Literature DB >> 24052459

Variation in centre-specific survival in patients starting renal replacement therapy in England is explained by enhanced comorbidity information from hospitalization data.

James Fotheringham1, Richard M Jacques, Damian Fogarty, Charles R V Tomson, Meguid El Nahas, Michael J Campbell.   

Abstract

BACKGROUND: Unadjusted survival on renal replacement therapy (RRT) varies widely from centre to centre in England. Until now, missing data on case mix have made it impossible to determine whether this variation reflects genuine differences in the quality of care. Data linkage has the capacity to reduce missing data.
METHODS: Modelling of survival using Cox proportional hazards of data returned to the UK Renal Registry on patients starting RRT for established renal failure in England. Data on ethnicity, socioeconomic status and comorbidity were obtained by linkage to the Hospital Episode Statistics database, using data from hospitalizations prior to starting RRT.
RESULTS: Patients with missing data were reduced from 61 to 4%. The prevalence of comorbid conditions was remarkably similar across centres. When centre-specific survival was compared after adjustment solely for age, survival was below the 95% limit for 6 of 46 centres. The addition of variables into the multivariable model altered the number of centres that appeared to be 'outliers' with worse than expected survival as follows: ethnic origin four outliers, socioeconomic status eight outliers and year of the start of RRT four outliers. The addition of a combination of 16 comorbid conditions present at the start of RRT reduced the number of centres with worse than expected survival to one.
CONCLUSIONS: Linked data between a national registry and hospital admission dramatically reduced missing data, and allowed us to show that nearly all the variation between English renal centres in 3-year survival on RRT was explained by demographic factors and by comorbidity.

Entities:  

Keywords:  data linkage; open data; performance measures; renal replacement therapy; survival

Mesh:

Year:  2013        PMID: 24052459     DOI: 10.1093/ndt/gft363

Source DB:  PubMed          Journal:  Nephrol Dial Transplant        ISSN: 0931-0509            Impact factor:   5.992


  10 in total

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2.  Primary kidney disease modifies the effect of comorbidities on kidney replacement therapy patients' survival.

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Authors:  Nitin V Kolhe; Andrew W Muirhead; Sally R Wilkes; Richard J Fluck; Maarten W Taal
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5.  Weekend admissions may be associated with poorer recording of long-term comorbidities: a prospective study of emergency admissions using administrative data.

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6.  Do routine hospital data accurately record comorbidity in advanced kidney disease populations? A record linkage cohort study.

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Journal:  BMC Nephrol       Date:  2021-03-17       Impact factor: 2.388

7.  A breakthrough series collaborative to increase patient participation with hemodialysis tasks: A stepped wedge cluster randomised controlled trial.

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8.  One- and 2-Year Mortality Prediction for Patients Starting Chronic Dialysis.

Authors:  Mikko Haapio; Jaakko Helve; Carola Grönhagen-Riska; Patrik Finne
Journal:  Kidney Int Rep       Date:  2017-06-24

9.  Effect of weekend admission on mortality associated with severe acute kidney injury in England: A propensity score matched, population-based study.

Authors:  Nitin V Kolhe; Richard J Fluck; Maarten W Taal
Journal:  PLoS One       Date:  2017-10-10       Impact factor: 3.240

10.  Declining comorbidity-adjusted mortality rates in English patients receiving maintenance renal replacement therapy.

Authors:  Benjamin C Storey; Natalie Staplin; Charlie H Harper; Richard Haynes; Christopher G Winearls; Raph Goldacre; Jonathan R Emberson; Michael J Goldacre; Colin Baigent; Martin J Landray; William G Herrington
Journal:  Kidney Int       Date:  2018-02-12       Impact factor: 10.612

  10 in total

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