Aim
To determine whether body mass index (BMI) can be accurately identified in epidemiological studies using claims databases.
Materials and methods
Using the Mass General Brigham Research Patient ...Data Repository‐Medicare‐linked database, we identified a cohort of patients with a BMI measurement for the periods January 1 to June 31, 2014 or January 1 to June 31, 2016, to capture both the International Classification of Disease (ICD)‐9 and ICD‐10 eras. Patients were divided into two groups, with or without an obesity‐related ICD code in the 6 months before or after the BMI measurement date. We created two binary measures, first for composite overweight, obesity, or severe obesity (BMI ≥25 kg/m2), and second for obesity or severe obesity (BMI ≥30 kg/m2). We calculated accuracy measures (sensitivity, specificity, positive predictive value PPV and negative predictive value NPV) for each obesity category for the overall cohort, and stratified by type 2 diabetes and ICD‐code era.
Results
The cohort included 73 644 patients with a BMI measurement in 2014 or 2016, of whom 16 280 had an obesity‐related ICD code. The specificity of obesity‐related ICD codes (ICD‐9 and ICD‐10) was 99.7% for underweight/normal weight, 97.4% for overweight, 99.7% for obese and 98.9% for severely obese. For binary categories capturing BMI ≥25 kg/m2 and BMI ≥30 kg/m2, specificity was 97.0% and 98.2%, and PPV was 86.9% and 97.3%. Sensitivity was low overall (<40%). Codes for patients with type 2 diabetes and codes in the ICD‐10 era had higher sensitivity, PPV and NPV.
Conclusion
Obesity‐related ICD codes can accurately identify patients with obesity in epidemiological studies using claims databases.
Direct oral anticoagulants (DOACs) revolutionized the management of thromboembolic disorders. Clinical care may be further improved as Factor XIs undergo large‐scale outcome trials. What role can ...non‐randomized database studies play in expediting understanding of these drugs in clinical practice? The RCT‐DUPLICATIVE Initiative emulated the design of eight DOAC randomized clinical trials (RCT) using non‐randomized claims database studies. RCT study design parameters and measurements were closely emulated by the database studies and produced highly concordant results. The results of the single database study that did not meet all agreement metrics with the specific RCT it was emulating were aligned with a meta‐analysis of six trials studying similar questions, suggesting the trial result was an outlier. Well‐designed database studies using fit‐for‐purpose data came to the same conclusions as DOAC trials, illustrating how database studies could complement RCTs for Factor XI inhibitors—by accelerating insights in underrepresented populations, demonstrating effectiveness and safety in clinical practice, and testing broader indications.
Purpose
Oncology electronic health record (EHR) databases have increased in quality and availability over the past decade, yet it remains unclear whether these clinical practice data can be used to ...conduct reliable comparative effectiveness studies. We sought to emulate a clinical trial with EHR data in the advanced breast cancer population and compare our results against the trial.
Methods
This cohort study used EHR data from US oncology practices. All elements of the study were defined to mimic the PALOMA‐2 trial as closely as possible. Patients with hormone‐positive, HER‐2 negative metastatic breast cancer with no prior treatment for metastatic disease were included. Patients initiating palbociclib and letrozole on the same day following the earliest record of metastasis were compared to those initiating letrozole only. The primary associational measure was the conditional hazard ratio for time‐to‐next treatment (TTNT). TTNT is well‐measured in our data source and amenable for calibration against the randomized study results of the PALOMA‐2 trial. We used multiple imputation for several patient characteristics with missing values.
Results
There were 3836 study‐eligible women with advanced breast cancer. The hazard ratio for TTNT in the observational study (HR: 0.62; 95% CI: 0.56–0.68) was closely aligned with that of the randomized trial (HR: 0.64; 95% CI: 0.52–0.78).
Conclusions
Under our assumptions on missing data and comparability of the two study populations, results from our non‐randomized study closely matched that of the randomized trial. Further studies are needed to determine whether EHR data can yield reliable conclusions on treatment effects in oncology.
Choosing optimal P2Y
inhibitor in frail older adults is challenging because they are at increased risk of both ischemic and bleeding events. We conducted a retrospective cohort study of Medicare ...Advantage Plan beneficiaries who were prescribed clopidogrel, prasugrel, or ticagrelor after percutaneous coronary intervention-treated ST-elevation myocardial infarction from January 1, 2010 to December 31, 2020. Frailty was defined using claims-based frailty index ≥0.25. We conducted multivariable logistic regression to identify factors associated with using potent P2Y
inhibitors and multivariable-adjusted competing risk analyses to compare the rate of discontinuation of potent P2Y
inhibitors in frail versus non-frail patients. There were 11,239 patients (mean age 74 years, 39% women). The prevalence of cardiovascular and geriatric co-morbidities was as follows: 32% chronic kidney disease, 28% heart failure, 10% previous myocardial infarction, 6% dementia, 20% anemia, and 12% frailty. The proportion of patients receiving clopidogrel decreased from 78.3% in 2010 to 2013 to 42.1% in 2018 to 2020, with a concurrent increase in those receiving potent P2Y
inhibitors (mostly ticagrelor) from 21.7% to 57.9%. Frailty was independently associated with reduced odds of initiation (odds ratio 0.78, 95% confidence interval 0.67 to 0.90) but not with discontinuation of potent P2Y
inhibitors (subdistribution hazard ratio 1.09, 95% confidence interval 0.98 to 1.22). In conclusion, frail older adults are less likely to receive potent P2Y
inhibitors after percutaneous coronary intervention-treated ST-elevation myocardial infarction, but they are as likely as non-frail patients to continue with the prescribed P2Y
inhibitor.
The emergence and global spread of the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has resulted in an urgent need for evidence on medical interventions and outcomes of the resulting ...disease, coronavirus disease 2019 (COVID‐19). Although many randomized controlled trials (RCTs) evaluating treatments and vaccines for COVID‐19 are already in progress, the number of clinical questions of interest greatly outpaces the available resources to conduct RCTs. Therefore, there is growing interest in whether nonrandomized real‐world evidence (RWE) can be used to supplement RCT evidence and aid in clinical decision making, but concerns about nonrandomized RWE have been highlighted by a proliferation of RWE studies on medications and COVID‐19 outcomes with widely varying conclusions. The objective of this paper is to review some clinical questions of interest, potential data types, challenges, and merits of RWE in COVID‐19, resulting in recommendations for nonrandomized RWE designs and analyses based on established RWE principles.
Background
Accurately identifying alopecia in claims data is important to study this rare medication side effect.
Objectives
To develop and validate a claims‐based algorithm to identify alopecia in ...women of childbearing age.
Methods
We linked electronic health records from a large healthcare system in Massachusetts (Mass General Brigham) with Medicaid claims data from 2016 through 2018 to identify all women aged 18 to 50 years with an ICD‐10 code for alopecia, including alopecia areata, androgenic alopecia, non‐scarring alopecia, or cicatricial alopecia, from a visit to the MGB system. Using eight predefined algorithms to identify alopecia in Medicaid claims data, we randomly selected 300 women for whom we reviewed their charts to validate the alopecia diagnosis. Positive predictive values (PPVs) were computed for the primary algorithm and seven algorithm variations, stratified by race.
Results
Out of 300 patients with at least 1 ICD‐10 code for alopecia in the Medicaid claims, 286 had chart‐confirmed alopecia (PPV = 95.3%). The algorithm requiring two diagnosis codes plus one prescription claim for alopecia treatment identified 55 patients (PPV = 100%). The algorithm requiring 1 diagnosis code for alopecia plus 1 procedure claim for intralesional triamcinolone injection identified 35 patients (PPV = 100%). Across all 8 algorithms tested, the PPV varied between 95.3% and 100%. The PPV for alopecia ranged from 94% to 100% in White and 96%–100% in 48 non‐White women. The exact date of alopecia onset was difficult to determine in charts.
Conclusion
At least one recorded ICD‐10 code for alopecia in claims data identified alopecia in women of childbearing age with high accuracy.
Evidence and guidelines do not support use of systemic steroids for acute respiratory tract infections (ARTIs), but such practice appears common. We aim to quantify such use and determine its ...predictors.
We conducted a cohort study based on a large United States national commercial claims database, the IBM MarketScan, to identify patients aged 18-64 years with an ARTI diagnosis (acute bronchitis, sinusitis, pharyngitis, otitis media, allergic rhinitis, influenza, pneumonia, and unspecified upper respiratory infections) recorded in ambulatory visits from 2007 to 2016. We excluded those with systemic steroid use in the prior year and an extensive list of steroid-indicated conditions, including asthma, chronic obstructive pulmonary disease, and various autoimmune diseases. We calculated the proportion receiving systemic steroids within 7 days of the ARTI diagnosis and determined its significant predictors. We identified 9,763,710 patients with an eligible ARTI encounter (mean age 39.6, female 56.0%) and found 11.8% were prescribed systemic steroids (46.1% parenteral, 47.3% oral, 6.6% both). All ARTI diagnoses but influenza predicted receiving systemic steroids. There was high geographical variability: the adjusted odds ratio (aOR) of receiving parenteral steroids was 14.48 (95% confidence interval CI 14.23-14.72, p < 0.001) comparing southern versus northeastern US. The corresponding aOR was 1.68 (95% CI 1.66-1.69, p < 0.001) for oral steroids. Other positive predictors for prescribing included emergency department (ED) or urgent care settings (versus regular office), otolaryngologist/ED doctors (versus primary care), fewer comorbidities, and older patient age. There was an increasing trend from 2007 to 2016 (aOR 1.93 95% CI 1.91-1.95 comparing 2016 to 2007, p < 0.001). Our findings are based on patients between 18 and 64 years old with commercial medical insurance and may not be generalizable to older or uninsured populations.
In this study, we found that systemic steroid use in ARTI is common with a great geographical variability. These findings call for an effective education program about this practice, which does not have a clear clinical net benefit.
To determine the impact of electronic health record (EHR)-discontinuity on the performance of prediction models.
The study population consisted of patients with a history of cardiovascular (CV) ...comorbidities identified using US Medicare claims data from 2007 to 2017, linked to EHR from two networks (used as model training and validation set, respectively). We built models predicting one-year risk of mortality, major CV events, and major bleeding events, stratified by high vs. low algorithm-predicted EHR-continuity. The best-performing models for each outcome were chosen among 5 commonly used machine-learning models. We compared model performance by Area under the ROC curve (AUROC) and Area under the precision-recall curve (AUPRC).
Based on 180,950 in the training and 103,061 in the validation set, we found EHR captured only 21.0-28.1% of all the non-fatal outcomes in the low EHR-continuity cohort but 55.4-66.1% of that in the high EHR-continuity cohort. In the validation set, the best-performing model developed among high EHR-continuity patients had consistently higher AUROC than that based on low-continuity patients: AUROC was 0.849 vs. 0.743 when predicting mortality; AUROC was 0.802 vs. 0.659 predicting the CV events; AUROC was 0.635 vs. 0.567 predicting major bleeding. We observed a similar pattern when using AUPRC as the outcome metric.
Among patients with CV comorbidities, when predicting mortality, major CV events, and bleeding outcomes, the prediction models developed in datasets with low EHR-continuity consistently had worse performance compared to models developed with high EHR-continuity.
BACKGROUND:It is unclear how out-of-system care or electronic health record (EHR) discontinuity (i.e., receiving care outside of an EHR system) may affect validity of comparative effectiveness ...research using these data. We aimed to compare the misclassification of key variables in patients with high versus low EHR continuity.
METHODS:The study cohort comprised patients ages ≥65 identified in electronic health records from two US provider networks linked with Medicare insurance claims data from 2007 to 2014. By comparing electronic health records and claims data, we quantified EHR continuity by the proportion of encounters captured by the EHRs (i.e., “capture proportion”). Within levels of EHR continuity, for 40 key variables, we quantified misclassification by mean standardized differences between coding based on EHRs alone versus linked claims and EHR data.
RESULTS:Based on 183,739 patients, we found that mean capture proportion in a single electronic health record system was 16%–27% across two provider networks. Patients with highest level of EHR continuity (capture proportion ≥ 80%) had 11.4- to 17.4-fold less variable misclassification, when compared with those with lowest level of EHR continuity (capture proportion< 10%). Capturing at least 60% of the encounters in an EHR system was required to have reasonable variable classification (mean standardized difference <0.1). We found modest differences in comorbidity profiles between patients with high and low EHR continuity.
CONCLUSIONS:EHR discontinuity may lead to substantial misclassification in key variables. Restricting comparative effectiveness research to patients with high EHR continuity may confer a favorable benefit (reducing information bias) to risk (losing generalizability) ratio.
Alzheimer's Disease and Related Dementias (ADRD) may result in poor surgical outcomes. The current study aims to characterize the risk of ADRD on outcomes for patients undergoing colorectal surgery.
...Colorectal surgery patients with and without ADRD from 2007 to 2017 were identified using electronic health record-linked Medicare claims data from two large health systems. Unadjusted and adjusted analyses were performed to evaluate postoperative outcomes.
5926 patients (median age 74) underwent colorectal surgery of whom 4.8% (n = 285) had ADRD. ADRD patients were more likely to undergo emergent operations (27.7% vs. 13.6%, p < 0.001) and be discharged to a facility (49.8% vs 28.9%, p < 0.001). After multi-variable adjustment, ADRD patients were more likely to have complications (61.1% vs 48.3%, p < 0.001) and required longer hospitalization (7.1 vs 6.1 days, p = 0.001).
The diagnosis of ADRD is an independent risk factor for prolonged hospitalization and postoperative complications after colorectal surgery.
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•Dementia may complicate recovery after colorectal surgery.•Multi-variable analysis of 5926 patients was performed using a large dataset.•Dementia was associated with worse outcomes after elective and emergent colorectal surgery.
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