Jodi B. Segal

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Background: Patients with non-dialysis-dependent chronic kidney disease (NDD-CKD) develop progressive symptoms which impact quality of life. We distributed the Kidney Disease Symptom Survey (KDSS), an electronic patient-reported outcome measure (PROM), partially based on the Kidney Disease Quality of Life 36 (KDQoL-36) instrument, to patients with NDD-CKD. We aimed to evaluate the measurement properties of the KDSS when used in usual clinical care. Methods: We conducted a retrospective analysis of electronic health record (EHR) data for patients with NDD-CKD who completed the KDSS as part of their routine nephrology care. We evaluated temporal stability of KDSS scores for individuals with stable kidney function, responsiveness of KDSS scores for individuals with worsening kidney function, and convergent construct validity of the KDSS with Medicare Annual Wellness Visit (AWV) assessments of patient-reported outcomes. Results: Among 147 patients with stable NDD-CKD, there were strong correlations between sequential KDSS assessments of general health [Spearman’s rank correlation (rho) 0.76], QoL (rho 0.63), physical symptoms (rho 0.74), and mental health (rho 0.71). For 35 individuals with worsening kidney function, the KDSS detecting a clinically important difference in physical symptom and mental health scores in ∼40% of respondents. There were moderate to strong correlations between KDSS and AWV assessments of general health (rho 0.64) and depressive symptoms (rho 0.50). Conclusions: When used by diverse individuals with NDD-CKD, the KDSS had temporal stability for patients with stable kidney function, as well as moderate convergent construct validity for measuring general health and depressive symptoms. Responsiveness of the KDSS for physical symptoms and mental health was seen in only some individuals with kidney disease. Additional data demonstrating responsiveness to changes in kidney function, as well as interventions such as symptom management strategies, are needed to determine the clinical utility of the KDSS when used in usual care of patients with NDD-CKD.

Background: While apixaban has demonstrated advantages over alternative direct oral anticoagulants (DOACs) in some settings, its comparative safety and effectiveness in cancer-associated venous thromboembolism (VTE) remain uncertain. Current guidelines recommend DOACs as first-line treatment for cancer-associated VTE, though they do not recommend any specific DOAC over another. This study aimed to quantify the risk of recurrent VTE, major bleeding, and clinically relevant non-major bleeding among individuals with cancer-associated VTE treated with apixaban versus rivaroxaban. Methods and findings: In this retrospective cohort study, we used data from Medicare fee-for-service (2016–2020) and MarketScan (2016–2022), two U.S. administrative claims databases covering publicly and commercially insured individuals. We included individuals aged ≥65 years (Medicare) or 18–64 years (MarketScan) with active cancer, defined as a cancer diagnosis within 6 months before an index VTE event, who newly initiated apixaban or rivaroxaban within 30 days of that event. The outcomes were (1) hospitalization for recurrent VTE; (2) hospitalization for major bleeding; and (3) hospitalization or outpatient visit for clinically relevant non-major bleeding events. Eligible individuals were followed for outcomes at 6 months (consistent with guideline recommendations) and during the entire follow-up period. We used inverse probability of treatment weighting to adjust for baseline differences, including demographics, comorbidities (e.g., prior bleed), VTE risk factors, cancer type and treatments, and medication use, and applied inverse probability of censoring weighting to account for differential loss to follow-up. We analyzed outcomes using adjusted Cox proportional hazards models, pooling estimates using an inverse variance-weighted fixed-effects model. The final cohort included 6,329 apixaban and 4,260 rivaroxaban users across both databases. At 6 months, apixaban was associated with similar risks of recurrent VTE (hazard ratio [HR] 0.66, 95% confidence interval [CI] [0.40, 1.11]; p-value = 0.11) and major bleeding (HR 0.95, 95% CI [0.73, 1.23]; p = 0.70), and a lower risk of clinically relevant non-major bleeding (HR 0.84, 95% CI [0.74, 0.96]; p = 0.009) compared to rivaroxaban. The same pattern persisted during the extended follow‑up. The main limitation is the observational design, which may leave residual confounding despite adjustments using inverse probability weighting. Conclusions: In cancer-associated VTE, apixaban was associated with similar risks of recurrent VTE and major bleeding, and a lower risk of clinically relevant non-major bleeding compared with rivaroxaban. These findings suggest apixaban may be a favorable option for anticoagulation in cancer-associated VTE when minimizing bleeding risk is a priority.

Objective: To test the impact of virtual care usage on quality metrics used for performance measurement. Background: Virtual care improves access to primary care; however, the quality of care must not be adversely impacted by its use. Methods: This is a mixed-design etiologic study using data from patients receiving primary care in a large, regional health system from January 2020 through December 2021. Eligible patients had at least one primary care contact. Eligible physicians had 10 or more patient contacts. The quartile of virtual visits per physician per month is calculated as the percentage of total visits conducted by phone or video (Q1 is the lowest). Six metrics used for value-based reimbursement were chosen for modeling with generalized linear mixed models. Results: The data included 200,090 patients of 683 physicians in 42 clinics over 24 months. Virtual care usage peaked in April 2020 at 78% and then stabilized at 18%. The blood pressure metric was met in 66% (95% CI: 63%–69%) of physician months in Q1 and 65% (95% CI: 63%–68%) in Q4 (P = 0.003). The hemoglobin A1c metric was met in 73% (95% CI: 70%–76%) of physician months in Q1 and 72% (95% CI: 69%–75%) in Q4, not a significant difference. Breast cancer screening completion and colon cancer screening completion did not differ across virtual care quartiles. Medicare annual wellness visits were completed in 55% (95% CI: 50%–60%) of Q1 physician months and 54% in each of Q2, Q3, and Q4 (P < 0.0001). Conclusions: Some quality metrics were modestly impacted by high virtual primary care usage; the absolute differences in rates were small. This may provide reassurance to physicians and their health systems that telemedicine use may not adversely impact quality metrics.

Background Early identification of a patient with resistant hypertension (RH) enables quickly intensified treatment, short-interval follow-up, or perhaps case management to bring his or her blood pressure under control and reduce the risk of complications. Objective To identify predictors of RH among individuals with newly diagnosed hypertension (HTN), while comparing different prediction models and techniques for managing missing covariates using electronic health records data. Design Risk prediction study in a retrospective cohort. Participants Adult patients with incident HTN treated in any of the primary care clinics of one health system between April 2013 and December 2016. Main Measures Predicted risk of RH at the time of HTN identification and candidate predictors for variable selection in future model development. Key Results Among 26,953 individuals with incident HTN, 613 (2.3%) met criteria for RH after 4.7 months (interquartile range, 1.2–11.3). Variables selected by the least absolute shrinkage and selection operator (LASSO), included baseline systolic blood pressure (SBP) and its missing indicator (a dummy variable created if baseline SBP is absent), use of antihypertensive medication at the time of cohort entry, body mass index, and atherosclerosis risk. The random forest technique achieved the highest area under the curve (AUC) of 0.893 (95% CI, 0.881–0.904) and the best calibration with a calibration slope of 1.01. Complete case analysis is not a valuable option (AUC = 0.625). Conclusions Machine learning techniques and traditional logistic regression exhibited comparable levels of predictive performance after handling the missingness. We suggest that the variables identified by this study may be good candidates for clinical prediction models to alert clinicians to the need for short-interval follow up and more intensive early therapy for HTN.

Aims: There is a paucity of efficient processes for collecting information in a primary care setting to connect patients afflicted with type 2 diabetes to valuable resources. The objective of this research project was to develop a Comprehensive Diabetes Assessment (CDA) instrument which could be used to assess patients’ barriers to best outcomes. Methods: We reviewed published literature and online compilations for validated tools assessing threats to optimal diabetes self-management. We conducted focus groups with patients, clinicians, and service providers who provided feedback on the tools’ appropriateness and feasibility. We aggregated the favored tools and did cognitive testing with patients to assess understanding and affective response to the instrument. Results: Five focus groups involved varied stakeholders in Baltimore, MD and Honolulu, HI. We presented 2 tools assessing knowledge barriers, 3 tools assessing psychological barriers, 4 tools assessing literacy, and 1 numeracy. The final instrument included 6 multi-part items and takes 3 minutes to complete. Cognitive interviewing with 8 patients in Baltimore and 8 in Hawaii confirmed that the instrument is understandable, quick to complete, and is acceptable to patients. Conclusions: Because of the complexity of self-management of diabetes, we suggest that this CDA instrument, plus a social needs assessment, should be administered at least annually and at times of clinical deterioration. We anticipate the instrument will be proven valuable in connecting patients to services from which they will benefit.

Background: Given the absence of guidelines for use of virtual visits for primary care delivery, a framework is needed to inform the most appropriate use of virtual visits. Methods: We conducted in-depth, structured interviews of 18 patients, primary care clinicians, and other select informants. They were asked to discuss optimal, acceptable, and suboptimal uses of telemedicine for delivering care relative to in-person care delivery. The concepts expressed informed our development of a framework about appropriate use of virtual visits. Results: The 103 concepts supported 5 main themes that emerged as a framework: clinical situations which are optimal for in-person care; situations optimal for virtual visits; situations that might be exchangeable between sites; contextual factors favoring in-person care; and contextual factors favoring virtual visits. Conclusions: After further validation, we expect that this framework may guide future research and practice: it may be valuable for clinical practice redesign, for designing evaluations of the outcomes of virtual visits, for outcomes research, for patient education, for triage, and possibly for reimbursement considerations.