Patient Characteristics Associated With Using Transcatheter Left Atrial Appendage Occlusion Versus Oral Anticoagulants for Atrial Fibrillation.

BACKGROUND: Transcatheter left atrial appendage occlusion (LAAO) is an alternative to oral anticoagulants (OACs) for stroke prevention in patients with atrial fibrillation, but the predictors of LAAO use in routine care are unclear. We aimed to assess the utilization trends of LAAO and compare the change in characteristics of LAAO users versus OACs since its marketing. METHODS: Using the US Medicare claims database (March 15, 2015, to December 31, 2020), we identified patients with atrial fibrillation, ≥65 years, and CHA2DS2-VASc score ≥2 (men) or ≥3 (women), with either first implantation of an LAAO device or initiation of OACs, including apixaban, dabigatran, rivaroxaban, edoxaban, or warfarin. Patient characteristics, measured 365 days before the first LAAO or OAC use date, were compared using logistic regression. RESULTS: There were 30 058 LAAO recipients (mean age, 77.74 years; female, 42.1%) and 792 600 OAC initiators (mean age, 78.48; female, 53.3%). In 2020, patients had higher odds of initiating LAAO use than in 2015 (0.52 versus 9.32%; adjusted odds ratio [aOR], 13.64 [95% CI, 12.56-14.81]). Old age (ie, >85 versus 65-75 years; aOR, 0.84 [95% CI, 0.80-0.88]), female sex (aOR, 0.74 [95% CI, 0.71-0.76]), Black race (aOR, 0.63 [95% CI, 0.58-0.68]) versus White race, and Medicaid eligibility (aOR, 0.61 [95% CI, 0.58-0.64]) were associated with lower odds of receiving LAAO. Among clinical characteristics, frailty, cancer, fractures, and venous thromboembolism were associated with lower odds of LAAO use, while history of intracranial and extracranial bleeding, coagulopathy, and falls were associated with higher odds of receiving LAAO. CONCLUSIONS: Among patients with atrial fibrillation receiving stroke-preventive therapy, LAAO use increased rapidly from 2015 to 2020 and was positively associated with the risk factors for OAC complications but negatively associated with old age, advanced frailty, and cancer. Black race and female sex were associated with a lower likelihood of receiving LAAO.

Identifying Functional Status Impairment in People Living With Dementia Through Natural Language Processing of Clinical Documents: Cross-Sectional Study.

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.

Development and Validation of a Claims-Based Model to Predict Categories of Obesity.

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.

Comparative Safety and Effectiveness of Warfarin or Rivaroxaban Versus Apixaban in Patients With Advanced CKD and Atrial Fibrillation: Nationwide US Cohort Study.

RATIONALE & OBJECTIVE: Head-to-head data comparing the effectiveness and safety of oral anticoagulants in patients with atrial fibrillation (AF) and advanced chronic kidney disease (CKD) are lacking. We compared the safety and effectiveness of warfarin or rivaroxaban versus apixaban in patients with AF and non-dialysis-dependent CKD stage 4/5. STUDY DESIGN: Propensity score-matched cohort study. SETTING & PARTICIPANTS: 2 nationwide US claims databases, Medicare and Optum's deidentified Clinformatics Data Mart Database, were searched for the interval from January 1, 2013, through March 31, 2022, for patients with nonvalvular AF and CKD stage 4/5 who initiated warfarin versus apixaban (matched cohort, n=12,488) and rivaroxaban versus apixaban (matched cohort, n = 5,720). EXPOSURES: Warfarin, rivaroxaban, or apixaban. OUTCOMES: Primary outcomes included major bleeding and ischemic stroke. Secondary outcomes included all-cause mortality, major gastrointestinal bleeding, and intracranial bleeding. ANALYTICAL APPROACH: Cox regression was used to estimate HRs, and 1:1 propensity-score matching was used to adjust for 80 potential confounders. RESULTS: Compared with apixaban, warfarin initiation was associated with a higher rate of major bleeding (HR, 1.85; 95% CI, 1.59-2.15), including major gastrointestinal bleeding (1.86; 1.53-2.25) and intracranial bleeding (2.15; 1.42-3.25). Compared with apixaban, rivaroxaban was also associated with a higher rate of major bleeding (1.69; 1.33-2.15). All-cause mortality was similar for warfarin (1.08; 0.98-1.18) and rivaroxaban (0.94; 0.81-1.10) versus apixaban. Furthermore, no statistically significant differences for ischemic stroke were observed for warfarin (1.14; 0.83-1.57) or rivaroxaban (0.71; 0.40-1.24) versus apixaban, but the CIs were wide. Similar results were observed for warfarin versus apixaban in the positive control cohort of patients with CKD stage 3, consistent with randomized trial findings. LIMITATIONS: Few ischemic stroke events, potential residual confounding. CONCLUSIONS: In patients with AF and advanced CKD, rivaroxaban and warfarin were associated with higher rates of major bleeding compared with apixaban, suggesting a superior safety profile for apixaban in this high-risk population. PLAIN-LANGUAGE SUMMARY: Different anticoagulants have been shown to reduce the risk of stroke in patients with atrial fibrillation, such as warfarin and direct oral anticoagulants like apixaban and rivaroxaban. Unfortunately, the large-scale randomized trials that compared direct anticoagulants versus warfarin excluded patients with advanced chronic kidney disease. Therefore, the comparative safety and effectiveness of warfarin, apixaban, and rivaroxaban are uncertain in this population. In this study, we used administrative claims data from the United States to answer this question. We found that warfarin and rivaroxaban were associated with increased risks of major bleeding compared with apixaban. There were few stroke events, with no major differences among the 3 drugs in the risk of stroke. In conclusion, this study suggests that apixaban has a better safety profile than warfarin and rivaroxaban.

A population-based cohort defined risk of hyperkalemia after initiating SGLT-2 inhibitors, GLP1 receptor agonists or DPP-4 inhibitors to patients with chronic kidney disease and type 2 diabetes.

Hyperkalemia is a common adverse event in patients with chronic kidney disease (CKD) and type 2 diabetes and limits the use of guideline-recommended therapies such as renin-angiotensin system inhibitors. Here, we evaluated the comparative effects of sodium-glucose cotransporter-2 inhibitors (SGLT-2i), glucagon-like peptide-1 receptor agonists (GLP-1RA) and dipeptidyl peptidase-4 inhibitors (DPP-4i) on the risk of hyperkalemia. We conducted a population-based active-comparator, new-user cohort study using claims data from Medicare and two large United States commercial insurance databases (April 2013-April 2022). People with CKD stages 3-4 and type 2 diabetes who newly initiated SGLT-2i vs. DPP-4i (141671 patients), GLP-1RA vs. DPP-4i (159545 patients) and SGLT-2i vs. GLP-1RA (93033 patients) were included. The primary outcome was hyperkalemia diagnosed in inpatient or outpatient settings. Secondary outcomes included hyperkalemia diagnosed in inpatient or emergency department setting, and serum potassium levels of 5.5 mmol/L or more. Pooled hazard ratios and rate differences were estimated after propensity score matching to adjust for over 140 potential confounders. Initiation of SGLT-2i was associated with a lower risk of hyperkalemia compared with DPP-4i (hazard ratio 0.74; 95% confidence interval 0.68-0.80) and contrasted to GLP-1RA (0.92; 0.86-0.99). Compared with DPP-4i, GLP-1RA were also associated with a lower risk of hyperkalemia (0.80; 0.75-0.86). Corresponding absolute rate differences/1000 person-years were -24.8 (95% confidence interval -31.8 to -17.7), -5.0 (-10.9 to 0.8), and -17.7 (-23.4 to -12.1), respectively. Similar findings were observed for the secondary outcomes, among subgroups, and across single agents within the SGLT-2i and GLP-1RA classes. Thus, SGLT-2i and GLP-1RA are associated with a lower risk of hyperkalemia than DPP-4i in patients with CKD and type 2 diabetes, further supporting the use of these drugs in this population.

Frailty, Home Time, and Health Care Costs in Older Adults With Atrial Fibrillation Receiving Oral Anticoagulants.

Importance: There are no data on patient-centered outcomes and health care costs by frailty in patients with atrial fibrillation (AF) taking oral anticoagulants (OACs). Objective: To compare home time, clinical events, and health care costs associated with OACs by frailty levels in older adults with AF. Design, Setting, and Participants: This community-based cohort study assessed Medicare fee-for-service beneficiaries 65 years or older with AF from January 1, 2013, to December 31, 2019. Data analysis was performed from January to December 2022. Exposures: Apixaban, rivaroxaban, and warfarin use were measured from prescription claims. Frailty was measured using a validated claims-based frailty index. Main outcomes and measures: Outcome measures were (1) home time (days alive out of the hospital and skilled nursing facility) loss greater than 14 days; (2) a composite end point of ischemic stroke, systemic embolism, major bleeding, or death; and (3) total cost per member per year after propensity score overlap weighting. Results: The weighted population comprised 136 551 beneficiaries, including 45 950 taking apixaban (mean [SD] age, 77.6 [7.3] years; 51.3% female), 45 320 taking rivaroxaban (mean [SD] age, 77.6 [7.3] years; 51.9% female), and 45 281 taking warfarin (mean [SD] age, 77.6 [7.3] years; 52.0% female). Compared with apixaban, rivaroxaban was associated with increased risk of home time lost greater than 14 days (risk difference per 100 persons, 1.8 [95% CI, 1.5-2.1]), composite end point (rate difference per 1000 person-years, 21.3 [95% CI, 16.4-26.2]), and total cost (mean difference, $890 [95% CI, $652-$1127]), with greater differences among the beneficiaries with frailty. Use of warfarin relative to apixaban was associated with increased home time lost (risk difference per 100 persons, 3.2 [95% CI, 2.9-3.5]) and composite end point (rate difference per 1000 person-years, 29.4 [95% CI, 24.5-34.3]), with greater differences among the beneficiaries with frailty. Compared with apixaban, warfarin was associated with lower total cost (mean difference, -$1166 [95% CI, -$1396 to -$937]) but higher cost when excluding OAC cost (mean difference, $1409 [95% CI, $1177 to $1642]) regardless of frailty levels. Conclusions and Relevance: In older adults with AF, apixaban was associated with increased home time and lower rates of clinical events than rivaroxaban and warfarin, especially for those with frailty. Apixaban was associated with lower total cost compared with rivaroxaban but higher cost compared with warfarin due to higher OAC cost. These findings suggest that apixaban may be preferred for older adults with AF, particularly those with frailty.

Utilization of P2Y12 Inhibitors in Older Adults With ST-Elevation Myocardial Infarction and Frailty.

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.

Comparison of EHR Data-Completeness in Patients with Different Types of Medical Insurance Coverage in the United States.

Prior studies have demonstrated that misclassification of study variables due to electronic health record (EHR)-discontinuity can be mitigated by restricting EHR-based analyses to subjects with high predicted EHR-continuity based on a simple algorithm. In this study, we compared EHR continuity in populations covered by Medicare, Medicaid, or commercial insurance. Using claims-linked EHRs from a multicenter network in Massachusetts, including Medicare (MA EHR-Medicare cohort) and Medicaid (MA EHR-Medicaid cohort) claims data; and TriNetX (TriNetX cohort) claims-linked EHR data from 11 US-based healthcare organizations, we assessed (1) EHR-continuity quantified by proportion of encounters captured by EHR (capture proportion (CP)); (2) area under receiver operating curve (AUROC) of previously validated model to identify patients with high EHR-continuity (CP ≥ 0.6); (3) misclassification of 40 patient characteristics, quantified by average standardized absolute mean difference (ASAMD). Study participants were ≥ 65 years (Medicare) or ≥ 18 years (Medicaid, TriNetX) with ≥ 365 days of continuous insurance enrollment overlapping with an EHR encounter. We found that the mean CP was 0.30, 0.18, and 0.19 and AUROC of the prediction model to identify patients with high EHR-continuity was 0.92, 0.89, and 0.77 in the MA EHR-Medicare, MA EHR-Medicaid, and TriNetX cohorts, respectively. Restricting to patients with predicted EHR-continuity percentile of top 20%, 50%, and 50% in MA EHR-Medicare, MA EHR-Medicaid, and TriNetX cohorts resulted in acceptable levels of misclassification (ASAMD < 0.1). Using a prediction model to identify cohorts with high EHR-continuity can improve validity, but cutoffs to achieve this goal vary by population.

Claims-Based Frailty Index as a Measure of Dementia Severity in Medicare Claims Data.

BACKGROUND: Dementia severity is unavailable in administrative claims data. We examined whether a claims-based frailty index (CFI) can measure dementia severity in Medicare claims. METHODS: This cross-sectional study included the National Health and Aging Trends Study Round 5 participants with possible or probable dementia whose Medicare claims were available. We estimated the Functional Assessment Staging Test (FAST) scale (range: 3 [mild cognitive impairment] to 7 [severe dementia]) using information from the survey. We calculated CFI (range: 0-1, higher scores indicating greater frailty) using Medicare claims 12 months prior to the participants' interview date. We examined C-statistics to evaluate the ability of the CFI in identifying moderate-to-severe dementia (FAST stage 5-7) and determined the optimal CFI cut-point that maximized both sensitivity and specificity. RESULTS: Of the 814 participants with possible or probable dementia and measurable CFI, 686 (72.2%) patients were ≥75 years old, 448 (50.8%) were female, and 244 (25.9%) had FAST stage 5-7. The C-statistic of CFI to identify FAST stage 5-7 was 0.78 (95% confidence interval: 0.72-0.83), with a CFI cut-point of 0.280, achieving the maximum sensitivity of 76.9% and specificity of 62.8%. Participants with CFI ≥0.280 had a higher prevalence of disability (19.4% vs 58.3%) and dementia medication use (6.0% vs 22.8%) and higher risk of mortality (10.7% vs 26.3%) and nursing home admission (4.5% vs 10.6%) over 2 years than those with CFI <0.280. CONCLUSIONS: Our study suggests that CFI can be useful in identifying moderate-to-severe dementia from administrative claims among older adults with dementia.

The impact of electronic health record discontinuity on prediction modeling.

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.

Common non-cardiovascular multimorbidity groupings and clinical outcomes in older adults with major cardiovascular disease.

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.

Outcomes for patients with dementia undergoing emergency and elective colorectal surgery: A large multi-institutional comparative cohort study.

BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: The diagnosis of ADRD is an independent risk factor for prolonged hospitalization and postoperative complications after colorectal surgery.

The Impact of Longitudinal Data-Completeness of Electronic Health Record Data on the Prediction Performance of Clinical Risk Scores.

The impact of electronic health record (EHR) discontinuity (i.e., receiving care outside of a given EHR system) on EHR-based risk prediction is unknown. We aimed to assess the impact of EHR-continuity on the performance of clinical risk scores. The study cohort consisted of patients aged ≥ 65 years with ≥ 1 EHR encounter in the 2 networks in Massachusetts (MA; 2007/1/1-2017/12/31, internal training and validation dataset), and one network in North Carolina (NC; 2007/1/1-2016/12/31, external validation dataset) that were linked with Medicare claims data. Risk scores were calculated using EHR data alone vs. linked EHR-claims data (not subject to misclassification due to EHR-discontinuity): (i) combined comorbidity score (CCS), (ii) claim-based frailty score (CFI), (iii) CHAD2 DS2 -VASc, and (iv) Hypertension, Abnormal renal/liver function, Stroke, Bleeding, Labile, Elderly, and Drugs (HAS-BLED). We assessed the performance of CCS and CFI predicting death, CHAD2 DS2 -VASc predicting ischemic stroke, and HAS-BLED predicting bleeding by area under receiver operating characteristic curve (AUROC), stratified by quartiles of predicted EHR-continuity (Q1-4). There were 319,740 patients in the MA systems and 125,380 in the NC system. In the external validation dataset, AUROC for EHR-based CCS predicting 1-year risk of death was 0.583 in Q1 (lowest) EHR-continuity group, which increased to 0.739 in Q4 (highest) EHR-continuity group. The corresponding improvement in AUROC was 0.539 to 0.647 for CFI, 0.556 to 0.637 for CHAD2 DS2 -VASc, and 0.517 to 0.556 for HAS-BLED. The AUROC in Q4 EHR-continuity group based on EHR alone approximates that based on EHR-claims data. The prediction performance of four clinical risk scores was substantially worse in patients with lower vs. high EHR-continuity.

Comparative Effectiveness and Safety of Oral Anticoagulants by Dementia Status in Older Patients With Atrial Fibrillation.

Importance: The development of an optimal stroke prevention strategy, including the use of oral anticoagulant (OAC) therapy, is particularly important for patients with atrial fibrillation (AF) who are living with dementia, a condition that increases the risk of adverse outcomes. However, data on the role of dementia in the safety and effectiveness of OACs are limited. Objective: To assess the comparative safety and effectiveness of specific OACs by dementia status among older patients with AF. Design, Setting, and Participants: This retrospective comparative effectiveness study used 1:1 propensity score matching among 1 160 462 patients 65 years or older with AF. Data were obtained from the Optum Clinformatics Data Mart (January 1, 2013, to June 30, 2021), IBM MarketScan Research Database (January 1, 2013, to December 31, 2020), and Medicare claims databases maintained by the Centers for Medicare & Medicaid Services (inpatient, outpatient, and pharmacy; January 1, 2013, to December 31, 2017). Data analysis was performed from September 1, 2021, to May 24, 2022. Exposures: Apixaban, dabigatran, rivaroxaban, or warfarin. Main Outcomes and Measures: Composite end point of ischemic stroke or major bleeding events over the 6-month period after OAC initiation, pooled across databases using random-effects meta-analyses. Results: Among 1 160 462 patients with AF, the mean (SD) age was 77.4 (7.2) years; 50.2% were male, 80.5% were White, and 7.9% had dementia. Three comparative new-user cohorts were established: warfarin vs apixaban (501 990 patients; mean [SD] age, 78.1 [7.4] years; 50.2% female), dabigatran vs apixaban (126 718 patients; mean [SD] age, 76.5 [7.1] years; 52.0% male), and rivaroxaban vs apixaban (531 754 patients; mean [SD] age, 76.9 [7.2] years; 50.2% male). Among patients with dementia, compared with apixaban users, a higher rate of the composite end point was observed in warfarin users (95.7 events per 1000 person-years [PYs] vs 64.2 events per 1000 PYs; adjusted hazard ratio [aHR], 1.5; 95% CI, 1.3-1.7), dabigatran users (84.5 events per 1000 PYs vs 54.9 events per 1000 PYs; aHR, 1.5; 95% CI, 1.2-2.0), and rivaroxaban users (87.4 events per 1000 PYs vs 68.5 events per 1000 PYs; aHR, 1.3; 95% CI, 1.1-1.5). In all 3 comparisons, the magnitude of the benefits associated with apixaban was similar regardless of dementia diagnosis on the HR scale but differed substantially on the rate difference (RD) scale. The adjusted RD of the composite outcome per 1000 PYs for warfarin vs apixaban users was 29.8 (95% CI, 18.4-41.1) events in patients with dementia vs 16.0 (95% CI, 13.6-18.4) events in patients without dementia. The corresponding adjusted RD estimates of the composite outcome were 29.6 (95% CI, 11.6-47.6) events per 1000 PYs in patients with dementia vs 5.8 (95% CI, 1.1-10.4) events per 1000 PYs in patients without dementia for dabigatran vs apixaban users and 20.5 (95% CI, 9.9-31.1) events per 1000 PYs in patients with dementia vs 15.9 (95% CI, 11.4-20.3) events per 1000 PYs in patients without dementia for rivaroxaban vs apixaban users. The pattern was more distinct for major bleeding than for ischemic stroke. Conclusions and Relevance: In this comparative effectiveness study, apixaban was associated with lower rates of major bleeding and ischemic stroke compared with other OACs. The increased absolute risks associated with other OACs compared with apixaban were greater among patients with dementia than those without dementia, particularly for major bleeding. These findings support the use of apixaban for anticoagulation therapy in patients living with dementia who have AF.

Scalable Feature Engineering from Electronic Free Text Notes to Supplement Confounding Adjustment of Claims-Based Pharmacoepidemiologic Studies.

Natural language processing (NLP) tools turn free-text notes (FTNs) from electronic health records (EHRs) into data features that can supplement confounding adjustment in pharmacoepidemiologic studies. However, current applications are difficult to scale. We used unsupervised NLP to generate high-dimensional feature spaces from FTNs to improve prediction of drug exposure and outcomes compared with claims-based analyses. We linked Medicare claims with EHR data to generate three cohort studies comparing different classes of medications on the risk of various clinical outcomes. We used "bag-of-words" to generate features for the top 20,000 most prevalent terms from FTNs. We compared machine learning (ML) prediction algorithms using different sets of candidate predictors: Set1 (39 researcher-specified variables), Set2 (Set1 + ML-selected claims codes), and Set3 (Set1 + ML-selected NLP-generated features), vs. Set4 (Set1 + 2 + 3). When modeling treatment choice, we observed a consistent pattern across the examples: ML models utilizing Set4 performed best followed by Set2, Set3, then Set1. When modeling the outcome risk, there was little to no improvement beyond models based on Set1. Supplementing claims data with NLP-generated features from free text notes improved prediction of prescribing choices but had little or no improvement on clinical risk prediction. These findings have implications for strategies to improve confounding using EHR data in pharmacoepidemiologic studies.

Trends in Use of Oral Anticoagulants in Older Adults With Newly Diagnosed Atrial Fibrillation, 2010-2020.

Importance: Undertreatment of older adults with atrial fibrillation with anticoagulation therapy is an important practice gap. It has been posited that the availability of direct oral anticoagulants (DOACs) would improve oral anticoagulant (OAC) initiation in older adults with atrial fibrillation given their superior safety profile compared with warfarin. Objectives: To systematically examine trends in OAC initiation and nonadherence in older adults with atrial fibrillation and coexisting geriatric conditions. Design, Setting, and Participants: This retrospective cohort study uses administrative claims data from Optum's Clinformatics Data Mart from January 1, 2010, to December 31, 2020. Participants included beneficiaries of Medicare Advantage plans aged 65 years and older with atrial fibrillation and elevated risk of ischemic stroke. Data analysis was performed from October 2021 to October 2022. Exposures: Coexisting dementia, frailty, and anemia. Main Outcomes and Measures: The primary outcomes were OAC initiation within 12 months after the first diagnosis of atrial fibrillation per year and nonadherence with OAC per year (defined as <80% of proportion of days covered among patients newly started on OAC in each year). Results: There were 21 603 to 51 236 patients per year (total for 2010-2020, 381 488 patients) in the OAC-eligible incident AF cohort (mean [SD] age, 77.2 [6.1] to 77.4 [6.8] years; 13 871 [51.8%] to 22 901 [49.8%] women). OAC initiation within 12 months after incident AF increased from 20.2% (5405 of 26 782 patients) in 2010 to 32.9% (7111 of 21 603 patients) in 2020. DOAC uptake increased from 1.1% (291 of 26 782 patients) to 30.9% (6678 of 21 603 patients), and warfarin initiation decreased from 19.1% (5114 of 26 782 patients) to 2.0% (436 of 21 603 patients). Older age (odds ratio [OR], 0.98; 95% CI, 0.98-0.98), dementia (OR, 0.57; 95% CI, 0.55-0.58), frailty (OR, 0.74; 95% CI, 0.72-0.76), and anemia (OR, 0.75; 95% CI, 0.74-0.77) were associated with lower odds of OAC initiation. During the study period, the median (IQR) proportion of days covered increased from 77.6% (41.0%-96.4%) to 90.2% (57.4%-98.6%), and OAC nonadherence decreased from 52.2% (2290 of 4389 patients) to 39.0% (3434 of 8798 patients). Conclusions and Relevance: Since the introduction of DOACs, OAC initiation in older adults with has improved but remained suboptimal in 2020. Additional strategies are needed to improve stroke prophylaxis in all older adults with atrial fibrillation including those with coexisting dementia, frailty, and anemia.

An algorithm to predict data completeness in oncology electronic medical records for comparative effectiveness research.

INTRODUCTION: Electronic health record (EHR) discontinuity (missing out-of-network encounters) can lead to information bias. We sought to construct an algorithm that identifies high EHR-continuity among oncology patients. METHODS: Using a linked Medicare-EHR database and regression, we sought to 1) measure how often Medicare claims for outpatient encounters were substantiated by visits recorded in the EHR, and 2) predict continuity ratio, defined as the yearly proportion of outpatient encounters reported to Medicare that were captured by EHR data. The prediction model...s performance was evaluated with the coefficient of determination and Spearman...s correlation. We quantified variable misclassification by decile of continuity ratio using standardized difference and sensitivity. RESULTS: A total of 79,678 subjects met all eligibility criteria. Predicted and observed continuity was highly correlated (σSpearman=0.86). On average across all variables measured, MSD was reduced by a factor of 1/7th and sensitivity was improved 35-fold comparing subjects in the highest vs. lowest decile of CR. CONCLUSION: In the oncology population, restricting EHR-based study cohorts to subjects with high continuity may reduce misclassification without greatly impacting representativeness. Further work is needed to elucidate the best manner of implementing continuity prediction rules in cohort studies.

Patients living with dementia have worse outcomes when undergoing high-risk procedures.

BACKGROUND: Patients with Alzheimer's Disease and Related Dementias (ADRD) undergoing inpatient procedures represent a population at elevated risk for adverse outcomes including postoperative complications, mortality, and discharge to a higher level of care. Outcomes may be particularly poor in patients with ADRD undergoing high-risk procedures. We sought to determine traditional (e.g., 30-day mortality) and patient-centered (e.g., discharge disposition) outcomes in patients with ADRD undergoing high-risk inpatient procedures. METHODS: This retrospective cohort study analyzed electronic health records linked to fee-for-service Medicare claims data at a tertiary care academic health system. All patients from a large multi-hospital health system undergoing high-risk inpatient procedures from October 1, 2015 to September 30, 2017 with continuous Medicare Parts A and B enrollment in the 12 months prior to and 90 days following the procedure were included. RESULTS: This study included 6779 patients. 536 (7.9%) had ADRD. A multivariable analysis of outcomes demonstrated higher risks for postoperative complications (OR 1.49, 95% CI 1.23-1.81) and 90-day mortality (OR 1.44 [95% CI 1.09-1.91]) in patients with ADRD compared to those without. Patients with ADRD were more likely to be discharged to a higher level of care (OR 1.70, 95% CI 1.32-2.18) and only 37.3% of patients admitted from home were discharged to home. CONCLUSIONS: Compared to those without ADRD, patients living with ADRD undergoing high-risk procedures have poor traditional and patient-centered outcomes including increased risks for 90-day mortality, postoperative complications, longer hospital lengths of stay, and discharge to a higher level of care. These data may be used by patients, their surrogates, and their physicians to help align surgical decision-making with health care goals.

Impact of longitudinal data-completeness of electronic health record data on risk score misclassification.

BACKGROUND: Electric health record (EHR) discontinuity, that is, receiving care outside of a given EHR system, can lead to substantial information bias. We aimed to determine whether a previously described EHR-continuity prediction model can reduce the misclassification of 4 commonly used risk scores in pharmacoepidemiology. METHODS: The study cohort consists of patients aged ≥ 65 years identified in 2 US EHR systems linked with Medicare claims data from 2007 to 2017. We calculated 4 risk scores, CHAD2DS2-VASc, HAS-BLED, combined comorbidity score (CCS), claims-based frailty index (CFI) based on information recorded in the 365 days before cohort entry, and assessed their misclassification by comparing score values based on EHR data alone versus the linked EHR-claims data. CHAD2DS2-VASc and HAS-BLED were assessed in atrial fibrillation (AF) patients, whereas CCS and CFI were assessed in the general population. RESULTS: Our study cohort included 204 014 patients (26 537 with nonvalvular AF) in system 1 and 115 726 patients (15 529 with nonvalvular AF) in system 2. Comparing the low versus high predicted EHR continuity in system 1, the proportion of patients with misclassification of ≥2 categories improved from 55% to 16% for CHAD2DS2-VASc, from 55% to 12% for HAS-BLED, from 37% to 16% for CCS, and from 10% to 2% for CFI. A similar pattern was found in system 2. CONCLUSIONS: Using a previously described prediction model to identify patients with high EHR continuity may significantly reduce misclassification for the commonly used risk scores in EHR-based comparative studies.

Using a Simple Prescription Gap to Determine Warfarin Discontinuation Can Lead to Substantial Misclassification.

BACKGROUND: Warfarin remains widely used and a key comparator in studies of other direct oral anticoagulants. As longer-than-needed warfarin prescriptions are often provided to allow for dosing adjustments according to international normalized ratios (INRs), the common practice of using a short allowable gap between dispensings to define warfarin discontinuation may lead to substantial misclassification of warfarin exposure. We aimed to quantify such misclassification and determine the optimal algorithm to define warfarin discontinuation. METHODS: We linked Medicare claims data from 2007 to 2014 with a multicenter electronic health records system. The study cohort comprised patients ≥65 years with atrial fibrillation and venous thromboembolism initiating warfarin. We compared results when defining warfarin discontinuation by (1) different gaps (3, 7, 14, 30, and 60 days) between dispensings and (2) having a gap ≤60 days or bridging larger gaps if there was INR ordering at least every 42 days (60_INR). Discontinuation was considered misclassified if there was an INR ≥2 within 7 days after the discontinuation date. RESULTS: Among 3,229 patients, a shorter gap resulted in a shorter mean follow-up time (82, 95, 117, 159, 196, and 259 days for gaps of 3, 7, 14, 30, 60, and 60_INR, respectively; p < 0.001). Incorporating INR (60_INR) can reduce misclassification of warfarin discontinuation from 68 to 4% (p < 0.001). The on-treatment risk estimation of clinical endpoints varied significantly by discontinuation definitions. CONCLUSION: Using a short gap between warfarin dispensings to define discontinuation may lead to substantial misclassification, which can be improved by incorporating intervening INR codes.