Utilisation and Management of an Emergency Department in a Tertiary Hospital in the Philippines During the COVID-19 Pandemic

Abstract

The Emergency Department (ED) plays the role of providing efficient and quality healthcare services to patients. During the COVID-19 pandemic, there were observed changes in the ED’s utilisation and management reflecting the underlying challenges faced by most tertiary hospitals in the Philippines. This study aims to describe the changes in the utilisation and management of ED in a major COVID-19 hospital in the Philippines, its implications for inpatient admissions, and effect on ED staff. Patient data from 2019 (pre-pandemic) and 2020 (pandemic) were compared. In addition, this study administered a COVID-19-specific psychometric tool to assess the pandemic’s effect on ED staff. Comparing the pre-pandemic and pandemic census, this study found a 59.0% and 67.6% decrease in ED consultations and hospital admissions, respectively. ED consultations significantly shifted to older patients, with longer length of stay, increased out-of-pocket payment, and mostly presenting with respiratory-related chief complaints. There is a decrease in general hospital unit utilisation, and the addition of a COVID-19 ward and an ICU. Despite the changes, 63.6% of the ED staff exhibited good emotional adjustment to the stress brought by the pandemic. This study reported the situation of Philippine ED amid the pandemic and indicated the important management changes in ED.

Keywords

COVID-19 emergency department hospital admission Philippines

Introduction

Responding to public health emergencies remains a challenge in the Philippines due to inadequate healthcare resource distribution. The COVID-19 response of the country exemplified this situation. Despite the longest lockdown in Southeast Asia, local community transmission continues in the Philippines (World Health Organization [WHO], 2021). Consequently, the Philippines ranks high in the number of COVID-19 incidences, with the highest number of deaths per million population in Southeast Asia late in 2020 (De Castro et al., 2021). The National Capital Region (NCR) is considered the epicentre of COVID-19 in the country. As of December 2021, only 33.6% of the population was fully vaccinated (Our World in Data, 2021).

Only 40% of the Philippine hospitals are public (Department of Health, 2021). The inequity of healthcare access during COVID-19 is evident since the citizens must decide whether to avail healthcare services in free but underequipped public hospitals versus well-equipped private hospitals that charge at full cost (De Castro et al., 2021). To accommodate the surge of patients, the Department of Health mandated private hospitals to increase their bed capacity for COVID-19 patients by 20%–30% (Inter-agency Task Force, 2021). The expenses associated with the COVID-19 management were subsidised by the national health insurance programme, the Philippine Health Insurance Corporation (PhilHealth), depending on the case rates. Due to delayed reimbursements from PhilHealth, an estimated 300 private hospitals were on the verge of closure as early as May 2020 (Business Mirror, 2020). Currently, an estimated amount of unpaid reimbursement amounting totalling of billion pesos persists (Business Mirror, 2021).

The Medical City (TMC), a tertiary private hospital classified as a level 4 health service provider, experienced economic and financial loss brought about by the decreasing number of non-COVID-19 admissions, delayed PhilHealth reimbursements, and increased infection-related expenditures while preserving its personnel count. TMC was among the hospitals in Metro Manila to report initial COVID-19 cases and implemented a series of hospital operation reforms (Abad et al., 2021). TMC’s Emergency Department’s (ED) pre-pandemic census was among the highest nationwide, with an average annual consultation of 113,000 since 2018 (Jimenez et al., 2018). Given the drastic change in the operation, there has been a significant decline in the number of ED consultations, as also observed worldwide (Hartnett et al., 2020; Nourazari et al., 2021). During the pandemic, TMC-ED extended its function by assuming as the default healthcare facility for all disease severities, and an entry point for COVID-19 patients in the hospital. With the current lack of understanding of the dynamics of ED operations at the time of the pandemic, this study aims to determine (a) the changes in TMC-ED utilisation in 2019 (pre-pandemic) and 2020 (pandemic), (b) the profile of inpatient admissions from the ED in pre-pandemic and pandemic periods, and (c) the psychological effect of the pandemic on TMC-ED staff.

Methods

Data Source

This research was conducted in two phases, consisting of a data review and survey. For the data review, the data available from the electronic consultation records of the Emergency Department (ED) and inpatient medical records at The Medical City (TMC) were used. For the survey phase, the self-administered Acute Stress Scale for Health Professionals Caring for COVID-19 Patients (COVID EASE Scale, Mira et al., 2020) was used. Data were collected using a web-based form from 3 June to 5 July, 2021.

Data Review (ED and Inpatient)

The data were screened for completeness, and all records with incomplete data were excluded to arrive at the final dataset. For both ED and inpatient databases, the age was stratified into age groups following a previous study (Jimenez et al., 2021). The consultation and admission dates of the patients were clustered based on months, and the ED and hospital length of stay (LOS) were divided into hourly and daily ranges, respectively (Jimenez et al., 2020). The patients’ chief complaints were clustered per organ system as previously described (Jimenez et al., 2021). For the payment scheme, Health Maintenance Organizations (HMOs) were defined as cases covered by local and international health cards, and hospital benefits and out-of-pocket (OOP) as those who paid outright, with or without discounts, including PhilHealth coverage. For inpatients, hospital nursing units were defined based on published criteria (Park et al., 2014), with the addition of general COVID-19 units and COVID-19 intensive care units. Finally, the inpatient final diagnoses were grouped based on the International Statistical Classification of Diseases and Related Health Problems—10th Revision (ICD-10, 2019).

Survey Using COVID EASE Scale

The EASE Scale was adapted based on a recently developed tool (Mira et al., 2020). The tool was initially validated with ten TMC-ED staff, where we found good internal consistency and reliability of the survey items (Cronbach’s alpha = 0.899). After the validation, the link to the online survey of the EASE Scale was disseminated to the ED staff. Only TMC-ED staff employed in TMC for a minimum of six months and without declared, pre-existing mental health issues (based on their consent response) were included in the recruitment. All survey responses received were deemed complete and used in the analysis.

Data Analysis

The statistical analyses were performed using SPSS version 22.0 (IBM SPSS, Chicago, IL, USA). For the data review phase, the categorical variables were presented as frequencies and percentages, and the numerical variables as means and standard deviations. For the survey phase, the scale results were summarised for each item as averages at 95% confidence intervals. To interpret the results, the scores for all items were added, and the total was used to determine its interpretation (Mira et al., 2020). To determine the association of the variables with pre-pandemic and pandemic consultation, as represented by the years 2019 and 2020, respectively, a Chi-square test was conducted. A binary logistic regression was also done to determine a model that explains the statistical significance of each variable, with its differences in each year as a possible explanation for the changes in ED utilisation. The 95% confidence intervals were computed, and the significance was set at p < 0.05.

Results

ED Utilisation and Management

ED Operation

The national government placed the entire Luzon area under an enhanced community quarantine (ECQ), classified as the strictest lockdown category, from 16 March to 14 April 2020 (Inter-agency Task Force, 2021). Concurrent to this, the hospital implemented entry restrictions to screen patients with COVID-19 symptoms. From 1–5 April 2020, a full-capacity status was declared due to the unavailability of COVID-ICU, hospital and ED beds. As the number of COVID-19 cases lessened, the hospital implemented a 2-in-1 hospital system by physically separating the management of COVID-19 and non-COVID-19 patients. On 15 May 2020, an easing of lockdown restrictions followed, known as general community quarantine (GCQ) (Inter-agency Task Force, 2021). GCQ led to a gradual increase in the ED census (Figure 1). However, due to another surge in COVID-19 cases, another lockdown restriction, the modified enhanced quarantine (MECQ), was implemented from 4–18 August 2020. Before the MECQ, the hospital reinstated a full capacity advisory from 1–5 August 2020, which limited the ED consultations only to life-threatening cases.

Figure 1.

Source: The authors.

ED Patient Characteristics

Overall, there is a 59.0% decrease in the total census of ED consultations from 2019 to 2020. In 2019, most of the patients who consulted at the ED were female (55.3%), predominantly young adults and paediatric patients (51.7%), who stayed at the ED for six hours (91.8%), paid via HMO (91.7%) and presented with either a digestive (17.4%) or infectious (16.3%) complaint. Meanwhile, in 2020, there was a shift to adult patient population, with an increased proportion of patients paying via OOP (19.1%) and presenting with respiratory symptoms (21.1%).

ED Consultations

Chi-square test revealed the significant shift of ED patient characteristics to older age with longer ED LOS in 2020 (pandemic period). There is also a significant decrease in patients who paid using HMO during this period, proportionally increasing the OOP for 2020. A decrease in those with digestive and non-COVID-19 infectious chief complaints was observed. In contrast, the number of patients consulting for respiratory-related complaints significantly increased during the pandemic. The univariate analysis is summarised in Table 1.

Table 1.

Comparison of the Sociodemographic and Clinical Characteristics of ED Patients in the 2019 (pre-pandemic) and 2020 (pandemic) Periods with Logistic Regression Analysis of the Predictors of ED Consultation During the Time of the Pandemic.

Variables	2019		2020		X² p-Value¹	Logistic Regression Analysis
Variables	n = 86,670	%	n = 35,874	%	X² p-Value¹	C ²	p ³	OR⁴	Lower CI⁵	Upper CI⁶
Age (in years) 1–18 19–30 31–40 41–50 51–60 61 and above	24,283 20,807 17,649 9,674 6,862 7,395	28.0 23.7 20.1 11.0 7.8 8.4	972 11,554 9,877 5,457 3,822 4,192	2.7 32.1 27.5 15.2 10.6 11.7	<0.001 <0.001 <0.001 <0.001 <0.001 <0.001	0.26	<0.001	1.298	1.287	1.309
ED LOS (7–12 hours)	6,289	7.2	2,855	7.9	<0.001	0.06	0.030	1.056	1.005	1.110
Male gender	39,151	44.7	16,202	45.1	0.224	0.07	<0.001	1.076	1.047	1.105
Out of pocket payment scheme	7,299	8.3	6,867	19.1	<0.001	0.84	<0.001	2.320	2.233	2.411
Digestive-related chief complaint	15,243	17.4	4,517	13.4	<0.001	−0.26	<0.001	0.768	0.739	0.797
Infectious-related chief complaint	14,324	16.3	3,005	8.4	<0.001	−0.48	<0.001	0.619	0.592	0.647
Respiratory-related chief complaint	8,263	9.4	7,600	21.1	<0.001	0.66	<0.001	1.931	1.856	2.009
Constant						−1.84	<0.001	0.158

Source: The authors.

Notes: 1. p-value chi-square test of independence; significant at p < 0.05.

2. Coefficient of binary logistics regression.

3. p-value based on binary logistic regression; significant at p < 0.05.

4. Odds ratio.

5. 95% confidence interval lower limit.

6. 95% confidence interval lower limit.

Predictors of ED Consultations

The significant predictors of ED consultations during the pandemic are summarised in Table 1. Patients who were more likely to consult during the pandemic were mostly using OOP as their payment scheme (2.3 times more likely), were from a higher age group (1.3 times more likely), stayed longer in the ED (1.1 times more likely) and are usually males (1.1 times more likely). Respiratory-related cases also showed a positive coefficient, and they were 1.9 times more likely to consult.

Inpatient Utilisation and Management

Hospital Operation

An overall decrease in inpatient admissions was observed during the initial periods of strict quarantine measure implementation (Figure 2). In adherence to the Inter Agency Task Force (IATF) resolution during surges, TMC allotted 22% of its total bed capacity to COVID-19 cases (107 out of 478 hospital beds). In 2020, the total operational bed capacity decreased by 8% due to (a) the allotment of donning and doffing areas and (b) the conversion of semi-private rooms to single rooms. As a measure to preserve the 2-in-1 hospital system, three resolutions were also implemented: (a) the requirement for a negative RT-PCR test for non-COVID-19 patients, (b) the deferment of direct hospital admissions for patients with COVID-19-related symptoms and (c) the redirection of patients with COVID-19 symptoms to ED.

Figure 2.

Source: The authors.

Inpatient Characteristics

The inpatient census declined from 2019 to 2020. In 2019, most of the inpatients admitted at TMC were male (51.4%), stayed at the ED for six hours before admission (63.6%), stayed at the hospital for one week or less (91.6%) and paid via HMO (88.3%). They were predominantly consulted for digestive (20.9%) and infection-related (21.7%) complaints, and diagnosed mostly with infectious-related diseases (21.7%). There is an equal representation of paediatric and geriatric patients. Meanwhile, in 2020, there was an inverse proportion of geriatric and paediatric patients. We also observed a decrease in utilisation of general nursing units and intensive care units (ICU), and an addition of COVID-19 wards and COVID-ICU during the pandemic. There is an increase in the OOP payment scheme and a shift to respiratory-related chief complaints and final diagnoses.

Inpatient Admissions

Significant increases in age, ED and hospital LOS were found from pre-pandemic to pandemic periods. There is also an increase in chief complaints related to the digestive and respiratory systems. Meanwhile, significant decreases in HMO payments, non-COVID-19 infection-related complaints, general nursing and intensive care unit utilisation were observed. The utilisation of COVID-19 wards and ICU was also apparent during the pandemic. The univariate analysis is summarised in Table 2.

Table 2.

Comparison of the Sociodemographic and Clinical Characteristics of Inpatients in the 2019 (pre-pandemic) and 2020 (pandemic) Periods with Logistic Regression Analysis of the Predictors of COVID-19 Ward Admission During the Time of the Pandemic.

Variables	2019		2020		X² p-Value¹	Logistic Regression Analysis
Variables	n = 86,670	%	n = 35,874	%	X² p-Value¹	C ²	p ³	OR⁴	Lower CI⁵	Upper CI⁶
Age group 1–18 19–30 31–40 41–50 51–60 61 above	6,4602,0952,1071,7502,1356,456	30.19.89.88.21030.1	1898749179031,0852,945	2.712.613.21315.642.5	<0.001<0.001<0.001<0.001<0.001<0.001	0.23	<0.001	1.252	1.219	1.287
ED LOS (7-12 hours)	6,270	29.3	2,238	32.3	<0.001	0.03	0.525	1.033	0.935	1.141
Hospital LOS (8–14 days)	1362	6.4	888	12.8	<0.001	0.76	<0.001	2.140	1.870	2.448
Male gender	11,016	51.4	3,499	50.4	0.080	0.13	0.009	1.134	1.032	1.246
Out-of-pocket payment scheme	2,501	11.7	1,621	23.4	<0.001	0.85	<0.001	2.327	2.090	2.592
Digestive-related chief complaint	4,467	20.9	1,420	21.1	<0.001	0.01	0.842	1.013	0.890	1.154
Infectious-related chief complaint	4,646	21.7	616	9.1	<0.001	−0.07	0.391	0.935	0.802	1.090
Respiratory-related chief complaint	3,502	16.4	1,296	19.2	<0.001	0.40	<0.001	1.492	1.321	1.685
Constant						−3.66	0.000	0.026
General nursing unit admissionIntensive care unit admissionIsolation ward admissionOncology ward admissionCOVID-19 ward admissionCOVID-19 ICU admission	19,5371,46817923900	91.26.850.81.100	3,76816729332,498440	54.32.410.40.536.06.3	<0.001<0.0010.2700.060n/an/a	NA	NA	NA	NA	NA

Source: The authors.

Notes: 1. p-value chi-square test of independence; significant at p < 0.05.

2. Coefficient of binary logistics regression.

3. p-value based on binary logistic regression; significant at p < 0.05.

4. Odds ratio.

5. 95% confidence interval lower limit.

6. 95% confidence interval lower limit.

Predictors of Hospital Admissions

The significant predictors of COVID-19 ward admissions during the pandemic is presented in Table 2. Patients in the COVID-19 general wards were 1.1 times more likely to be male and 2.3 times more likely to pay using OOP. They are also older (1.3 times more likely), have respiratory-related chief complaints (1.5 times more likely) and have a longer hospital stay (2.1 times more likely).

Psychological State of ED Staff

A total of 118 (74%) out of 160 ED staff completed the EASE Scale survey. The mean total score of the respondents is 8.03 (95% CI = 9.08 to 6.98), which corresponds to ‘good emotional adjustment’ of the respondents based on the recommended interpretation (Mira et al., 2020). Majority of the respondents have good emotional adjustment (63.6%) while only one participant (0.8%) had extreme acute stress. The individual scores and top responses per item of the EASE Scale are shown in Table 3.

Table 3.

Summary of EASE Scale Response of the Emergency Department Staff Handling COVID-19 Cases.

Items	Mean (95% CI)¹	SD²	It’s Not Happening to Me (%)	It Happens to Me in Concrete Situations (%)
I cannot help but think of recent critical situations. I cannot get out of work.	0.93 (0.79–1.07)	0.77	30.51	48.31
I have completely lost the taste for things that gave me peace of mind.	0.69 (0.54–0.84)	0.82	50.00	35.59
I keep my distance, I resent dealing with people and I am irascible even at home.	0.68 (0.53–0.82)	0.80	50.85	33.05
I feel that I am neglecting many people who need my help.	0.64 (0.50–0.79)	0.80	53.39	31.36
I have difficulty thinking and making decisions, I have many doubts and I have entered a kind of emotional blockage.	0.68 (0.54–0.82)	0.77	49.15	35.59
I feel intense physiological reactions (shocks, sweating, dizziness, shortness of breath, insomnia, etc.) related to the current crisis situation.	0.47 (0.34–0.59)	0.71	64.41	26.27
I feel on permanent alert. I believe that my reactions now put other patients, my colleagues or myself at risk.	0.75 (0.60–0.91)	0.86	46.61	36.44
Worrying about not getting sick causes me a strain that’s hard to bear.	0.91 (0.75–1.07)	0.88	35.59	45.76
I am afraid I am going to infect my family.	1.65 (1.49–1.81)	0.90	7.63	40.68
I have difficulty empathising with patients’ suffering or connecting with their situation (emotional distancing, emotional anaesthesia).	0.64 (0.50–0.77)	0.77	50.85	38.14

Source: Mira et al. (2020).

Notes: 1 95% confidence interval, 2 Standard deviation.

The survey is coded on a four-point scale, with 1 as the lowest score (“it’s not happening to me”), and 4 as the highest (“I’m like this all the time”).

Discussion

The findings of 60% and 67% overall decrease in ED utilisation and hospital admissions, respectively, were consistent in other studies (Nourazari et al., 2021). Some of the possible reasons for this decrease include: fear of contracting the illness (Birkmeyer et al., 2020; Nourazari et al., 2021), aggressive hospital containment measures (Mahmassani et al., 2021), reduced patient mobility (Nourazari et al., 2021), use of alternative healthcare providers (Hartnett et al., 2020; Nourazari et al., 2021), deferred patient care (Nourazari et al., 2021) and suspension of elective and non-critical medical services (Birkmeyer et al., 2020). A reduction in the number of paediatric ED consultations was observed, as described in other studies (Nourazari et al., 2021). Researchers hypothesised that this reduction was brought about by the closure of educational and recreational activities for children, resulting in reduced school-related stress and avoidance of potential viral exposure (Raucci et al., 2021). Children are also less affected by COVID-19, accounting for only 2–3.3% of cases (Raucci et al., 2021) and presenting with less severe infection manifestations attributable to age-dependent exposure factors (Dong et al., 2020; Lazzerini et al., 2020). Factors such as hospital operational changes may have also played a role in the decrease of paediatric cases (Lazzerini et al., 2020). Early on during the pandemic, we relocated the paediatric emergency department and converted the original one to a non-COVID ED due to lack of utilisation.

Over the years, the ED has become a dominant source of hospital admissions, contributing up to 70% of inpatients (Augustine, 2021). In our previous study, an estimated 18% of hospital admissions came from the ED (Jimenez et al., 2018). Therefore, a decline in the ED census would affect hospital admissions as well. During the COVID-19 pandemic, global reports indicated an inpatient reduction of about 32% (Nourazari et al., 2021). This phenomenon can reflect a change in the behaviour of a population in response to the pandemic threat (Mantica et al., 2020). It also resulted to the deferment of care for patients whose clinical condition may worsen (Nourazari et al., 2021). A significant disproportion between the inpatient admissions of <18-year-old and >60 years was found, with more geriatric patients consulting in the ED and eventually getting admitted during the pandemic. This disproportion can be explained by the increased susceptibility, higher case fatality rate, and presence of pre-existing co-morbidities among the geriatric population (Hartnett et al., 2020).

Previous local studies associated ED utilisation with HMOs (Jimenez et al., 2018, 2020, 2021). However, in 2020, we observed a significant increase in out-of-pocket (OOP) payment in ED consultation and hospital admission. We expected the OOP payment scheme to increase due to the overcapacity of government hospitals and the limitations of HMO coverage. We hypothesize that other factors may have contributed to our observations, like patients without HMO coverage now consulting out of necessity or that HMOs became stricter in determining coverage.

This study showed that the hospital experienced longer ED LOS at the onset due to the limited national testing capacity and high demand for RT-PCR. The situation prompted patients to saturate the hospitals (Amit et al., 2021). Eventually, longer hospital LOS was also observed due to compliance with the CDC recommendation for a negative RT-PCR result before disposition (Olanipekun, 2021). The longer hospital LOS can also be due to the limited COVID-19 bed allocation, slow PhilHealth reimbursements resulting in hospital financial constraints, older cases mixed with more complex conditions (Guo et al., 2021), requirement for RT-PCR testing prior to admission and discharge, and inconsistent guidelines. Meanwhile, a significant increase in respiratory chief complaints can be attributed to usual COVID-19 symptoms of cold and cough (Hasani et al., 2020). Likewise, a significant decrease in non-COVID-19 infectious complaints can be explained by mobility restrictions that can affect all other infectious-related illnesses (Zhou et al., 2020) or an override of COVID-19 disease as a primary consideration among other infectious illnesses (Can Sarınoğlu et al., 2020).

Majority of the ED staff retained a ‘good emotional adjustment’ outlook, reflecting a lower level of psychological impact that is contrary to those reported in other countries for the general population (Mira et al., 2020). A possible explanation for this observation is the resiliency of Filipino frontline healthcare workers during the pandemic (Labrague, 2021). However, it is important to note that one-third of TMC-ED staff experienced a significant degree of medium to high emotional overload. Recent studies showed that psychologic response can evolve depending on the situation’s complexity, which can affect the hospital staff’s resilience once a new surge occurs (Mira et al., 2020).

Limitations

This study was only conducted in a single ED and hospital and may not reflect the experience in other Philippine hospitals. Establishing our experience can give an insight into the other COVID-19 hospitals’ experiences and may hopefully lead to more studies on the matter in the future. Meanwhile, a number of ED and inpatient records have been excluded from our analysis due to the incompleteness of entries, which could have been brought about by clerical errors. Finally, the EASE scale survey was conducted using only a cross-sectional study design at a time when the ED was not on its peak operations. The EASE Scale results were also not compared to any sociodemographic data of the respondents.

Conclusion

This study showed that the utilisation and management of the ED of a tertiary hospital in the Philippines drastically changed with the COVID-19 pandemic. The redesigning of the hospital’s operational workflow by stratifying the different case severities for both COVID-19 and non-COVID-19 patients, and extending patient services to ambulatory, telemedicine, home care and quarantine facilities was advised. The redeployment of the staff from units with low utilisation to COVID-19-related activities to augment the low manpower capacity and to prevent the staff exhaustion was also recommended for exploration. Finally, institutional clinical guidelines should be followed to preserve consistency and lessen variations in terms of clinical and operational management.

Footnotes

Acknowledgement(s)

The authors would like to acknowledge the contributions of Ms Rosalinda Calingasan for her help in the logistical aspects of the study, and Dr Roland Gilbert Remenyi of the Clinical and Translational Research Institute for his insights on the improvement of the manuscript.

Author Contributions

M. L. C. Jimenez conceptualized, designed, analysed, interpreted and drafted the research; R. Manzanera conceptualised, interpreted and edited the research; M. B. Carascal designed, analysed, interpreted and drafted the research; M. D. Figueras analysed, interpreted and drafted the research; J. Q. Wong analysed and interpreted the research; J. Mira and D. Moya conceptualised, interpreted and edited the research.

Consent to Participate

Each participant gave their informed consent before participation. Participants were briefed on the nature of the study, were aware that their participation was purely voluntary without remuneration, and were assured that all data collected will be kept confidential.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Ethics Approval

The protocol for this study was reviewed and approved by The Medical City’s Institutional Review Board on 6 May 2021, with a research registry number of GCS-ER-2020-114.

Funding

The authors disclosed receipt of the following financial support for the research, authorship and/or publication of this article: The Medical City—Clinical and Translational Research Institute Intramural Grant for Quality improvement and Hospital Operations Research awarded to MLC Jimenez (Grant Number 2021-001).

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