Dataset Information

Patient and treatment characteristics associated with patient activation in patients undergoing hemodialysis: a cross-sectional study.

ABSTRACT:

Background

Patient activation is associated with better outcomes and lower costs. Although the concept is widely investigated, little attention was given to patient activation and its predictors in patients undergoing hemodialysis. Hence, we aimed to investigate the level of patient activation and aimed to determine patient- and treatment-related predictors of activation in patients undergoing hemodialysis.

Methods

This cross-sectional observational study recruited patients undergoing hemodialysis in three Flemish hospitals. Participants were questioned about patient characteristics (i.e., age, sex, education, employment, children, social support, leisure-time, living condition, and care at home), treatment- and health-related characteristics (i.e., hospital, time since first dialysis, transplantation, self-reported health (EQ-VAS) and depressive symptoms (PHQ-2)), and patient activation (PAM-13). Univariate and multiple linear regression analyses with dummy variables were conducted to investigate the associations between the independent variables and patient activation.

Results

The average patient activation-score was 51. Of 192 patients, 44% patients did not believe they had an important role regarding their health. Multiple linear regression showed that older patients, who reported being in bad health, treated in a particular hospital, without leisure-time activities, and living in a residential care home, had lower patient activation. These variables explained 31% of the variance in patient activation. Based on literature, we found that activation of patients on hemodialysis is low, compared to that of other chronic patient groups.

Conclusion

It could be useful to implement patient activation monitoring, since the level of activation is low in patients undergoing hemodialysis. Older patients, who reported being in bad health, treated in a particular hospital, without leisure-time activities, living in a residential care home, are at higher risk for lower activation.

SUBMITTER: Van Bulck L

PROVIDER: S-EPMC5984733 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Publications

Patient and treatment characteristics associated with patient activation in patients undergoing hemodialysis: a cross-sectional study.

Van Bulck Liesbet L Claes Kathleen K Dierickx Katrien K Hellemans Annelies A Jamar Sofie S Smets Sven S Van Pottelbergh Gijs G

BMC nephrology 20180601 1

<h4>Background</h4>Patient activation is associated with better outcomes and lower costs. Although the concept is widely investigated, little attention was given to patient activation and its predictors in patients undergoing hemodialysis. Hence, we aimed to investigate the level of patient activation and aimed to determine patient- and treatment-related predictors of activation in patients undergoing hemodialysis.<h4>Methods</h4>This cross-sectional observational study recruited patients underg ...[more]

PMID: 29859047

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Project description:ObjectivesTo 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).DesignAnalysis 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).SettingNational survey of patients with advanced kidney disease receiving treatment with maintenance HD in UK renal centres in 2018.ParticipantsThe 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 measuresThe 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.ResultsThere 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.ConclusionsCentre 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.

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Project description:Although dialysis patients are at high risk of stroke and have a high burden of cognitive impairment, there are few reports of anatomic brain findings in the hemodialysis population. Using magnetic resonance imaging of the brain, we compared the prevalence of brain abnormalities in hemodialysis patients with that in a control population without known kidney disease.Cross-sectional cohort.45 maintenance hemodialysis patients and 67 controls without reported kidney disease, both without history of known stroke.The primary predictor was dialysis status. Covariates included demographics (age, race, and sex), vascular risk factors (diabetes and hypertension), and cardiovascular disease (coronary artery disease and congestive heart failure).Magnetic resonance imaging of the brain features, including severity of white matter disease and cerebral atrophy (sulcal prominence and ventricular atrophy), hippocampal size, and small-/large-vessel infarcts.Semiquantitative scale (0-9 for white matter disease and cerebral atrophy, 0-3 for hippocampal size) and infarct prevalence.Mean ages of hemodialysis patients and controls were 55 ± 17 (SD) and 53 ± 13 years, respectively. In comparison to controls, hemodialysis patients had more severe white matter disease (1.6 vs 0.7) and cerebral atrophy (sulcal prominence, 2.3 vs 0.6; ventricular enlargement, 2.3 vs 0.9; hippocampal size, 1.3 vs 1.0), with all P < 0.001. In multivariable analyses, hemodialysis status was associated independently with worse white matter disease and atrophy grades. Hemodialysis patients also had a higher prevalence of small- (17.8%) and large- (7.8%) vessel infarcts than controls (combined, 22% vs 0%; P < 0.001).The dialysis cohort likely is healthier than the overall US hemodialysis population, partly limiting generalizability.Hemodialysis patients have more white matter disease and cerebral atrophy compared with controls without known kidney disease. Hemodialysis patients also have a high prevalence of unrecognized infarcts.

Dataset Information

Patient and treatment characteristics associated with patient activation in patients undergoing hemodialysis: a cross-sectional study.

Background

Methods

Results

Conclusion

Publications

Patient and treatment characteristics associated with patient activation in patients undergoing hemodialysis: a cross-sectional study.

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