# Hospital Resilience in the Face of Covid-19 in France: A Multilevel Analysis of the Impact of Past Practice Quality on Cancer Surgery Resumption

Noémie Malléjac, Zeynep Or

► To cite this version:

Noémie Malléjac, Zeynep Or. Hospital Resilience in the Face of Covid-19 in France: A Multilevel Analysis of the Impact of Past Practice Quality on Cancer Surgery Resumption. Health Policy, 2025, 155, pp.105309. 10.1016/j.healthpol.2025.105309. hal-05018466

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# Hospital resilience in the Face of Covid-19 in France: A multilevel analysis of the impact of past practice quality on cancer surgery resumption

Noémie Malléjac<sup>a,b,c,*</sup> <sup>□</sup>, Zeynep Or<sup>c,d □</sup>

<figure><img src="image_3.png" /></figure>

## ARTICLE INFO

### Keywords:

- Resilience

- Hospital activity

- Quality

- Organisational innovation

## ABSTRACT

The COVID-19 pandemic disrupted routine hospital services, causing a substantial backlog of surgeries in 2020. This study investigates hospital resilience in resuming activities during the pandemic, focusing on the impact of pre-pandemic adoption of enhanced recovery after surgery protocols (ERAS) in digestive cancer surgery. ERAS involves patient-centered care protocols proven to improve care process and outcomes but are not systematically implemented in hospitals. We define hospital resilience as the ability to maintain and resume surgery levels in the second half of 2020 during the pandemic. Using French national hospital data for digestive cancer surgeries, we categorized hospitals by the intensity of their ERAS volume before the pandemic and estimated a multilevel model allowing to control for hospital characteristics and pandemic conditions in the area they are situated.

Results show that, all else being equal, hospitals that implemented ERAS before the pandemic absorbed the surgical backlog and recovered their pre-pandemic activity level more quickly. High-volume hospitals and specialized cancer centers were also quicker than other hospitals in resuming surgical operations. The findings highlight the differences in care practices across hospitals and the importance of quality protocols in bolstering hospital resilience during health crises. Beyond improving patient outcomes, widespread adoption of such protocols could enhance healthcare resource utilization and help to mitigate broader economic and environmental pressures.

## 1. Background

The Covid-19 pandemic has significantly impacted healthcare facilities and services and affected hospitals' ability to provide care for all types of patients during 2020. This paper uses the Covid-19 pandemic as an exogenous shock affecting the entire healthcare system to examine the factors determining hospital resilience. All hospital departments, even those that did not care for Covid-19 patients, experienced a decline in the number of admissions during the first two waves of the pandemic. This is partly linked to the fact that patients, fearing contagion, avoided hospitals and partly due to the postponement of surgical procedures, as part of a pandemic plan, including for patients with serious conditions [11]. In France, early March 2020, the government asked hospitals to activate their emergency plans (White plans) and introduced a strict lockdown of population between and March and May 2020. White plans - used to deal with a massive influx of victims of an accident, disaster, or

epidemic event - meant that all programmed hospitalisations and surgery were rescheduled, without a clear prioritisation strategy, to free up a maximum number of beds and staff. Therefore, after the lockdown, hospitals had to catch up on a large range of surgeries. While there was a second milder lock-down in November-December 2020 (schools and most workplaces remained open) and white plans were reactivated in some areas, these were more lenient with better prioritisation of essential surgeries. Hence the major "shock" for hospitals was during the first lock-down when the pandemic was new and not predictable. This can have adverse consequences on patients' health outcomes in the short and longer-term [19]. An important concern was patients with cancer, for whom delays in diagnosis and treatment can have a direct impact on survival [28].

During the pandemic, it became clear that the resilience and adaptability of hospitals to maintain healthcare production were essential for the healthcare system. The term "resilience", appeared in

<footnote><sup>a</sup> The French School of Public Health (EHESP), 15 Av. du Professeur Léon Bernard, 35043 Rennes, France</footnote>

<footnote><sup>b</sup> Arènes CNRS (UMR 6051 Arènes) & INSERM (ERL U1309 RSMS), 108 Bd de la Duchesse Anne, 35700 Rennes, France</footnote>

<footnote><sup>c</sup> Institute for Research and Information in Health Economics (IRDES), 21 Rue des Ardennes, 75019 Paris, France</footnote>

<footnote><sup>d</sup> LIRAES (URP 4470) Laboratoire Interdisciplinaire de Recherche Appliquée en Economie de la Santé - Université Paris Cité, 45 rue des Saints-Pères, 75006 Paris, France</footnote>

<footnote>* Corresponding author.
E-mail address: noemie.mallejac@ehesp.fr (N. Malléjac).</footnote>
healthcare literature since the Ebola crisis, has become increasingly relevant with the Covid-19 pandemic [37,38,50]. The concept of resilience refers to the capacity to withstand shocks and cumulative stress, and to adapt to situations while minimizing the negative consequences. For healthcare organisations, it is defined as the capacity to resist and adapt to shocks and structural changes "in a way that allows to (i) sustain required operations, (ii) resume optimal performance as quickly as possible, (iii) transform its structure and functions to strengthen the system, and (iv) (possibly) reduce its vulnerability to similar shocks and structural changes in the future" [20].

The literature on the resilience of healthcare systems and organizations in response to the Covid-19 pandemic is growing exponentially. Initially, the main interest was in comparing healthcare systems' capacity to prevent the spread of the virus or limit the mortality linked to Covid-19. For example, Costa Font et al. [14] compared the Covid-19 mortality rates in different Italian regions (Costa Font, Levaggi, and Turati 2022). They hypothesized that the observed variations in mortality rates revealed the resilience of local healthcare governance by differentiating between centralized (Emilia Romagna and Veneto) and decentralized regions (Lombardy) where competition between public and private hospitals were high [66]. However, assessing resilience only based on Covid-19 mortality or incidence rates can be misleading [15, 67] since the pandemic and the measures to contain it can have other negative consequences on population health and well-being. Moreover, death or case counts do not capture the healthcare system's ability to maintain its essential functions and prevent aggravation of health problems and save lives in longer term [24]. Ensuring the continuity of healthcare services for patients is indeed a significant challenge. Several studies have explored the impact of Covid-19 on healthcare utilization, including both emergency services and elective procedures during the pandemic. They showed that the utilisation of both routine healthcare services and urgent care dropped significantly during the initial phases of the pandemic, which also increased the demand for other mental health related problems [45,48,49,71].

In this paper, we question, in the French context, the relationship between hospitals' resilience and their quality management. We use hospitals' capacity to maintain their volume of digestive cancer surgery as a proxy for their resilience or ability to absorb the pandemic shock during 2020. We focus on digestive cancer surgeries (rectum, colon, pancreas, etc.) for several reasons. First, digestive cancer is a leading cause of morbidity and mortality representing about 30% of the global cancer incidence and 40% of all cancer-related deaths worldwide [63]. Often it can be treated by surgery if diagnosed on time. Hence, patient outcomes depend highly on early diagnosis and timely surgery, making regular access to care a crucial issue.

To approach quality management, we focus on largely consensual patient centered care protocols called Enhanced Recovery After Surgery (ERAS). ERAS protocols modify conventional surgical practices and propose simple pre-, per- and post-operative measures that were shown to be effective in reducing the consequences of surgical stress and helping patients to recover more quickly [16,40]. Systematic information and involvement of patients in their care process, minimisation of surgical stress (less invasive surgical techniques, lighter anaesthesia etc.) and early preparation for discharge are fundamental aspects of this approach. Today, it refers to a patient-centred medical culture with evidence-based care protocols for a surgical specialty developed by a multidisciplinary team [1,25]. Literature has largely demonstrated multiple benefits of ERAS, such as shorter length of stay in hospital, lower readmission and/or complication rates and better patient satisfaction [2,4,44,52,58,59,62,65]. Despite their benefits, the adoption of ERAS protocols in France has been very slow and there are wide variations in their utilisation across hospitals [53].

In this paper, we test the hypothesis that ERAS adoption enhances hospital resilience through multidisciplinary teamwork, better care process and clear patient care pathways. We assume that hospitals that introduced ERAS before the pandemic were better adapted to absorb the

surgical backlog induced by Covid-19 in 2020. Implementing ERAS requires strong teamwork and better management of patient pathways. Shorter lengths of stay, due to less invasive techniques, enable patients to return home quickly, which is especially important during a pandemic. Together, these factors could enhance hospitals' confidence in managing patients and maintaining activity under stress. Digestive surgery is one of the pioneer specialties in ERAS, with well-developed protocols. Moreover, focusing on a specific cancer is appropriate to approach the resilience of surgical teams organised by specialty in hospital.

This paper contributes to the literature by providing new insights into surgical activity during the Covid-19 pandemic and analysing the links between organizational quality innovations like ERAS and hospital resilience. The rest of the paper is organized as follows. The next section describes the empirical strategy and the data used. The results and sensitivity analyses are presented in the third section. We call attention to main limitations of this study before discussing the implications of our results for health policy.

## 2. Methods

### 2.1. Empirical strategy

To assess the resilience or the capacity to resume surgical activity of hospitals, we compare the volume of digestive cancer surgery stays between May (end of the first lockdown) and December 2020, with the average volume of stays in 2018 and 2019 for the same period (May to December). Comparing two identical periods in different years helps avoiding biases related to potential seasonal effects and is a common way to infer the effect of the Covid-19 epidemic [9,41].

The difference in activity volumes can be expressed as:

$$ \Delta_{ij} = Y_{ij20} - \bar{Y}_{ij1819} $$

Where $Y_{ijyear}$ represent the number of digestive cancer surgery admissions at hospital i in local area j between May and December of the corresponding year. The lower the level of activity in 2020 compared to the average of the two previous years, the lower $\Delta_{ij}$ will be). If $\Delta_{ij}$ is positive, it means that hospital i had more surgeries in May to December 2020 compared to the average activity in the same period of 2018 and 2019. The assumption is that the higher $\Delta_{ij}$ is, the more resilient the hospital i is, as it increased its volume of activity quicker in 2020 during the pandemic. We further assume that the capacity of an hospital to recover in 2020 after the first wave of Covid-19 is related to its previous activity volume, surgical capacity (beds) and previous medical practice - measured by the share of patients benefiting from ERAS before the pandemic- and pandemic stress measured by the number of Covid-19 patients in the hospital during this period, controlling for the local epidemiological context in the local area (département) where hospital is located. We use a multilevel regression model to account for the correlation between hospitals' outputs in the same local area (LA), because the prevalence of Covid-19 and public health measures introduced varied across local areas. Multilevel models allow also to control for the unobservable factors at the local area level [27,32]. We estimate the following GLS model for hospital i located in local area j:

$$ \Delta_{ij} = \omega_{oj} + \beta_1 Y_{ij2019} + \beta_2 ERAS + \beta_3 Beds_{ij2019} + \beta_4 Covid_{ij2020} + \beta_5 Status_{ij} + \epsilon_{ij} \quad (1) $$

with

$$ \omega_{oj} = \alpha_0 + \theta ICU_j + \mu_{oj} \quad (2) $$

where $Y_{ij2019}$ is the number of digestive cancer surgeries in 2019 in hospital i in LA j; ERAS corresponds to a categorical variable describing the intensity of ERAS practices in hospital i. This score is equal to 0 for hospitals that did not code any patient as ERAS in digestive cancer
surgery in 2019 and until March 2020. The score is equal to 1 for hospitals with less than 6 per cent of digestive cancer admissions coded as ERAS (1st tertile), 2 if it is between 6 per cent and 20 per cent (2nd tertile), and 3 for hospitals with more than 20 per cent of ERAS admissions (last tertile). The coefficient $β_2$, therefore, represents the estimated effect of the intensity of ERAS care before the pandemic on hospitals' capacity to catch up with digestive cancer surgeries. *Beds*<sub>ij2019</sub> corresponds to the number of surgical beds in hospital *i* in 2019, assuming that this may impact hospital capacity for resuming activity in 2020. Two hospitals with a similar number of admissions but a different number of beds allocated for surgery may have different capacity for recuperation after the lockdown. The variable *Covid*<sub>ij2020</sub> corresponds to the cumulative number of admissions for Covid-19 as the main diagnosis between May and December 2020 in hospital *i* in LA *j*. Finally, we control for hospital status by differentiating between public, private for-profit, private non-profit hospitals, and cancer centers (CLCC) to account for structural differences between hospitals.

At the local area *level*(Eq. (2)), $ω_{0j}$ corresponds to the constant specific to each LA, with $ω_0$ average and $μ_{0j}$ the residual error term that accounts for the unobservable factors that vary between local areas and may impact hospitals' resilience. We controlled for the intensity of the Covid-19 pandemic in the LA by the average monthly number of patients in intensive care units, $ICU_j$. Data on the incidence of digestive cancers on a detailed geographical scale were not available. Furthermore, for the most frequent cancers (breast, prostate, colorectal), incidence data suggest that the variation across regions is small. However, the spatial distribution of mortality for these cancers is more heterogeneous with excess mortality observed in the northern part of France (Santé Publique France, URL: https://www.santepubliquefrance.fr/content/download/104006/1693075?version=5). We considered controlling for the proportion of population over 75 years old in the local area, as a risk factor for cancer [3,23]. However, this variable is highly correlated with the average number of Covid-19 patients in intensive care (approximately 90 per cent) Therefore, we excluded it from the analysis. The random effects model (versus fixed-effects model) is appropriate when the number of groups is high, and/or the sample size within each group is small [10,43]. In the final sample, there are 521 hospitals distributed across 99 local areas, with an average of 9 hospitals per local area. Therefore, a hierarchical model is appropriate to account for group effects. Nevertheless, we also tested a fixed effects model to assess the sensitivity of the results (see table A3 in Appendix).

In France, volume thresholds are used in cancer surgery for strengthening the quality of care since the literature shows that the mortality and postoperative complication rates after cancer surgery are higher in hospitals with low activity volumes [12,22,54]. Concerning digestive cancer surgery, the threshold is set at 30 cases per year, but these thresholds are not always enforced. We tested the impact of excluding hospitals below the activity threshold to ensure that the effect of ERAS is not solely driven by hospital volume. In addition, we checked the robustness of the link between ERAS and hospital resumption of activity by estimating an Interrupted-Time Series (ITS) model and conducting a placebo test (Section 3.3).

## 2.2. Data

The analysis is based on patient data between January 2018 and December 2020 extracted from the national hospital database (PMSI). We identified all digestive surgery stays (both inpatient and day surgeries) for adult patients (>17 years) using cancer diagnostic codes established by the French National Cancer Institute crossed by DRG (Diagnosis Related Group) surgery codes (see Annex A1 for codes used). In PMSI, patients who had a digestive cancer surgery could be coded as ERAS with a dedicated code. Patient level data are aggregated at hospital level for computing, for each hospital, the proportion of digestive cancer stays coded as ERAS to calculate an indicator of ERAS intensity.

Covid-19-related admissions are identified by the diagnostic code U071 as the primary diagnosis. Further data on hospital characteristics (such as the number of beds per discipline) and their geographical location, come from the Administrative Hospital Statistics (SAE) database. Data on local epidemiological situation at the local area (département) level, including the average incidence rate of Covid-19 (per 100,000 inhabitants), the average number of patients in intensive care (per 100,000 inhabitants), and the average number of patients hospitalized for Covid-19 (per 100,000 inhabitants) come from Santé Publique France and Insee. The initial sample consisted of 775 hospitals that performed a digestive cancer surgery in 2018–2020. We restricted the sample to hospitals that performed at least 10 digestive cancer surgeries in 2019 to have a more homogeneous group of hospitals that potentially have an oncological surgery service for digestive cancer (603 hospitals). We further excluded hospitals that started coding ERAS during the pandemic (after March 2020 and in 2021) to minimize the risk of confounding with the assumption that these hospitals would have begun implementing ERAS protocols before the pandemic and it would be misleading to group them with no ERAS hospitals. Our final sample comprises of 521 hospitals.

# 3. Results

## 3.1. Descriptive statistics

The analysis is based on data from 521 hospitals distributed across 99 local areas. Table A1 in Appendix displays the distribution of ownership of the sample. About 40 % of hospitals are private for-profit, 3 % are cancer centers and 47 % are public hospitals (of which one fifth are teaching hospitals). Out of the 521 hospitals, 47 percent (246 hospitals) were practicing ERAS in 2019.

Fig. 1 shows the monthly trends of number of digestive cancer admissions in France in 2018, 2019 and 2020. Patient care follows a seasonal pattern throughout the year, with, a decrease in admissions in August. In 2020, there was a significant drop in the number of stays for digestive cancer in April (a 30 percent drop compared to April 2019). At the national level, this the surgical gap was not recovered by the end of the year, as the number of admissions remained below the monthly averages of the previous years despite the pick up from November 2020.

Source: PMSI MCO 2018–2020

Fig. 2 displays the average number of digestive cancer admissions by hospital per month. Hospitals are classified by their intensity of ERAS as presented earlier. The first observation is that hospitals that had ERAS practice before the epidemic are also those with a high surgical volume

<figure><img src="image_4.png" /><figcaption>Fig. 1. Trends in total number of digestive cancer admissions per month in France.</figcaption></figure>

Note: Total number of stays in France for digestive cancer surgery
<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Average monthly number of surgical stays for digestive cancer by ERAS indicator.</figcaption></figure>

Note: if ERAS = 0 are facilities with no ERAS stays in digestive cancer in 2019, if =1 < 6 % ERAS stays, if =2 between 6 and 20 % and if =3 > 20 % ERAS stays in digestive cancer surgery.

per month: approximately 10 surgical stays compared to 3 for hospitals with no ERAS practice in digestive cancer.

Source: PMSI MCO 2019–2021 - All hospitals

**Table 1** presents descriptive statistics of hospitals, by their ERAS adoption level. The differences in the number of admissions in May-December 2020 and the average of 2019–18 ($\Delta_{ij}$) are negative for all types of hospitals and regardless of their ERAS practices in 2019,

although averages hide significant disparities. More precisely, ERAS 3 hospitals experiencing the smallest decrease (−2.71) and ERAS 1 hospitals the largest (−5.94). Hospitals practicing ERAS tend to be larger and more specialized in digestive cancer care. These hospitals also show a higher average volume of cancer surgery stays, especially for hospitals in the ERAS 3 group (83.51 stays), reflecting a focus on digestive cancer treatment. Additionally, less than 10 percent are under the 30 surgical stays threshold against around 30 percent for hospitals who had not implement ERAS protocols. Amongst the hospitals with the highest ERAS intensity (ERAS = 3, more than 20 percent of patients coded ERAS), 10 percent are affiliated with a Cancer Center (CLCC). Hospitals practicing ERAS for digestive cancer surgeries also have an average of 100 beds for surgery in the hospital, which is 30 beds more than those that do not practice it. Covid-19 patient volumes, in contrast, do not strongly correlate with ERAS levels. ERAS 3 hospitals had a similar Covid-19 patient volume (205.28) as hospitals without ERAS (216.86), though slightly lower than other ERAS categories. In terms of hospital type, private for-profit hospitals are overrepresented in lower ERAS levels, particularly in ERAS 1 (50.6 %). Public hospitals are most common among those without ERAS (56.36 %) and decrease sharply with ERAS adoption, reaching a low at ERAS 2 (33.33 %). Their share rises again at ERAS 3 (46.34 %), suggesting that advanced ERAS practices may be more present in specialized public hospitals At the local area level, the intensity of the pandemic, measured by ICU Covid-19 patients per 100,000 people, remains relatively stable across ERAS levels, with values around 3.1–3.4 patients per 100,000.

Composition of hospitals above volume threshold (with more than 30 stays per year) is quite similar and presented in Appendix Table A2.

## 3.2. Regression results

**Table 2** presents the results of the main regressions. The results in the first column are for the entire sample of hospitals, and the results in the second column are for a sample restricted to hospitals that had minimum 30 cancer surgeries a year. All else being equal, hospitals that were involved more intensely in ERAS protocols before the pandemic (i.e., hospitals with more than 20 percent of digestive cancer surgeries coded as ERAS) appear to resume their activity more quickly. For instance, ERAS3 hospitals had on average 7 more surgeries in May-December 2020 compared to the hospitals that did not use ERAS protocols. The positive coefficients for ERAS intensity suggest a dose-response relationship, where hospitals with a higher percentage of ERAS surgeries experienced quicker recovery in surgical volume. Considering that hospitals in the “+20 % ERAS” group performed, on average, 83 surgeries between May and December 2020 (Table 1). The increase of 6.89 surgeries represents about _8.4 %_ rise in surgical volume which be significant given the life-saving potential of these surgeries.

As expected, the drop in surgery volume in 2020 in a hospital is directly linked to the surgery volume in 2019: hospitals with higher volumes of cancer surgeries before the pandemic experienced a greater absolute reduction in surgical activity in 2020. This suggests that hospitals cancelled programmed surgeries over March-April proportional to their activity volumes. The number of beds for surgery in 2019 is also positively associated with the resumption capacity in 2020 suggesting that hospitals with more beds for surgery in 2019 increased more quickly their volumes. All else being equal, cancer centers increased their surgery volumes faster than others (+10 cases on average). Excluding cancer centers, the type of hospital, i.e., whether the hospital is for-profit, non-profit, or public, is not associated with significant differences in resilience. The number of Covid-19-related admissions in a hospital has no effect on the recovery capacity in cancer. This may suggest that after the first shock (white plan with lock-down), from May 2020 onwards, the organization of cancer surgeries, considered as essential, was less impacted by the organisation of intensive care services for Covid-19 patients which were managed separately. At the local area level, the number of patients in intensive care units has no

<table><caption>**Table 1**
Sample characteristics according to their ERAS practice.</caption><thead><tr><th></th><th>No ERAS</th><th>ERAS = 1</th><th>ERAS = 2</th><th>ERAS = 3</th><th>Total</th></tr></thead><tbody><tr><td>Hospital level</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Volume difference (dependant variable)</td><td>-4.45 (0.82)</td><td>-5.94 (2.038)</td><td>-3.41 (2.12)</td><td>-2.71 (1.56)</td><td>-4.25 (0.68)</td></tr><tr><td><b>Y<sub>ij2020</sub> - Y<sub>ij201918</sub> (Δ<sub>ij</sub>)</b></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Average volume of digestive cancer surgery stays from May to December 2019–18</td><td>35.73 (2.04)</td><td>76.36 (8.04)</td><td>75.43 (6.33)</td><td>83.51 (9.41)</td><td>55.89 (2.61)</td></tr><tr><td><b>Y<sub>ij201918</sub></b></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Number of beds for surgery (2019)</td><td>65.77 (2.91)</td><td>103.66 (8.92)</td><td>96.11 (5.49)</td><td>102.02 (8.81)</td><td>82.23 (2.75)</td></tr><tr><td>Number of Covid-19 patients from May to December 2020</td><td>216.86 (51.45)</td><td>163.78 (22.15)</td><td>190.74 (24.53)</td><td>205.28 (29.11)</td><td>202.52 (28.01)</td></tr><tr><td>Share of public hospitals</td><td>56.36 %</td><td>38.55 %</td><td>33.33 %</td><td>46.34 %</td><td>47.60 %</td></tr><tr><td>Share of private for-profit hospitals (%)</td><td>34.55 %</td><td>50.60 %</td><td>49.38 %</td><td>40.24 %</td><td>40.30 %</td></tr><tr><td>Share of private non-for-profit hospitals</td><td>9.09 %</td><td>8.43 %</td><td>12.35 %</td><td>3.66 %</td><td>9.40 %</td></tr><tr><td>Share of cancer centers (%)</td><td>0 %</td><td>2.41 %</td><td>4.94 %</td><td>9.76 %</td><td>2.68 %</td></tr><tr><td>Share of hospitals above the volume threshold (%)</td><td>6.8 %</td><td>8.8 %</td><td>9.0 %</td><td>8.9 %</td><td>76.19 %</td></tr><tr><td>Local area level</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Average number of patients in ICU for Covid-19 per 100,000 habitants (2020)</td><td>3.16 (0.11)</td><td>3.09 (0.22)</td><td>3.41 (0.23)</td><td>3.41 (0.23)</td><td>3.22 (0.87)</td></tr><tr><td>Number of hospitals</td><td>275</td><td>83</td><td>81</td><td>82</td><td>521</td></tr></tbody></table>

Note: Standard deviations in brackets. Hospitals which introduced for a first time ERAS after 2019 (during pandemics) are excluded.

Source: PMSI MCO data (2018–2020) ° - Restricted to hospitals with at least 10 stays in 2019
<table><caption>**Table 2**
Determinants of hospital's resumption of activity: multilevel model.</caption><thead><tr><th rowspan="2">VARIABLES</th><th colspan="2">Difference in volume between May-December 2020 and the volume of May-December 2018-2019</th></tr><tr><th>All hospitals</th><th>Hospitals above the threshold of 30 stays in 2019</th></tr></thead><tbody><tr><td>Ref: No ERAS between 2019 and 2021<br/>&lt;6 % of ERAS</td><td>3.069*<br/>(1.802)</td><td>2.976<br/>(2.094)</td></tr><tr><td>Between 6 % and 20 % of ERAS</td><td>5.559***<br/>(1.815)</td><td>5.693***<br/>(2.101)</td></tr><tr><td>+20 % of ERAS</td><td>6.897***<br/>(1.699)</td><td>6.542***<br/>(2.166)</td></tr><tr><td>Number of digestive cancer surgeries in 2019 (May to Dec.)</td><td>-0.147***<br/>(0.0135)</td><td>-0.164***<br/>(0.0158)</td></tr><tr><td>Number of beds for surgery in 2019</td><td>0.0302**<br/>(0.0128)</td><td>0.0558***<br/>(0.0163)</td></tr><tr><td>Ref: Public</td><td></td><td></td></tr><tr><td>Private not-for-profit</td><td>1.036<br/>(2.268)</td><td>0.204<br/>(2.544)</td></tr><tr><td>Private for-profit</td><td>-0.935<br/>(1.345)</td><td>-0.183<br/>(1.505)</td></tr><tr><td>Cancer centers</td><td>9.877**<br/>(4.014)</td><td>12.933***<br/>(4.472)</td></tr><tr><td>Number of stays with Covid-19 as main diagnosis (May to Dec. 2020) (hospital)</td><td>-0.000579<br/>(0.00102)</td><td>-0.000822<br/>(0.00109)</td></tr><tr><td>Number of patients in intensive care for Covid-19 per 100,000 people (in local area, May to Dec. 2020)</td><td>-0.468<br/>(0.311)</td><td>-0.547<br/>(0.386)</td></tr><tr><td>Constant</td><td>0.364<br/>(1.481)</td><td>-0.0115<br/>(1.878)</td></tr><tr><td>Number of observations</td><td>521</td><td>397</td></tr><tr><td>Number of local areas</td><td>99</td><td>95</td></tr></tbody></table>

Note: ***p < 0.01, **p < 0.05, *p < 0.1; Standard deviations in parentheses.

Multilevel random-effects regressions at the local area level.

Source: Data derived from the PMSI MCO 2018-2020.

significant effect either.

The results from hospitals above the volume threshold (column 2) confirm the previous findings, with a stronger magnitude of effect for hospitals practicing ERAS. By focusing on hospitals that have significant surgical volumes before the pandemic crisis, we confirm that hospitals that practiced ERAS had a quicker recovery of their activity in 2020. This suggests that even in high volume hospitals ERAS protocols improve efficiency.

### 3.3. Analysis of robustness

We tested the robustness of our results in several ways. To check that the impact we observed is really that of ERAS practices, we performed two placebo tests. First, we estimated the same model but considered hospitals that had not yet implemented ERAS in 2019, i.e. those implemented it from 2021 onwards. We thus created a new ERAS indicator measuring the share of patients treated as ERAS in 2021. 51 hospitals coded practicing ERAS in 2021 and had never coded it before. Among them, 41 were above the threshold of 30 stays per year. The new ERAS_2021 indicator is 0 if the hospital never practiced ERAS between 2019 and 2021 for digestive cancer surgery, same as before, 1 if at most 2 percent of stays were coded ERAS in 2021 (1st tertile), 2 if the share of ERAS stays is from over 2 to 9 percent (2nd tertile), 3 if more than 9 percent of stays were coded ERAS (last tertile). Hospitals that had ERAS practice in 2020 and 2019 were excluded. The assumption is that we should find no impact of ERAS on resilience in 2020, as these hospitals had not yet started practicing it. The results, reported in Table A4, show that the coefficients associated with ERAS are not significant at the 5 %

threshold. These results are reassuring as they indicate that hospitals coded ERAS in 2019 were different than others.

Second, we run a placebo test by applying the same model to estimate the difference in surgery volumes between May-December 2019 and May-December 2018 (Table A5 in Appendix). While hospitals coding ERAS may have increasing volumes, we would expect no or a considerably smaller effect in this period, as there was no external disruption. The results confirm this intuition. We found no significant impact of ERAS on hospitals with high volume (over 30 surgeries per year), while there is a small impact in low-volume hospitals.

We also tested the robustness of the results by estimating an Interrupted Time Series (ITS) model [39] which allow understanding the dynamic impact of pre-existing trends on surgical volume. For this we used monthly surgery data without restricting analysis to a comparison between two similar periods. Details for this model and the results are reported in table A6 (supplementary material) and globally confirm the previous results. Hospitals practicing ERAS in 2019 had an average initial level of about 10 stays per month). There is a stronger upward trend in the number of stays in 2020 for hospitals practicing ERAS. On average, hospitals practicing ERAS more than 20 percent increased the number of stays by 0.12 per month (sum of the trends before and after the pandemic shock)), compared to 0.04 in other hospitals. Overall, these findings confirm that hospitals practicing ERAS had higher initial volume levels, and an upward trend before the pandemic, but experienced a greater decrease in admissions during the pandemic, and a stronger increase in volume compared to other hospitals.

### 4. Limits

The identification of ERAS practices in hospitals is based on patient coding introduced in March 2019. Despite external controls of coding, including ERAS, by regional health agencies (ARS) and the funding bodies (CNAM), there likely to be variation in coding intensity and consistency across hospitals in 2019. The variation in coding practices may lead to an underestimation of the number of ERAS patients in some hospitals. In general, hospitals have an incentive to code ERAS since coding allows hospitals to receive DRG payments regardless of patients' length of stay (LOS). Indeed, in French DRG classification the length of stay is used to determine case severity, hence can impact the payment. ERAS can reduce LOS significantly thanks to less invasive surgical techniques. Hence, for most patients, hospitals would use the coding to ensure full DRG payment but may ignore coding for a few patients when LOS does not impact the tariff. However, we use coding intensity as a proxy for a hospital's capacity to practice ERAS rather than to measure the exact number of patients who benefited from ERAS protocols. Using a categorical variable helps to smooth out differences in coding practices across hospitals.

Pre-existing differences between hospitals practicing ERAS and others may relate to other factors, leading to a potential omitted variable bias. Our ERAS estimate would be biased if a factor explains both ERAS practice in 2019 and the capacity for digestive surgery in 2020. For example, regional differences in digestive cancer incidence could affect surgery volumes independent of hospital organization or performance. Random-effects and fixed-effects models help to control unobserved variables and account for time-invariant heterogeneity across local areas.

The analysis focused on healthcare facilities' recovery ability but does not account for a potential decrease in demand due to the pandemic, which may have kept patients away from hospitals due to fear of contamination. However, foregone care for treatment or surgery for a diagnosed cancer, often life-saving, is expected to be lower than other types of programmed surgery [30,60,69]. We also control for the rate of Covid-19 patients in ICU to adjust for differences in pandemic severity, as public communication in France was heavily focused on daily ICU Covid-19 patient numbers. Finally, data on department level healthcare personnel is unavailable in France. Hence, we could not control for
variations in hospital staffing, which could play a crucial role in resilience and adaptability during the Covid-19 crisis. Hospital fixed effects would partly capture this result.

## 5. Discussion

The Covid-19 pandemic underscored the need for resilient healthcare organisations and professionals who can quickly adapt to new constraints to mitigate its negative impacts. The pandemic disrupted access to care and increased mortality risks for cancer patients. Enhanced Recovery After Surgery (ERAS) protocols proved valuable during this period, as they facilitate faster patient recovery and reduce length of hospital stays, minimizing the risk of Covid-19 exposure due to hospitalization [36,42,44,62]. These outcomes become particularly desirable during the pandemic since the risk of contamination increases with the length of hospitalization. Several qualitative studies examined the novel practices implemented within hospitals to satisfy healthcare needs of non-Covid patients while accommodating a growing number of Covid patients [31,51,68]. Globally, these studies show that healthcare facilities changed their medical practices for increasing day surgeries [13], to reduce lengths of stay and invested in shifting care out of hospitals with more home care and telemedicine [8,17,26].

Our study examined whether hospitals that practiced ERAS protocols before the pandemic had a greater capacity to adapt and resume activity quickly in 2020. Our results show that the capacity to recover during pandemic was influenced by factors such as hospital size and specialty but also by their process quality. Hospitals that had implemented ERAS protocols for digestive cancer surgery before the pandemic were able to increase their volumes more rapidly in 2020 after the lockdown. This supports the idea that integrated patient-centered care approaches, which enforces clear guidelines, better patient information, and better communication among healthcare professionals are also important components of hospital resilience [57]. It is useful to think about resilience not only at the scale of global healthcare system but also at care provider level to understand the local dynamics of healthcare actors [46], and pinpoint issues in different organisations. Hospitals must encounter and manage multiple challenges continuously, adjusting to various technological and social changes. Practical and systematic guidance to enhance hospital resilience in both regular and emergency situations is essential. Barasa et al. [5] proposed the concept of "everyday resilience", emphasizing the importance of available capacities and resources faced by individuals in the daily provision of care [5, 6,21]. This concept of hospital resilience differs from conventional disaster preparedness approaches [7]. Unlike preparedness, which primarily serves in times of big, sudden shocks such as a natural disaster or pandemic, elements contributing to resilience can also improve daily healthcare quality, and vice versa. For instance, it is shown that an adaptive and flexible organisation is an attribute associated with high-performing hospitals and innovation in health care [33,64]. Our results add to this literature by showing that innovative care protocols like ERAS which improve quality of patient care are also associated with enhanced hospital resilience. The enablers for implementing rapid changes during the pandemic can be similar to those required for routine improvements in medical practice.

Moreover, our results indicate that advanced care protocols were primarily implemented in high-volume, specialized hospitals, which is consistent with existing literature linking hospital volume to care quality [12,22,29]. Many countries, including France, use minimum activity thresholds for improving patient care in cancer treatment [18, 55]. Larger hospitals with more resources are better positioned to adopt and sustain new technologies and organizational innovations like ERAS [47,56,61,70]. Ultimately, our results indicate the importance of improving care process by encouraging care providers to engage in continuous quality improvement for improving both care quality and resilience of hospitals. It is important to think about the appropriate financial models to support such organizational innovations.

Implementing new care protocols like ERAS can be costly for healthcare professionals, since they require changing medical routines. This may also involve funding for new health professionals, such as coordinating nurses, and adapting to a rapid turnover in patient stays, which affects workload and hospital organization [34,35]. Current activity-based funding models do not necessarily support the investments needed for changing medical practice routines. Therefore, investments in communication tools to disseminate best practices and evaluation programs to monitor costs, outcomes, and experiences are crucial for sustaining these improvements.

## 6. Conclusion

This study estimated the impact of adopting ERAS protocols for digestive cancer surgery before the pandemic on hospitals' capacity to resume activity in 2020 during Covid-19 pandemic. Our results contribute to the literature on the determinants of hospital resilience by showing that organizational quality innovations such as ERAS can improve the resilience of hospitals. From a health policy perspective, it is important to support the diffusion of these protocols and other organizational innovations that can improve care pathways with adequate funding incentives. Enforcing these protocols is necessary not only to ensure better quality care for all patients but also to improve the efficiency and resilience of the healthcare system.

## Funding

This work is partly funded by Elsan Hospital group via a PhD scholarship program (no. 2018/0965) via the Agence Nationale de la Recherche et de la Technologie (ANRT)

## CRediT authorship contribution statement

Noémie Malléjac: Writing – original draft, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Zeynep Or: Writing – review & editing, Supervision, Methodology, Conceptualization.

## Declaration of competing interest

None.

## Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.healthpol.2025.105309.

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