The impact of the COVID-19 pandemic on hospital admissions for psychiatric disorders: results from the multicentre CoMeH study on the Italian population Running title: The impact of COVID-19 on hospital admissions for psychiatric disorders

doi:10.21203/rs.3.rs-4951765/v1

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Research Article

The impact of the COVID-19 pandemic on hospital admissions for psychiatric disorders: results from the multicentre CoMeH study on the Italian population Running title: The impact of COVID-19 on hospital admissions for psychiatric disorders

https://doi.org/10.21203/rs.3.rs-4951765/v1

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Background. To evaluate the impact of the COVID-19 pandemic on hospital admissions for psychiatric disorders, with a focus on the patients’ socioeconomic and demographic characteristics and/or the diagnostic group and type of admission.

Methods. Open cohort of individuals aged ≥ 10 years resident for at least two years in one of three large areas of Italy. The outcome was the first admission for a psychiatric disorder (First Mental Health Admission: FMHA) during the study period (January 2018–December 2021).

Municipality of residence, sex, census tract deprivation index, citizenship, type of admission and the diagnostic group were considered as covariates of interest.

Incidence rate ratios of FMHAs were estimated via an interrupted time series (ITS) analysis using a step-change negative binomial model. Moreover, an ITS analysis was conducted on the monthly number of FMHAs to evaluate the impact of COVID-19 on the temporal trend of FMHAs.

Results. Of the 5,159,363 subjects enrolled, 11,171 had an FMHA in the study period. The incidence of FMHAs decreased after the outbreak of the pandemic, overall and by sex, deprivation level and citizenship. Immigrants from high migration pressure countries (HMPCs) had a greater reduction in FMHAs during COVID-19. A decrease in FMHAs was observed for all diagnoses, the only exceptions being for post-traumatic stress and related disorders, which increased. Involuntary admissions also increased dramatically at the outbreak of the pandemic. Younger age (< 34) and high deprivation level were associated with higher risk of hospitalization. In the following post-outbreak period (March 2020-December 2021), a moderate but significant growing trend of FMHAs was observed, although not reaching the pre-pandemic levels. A more robust increase was found especially for patients with eating disorders, while FMHAs for patients with post-traumatic stress and related disorders decreased to the low pre-pandemic levels. Involuntary FMHAs also decreased in the post-outbreak period.

Conclusions. The pandemic had a considerable, and in some cases dramatic, impact on hospitalizations for psychiatric disorders. However, the effect appeared temporary, suggesting that the expectations of a dramatic surge in mental health issues due to the pandemic could have been overemphasized, at least in the short term. Longer follow-up surveys are needed.

psychiatry

mental health

hospitalizations

immigrants

socioeconomic inequalities

inpatient services

The COVID-19 pandemic had an impact on mental health on different levels, including changes in the accessibility of mental health services. Regarding hospitalization for mental disorders, the evidence varies from nation to nation; a decrease in psychiatric hospitalizations was generally observed but due to the reduction in the number of beds dedicated to non-COVID patients so as to free up beds compatible with mechanical ventilation [1]. Additional reasons for the reduction included difficulties in accessing hospitals, whose emergency departments were full of COVID-19 patients, personal fears of contracting nosocomial infections, and so on. At the same time, the reduced accessibility of outpatient services [2] may have led patients unable to access the outpatient services to go to hospitals as an alternative.

In general, with some variability, the overall trend was a reduction in the number of new patients attending inpatient mental health facilities [3–5], with no differential impact on males or females [4, 6]. Regarding age, the evidence varies; some studies found a reduction only in older patients (≥ 65 years) [6], while others found no difference in terms of age [4]. Apparently, the number of involuntary admissions did not change significantly during the pandemic [3], although some differences were found concerning the diagnostic groups [4, 6]. However, the impact on the distribution of diagnoses appears to be inconsistent. Other differences in terms of the risk of psychiatric admission were reported for young migrants [7] and for individuals experiencing worsening financial situation [8].

Overall, the available evidence suggests that the reduction in hospital admissions for mental disorders after the outbreak of the COVID-19 pandemic tended to persist. Finally, some differences between migrants and natives and in relation to socioeconomic factors have been reported, but to our knowledge, these important factors have not been examined in detail in population studies.

More generally, the available studies counted the number of hospitalizations without reference to the catchment area, so that, to our knowledge, there are no population studies measuring hospitalization rates and their changes during the pandemic in the general population.

The aim of this study was to evaluate the impact of the COVID-19 pandemic on hospital admissions for psychiatric disorders. In particular, trends and rates of these admissions before and after the outbreak of the pandemic were analysed, with a focus on differences related to patients’ socioeconomic and demographic characteristics and/or to the diagnostic group and type of admission.

This study is part of the larger COVID-19 and Mental Health (CoMeH) project [9], evaluating the impact of the COVID-19 pandemic on the use of mental health services in Italy, with a particular focus on socioeconomic and citizenship inequalities. The CoMeH project is a collaborative multicentre study promoted by the National Epidemiologic Observatory for Equity in Health (OENES) of the National Institute for Health, Migration and Poverty (INMP) and conducted in a large Italian area.

The Tuscany Regional Health Agency (RHA), the Bergamo Local Health Authority (LHA) and the Rome 2 LHA participated in the study. The geographic areas covered by the three participating centres represent almost six million beneficiaries (nearly 10% of the entire population) of the Italian National Health Service (NHS).

Within the CoMeH project, we enrolled an open cohort of subjects aged ≥ 10 years resident for at least two years in one of the participating areas and assisted by an NHS general practitioner (GP). The enrolment period is planned from 01 January 2018 to 31 December 2024. Data of the present study are updated to 31 December 2021. The cohort was created retrospectively from the Municipal Registries and the GP Registries of each participating center.

The enrolled subjects exited the cohort at the end of the planned period (31 December 2021) or at time of death or at time of emigration, whichever occurred first. Given the open cohort design, individuals could re-enter the cohort through re-immigration to the resident population of the areas of the participating health centers.

Outcome

We considered as outcome the first admission during the period of follow-up (January 2018 - December 2021) of subjects at least 14 years old for a psychiatric disorder as first diagnosis leading to hospitalization (First Mental Health Admission: FMHA). Having included in the cohort subjects from age 10 years, and because the study covered four years (from 2018 to 2021), 14 years old was the minimum age needed to assess the outcome during the study period.

Data on hospitalizations were retrieved through a deterministic record linkage with the Italian hospital discharge database, which collects information on patients discharged from public and private hospitals, including diagnoses recorded using the International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM). We included in this study all patients that had as their first diagnosis one of the following diagnostic codes of the ICD-9-CM: 291–292 and 303–305 (alcohol and substance disorders); 293–294 (transient psychic disorders due to other conditions); 295 (schizophrenia and related disorders); 296 and 311 (mood disorders); 297 (delusional disorders); 298–299 (other psychoses); 300 (anxiety and neurotic disorders); 301 (personality disorders); 307.1, 307.50 and 307.51 (eating disorders); 307.4 (sleep disorders); 307.8 (pain disorders); 308–309 (traumatic stress and adjustment disorders); 312.30 and 312.31 (impulse and gambling).

Only incident hospitalizations, identified as those events without any other admission for the same selection of psychiatric disorders in the two years prior to the event date, were considered as outcomes.

Covariates

The sociodemographic information of the individuals enrolled in the cohort was obtained from municipal population registers and included date of birth, date of death, date of emigration from or re-immigration to the residence area, municipality of residence, census tract, sex and citizenship.

Socioeconomic status was determined using the national census tract deprivation index, calculated as the sum of five standardized indicators and categorized in quintiles (Low, Middle-Low, Middle, Middle-High, and High Deprivation); it was used as a proxy for the individual measure [10].

For the analysis of migration background, all the residents in Italy without Italian citizenship were considered as immigrants. As they accounted for only about 5% of the foreign resident population in the cohort and generally have a health profile comparable to that of the native population, immigrants from highly developed countries (HDCs) were included in the “Italians” group; immigrants from high migratory pressure countries (HMPCs) were included in the “immigrants” group [11].

The study period was divided in two phases: pre-COVID-19 (from January 2018 to February 2020) and post-COVID-19 (from the outbreak of pandemic in March 2020 to December 2021).

The type of admission (planned, urgent or involuntary) and the group of diagnoses were used to characterize the hospitalizations. Regarding psychiatric diagnoses, the ICD-9-CM single codes were grouped in the following 15 general categories: Adjustment Disorders (all 309 except 309.81); Anxiety Disorders (293.84, 300.00-300.02, 300.09, 300.20-300.23, 300.29, 300.3, 300.5); Delirium/Mental Confusion (291.0, 292.81, 293.0, 293.1, 298.2); Dependencies (291–292, 303–305); Dissociation (300.10-300.15, 300.6); Eating Disorders (307.1, 307.5, 307.50, 307.51); Mood Disorders (293.83, 296, 298.0, 300.4, 309.1, 311); Personality Disorders (301); Post-Traumatic Stress and related Disorders (308, 309.81); unspecified Psychoses (293.81, 293.82, 298, 298.1, 298.4, 298.8, 298.9, 299.90, 299.91); Schizoaffective Disorder (295.7); Schizophrenic Spectrum (295, 295.0-295.6, 295.8-295.9, 297.0-297.9, 298.3); Sleep Disorders (307.4); Somatization (300.7, 300.8, 307.8); Others (293, 293.8, 293.9, 294, 294.8, 294.9, 300.16, 300.19, 300.9, 312.3).

Ethics and Privacy

The study protocol was approved by the following ethics committee: The ethics committee of the Italian National Institute of Health (Istituto Superiore di Sanità), protocol n. 0029105, 25 July 2022. The study was conducted in accordance with the Declaration of Helsinki.

Authorization for the use of anonymized data was obtained from the Data Protection Officer of all the participating centres according to EU regulation 2016/679.

Privacy protection was ensured by assigning each individual a validated anonymous patient identifier so that multiple data sources could be linked, thereby providing the study with the complete care pathway of all the citizens resident in the three geographical areas involved in the study. Any personally identifiable information was hidden from individual records.

Statistical analysis

Baseline demographic and socioeconomic characteristics of the CoMeH study cohort and of the FPDAs identified during the follow-up are described as frequency and percentages.

To assess the effect of the pandemic on FMHAs, crude incidence rates per 100,000 person days, with 95%CI, were calculated overall and comparing the two time periods (pre-COVID-19 and post-COVID-19) by sex, deprivation level, citizenship and group of diagnosis.

In order to capture the impact of the pandemic on hospital admissions for psychiatric disorders, we conducted two types of analysis, both in the context of interrupted time series (ITS) [12].

In the first analysis, incidence rate ratios (IRR) of FMHAs with 95%CI were estimated via an ITS analysis using a step-change negative binomial model [13]. The model was performed taking into account the presence of over-dispersion, with the log person time of follow-up for each group as offset and adjusted for age classes, sex, a binary period term (pre-pandemic and pandemic), citizenship, deprivation level, a linear time variable to account for trends and a categorical calendar month variable to capture any seasonal effects. Moreover, to assess the effect of citizenship and deprivation level on FMHAs pre-pandemic and pandemic, two interaction terms between citizenship and time period and between deprivation level and time period were included. Moreover, the interaction between age and time period was also tested.

In the second analysis, the impact of the pandemic on the temporal trend of FMHAs was investigated, estimating IRR, overall and stratified by sex, age groups, citizenship, deprivation level, type of admission and diagnoses, selecting only those diagnostic groups with at least 150 admissions. In this case, the ITS analysis was conducted on the monthly number of FMHAs. According to the procedure proposed by Schuengel, et al. [14], data were detrended using Loess regression and smoothing [15], and seasonality was tested. If the presence of seasonal effects was identified, an adjustment was performed. The change in slope from the pre-pandemic to the pandemic period was tested using Poisson segmented regression with Newey-West standard errors to account for autocorrelation and heteroscedasticity [12]. The pre-COVID-19 trend, the immediate effect of the outbreak of the pandemic and the post-COVID-19 trend were evaluated.

All statistical analyses were performed using SAS 9.3 and R Studio (version 4.1.3).

Overall, 5,159,363 subjects were enrolled in the cohort between the 01 January 2018 and 31 December 2021. During follow-up, 11,171 FMHAs were observed (Table 1). Compared to the general population, the patients admitted to the hospital with a psychiatric diagnosis were younger (34.1% vs. 24.3% aged < 34 years), while the distributions by sex, deprivation level and citizenship were similar.

Table 1

Baseline characteristics of the study population and of first mental health hospital admissions (FMHAs).
Baseline characteristics	Population		First MH hospital admission
Baseline characteristics	N	%	N	%
Total	5.159.363		11.171	0,22%
Age-groups
≤ 34	1.254.290	24,3%	3.811	34,1%
35–64	2.510.617	48,7%	5.130	45,9%
65–74	664.706	12,9%	964	8,6%
75–84	506.405	9,8%	896	8,0%
85+	223.345	4,3%	370	3,3%
Sex
Males	2.466.975	47,8%	5.359	48,0%
Females	2.692.388	52,2%	5.812	52,0%
Deprivation level (quintiles)
Low	1.026.856	19,9%	2.277	20,4%
Middle-low	1.193.167	23,1%	2.628	23,5%
Middle	1.065.511	20,7%	2.289	20,5%
Middle- high	753.674	14,6%	1.685	15,1%
High	464.521	9,0%	1.114	10,0%
Missing data	655.634	12,7%	1.178	10,6%
Citizenship
Italians	4.614.768	89,4%	10.093	90,4%
Immigrants from HDCs	22.650	0,4%	112	1,0%
Immigrants from HPMCs	446.334	8,7%	906	8,1%
Missing data	75.611	1,5%	60	0,5%
Group of diagnoses
Delirium/Mental Confusion			728	6,5%
Dependencies			1.317	11,8%
Dissociation			100	0,9%
Eating Disorders			493	4,4%
Anxiety Disorders			364	3,3%
Sleep Disorders			12	0,1%
Mood Disorders			3.694	33,1%
Personality Disorders			804	7,2%
Schizoaffective Disorder			311	2,8%
Unspecified Psychoses			1.117	10,0%
Adjustment Disorders			733	6,6%
Post-Traumatic Stress and related Disorders			244	2,2%
Somatization			134	1,2%
Schizophrenic Spectrum			961	8,6%
Others			159	1,4%
Type of admission
Scheduled			2.191	19,6%
Urgent			8.533	76,4%
Involuntary medical treatment			386	3,5%

Mood Disorders were the most frequent diagnoses (33.1%), followed by Dependencies (11.8%), unspecified Psychoses (10%), Schizophrenic Spectrum (8.6%) and Personality Disorders (7.2%). Most of the hospitalizations were urgent (76.4%).

As shown in Table 2, crude rates of incidence of FMHAs decreased after the outbreak of the pandemic, overall and by sex, deprivation level and citizenship. Immigrants from HMPCs had higher rates compared to Italians in the pre-pandemic period and experienced a higher reduction in rates during the pandemic. Analysing rates by group of diagnoses, a decrease was observed for all diagnoses, the only exception being for post-traumatic stress disorders, which increased.

Table 2

FMHAs: Crude incidence rates *100,000 person days by sociodemographic characteristics and group of diagnosis in pre- and post-COVID-19 periods.
	Pre COVID-19		Post COVID-19
	Users	Crude incidence rate (95% CI)*100,000 person-days	Users	Crude incidence rate (95% CI)*100,000 person-days
Total	6.401	0.169 (0.165–0.173)	4.770	0.147 (0.143–0.151)
Sex
Males	3.091	0.171 (0.165–0.177)	2.268	0.147 (0.141–0.153)
Females	3.310	0.167 (0.161–0.173)	2.502	0.148 (0.142–0.154)
Deprivation level (quintiles)
Low	1.281	0.169 (0.160–0.179)	996	0.154 (0.145–0.164)
Middle-low	1.533	0.174 (0.166–0.183)	1.095	0.146 (0.137–0.155)
Middle	1.291	0.165 (0.156–0.174)	998	0.149 (0.140–0.159)
Middle-high	974	0.176 (0.165–0.187)	711	0.151 (0.140–0.162)
High	637	0.186 (0.172–0.201)	477	0.165 (0.150–0.180)
Citizenship
Italians + Immigrants from HDCs	5.816	0.169 (0.165–0.173)	4.337	0.148 (0.144–0.153)
Immigrants from HPMCs	510	0.175 (0.160–0.191)	396	0.146 (0.132–0.161)
Group of diagnoses
Delirium/Mental Confusion	438	0.0135 (0.0123–0.0148)	290	0.0089 (0.0079-0.01)
Dependencies	817	0.0252 (0.0235–0.027)	500	0.0154 (0.0141–0.0168)
Dissociation	62	0.0019 (0.0015–0.0025)	38	0.0012 (0.0008–0.0016)
Eating Disorders	273	0.0084 (0.0075–0.0095)	220	0.0068 (0.0059–0.0077)
Anxiety Disorders	199	0.0061 (0.0053–0.0071)	165	0.0051 (0.0043–0.0059)
Sleep Disorders	9	0.0003 (0.0001–0.0005)	3	0.00009 (0.00002-0.00027)
Mood Disorders	2.081	0.0642 (0.0615–0.0671)	1.613	0.0498 (0.0474–0.0522)
Personality Disorders	448	0.0138 (0.0126–0.0152)	356	0.011 (0.0099–0.0122)
Schizoaffective Disorder	201	0.0062 (0.0054–0.0071)	110	0.0034 (0.0028–0.0041)
Unspecified Psychoses	582	0.018 (0.0165–0.0195)	535	0.0165 (0.0151–0.018)
Adjustment Disorders	427	0.0132 (0.012–0.0145)	306	0.0094 (0.0084–0.0106)
Post-Traumatic Stress and related Disorders	95	0.0029 (0.0024–0.0036)	149	0.0046 (0.0039–0.0054)
Somatization	93	0.0029 (0.0023–0.0035)	41	0.0013 (0.0009–0.0017)
Schizophrenic Spectrum	586	0.0181 (0.0167–0.0196)	375	0.0116 (0.0104–0.0128)
Others	90	0.0028 (0.0022–0.0034)	69	0.0021 (0.0017–0.0027)

The results of the multivariate ITS analysis are shown in Table 3. Model 1 shows a reduction in accesses in the pandemic period compared to the pre-pandemic one (IRR = 0.80 p < 0.001), which was confirmed after adjusting for age, sex, deprivation level and citizenship. Instead, no significant interactions were detected between the COVID-19 period and deprivation level, or COVID-19 period and citizenship. All age classes showed lower probabilities of FMHAs compared to the youngest class (< 34). High deprivation level was associated with a higher risk of hospitalization, although at the limit of statistical significance. When we tested the interaction between age class and the COVID-19 period, a significant effect modification was found by age, with a greater impact of COVID-19 period in terms of decreasing probabilities of FMHAs on people aged 65 or more (Model 2).

Table 3

Results of ITS multivariate regression models. Adjusted incidence rate ratios and 95%CI of FMHAs
	Model1			Model2
Predictors	IRR	CI	p	IRR	CI	p
Time period (ref. Pre-COVID-19)
Post-COVID-19	0,80	0.72–0.90	< 0.001	0,88	0.79–0.97	0,011
Time (continuous)	1,00	1.00–1.01	0,002	1	1.00–1.01	0,002
Study Month (ref. January)
February	1,01	0.92–1.12	0,831	1,01	0.92–1.12	0,831
March	0,98	0.89–1.09	0,760	0,98	0.89–1.09	0,762
April	0,91	0.82–1.01	0,067	0,91	0.82–1.01	0,066
May	1,04	0.94–1.14	0,467	1,04	0.94–1.14	0,467
June	1,05	0.95–1.16	0,361	1,05	0.95–1.15	0,363
July	1,07	0.97–1.18	0,159	1,07	0.97–1.18	0,159
August	0,97	0.88–1.07	0,539	0,97	0.88–1.07	0,529
September	1,03	0.94–1.14	0,506	1,03	0.94–1.14	0,515
October	0,97	0.88–1.07	0,515	0,97	0.88–1.07	0,507
November	0,98	0.88–1.08	0,649	0,98	0.88–1.08	0,638
December	0,89	0.81–0.99	0,030	0,89	0.81–0.99	0,028
Deprivation Level (ref. Low)
Middle-low	1,02	0.94–1.10	0,663	0,99	0.93–1.04	0,624
Middle	0,96	0.88–1.04	0,295	0,96	0.91–1.02	0,216
Middle-high	1,02	0.93–1.11	0,718	1,00	0.93–1.06	0,936
High	1,08	0.98–1.19	0,112	1,08	1.00–1.16	0,054
Citizenship (ref. Italians + HDCs)
Immigrants from HPMCs	0,93	0.84–1.02	0,117	0,91	0.84–0.98	0,009
Sex (ref. Females)
Males	0,98	0.94–1.02	0,413	0,98	0.94–1.02	0,404
Age groups (ref. ≤34)
35–64	0,65	0.63–0.69	< 0.001	0,71	0.67–0.75	< 0.001
65–74	0,46	0.43–0.50	< 0.001	0,51	0.46–0.56	< 0.001
75–84	0,59	0.55–0.64	< 0.001	0,61	0.55–0.68	< 0.001
85+	0,69	0.61–0.77	< 0.001	0,81	0.71–0.93	0,003
*Deprivation LevelTime period**			p = 0.6
Middle-low	0,93	0.82–1.04	0,215
Middle	1,01	0.90–1.14	0,856
Middle-high	0,96	0.84–1.09	0,517
High	0,98	0.85–1.14	0,831
*Citizenship Time period**			p = 0.6
Immigrants from HPMCs	0,96	0.83–1.11	0,557
*Age groupsTime period**
35–64				0,84	0.77–0.92	< 0.001
65–74				0,81	0.70–0.95	0,009
75–84				0,92	0.79–1.08	0,309
85+				0,61	0.47–0.79	< 0.001

Table 4 shows the results of the ITS analysis conducted on the trend of the number of monthly FMHAs, overall and stratified by sex, citizenship, deprivation level, diagnostic group and type of admission. Overall, the average number of FMHAs was 232.7 per month (SD = 25.8), with a significant drop of 23% (IRR = 0.77, 95%CI 0.67–0.89) in all FMHAs, coinciding with the outbreak of the COVID-19 pandemic (March 2020). In the subsequent period, up to 31 December 2021, a moderate but significant growing trend (IRR = 1.01, 95%CI 1.002–1.017) was observed, although it did not reach the pre-pandemic levels (Table 3 and Fig. 1).

Table 4

Results of ITS analysis of the monthly number of admissions, by demographic and socioeconomic variables, type of admission and group of diagnosis.
FMHA characteristics	Mean (per month)	SD	Trend pre COVID-19	COVID-19 immediate effect	Trend post COVID-19
FMHA characteristics	Mean (per month)	SD	IRR (95%CI)	IRR (95%CI)	IRR (95%CI)
Total	232,7	25,8	1.002 (1.000-1.004)	0.770 (0.667–0.889)	1.010 (1.002–1.017)
Sex
Males	111,7	14,7	1.002 (0.999–1.005)	0.785 (0.669–0.920)	1.007 (0.996–1.018)
Females	121,1	16,1	1.003 (1.000-1.005)	0.757 (0.703–0.814)	1.011 (1.006–1.016)
Age classes
14–34	79,4	12,4	1.012 (1.008–1.016)	0.738 (0.604–0.903)	1.017 (1.014–1.019)
35–64	106,9	15,0	0.999 (0.996–1.002)	0.870 (0.733–1.031)	0.998 (0.986–1.010)
65–74	20,1	4,5	0.998 (0.995–1.002)	0.680 (0.602–0.767)	1.017 (1.007–1.028)
75–84	18,7	5,4	1.003 (0.993–1.013)	0.541 (0.415–0.706)	1.030 (1.013–1.047)
85+	7,9	3,8	0.974 (0.961–0.987)	0.581 (0.395–0.854)	1.013 (0.991–1.036)
Deprivation level (quintiles)
Low	47,4	7,4	1.004 (1.001–1.008)	0.759 (0.680–0.848)	1.012 (1.005–1.019)
Middle-low	54,8	8,6	0.997 (0.991–1.003)	0.817 (0.682–0.978)	1.006 (0.996–1.016)
Middle	47,7	7,7	1.005 (1.000-1.010)	0.793 (0.644–0.977)	1.007 (0.994–1.020)
Middle- high	35,1	8,1	1.003 (1.002–1.005)	0.694 (0.670–0.719)	1.015 (1.013–1.017)
High	23,2	5,1	1.000 (0.996–1.004)	0.783 (0.663–0.925)	1.010 (0.998–1.022)
Citizenship
Italians + HDCs	211,5	23,7	1.002 (1.000-1.004)	0.767 (0.666–0.884)	1.010 (1.000-1.020)
Immigrants from HPMCs	18,9	4,7	1.006 (1.001–1.011)	0.805 (0.706–0.918)	1.005 (0.998–1.013)
Group of diagnoses
Delirium/Mental Confusion	15,2	4,7	0.991 (0.981-1.000)	0.582 (0.447–0.759)	1.035 (1.020–1.049)
Dependencies	27,4	7,1	1.003 (0.997–1.009)	0.625 (0.462–0.843)	1.010 (0.993–1.027)
Eating Disorders	10,3	3,1	1.004 (1.002–1.006)	0.651 (0.619–0.684)	1.028 (1.025–1.031)
Anxiety Disorders	7,6	2,6	0.991 (0.985–0.998)	0.729 (0.649–0.819)	1.034 (1.029–1.039)
Mood Disorders	77,0	11,4	1.005 (1.002–1.009)	0.727 (0.644–0.822)	1.014 (1.004–1.024)
Personality Disorders	16,8	3,9	1.003 (0.998–1.008)	1.018 (0.940–1.102)	0.989 (0.986–0.993)
Schizoaffective Disorder	6,5	3,5	0.998 (0.974–1.003)	0.825 (0.569–1.194)	0.992 (0.964–1.021)
Unspecified Psychoses	23,3	5,3	1.001 (0.997–1.005)	0.970 (0.873–1.079)	1.009 (1.004–1.014)
Adjustment Disorders	15,3	4,1	1.011 (1.006–1.016)	0.647 (0.518–0.808)	1.012 (0.999–1.024)
Post-Traumatic Stress and related Disorders	5,1	3,1	1.021 (1.009–1.032)	1.973 (1.188–3.276)	0.972 (0.942–1.004)
Schizophrenic Spectrum	20,0	5,1	0.993 (0.982–1.004)	0.972 (0.776–1.216)	0.986 (0.973–0.998)
Others	3,3	1,6	1.025 (1.016–1.034)	0.621 (0.466–0.829)	1.007 (0.986–1.029)
Type of admission
Scheduled	45,7	10,9	1.007 (1.004–1.009)	0.558 (0.501–0.622)	1.018 (1.010–1.026)
Urgent	177,8	17,6	1.003 (1.000-1.005)	0.816 (0.714–0.932)	1.009 (1.000-1.017)
Involuntary medical treatment	8,0	3,4	0.985 (0.972–0.999)	1.323 (0.853–2.053)	0.972 (0.937–1.008)

Relevant differences were found by diagnostic group (Table 4 and Figs. 2–3). A significant drop in FMHAs at the outbreak of the pandemic was observed for delirium/mental confusion (-42%), dependencies (-38%), adjustment disorders (-35%), eating disorders (-35%), anxiety and mood disorders (both − 27%). In patients with schizophrenia, schizoaffective disorder, unspecified psychoses and personality disorders, changes were not significant. In countertendency, post-traumatic stress and related disorders showed a dramatic increase in FMHAs (+ 97%).

The dynamics of FMHAs in the subsequent period up to December 2021 also showed considerable differences: a significant monthly increase in FMHAs was observed for unspecified psychoses, eating disorders, anxiety disorders, mood disorders and delirium/mental confusion. Mood disorders returned to the pre-pandemic levels but below the counterfactual line. Schizoaffective disorder showed a flat post-outbreak trend but in line with a decreasing trend that had already started before the pandemic outbreak. Personality disorders and schizophrenia showed a decreasing trend post-outbreak; in December 2021, the number of FMHAs was below both the pre-pandemic level and the counterfactual line. In the case of schizophrenia, the decreasing trend had already started before the pandemic, while the pre-pandemic trend for personality disorders had been stable. Finally, post-traumatic stress and related disorders showed a peculiar trend, with a reduction in this period, returning to pre-pandemic levels largely below the counterfactual line.

When analysing differences by sex, citizenship and deprivation level, the trends were similar to those observed for the general population, in both the COVID-19 immediate effect and the subsequent trends. The analysis by age group showed a stronger COVID-19 immediate effect in people aged ≥ 75 (Table 4 and Supplementary Figs. 1–4).

As shown in Table 4 and Fig. 4, there was a decrease in both planned and urgent FMHAs at the outbreak of the pandemic (-44% and − 18%, respectively), while there was a significant increase (+ 32%) in involuntary FMHAs. In the post-outbreak pandemic period up to December 2021, there was a significant increasing trend only for planned admissions, although they were still below the pre-pandemic level. In the same period, urgent admissions had returned to pre-pandemic levels but below the counterfactual level. Finally, involuntary FMHAs decreased in the post-outbreak period, in line with the counterfactual trend.

Our study shows that the outbreak of the COVID-19 pandemic was associated with an overall reduction in first admissions in hospitals for mental disorders. Many factors may have played a role in determining this result, despite the fact that an increase in hospitalizations due to the unavailability of alternative treatments in outpatient services was to be expected. Among these factors were a reduction in the number of beds in the psychiatric ward because they were transformed into beds for COVID-19 patients, difficulty in reaching hospitals, whose access points were busy with COVID-19 patients, the blocking of waiting lists for new scheduled admissions, fear of going to hospitals due to the increased risk of being infected, etc. [1, 3–5, 16]. This overall reduction was confirmed also after adjusting for age, sex, deprivation level and citizenship. In line with previous studies [4, 6], the reduction in FMHAs was not significantly different between males and females.

Younger patients (age < 34) had a significantly lower reduction in FMHAs compared to older people, albeit within an overall reduction. This finding is in line with Hamlin et al. [6] but contrasts with Kim et al. [4], who had found no differences related to the age of patients.

During the period of observation, high deprivation level was associated with a higher risk of hospitalization, consistently with the international literature that shows worse mental health among people living in more deprived areas [17]. Further study using indicators of multiple dimensions of social status and their relationship to mental health services accessibility is needed to investigate how socioeconomic conditions changed during the pandemic.

Our results show that migrants from HMPCs had lower rates of FMHAs than did Italians and immigrants from HDCs, both before and after the outbreak of COVID-19. Immigration in Italy is a relatively recent phenomenon, so that immigrants are younger than the Italians and have better health conditions and this could explain the lower use of mental health services [18]. Moreover, in our study the reduction of psychiatric hospitalizations in immigrants from HMPCs was greater during the first phase of the pandemic, but the slope of the post-outbreak pandemic increase curve was also less steep compared to that for Italians and immigrants from HDCs. This finding is in line with previous pre-pandemic research showing that immigrants from HMPCs usually have lower rates of FMHAs compared to the Italian population [19]. During the pandemic, another study conducted in an Italian setting showed an increase in psychiatric admissions among migrants, especially those in the youngest age group, who were also at higher risk of involuntary treatment [7]. Our findings apparently do not confirm this evidence, but considering the methodological differences (e.g., Tarricone et al.’s study [7] covers a different Italian area and a shorter period of time), a future study focusing in detail on immigrants is needed.

Regarding the types of hospital admission, before the outbreak of the pandemic scheduled and urgent admissions had a similar slightly increasing trend, while involuntary admissions were decreasing. With the onset of the pandemic, scheduled and urgent admissions dropped abruptly, while involuntary admissions increased dramatically. Finally, the post-outbreak pandemic trend returned to the pre-pandemic dynamic. Our evidence of a temporary abrupt increase in involuntary treatments during the first phase of the pandemic contrasts with previous reports of unchanged involuntary admission in the COVID period [3, 18]. However, our findings seem more in line with the expectation that during the COVID emergency, scheduled or urgent hospitalizations would be more difficult to organize, while involuntary treatment in cases of a psychiatry emergency did not encounter the same barriers to access. The study by Di Lorenzo et al. [20] indirectly confirms this expectation, because, even if they did not report an increase in involuntary admissions, they still found a relevant reduction during the pandemic in the number of voluntary admissions, so that in 2022, involuntary admissions became prevalent.

Finally, the impact of the pandemic restrictions appeared to be different by diagnostic group. Overall, there was a general drop in FMHAs at the outbreak of the pandemic for all diagnoses, with the exception of post-traumatic stress and related disorders, which increased dramatically at the beginning and then dropped in the subsequent period up to December 2021 (the robust increase in the initial period being only temporary). Regarding the other diagnostic groups, there was a general return towards the pre-pandemic levels in the post-outbreak period, with a more or less rapid increase depending on the diagnosis. Anxiety disorders, eating disorders and delirium/mental confusion showed the most rapid increases.

These findings differ from previous studies that had found no significant differences in the slight reduction of hospital admissions for mood disorders and stress-related disorders [6], or an increasing pattern for bipolar disorder, depression and anxiety disorders [4]. The non-significant differences in FMHAs in the case of psychoses are in line with Hamlin et al. [6], who also found a significant decrease in admissions for substance use disorders, confirmed in our study. However, their report of a significant increase for personality disorders [6] was not confirmed by our data.

Eating disorders showed a rapid post-outbreak increase in FMHAs that at December 2021 were above both the pre-pandemic incidence and the counterfactual line. This finding is in line with the evidence that patients with eating disorders experienced worsening symptomatology and increased isolation, with an upsurge in hospital admissions as a result of the timing of COVID-19 pandemic lockdowns [21]. Further studies should identify vulnerable groups among the different kinds of eating disorders and study the long-term consequences of the pandemic period [22].

Regarding psychoses, schizophrenia showed a post-outbreak reduction in the trend of FMHAs, in line with Kim et al. [4], while unspecified psychoses increased significantly, with an incidence of FMHAs in December 2021 that was above the pre-pandemic incidence. The reasons for the opposite trend observed in our study are not clear, and further research is needed to understand whether this was only an artefact due to the way the diagnoses were made or whether it is a signal that something is changing in the way patients are presenting their psychotic symptoms.

It was expected that the pandemic had a significant impact on patients with personality disorders; in these patients, social distancing and loneliness may have caused anxiety of being abandoned, social withdrawal and feelings of emptiness [23]. However, this effect was not evident in rates of FMHAs in our population, whose incidence in December 2021 remained below both the pre-pandemic levels and the counterfactual line. Further research using other proxies to study this possible effect is needed.

As expected, the COVID-19 emergency was responsible of a collective anxiety that was better managed once the authorities disseminated messages to reduce the level of uncertainty around the evolving COVID-19 situation [24]. In general, it was estimated that cases of anxiety disorders increased by 25% globally due to the pandemic [25]. However, thanks to the induction of resilience capabilities, the acute increase in anxiety at the pandemic onset could have declined over time, returning to pre-pandemic levels [26], suggesting that these findings may be overestimated [27]. Hospitalizations are not the best proxy to study anxiety because it usually does not require inpatient treatment. However, some effect was detected even at this level, considering that we found that the pre-pandemic trend of a reduction in FMHAs for anxiety disorders was inverted, with a significant rapid increase after the outbreak of the pandemic. As, to our knowledge, there are no studies specifically addressing possible severe forms of pandemic-induced anxiety, further longitudinal research on this is needed.

Symptoms of post-traumatic stress were largely expected due to the relevant impact of fear of COVID worldwide, and PTSD was in fact reported to be increased both in prospective and retrospective symptom analyses [28]. Despite the low number of FMHAs for post-traumatic stress and related disorders in our population, their significant increase (+ 97%) at the beginning of the pandemic, followed by a post-outbreak return to the pre-pandemic levels, is interesting because it confirms an acute post-traumatic impact of the pandemic that was only temporary, at least for the most severe forms that required hospitalization. This finding is in line with Bourmistrova et al.’s [26] long-term reduction in the effect of the pandemic on PTSD in the population. Because there are relevant differences of rates of PTSD in specific subgroups, including among others, children, adolescents, COVID-19 survivors and health professionals [29], further studies addressing the characteristics of the patients hospitalized with a diagnosis of PTSD and related disorders in more detail are needed.

Finally, we observed a rapid increase in FMHAs for delirium/mental confusion in the post-pandemic period. The reasons behind this finding are not clear, and the group is too heterogeneous to permit explanatory hypotheses.

Strengths and limitations of the study

To our knowledge, this is the first longitudinal study investigating the impact of the pandemic on hospital admissions for psychiatric disorders in Italy. Our study is based on a large population-based cohort followed up longitudinally through a powerful approach that allowed us to evaluate the large amount of information regarding sociodemographic and clinical conditions of the population cohort and their hospital admissions.

Using the Italian hospital information system allowed us to analyse the diagnostic groups that led to a hospitalization, thus accurately identifying the outcome of interest, and to exclude those patients with psychiatric disorders but who were hospitalized for other causes.

A limitation of our study is the relatively short follow-up of the cohort, as only the data up to the end of 2021 were available, which did not allow us to investigate the long-term effect of the pandemic. However, we were able to cover the most difficult phases of the pandemic. Moreover, as the project has planned to extend the follow-up until 2024, we will be able to study the long-term effect of the pandemic on hospital admissions for psychiatric disorders in Italy in the near future.

Another limitation is that we used an area-based indicator, i.e., the census tract deprivation index, as a proxy to study individuals’ socioeconomic status, which may have introduced ecological bias. Consequently, we have no direct information on the subjects’ individual socioeconomic status, such as income or education level. Such individual information is important because it has been shown that many individual social factors, such as living alone and low or decreased income during the pandemic, were associated with exacerbating barriers to accessing mental health care [30]. Furthermore, the use of citizenship as a proxy for immigrant status could result in a residual information bias. In fact, according to Italian legislation, individuals born in Italy to non-Italian citizens are considered foreigners until the age of 18 years, while individuals born abroad can obtain Italian citizenship if they are descendants of Italian ancestors. These two facts slightly influenced the selection of the immigrant population: while boys and girls born in Italy were included as immigrants, people born abroad were included in the Italian population. Moreover, having enrolled the subjects who were resident in the catchment areas of the study, undocumented migrants and migrants without a formal residence were not included.

Furthermore, it should be mentioned that the case definition for incident cases (i.e., absence of hospitalization for psychiatric disorders in the previous two years) probably led us to overestimate the incidence in that this is a relatively brief period for excluding previous hospitalizations.

Finally, although our population cohort covers about 6 million beneficiaries (nearly 10% of the entire Italian population), it is made up of residents in northern and central Italy. It is possible that the lack of coverage of any area located in the south of Italy could have introduced a bias in overestimating the impact of COVID-19, which more strongly affected the regions in the North.

This study is part of the CoMeH project, designed to investigate the impact of the pandemic on mental health more comprehensively by evaluating all the main mental health services, including hospitalization, emergency care, outpatient care, psychiatric residential facilities and psychopharmacological prescriptions.

Regarding hospitalization for mental disorders during the pandemic, we found a general drop in hospitalizations at the outbreak of the COVID-19 emergency, followed by an increase in the period from the end of March 2020 to December 2021 that, in many instances, remained below the expected trend. In particular, the drop in hospitalizations in the initial period of the pandemic was higher in younger patients, migrants from high migratory pressure countries and patients with scheduled/urgent admissions. High deprivation level was associated with a higher risk of hospitalization. Finally, in countertendency, at the outbreak of the pandemic the hospitalizations increased in patients with involuntary admissions and in patients with post-traumatic stress and related disorders.

In the subsequent period, hospitalizations generally tended to increase, more slowly in immigrants and more rapidly in patients with eating disorders, while hospitalizations of patients with involuntary admissions and patients with post-traumatic stress and related disorders decreased to pre-pandemic levels.

Overall, the study suggests that the pandemic had a relevant, and in some cases dramatic, impact on hospitalizations for mental health diagnoses. However, even in those patients who seemed more affected (e.g., those with post-traumatic stress and related disorders), the effect appeared temporary, suggesting that the expectations of a dramatic surge in mental health problems due to the pandemic may have been overemphasized, at least in the short term. It is possible that long-lasting effects will be more evident in longer follow-up surveys, so further studies are needed to track these trends in the next few years.

Competing interests:

The authors have no competing interests.

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Author Contribution

Massimiliano Aragona, Martina Ventura, Roberta Ciampichini, Anteo Di Napoli, Valeria Fano, Sara Leone, Martina Pacifici, Claudio Rosini, Caterina Silvestri, Fabio Voller, Alberto Zucchi, and Alessio Petrelli projected the study and settled the methodology.Roberta Ciampichini, Valeria Fano, Claudio Rosini, Caterina Silvestri, Fabio Voller, and Alberto Zucchi collected the data.Martina Ventura, Sara Leone and Alessio Petrelli statistically analysed the data.Massimiliano Aragona, Martina Ventura, and Alessio Petrelli wrote the manuscript.All authors reviewed a first draft of the manuscript and provided suggestions for appropriate changes.All authors have approved the submitted version and have agreed both to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature.

Data Availability

Data that support the findings of this study cannot be shared openly but are available on request writing to the correspondance author of this manuscript.

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The impact of the COVID-19 pandemic on hospital admissions for psychiatric disorders: results from the multicentre CoMeH study on the Italian population Running title: The impact of COVID-19 on hospital admissions for psychiatric disorders

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