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      The Use of Telemedicine by US Nephrologists for In-Center Hemodialysis Care During the Pandemic: An Analysis of National Medicare Claims

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          Abstract

          Rationale & Objective

          Because of coronavirus disease 2019 (COVID-19), the US government issued emergency waivers in March 2020 that removed regulatory barriers around the use of telemedicine. For the first time, nephrologists were reimbursed for telemedicine care delivered during in-center hemodialysis. We examined the use of telemedicine for in-center hemodialysis during the first 16 months of the pandemic.

          Study Design

          We ascertained telemedicine modifiers on nephrologist claims. We used multivariable regression to examine time trends and patient, dialysis facility, and geographic correlates of telemedicine use. We also examined whether the estimated effects of predictors of telemedicine use changed over time.

          Setting & Participants

          US Medicare beneficiaries receiving in-center hemodialysis between March 1, 2020, and June 30, 2021.

          Exposu res

          Patient, geographic, and dialysis facility characteristics.

          Outcomes

          The use of telehealth for in-center hemodialysis care.

          Analytic Approach

          Retrospective cohort analysis.

          Results

          Among 267,434 Medicare beneficiaries identified, the reported use of telemedicine peaked at 9% of patient-months in April 2020 and declined to 2% of patient-months by June 2021. Telemedicine use varied geographically and was more common in areas that were remote and socioeconomically disadvantaged. Patients were more likely to receive care by telemedicine in areas with higher incidence of COVID-19, although the predictive value of COVID-19 diminished later in the pandemic. Patients were more likely to receive care using telemedicine if they were at facilities with more staff, and the use of telemedicine varied by facility ownership type.

          Limitations

          Limited reporting of telemedicine on claims could lead to underestimation of its use. Reported telemedicine use was higher in an analysis designed to address this limitation by focusing on patients whose physicians used telemedicine at least once during the pandemic.

          Conclusions

          Some US nephrologists continued to use telemedicine for in-center hemodialysis throughout the pandemic, even as the association between COVID-19 incidence and telemedicine use diminished over time. These findings highlight unique challenges and opportunities to the future use of telemedicine in dialysis care.

          Plain-Language Summary

          Emergency waivers issued during the coronavirus disease 2019 pandemic enabled reimbursement to US nephrologists for telemedicine care delivered during in-center hemodialysis. Using modifiers from Medicare claims, we examined telemedicine use in the first 16 months of the pandemic. Reported telemedicine use peaked early in the pandemic and declined subsequently. Telemedicine use was more common in areas that were remote and socioeconomically disadvantaged and at facilities with more staff. Telemedicine use also varied by facility ownership type. Some nephrologists continued to use telemedicine for in-center hemodialysis throughout the pandemic, even as the association between coronavirus disease 2019 incidence and telemedicine use diminished over time. These findings highlight unique challenges and opportunities to the future use of telemedicine in dialysis care.

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          Most cited references41

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          Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples

          The propensity score is a subject's probability of treatment, conditional on observed baseline covariates. Conditional on the true propensity score, treated and untreated subjects have similar distributions of observed baseline covariates. Propensity-score matching is a popular method of using the propensity score in the medical literature. Using this approach, matched sets of treated and untreated subjects with similar values of the propensity score are formed. Inferences about treatment effect made using propensity-score matching are valid only if, in the matched sample, treated and untreated subjects have similar distributions of measured baseline covariates. In this paper we discuss the following methods for assessing whether the propensity score model has been correctly specified: comparing means and prevalences of baseline characteristics using standardized differences; ratios comparing the variance of continuous covariates between treated and untreated subjects; comparison of higher order moments and interactions; five-number summaries; and graphical methods such as quantile–quantile plots, side-by-side boxplots, and non-parametric density plots for comparing the distribution of baseline covariates between treatment groups. We describe methods to determine the sampling distribution of the standardized difference when the true standardized difference is equal to zero, thereby allowing one to determine the range of standardized differences that are plausible with the propensity score model having been correctly specified. We highlight the limitations of some previously used methods for assessing the adequacy of the specification of the propensity-score model. In particular, methods based on comparing the distribution of the estimated propensity score between treated and untreated subjects are uninformative. Copyright © 2009 John Wiley & Sons, Ltd.
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            Comorbidity measures for use with administrative data.

            This study attempts to develop a comprehensive set of comorbidity measures for use with large administrative inpatient datasets. The study involved clinical and empirical review of comorbidity measures, development of a framework that attempts to segregate comorbidities from other aspects of the patient's condition, development of a comorbidity algorithm, and testing on heterogeneous and homogeneous patient groups. Data were drawn from all adult, nonmaternal inpatients from 438 acute care hospitals in California in 1992 (n = 1,779,167). Outcome measures were those commonly available in administrative data: length of stay, hospital charges, and in-hospital death. A comprehensive set of 30 comorbidity measures was developed. The comorbidities were associated with substantial increases in length of stay, hospital charges, and mortality both for heterogeneous and homogeneous disease groups. Several comorbidities are described that are important predictors of outcomes, yet commonly are not measured. These include mental disorders, drug and alcohol abuse, obesity, coagulopathy, weight loss, and fluid and electrolyte disorders. The comorbidities had independent effects on outcomes and probably should not be simplified as an index because they affect outcomes differently among different patient groups. The present method addresses some of the limitations of previous measures. It is based on a comprehensive approach to identifying comorbidities and separates them from the primary reason for hospitalization, resulting in an expanded set of comorbidities that easily is applied without further refinement to administrative data for a wide range of diseases.
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              Telehealth and patient satisfaction: a systematic review and narrative analysis

              Background The use of telehealth steadily increases as it has become a viable modality to patient care. Early adopters attempt to use telehealth to deliver high-quality care. Patient satisfaction is a key indicator of how well the telemedicine modality met patient expectations. Objective The objective of this systematic review and narrative analysis is to explore the association of telehealth and patient satisfaction in regards to effectiveness and efficiency. Methods Boolean expressions between keywords created a complex search string. Variations of this string were used in Cumulative Index of Nursing and Allied Health Literature and MEDLINE. Results 2193 articles were filtered and assessed for suitability (n=44). Factors relating to effectiveness and efficiency were identified using consensus. The factors listed most often were improved outcomes (20%), preferred modality (10%), ease of use (9%), low cost 8%), improved communication (8%) and decreased travel time (7%), which in total accounted for 61% of occurrences. Conclusion This review identified a variety of factors of association between telehealth and patient satisfaction. Knowledge of these factors could help implementers to match interventions as solutions to specific problems.
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                Author and article information

                Contributors
                Journal
                Kidney Med
                Kidney Med
                Kidney Medicine
                Elsevier
                2590-0595
                17 February 2024
                April 2024
                17 February 2024
                : 6
                : 4
                : 100798
                Affiliations
                [1 ]Section of Nephrology, Baylor College of Medicine, Houston, Texas
                [2 ]Center for Epidemiology and Population Health, Baylor College of Medicine, Houston, Texas
                [3 ]Division of Renal Diseases and Hypertension, George Washington University, Washington, DC
                [4 ]Division of Nephrology, Stanford University School of Medicine, Palo Alto, California
                [5 ]Baker Institute for Public Policy, Rice University, Houston, Texas
                Author notes
                [] Address for Correspondence: Kevin Erickson, MD, MS, 2002 Holcombe Blvd, Mail Code 152, Houston, TX 77030. kevin.erickson@ 123456bcm.edu
                Article
                S2590-0595(24)00009-8 100798
                10.1016/j.xkme.2024.100798
                11026969
                38645734
                038b8384-735b-4230-bf6c-aba396a9a46c
                © 2024 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                Categories
                Original Research

                covid-19 pandemic,hemodialysis,nephrologist,telemedicine,variation

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