Variations of the quality of care during the COVID-19 pandemic affected the mortality rate of non-COVID-19 patients with hip fracture

  1. Davide Golinelli
  2. Francesco Sanmarchi
  3. Angelo Capodici
  4. Giorgia Gribaudo
  5. Mattia Altini
  6. Simona Rosa
  7. Francesco Esposito
  8. Maria Pia Fantini
  9. Jacopo Lenzi

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Abstract

As COVID-19 roared through the world, governments worldwide enforced containment measures that affected various treatment pathways, including those for hip fractures (HFs). This study aimed to measure process and outcome indicators related to the quality of care provided to non-COVID-19 elderly patients affected by HF in Emilia-Romagna, a region of Italy severely hit by the pandemic.

Methods

We collected the hospital discharge records of all patients admitted to the hospitals of Emilia-Romagna with a diagnosis of HF from January to May in the years 2019 (pre-pandemic period) and 2020 (pandemic period). We analyzed surgery rate, surgery delays, length of hospital stay, timely rehabilitation, and 30-day mortality for each HF patient. We evaluated monthly data (2020 vs. 2019) with the chi-square and t-test, where appropriate. Logistic regression was used to investigate the differences in 30-day mortality.

Results

Our study included 5379 patients with HF. In April and May 2020, there was a significant increase in the proportion of HF patients that did not undergo timely surgery. In March 2020, we found a significant increase in mortality (OR = 2.22). Male sex (OR = 1.92), age ≥90 years (OR = 4.33), surgery after 48 hours (OR = 3.08) and not receiving surgery (OR = 6.19) were significantly associated with increased mortality. After adjusting for the aforementioned factors, patients hospitalized in March 2020 still suffered higher mortality (OR = 2.21).

Conclusions

There was a reduction in the overall quality of care provided to non-COVID-19 elderly patients affected by HF, whose mortality increased in March 2020. Patients’ characteristics and variations in processes of care partially explained this increase. Policymakers and professionals involved in the management of COVID-19 patients should be aware of the needs of patients with other health needs, which should be carefully investigated and included in future emergency preparedness and response plans.

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  1. Version published to 10.1371/journal.pone.0263944
  2. ScreenIT

    SciScore for 10.1101/2021.11.27.21266927: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableWe excluded non-residents in Emilia-Romagna, transfers from other hospitals, polytraumas (diagnosis-related group 484–487), diagnoses or history of malignant tumors (ICD-9-CM code 140.0–208.9, 238.6, V10), and cases of COVID-19 using the criteria issued on March 10, 2020 by Italy’s Ministry of Health (ICD-9-CM code V01.82, 079.82, 480.3, V07.0).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All analyses were performed using SPSS 26.0 (IBM Corp.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    Armonk, NY: IBM Corp) and Stata 15 (StataCorp. 2017. Stata Statistical Software: Release 15.
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Strengths and limitations: Analysis of complete data related to the whole healthcare system of a wide region is the main strength of this study. Moreover, the Italian experience during the first wave of the COVID-19 pandemic represents a teachable event illustrating the healthcare system early response to a severe health crisis. Misreporting and misclassification of COVID-19 cases and deaths is the main limitation of our study. However, we relied upon the ICD-9-CM classification system issued by Italy’s Ministry of Health and Regional Authorities for the correct identification of COVID-19 cases and deaths. Other limitations are common to all studies based on administrative data, including lack of accuracy and differences in the coding criteria over time, but it is hard to believe that such potential sources of information bias might have significantly affected our estimates.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.11.27.21266927v1 on medRxiv