Impact of COVID-19 on Key Performance Indicators of the National Hip Fracture Database and the Management of Hip Fracture Patients

Waterman, Jennifer  L; Jayaraju, Ullas; Nadimi, Joshua K; Morgan, David

doi:10.7759/cureus.20575

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…Many specific COVID-related clinical endpoints or specific organizational Key Performance Indicators (KPI) have been analysed in the literature ( 16 , 17 ) but, mostly, they focus on few specific points of the clinical pathway or the organizational workflow ( 18 ). More comprehensive approaches able to consider the entire clinical pathways are emerging thanks to a crossover between methods coming from Business Process Analysis and Machine Learning.…”

Section: Introductionmentioning

confidence: 99%

A differential process mining analysis of COVID-19 management for cancer patients

et al. 2022

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During the acute phase of the COVID-19 pandemic, hospitals faced a challenge to manage patients, especially those with other comorbidities and medical needs, such as cancer patients. Here, we use Process Mining to analyze real-world therapeutic pathways in a cohort of 1182 cancer patients of the Lausanne University Hospital following COVID-19 infection. The algorithm builds trees representing sequences of coarse-grained events such as Home, Hospitalization, Intensive Care and Death. The same trees can also show probability of death or time-to-event statistics in each node. We introduce a new tool, called Differential Process Mining, which enables comparison of two patient strata in each node of the tree, in terms of hits and death rate, together with a statistical significance test. We thus compare management of COVID-19 patients with an active cancer in the first vs. second COVID-19 waves to quantify hospital adaptation to the pandemic. We also compare patients having undergone systemic therapy within 1 year to the rest of the cohort to understand the impact of an active cancer and/or its treatment on COVID-19 outcome. This study demonstrates the value of Process Mining to analyze complex event-based real-world data and generate hypotheses on hospital resource management or on clinical patient care.

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Section: Introductionmentioning

confidence: 99%

A differential process mining analysis of COVID-19 management for cancer patients

et al. 2022

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“…In our study, the LOS increased by 2% contrary to the decrease of LOS in studies from other countries. 7 21 28 29 This is probably because South Korea’s quarantine policy to actively detect infected patients might have reduced the fear COVID-19 could be transmitted during the hospitalization.…”

Section: Discussionmentioning

confidence: 99%

Analysis of the Effects of COVID-19 on Hip Fractures in Korea Without Lockdown: Interrupted Time Series Analysis Using a Nationwide Cohort

et al. 2023

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Background The purpose of this study was to investigate the change in the incidence rate, length of hospital stay (LOS), in-hospital mortality rate, and surgical method of hip fractures during the coronavirus disease 2019 (COVID-19) pandemic in South Korea where lockdown restrictions were not implemented. Methods We calculated the expected values of the incidence of hip fractures, in-hospital mortality and LOS of hip fracture patients in 2020 (COVID period) based hip fracture database of the Korean National Health Insurance Review and Assessment (HIRA) during a 9-year period from 2011 to 2019 (pre-COVID period). A generalized estimating equation model with Poisson distribution and logarithmic link function was used to estimate adjusted annual percent change (PC) of incidence rate and 95% confidence intervals (CIs). Then, we compared the annual incidence, in-hospital mortality rate and LOS in 2020 with the expected values. Results The overall incidence rate of hip fracture in 2020 was not significantly different from the expected value (PC, −5%; 95% CI, −13 to 4; P = 0.280). In women, the incidence rate of hip fracture in age groups over 70 years was smaller than the predicted value ( P < 0.001). The in-hospital mortality rate was not significantly different from the expected value (PC, 5%; 95% CI, −8 to 19; P = 0.461). The mean LOS was larger than the expected value by 2% (PC, 2%; 95% CI, 1 to 3; P < 0.001). In intertrochanteric fracture, the proportion of internal fixation was smaller than the predicted value by 2% (PC, −2%; 95% CI, −3 to −1; P < 0.001), and that of hemiarthroplasty was larger than the predicted value by 8% (PC, 8%; 95% CI, 4 to 14; P < 0.001). Conclusions In 2020, the incidence rate of hip fracture did not significantly decrease, and in-hospital mortality rate did not significantly increase compared to the expected rates, which were projected based on the HIRA hip fracture data from 2011 to 2019. Only LOS increased slightly.

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The Impact of COVID-19 on the Prevalence, Mortality, and Associated Risk Factors for Mortality in Patients with Hip Fractures: A Meta-Analysis

Ding

Wei

Wang

2023

Journal of the American Medical Directors Association

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Impact of COVID-19 on Key Performance Indicators of the National Hip Fracture Database and the Management of Hip Fracture Patients

Cited by 3 publications

References 9 publications

A differential process mining analysis of COVID-19 management for cancer patients

A differential process mining analysis of COVID-19 management for cancer patients

Analysis of the Effects of COVID-19 on Hip Fractures in Korea Without Lockdown: Interrupted Time Series Analysis Using a Nationwide Cohort

The Impact of COVID-19 on the Prevalence, Mortality, and Associated Risk Factors for Mortality in Patients with Hip Fractures: A Meta-Analysis

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