Post-hospitalization dialysis facility processes of care and hospital readmissions among hemodialysis patients: a retrospective cohort study

Hospital Readmissions for Fluid Overload among Individuals with Diabetes and Diabetic Kidney Disease: Risk Factors and Multivariable Prediction Models

AIMS

Hospital readmissions due to recurrent fluid overload in diabetes and diabetic kidney disease can be avoided with evidence-based interventions. We aimed to identify at-risk patients who can benefit from these interventions by developing risk prediction models for readmissions for fluid overload in people living with diabetes and diabetic kidney disease.

METHODS

This was a single-center retrospective cohort study of 1,531 adults with diabetes and diabetic kidney disease hospitalized for fluid overload, congestive heart failure, pulmonary edema, and generalized edema between 2015 and 2017. The multivariable regression models for 30-day and 90-day readmission for fluid overload were compared with the LACE score for discrimination, calibration, sensitivity, specificity, and net reclassification index (NRI).

RESULTS

Readmissions for fluid overload within 30 days and 90 days occurred in 8.6% and 17.2% of patients with diabetes, and 8.2% and 18.3% of patients with diabetic kidney disease, respectively. After adjusting for demographics, comorbidities, clinical parameters, and medications, a history of alcoholism (HR 3.85, 95% CI: 1.41-10.55) and prior hospitalization for fluid overload (HR 2.50, 95% CI: 1.26-4.96) were independently associated with 30-day readmission in patients with diabetic kidney disease, as well as in individuals with diabetes. Additionally, current smoking, absence of hypertension, and high-dose intravenous furosemide were also associated with 30-day readmission in individuals with diabetes. Prior hospitalization for fluid overload (HR 2.43, 95% CI: 1.50-3.94), cardiovascular disease (HR 1.44, 95% CI: 1.03-2.02), eGFR ≤45 mL/min/1.73 m2 (HR 1.39, 95% CI: 1.003-1.93) was independently associated with 90-day readmissions in individuals with diabetic kidney disease. Additionally, thiazide prescription at discharge reduced 90-day readmission in diabetic kidney disease, while the need for high-dose intravenous furosemide predicted 90-day readmission in diabetes. The clinical and clinico-psychological models for 90-day readmission in individuals with diabetes and diabetic kidney disease had better discrimination and calibration than the LACE score. The NRI for the clinico-psychosocial models to predict 30- and 90-day readmissions in diabetes was 22.4% and 28.9%, respectively. The NRI for the clinico-psychosocial models to predict 30- and 90-day readmissions in diabetic kidney disease was 5.6% and 38.9%, respectively.

CONCLUSION

The risk models can potentially be used to identify patients at risk of readmission for fluid overload for evidence-based interventions, such as patient education or transitional care programs to reduce preventable hospitalizations.

Pay-for-performance programs effectiveness in healthcare: the case of the end-stage renal disease quality incentive program

This paper focuses on Medicare's End-Stage Renal Disease Quality Incentive Program (QIP). QIP aims to promote high-quality services in outpatient dialysis facilities by tying their payments to their performance on pre-specified quality measures. In this paper, employing principal-agent theory, we examine the effectiveness of QIP by exploring the changes in various clinical/operational measures when they become a part of the program as a performance measure. We study five QIP quality measures; two are operational: hospitalization and readmission. And three others are clinical: blood transfusion, hypercalcemia, and dialysis adequacy. Overall, we observe a significant improvement in all QIP quality measures after being included in the program, except for readmission. We recommend adjusting the weight and redesigning the readmission measure for Medicare to incentivize providers to reduce readmission. We also discuss establishing care coordination and employing data-driven clinical decision support systems as opportunities for dialysis facilities to improve the care delivery process.

Digital health technology to support care and improve outcomes of chronic kidney disease patients: as a case illustration, the Withings toolkit health sensing tools

Cardiovascular disease (CVD) is a major burden in dialysis-dependent chronic kidney disease (CKD5D) patients. Several factors contribute to this vulnerability including traditional risk factors such as age, gender, life style and comorbidities, and non-traditional ones as part of dialysis-induced systemic stress. In this context, it appears of utmost importance to bring a closer attention to CVD monitoring in caring for CKD5D patients to ensure early and appropriate intervention for improving their outcomes. Interestingly, new home-used, self-operated, connected medical devices offer convenient and new tools for monitoring in a fully automated and ambulatory mode CKD5D patients during the interdialytic period. Sensoring devices are installed with WiFi or Bluetooth. Some devices are also available in a cellular version such as the Withings Remote Patient Monitoring (RPM) solution. These devices analyze the data and upload the results to Withings HDS (Hybrid data security) platform servers. Data visualization can be viewed by the patient using the Withings Health Mate application on a smartphone, or with a web interface. Health Care Professionals (HCP) can also visualize patient data via the Withings web-based RPM interface. In this narrative essay, we analyze the clinical potential of pervasive wearable sensors for monitoring ambulatory dialysis patients and provide an assessment of such toolkit digital medical health devices currently available on the market. These devices offer a fully automated, unobtrusive and remote monitoring of main vital functions in ambulatory subjects. These unique features provide a multidimensional assessment of ambulatory CKD5D patients covering most physiologic functionalities, detecting unexpected disorders (i.e., volume overload, arrhythmias, sleep disorders) and allowing physicians to judge patient's response to treatment and recommendations. In the future, the wider availability of such pervasive health sensing and digital technology to monitor patients at an affordable cost price will improve the personalized management of CKD5D patients, so potentially resulting in improvements in patient quality of life and survival.

Readmission rates and risk factors for readmission after transcatheter aortic valve replacement in patients with end-stage renal disease

Objectives

We sought to examine readmission rates and predictors of hospital readmission following TAVR in patients with ESRD.

Background

End-stage renal disease (ESRD) is associated with poor outcomes following transcatheter aortic valve replacement (TAVR).

Methods

We assessed index hospitalizations for TAVR from the National Readmissions Database from 2017 to 2018 and used propensity scores to match those with and without ESRD. We compared 90-day readmission for any cause or cardiovascular cause. Length of stay (LOS), mortality, and cost were assessed for index hospitalizations and 90-day readmissions. Multivariable logistic regression was performed to identify predictors of 90-day readmission.

Results

We identified 49,172 index hospitalizations for TAVR, including 1,219 patients with ESRD (2.5%). Patient with ESRD had higher rates of all-cause readmission (34.4% vs. 19.2%, HR 1.96, 95% CI 1.68–2.30, p<0.001) and cardiovascular readmission (13.2% vs. 7.7%, HR 1.85, 95% CI 1.44–2.38, p<0.001) at 90 days. During index hospitalization, patients with ESRD had longer length of stay (mean difference 1.9 days), increased hospital cost (mean difference $42,915), and increased in-hospital mortality (2.6% vs. 0.9%). Among those readmitted within 90 days, patients with ESRD had longer LOS and increased hospital charge, but similar in-hospital mortality. Diabetes (OR 1.86, 95% CI 1.31–2.64) and chronic pulmonary disease (OR 1.51, 95% CI 1.04–2.18) were independently associated with higher odds of 90-day readmission in patients with ESRD.

Conclusion

Patients with ESRD undergoing TAVR have higher mortality and increased cost associated with their index hospitalization and are at increased risk of readmission within 90 days following TAVR.

Causes of Hospitalization among End-Stage Kidney Disease Cohort before and after Hemodialysis

Patients with end-stage kidney disease (ESKD) have a greater risk of comorbidities, including diabetes and anemia, and have higher hospital admission rates than patients with other diseases. The cause of hospital admissions is associated with ESKD prognosis. This retrospective cohort study involved patients with ESKD who received hemodialysis and investigated whether the cause of hospital admission changed before versus after they started hemodialysis. This study recruited 592 patients with ESKD who received hemodialysis at any period between January 2005 and November 2017 and had been assigned the International Classification of Diseases Ninth Revision Clinical Modification (ICD-9-CM) code for ESKD. The patients' demographic data and hospitalization status one year before and two years after they received hemodialysis were analyzed. A McNemar test was conducted to analyze the diagnostic changes from before to after hemodialysis in patients with ESKD. The study's sample of patients with ESKD comprised more women (51.86%) than men and had an average age of 67.15 years. The numbers of patients admitted to the hospital for the following conditions all decreased significantly after they received hemodialysis: type 2 (non-insulin-dependent and adult-onset) diabetes; native atherosclerosis; urinary tract infection; gastric ulcer without mention of hemorrhage, perforation, or obstruction; pneumonia; reflux esophagitis; duodenal ulcer without mention of hemorrhage, perforation, or obstruction; and bacteremia. Most patients exhibited one or more of the following comorbidities: diabetes (n = 407, 68.75%), hypertension (n = 491, 82.94%), congestive heart failure (n = 161, 27.20%), ischemic heart disease (n = 125, 21.11%), cerebrovascular accident (n = 93, 15.71%), and gout (n = 96, 16.22%). An analysis of variance (ANOVA) indicated that changes in the ICD-9-CM codes for native atherosclerosis, urinary tract infection, pneumonia, and hyperkalemia were associated with age. Patients who developed pneumonia before or after they received hemodialysis tended to be older (range: 69-70 years old). This study investigated the causes of hospital admission among patients with ESKD one year before and two years after they received hemodialysis. This study's results revealed hypertension to be the most common comorbidity. Regarding the cause of admission, pneumonia was more prevalent in older than in younger patients. Moreover, changes in the ICD-9-CM codes of native atherosclerosis, urinary tract infection, pneumonia, and hyperkalemia were significantly correlated with age. Therefore, when administering comprehensive nursing care and treatment for ESKD, clinicians should not only focus on comorbidities but also consider factors (e.g., age) that can affect patient prognosis.

Effectiveness of a Web-Based Provider Communications Platform in Reducing Hospital Readmissions Among Patients Receiving Dialysis: A Pilot Pre-Post Study

Rationale & Objective

Suboptimal care coordination between dialysis facilities and hospitals is an important driver of 30-day hospital readmissions among patients receiving dialysis. We examined whether the introduction of web-based communications platform (“DialysisConnect”) was associated with reduced hospital readmissions.

Study Design

Pilot pre-post study.

Setting & Participants

A total of 4,994 index admissions at a single hospital (representing 2,419 patients receiving dialysis) during the study period (January 1, 2019-May 31, 2021).

Intervention

DialysisConnect was available to providers at the hospital and 4 affiliated dialysis facilities (=intervention facilities) during the pilot period (November 1, 2020-May 31, 2021).

Outcomes

The primary outcome was 30-day readmission; secondary outcomes included 30-day emergency department visits and observation stays. Interrupted time series and linear models with generalized estimating equations were used to assess pilot versus prepilot differences in outcomes; difference-in-difference analyses were performed to compare these differences between intervention versus control facilities. Sensitivity analyses included a third, prepilot/COVID-19 period (March 1, 2020-October 31, 2020).

Results

There was no statistically significant difference in the monthly trends in the 30-day readmissions pilot versus prepilot periods (−0.60 vs -0.13, P = 0.85) for intervention facility admissions; the difference-in-difference estimate was also not statistically significant (0.54 percentage points, P = 0.83). Similar analyses including the prepilot/COVID-19 period showed that, despite a substantial drop in admissions at the start of the pandemic, there were no statistically significant differences across the 3 periods. The age-, sex-, race-, and comorbid condition-adjusted, absolute pilot versus prepilot difference in readmissions rate was 1.8% (−3.7% to 7.3%); similar results were found for other outcomes.

Limitations

Potential loss to follow-up and pandemic effects.

Conclusions

In this pilot, the introduction of DialysisConnect was not associated with reduced hospital readmissions. Tailored care coordination solutions should be further explored in future, multisite studies to improve the communications gap between dialysis facilities and hospitals.

Epidemiology of End-Stage Renal Disease in Mogadishu, Somalia: First Report at a Tertiary Care Hospital

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.

A Web-based, Provider-driven Mobile App to Enhance Patient Care Coordination between Dialysis Facilities and Hospitals: Development and Pilot Implementation Study (Preprint)

Background

Objective

Methods

Results

Conclusions

Lung Ultrasound: A "Biomarker" for Fluid Overload?

Fluid overload is associated with poor outcomes in patients with acute kidney injury as well as end-stage kidney disease. Lung ultrasound (LUS) has been used in many different settings and specialties including the emergency department, intensive care unit, trauma, cardiology, and nephrology. Although LUS has been a valuable tool in assessing pulmonary congestion, LUS findings may not always be pathognomonic for pulmonary congestion. Furthermore, the feasibility of doing an extensive LUS examination as has been done in research studies may be hard to implement within the clinical setting. This review will go over the use of LUS to evaluate for fluid overload, compare LUS with other markers of fluid overload, review limitations of LUS, and suggest potential future directions in the use of LUS in nephrology.

Strategies to Reduce Rehospitalization in Patients with CKD and Kidney Failure

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.

Long-term outcomes among Medicare patients readmitted in the first year of hemodialysis: a retrospective cohort study

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.