Impact of the pandemic COVID-19 on the strategy, efficiency and quality of Portuguese public hospitals

Introduction

At the end of December 2019, an unprecedented challenge began with the identification of cases of severe pneumonia of

unknown aetiology, which rapidly progressed to severe acute respiratory syndrome and respiratory fail (1,2). This new pathology has been named coronavirus disease 2019 (COVID-19) by the World Health Organisation (WHO) and has been attributed to the action of the virus known as Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) (2,3). On 11 March 2020, the WHO classified COVID-19 as a pandemic, marking the beginning of a new global pandemic situation (4).

In this challenging context, the healthcare sector has become the epicentre of the COVID-19 pandemic worldwide, which has required an agile response from healthcare organisations in order to develop mechanisms that maintain organisational resilience and enable an effective response to the pandemic (5). To cope with the pandemic, hospital care has played a crucial role in mitigating the effects of the pandemic on the population, especially on the number of deaths (6).

The aims of this article were to quantitatively analyse how the pandemic has affected the technical efficiency of Portuguese public hospitals, according to their organisational and management model, and to analyse the effect of the quality of hospital care on efficiency during the pandemic. On the other hand, it aimed to qualitatively analyse the strategies used by hospital management to mitigate the effect of the pandemic in Portuguese public hospitals.

Background

The COVID-19 pandemic has created unprecedented pressure on hospital care, and one of the main consequences of the pandemic has been the overload, especially of the infectious diseases, pneumology and intensive care units (7-9). Due to the overload of hospital establishments, the population has not been able to access the necessary health care, so direct mortality from COVID-19 and indirect mortality from preventable and treatable problems have increased dramatically (10). The majority of hospital services in many countries around the world have had their activity partially or totally interrupted, which have implemented minimum services with scheduled activity cancelled or suspended (11,12).

In Portugal, the increase in the number of COVID-19 cases and hospital admissions has led to rapid hospital reorganisation, reducing the provision of non-priority healthcare and increasing the capacity to treat critically ill patients (13). Hospital reorganisation led to a partial or total suspension of non-priority elective activity that affected more than 90% of hospital establishments at the start of the pandemic (14). Hospital activity fell significantly, leading to a reduction in the number of face-to-face medical consultations, surgical activity, hospitalisations (medical and surgical) and the number of emergency episodes (15). Hospital admissions in the first phase of the pandemic fell by 57% and the average length of stay and number of deaths in non-COVID-19 inpatients were higher than expected (16). The interruption of elective care to focus on the pandemic has resulted in financial losses and concerns about their ability to provide quality healthcare in the long term. Questioning the need for hospitals to maintain their costs and the quality of their services at a reasonable level to ensure financial stability and the sustainability of their performance (17).

In this way, the issue of efficiency and, consequently, the sustainability of health systems has become more present since governments began looking for solutions, especially for the financing of health systems during the pandemic (9). In the health sector, hospital efficiency has been a major issue of interest due to the significant increase in care costs as a result of the pandemic (18,19). The pandemic has increased the demand for capital and human resources and with the scarcity of resources, it has become imperative to use resources efficiently and effectively (20). Hospital management had to find strategies to keep its costs and the quality of its services at a reasonable level to ensure financial stability and the sustainability of its performance (17). Regardless of the healthcare system, the main goal of governments is for hospitals to be efficient and provide a standard of care that can keep the population in good health, and for this to happen, hospitals need to make efficient use of their resources and, in particular, their budgets (21). This situation has led to an effort to find strategies to maintain quality standards in healthcare (22,23). Efficiency and quality in healthcare are intrinsically linked; quality functions as an external dimension, explaining its effect on levels of (in)efficiency (24,25). The quality of health care and the efficiency of hospital establishments were central themes during the COVID-19 pandemic. The quality of healthcare has been put to the test in several aspects, from basic care to intensive care. One of the most obvious challenges was the ability to provide quality healthcare at a time when hospital care was overloaded.

Rationale and knowledge gap

Portuguese hospitals have been under a lot of pressure due to the pandemic, which has forced hospital managers to make organisational changes in infrastructure, human resources and technology in order to maintain their efficiency and quality of care. The context of high complexity and uncertainty resulting from the COVID-19 pandemic, the measures implemented and the budgetary effort made have promoted the need to evaluate performance, thus constituting one of the central points of this study. In Portugal, the impact of the pandemic on hospital management has not been comprehensively studied, so this study aims to contribute to an analysis of the impact of the pandemic on the performance of Portuguese hospital establishments and the quality of their care. And it aims to contribute to knowledge of the main strategies used to mitigate the effects of the pandemic on hospital care.

Methods

At the time of the study, there were 111 public hospitals in Portugal, excluding military, psychiatric and oncological hospitals and those integrated into the Local Healthcare Units (LHU). The LHU (which resulted from the vertical integration of hospital healthcare with primary healthcare) were excluded because its funding is different from hospitals or hospital centres. LHU costs are also calculated differently. Because of these situations, it is not possible to compare the LHU with hospital establishments (whether single hospitals or hospital centres). The military, psychiatric and oncological hospitals did not offer the same hospital care as the other National Health Service (NHS) hospitals. The aim was to study hospital establishments with the same services so that they could be compared. Therefore, we selected public hospitals that offered the same range of healthcare services, i.e., inpatient care, day hospitals, emergency services, consultations and surgery. The selection of the sample also took into account the criteria of hospital organisation model and management model. With regard to the type of organisation, the sample was made up of single hospitals and hospital centres, these two organisational models that provide health services to the population. We thus obtained 21 hospital centres and 11 single hospitals, giving a final sample of 32 public hospital establishments studied.

Regarding the hospital management model, the sample was composed of 31 hospital establishments (hospital centres and individual hospitals) under Public Enterprise Management (PEM) and one under Public-Private Partnership (PPP)¹ management. This hospital management model is the one that exists in Portuguese public hospitals and differs in terms of its financing. The PEM management model is financed through program contracts signed with the supervisory authority, which define the qualitative and quantitative objectives and goals, their timing, the means and instruments to pursue them. The PPP management model is financed through private and public capital.

Thus, the sample was composed of the following hospital establishments: Centro Hospitalar Barreiro Montijo, PEM (CHBM); Centro Hospitalar do Baixo Vouga, PEM (CHBV); Centro Hospitalar Universitário Cova da Beira, PEM (CHCB); Centro Hospitalar de Entre o Douro e Vouga, PEM (CHEDV); Centro Hospitalar de Leiria, PEM (CHL); Centro Hospitalar Universitário de Lisboa Central, PEM (CHLC); Centro Hospitalar Universitário Lisboa Norte, PEM (CHLN); Centro Hospitalar de Lisboa Ocidental, PEM (CHLO); Centro Hospitalar do Médio Ave, PEM (CHMA); Centro Hospitalar do Médio Tejo, PEM (CHMT); Centro Hospitalar do Oeste, PEM (CHO); Centro Hospitalar Póvoa de Varzim/Vila do Conde, PEM (CHPVVC); Centro Hospitalar de Setúbal, PEM (CHS); Centro Hospitalar Universitário de São João, PEM (CHSJ); Centro Hospitalar de Trás-os-Montes e Alto Douro, PEM (CHTMAD); Centro Hospitalar do Tâmega e Sousa, PEM (CHTS); Centro Hospitalar Tondela Viseu, PEM (CHTV); Centro Hospitalar Universitário do Algarve, PEM (CHUA); Centro Hospitalar e Universitário de Coimbra, PEM (CHUC); Centro Hospitalar Universitário do Porto, PEM (CHUP); Centro Hospitalar de Vila Nova de Gaia/Espinho, PEM (CHVNGE); Hospital de Braga, PEM (HP); Hospital de Cascais Dr. José de Almeida PPP (HC); Hospital Distrital de Santarém, PEM (HDS); Hospital do Espírito Santo de Évora, PEM (HESE); Hospital Distrital da Figueira da Foz, PEM (HFF); Hospital Garcia de Orta, PEM (HGO); Hospital de Loures, PEM (HL); Hospital Professor Doutor Fernando Fonseca, PEM (HPDFF); Hospital Santa Maria Maior, PEM (HSMM); Hospital da Senhora da Oliveira Guimarães, PEM (HSOG); Hospital de Vila Franca de Xira, PEM (HVFX).

The time frame defined for the study was from 2017 to 2021, taking into account the comparison between the pre-pandemic period in Portugal (2017–2019) and the pandemic period (2020–2021).

A mixed methodology was used to verify the effects of the COVID-19 pandemic on the technical efficiency of Portuguese hospitals and how the quality of hospital care influenced efficiency during this period. And, to complement the study, semi-structured interviews were used to analyse aspects related to the strategies adopted by hospital managers to minimise the effect of the pandemic on hospital care.

Quantitative methodology

The data envelopment analysis (DEA) methodology was used in the quantitative component of this study because there is no susceptibility to model specification errors (26). DEA is easily applied to multiple inputs and outputs, which makes it particularly suitable for analysing the technical efficiency of hospital establishments, since they use multiple inputs to produce multiple outputs (27,28). The Variable Returns to Scale (VRS) model was chosen to assess the efficiency of NHS hospital establishments due to the presence of imperfect competition, government regulations and financial restrictions that force hospitals to operate at a sub-optimal scale (29). In addition, the VRS can assess the impact of variations in the size of hospital establishments, assuming a non-linear relationship between inputs and outputs (30). And finally, this model becomes more appropriate in the dynamic environment created by health system reforms (31).

As public hospitals are under pressure to increase the provision of health services, they tend to maximise production with the resources available, so the output-oriented perspective was chosen (31-35). Regardless of the orientation of the perspective, there is always the possibility of model slack due to the uncontrollability of production (36). Thus, the slack-based measurement model (SBM) was used to determine the technical efficiency of the establishments under study. However, a limitation arose for decision making units (DMUs) with a score =1. To resolve this situation, the Andersen and Petersen model was used, which made it possible to measure super-efficiency in order to classify efficient units in rankings for radial models (37). However, the Andersen and Petersen super-efficiency model presented some inconsistencies for the VRS model, so Chen’s modified VRS super-efficiency model was used, which solves the problems of infeasibility that occurred in the traditional super-efficiency model (38). Thus, the super-SBM-VRS model was used so that the fully efficient DMUs (score =1) could be ranked. To summarise, this study used the output-oriented super-SBM-VRS model.

The data used for DEA as inputs were: total cost of hospital activity, and the outputs were: Number of patients discharged from hospitalisation; Total number of day hospital sessions; total number of emergency episodes; total number of consultations carried out; total number of surgeries. The data used in the DEA was collected by consulting the resources provided by the Central Administration of the Health System, I.P. (https://benchmarking-acss.min-saude.pt/) and by the Technical Project Monitoring Unit (https://www.utap.gov.pt/), as well as the Accounts Reports of the hospital establishments (data available on the portal of each establishment) that were the subject of the study.

Beforehand, descriptive statistics were carried out on the DEA scores for each year, including the geometric average, maximum, minimum, coefficient of variation, standard deviation and quartiles. With regard to the quality indicators, the variation of each was calculated for each year in relation to the previous one.

Statistical analysis

As the efficiency scores resulted from the non-parametric DEA test, the Mann-Whitney U-test was used to see if there were any differences between the pre-pandemic and pandemic periods in hospitals and hospital centres. This test has the great advantage of being able to be used in small samples (39), which is the case in this study.

Spearman’s correlation coefficient was used with the efficiency scores and quality indicators to check which quality indicators were associated with variations in hospital efficiency. Spearman’s correlation coefficient was used because it is a non-parametric coefficient, since the efficiency scores of the hospital establishments were determined using a non-parametric technique DEA. This coefficient is not sensitive to asymmetries in the distribution, nor to the presence of outliers, and therefore does not require the data to come from two normal populations.

The following quality indicators were used in this study: hip fractures (surgeries in the first 48 hours); mortality from ischaemic and haemorrhagic strokes (within 30 days of the episode); hospitalisation rate for acute complications of diabetes; hospitalisation rate for hypertension; readmissions within 30 days; post-operative sepsis p/100,000; and pressure ulcer rate. These indicators were selected because they are approved by the Portuguese Ministry of Health and reflect the quality standards of hospital care. The data for the quality indicators was collected by consulting the National Statistics Institute portal (https://www.ine.pt/xportal/xmain?xpgid=ine_main&xpid=INE), the NHS Transparency portal (https://transparencia.sns.gov.pt/explore/?sort=modified) and the hospital accounts reports (data available on the portal of each establishment).

Qualitative methodology

As part of the qualitative component, semi-structured interviews were carried out, using purposive sampling, with members of the boards of directors who held managerial positions in the hospitals with the best efficiency scores, thus complementing the results obtained in the quantitative analysis. The interviewees were selected based on who was in charge at the time of the pandemic, i.e., who had the decision-making and organisational power to deal with the pandemic. Hospital managers were contacted by email, and face-to-face interviews were scheduled with one of the research team members, lasting 30 minutes; those who took more than four months to schedule a meeting were excluded. This resulted in 12 interviews with managers from different hospitals. The interviews provided a deeper understanding of aspects related to the strategies adopted to minimise the effect of the pandemic on hospital care. To find out which factors influenced the hospital’s performance, the hospital managers were asked the following questions:

• What strategy(ies) have been adopted in the health unit to mitigate the effects of the pandemic on production?
• Good coordination between the central authorities (Regional Health Administration and Ministry of Health) and those on the ground is essential if central decisions are to be put into practice. In your opinion, has the coordination between your hospital unit and the Ministry of Health been positive in terms of reorganising and promoting the optimisation of existing resources?

The content of the interviews was analysed using NVivo 14 qualitative data analysis software.

Results

To assess technical efficiency at the organisational level of the hospital establishments under study, DEA methodology was used, using the super-SBM-VRS model. The efficiency scores presented in the following table were calculated using the super-SBM DEA model, which unlike the traditional DEA model, which limits efficiency scores to a range between 0 and 1, the super-SBM model allows efficiency scores to exceed 1. These values represent the relative efficiency of units that are already considered efficient (score =1) according to the traditional DEA approach, providing additional differentiation between highly efficient units. The results were obtained separately for each of the groups (hospitals vs. hospital centres). Table 1 shows descriptive statistics for the hospitals’ efficiency scores during the pre-pandemic and pandemic periods.

In the hospital organisational model, the lowest efficiency score in the pre-pandemic period was in 2019, with a score of 0.446, at Hospital Garcia de Orta, PEM (Table 1). As for the maximum value, this was recorded in 2018 with a score of 1.098, recorded at Braga Hospital, PEM. In the pandemic period, it was also Hospital Garcia de Orta, PEM that registered a minimum efficiency score of 0.475 in 2020. The maximum efficiency score was 1.126, recorded by Hospital do Espírito Santo de Évora, PEM, in 2021 (Table 1). The average value of technical efficiency in the hospital model for 2017, 2018 and 2019 was 0.814, 0.748 and 0.788, respectively. Looking at the figures, there was a decrease in 2018 and 2019 compared to 2017, when the highest figure was recorded. In the pandemic years of 2020 and 2021, the average technical efficiency values were 0.802 and 0.834, respectively (Table 1). During the pandemic, hospital efficiency reversed the downward trend of the previous two years, improving and peaking at 0.834 in 2021 (Table 1). The standard deviation values for the hospital organisational model group in the pre-pandemic and pandemic periods were between 20.1% and 22.3%, indicating a high dispersion of the data in relation to the average (Table 1). Analysing the standard deviation values in the context of this study shows that the dispersion of the technical efficiency scores of this organisational model was high. The coefficient of variation for the hospital model group in the period under study was between 26.3% and 27.2%, with the highest recorded in 2019 (27.2%). The coefficients of variation recorded in the pre-pandemic and pandemic periods were high (≥23%) and very similar, which showed that there was a wide dispersion of results; thus there was a high degree of heterogeneity in technical efficiency scores in the hospital organisation model (Table 1).

Table 2 shows the descriptive statistics of the hospital centres’ efficiency scores during the pre-pandemic and pandemic periods.

Regarding the organisational model of hospital centres, the minimum value of the efficiency scores in the pre-pandemic period was in 2019, with a score of 0.507, at the Centro Hospitalar Universitário Cova da Beira, PEM. As for the maximum value, this was recorded in 2017 with a score of 1.197, at the Coimbra Hospital and University Centre, PEM. In the pandemic period, Centro Hospitalar Universitário Cova da Beira, PEM obtained the minimum efficiency score of 0.513 in 2021. However, the maximum efficiency score was also achieved in 2021 by the Centro Hospitalar Universitário de São João, PEM, with a value of 1.219 (Table 2). The hospital centres model recorded an average technical efficiency value for 2017, 2018 and 2019 of 0.886, 0.855 and 0.876, respectively. For the 2020 and 2021 pandemic years, the average technical efficiency values were 0.875 and 0.842, respectively (Table 2). Comparing the two periods showed that the values were very similar. The standard deviation values for the hospital centres organisational model group in the pre-pandemic and pandemic periods were between 18.8% and 20.7%, indicating a high dispersion of the data in relation to the average (Table 2). The coefficient of variation for the hospital centres model group in the period under study was between 21.5% and 24.2%, with the highest being recorded in 2018 (24.2%) (Table 2). The coefficients of variation recorded in the pre-pandemic and pandemic periods were high (≥23%) and very similar, which showed that there was a wide dispersion of results, thus showing a high degree of heterogeneity in the hospital organisation model.

The Mann-Whitney U-test was used to check for statistically significant differences between the pre-pandemic and pandemic periods in hospitals and hospital centres. The results are shown in Table 3.

As can be seen in Table 3, there was no statistically significant association (ρ value >0.05) between the two time periods for hospitals. Similarly, there was no statistically significant association (ρ value >0.05) between the two periods for hospital centres.

In order to get a better idea of the average technical efficiency values of the two types of hospital organisation over the time periods under study (Figure 1).

Figure 1 Comparison of the average efficiency scores of hospitals and hospital centres.

Table 4 gives an idea of the number and percentage of hospital establishments, according to the management and organisation model, which are efficient according to the DEA model calculated above for each year of the period studied.

Overall, the percentage of efficient hospitals (Table 4) in the pre-pandemic years studied was 54.5%, 27.3% and 45.5%, respectively. In the first year of the pandemic (2020) the percentage of efficient hospitals was 45.5% and in 2021 it increased to 54.5%. In relation to the percentage of efficient hospital centres (Table 4) in the period from 2017 to 2019, these were 52.4%, 47.6% and 57.1% respectively. During the pandemic, in the first year, the percentage of efficient hospital centres was 52.4%, while in 2021 the percentage fell to 42.9%. When comparing the two organisational models, the second year of the pandemic had a greater impact on hospital centres. In terms of the hospital management model, Table 5 shows that in the pre-pandemic years 2017, 2018 and 2019, the percentage of efficient PEM hospitals was 54.8%, 41.9% and 54.8% respectively, while in the same period, the only PPP hospital unit was inefficient. In the pandemic period, 2020 and 2021, the percentage of efficient PEM hospitals was the same (51.6%) and very similar to inefficient hospital establishments (51.6% vs. 48.4%). In 2021, the PPP hospital became efficient.

The average of each quality indicator was calculated for the pre-pandemic period and the pandemic period. Using the average values for each period under study, the variation of each quality indicator in the pandemic period compared to the pre-pandemic period was calculated for each hospital. With the variation in each indicator, it was possible to see which quality indicators had worsened or improved in the hospitals under study (Table 5).

The quality indicators that worsened in the largest number of hospital establishments were: Q1: hip fractures (surgeries in the first 48 hours); Q2: ischaemic and haemorrhagic stroke mortality (in the 30 days following the episode); Q3: hospitalisation rate for acute complications of diabetes; Q6: post-operative sepsis p/100,000; and Q7: pressure ulcer rate (‰) (Table 5). When analysing the quality indicators of hospital care, five worsened and two improved in the majority of hospitals. The indicators that improved in the largest number of hospitals were: Q4: hospitalisation rate for hypertension; and Q5: readmissions within 30 days (Table 5).

Spearman’s correlation was applied to check the relationship between quality indicators and efficiency scores in the pre-pandemic period (Table 6). Spearman’s correlation coefficient measures the strength and direction of a monotonic relationship between two variables. The values range from −1 to +1:

+1: perfect positive correlation (as one variable increases, so does the other).

0: no correlation (no monotonic relationship).

−1: perfect negative correlation (as one variable increases, the other decreases).

Spearman’s correlation was applied to check the relationship between quality indicators and efficiency scores in the pandemic periods (Table 7).

The qualitative analysis aimed not only to map the concrete actions taken by hospital managers, but also to understand the motivations and decision-making processes that underpinned these strategies.

To find out which strategies were adopted, interviewees from the hospital establishments that had maintained or improved their efficiency were asked the following question:

Question 1: What strategy(ies) have been adopted in the health unit to mitigate the effects of the pandemic on production?

Using NVivo 14 software to analyse the answers to this question, 12 segments of text from the interviewees were recorded, which were summarised after coding into 6 recording units (Table 8).

Liaising with the tutelage, i.e., the government and health authorities, was fundamental to guaranteeing a coordinated response to the pandemic. In order to assess whether coordination with the supervisory body has helped to adjust the strategies of each hospital unit, we decided to ask the interviewees the following question.

Question 2: Good coordination between the central authorities (Regional Health Administration and Ministry of Health) and those on the ground is essential if central decisions are to be put into practice. In your opinion, has the coordination between your hospital unit and the Ministry of Health been positive in terms of reorganising and promoting the optimisation of existing resources?

In response to this question, using NVivo 14 software, 10 segments of text from the interviewees were recorded, which were summarised after coding into 2 registration units and 3 registration sub-units (Table 8).

When analysing the interviews in order to understand the strategies adopted to mitigate the effect of pandemic on hospital management, the reallocation of physical spaces to continue producing healthcare was one of the most mentioned strategies (N=3; 25.0%) [e.g., ‘we allocated space and areas for use in other activities.’ (E2); “the ability to transform conventional wards into ‘intensive care units’” (E11)]. Teleconsultations and video consultations were also used (N=3; 25.0%) as a strategy to keep patients followed up during consultations [e.g., ‘our strategy was essentially to follow up patients via telephone contact’ (E1); ‘whenever possible we used computerised means’ (E10)]. The strategy of creating safe circuits to maintain the continuity of care for non-COVID-19 patients (N=2; 16.67%) [e.g., ‘in essence it was creating the circuits’ (E1); ‘the need to create safety circuits’ (E2)] and the extension of opening hours for users (N=2; 16.67%) [e.g., ‘We also resorted to strategies to change the timetable, we increased the opening hours of outpatient consultations’ (E3); ‘the reorganisation of surgery times and the consultation calendar made it possible to reschedule urgent patients’ (E4). ‘The extension of activity hours also contributed to this’ (E8)]. Strategies were adopted to mitigate the effects of the pandemic. The least mentioned strategy for dealing with the pandemic was the creation of work and action procedures (N=1; 8.33%) [e.g., ‘the creation of technical documents, known by all, constituting standards for action’ (E4)] (Table 8).

The majority (N=6; 60.0%) of the interviewees’ perception of the support provided by the authority was positive [e.g., ‘it was a very positive articulation and I see the positive part as being a constant articulation with the Regional Health Administrations (RHA), which I’m referring to is the RHA Lisboa and Vale do Tejo (RHA/LVT).’ (E1); ‘The coordination that RHA/LVT provided during the pandemic was a cornerstone for the success of the whole process.’ (E4)]. The positive aspects were related to the acquisition of materials [e.g., ‘The acquisition of medicines, the acquisition of protective material, the RHA acquired and supplied the hospitals with this material on a weekly basis.’ (E1)] and for the management of available beds [e.g., ‘To analyse the situation of each hospital, each hospital presented the number of COVID-19 patients at these meetings.’ (E1)] and for the management of available beds [e.g., ‘to analyse the situation of each hospital, each hospital at these meetings presented the number of COVID patients, how many entered, how many left’ (E3); ‘It allowed daily knowledge of the reality in the hospitals involved; the management of everyone’s needs in order to effectively help each other (including material, for example) and the management of vacancies.’ (E4)]. On the other hand, some interviewees said that the support from the ministry was negative (N=4; 40.0%) [e.g., ‘It depends, with the RHA it didn’t play a role, that is, it wasn’t significant. In other words, there was no regional coordination.’ (E3); ‘There was no articulation.’ (E5)]. The reasons given were that the standards were created too late, i.e., the standards were not updated quickly enough [e.g., ‘It might have been desirable for the standards to be updated more quickly, with greater flexibility and dialogue, but it was not possible.’ (E2)] (Table 8).

Discussion

The standard deviation values were generally high in both organisational models for the period under study. However, the hospital centre organisational model showed slightly lower standard deviation values than the hospital organisational model, especially during the pandemic period. In other words, hospital establishments organised in hospital centres show a dispersion of the model’s technical efficiency scores closer to the group average. The hospital centres organisational model had lower coefficient of variation values than the hospital model. This means that the technical efficiency scores of the hospital centres model are less heterogeneous than those of the Hospital organisation model. In both periods, the hospital centre model showed better average technical efficiency than the hospital model. During the pandemic, the hospital model always improved its average efficiency. In the second year of the pandemic, the hospital centre model saw a slight drop in its average efficiency (Figure 1). Studies have shown that large hospitals have performed worse during the pandemic (40). The results of this study show that the hospital centre model was always better during the pandemic than the hospital model.

During the pandemic, patients have sought hospitals less for fear of COVID-19, so the number of hospitalisations has dropped substantially, leading to a decrease in hospital activity (41). And it resulted in an improvement in the above-mentioned indicators in most of the hospital establishments studied. These results reinforce the conclusions reported in other studies, which found a marked reduction in the number of hospitalisations (42-44).

Globally, the average efficiency of health systems during the pandemic was very low (45). This result did not occur in the public hospitals of the Portuguese NHS, since there was no statistically significant association between the pre-pandemic and pandemic periods in the hospitals or hospital centres (Tables 2,4). In other words, Portuguese public hospitals did not lose efficiency during the pandemic. In the first phase of the pandemic, health systems in Western Europe registered very high inefficiencies (46,47), which is not the case in this study, where the average efficiency of hospitals during the pandemic was very similar to the pre-pandemic period. Compared to Germany, a benchmark country in Europe, Portuguese public hospitals counteract the deterioration in average technical efficiency experienced in German hospitals due to the COVID-19 pandemic (9). At the national level, there was a reduction in the efficiency of Portuguese hospitals from 2019 to 2020, but it recovered in the following years (48). The results of this study indicate that there was no decrease in efficiency during the pandemic; on the contrary, it increased slightly compared to the pre-pandemic period. On the other hand, an average technical efficiency of 0.804 was found for the NHS during the pandemic (47), very similar to the results found in this study.

In this study, the indicator ‘Hip Fractures (surgeries in the first 48 h)’ was one of the indicators that worsened, in the literature the results of this indicator were not consensual during the pandemic, there were studies that concluded that the response of hospital services to the pandemic had no negative impact on the surgical time of hip fractures (49,50). However, studies in the same country have found asymmetries between regions, as was the case in Italy, where the patterns differed in the regions of Piedmont and Emilia Romagna (51). The Piedmont region recorded no change in surgeries in the first 48 hours of the hip fracture, however, Emilia-Romagna recorded a significant decline. These local differences at the time of the pandemic, reflect the capacity of health services, management and emergency preparedness (51).

During the pandemic there was a higher mortality from ischaemic and haemorrhagic strokes, leading to a worsening of the indicator. This situation was seen in several hospitals, where mortality from ischaemic and haemorrhagic strokes increased during the lockdown period, later falling back to the reference value (52-54). The explanation for the majority of hospitals (N=24) showing worse results for the indicator ‘Ischaemic and Haemorrhagic Stroke (within 30 days of the episode)’ can be found in the fact that the time elapsed between the onset of the illness and arrival at the emergency department increased substantially and the proportion of patients who underwent intravenous thrombolysis within the indicated time limit decreased during the pandemic (55). The indicator ‘Rate of hospitalisation for acute complications of diabetes’ worsened in most of the hospitals studied (N=19), due to less rigorous control and less activity in primary health care during the pandemic (40,46).

During the pandemic, the likelihood of post-operative sepsis increased (56), and this was true of the sample in this study, with 25 of the 32 hospital establishments in the study worsening the ‘Post-operative sepsis p/100,000’ indicator. This may be due to the delay in recognising and treating in-hospital infections that can develop into sepsis, or due to the decrease in healthcare utilisation and the cancellation of elective activity at the start of the COVID-19 pandemic, which meant that when it was possible to submit patients to surgery, they were in a more serious condition (56). Sepsis increased by 28% in the first months of the pandemic, with disappointing trends similar to other infections, falls and pressure ulcers (57).

The ‘pressure ulcer rate’ can be a preventable event related to good health care; when the rate increases, it is due to failures in the care provided (58). As was seen in this study, this indicator worsened in the majority of hospital establishments (N=24), which is evidence of inadequate health care. On the other hand, during the pandemic, there has been an increase in the number of patients admitted to COVID-19 ICUs who have required respiratory support, requiring more professionals available to mobilise the patient. During the pandemic, the number of professionals available was scarce, which may have had an influence on the increase in the incidence of pressure ulcers. Ventilated patients are more difficult for the team to mobilise in bed, requiring a greater number of health professionals to mobilise the patient properly (59).

Spearman’s correlation coefficient showed a moderate positive association between the variable ‘Hip fractures (surgeries in the first 48 hours)’ and the DEA score, which did not exist in the pre-pandemic period (see Table 8). Surgeries performed within 48 hours generally result in lower hospital costs due to the reduction in hospitalisation time and associated complications. Hip fractures are among the most common hospital admissions and require the most hospital days compared to most other acute illnesses (60). As a result, the risk of developing nosocomial infections increases, which leads to excessive costs and reduced hospital capacity (61,62). A study in Spanish hospitals revealed that prolonged hospitalisation for a hip fracture had an increase in cost of 14.44%; however, considering the cost that would have corresponded to the same Diagnosis Related Groups (DRG) and year of discharge, it could amount to 21.17% (63). In Greece, a study showed that during the pandemic, the time to surgery and length of stay were longer (64). The results of this study suggest that the contingency measures of the COVID-19 pandemic have led to some orthopaedic services having their production reduced (64). The pandemic has led to a transformation in the way hospitals operate, causing a reduction in the time and effort dedicated to surgical activity, which in turn has led to delays in the surgical calendar of most hospitals, which has had a negative impact on the efficient use of operating theatres (65). In this way, this study found that the more hip fracture surgeries that are carried out within 48 hours, the lower the costs, which influences the technical efficiency of the hospital unit. The indicator ‘Hip fractures (surgeries in the first 48 hours)’ was one of the indicators that worsened in most of the hospitals under study during the pandemic (Table 5), so this reduction in surgeries within the first 48 hours resulted in a loss of technical efficiency on the part of the hospitals.

For the other quality indicators under study, there was no statistically significant association with efficiency. This result shows that these indicators had no effect on hospital efficiency during the pandemic. Although the indicator ‘Post-operative sepsis p/100,000’ worsened during the pandemic in the majority of hospitals, it had no influence on efficiency as it had in the pre-pandemic period. The quality indicator ‘Post-operative sepsis p/100,000’, despite having worsened during the pandemic in most hospitals, was not influenced by efficiency as it had been in the pre-pandemic period, due to the number of surgeries having decreased during the pandemic. In other words, the likelihood of having post-operative sepsis was higher due to the delay in recognising and treating in-hospital infections that can develop into sepsis, or due to the decrease in healthcare utilisation and the cancellation of elective activity at the start of the COVID-19 pandemic, which meant that when it was possible to have patients undergo surgery, they were in a more serious situation (56), but the number of patients with post-operative sepsis was lower because fewer surgeries were performed during the pandemic.

In terms os strategies, one of the main approaches adopted to mitigate the effect of the pandemic on hospital management was the relocation of physical spaces to continue producing healthcare. During the pandemic, management challenges were identified, such as insufficient resources and physical space (66). The utilisation of physical spaces has been one of the concerns of hospital management in order to continue providing hospital care and increase capacity to respond to COVID-19 patients. The Portuguese government, like other European governments, used a variety of measures to create sufficient physical infrastructure to increase labour capacity right at the start of the pandemic (67,68).

Teleconsultations and video consultations were also among the most widely used strategies for keeping track of patients during consultations. The use of telemedicine has been effective in reducing the impact of the pandemic on hospital care, as a low-cost measure for reducing infections and allowing care activity to be maintained (69). The use of telemedicine has improved the delivery of healthcare, so it has been an important tool for maintaining care, keeping users and healthcare professionals safe during the pandemic (70-72). With the pandemic, telehealth, previously considered a novelty for many, almost instantly became a new standard for user protection (73).

The strategy of creating safety circuits to maintain continuity of care for non-COVID-19 patients and extending opening hours for users was also a strategy adopted to mitigate the effects of the pandemic. Hospital managers’ strategy to mitigate the effect of the pandemic has focused on three main areas: controlling the source of infection, breaking transmission and protecting the most vulnerable (74). The creation of safe circuits was a structural measure to prevent contagion and allow the continuity of care for non-COVID-19 patients, which resulted in practice in the adaptation of waiting rooms so that the minimum distance was guaranteed and in the delimitation of corridors and safety zones (75). Extended opening hours was a strategy adopted by many hospital administrations at an early stage because they had too few professionals to respond to the pandemic (76,77). On the other hand, the extended hours have been used, particularly since the suspension of elective surgeries due to COVID-19, to reduce waiting lists by taking advantage of empty operating theatres and existing surgical teams (78).

The least mentioned strategy for dealing with the pandemic was the creation of work and action procedures (N=1; 8.33%) [e.g., ‘the creation of technical documents, known by all, constituting standards for action’ (E4)]. Due to the development of procedures with guidelines for the work and performance of health professionals, it was possible to improve the knowledge and performance of professionals and managers, becoming more efficient (66). Essentially, the guidelines and protocols are designed to reduce the hospital spread of COVID-19 (79). With proper management of nursing staff and the use of appropriate procedures when caring for COVID-19 patients, it has been possible to improve the quality of nursing services and the safety of hospitalised patients (80).

The use of external organisations to receive patients was the least used strategy, but important for maintaining the production of hospital care. During the pandemic, collaboration between public entities and private sector and military entities was a frequent strategy to mitigate the effect of the pandemic on the population and relieve the public health sector (81). In several countries, the private sector has helped to limit the serious consequences of the COVID-19 pandemic, when public hospital establishments reached saturation (82-84). The use of private establishments allowed the utilisation of structures, equipment and health professionals (82,84).

It was found that most of the strategies adopted by the executive management of the hospital establishments under study were similar to those described by hospital executives in China, Norway and the United Kingdom, where their strategies to mitigate the effects of the pandemic were: redesigning the organisation to separate COVID-19 and non-COVID-19 services within and between hospitals; expanding virtual care strategies to improve access; using data-driven models to allocate resources between COVID-19 and non-COVID-19 units; investing in programmes to promote the well-being of frontline staff; and ensuring financial support to continue fulfilling healthcare responsibilities (85). The strategies used in the pandemic by hospital establishments have largely been traditional strategies, designed to maintain safety during times of great need, based on increasing bed availability, managing human resource shortages, changing skills and dealing with critical shortages of equipment and consumables (86).

In this study, it was found that the effect of liaison between their hospital unit and the Ministry of Health in responding to the pandemic was heterogeneous, i.e., in some hospital establishments it had a positive effect and in others it had a negative effect. The Ministry of Health has had a negative effect due to the delay in creating and updating standards for hospital establishments, while on the other hand, it has had a positive effect on liaising between hospital establishments to acquire materials and manage beds. At a central level, the perception was positive due to the constant support of the Ministry of Health, through the Minister, to find daily solutions in the management of beds, equipment and consumables. The asymmetry in perception was felt at the RHA level, due to the fact that each had its own management team and did not act as a whole, with some being closer to the hospitals in resolving their daily problems and others not following up so closely on the hospitals in their area. The governance structure and its effect on the reaction to the pandemic were nuanced. Centralised and decentralised governance structures can have a differential effect on reactive and proactive strategies in the management of a pandemic; however, a centralised governance structure may not facilitate a proactive response to a pandemic (87).

Based on the interviewees’ perceptions, it was possible to create a conceptual framework that synthesises all the information gathered, allowing a better understanding of the strategic process and mapping the concrete actions taken by the establishments under study that have maintained or improved efficiency (Figure 2).

Figure 2 Framework summarising the strategic process of hospital establishments.

During the course of this research, some limitations were encountered. One of the limitations is related to the PPP management model, as at the time of the study, there was only one PPP hospital in Portugal. This did not allow for an adequate analysis of the effect of the pandemic on this management model. On the other hand, there was a limitation with the pandemic period, which had to be restricted from 2020–2021, because in February 2022, hospitals would operate normally, without restrictions and the databases for the years 2022 and 2023 were incomplete, making it impossible to collect all the data for the hospital establishments studied.

Conclusions

This study confirmed that the organisational model of hospitals influenced the performance of hospital establishments during the pandemic. Hospital centres maintained very similar average technical efficiency values in the pre-pandemic and pandemic periods. The organisational model of hospital centres showed greater consistency in technical efficiency throughout the pandemic. With regard to the PEM management model, it can be concluded that efficiency remained stable during the pandemic period. The only PPP hospital became efficient in the second year of the pandemic. In this study, it was not found that hospital centres or hospitals did not lose efficiency during the pandemic compared to pre-pandemic.

The pandemic had a negative impact on most hospital quality indicators, with the exception of some improvements related to the reduction in hospitalisations. It was confirmed that the quality of hospital care during the pandemic influenced technical efficiency, with a positive association between hip fracture surgeries and hospital technical efficiency.

The main strategies used by management were aimed at maintaining hospital production. However, some of the strategies adopted have served to prevent the spread of the COVID-19 virus. The management of the pandemic has been positive for the majority of hospitals.

It is hoped to provide hospital managers with the knowledge to improve the accessibility and quality of hospital care more efficiently in future situations that put hospitals under stress. The strategies mentioned in this study can benefit managers’ decision-making and coordination actions so that they are more efficient and effective. The aim of this study is to contribute to the existing literature on hospital management in times of crisis and to provide practical insights that can be applied in future health emergency situations.

Acknowledgments

None.

Footnote

At the time of the study, there was only one hospital unit in the PPP management model because the Portuguese government converted the other 3 establishments to the PEM model.

Peer Review File: Available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-24-126/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jhmhp.amegroups.com/article/view/10.21037/jhmhp-24-126/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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