Treatment of kidney disease: an analytical decision model at a Swiss university hospital

Abstract Background An observational hospital-based cohort study, where the kidney disease staging is identified as a digital marker, and the association between the standardised staging of Kidney Disease (KD) and the outcomes is assessed along the treatment process. Methods The clinical and administrative data for all patients are stored in the Clinical Data Warehouse. A specific digital marker for an exact KD staging is applied. Three retrospective patient cohorts for exact and imprecise staging and missing diagnosis are defined and compared regarding the in-hospital mortality, all-cause mortality and disease progression. Results In total, 83146 hospitalisations of 40421 patients with KD, treated in 2014-2023 (2016-2023 will be updated) were identified; the number of the first hospitalisations with exact staging was 847 (2%), unprecise 29934 (72%) and missing diagnosis (26%). The demographic and baseline factors distribution between groups was tested with no association (chi-squared test statistic). The median survival time with a 95% CI was 7.94 (7.66, 8.81) years for the exact and 7.47 (7.42, 7.53) for the imprecise staging group. A log-rank and loglikelihood tests indicated a significant difference in survival between the groups, p < 0.0001. The Cox regression model shows a statistically significant difference in Hazard Ratio; KD staging, age, Elixhauser van Walraven index, treatment, nephrotoxic medication, contrast agent application, and AKI were identified as the significant covariates, C-statistic 0.730, Likelihood ratio test, Wald test, log-rank score on 42 df, p < 2e-16. ANOVA analysis confirmed a significant difference in cost distribution between the groups. An economic decision model proposal integrates the findings, combining a profile-level Markov cohort with a Discreet Time-To-Event Simulation DICE. Conclusions The study demonstrates a better outcome regarding all-cause mortality, in-hospital mortality, and costs if a standardised KD staging was applied. Key messages • Intuition (clinical judgement) and standardised kidney disease staging perform differently regarding clinical outcomes and costs. • The study demonstrates a better outcome regarding all-cause mortality, in-hospital mortality, and costs if a standardised KD staging was applied.

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Journal
European Journal of Public Health
Published
2024-10-28
DOI
https://doi.org/10.1093/eurpub/ckae144.1042
Primary Topic
Healthcare Operations and Scheduling Optimization
Type
article
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article

Treatment of kidney disease: an analytical decision model at a Swiss university hospital

Karen Triep, Christos Theodoros Nakas, Martin Fiedler, Olga Endrich et al.
European Journal of Public Health
Healthcare Operations and Scheduling Optimization
article

Treatment of kidney disease: an analytical decision model at a Swiss university hospital

Karen Triep, Christos Theodoros Nakas, Martin Fiedler, Olga Endrich, Markus Messerli
article en

Abstract

Abstract Background An observational hospital-based cohort study, where the kidney disease staging is identified as a digital marker, and the association between the standardised staging of Kidney Disease (KD) and the outcomes is assessed along the treatment process. Methods The clinical and administrative data for all patients are stored in the Clinical Data Warehouse. A specific digital marker for an exact KD staging is applied. Three retrospective patient cohorts for exact and imprecise staging and missing diagnosis are defined and compared regarding the in-hospital mortality, all-cause mortality and disease progression. Results In total, 83146 hospitalisations of 40421 patients with KD, treated in 2014-2023 (2016-2023 will be updated) were identified; the number of the first hospitalisations with exact staging was 847 (2%), unprecise 29934 (72%) and missing diagnosis (26%). The demographic and baseline factors distribution between groups was tested with no association (chi-squared test statistic). The median survival time with a 95% CI was 7.94 (7.66, 8.81) years for the exact and 7.47 (7.42, 7.53) for the imprecise staging group. A log-rank and loglikelihood tests indicated a significant difference in survival between the groups, p < 0.0001. The Cox regression model shows a statistically significant difference in Hazard Ratio; KD staging, age, Elixhauser van Walraven index, treatment, nephrotoxic medication, contrast agent application, and AKI were identified as the significant covariates, C-statistic 0.730, Likelihood ratio test, Wald test, log-rank score on 42 df, p < 2e-16. ANOVA analysis confirmed a significant difference in cost distribution between the groups. An economic decision model proposal integrates the findings, combining a profile-level Markov cohort with a Discreet Time-To-Event Simulation DICE. Conclusions The study demonstrates a better outcome regarding all-cause mortality, in-hospital mortality, and costs if a standardised KD staging was applied. Key messages • Intuition (clinical judgement) and standardised kidney disease staging perform differently regarding clinical outcomes and costs. • The study demonstrates a better outcome regarding all-cause mortality, in-hospital mortality, and costs if a standardised KD staging was applied.

European Journal of Public HealthVol. 34(Supplement_3)
University of Thessaly (GR), University Hospital of Bern (CH), Zimmer Biomet (United States) (US), Health Information Management (BE)
Good health and well-being
Openalex Percentile: Top 67%
Healthcare Operations and Scheduling Optimization
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