Hulleman, D. (Demi) (2021) Combining objective clinical (R3) and subjective post-clinical (BORN) data of burn patients until one year after hospital discharge. thesis, Human Movement Sciences.
Full text available on request.Abstract
Introduction: To enable prevention of long term consequences after burns, one should seek for early predictors on specific risks. In the Dutch Burns Repository (R3) patient and injury related variables are collected during hospitalization, and in the Burn Center Outcome Registry the Netherlands (BORN) burn patients participate by filling in nine questionnaires regarding their recovery, at discharge (T0), one week (T1), three months (T2), and twelve months (T3) after hospitalization. Before using this data, the first aim was to get medical ethical approval for combining both datasets, gather the datasets, and restructure them. Hereafter, representativeness of the total dataset was studied, i.e. BORN response rates at all measurement moments, as well as R3 characteristics of non-responders, as it was hypothesized that patients with minor burns would participate shorter in the BORN. Methods: Burn professionals from Groningen, Beverwijk and Rotterdam were contacted to set up the project, write the MEC, and gather the requested R3 and BORN data. This retrospective study used data from June 1, 2018 to December 31, 2019, eventually only using those collected in the Martini Hospital, Groningen. The datasets were restructured and merged. Data analysis consisted of I) calculating response rates per measurement moment and checking the literature based chosen criterium of 60%, and II) performing a binary logistic regression to find predictors for non-response, looking at age, Total Body Surface Area (TBSA) burned, and length of hospital stay. Results: In this study, data of 129 burn patients from Groningen were included. The response rates on the BORN questionnaires at the measurement moments were 84% (T0), 71% (T1), 61% (T2), and 59% (T3), indicating a decrease of response rate over time, and showing that T3 does not meet the criteria of 60%. The binary logistic regression show that TBSA burned is a significant predictor for non-response at T1 (OR= .863, p=.014), T2 (OR=.900, p=.031) and T3 (OR=.824, p=.050), and length of hospital stay at T1 (OR=1.054, p=.024). No other predictors were found. Discussion: Based on the results of this study it can not be confirmed whether time after hospital discharge or patient burden has a higher impact on response rates. Further research should be focused on reproducing the current study with the data of Beverwijk and Rotterdam, on comparison studies of the current dataset and data collected after January 2020, and on the effect of the COVID-19 pandemic on response rates and outcomes of the BORN. Conclusion: The combined dataset of R3 and BORN is representative for the burn population until 3 months after hospital discharge, and the predictors for non-response TBSA burned and length of hospital stay enable encouragement of patients that are more likely to become non-responders. Keywords: Response rate, burn patient, non-response, PROMs, predictors
| Item Type: | Thesis (UNSPECIFIED) |
|---|---|
| Supervisor name: | Mouton, N. and Nieuwenhuis, M. |
| Faculty: | Medical Sciences |
| Date Deposited: | 13 May 2022 10:08 |
| Last Modified: | 13 May 2022 10:08 |
| URI: | https://umcg.studenttheses.ub.rug.nl/id/eprint/3301 |
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