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1.
Am J Epidemiol ; 193(1): 203-213, 2024 Jan 08.
Article in English | MEDLINE | ID: mdl-37650647

ABSTRACT

We developed and validated a claims-based algorithm that classifies patients into obesity categories. Using Medicare (2007-2017) and Medicaid (2000-2014) claims data linked to 2 electronic health record (EHR) systems in Boston, Massachusetts, we identified a cohort of patients with an EHR-based body mass index (BMI) measurement (calculated as weight (kg)/height (m)2). We used regularized regression to select from 137 variables and built generalized linear models to classify patients with BMIs of ≥25, ≥30, and ≥40. We developed the prediction model using EHR system 1 (training set) and validated it in EHR system 2 (validation set). The cohort contained 123,432 patients in the Medicare population and 40,736 patients in the Medicaid population. The model comprised 97 variables in the Medicare set and 95 in the Medicaid set, including BMI-related diagnosis codes, cardiovascular and antidiabetic drugs, and obesity-related comorbidities. The areas under the receiver-operating-characteristic curve in the validation set were 0.72, 0.75, and 0.83 (Medicare) and 0.66, 0.66, and 0.70 (Medicaid) for BMIs of ≥25, ≥30, and ≥40, respectively. The positive predictive values were 81.5%, 80.6%, and 64.7% (Medicare) and 81.6%, 77.5%, and 62.5% (Medicaid), for BMIs of ≥25, ≥30, and ≥40, respectively. The proposed model can identify obesity categories in claims databases when BMI measurements are missing and can be used for confounding adjustment, defining subgroups, or probabilistic bias analysis.


Subject(s)
Medicare , Obesity , Aged , Humans , United States/epidemiology , Obesity/epidemiology , Body Mass Index , Comorbidity , Hypoglycemic Agents , Electronic Health Records
2.
Pharmacoepidemiol Drug Saf ; 33(1): e5684, 2024 Jan.
Article in English | MEDLINE | ID: mdl-37654015

ABSTRACT

BACKGROUND: We aimed to determine whether integrating concepts from the notes from the electronic health record (EHR) data using natural language processing (NLP) could improve the identification of gout flares. METHODS: Using Medicare claims linked with EHR, we selected gout patients who initiated the urate-lowering therapy (ULT). Patients' 12-month baseline period and on-treatment follow-up were segmented into 1-month units. We retrieved EHR notes for months with gout diagnosis codes and processed notes for NLP concepts. We selected a random sample of 500 patients and reviewed each of their notes for the presence of a physician-documented gout flare. Months containing at least 1 note mentioning gout flares were considered months with events. We used 60% of patients to train predictive models with LASSO. We evaluated the models by the area under the curve (AUC) in the validation data and examined positive/negative predictive values (P/NPV). RESULTS: We extracted and labeled 839 months of follow-up (280 with gout flares). The claims-only model selected 20 variables (AUC = 0.69). The NLP concept-only model selected 15 (AUC = 0.69). The combined model selected 32 claims variables and 13 NLP concepts (AUC = 0.73). The claims-only model had a PPV of 0.64 [0.50, 0.77] and an NPV of 0.71 [0.65, 0.76], whereas the combined model had a PPV of 0.76 [0.61, 0.88] and an NPV of 0.71 [0.65, 0.76]. CONCLUSION: Adding NLP concept variables to claims variables resulted in a small improvement in the identification of gout flares. Our data-driven claims-only model and our combined claims/NLP-concept model outperformed existing rule-based claims algorithms reliant on medication use, diagnosis, and procedure codes.


Subject(s)
Gout , Aged , Humans , United States/epidemiology , Gout/diagnosis , Gout/epidemiology , Natural Language Processing , Electronic Health Records , Medicare , Symptom Flare Up , Algorithms
3.
J Med Internet Res ; 26: e47739, 2024 Feb 13.
Article in English | MEDLINE | ID: mdl-38349732

ABSTRACT

BACKGROUND: Assessment of activities of daily living (ADLs) and instrumental ADLs (iADLs) is key to determining the severity of dementia and care needs among older adults. However, such information is often only documented in free-text clinical notes within the electronic health record and can be challenging to find. OBJECTIVE: This study aims to develop and validate machine learning models to determine the status of ADL and iADL impairments based on clinical notes. METHODS: This cross-sectional study leveraged electronic health record clinical notes from Mass General Brigham's Research Patient Data Repository linked with Medicare fee-for-service claims data from 2007 to 2017 to identify individuals aged 65 years or older with at least 1 diagnosis of dementia. Notes for encounters both 180 days before and after the first date of dementia diagnosis were randomly sampled. Models were trained and validated using note sentences filtered by expert-curated keywords (filtered cohort) and further evaluated using unfiltered sentences (unfiltered cohort). The model's performance was compared using area under the receiver operating characteristic curve and area under the precision-recall curve (AUPRC). RESULTS: The study included 10,000 key-term-filtered sentences representing 441 people (n=283, 64.2% women; mean age 82.7, SD 7.9 years) and 1000 unfiltered sentences representing 80 people (n=56, 70% women; mean age 82.8, SD 7.5 years). Area under the receiver operating characteristic curve was high for the best-performing ADL and iADL models on both cohorts (>0.97). For ADL impairment identification, the random forest model achieved the best AUPRC (0.89, 95% CI 0.86-0.91) on the filtered cohort; the support vector machine model achieved the highest AUPRC (0.82, 95% CI 0.75-0.89) for the unfiltered cohort. For iADL impairment, the Bio+Clinical bidirectional encoder representations from transformers (BERT) model had the highest AUPRC (filtered: 0.76, 95% CI 0.68-0.82; unfiltered: 0.58, 95% CI 0.001-1.0). Compared with a keyword-search approach on the unfiltered cohort, machine learning reduced false-positive rates from 4.5% to 0.2% for ADL and 1.8% to 0.1% for iADL. CONCLUSIONS: In this study, we demonstrated the ability of machine learning models to accurately identify ADL and iADL impairment based on free-text clinical notes, which could be useful in determining the severity of dementia.


Subject(s)
Dementia , Natural Language Processing , United States , Humans , Aged , Female , Aged, 80 and over , Male , Cross-Sectional Studies , Activities of Daily Living , Functional Status , Medicare
4.
JAMA ; 329(16): 1376-1385, 2023 04 25.
Article in English | MEDLINE | ID: mdl-37097356

ABSTRACT

Importance: Nonrandomized studies using insurance claims databases can be analyzed to produce real-world evidence on the effectiveness of medical products. Given the lack of baseline randomization and measurement issues, concerns exist about whether such studies produce unbiased treatment effect estimates. Objective: To emulate the design of 30 completed and 2 ongoing randomized clinical trials (RCTs) of medications with database studies using observational analogues of the RCT design parameters (population, intervention, comparator, outcome, time [PICOT]) and to quantify agreement in RCT-database study pairs. Design, Setting, and Participants: New-user cohort studies with propensity score matching using 3 US claims databases (Optum Clinformatics, MarketScan, and Medicare). Inclusion-exclusion criteria for each database study were prespecified to emulate the corresponding RCT. RCTs were explicitly selected based on feasibility, including power, key confounders, and end points more likely to be emulated with real-world data. All 32 protocols were registered on ClinicalTrials.gov before conducting analyses. Emulations were conducted from 2017 through 2022. Exposures: Therapies for multiple clinical conditions were included. Main Outcomes and Measures: Database study emulations focused on the primary outcome of the corresponding RCT. Findings of database studies were compared with RCTs using predefined metrics, including Pearson correlation coefficients and binary metrics based on statistical significance agreement, estimate agreement, and standardized difference. Results: In these highly selected RCTs, the overall observed agreement between the RCT and the database emulation results was a Pearson correlation of 0.82 (95% CI, 0.64-0.91), with 75% meeting statistical significance, 66% estimate agreement, and 75% standardized difference agreement. In a post hoc analysis limited to 16 RCTs with closer emulation of trial design and measurements, concordance was higher (Pearson r, 0.93; 95% CI, 0.79-0.97; 94% meeting statistical significance, 88% estimate agreement, 88% standardized difference agreement). Weaker concordance occurred among 16 RCTs for which close emulation of certain design elements that define the research question (PICOT) with data from insurance claims was not possible (Pearson r, 0.53; 95% CI, 0.00-0.83; 56% meeting statistical significance, 50% estimate agreement, 69% standardized difference agreement). Conclusions and Relevance: Real-world evidence studies can reach similar conclusions as RCTs when design and measurements can be closely emulated, but this may be difficult to achieve. Concordance in results varied depending on the agreement metric. Emulation differences, chance, and residual confounding can contribute to divergence in results and are difficult to disentangle.


Subject(s)
Randomized Controlled Trials as Topic , Humans , Research Design , Observational Studies as Topic
5.
Circulation ; 143(10): 1002-1013, 2021 03 09.
Article in English | MEDLINE | ID: mdl-33327727

ABSTRACT

BACKGROUND: Regulators are evaluating the use of noninterventional real-world evidence (RWE) studies to assess the effectiveness of medical products. The RCT DUPLICATE initiative (Randomized, Controlled Trials Duplicated Using Prospective Longitudinal Insurance Claims: Applying Techniques of Epidemiology) uses a structured process to design RWE studies emulating randomized, controlled trials (RCTs) and compare results. We report findings of the first 10 trial emulations, evaluating cardiovascular outcomes of antidiabetic or antiplatelet medications. METHODS: We selected 3 active-controlled and 7 placebo-controlled RCTs for replication. Using patient-level claims data from US commercial and Medicare payers, we implemented inclusion and exclusion criteria, selected primary end points, and comparator populations to emulate those of each corresponding RCT. Within the trial-mimicking populations, we conducted propensity score matching to control for >120 preexposure confounders. All study measures were prospectively defined and protocols registered before hazard ratios and 95% CIs were computed. Success criteria for the primary analysis were prespecified for each replication. RESULTS: Despite attempts to emulate RCT design as closely as possible, differences between the RCT and corresponding RWE study populations remained. The regulatory conclusions were equivalent in 6 of 10. The RWE emulations achieved a hazard ratio estimate that was within the 95% CI from the corresponding RCT in 8 of 10 studies. In 9 of 10, either the regulatory or estimate agreement success criteria were fulfilled. The largest differences in effect estimates were found for RCTs where second-generation sulfonylureas were used as a proxy for placebo regarding cardiovascular effects. Nine of 10 replications had a standardized difference between effect estimates of <2, which suggests differences within expected random variation. CONCLUSIONS: Agreement between RCT and RWE findings varies depending on which agreement metric is used. Interim findings indicate that selection of active comparator therapies with similar indications and use patterns enhances the validity of RWE. Even in the context of active comparators, concordance between RCT and RWE findings is not guaranteed, partially because trials are not emulated exactly. More trial emulations are needed to understand how often and in what contexts RWE findings match RCTs. Registration: URL: https://www.clinicaltrials.gov; Unique identifiers: NCT03936049, NCT04215523, NCT04215536, NCT03936010, NCT03936036, NCT03936062, NCT03936023, NCT03648424, NCT04237935, NCT04237922.


Subject(s)
Pragmatic Clinical Trials as Topic/methods , Randomized Controlled Trials as Topic/methods , Aged , Female , Humans , Male , Middle Aged
6.
Am Heart J ; 254: 203-215, 2022 Dec.
Article in English | MEDLINE | ID: mdl-36150454

ABSTRACT

BACKGROUND: The effect of sodium glucose cotransporter 2 inhibitors (SGLT2i) on the total (first and recurrent) burden of cardiovascular (CV) hospitalizations, including hospitalization for heart failure, myocardial infarction, and stroke, is poorly understood. OBJECTIVE: To assess the effect of empagliflozin, an SGLT2i, on total CV hospitalizations among older adults with T2D. METHODS: Using data from Medicare fee-for-service (08/2014-09/2017), we identified 1:1 propensity score-matched cohorts of patients with T2D initiating empagliflozin versus sitagliptin or empagliflozin versus glucagon-like peptide-1 receptor agonists (GLP-1RA), balancing >140 baseline covariates. We compared the risk of first and recurrent hospitalizations with any CV condition as the primary discharge diagnosis (ICD-9: 390-459; ICD-10: I00-I99), hospitalizations for heart failure (HHF), and myocardial infarctions (MI) or stroke. We estimated treatment effects based on the Ghosh-Lin semiparametric model for recurrent events as primary and joint frailty model as secondary analysis. RESULTS: We included 11,429 matched-pairs of empagliflozin and sitagliptin initiators and 17,502 matched-pairs of empagliflozin and GLP1-RA initiators with an average age of 72 years. Empagliflozin was associated with a reduced risk of total CV hospitalizations (0.80 [0.69-0.93] vs sitagliptin; 0.88 [0.77-1.00] vs GLP-1RA) and total HHF (0.70 [0.51-0.98] vs sitagliptin; 0.76 [0.56-1.03] vs GLP1-RA) over a mean follow up of 6.3 months. No differences between treatments were observed for MI or stroke. Results were consistent for joint frailty models. CONCLUSION: Empagliflozin, compared to sitagliptin or to a lesser extent GLP1-RA, was associated with a reduction in the burden of total CV hospitalizations and HHF in older patients with T2D.


Subject(s)
Cardiovascular Diseases , Diabetes Mellitus, Type 2 , Heart Failure , Sodium-Glucose Transporter 2 Inhibitors , Stroke , Humans , Aged , United States/epidemiology , Sodium-Glucose Transporter 2 Inhibitors/therapeutic use , Sodium-Glucose Transporter 2 Inhibitors/pharmacology , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/drug therapy , Diabetes Mellitus, Type 2/diagnosis , Hypoglycemic Agents/therapeutic use , Medicare , Sitagliptin Phosphate/therapeutic use , Cardiovascular Diseases/complications , Heart Failure/drug therapy , Heart Failure/epidemiology , Heart Failure/complications , Stroke/drug therapy
7.
Diabetes Obes Metab ; 24(3): 442-454, 2022 03.
Article in English | MEDLINE | ID: mdl-34729891

ABSTRACT

AIM: To investigate effectiveness and safety outcomes among patients with type 2 diabetes (T2D) initiating empagliflozin versus dipeptidyl peptidase-4 (DPP-4) inhibitor treatment across the broad spectrum of cardiovascular risk. METHODS: In a population-based cohort study we identified 39 072 pairs of 1:1 propensity score-matched adult patients with T2D initiating empagliflozin or DPP-4 inhibitors, using data from 2 US commercial insurance databases and Medicare between August 2014 and September 2017. The primary outcomes were a composite of myocardial infarction (MI)/stroke, and hospitalization for heart failure (HHF). Safety outcomes were bone fractures, lower-limb amputations (LLAs), diabetic ketoacidosis (DKA), and acute kidney injury (AKI). We estimated pooled hazard ratios (HRs) and 95% confidence intervals (CIs) adjusting for more than 140 baseline covariates. RESULTS: Study participants had a mean age of 60 years and only 28% had established cardiovascular disease. Compared to DPP-4 inhibitors, empagliflozin was associated with similar risk of MI/stroke (HR 0.99 [95% CI 0.81-1.21]), and lower risk of HHF (HR 0.48 [95% CI 0.35-0.67] and 0.63 [95% CI 0.54-0.74], based on a primary and any heart failure discharge diagnosis, respectively). The HR was 0.52 (95% CI 0.38-0.72) for all-cause mortality (ACM) and 0.83 (95% CI 0.70-0.98) for a composite of MI/stroke/ACM. Empagliflozin was associated with a similar risk of LLA and fractures, an increased risk of DKA (HR 1.71 [95% CI 1.08-2.71]) and a decreased risk of AKI (HR 0.60 [95% CI 0.43-0.85]). CONCLUSIONS: In clinical practice, the initiation of empagliflozin versus a DPP-4 inhibitor was associated with a lower risk of HHF, ACM and MI/stroke/ACM, a similar risk of MI/stroke, and a safety profile consistent with documented information.


Subject(s)
Cardiovascular Diseases , Diabetes Mellitus, Type 2 , Dipeptidyl-Peptidase IV Inhibitors , Myocardial Infarction , Sodium-Glucose Transporter 2 Inhibitors , Adult , Aged , Benzhydryl Compounds , Cardiovascular Diseases/complications , Cohort Studies , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/drug therapy , Dipeptidyl-Peptidase IV Inhibitors/adverse effects , Glucosides , Humans , Medicare , Middle Aged , Myocardial Infarction/complications , Sodium-Glucose Transporter 2 Inhibitors/therapeutic use , Treatment Outcome , United States
8.
Pharmacoepidemiol Drug Saf ; 31(4): 467-475, 2022 04.
Article in English | MEDLINE | ID: mdl-34908211

ABSTRACT

BACKGROUND: Prior validation studies of claims-based definitions of chronic kidney disease (CKD) using ICD-9 codes reported overall low sensitivity, high specificity, and variable but reasonable PPV. No studies to date have evaluated the accuracy of ICD-10 codes to identify a US patient population with CKD. METHODS: We assessed the accuracy of claims-based algorithms to identify adults with CKD Stages 3-5 compared with laboratory values in a subset (~40%) of a US commercial insurance claims database (Optum's de-identified Clinformatics® Data Mart Database). We calculated the positive predictive value (PPV) of one or two ICD-9 (2012-2014) or ICD-10 (2016-2018) codes for CKD compared with a lab-based estimated glomerular filtration rate (eGFR) occurring within prespecified windows (±90 days, ±180 days, ±365 days) of the ICD-based CKD code(s). RESULTS: The study population ranged between 104 774 and 161 305 patients (ICD-9 cohorts) and between 285 520 and 373 220 patients (ICD-10 cohorts). The mean age was 74.4 years (ICD-9) and 75.6 years (ICD-10) and the median eGFR was 48 ml/min/1.73 m2 . The algorithm of two CKD codes compared with a lab value ±90 days of the first code achieved the highest PPV (PPV 86.36% [ICD-9] and 86.07% [ICD-10]). Overall, ICD-10 based codes had comparable PPVs to ICD-9 based codes and all ICD-10 based algorithms had PPVs >80%. The algorithm of one CKD code compared with laboratory value ±180 days maintained the PPV above 80% but still retained a large number of patients (PPV 80.32% [ICD-9] and 81.56% [ICD-10]). CONCLUSION: An ICD-10-based definition of CKD identified with sufficient accuracy a patient population with CKD Stages 3-5. Our findings suggest that claims databases could be used for future real-world research studies in patients with CKD Stages 3-5.


Subject(s)
International Classification of Diseases , Renal Insufficiency, Chronic , Adult , Aged , Algorithms , Databases, Factual , Glomerular Filtration Rate , Humans , Predictive Value of Tests , Renal Insufficiency, Chronic/diagnosis , Renal Insufficiency, Chronic/epidemiology
9.
Ann Intern Med ; 174(9): 1214-1223, 2021 09.
Article in English | MEDLINE | ID: mdl-34280330

ABSTRACT

BACKGROUND: The role of differing levels of frailty in the choice of oral anticoagulants for older adults with atrial fibrillation (AF) is unclear. OBJECTIVE: To examine the outcomes of direct oral anticoagulants (DOACs) versus warfarin by frailty levels. DESIGN: 1:1 propensity score-matched analysis of Medicare data, 2010 to 2017. SETTING: Community. PATIENTS: Medicare beneficiaries with AF who initiated use of dabigatran, rivaroxaban, apixaban, or warfarin. MEASUREMENTS: Composite end point of death, ischemic stroke, or major bleeding by frailty levels, defined by a claims-based frailty index. RESULTS: In the dabigatran-warfarin cohort (n = 158 730; median follow-up, 72 days), the event rate per 1000 person-years was 63.5 for dabigatran initiators and 65.6 for warfarin initiators (hazard ratio [HR], 0.98 [95% CI, 0.92 to 1.05]; rate difference [RD], -2.2 [CI, -6.5 to 2.1]). For nonfrail, prefrail, and frail persons, HRs were 0.81 (CI, 0.68 to 0.97), 0.98 (CI, 0.90 to 1.08), and 1.09 (CI, 0.96 to 1.23), respectively. In the rivaroxaban-warfarin cohort (n = 275 944; median follow-up, 82 days), the event rate per 1000 person-years was 77.8 for rivaroxaban initiators and 83.7 for warfarin initiators (HR, 0.98 [CI, 0.94 to 1.02]; RD, -5.9 [CI, -9.4 to -2.4]). For nonfrail, prefrail, and frail persons, HRs were 0.88 (CI, 0.77 to 0.99), 1.04 (CI, 0.98 to 1.10), and 0.96 (CI, 0.89 to 1.04), respectively. In the apixaban-warfarin cohort (n = 218 738; median follow-up, 84 days), the event rate per 1000 person-years was 60.1 for apixaban initiators and 92.3 for warfarin initiators (HR, 0.68 [CI, 0.65 to 0.72]; RD, -32.2 [CI, -36.1 to -28.3]). For nonfrail, prefrail, and frail persons, HRs were 0.61 (CI, 0.52 to 0.71), 0.66 (CI, 0.61 to 0.70), and 0.73 (CI, 0.67 to 0.80), respectively. LIMITATIONS: Residual confounding and lack of clinical frailty assessment. CONCLUSION: For older adults with AF, apixaban was associated with lower rates of adverse events across all frailty levels. Dabigatran and rivaroxaban were associated with lower event rates only among nonfrail patients. PRIMARY FUNDING SOURCE: National Institute on Aging.


Subject(s)
Anticoagulants/administration & dosage , Atrial Fibrillation/drug therapy , Frail Elderly , Warfarin/administration & dosage , Administration, Oral , Aged , Dabigatran/administration & dosage , Female , Humans , Male , Massachusetts , Medicare , Propensity Score , Pyrazoles/administration & dosage , Pyridones/administration & dosage , Retrospective Studies , Rivaroxaban/administration & dosage , United States
10.
Ann Intern Med ; 174(11): 1528-1541, 2021 11.
Article in English | MEDLINE | ID: mdl-34570599

ABSTRACT

BACKGROUND: Both sodium-glucose cotransporter-2 (SGLT2) inhibitors and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have shown cardiovascular benefits in placebo-controlled trials of patients with type 2 diabetes (T2D) and established cardiovascular disease (CVD). OBJECTIVE: To evaluate whether SGLT2 inhibitors and GLP-1 RAs are associated with differential cardiovascular benefit among T2D patients with and without CVD. DESIGN: Population-based cohort study. SETTING: Medicare and 2 U.S. commercial claims data sets (April 2013 to December 2017). PARTICIPANTS: 1:1 propensity score-matched adult T2D patients with and without CVD (52 901 and 133 139 matched pairs) initiating SGLT2 inhibitor versus GLP-1 RA therapy. MEASUREMENTS: Primary outcomes were myocardial infarction (MI) or stroke hospitalization and hospitalization for heart failure (HHF). Pooled hazard ratios (HRs) and rate differences (RDs) per 1000 person-years were estimated, with 95% CIs, controlling for 138 preexposure covariates. RESULTS: The initiation of SGLT2 inhibitor versus GLP-1 RA therapy was associated with a slightly lower risk for MI or stroke in patients with CVD (HR, 0.90 [95% CI, 0.82 to 0.98]; RD, -2.47 [CI, -4.45 to -0.50]) but similar risk in those without CVD (HR, 1.07 [CI, 0.97 to 1.18]; RD, 0.38 [CI, -0.30 to 1.07]). The initiation of SGLT2 inhibitor versus GLP-1 RA therapy was associated with reductions in HHF risk regardless of baseline CVD in patients with CVD (HR, 0.71 [CI, 0.64 to 0.79]; RD, -4.97 [CI, -6.55 to -3.39]) and in those without CVD (HR, 0.69 [CI, 0.56 to 0.85]; RD, -0.58 [CI, -0.91 to -0.25]). LIMITATION: Treatment selection was not randomized. CONCLUSION: Use of SGLT2 inhibitors versus GLP-1 RAs was associated with consistent reductions in HHF risk among T2D patients with and without CVD, although the absolute benefit was greater in patients with CVD. There were no large differences in risk for MI or stroke among T2D patients with and without CVD. PRIMARY FUNDING SOURCE: Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School.


Subject(s)
Cardiovascular Diseases/epidemiology , Glucagon-Like Peptide-1 Receptor/agonists , Sodium-Glucose Transporter 2 Inhibitors/therapeutic use , Aged , Cohort Studies , Diabetes Mellitus, Type 2/drug therapy , Female , Heart Failure/epidemiology , Hospitalization/statistics & numerical data , Humans , Male , Matched-Pair Analysis , Middle Aged , Myocardial Infarction/epidemiology , Stroke/epidemiology , United States/epidemiology
11.
Subst Abus ; 43(1): 127-130, 2022.
Article in English | MEDLINE | ID: mdl-32348190

ABSTRACT

BACKGROUND: The May 2017 publication of the updated Associated Press (AP) Stylebook offered guidance that advised against stigmatizing. The objective of this study was to assess the frequency of stigmatizing terms describing substance use and disorder in news articles before and after the update of the AP Stylebook.Methods: We reviewed articles containing terms "opioid" or "addiction" from three major news outlets. We counted the number of AP Stylebook proscribed terms found in each article and compared the proportions of articles from each outlet with proscribed terms before and after AP Stylebook publication.Results: In 2016, 56-94% of articles from each of the three news outlets contained a proscribed term. The use of proscribed terms in articles identified by searching "opioid" published in the New York Times decreased (72% vs. 94%, p = 0.01) after the AP Stylebook change. For other news outlets, there were no significant differences, though all proportions were lower after publication.Conclusions: Evidence for a decrease in the use of stigmatizing terminology for substance use and disorders in news articles after publication of guidance was limited. Additional efforts should address use of such terminology to maximize implementation of effective addiction health policies and practices.


Subject(s)
Behavior, Addictive , Substance-Related Disorders , Analgesics, Opioid , Humans , Mass Media , New York
12.
Pharmacoepidemiol Drug Saf ; 30(7): 868-874, 2021 07.
Article in English | MEDLINE | ID: mdl-33715280

ABSTRACT

PURPOSE: Accurately identifying patients with psoriasis (PsO) is crucial for generating real-world evidence on PsO disease course and treatment utilization. METHODS: We developed nine claims-based algorithms for PsO using a combination of the International Classification of Diseases (ICD)-9 codes, specialist visit, and medication dispensing using Medicare linked to electronic health records data (2013-2014) in two healthcare provider networks in Boston, Massachusetts. We calculated positive predictive value (PPV) and 95% confidence interval (CI) for each algorithm using the treating physician's diagnosis of PsO via chart review as the gold standard. Among the confirmed PsO cases, we assessed their PsO disease activity. RESULTS: The nine claims-based algorithms identified 990 unique patient records. Of those, 918 (92.7%) with adequate information were reviewed. The PPV of the algorithms ranged from 65.1 to 82.9%. An algorithm defined as ≥1 ICD-9 diagnosis code for PsO and ≥1 prescription claim for topical vitamin D agents showed the highest PPV (82.9%). The PPV of the algorithm requiring ≥2 ICD-9 diagnosis codes and ≥1 prescription claim for PsO treatment excluding topical steroids was 81.1% but higher (82.5%) when ≥1 diagnosis was from a dermatologist. Among 411 PsO patients with adequate information on PsO disease activity in EHRs, 1.5-5.8% had no disease activity, 31.3-36.8% mild, and 26.9-35.1% moderate-to-severe across the algorithms. CONCLUSIONS: Claims-based algorithms based on a combination of PsO diagnosis codes and dispensing for PsO-specific treatments had a moderate-to-high PPV. These algorithms can serve as a useful tool to identify patients with PsO in future real-world data pharmacoepidemiologic studies.


Subject(s)
Medicare , Psoriasis , Aged , Algorithms , Databases, Factual , Electronic Health Records , Humans , International Classification of Diseases , Psoriasis/diagnosis , Psoriasis/drug therapy , United States
13.
Circulation ; 139(25): 2822-2830, 2019 06 18.
Article in English | MEDLINE | ID: mdl-30955357

ABSTRACT

BACKGROUND: The EMPA-REG OUTCOME trial (Empagliflozin Cardiovascular Outcome Event Trial in Type 2 diabetes Mellitus Patients) showed that empagliflozin, a sodium-glucose cotransporter-2 inhibitor, reduces the risk of hospitalization for heart failure (HHF) by 35%, on top of standard of care in patients with type 2 diabetes mellitus (T2D) and established cardiovascular disease. The EMPRISE (Empagliflozin Comparative Effectiveness and Safety) study aims to assess empagliflozin's effectiveness, safety, and healthcare utilization in routine care from August 2014 through September 2019. In this first interim analysis, we investigated the risk of HHF among T2D patients initiating empagliflozin versus sitagliptin, a dipeptidyl peptidase-4 inhibitor. METHODS: Within 2 commercial and 1 federal (Medicare) claims data sources in the United States, we identified a 1:1 propensity score-matched cohort of T2D patients ≥18 years old initiating empagliflozin or sitagliptin from August 2014 through September 2016. The HHF outcome was defined as a HF discharge diagnosis in the primary position (HHF-specific); a broader definition was based on a HF discharge diagnosis in any position (HHF-broad). Hazard ratios (HRs) and 95% CIs were estimated controlling for over 140 baseline characteristics in each data source and pooled by fixed-effects meta-analysis. RESULTS: After propensity-score matching, we identified 16,443 patient pairs who initiated empagliflozin or sitagliptin. Average age was approximately 59 years, almost 54% of the participants were males, and approximately 25% had records of existing cardiovascular disease. Compared with sitagliptin, the initiation of empagliflozin decreased the risk of HHF-specific by 50% (HR, 0.50; 95% CI, 0.28-0.91), and the risk of HHF-broad by 49% (HR, 0.51;95% CI, 0.39-0.68), over a mean follow-up of 5.3 months. The results were consistent in patients with and without baseline cardiovascular disease, and for empagliflozin at both the 10- and 25-mg daily doses; analyses comparing empagliflozin versus the dipeptidyl peptidase-4 inhibitor class, and comparing sodium-glucose cotransporter-2 inhibitor versus dipeptidyl peptidase-4 inhibitor classes also produced consistent findings. CONCLUSIONS: The first interim analysis from EMPRISE showed that compared with sitagliptin, the initiation of empagliflozin was associated with a decreased risk of HHF among patients with T2D as treated in routine care, with and without a history of cardiovascular disease. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifier: NCT03363464.


Subject(s)
Benzhydryl Compounds/therapeutic use , Diabetes Mellitus, Type 2/drug therapy , Dipeptidyl-Peptidase IV Inhibitors/therapeutic use , Glucosides/therapeutic use , Heart Failure/therapy , Hospitalization , Sitagliptin Phosphate/therapeutic use , Sodium-Glucose Transporter 2 Inhibitors/therapeutic use , Aged , Benzhydryl Compounds/adverse effects , Comparative Effectiveness Research , Databases, Factual , Diabetes Mellitus, Type 2/diagnosis , Diabetes Mellitus, Type 2/epidemiology , Dipeptidyl-Peptidase IV Inhibitors/adverse effects , Female , Glucosides/adverse effects , Heart Failure/diagnosis , Heart Failure/epidemiology , Humans , Male , Middle Aged , Risk Assessment , Risk Factors , Sitagliptin Phosphate/adverse effects , Sodium-Glucose Transporter 2 Inhibitors/adverse effects , Time Factors , Treatment Outcome , United States/epidemiology
15.
Clin Epidemiol ; 16: 267-279, 2024.
Article in English | MEDLINE | ID: mdl-38645475

ABSTRACT

Background: High risk of intracranial hemorrhage (ICH) is a leading reason for withholding anticoagulation in patients with atrial fibrillation (AF). We aimed to develop a claims-based ICH risk prediction model in older adults with AF initiating oral anticoagulation (OAC). Methods: We used US Medicare claims data to identify new users of OAC aged ≥65 years with AF in 2010-2017. We used regularized Cox regression to select predictors of ICH. We compared our AF ICH risk score with the HAS-BLED bleed risk and Homer fall risk scores by area under the receiver operating characteristic curve (AUC) and assessed net reclassification improvement (NRI) when predicting 1-year risk of ICH. Results: Our study cohort comprised 840,020 patients (mean [SD] age 77.5 [7.4] years and female 52.2%) split geographically into training (3963 ICH events [0.6%] in 629,804 patients) and validation (1397 ICH events [0.7%] in 210,216 patients) sets. Our AF ICH risk score, including 50 predictors, had superior AUCs of 0.653 and 0.650 in the training and validation sets than the HAS-BLED score of 0.580 and 0.567 (p<0.001) and the Homer score of 0.624 and 0.623 (p<0.001). In the validation set, our AF ICH risk score reclassified 57.8%, 42.5%, and 43.9% of low, intermediate, and high-risk patients, respectively, by HAS-BLED score (NRI: 15.3%, p<0.001). Similarly, it reclassified 0.0, 44.1, and 19.4% of low, intermediate, and high-risk patients, respectively, by the Homer score (NRI: 21.9%, p<0.001). Conclusion: Our novel claims-based ICH risk prediction model outperformed the standard HAS-BLED score and can inform OAC prescribing decisions.

16.
NPJ Digit Med ; 7(1): 39, 2024 Feb 19.
Article in English | MEDLINE | ID: mdl-38374424

ABSTRACT

Text messaging can promote healthy behaviors, like adherence to medication, yet its effectiveness remains modest, in part because message content is rarely personalized. Reinforcement learning has been used in consumer technology to personalize content but with limited application in healthcare. We tested a reinforcement learning program that identifies individual responsiveness ("adherence") to text message content and personalizes messaging accordingly. We randomized 60 individuals with diabetes and glycated hemoglobin A1c [HbA1c] ≥ 7.5% to reinforcement learning intervention or control (no messages). Both arms received electronic pill bottles to measure adherence. The intervention improved absolute adjusted adherence by 13.6% (95%CI: 1.7%-27.1%) versus control and was more effective in patients with HbA1c 7.5- < 9.0% (36.6%, 95%CI: 25.1%-48.2%, interaction p < 0.001). We also explored whether individual patient characteristics were associated with differential response to tested behavioral factors and unique clusters of responsiveness. Reinforcement learning may be a promising approach to improve adherence and personalize communication at scale.

17.
PLoS One ; 18(7): e0287985, 2023.
Article in English | MEDLINE | ID: mdl-37410777

ABSTRACT

BACKGROUND: To determine the impact of electronic health record (EHR)-discontinuity on the performance of prediction models. METHODS: 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). RESULTS: 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. CONCLUSIONS: 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.


Subject(s)
Electronic Health Records , Medicare , Humans , Aged , United States/epidemiology , Machine Learning , Heart , Algorithms
18.
JAMA Netw Open ; 6(2): e230063, 2023 02 01.
Article in English | MEDLINE | ID: mdl-36800180

ABSTRACT

Importance: There are limited data on discontinuation rates of antipsychotic medications (APMs) used to treat delirium due to acute hospitalization in the routine care of older adults. Objective: To investigate discontinuation rates and patient characteristics of APMs used to treat delirium following infection-related hospitalization among older US adults. Design, Setting, and Participants: This retrospective cohort study was conducted using US claims data (Optum's deidentified Clinformatics Data Mart database) for January 1, 2004, to May 31, 2022. Patients were aged 65 years or older without prior psychiatric disorders and had newly initiated an APM prescription within 30 days of an infection-related hospitalization. Statistical analysis was performed on December 15, 2022. Exposures: New use (no prior use any time before cohort entry) of oral haloperidol and atypical APMs (aripiprazole, olanzapine, quetiapine, risperidone, etc). Main Outcomes and Measures: The primary outcome was APM discontinuation, defined as a gap of more than 15 days following the end of an APM dispensing. Survival analyses and Kaplan-Meier analyses were used. Results: Our study population included 5835 patients. Of these individuals, 790 (13.5%) were new haloperidol users (mean [SD] age, 81.5 [6.7] years; 422 women [53.4%]) and 5045 (86.5%) were new atypical APM users (mean [SD] age, 79.8 [7.0] years; 2636 women [52.2%]). The cumulative incidence of discontinuation by 30 days after initiation was 11.4% (95% CI, 10.4%-12.3%) among atypical APM users and 52.1% (95% CI, 48.2%-55.7%) among haloperidol users (P < .001 for difference between haloperidol vs atypical APMs). We observed an increasing trend in discontinuation rates from 2004 to 2022 (5% increase [95% CI, 3%-7%] per year) for haloperidol users (adjusted hazard ratio, 1.05 [1.03-1.07]; P < .001) but not for atypical APM users (1.00 [0.99-1.01]; P = .67). Prolonged hospitalization and dementia were inversely associated with the discontinuation of haloperidol and atypical APMs. Conclusions and Relevance: The findings of this cohort study suggest that the discontinuation rate of newly initiated APMs for delirium following infection-related hospitalization was lower in atypical APM users than in haloperidol users, with prolonged hospitalization and dementia as major associated variables. The discontinuation rate was substantially higher in recent years for haloperidol but not for atypical APMs.


Subject(s)
Antipsychotic Agents , Delirium , Dementia , Humans , Female , Adult , Middle Aged , Aged , Aged, 80 and over , Antipsychotic Agents/therapeutic use , Haloperidol/therapeutic use , Cohort Studies , Retrospective Studies , Hospitalization , Dementia/drug therapy , Delirium/drug therapy , Delirium/epidemiology
19.
Am J Cardiol ; 207: 245-252, 2023 11 15.
Article in English | MEDLINE | ID: mdl-37757521

ABSTRACT

Choosing optimal P2Y12 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 P2Y12 inhibitors and multivariable-adjusted competing risk analyses to compare the rate of discontinuation of potent P2Y12 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 P2Y12 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 P2Y12 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 P2Y12 inhibitors after percutaneous coronary intervention-treated ST-elevation myocardial infarction, but they are as likely as non-frail patients to continue with the prescribed P2Y12 inhibitor.


Subject(s)
Frailty , Percutaneous Coronary Intervention , ST Elevation Myocardial Infarction , Humans , Female , Aged , United States/epidemiology , Male , Clopidogrel/therapeutic use , Ticagrelor/therapeutic use , Platelet Aggregation Inhibitors/therapeutic use , Purinergic P2Y Receptor Antagonists/therapeutic use , ST Elevation Myocardial Infarction/drug therapy , ST Elevation Myocardial Infarction/etiology , Frailty/epidemiology , Frailty/etiology , Retrospective Studies , Medicare , Prasugrel Hydrochloride , Percutaneous Coronary Intervention/adverse effects , Treatment Outcome
20.
J Am Geriatr Soc ; 71(10): 3179-3188, 2023 10.
Article in English | MEDLINE | ID: mdl-37354026

ABSTRACT

BACKGROUND: Among older adults, non-cardiovascular multimorbidity often coexists with cardiovascular disease (CVD) but their clinical significance is uncertain. We identified common non-cardiovascular comorbidity patterns and their association with clinical outcomes in Medicare fee-for-service beneficiaries with acute myocardial infarction (AMI), congestive heart failure (CHF), or atrial fibrillation (AF). METHODS: Using 2015-2016 Medicare data, we took 1% random sample to create 3 cohorts of beneficiaries diagnosed with AMI (n = 24,808), CHF (n = 57,285), and AF (n = 36,277) prior to 1/1/2016. Within each cohort, we applied latent class analysis to classify beneficiaries based on 9 non-cardiovascular comorbidities (anemia, cancer, chronic kidney disease, chronic lung disease, dementia, depression, diabetes, hypothyroidism, and musculoskeletal disease). Mortality, cardiovascular and non-cardiovascular hospitalizations, and home time lost over a 1-year follow-up period were compared across non-cardiovascular multimorbidity classes. RESULTS: Similar non-cardiovascular multimorbidity classes emerged from the 3 CVD cohorts: (1) minimal, (2) depression-lung, (3) chronic kidney disease (CKD)-diabetes, and (4) multi-system class. Across CVD cohorts, multi-system class had the highest risk of mortality (hazard ratio [HR], 2.7-3.9), cardiovascular hospitalization (HR, 1.6-3.3), non-cardiovascular hospitalization (HR, 3.1-7.2), and home time lost (rate ratio, 2.7-5.4). Among those with AMI, the CKD-diabetes class was more strongly associated with all the adverse outcomes than the depression-lung class. In CHF and AF, differences in risk between the depression-lung and CKD-diabetes classes varied per outcome; and the depression-lung and multi-system classes had double the rates of non-cardiovascular hospitalizations than cardiovascular hospitalizations. CONCLUSION: Four non-cardiovascular multimorbidity patterns were found among Medicare beneficiaries with CHF, AMI, or AF. Compared to the minimal class, the multi-system, CKD-diabetes, and depression-lung classes were associated with worse outcomes. Identification of these classes offers insight into specific segments of the population that may benefit from more than the usual cardiovascular care.


Subject(s)
Atrial Fibrillation , Cardiovascular Diseases , Diabetes Mellitus , Heart Failure , Myocardial Infarction , Renal Insufficiency, Chronic , Humans , Aged , United States/epidemiology , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/complications , Multimorbidity , Medicare , Heart Failure/epidemiology , Heart Failure/therapy , Heart Failure/complications , Atrial Fibrillation/epidemiology , Diabetes Mellitus/epidemiology , Renal Insufficiency, Chronic/epidemiology , Renal Insufficiency, Chronic/therapy , Renal Insufficiency, Chronic/complications , Lung
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