Hemodialysis patient characteristics associated with better experience as measured by the In-center Hemodialysis Consumer Assessment of Healthcare Providers and Systems (ICH CAHPS) survey

Identifying Patient Satisfaction Determinants in Hemodialysis Settings: A Systematic Review

Purpose

Patient satisfaction is a measure of care quality that assists providers in determining the effectiveness of their services while meeting patients’ expectations. This study aimed to review existing studies that have focused on patients’ satisfaction determinants in Hemodialysis (HD) settings.

Methods

Electronic databases (PubMed, ScienceDirect, Scopus, and Google Scholar) were searched from 2000 onwards to identify studies using search terms related to patient satisfaction and hemodialysis centers. Article review was limited to studies written in English. A total of 19 articles were included by following the PRISMA statement. Data were extracted using a structured form and summarized in a tabular format to identify different determinants that showed a relationship with patient satisfaction. Determinants were classified into provider-related determinants and patient-related characteristics.

Results

Provider-related determinants of patient satisfaction in HD centers include staff, facility, service, and treatment. Patient-related characteristics associated with satisfaction include demographics and health status history. Based on this systematic review, key correlates of patient satisfaction in hemodialysis centers include: staff, facility, service, treatment, patient’s demographics, and health status.

Conclusion

The findings of this study can help healthcare facilities in taking measures in line with the specified determinants to enhance patient satisfaction and improve the organizational performance of the healthcare centers. It is important to constantly study and improve these determinants based on patient feedback to improve patient satisfaction and quality of care.

Organizational Health Literacy in a Hospital-Insights on the Patients' Perspective

Health literacy-sensitive communication has been found to be an important dimension of organizational health literacy measured from the patients' perspective. Little is known about the role of health literacy-sensitive communication in complex care structures. Therefore, our aim was to assess which hospital characteristics (in terms of process organization) and patient characteristics (e.g., age, chronic illness, etc.) contribute to better perceptions of health literacy-sensitive communication, as well as whether better health literacy-sensitive communication is associated with better patient reported experiences. Data were derived from a patient survey conducted in 2020 in four clinical departments of a university hospital in Germany. Health literacy-sensitive communication was measured with the HL-COM scale. Data from 209 patients (response rate 24.2%) were analyzed with a structural equation model (SEM). Results revealed that no patient characteristics were associated with HL-COM scores. Better process organization as perceived by patients was associated with significantly better HL-COM scores, and, in turn, better HL-COM scores were associated with more patient-reported social support provided by physicians and nurses as well as fewer unmet information needs. Investing into good process organization might improve health literacy-sensitive communication, which in turn has the potential to foster the patient-provider relationship as well as to reduce unmet information needs of patients.

Patient-Reported Experiences with Dialysis Care and Provider Visit Frequency

BACKGROUND AND OBJECTIVES

New payment models resulting from the Advancing American Kidney Health initiative may create incentives for nephrologists to focus less on face-to-face in-center hemodialysis visits. This study aimed to understand whether more frequent nephrology practitioner dialysis visits improved patient experience and could help inform future policy.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

In a cross-sectional study of patients receiving dialysis from April 1, 2015 through January 31, 2016, we linked patient records from a national kidney failure registry to patient experience data from the In-Center Hemodialysis Consumer Assessment of Healthcare Providers and Systems survey. We used a multivariable mixed effects linear regression model to examine the association between nephrology practitioner visit frequency and patient-reported experiences with nephrologist care.

RESULTS

Among 5125 US dialysis facilities, 2981 (58%) had ≥30 In-Center Hemodialysis Consumer Assessment of Healthcare Providers and Systems surveys completed between April 2015 and January 2016, and 243,324 patients receiving care within these facilities had Medicare Parts A/B coverage. Face-to-face practitioner visits per month were 71% with four or more visits, 17% with two to three visits, 4% with one visit, and 8% with no visits. Each 10% absolute greater proportion of patients seen by their nephrology practitioner(s) four or more times per month was associated with a modestly but statistically significant lower score of patient experience with nephrologist care by -0.3 points (95% confidence interval, -0.5 to -0.1) and no effect on experience with other domains of dialysis care.

CONCLUSIONS

In an analysis of patient experiences at the dialysis facility level, frequent nephrology practitioner visits to facilities where patients undergo outpatient hemodialysis were not associated with better patient experiences.

Contributions of treatment centre and patient characteristics to patient-reported experience of haemodialysis: a national cross-sectional study

OBJECTIVES

To examine the relative importance of patient and centre level factors in determining self-reported experience of care in patients with advanced kidney disease treated by maintenance haemodialysis (HD).

DESIGN

Analysis of data from a cross sectional national survey; the UK Renal Registry (UKRR) national Kidney patient-reported experience measure (PREM) survey (2018). Centre-level data were obtained from the UKRR report (2018).

SETTING

National survey of patients with advanced kidney disease receiving treatment with maintenance HD in UK renal centres in 2018.

PARTICIPANTS

The Kidney PREM was distributed to all UK renal centres by the UKRR in May 2018. Each centre invited patients receiving outpatient treatment for kidney disease to complete the PREM. These included patients with chronic kidney disease, those receiving dialysis-both HD and peritoneal dialysis, and those with a functioning kidney transplant. There were no formal inclusion/exclusion criteria.

MAIN OUTCOME MEASURES

The Kidney PREM has 38 questions in 13 subscales. Responses were captured using a 7-point Likert scale (never 1, always 7). The primary outcome of interest was the mean PREM score calculated across all questions. Multilevel modelling was used to determine the proportion of variation of the mean PREM score across centres due to patient-related and centre-related factors.

RESULTS

There were records for 8253 HD patients (61% men, 77% white) from 69 renal centres (9-710 patients per centre). There was significant variation in mean PREM score across centres (5.35-6.53). In the multivariable analysis there was some variation in relation to both patient- and centre-level factors but these contributed little to explaining the overall variation. However, multilevel modelling showed that the overwhelming proportion of the explained variance (45%) was explained by variation between centres (40%), only a small proportion of which is identified by measured factors. Only 5% of the variation was related to patient-level factors.

CONCLUSIONS

Centre rather than patient characteristics determine the experience of care of patients receiving HD. Further work is required to define the characteristics of the treating centre which determine patient experience.

Hemodialysis as long term treatment: Patients satisfaction and its impact on quality of life

Objective:

To determine the level of satisfaction as hemodialysis a long term treatment and quality of life in patients off End Stage Kidney Disease ESKD on hemodialysis.

Methods:

A cross-sectional study was carried out from January to April 2019 in hemodialysis unit of Lahore General Hospital on 141 ESKD patients by using self-designed questionnaire after informed consent.

Results:

Majority (82.56%) of the participants were satisfied with the care provided at the dialysis center. except with the time spent with doctor and 36.9% were not satisfied with their cannulation technique for dialysis. About 89.9% were satisfied with the knowledge provided to them about self-care. Satisfaction is subjective well-being in different aspects of life, including mental health and behavior of people experiencing serious health concerns. Quality of Life (QOL) is defined as “perception of one’s position in life, in the light of his culture and customs, consisting someone’s goals, standards or expectations. Financial problems to the patient was limited to the transportation as dialysis session and erythropoietin were free, but 54.1% of the patients were unable to earn due to their disease even those who were working ,80% of them had to take the day off for dialysis. The financial burden and debilitating illness didn’t cause separation/divorce from spouse but led to increased frequency of scuffles. Among the unmarried population, 40% of it does not want to start a relationship and 40% is facing difficulties in finding a partners while 97.9% of the population is satisfied with the psychological and emotional support of family.

Conclusion:

Most patients were satisfied with their decision of opting hemodialysis as treatment and care provided at dialysis centre, although Quality of Life was badly affected in terms of financial and psycho-social aspects. Employed, married with good income have good quality of life. Loopholes of unit environment and health education were also exposed. Despite the medical advancement and emerging techniques to make dialysis better, the outcome of hemodialysis has yet to reach a safe level and more work should be done to improve patient’s outcome.

Using Patient Experience Survey Data to Improve In-Center Hemodialysis Care: A Practical Review

Patient experience is an integral aspect of the care we deliver to our dialysis patients. Standardized evaluation of patient experience with in-center hemodialysis started in the United States in 2012 with the In-Center Hemodialysis Consumer Assessment of Healthcare Providers and Systems (ICH CAHPS) survey. Over time there have been a few changes to this survey, how it is administered, and how it fits within the Centers for Medicare & Medicaid Services End-Stage Renal Disease Quality Incentive Program. Although the importance of this survey has been growing, knowledge of this survey among nephrologists has lagged. We provide a review of the survey development and how its use has evolved since 2012. We discuss in detail research done on this survey to date, including survey psychometric evaluation. We highlight gaps in our knowledge that need further research and end with general recommendations to improve patient experience within hemodialysis facilities, which we believe is a worthy goal for all members of the dialysis team.

Long-term Clinical Outcomes Among Responders and Nonresponders to the In-Center Hemodialysis Consumer Assessment of Healthcare Providers and Systems (ICH CAHPS) Survey

Rationale & Objective

The In-Center Hemodialysis Consumer Assessment of Healthcare Providers and Systems (ICH CAHPS) survey, introduced into the End-Stage Renal Disease Quality Incentive Program, is the only patient-reported outcome currently used for value-based reimbursement in dialysis. Current response rates are ∼30% and differences in long-term clinical outcomes between survey responders and nonresponders are unknown.

Study Design

Retrospective cohort study.

Setting & Participants

Patients from all Dialysis Clinic Incorporated facilities from across the United States who met survey eligibility (aged ≥18 years and had been treated at their facility for at least 3 months).

Exposures

Patient-level demographic, clinical, and treatment-related characteristics.

Outcomes

Mortality, all-cause hospitalization, and kidney transplantation.

Analytical Approach

Time-to-event analyses using competing-risks models. Sensitivity analyses performed after multiple imputation for missing covariate data.

Results

Among 10,395 eligible patients, 3,794 (36%) responded to the survey. During a median follow-up of 33 months, 4,588 patients died, 7,638 patients were hospitalized at least once, and 789 patients received a transplant. In multivariable models, survey response was associated with lower mortality (subdistribution hazard ratio [sHR], 0.80; 95% CI, 0.75-0.86) and hospitalization (sHR, 0.94; 95% CI, 0.89-0.99) and higher likelihood for a kidney transplant (sHR, 1.27; 95% CI, 1.10-1.46). Results were consistent across sensitivity analyses after multiple imputation for missing covariates.

Limitations

Small amount of missing covariate data, baseline covariate data assigned at the first month of the 3-month survey administration period, reasons for nonresponse unknown.

Conclusions

Response to the ICH CAHPS survey is associated with lower risk for mortality and hospitalization and higher likelihood for kidney transplantation. These findings suggest that survey responders are healthier than nonresponders, emphasizing the need for caution when interpreting facility-level survey results to inform quality improvement and public policy efforts and the critical need to better capture patient-reported outcomes from more vulnerable patients.

An integrated model using the Taguchi method and artificial neural network to improve artificial kidney solidification parameters

BACKGROUND

Hemodialysis mainly relies on the "artificial kidney," which plays a very important role in temporarily or permanently substituting for the kidney to carry out the exchange of waste and discharge of water. Nevertheless, a previous study on the artificial kidney has paid little attention to the optimization of factors and levels for reducing the solidification of the artificial kidney during the hemodialysis procedure. Thus, this study proposes an integrated model that uses the Taguchi method, omega formula, and back-propagation network to determine the optimal factors and levels for addressing this issue.

METHODS

First, we collected the recommendations of medical doctors and nursing staff through a small group discussion, and used the Taguchi method to analyze the key factors at different levels. Next, the omega formula was used to convert the analysis results from the Taguchi method to assess the defect rate. Finally, we utilized back-propagation network algorithms to predict the optimal factors and levels for artificial kidney solidification, in order to confirm that the key factors and levels identified can effectively improve the solidification rate of the artificial kidney and thereby enhance the effect of hemodialysis.

RESULTS

The research finding proposes the following as the optimal factors and levels for artificial kidney solidification: the amount of anticoagulation should be set at 500 units, the velocity of blood flow at 300 ml/min, the dehydration volume at 2.5 kg, and the vascular access type as autologous blood vessels. We obtained 270 sets of data from the patients of End Stage Renal Disease (ESRD) under the setting of the optimal combination of the factors at different levels; the defect rate of artificial kidney solidification is 12.9%, which is better than the defect rate of 32% in the original experiment. Meanwhile, the patient characteristics for physiological status in BMI, serum calcium, hematocrit, ferritin, and transferrin saturation percentage are improved by this study.

CONCLUSION

This conclusion validates the ability of the proposed model in this study to improve the solidification rate of the artificial kidney, thereby confirming the model's use as a standard operation procedure in the hemodialysis experiment. The ideas behind and the implications of the proposed model are further discussed in this study.