ArticleHealth science reports2025
Measuring Health System Resilience During the COVID-19 Pandemic Using Dynamic Indicators of Resilience Based on Sick-Leave Data.
Article in Health science reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Aims: Healthcare system resilience is generally understood as the capacity of a healthcare system to prepare, withstand, and adapt to disruptive health events while maintaining the continuity and quality of essential health services. So-called dynamic indicators of resilience (DIORs) allow us to examine resilience by analysing patterns of functioning of the healthcare system in time series data. The aim of this study was to examine whether DIORs can be estimated from time series data of the functioning of the Dutch healthcare system before, during and after the COVID-19 pandemic, and whether these DIORs are indicative of the resilience of the Dutch healthcare system during the COVID-19 pandemic. Methods: To select a measure of healthcare functioning, healthcare experts completed a questionnaire in which they selected the five most relevant indicators of healthcare availability (table s14). Based on the questionnaire results and datasets available, time series data of sick-leave absenteeism rates among Dutch healthcare workers before, during and after the COVID-19 pandemic were used to quantify the functioning of the Dutch healthcare system. DIORs were estimated using moving window techniques on the time series data of each healthcare sector, each safety region in the Netherlands, and all healthcare sectors and safety regions in the Netherlands combined. Results: Short-term sick-leave increased from 3.2% to 4.5% and long-term from 3.0% to 4.0% post-pandemic ( Conclusion: Our results indicate that DIORs, estimated from time series data of sick-leave absenteeism rates among healthcare workers in the Netherlands during the COVID-19 pandemic, potentially provide useful insights into healthcare system's resilience during and following disruptive health events, such as the COVID-19 pandemic.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.