Abstract
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.
Electronic health record (EHR)‐discontinuity, i.e., having medical information recorded outside of the study EHR system, is associated with substantial information bias in EHR‐based comparative ...effectiveness research (CER). We aimed to develop and validate a prediction model identifying patients with high EHR‐continuity to reduce this bias. Based on 183,739 patients aged ≥65 in EHRs from two US provider networks linked with Medicare claims data from 2007–2014, we quantified EHR‐continuity by mean proportion of encounters captured (MPEC) by the EHR system. We built a prediction model for MPEC using one EHR system as training and the other as the validation set. Patients with top 20% predicted EHR‐continuity had 3.5–5.8‐fold smaller misclassification of 40 CER‐relevant variables, compared to the remaining study population. The comorbidity profiles did not differ substantially by predicted EHR‐continuity. These findings suggest that restriction of CER to patients with high predicted EHR‐continuity may confer a favorable validity to generalizability trade‐off.
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.
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) CHAD2DS2‐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, CHAD2DS2‐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 CHAD2DS2‐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.
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.
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.
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;
< 0.001). Incorporating INR (60_INR) can reduce misclassification of warfarin discontinuation from 68 to 4% (
< 0.001). The on-treatment risk estimation of clinical endpoints varied significantly by discontinuation definitions.
Using a short gap between warfarin dispensings to define discontinuation may lead to substantial misclassification, which can be improved by incorporating intervening INR codes.
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.
Propensity score–matched cohort study.
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).
Warfarin, rivaroxaban, or apixaban.
Primary outcomes included major bleeding and ischemic stroke. Secondary outcomes included all-cause mortality, major gastrointestinal bleeding, and intracranial bleeding.
Cox regression was used to estimate HRs, and 1:1 propensity-score matching was used to adjust for 80 potential confounders.
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.
Few ischemic stroke events, potential residual confounding.
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.
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.
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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.
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