Acute Psychiatric Admissions 2017-2024: are we back to pre-pandemic patterns?

doi:10.21203/rs.3.rs-4997864/v1

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Research Article

Acute Psychiatric Admissions 2017-2024: are we back to pre-pandemic patterns?

https://doi.org/10.21203/rs.3.rs-4997864/v1

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Background

The COVID-19 pandemic lead to changes concerning access and type of clinical care available in healthcare systems and facilities around the world. This study aims to understand the changes in patterns of acute psychiatric admissions in the periods before, during and now after the virus hit.

Methods

In this retrospective study, all episodes of admissions in acute psychiatric wards in Hospital Júlio de Matos (age 18 or older) were obtained from January 2017 until March 2024. Three time frames were considered: pre-pandemic (until March 17th, 2020), pandemic (until April 30th, 2021), and post-pandemic (from that date forward); comparing gender, age, diagnosis at discharge, length of stay (LOS), number of daily admissions and number of patients occupying psychiatric hospital beds.

Results

11146 admissions were identified (5706 during the pre-pandemic, 1283 during the pandemic, and 4157 in the post-pandemic period), with a median age of 47 years old, median LOS of 15 days; 4 daily admissions and occupation of 103 beds. Statistical significance was found for every variable between the three groups. Post-hoc analysis identified a higher rate of males during the post-pandemic compared to the pre-pandemic period, a higher median of age in the pre-pandemic period compared to the others; a higher median of previous admissions in the pandemic compared to the post-pandemic, a lower median LOS in the pre-pandemic period compared to the others. The proportion of patients with primary psychotic disorders was significantly lower in the pre-pandemic period compared to other diagnoses and significantly higher in the post-pandemic group. These patients were younger, with longer LOS and bed occupation. The proportion of substance use disorders was significantly lower than any other diagnosis during the pandemic period.

Conclusions

The profile of acute psychiatric patients in the post-pandemic period presents as being more male, younger and with a higher proportion of primary psychotic disorders. Further debate is needed towards the development of community and hospital services better adapted to this new reality.

Trial registration:

The current study was approved by the hospital’s scientific and ethics committees (CCP number 0060/2021 and CES 09/2021)

COVID-19

Psychiatric Department

Delivery of Health Care

Mental Disorders

Patient Admissions

Throughout the years, the means of care towards patients with psychiatric disorders have evolved from permanent institutionalization towards healthcare practices in the community, as close as possible to their families, known environment and activities. This is important especially in regards to the treatment of people going through acute decompensation, who may eventually present harm to themselves or others, and in situations where treatment at home is not possible. Most psychiatric hospitals maintain a certain number of hospital beds for these delicate scenarios, where community care is not enough or may actually put the patient, the family or even health professionals at risk. The development of community care and related services seems to have been accompanied by a diminished need of hospital intervention ^1–6, but even though evidence has shown the benefits of this balance shift, some reports are already stating there are too few mental health to meet psychiatric need, despite progressively diminishing resources ^5,7.

Additionally, the spread of SARS-CoV-2, the virus responsible for the coronavirus disease (COVID-19) and pandemic in 2020 (declared an international public health emergency by the World Health Organization (WHO) ⁸, has transformed the standards of care provided at hospitals, at the time mainly focused on respiratory and related diseases and overall control of the pandemic. On a public health level, strict measures of social distancing, such as the implementation of online labour, the closing of schools and cancelation of major public events and limiting contact outside the family core, were determined. Although these had the purpose of ensuring safety and preventing the spread of the virus, they also imposed disruption in people’s lives and the way they socially relate to and regard hospital care ^9–12. This has led to a raise in concerns regarding different mental health treatment modalities, not only in terms of their availability, but also of the potential inadequacy of some kinds of treatment (for example, telemedicine) ^13–16. Some previously published data also raised the hypothesis that COVID-19 infection itself and possibly quarantine measures may have posed as a personalized trauma and subsequent risk factor for those who go through the process, with possible short and long-time effects on mental health and psychiatric admissions ^10,17,18.

Evidence shows that individuals with psychiatric illness may be more prone to COVID-19 infection ¹⁹, possibly due to an increased susceptibility for infection, such as suboptimal behaviours and lifestyle choices (smoking), socioeconomic status, cognitive deficits, poor awareness level, impaired risk perception and reduced concern about hygiene ^{16,18,20–22}. Patients with severe mental illness also need regular outpatient visits for evaluation and access to prescribed medication. The focus on sanitary regulations during COVID-19 lead to a restriction of this kind of care, with disruption not only of psychiatric outpatient care, but also of other in-person therapies. The evidence on the impact of the pandemic on the volumes and nature of psychiatric hospitalizations is, however, sparse.

Data from a team in the United States showed an increase in observations in emergency rooms due to mental health conditions during the pandemic period ¹³, whereas in our country, as well as in other studies, a reduction of the total number of emergency episodes was found ^12,23.

Our previous work comparing the number of admissions on a period of one year before and after the declaration of a national state of emergency due to COVID-19 showed a reduction in overall admissions (as well as compulsory ones), days of admission and distribution between them (with lower reductions regarding dementias, schizophrenia and affective disorders, while substance use disorders and intellectual disabilities presented reductions of over 50%), with no differences between gender, median age, previous admissions or readmissions ²². However, those results referred only to one year of the pandemic period, so we found it was relevant to understand if the trend of admissions and length of these admissions were maintained after the pandemic period (i.e., after the end of the state of emergency), or if these patterns have changed (back to previous values, or towards a different average of hospital bed occupation, LOS and number of admissions). Still, these results were in line with other publications ^{10,13,24–26}, even though diverging results were also registered ^18,27.

Related studies suggested a shift towards a more severe presentation of psychiatric illness during the COVID pandemic period, although still lacking the understanding of the evolution of the number of cases in the following years ^22,28. In a paper regarding an Italian population, the number of involuntary admissions ended up surpassing the voluntary ones, suggesting the inpatient population presented as more mentally ill and required more intensive treatment ⁶, while another one algo suggested a progressive worsening of the clinical presentation of patients arriving to the emergency department during the COVID-19 period ⁷.

The occurrence of worldwide events such as the COVID-19 pandemic usually creates a disproportionate effect on the health of communities and trends in care throughout the years, and few studies have been presented regarding psychiatric hospitalization trends after the pandemic period. While it is important to understand if there was a “return to normal” versus a deep impact on hospital acute care, it is also relevant to understand and identify new challenges being felt, including efficiency of the care provided thus far ¹⁶. LOS in a psychiatric hospital bed can be a way of deducting this efficiency, albeit still being a complex variable that can be affected by several factors (besides the severity of each case, individual patient characteristics and social determinants need to be considered). Knowing that in psychiatry LOS is usually higher than the average of other medical specialties, hospital stays that are too short could also be considered a risk factor for relapse and need for readmission ^5,16,29,30. Alternatively, a longer average LOS can be described as associated with an increased risk of hospital acquired harms (e.g., falls, infection, other adverse events), as well as with separation from the patient’s communities and families (promoting institutionalization), and overuse of healthcare resources ^16,31.

This study primarily aims to assess the changes in trends of psychiatric hospitalizations during different timelines - before, during and after the pandemic period -, not only regarding the overall volume of hospitalizations, but also regarding clinically relevant diagnostic groups (i.e., psychotic disorders, bipolar disorders, depressive episodes, substance-related and addictive disorders, disorders due to known physiological conditions, and all other conditions). Secondly, changes in trends of the patterns of hospitalizations, including previous admissions and LOS were assessed. Finally, the number of hospital beds occupied by these patients was compared.

To begin to fully understand how the pandemic may have affected mental health and help-seeking behaviours of the population in general and psychiatric patients in specific, the authors examined changes to volumes and characteristics of admissions of patients to acute psychiatric wards in a major psychiatric hospital in Lisbon, Portugal – Hospital Júlio de Matos (HJM, responsible for the care of a population of over 800.000 inhabitants). The Portuguese healthcare system is mainly public funded with free access to care, and involuntary admissions are mandated to be set in a public hospital.

National policies regarding COVID-19 social isolation, testing, and further social restrictions, were aligned with general guidelines and, in order to ensure these measures, a national state of emergency was declared on March 18th, 2020, ending in April 30th, 2021.

2.1. Data collection

The authors carried out a population-based, retrospective, observational study relying on anonymised data retrieved from hospital data. All methods were carried out in accordance with the relevant national guidelines and regulations.

Psychiatric hospitalizations with admission dates from January 1st, 2017, to March 31st, 2024, were identified from hospital records.

2.2. Study design

The authors focused solely on admission episodes, not individual patients, since the cornerstone was not to investigate specific clinical characteristics but overall volume of admissions and burden to healthcare services. From an initial 11585 episodes identified, records were excluded if they involved patients younger than 18 years of age or if they presented missing data - ending up with a result of 11146 episodes of hospital admissions in an acute mental health service.

During these periods variables like age, gender, admission and discharge dates, number of previous admissions and primary diagnosis at discharge were analysed retrospectively from hospital records.

Three time periods were defined, further called Admission Periods:

Pre-pandemic: from January 1st, 2017, until March 17th, 2020
Pandemic: COVID-19 period, compassing the national state of emergency (March 18th, 2020, until April 30th, 2021)
Post-pandemic: from May1st 2021 until March 31st, 2024.

Hospitalizations were classified according to main diagnosis at discharge, using the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) as:

Mental disorders due to known physiological conditions (F00-09)
Mental and behavioural disorders due to use of psychoactive substances (F10-19)
Schizophrenia, schizotypal and delusional disorders (F20-29)
Bipolar disorders (F30-31 and 39)
Depressive disorders (F32-38)
Other disorders (since the number of other diagnoses were very small overall)

The data obtained was transformed to create three more variables:

LOS (number of days between admission and discharge)
Number of daily admissions (on a separate datasheet, per each day of the study, the number of admissions by diagnostic group and total of patients)
Number of patients occupying psychiatric hospital beds (on a separate datasheet, per each day of the study, the number of occupied hospital beds by diagnostic group and total of patients)

2.3. Statistical analysis

All statistics were performed comparing the three groups and if statistical significance was found, post-hoc analysis was performed to compare between groups. This comparison between the three time periods was initially performed including the total number of patients, and in a second moment the same periods were compared regarding only each individual diagnostic group, evaluating possible different results between them.

The Kolmogorov-Smirnov test was used to assess whether continuous variables displayed a normal distribution. Since generally most distributions were not normal, continuous variables were reported as median, while categorical variables were reported as frequency and percentages.

Categorical and continuous variables were analysed and compared between the three groups, and then pairwise. Comparisons between the groups were evaluated with Kruskal–Wallis test for continuous variables, with Pairwise comparisons to assess significance between groups. Chi-squared test was applied for categorical variables (there were no cells with expected frequencies lower than 5), with post-hoc Bonferroni tests applied to determine the significant groups between each pair of variables (correcting for multiple tests). The significance level was taken as α = 0.05.

Data was received and number of daily admissions summed using Microsoft® Excel® (version 2406 Build 16.0). Regarding number of Hospital beds occupied every day, data was transformed, and variables created using RStudio version 2023.06.1, Build 524 using the packages ggplot2, reshape2, magrittr and dplyr. All statistics were then performed using the statistical software IBM SPSS 26.0 (IBM Corp. Released 2019. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp.).

3.1. Characterization of all admitted patients

A total of 11146 admissions were identified − 5706 during the pre-pandemic period, 1283 during the pandemic period and 4157 admissions in the post-pandemic period of time. Median age was 47 years old; median of previous admissions was 0, with a median LOS of 15 days, a median of 4 daily admissions of acute inpatients, occupying a median number of 103 hospital beds.

Results for the overall patients and for each Admission Period Group are displayed on Table 1. When comparing the three groups, statistical significance was found for every variable.

Table 1

Description of admission episodes (total and for each considered period), comparing the groups for the variables previously defined
Variables	Total (n = 11146)	Admission Period
Variables	Total (n = 11146)	Pre-pandemic (n = 5706)	Pandemic (n = 1283)	Post-Pandemic (n = 4157)	p-value
Sex – male (%)	5964 (53.5%)	3002 (52.6%)	671 (52.3%)	2291 (55.1%)	0.032
Age median (years)	47	48	46	45	< 0.001
Previous admissions median	0	0	1	0	< 0.001
Length of stay - median	15	14	17	16	< 0.001
Daily acute psychiatric admissions - median	4	5	3	4	< 0.001
Daily acute psychiatric beds occupied - median	103	105	89	106	< 0.001

Post-hoc analysis (with Bonferroni correction) helped to further understand differences between each pair of groups, namely identifying a higher rate of males being admitted in the post-pandemic group compared to the pre-pandemic (p < 0.05), a higher median of age in the pre-pandemic period compared to the others (p = 0.041 versus Pandemic and p < 0.001 versus Post-Pandemic period); a higher median of previous admissions in the pandemic group compared to post-pandemic (p < 0.001, non-significant between the other groups), a lower median of admission days in the pre-pandemic period compared to the others (p < 0.001 versus the other 2 periods). Regarding daily acute psychiatric admissions, statistical significance was found between every group in the post-hoc analysis (p < 0.001 for all comparisons) and, regarding the number of occupied psychiatric beds, there was no statistical difference between the pre and post-pandemic periods (p = 0.129, with other comparisons having p < 0.001).

3.2. Length of stay and diagnosis

Results discriminating each group of disorders are presented on Table 2.

Statistical difference is observed regarding the overall proportion of these diagnostic groups between the different admissions periods (p < 0.001). Specifically, the proportion of patients with Schizophrenia, schizotypal and delusional disorders is significantly lower in the pre-pandemic period compared to all other diagnostic groups (p < 0.001, for every comparison) and significantly higher in the post-pandemic group (p < 0.011). The proportion of patients with Mental and behavioural disorders due to use of psychoactive substances is significantly lower than any other diagnostic group in the pandemic period (p < 0.005 in every comparison).

Regarding the different diagnostic groups separately, and for the variables with statistical difference, post-hoc analysis was performed and results present as follows:

3.2.1. Mental disorders due to known physiological conditions

The proportion of patients in the post-pandemic group is statistically smaller than the other two (p < 0.05). Median age was significantly smaller in the post-pandemic group compared to the pre-pandemic period (p = 0.003); no statistical difference was found between groups regarding median LOS nor gender distribution after correction. Admissions in the post-pandemic group are significantly lower than during both pre-pandemic (p < 0.001) and pandemic (p = 0.009) periods. Median number of hospital beds occupied by this group of patients was significantly higher in the pre-pandemic period compared to the pandemic (p < 0.001) and post-pandemic (p < 0.001) groups.

3.2.2. Mental and behavioural disorders due to use of psychoactive substances

The proportion of patients with substance use disorders was significantly lower in the pandemic period compared with the other two, while also being lower in the post-pandemic period compared to the pre-pandemic. Median age was significantly lower in the pandemic group compared to the pre-pandemic (p = 0.003), but not in other comparisons. Median LOS is higher in the post-pandemic group compared to the pre-pandemic (p = 0.001), while the number of previous admissions is lower on the post-pandemic group compared to the others (p = 0.028 with the pre-pandemic, p = 0.038 with the pandemic period). When considering the number of daily admissions, every comparison between groups is statistically significant (p < 0.001). Regarding the number of daily hospital beds occupied, statistical difference has been observed between the three periods (p < 0.001 in every comparison), the highest belonging to the pre-pandemic group and the lowest to the pandemic group.

3.2.3. Schizophrenia, schizotypal and delusional disorders

The proportion of patients diagnosed with Schizophrenia, schizotypal and delusional disorders was significantly lower in the pre-pandemic period compared with the other two. In the post-pandemic group, median age was significantly lower than the other groups (p = 0.018), while median LOS was significantly lower in the pre-pandemic group compared to both pandemic (p = 0.013) and post-pandemic (p = 0.007) time frames. When comparing daily admissions, statistical significance was found between the pre-pandemic versus the post-pandemic periods (p = 0.022, higher in post-pandemic). Regarding the number of daily hospital beds occupied, statistical difference has been observed between the three periods (p < 0.001 in every comparison), the lowest being in the pre-pandemic group and gradually increasing until the post-pandemic time frame.

3.2.4. Bipolar disorders

No statistical differences regarding the proportion of patients were found between groups. Bipolar patients in the post-pandemic group are statistically younger than in the pre-pandemic (p < 0.001). Mean daily admissions was significantly higher in the pre-pandemic group compared to both pandemic (p < 0.001) and post-pandemic (p-0.001) groups. Regarding the number of daily hospital beds occupied, statistical difference has been observed between the three periods (p < 0.001 in every comparison), the highest being in the pre-pandemic group, and the lowest in the Pandemic group.

3.2.5. Depressive disorders

The proportion of patients diagnosed with Depressive disorders was significantly higher in the pre-pandemic period compared to the post-pandemic one, with the proportion of men being significantly higher in the post-pandemic compared to the pre-pandemic period (p < 0.05). Although being more than 10 years apart from the results in the pandemic group, the median age difference was not statistically significant. The LOS was significantly lower in the pre-pandemic group compared to the post-pandemic (p = 0.027). Mean daily admissions was significantly higher in the pre-pandemic group compared to both pandemic (p = 0.007) and post-pandemic (p < 0.001) groups. Regarding the number of daily hospital beds occupied, statistical difference has been observed between the three periods (p < 0.001 in every comparison), the highest being in the pre-pandemic group and the lowest in the pandemic group.

3.2.6. Other disorders

In this group, statistical difference was found in the pre-pandemic period, compared to the other two. In the post-pandemic group, median age was significantly lower than in the pre-pandemic group (p < 0.001). Mean daily admissions was significantly higher in the pre-pandemic group compared to both pandemic (p < 0.001) and post-pandemic (p < 0.001) groups. Regarding the number of daily hospital beds occupied, statistical difference has been observed between the three periods (p < 0.001 in every comparison), the highest being in the pre-pandemic group and the lowest in the pandemic group.

Table 2

Description of admission episodes, for different diagnostic groups, comparing the groups for the variables previously defined
			Total	Admission Period
			Total	Pre-pandemic	Pandemic	Post-pandemic	p-value (< 0.001)
Diagnostic Group	Mental disorders due to known physiological conditions	n (%)	693 (6.2%)	386 (6.8%)	103 (8.0%)	204 (4.9%)
		Sex – male (%)	43.3%	42.7%	37.9%	47.1%	0.292
		Age median (years)	76	79	73	74	0.003
		Previous Admissions median	0	0	0	0	0.095
		Length of stay - median	23	20	29	28	0.038
		Daily acute psychiatric admissions - median	0	0	0	0	< 0.001
		Daily acute psychiatric beds occupied - median	11	13	10	9	< 0.001
	Mental and behavioural disorders due to use of psychoactive substances	n (%)	1805 (16.2%)	1022 (17.9%)	124 (9.7%)	659 (15.9%)
		Sex – male (%)	75.6%	77.1%	71.8%	74.1%	0.213
		Age median (years)	49	50	45.5	49	0.004
		Previous Admissions median	0	1	1	0	< 0.001
		Length of stay - median	14	14	13	15	0.007
		Daily acute psychiatric admissions - median	0	1	0	0	< 0.001
		Daily acute psychiatric beds occupied - median	13	15	6	12	< 0.001
	Schizophrenia, schizotypal and delusional disorders	n (%)	3533 (31.7%)	1554 (27.2%)	489 (38.1%)	1490 (35.8%)
		Sex – male (%)	61.9%	61.3%	61.8%	62.6%	0.741
		Age median (years)	44	45	46	43	0.018
		Previous Admissions median	1	1	1	1	0.056
		Length of stay - median	20	19	22	21.5	0.001
		Daily acute psychiatric admissions - median	1	1	1	1	0.015
		Daily acute psychiatric beds occupied - median	42	35.5	44	47	< 0.001
	Bipolar disorders	n (%)	1893 (17.0%)	986 (17.3%)	198 (15.4%)	709 (17.1%)
		Sex – male (%)	42.6%	41.3%	44.9%	43.7%	0.468
		Age median (years)	49	51	49.50	45	0.000
		Previous Admissions median	1	1	1	1	0.132
		Length of stay - median	17	17	19	18	0.190
		Daily acute psychiatric admissions - median	1	1	0	0	< 0.001
		Daily acute psychiatric beds occupied - median	15	17	12	15	< 0.001
	Depressive disorders	n (%)	1695 (15.2%)	904 (15.8%)	211 (16.4%)	580 (14.0%)
		Sex – male (%)	35.8%	33.1%	36.5%	39.8%	0.029
		Age median (years)	488	48	37	49	0.089
		Previous Admissions median	0	0	0	0	0.524
		Length of stay - median	12	11	13	13	0.018
		Daily acute psychiatric admissions - median	0	1	0	0	< 0.001
		Daily acute psychiatric beds occupied - median	11	12	10	11	< 0.001
	Other disorders	n (%)	1527 (13.7%)	854 (15.0%)	158 (12.3%)	515 (12.4%)
		Sex – male (%)	45.8%	45.8%	47.5%	45.2%	0.886
		Age median (years)	38	41	38	32	< 0.001
		Previous Admissions median	1	0	1	1	0.180
		Length of stay - median	8	8	8.5	9	0.821
		Daily acute psychiatric admissions - median	0	1	0	0	< 0.001
		Daily acute psychiatric beds occupied - median	9	10	6	9	< 0.001

Through the study of psychiatric admissions, the authors intended to understand if there was a maintained change of hospitalization patterns between the period before and during the COVID period, but also if, after the pandemic, hospital admissions had returned to the previous values or, instead, assumed a new pattern.

We found the decrease in daily psychiatric admissions already previously recognized during the pandemic period was partly sustained during the three years after the restrictions due to COVID-19 were lifted. Except for Depressive disorders, during the post-pandemic periods we found patients who were admitted to acute psychiatric wards are overall younger. It would maybe be interesting to, in order to adequately interpret this change, study other socio-demographic variables, such as relationship status, education, employment or living status. Even though some research showed the increase of female gender patients¹⁶, the predominance of male gender in our inpatient population in every one of the time frames was also found in previously published evidence^,16,34.

When comparing pre-pandemic with pandemic and post-pandemic time frames, there is also a gradual increase of mean LOS during a hospital admission (from a median 14 days in the pre-pandemic group to 15 during the pandemic and 16 days after the pandemic), which represents a growing overload of psychiatric hospital beds. Patients diagnosed with Mental disorders due to known physiological conditions presented the largest increase in LOS (from 20 days in the pre-pandemic group to 29 and 28 in the pandemic and post-pandemic groups, respectively) and, not surprisingly, the highest median age (74 years), which is in line with a higher probability of the presence of multiple comorbidities given the age and the diagnosis in itself – variables that may require longer periods of hospitalization and, consequently, a larger consumption of resources. It is also fundamental do stress that individuals with this diagnosis seem to be progressively less admitted in psychiatric wards – this could show a concern to avoid hospitalizing these patients, usually older and or prone to worsening of their symptoms if they are removed from their usual references (house, known people).

Analysing the available data, it is also possible to conclude that the proportion of patients admitted to acute psychiatric wards diagnosed with Schizophrenia, schizotypal or delusional disorders during the post pandemic period was significantly higher. This aligns with previous work^16,28,34. Knowing these usually present with significant psychomotor agitation, aggressiveness towards themselves, others or even objects, and disorganised behaviour, this may furthermore indicate an increased burden of psychiatric services, especially taking it account the scarce availability of human resources. It would be interesting to assess whether these were also accompanied by an increase in involuntary admissions, which are usually associated with a higher administrative effort, besides increasing distress in both patients and their caregivers, and possibly representing a failure of psychiatric treatment.

Additionally, a lower proportion of patients with Mental and behavioural disorders due to use of psychoactive substances during the COVID pandemic could mean a lower access to psychoactive substances, but also maybe a different threshold for the admission of these cases.

Regarding Bipolar and Depressive disorders, there seems to be a lowering of the number of admissions, in general, compared to the pre-pandemic period, and number of patients occupying hospital beds in general. This reduction is not, however, in line with statistics regarding the increased rates of these problems in the general population during the pandemic^35,36. When considering Depressive disorders alone, the proportion of males admitted has increased, as well as the median LOS – this might be related to a different profile of patients, as the lethality of suicidal attempts in males is usually greater, so admissions may take longer to ensure that this risk is greatly reduced.

The main change during the post pandemic time frame is, undoubtedly, a higher proportion of hospital admissions due to primary psychotic disorders. If we take into consideration the fact that Schizophrenia is a disorder that usually leads to severe social, cognitive and executive dysfunction, this might indicate that the current means of care in the community are currently not satisfying patients’ needs - this may include number of outpatient visits, home visits or administration of medication such as long acting injectables. On another end, this may also represent a growing difficulty at the moment of discharge when it comes to meeting the patients’ social needs (both in terms of a place to live but also rehabilitation centres for psychotic patients). It is also fundamental to stress that longer stays have been consistently linked to more adverse outcomes (risk of suicidality, reduced social functioning, unemployment and housing), and increasing costs associated with mental illness^16,32,33. However, considering the current available data, the LOS cannot accurately discriminate the reasoning behind its value (either due to severe psychopathology or due to lack of social and community support), but it is nevertheless relevant to consider that, for this group, the median age is lower and the number of previous admissions is not statistically different – which are possible indicators that these patients would not present more severe symptoms (or symptoms refractory to current pharmacological treatments).

These results seem to be in line with other published studies ^13,16,28 – however, there is a general lack of data for psychiatric admissions regarding the period after COVID. This is a strength of the present study, therefore, aiming to resurface the discussion regarding mental health policies.

It is hypothesized that possible lack of social and rehabilitation facilities might be due to the profound changes of care during the COVID-19 period. These changes were bigger than the access to outpatient care or the redistribution of hospital beds – there was an inevitable breakdown in community resources and financing during this period (including, for example, more beds and resources for elderly people, affected by the virus), with repercussions for the remaining patients. This remark does not intend to point to eventual faults from past decisions, but to understand and identify current discrepancies and societal needs, so further programs and community projects can now reflect the current need in psychiatric care.

We consider this study to have several strengths, such as the usage of administrative data, large sample size and the inclusion of multiple inpatient services. However, there are some limitations to consider - our results may not be applicable to different settings or populations, as they are solely based on a single hospotal. This may lead to selection bias, given that our sample cannot represent a broader population. We also recognize that it would be interesting to collect some other clinical variables not available to us through this means of data collection. It is also important to acknowledge the possibility of data quality issues, such as inaccuracies or coding errors that may have influenced our results. Even though we identified a pre pandemic, a pandemic and a post pandemic time frame, we understand that these timelines might vary according to different criteria, which may have also introduced a bias to our final results.

The argument between community versus hospital based care in psychiatry is one that has been going on for the last decades, with advantages found in both¹.

Although there is a reduction of general psychiatric admissions when compared to the pre-pandemic period, the patients admitted nowadays seem to be younger and to stay hospitalized for longer periods of time, leading to the occupation of the same number of acute psychiatric beds. When considering the higher proportion of patients with Schizophrenia, schizotypal or delusional disorders, further discussion is needed, particularly on the adaptations needed in psychiatric wards for these conditions such as, for example, the possibility of incrementation of number of beds until the reform of proper community-based care is concluded. This may include reorganizing of community services in order to better accommodate these people, acknowledging their specific needs, and the implementation of assertive programs, increasing quality of life and to prevent further hospital admissions or even the need for institutionalization.

COVID-19 - 2019 Coronavirus Disease

HJM – Hospital Júlio de Matos

ICD-10 – International Classification of Diseases, 10^th Revision (World Health Organization)

LOS – Length of stay

SARS-CoV-2 - Severe acute respiratory syndrome coronavirus 2

WHO – World Health Organization

Ethics approval

Upon approval of the hospital’s ethical and scientific committees, the authors were given the anonymized dataset from the hospital, presenting only the requested variables, which made it impossible to contact or identify any of the patients. Since identification of single patients was not possible, no consent form was needed or demanded, and its need was also waivered by the same entity. Data management was conducted in accordance with the General Data Protection Regulation (GDPR) of the European Union. The full names of the Ethics Committees are: Ciro Oliveira, Jorge Poole da Costa, Tiago Casaleiro, Miguel Trigo and Paula Moniz.

Consent for publication

Not applicable.

Availability of data and materials

The data supporting the findings of this study are available from Hospital Júlio de Matos, but restrictions apply to the availability of these data, which were used under license for the purpose of the study, and so are not publicly available. However, these data are available to the authors and should be consulted under reasonable request and permission of Hospital Júlio de Matos. This access should be previously requested via e-mail to the corresponding author.

Competing interests

The authors declare that they have no competing interests.

Funding

No funding was provided for this study.

Authors’ contributions

MN statistically analyzed the available data. CAR and AL contributed to the remaining research and writing of the article, under the supervision of MN. All authors read and approved the final manuscript.

Acknowledgements

The authors acknowledge HJM for providing the data already anonymized, in line with the current data protection laws.

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No competing interests reported.

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Editorial decision: Revision requested
02 Sep, 2024
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You are reading this latest preprint version

Acute Psychiatric Admissions 2017-2024: are we back to pre-pandemic patterns?

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Trial registration:

1. Background

2. Methods

2.1. Data collection

2.2. Study design

2.3. Statistical analysis

3. Results

3.1. Characterization of all admitted patients

3.2. Length of stay and diagnosis

3.2.1. Mental disorders due to known physiological conditions

3.2.2. Mental and behavioural disorders due to use of psychoactive substances

3.2.3. Schizophrenia, schizotypal and delusional disorders

3.2.4. Bipolar disorders

3.2.5. Depressive disorders

3.2.6. Other disorders

4. Discussion

5. Conclusions

Abbreviations

Declarations

References

Additional Declarations

Status:

Version 1