database of commercially insured individuals. A total of 763,566 infants with insurance coverage through Aetna, Inc. for the first 6 months of post-natal life were included, and received approximately $8.4 billion (2016 USD) in healthcare services. Infants with billing codes indicating preterm status (<37 weeks, n = 50,511) incurred medical expenditures of $76,153 on average, while low-birthweight status (<2500 g) was associated with average spending of $114,437. Infants born at 24 weeks gestation (n = 418) had the highest per infant average expenditures of $603,778. Understanding the drivers of variation in costs within gestational age and birthweight bands is an important target for future studies.

Postsurgical prescriptions for opioid naive patients and association with overdose and misuse: retrospective cohort study.

OBJECTIVE: To quantify the effects of varying opioid prescribing patterns after surgery on dependence, overdose, or abuse in an opioid naive population. DESIGN: Retrospective cohort study. SETTING: Surgical claims from a linked medical and pharmacy administrative database of 37 651 619 commercially insured patients between 2008 and 2016. PARTICIPANTS: 1 015 116 opioid naive patients undergoing surgery. MAIN OUTCOME MEASURES: Use of oral opioids after discharge as defined by refills and total dosage and duration of use. The primary outcome was a composite of misuse identified by a diagnostic code for opioid dependence, abuse, or overdose. RESULTS: 568 612 (56.0%) patients received postoperative opioids, and a code for abuse was identified for 5906 patients (0.6%, 183 per 100 000 person years). Total duration of opioid use was the strongest predictor of misuse, with each refill and additional week of opioid use associated with an adjusted increase in the rate of misuse of 44.0% (95% confidence interval 40.8% to 47.2%, P<0.001), and 19.9% increase in hazard (18.5% to 21.4%, P<0.001), respectively. CONCLUSIONS: Each refill and week of opioid prescription is associated with a large increase in opioid misuse among opioid naive patients. The data from this study suggest that duration of the prescription rather than dosage is more strongly associated with ultimate misuse in the early postsurgical period. The analysis quantifies the association of prescribing choices on opioid misuse and identifies levers for possible impact.

Predicting Falls in People Aged 65 Years and Older from Insurance Claims.

BACKGROUND: Accidental falls among people aged 65 years and older caused approximately 2,700,000 injuries, 27,000 deaths, and cost more than 34 billion dollars in the US annually in recent years. Here, we derive and validate a predictive model for falls based on a retrospective cohort of those 65 years and older. METHODS: Insurance claims from a 1-year observational period were used to predict a fall-related claim in the following 2 years. The predictive model takes into account a person's age, sex, prescriptions, and diagnoses. Through random assignment, half of the people had their claims used to derive the model, while the remaining people had their claims used to validate the model. RESULTS: Of 120,881 individuals with Aetna health insurance coverage, 12,431 (10.3%) members fell. During validation, people were risk stratified across 20 levels, where those in the highest risk stratum had 10.5 times the risk as those in the lowest stratum (33.1% vs 3.1%). CONCLUSIONS: Using only insurance claims, individuals in this large cohort at high risk of falls could be readily identified up to 2 years in advance. Although external validation is needed, the findings support the use of the model to better target interventions.