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Samaan F, Mendes Á, Carnut L. Privatization and Oligopolies of the Renal Replacement Therapy Sector on Contemporary Capitalism: A Systematic Review and the Brazilian Scenario. CLINICOECONOMICS AND OUTCOMES RESEARCH 2024; 16:417-435. [PMID: 38765895 PMCID: PMC11100955 DOI: 10.2147/ceor.s464120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 05/03/2024] [Indexed: 05/22/2024] Open
Abstract
Worldwide the assistance on renal replacement therapy (RRT) is carried out mainly by private for-profit services and in a market with increase in mergers and acquisitions. The aim of this study was to conduct an integrative systematic review on privatization and oligopolies in the RRT sector in the context of contemporary capitalism. The inclusion criteria were scientific articles without language restrictions and that addressed the themes of oligopoly or privatization of RRT market. Studies published before 1990 were excluded. The exploratory search for publications was carried out on February 13, 2024 on the Virtual Health Library Regional Portal (VHL). Using the step-by-step of PRISMA flowchart, 34 articles were retrieved, of which 31 addressed the RRT sector in the United States and 26 compared for-profit dialysis units or those belonging to large organizations with non-profit or public ones. The main effects of privatization and oligopolies, evaluated by the studies, were: mortality, hospitalization, use of peritoneal dialysis and registration for kidney transplantation. When considering these outcomes, 19 (73%) articles showed worse results in private units or those belonging to large organizations, six (23%) studies were in favor of privatization or oligopolies and one study was neutral (4%). In summary, most of the articles included in this systematic review showed deleterious effects of oligopolization and privatization of the RRT sector on the patients served. Possible explanations for this result could be the presence of conflicts of interest in the RRT sector and the lack of incentive to implement the chronic kidney disease care line. The predominance of articles from a single nation may suggest that few countries have transparent mechanisms to monitor the quality of care and outcomes of patients on chronic dialysis.
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Affiliation(s)
- Farid Samaan
- Planning and Evaluation Group, São Paulo State Health Department, São Paulo, SP, Brazil
- Research Division, Dante Pazzanese Cardiology Institute, São Paulo, SP, Brazil
| | - Áquilas Mendes
- Public Health School, University of São Paulo, São Paulo, SP, Brazil
- Postgraduate Program, Pontifícia Universidade Católica, São Paulo, SP, Brazil
| | - Leonardo Carnut
- Center for the Development of Higher Education in Health, Federal University of São Paulo, São Paulo, SP, Brazil
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Torres-Toledano M, Granados-García V, Cortés-Sanabria L, Cueto-Manzano AM, Flores YN, Salmerón J. Service Utilization Patterns and Direct Medical Costs of Hospitalization in Patients With Renal Failure Before and After Initiating Home Peritoneal Dialysis. Value Health Reg Issues 2024; 41:114-122. [PMID: 38325244 DOI: 10.1016/j.vhri.2023.12.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 11/16/2023] [Accepted: 12/06/2023] [Indexed: 02/09/2024]
Abstract
OBJECTIVES This study aimed to determine the hospital service utilization patterns and direct healthcare hospital costs before and during peritoneal dialysis (PD) at home. METHODS A retrospective cohort study of patients with kidney failure (KF) was conducted at a Mexican Social Security Institute hospital for the year 2014. Cost categories included inpatient emergency room stays, inpatient services at internal medicine or surgery, and hospital PD. The study groups were (1) patients with KF before initiating home PD, (2) patients with less than 1 year of home PD (incident), and (3) patients with more than 1 year of home PD (prevalent). Costs were actualized to international dollars (Int$) 2023. RESULTS We found that 53% of patients with KF used home PD services, 42% had not received any type of PD, and 5% had hospital dialysis while waiting for home PD. The estimated costs adjusting for age and sex were Int$5339 (95% CI 4680-9746) for patients without home PD, Int$17 556 (95% CI 15 314-19 789) for incident patients, and Int$7872 (95% CI 5994-9749) for prevalent patients; with significantly different averages for the 3 groups (P < .001). CONCLUSIONS Although the use of services and cost is highest at the time of initiating PD, over time, using home PD leads to a significant reduction in use of hospital services, which translates into institutional cost savings. Our findings, especially considering the high rates of KF in Mexico, suggest a pressing need for interventions that can reduce healthcare costs at the beginning of renal replacement therapy.
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Affiliation(s)
| | - Víctor Granados-García
- Unidad de Investigación Epidemiológica y en Servicios de Salud, Área Envejecimiento, Instituto Mexicano del Seguro Social, Ciudad de México, México.
| | - Laura Cortés-Sanabria
- Dirección de Educación e Investigación en Salud, UMAE-Hospital de Especialidades, Centro Médico Nacional de Occidente, Instituto Mexicano del Seguro Social, Guadalajara, Jalisco, México
| | - Alfonso Martín Cueto-Manzano
- Unidad de Investigación Médica en Enfermedades Renales, UMAE-Hospital de Especialidades, Centro Médico Nacional de Occidente, Instituto Mexicano del Seguro Social, Guadalajara, Jalisco, México
| | - Yvonne N Flores
- Unidad de Investigación Epidemiológica y en Servicios de Salud, Morelos, Instituto Mexicano del Seguro Social, Cuernavaca, México; Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles (UCLA), Los Angeles, CA, USA; UCLA Center for Cancer Prevention and Control and UCLA-Kaiser Permanente Center for Health Equity, Fielding School of Public Health and Jonsson Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Jorge Salmerón
- Centro de Investigación en Políticas, Población y Salud, Universidad Nacional Autónoma de México, Ciudad de México, México
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Claudel SE, Valente C, Serafin H, Hassan Kamel M, Ghai S. Structured handoff to improve communication from inpatient to outpatient dialysis units: A quality improvement project. Hemodial Int 2023; 27:146-154. [PMID: 36696233 PMCID: PMC10101881 DOI: 10.1111/hdi.13060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Revised: 10/12/2022] [Accepted: 01/10/2023] [Indexed: 01/26/2023]
Abstract
BACKGROUND Patients with end-stage kidney disease requiring dialysis encounter high hospital readmission rates. One contributor is poor communication between hospitals and outpatient dialysis facilities. We hypothesized that improved communication may reduce 30-day hospital readmissions for patients on dialysis at an urban, safety net hospital. METHODS We created a standardized discharge handoff tool that is easy to use and provides concise data for dialysis centers. The handoff tool is a novel, electronic MACRO template (called a "dot-phrase") to be included in discharge documentation. Instructions for the dot-phrase and electronic facsimile (e-faxing) were sent to Internal Medicine residents immediately prior to their rotation on an inpatient Renal service. We then measured the intervention implementation rate and its impact on hospital readmission metrics. RESULTS We compared 3 months of preintervention and 6 months of postintervention data, identifying 82 and 135 index discharges in each respective study period. Patients were predominantly male (56.2%) and receiving hemodialysis (89.8%); a minority (9.2%) were undomiciled at the time of discharge. Mean age was 60.5 years (SD 14.0). Renal discharges followed by 30-day Renal readmission were not statistically lower in the postintervention group for the index discharge alone (26.8% vs. 20.0%, p = 0.12), but were for overall discharges (51.2% vs. 25.7%, p < 0.0001). The dot-phrase was used in 95.4% of discharge summaries, and 74.7% of discharge summaries were e-faxed within 24 h of discharge. CONCLUSION There was high uptake of a standardized discharge handoff tool among Internal Medicine residents on a Renal inpatient service. Using a handoff tool and e-faxing may improve communication with outpatient dialysis centers and may reduce readmissions among some patients but is likely insufficient to fully address high readmission rates. Subsequent intervention iterations would benefit from further collaboration with outpatient dialysis units for customization of the handoff tool to meet local communication needs.
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Affiliation(s)
- Sophie E Claudel
- Department of Internal Medicine, Boston Medical Center, Boston, Massachusetts, USA
| | - Christopher Valente
- Department of Internal Medicine, Boston Medical Center, Boston, Massachusetts, USA
| | - Hope Serafin
- Department of Pharmacy, Boston Medical Center, Boston, Massachusetts, USA
| | - Mohamed Hassan Kamel
- Section of Nephrology, Department of Internal Medicine, Boston Medical Center, Boston, Massachusetts, USA
| | - Sandeep Ghai
- Section of Nephrology, Department of Internal Medicine, Boston Medical Center, Boston, Massachusetts, USA
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Mohamed AH, Jeele MOO. Epidemiology of End-Stage Renal Disease in Mogadishu, Somalia: First Report at a Tertiary Care Hospital. Int J Gen Med 2022; 15:6259-6267. [PMID: 35903644 PMCID: PMC9315983 DOI: 10.2147/ijgm.s375280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 07/15/2022] [Indexed: 11/23/2022] Open
Abstract
Background End-stage renal disease (ESRD) in Somalia remains unexamined due to a lack of a national registry system, and the impact of the disease in the country is not estimated yet. The present study is the first report that aims to evaluate the epidemiological characteristics, causes, and dialysis-related factors associated with readmissions in ESRD patients who were going to routine hemodialysis. Patients and methods This cross-sectional observational study enrolled 208 patients with ESRD. Also, this study investigated patients readmitted to the hospital (n=135) after they enrolled in hemodialysis. The sociodemographic characteristics, risk factors, and comorbidities associated with these patients were reviewed. Admission site, length of hospital stay, outcome, and dialysis-related factors associated with readmissions in the first six months after being on a regular hemodialysis program were also assessed. Results The mean age of the patients was 52.7±15.0 years, 43.3% were >60 years, and 61.5% were male. The most common cause was diabetes at 39.4%, followed by hypertension (35.6%) and 12.5% for postrenal obstruction. The prevalence of 6-month hospital readmissions was 65%. The most common dialysis-related factor associated with readmissions was uremic complications due to missed hemodialysis sessions (40%), vascular access/catheter infection (20%), and anemia (17.8%) (95% CI: 0.825–5.357, OR: 3.017, p<0.04). Female cases were more vulnerable to vascular catheter site infection, anemia, and hyponatremia (p<0.001). 27.5% of the patients were admitted to the intensive care unit (ICU), and the most common reason for ICU admissions was pulmonary edema (53.8%), sepsis (42.8%), and uremia due to hemodialysis skip (26.4%) (95% CI: 1.507–13.632, OR: 2.08, p=0.01). The mortality rate was 5.2%. Conclusion The prevalence of unplanned hospital readmissions within six months was very high, and a missed hemodialysis session was identified as the leading cause. Inadequate knowledge, wrong social beliefs about the concept of dialysis and a lack of a health insurance system that covers the higher costs of each dialysis session are believed to be the causes of missed dialysis occasions.
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Affiliation(s)
| | - Mohamed Osman Omar Jeele
- Internal Medicine Department, Mogadishu Somalia Turkish Training and Research Hospital, Mogadishu, Somalia
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Xie F, Liu N, Yan L, Ning Y, Lim KK, Gong C, Kwan YH, Ho AFW, Low LL, Chakraborty B, Ong MEH. Development and validation of an interpretable machine learning scoring tool for estimating time to emergency readmissions. EClinicalMedicine 2022; 45:101315. [PMID: 35284804 PMCID: PMC8904223 DOI: 10.1016/j.eclinm.2022.101315] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Revised: 01/22/2022] [Accepted: 02/07/2022] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Emergency readmission poses an additional burden on both patients and healthcare systems. Risk stratification is the first step of transitional care interventions targeted at reducing readmission. To accurately predict the short- and intermediate-term risks of readmission and provide information for further temporal risk stratification, we developed and validated an interpretable machine learning risk scoring system. METHODS In this retrospective study, all emergency admission episodes from January 1st 2009 to December 31st 2016 at a tertiary hospital in Singapore were assessed. The primary outcome was time to emergency readmission within 90 days post discharge. The Score for Emergency ReAdmission Prediction (SERAP) tool was derived via an interpretable machine learning-based system for time-to-event outcomes. SERAP is six-variable survival score, and takes the number of emergency admissions last year, age, history of malignancy, history of renal diseases, serum creatinine level, and serum albumin level during index admission into consideration. FINDINGS A total of 293,589 ED admission episodes were finally included in the whole cohort. Among them, 203,748 episodes were included in the training cohort, 50,937 episodes in the validation cohort, and 38,904 in the testing cohort. Readmission within 90 days was documented in 80,213 (27.3%) episodes, with a median time to emergency readmission of 22 days (Interquartile range: 8-47). For different time points, the readmission rates observed in the whole cohort were 6.7% at 7 days, 10.6% at 14 days, 13.6% at 21 days, 16.4% at 30 days, and 23.0% at 60 days. In the testing cohort, the SERAP achieved an integrated area under the curve of 0.737 (95% confidence interval: 0.730-0.743). For a specific 30-day readmission prediction, SERAP outperformed the LACE index (Length of stay, Acuity of admission, Charlson comorbidity index, and Emergency department visits in past six months) and the HOSPITAL score (Hemoglobin at discharge, discharge from an Oncology service, Sodium level at discharge, Procedure during the index admission, Index Type of admission, number of Admissions during the last 12 months, and Length of stay). Besides 30-day readmission, SERAP can predict readmission rates at any time point during the 90-day period. INTERPRETATION Better performance in risk prediction was achieved by the SERAP than other existing scores, and accurate information about time to emergency readmission was generated for further temporal risk stratification and clinical decision-making. In the future, external validation studies are needed to evaluate the SERAP at different settings and assess their real-world performance. FUNDING This study was supported by the Singapore National Medical Research Council under the PULSES Center Grant, and Duke-NUS Medical School.
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Affiliation(s)
- Feng Xie
- Programme in Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, 169857, Singapore
| | - Nan Liu
- Programme in Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, 169857, Singapore
- Health Services Research Centre, Singapore Health Services, Singapore
- Institute of Data Science, National University of Singapore, Singapore
- Corresponding author at: Programme in Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, 169857, Singapore.
| | - Linxuan Yan
- Programme in Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, 169857, Singapore
| | - Yilin Ning
- Programme in Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, 169857, Singapore
| | - Ka Keat Lim
- School of Population Health and Environmental Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
- National Institute for Health Research (NIHR) Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust and King's College London, London, United Kingdom
| | - Changlin Gong
- Department of Internal Medicine, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yu Heng Kwan
- Programme in Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, 169857, Singapore
| | - Andrew Fu Wah Ho
- Programme in Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, 169857, Singapore
- Department of Emergency Medicine, Singapore General Hospital, Singapore
| | - Lian Leng Low
- Department of Family Medicine and Continuing Care, Singapore General Hospital, Singapore
- Department of Post-Acute and Continuing Care, Outram Community Hospital, Singapore
- SingHealth Duke-NUS Family Medicine Academic Clinical Program, Duke-NUS Medical School, Singapore
| | - Bibhas Chakraborty
- Programme in Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, 169857, Singapore
- Department of Statistics and Data Science, National University of Singapore, Singapore
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, United States
| | - Marcus Eng Hock Ong
- Programme in Health Services and Systems Research, Duke-NUS Medical School, 8 College Road, 169857, Singapore
- Health Services Research Centre, Singapore Health Services, Singapore
- Department of Emergency Medicine, Singapore General Hospital, Singapore
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Reisinger N, Koratala A. Quantitative Lung Ultrasonography for the Nephrologist: Applications in Dialysis and Heart Failure. KIDNEY360 2022; 3:176-184. [PMID: 35368560 PMCID: PMC8967614 DOI: 10.34067/kid.0003972021] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 11/03/2021] [Indexed: 06/14/2023]
Abstract
Volume overload, and its attendant increase in acute care utilization and cardiovascular morbidity and mortality, represents a critical challenge for the practicing nephrologist. This is particularly true among patients with ESKD on HD, where predialysis volume overload and intradialytic and postdialytic hypovolemia account for almost a third of all cost for the Medicare dialysis benefit. Quantitative lung ultrasound is a tool for assessing the extent of extravascular lung water that outperforms physical exam and plain chest radiography. B-lines are vertical hyperechoic artifacts present in patients with increased extravascular lung water. B-lines have been shown to decrease dynamically during the hemodialysis treatment in proportion to ultrafiltration volume. Among patients with chronic heart failure, titration of diuretics on the basis of the extent of pulmonary congestion noted on lung ultrasonography has been shown to decrease recurrent acute care utilization. Early data from randomized controlled trials of lung ultrasound-guided ultrafiltration therapy among patients with ESKD on HD have shown promise for potential reduction in recurrent episodes of decompensated heart failure and cardiovascular events. Ultimately, lung ultrasound may predict those who are ultrafiltration tolerant and could be used to decrease acute care utilization and, thus, cost in this population.
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Affiliation(s)
- Nathaniel Reisinger
- Perelman School of Medicine, Hospital of the University of Pennsylvania, Division of Renal, Electrolyte and Hypertension, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Abhilash Koratala
- Division of Nephrology, Medical College of Wisconsin, Milwaukee, Wisconsin
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Tummalapalli SL, Mendu ML. Value-Based Care and Kidney Disease: Emergence and Future Opportunities. Adv Chronic Kidney Dis 2022; 29:30-39. [PMID: 35690401 PMCID: PMC9199582 DOI: 10.1053/j.ackd.2021.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 09/16/2021] [Accepted: 10/05/2021] [Indexed: 01/03/2023]
Abstract
The United States health care system has increasingly embraced value-based programs that reward improved outcomes and lower costs. Health care value, defined as quality per unit cost, was a major goal of the 2010 Patient Protection and Affordable Care Act amid high and rising US health care expenditures. Many early value-based programs were specifically designed for patients with end-stage renal disease (ESRD) and targeted toward dialysis facilities, including the ESRD Prospective Payment System, ESRD Quality Incentive Program, and ESRD Seamless Care Organizations. While a great deal of attention has been paid to these ESRD-focused programs, other value-based programs targeted toward hospitals and health systems may also affect the quality and costs of care for a broader population of patients with kidney disease. Value-based care for kidney disease is increasingly relevant in light of the Advancing American Kidney Health initiative, which introduces new value-based payment models: the mandatory ESRD Treatment Choices Model in 2021 and voluntary Kidney Care Choices Model in 2022. In this review article, we summarize the emergence and impact of value-based programs on the quality and costs of kidney care, with a focus on federal programs. Key opportunities in value-based kidney care include shifting the focus toward chronic kidney disease, enhancing population health management capabilities, improving quality measurement, and leveraging programs to advance health equity.
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Affiliation(s)
- Sri Lekha Tummalapalli
- Division of Healthcare Delivery Science & Innovation, Department of Population Health Sciences, Weill Cornell Medicine, New York, NY,The Rogosin Institute, New York, NY
| | - Mallika L. Mendu
- Division of Renal Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA,Center for Population Health, Mass General Brigham, Boston, MA
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Omary C, Wright P, Kumarasamy MA, Franks N, Esper G, Mouzon HB, Barrolle S, Horne K, Cranmer J. Using Routinely Collected Electronic Health Record Data to Predict Readmission and Target Care Coordination. J Healthc Qual 2022; 44:11-22. [PMID: 34294659 DOI: 10.1097/jhq.0000000000000318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
ABSTRACT Patients with chronic renal failure (CRF) are at high risk of being readmitted to hospitals within 30 days. Routinely collected electronic health record (EHR) data may enable hospitals to predict CRF readmission and target interventions to increase quality and reduce readmissions. We compared the ability of manually extracted variables to predict readmission compared with EHR-based prediction using multivariate logistic regression on 1 year of admission data from an academic medical center. Categorizing three routinely collected variables (creatinine, B-type natriuretic peptide, and length of stay) increased readmission prediction by 30% compared with paper-based methods as measured by C-statistic (AUC). Marginal effects analysis using the final multivariate model provided patient-specific risk scores from 0% to 44.3%. These findings support the use of routinely collected EHR data for effectively stratifying readmission risk for patients with CRF. Generic readmission risk tools may be evidence-based but are designed for general populations and may not account for unique traits of specific patient populations-such as those with CRF. Routinely collected EHR data are a rapid, more efficient strategy for risk stratifying and strategically targeting care. Earlier risk stratification and reallocation of clinician effort may reduce readmissions. Testing this risk model in additional populations and settings is warranted.
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Doshi S, Wish JB. Strategies to Reduce Rehospitalization in Patients with CKD and Kidney Failure. Clin J Am Soc Nephrol 2021; 16:328-334. [PMID: 32660962 PMCID: PMC7863646 DOI: 10.2215/cjn.02300220] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Readmissions in patients with nondialysis-dependent CKD and kidney failure are common and are associated with significant morbidity, mortality, and economic consequences. In 2013, the Centers for Medicare and Medicaid Services implemented the Hospital Readmissions Reduction Program in an attempt to reduce high hospitalization-associated costs. Up to 50% of all readmissions are deemed avoidable and present an opportunity for intervention. We describe factors that are specific to the patient, the index hospitalization, and underlying conditions that help identify the "high-risk" patient. Early follow-up care, developing volume management strategies, optimizing nutrition, obtaining palliative care consultations for seriously ill patients during hospitalization and conducting goals-of-care discussions with them, instituting systematic advance care planning during outpatient visits to avoid unwanted hospitalizations and intensive treatment at the end of life, and developing protocols for patients with incident or prevalent cardiovascular conditions may help prevent avoidable readmissions in patients with kidney disease.
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Affiliation(s)
- Simit Doshi
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana
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Wyatt LH, Xi Y, Kshirsagar A, Di Q, Ward-Caviness C, Wade TJ, Cascio WE, Rappold AG. Association of short-term exposure to ambient PM 2.5 with hospital admissions and 30-day readmissions in end-stage renal disease patients: population-based retrospective cohort study. BMJ Open 2020; 10:e041177. [PMID: 33323443 PMCID: PMC7745516 DOI: 10.1136/bmjopen-2020-041177] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
OBJECTIVES To examine the effect of short-term exposure to ambient fine particulate matter (PM2.5) on all-cause, cardiovascular and respiratory-related hospital admissions and readmissions among patients receiving outpatient haemodialysis. DESIGN Retrospective cohort study. SETTING Inpatient hospitalisation claims identified from the US Renal Data System in 530 US counties. PARTICIPANTS All patients receiving in-centre haemodialysis between 2008 and 2014. PRIMARY AND SECONDARY OUTCOME MEASURES Risk of all-cause, cardiovascular and respiratory-related hospital admissions and 30-day all-cause and cause-specific readmission following an all-cause, cardiovascular, and respiratory-related discharges. Readmission risk was evaluated for early (1-7 days postdischarge) and late (8-30 days postdischarge) readmission time periods. Relative risk is expressed per 10 μg/m3 of PM2.5. RESULTS Same-day ambient PM2.5 was associated with increased hospital admission risk for cardiovascular causes (0.9%, 95% CI 0.2 to 1.7). Greater PM2.5-related associations were observed with 30-day readmission risk. Early-readmission risk was increased by 1.6%-1.8% following all-cause (1.6%, 95% CI 0.6% to 2.6%), cardiovascular (1.8%, 95% CI 0.4% to 3.2%) and respiratory (1.8%, 95% CI 0.4% to 3.2%) discharges; while late-readmission risk increased by 1.2%-1.3% following all-cause and cardiovascular discharges. PM2.5-related associations with readmission risk were greatest for certain cause-specific readmissions ranging 4.0%-6.5% for dysrhythmia and conduction disorder, heart failure, chronic obstructive pulmonary disease, other non-cardiac chest pain or respiratory syndrome and pneumonia. Following all-cause discharges, the cause-specific early-readmission risk was increased by 6.5% (95% CI 3.5% to 9.6%) for pneumonia, 4.8% (95% CI 2.3% to 7.4%) for dysrhythmia and conduction disorder, 3.7% (95% CI 1.4% to 6.0%) for heart failure and 2.7% (95% CI 1.2% to 4.2%) for other non-cardiac chest pain or respiratory syndrome-related causes. CONCLUSIONS Daily ambient PM2.5 was associated with an increased risk of cardiovascular admissions and 30-day readmissions following cardiopulmonary-related discharges in a vulnerable end-stage renal disease population. In the first week following discharge, greater PM2.5-related risk of rehospitalisation was identified for some diagnoses.
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Affiliation(s)
- Lauren H Wyatt
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency Research Triangle Park Campus, Research Triangle Park, North Carolina, USA
| | - Yuzhi Xi
- US Environmental Protection Agency (ORISE), Chapel Hill, North Carolina, USA
| | - Abhijit Kshirsagar
- University of North Carolina Kidney Center and Division of Nephrology and Hypertension, Chapel Hill, North Carolina, USA
| | - Qian Di
- Tsinghua University, Beijing, Beijing, China
| | - Cavin Ward-Caviness
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency Research Triangle Park Campus, Research Triangle Park, North Carolina, USA
| | - Timothy J Wade
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency Research Triangle Park Campus, Research Triangle Park, North Carolina, USA
| | - Wayne E Cascio
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency Research Triangle Park Campus, Research Triangle Park, North Carolina, USA
| | - Ana G Rappold
- Center for Public Health and Environmental Assessment, US Environmental Protection Agency Research Triangle Park Campus, Research Triangle Park, North Carolina, USA
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Golestaneh L, Cavanaugh KL, Lo Y, Karaboyas A, Melamed ML, Johns TS, Norris KC. Community Racial Composition and Hospitalization Among Patients Receiving In-Center Hemodialysis. Am J Kidney Dis 2020; 76:754-764. [PMID: 32673736 PMCID: PMC7844565 DOI: 10.1053/j.ajkd.2020.05.019] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 05/21/2020] [Indexed: 02/07/2023]
Abstract
RATIONALE & OBJECTIVE Community racial composition has been shown to be associated with mortality in patients receiving maintenenance dialysis. It is unclear whether living in communities with predominantly Black residents is also associated with risk for hospitalization among patients receiving hemodialysis. STUDY DESIGN Retrospective analysis of prospectively collected data from a cohort of patients receiving hemodialysis. SETTING & PARTICIPANTS 4,567 patients treated in 154 dialysis facilities located in 127 unique zip codes and enrolled in US Dialysis Outcomes and Practice Patterns Study (DOPPS) phases 4 to 5 (2010-2015). EXPOSURE Tertile of percentage of Black residents within zip code of patients' dialysis facility, defined through a link to the American Community Survey. OUTCOME Rate of hospitalizations during the study period. ANALYTIC APPROACH Associations of patient-, facility-, and community-level variables with community's percentage of Black residents were assessed using analysis of variance, Kruskal-Wallis, or χ2/Fisher exact tests. Negative binomial regression was used to estimate the incidence rate ratio for hospitalizations between these communities, with and without adjustment for potential confounding variables. RESULTS Mean age of study patients was 62.7 years. 53% were White, 27% were Black, and 45% were women. Median and threshold percentages of Black residents in zip codes in which dialysis facilities were located were 34.2% and≥14.4% for tertile 3 and 1.0% and≤1.8% for tertile 1, respectively. Compared with those in tertile 1 facilities, patients in tertile 3 facilities were more likely to be younger, be Black, live in urban communities with lower socioeconomic status, have a catheter as vascular access, and have fewer comorbid conditions. Patients dialyzing in communities with the highest tertile of Black residents experienced a higher adjusted rate of hospitalization (adjusted incidence rate ratio, 1.32; 95% CI, 1.12-1.56) compared with those treated in communities within the lowest tertile. LIMITATIONS Potential residual confounding. CONCLUSIONS The risk for hospitalization for patients receiving maintenance dialysis is higher among those treated in communities with a higher percentage of Black residents after adjustment for dialysis care, patient demographics, and comorbid conditions. Understanding the cause of this association should be a priority of future investigation.
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Affiliation(s)
- Ladan Golestaneh
- Renal Division, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY.
| | - Kerri L Cavanaugh
- Division of Nephrology and Hypertension, Vanderbilt University Medical Center, Nashville, TN
| | - Yungtai Lo
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | | | - Michal L Melamed
- Renal Division, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY
| | - Tanya S Johns
- Renal Division, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, NY
| | - Keith C Norris
- Division of General Internal Medicine, UCLA/David Geffen School of Medicine, Los Angeles, CA; Division of Nephrology, UCLA/David Geffen School of Medicine, Los Angeles, CA
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12
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Ross KH, Jaar BG, Lea JP, Masud T, Patzer RE, Plantinga LC. Long-term outcomes among Medicare patients readmitted in the first year of hemodialysis: a retrospective cohort study. BMC Nephrol 2019; 20:285. [PMID: 31357952 PMCID: PMC6664786 DOI: 10.1186/s12882-019-1473-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Accepted: 07/19/2019] [Indexed: 11/06/2022] Open
Abstract
Background Readmission within 30 days of hospital discharge is common and costly among end-stage renal disease (ESRD) patients. Little is known about long-term outcomes after readmission. We estimated the association between hospital admissions and readmissions in the first year of dialysis and outcomes in the second year. Methods Data on incident dialysis patients with Medicare coverage were obtained from the United States Renal Data System (USRDS). Readmission patterns were summarized as no admissions in the first year of dialysis (Admit-), at least one admission but no readmissions within 30 days (Admit+/Readmit-), and admissions with at least one readmission within 30 days (Admit+/Readmit+).We used Cox proportional hazards models to estimate the association between readmission pattern and mortality, hospitalization, and kidney transplantation, accounting for demographic and clinical covariates. Results Among the 128,593 Medicare ESRD patients included in the study, 18.5% were Admit+/Readmit+, 30.5% were Admit+/Readmit-, and 51.0% were Admit-. Readmit+/Admit+ patients had substantially higher long-term risk of mortality (HR = 3.32 (95% CI, 3.21–3.44)), hospitalization (HR = 4.46 (95% CI, 4.36–4.56)), and lower likelihood of kidney transplantation (HR = 0.52 (95% CI, 0.44–0.62)) compared to Admit- patients; these associations were stronger than those among Admit+/Readmit- patients. Conclusions Patients with readmissions in the first year of dialysis were at substantially higher risk of poor outcomes than either patients who had no admissions or patients who had hospital admissions but no readmissions. Identifying strategies to both prevent readmission and mitigate risk among patients who had a readmission may improve outcomes among this substantial, high-risk group of ESRD patients. Electronic supplementary material The online version of this article (10.1186/s12882-019-1473-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Katherine H Ross
- Department of Epidemiology, Emory Rollins School of Public Health, Atlanta, GA, USA
| | - Bernard G Jaar
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA.,Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, MD, USA.,Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.,Nephrology Center of Maryland, Baltimore, MD, USA
| | - Janice P Lea
- Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Tahsin Masud
- Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Rachel E Patzer
- Department of Epidemiology, Emory Rollins School of Public Health, Atlanta, GA, USA.,Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA.,Department of Surgery, Emory University School of Medicine, Atlanta, GA, USA
| | - Laura C Plantinga
- Department of Epidemiology, Emory Rollins School of Public Health, Atlanta, GA, USA. .,Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA.
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13
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Qi AC, Butler AM, Joynt Maddox KE. The Role Of Social Risk Factors In Dialysis Facility Ratings And Penalties Under A Medicare Quality Incentive Program. Health Aff (Millwood) 2019; 38:1101-1109. [DOI: 10.1377/hlthaff.2018.05406] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
- Andrew C. Qi
- Andrew C. Qi is a medical student at the Washington University School of Medicine, in Saint Louis, Missouri
| | - Anne M. Butler
- Anne M. Butler is an instructor of medicine at the Washington University School of Medicine, in Saint Louis
| | - Karen E. Joynt Maddox
- Karen E. Joynt Maddox is an assistant professor of medicine (cardiology) at the Washington University School of Medicine, in Saint Louis
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14
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Tesfaye WH, Peterson GM, Castelino RL, McKercher C, Jose MD, Wimmer BC, Zaidi STR. Medication Regimen Complexity and Hospital Readmission in Older Adults With Chronic Kidney Disease. Ann Pharmacother 2018; 53:28-34. [PMID: 30070583 DOI: 10.1177/1060028018793419] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Chronic kidney disease (CKD) is characterized by high rates of hospital admissions and readmissions. However, there is a scarcity of research into medication-related factors predicting such outcomes in this patient group. OBJECTIVE To evaluate the effect of medication regimen complexity at hospital discharge on subsequent readmissions and their timing in older adults with CKD. METHODS This was a 12-month retrospective cohort study of 204 older (⩾65 years) CKD patients in an Australian tertiary care hospital. Medication regimen complexity was quantified using the 65-item medication regimen complexity index (MRCI). The outcomes were the occurrence of readmission in 30 days and time to readmission within 12 months. Logistic regression was used to identify factors predicting 30-day readmission, and a competing risks proportional subdistribution hazard model, accounting for deaths, was used for factors predicting time to readmission. RESULTS Overall, 50 (24%) patients, predominantly men (72%), were readmitted within 30 days of follow-up. MRCI was not significantly associated with 30-day readmission (odds ratio [OR] = 1.27; 95% CI = 0.94-1.73). The median (interquartile range) time to readmission within 12 months was 145 (31-365) days. On a multivariate analysis, a 10-unit increase in MRCI was associated with a shorter time to readmission within 12 months (subdistribution HR = 1.18; 95% CI = 1.01-1.36). Conclusion and Relevance: Medication regimen complexity was not significantly associated with 30-day readmission; however, it was associated with a significantly shorter time to 12-month readmission in older CKD patients. This finding highlights the importance of medication regimen complexity as a potential target for medical interventions to reduce readmission risks.
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Affiliation(s)
| | | | | | | | - Matthew D Jose
- 3 Menzies Institute for Medical Research, Hobart, Tasmania, Australia
- 4 Royal Hobart Hospital, Tasmania, Australia
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