Abstract
We examine the volume and characteristics of psychiatric ED visitations through a perspective of four COVID-19 lockdowns. All adult visitations to the ED of Shalvata Mental Healthcare center (Israel) during 2020–2021 were retrieved and statistically analysed and data from 2017 to 2019 was considered as control. Voluntary and involuntary ED visitations were considered, separately and combined. We find that the significant decrease in the volume of voluntary ED visitations during the 1st lockdown was quickly overturned, roughly returning to the pre-pandemic state following its conclusion. In parallel, the volume of involuntary ED visitations has dramatically increased, with the most striking levels observed during the second and third lockdowns. Elapsed time since the first occurrence of COVID-19 in Israel and the level of governmental restrictions is significantly associated with the increase in the volume of ED visits and admissions, the admission rate and the rate of involuntary visits. The prolonged consequences associated with the pandemic and the measures taken to control it suggest that it is unreasonable to expect a return to normal ED utilization in the near future. As such, alternatives to strict lockdowns should be favored when possible and urgent strengthening of psychiatric care is warranted.
Keywords: Psychiatric emergency department, COVID-19, Governmental restrictions, Involuntary hospitalization
1. Introduction
Since the emergence of the Coronavirus disease 2019 (COVID-19) pandemic at the end of 2019, many countries have been intermittently implementing lockdowns and other restrictions in order to reduce transmission rates and virus-associated morbidity. As a result, many determinants of poor mental health were exacerbated, leading to increased depressive, anxious and post-traumatic stress symptoms in the general population (Vindegaard and Benros, 2020; Salari et al., 2020; Xiong et al., 2020; Santomauro et al., 2021; Czeisler et al., 2021; Henssler et al., 2021).
Focusing on severe mental conditions and symptoms, prior work has examined the possible association between lockdowns and the volume and characteristics of patients requiring urgent psychiatric help in either psychiatric or general Emergency Departments (EDs). These studies were conducted in a wide range of countries including the USA (Holland et al., 2021), Germany (Hoyer et al., 2021), France (Pignon et al., 2020), Portugal (Goncalves-Pinho et al., 2021), Switzerland (Ambrosetti et al., 2021b), Italy (Beghi et al., 2021), Spain (Rodriguez-Jimenez et al., 2021) and Australia (Jagadheesan et al., 2022), to name a few. These studies have consistently demonstrated a sharp reduction in the number of psychiatric ED visitations (ED visits, for short) during the first COVID-19 lockdown compared to the pre-pandemic period, which was later overturned during the post-lockdown period with a significant increase in the number of visitations who, according to most studies, present worse mental conditions and symptoms.
Over time, governments have implemented varying levels of restrictions in response to the COVID-19 outbreak, with most countries today avoiding lockdowns altogether (Hale et al., 2020). Unfortunately, little is known to date about the possible association between non-lockdown restrictions and psychiatric ED visitations.
In this work, we set to examine the volume and characteristics of psychiatric ED visits through a perspective of four COVID-19 lockdowns. We provide a longitudinal analysis of all visitations to the psychiatric ED of Shalvata Mental Healthcare center, Israel, between 2017 and 2021 (N = 15,052). Our analysis focuses on the four lockdowns implemented in Israel to date, and most importantly, the fourth one. This lockdown, termed “soft braking” by the government (N12 News, 2021), was significantly different than the former three as major restrictions were imposed on the population yet a complete lockdown was not strictly imposed. In our analysis, we further pay special attention to the issue of voluntary vs involuntary ED visitations (also known as involuntary or compulsory hospitalizations). In Israel, as in most countries, very strict legislative criteria exist for involuntary psychiatric hospitalizations (see Youngmann et al. (2021) for an up-to-date Israeli overview and Saya et al. (2019) for a worldwide perspective). As such, these involuntary ED visitations are indicative of the most severe and urgent mental conditions in the population who pose a danger to themselves or others (Riecher-Ro¨ssler and Ro¨ssler, 1993).
2. Materials and methods
2.1. Study population
All adult visitations to the psychiatric ED of Shalvata Mental Healthcare center, Israel, between January 1st 2017 and December 31st 2021 (N = 15,052) were retrieved from electronic records of the hospital. Shalvata Mental Healthcare center Shalvata was founded in 1956 in central Israel and currently serves a total population of roughly 600,000 people. It is affiliated with Tel-Aviv University and consists of 4 adult in-patients departments, each encompassing the full range of therapeutic modalities, a Department of Child and Adolescent Psychiatry, a day-care department, and a highly developed network of community-based services. In addition to these, it provides specialized services such as electroconvulsive therapy and a 24-hours ED which serves over 3000 adult visits per year.1
This study was approved by Shalvata mental healthcare center's Helsinki board and patient informed consent was waived (approval code 0015–21-SHA). All methods were carried out in accordance with relevant guidelines and regulations.
2.2. Measures
Each ED visit was characterised by the date, the patient's age and sex, referral indicator (voluntary vs involuntary) and admission status (discharged vs admitted). Daily data was aggregated as follows: for each day, the number of visits and admissions were accumulated along with the patients’ age, sex, admission and referral distributions. Accordingly, the daily male rate (i.e., the number of male visits divided by the total number of visits per day), admission rate (i.e., number of admissions divided by the total number of visits per day), and involuntary rate (i.e., number of involuntary visits divided by the total number of visits per day) were calculated.
The lockdown periods in Israel are defined based on an independent report by the Taub Center for Social Policy Studies in Israel (see Taub Center (2022)). Accordingly, we define the following lockdown periods:
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First lockdown: March 19, 2020 - April 24, 2020
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Second lockdown: September 18, 2020 - October 18, 2020
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Third lockdown: December 27, 2020 - February 6, 2021
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Fourth lockdown (“soft braking”): July 29, 2021 - November 27, 2021
We further cross-referenced our data with the Oxford Government Response Stringency Index (OxGR, for short), a common measure depicting the severity of countermeasures taken by authorities to contain the pandemic (Hale et al., 2021) in order to estimate the COVID-19 related burden on the public. It is important to note that the OxGR cannot truly attest to the level of stress and anxiety in the general public, but as those are both unavailable and highly individual, these measures are often assumed to roughly approximate the magnitude of external stressors that are associated with ED presentation (Segev et al., 2021).
As mentioned before, the fourth Israeli lockdown was significantly different from the previous ones as major restrictions were imposed on the population but a complete lockdown, as in the first three, was not strictly imposed (see Taub Center (2022) for a complete breakdown of the restrictions by date). In addition, we consider the 27th of November 2021 as the unofficial ending of the fourth lockdown as the first case of the Omicron variant was detected on that date in Israel, an event which could have changed the population's behavior (although governmental restrictions did not changed significantly during that time). Since the Omicron variant and its subvariants are still very prevalent in the Israeli population during the writing of this article, as well as worldwide, its investigation is left for future work.
2.3. Statistical approaches
Descriptive statistics are reported in a standard form with continuous variables presented as mean ± standard deviation (SD) and categorical variables are presented as percentages. Time series data is checked for stationarity using an Augmented Dickey-Fuller (ADF) test. Lockdown and between-lockdown periods, as defined in Section 2.2, are compared to the respective control periods between 2017 and 2019 using comparative χ2 tests for proportion data (e.g., sex) and Mann–Whitney U tests for continuous measures (e.g., age). p values are reported along with the relevant statistic in parentheses. We further preform a regressionbased analysis using Poisson regressions for count data (i.e., daily number of visitations and admissions) and Logistic regression for dichotomous data (e.g. individuals’ admission and referral status).
3. Results
Fig. 1 presents the (7-day smoothed) daily number of visits and admissions over time along with the (raw) OxGR index. Focusing on the time frame between 2017 and 2019 (i.e., the last 3 years prior to Covid19), we find that the daily number of visitations, admissions, admission rate, male rate and involuntary rate are all statistically stationary at p < 0.01. In other words, all measures examined in this study present no significant trends or seasonality in the 3 years prior to the COVID-19 outbreak, thus these should not be accounted for in the following analysis.
Fig. 1.
Primary Y-Axis: Daily visitations (top, in blue) and admissions (middle, in orange). Both are smoothed using a moving average over 7 days. Secondary Y-Axis: raw OxGR Stringy Index (bottom, in gray). Time periods between dotted horizontal lines (black, green, red and magenta) indicate the lockdown periods as defined in Section 2.2. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
We begin by comparing each lockdown period to the averaged corresponding pre-pandemic periods between 2017 and 2019 as shown in Table 1 . As was documented in earlier literature, in our data, the first lockdown resulted in a statistically significant reduction in the number of visits (265 vs 308.3) and admissions (110 vs 135.7) compared to the control periods. In addition, visiting patients during that lockdown period were significantly younger, compared to the control periods, by an average of 2.9 years (36.6 vs 39.5 years). Both differences are significant at p < 0.05. No significant differences were recorded for the patients’ admission rate and sex distribution, yet a notable increase in the involuntary rate was observed (9.1% vs 6.7%). When considering the second and third lockdowns, different phenomena arise. First, unlike the first lockdown, the second and third lockdowns demonstrated only very negligible differences in the number of visits during the lockdown periods compared to the control periods (second lockdown: 256 vs 255; third lockdown: 342 vs 332). Nevertheless, during these periods, a significant increase in the number of admissions (second lockdown: 117 vs 98.3; third lockdown: 165 vs 128), the admission rate (second lockdown: 45.7% vs 38.5%; third lockdown: 48.2% vs 38.5%) and the involuntary rate (second lockdown: 13.3% vs 4.5%; third lockdown: 10.6% vs 6%) were recorded, all significant at p < 0.05. No significant differences were recorded for patients’ age and sex distribution. When considering the fourth lockdown, we encounter a significant increase in the number of visitations (1079 vs 979), admissions (435 vs 391.5) and in the involuntary rate (10.1% vs 7%) as compared to the control periods; while the admission rate remained roughly the same as it was in the control period, the former three are significant at p < 0.05. As before, no significant differences were recorded for the patients’ age and sex distribution.
Table 1.
Lockdown periods compared to the averaged pre-pandemic control periods between 2017 and 2019. Results in bold are significant at p < 0.05.
| 1st Lockdown (19/3–24/4) | 2nd Lockdown (18/9–18/10) | 3rd Lockdown (27/12–6/2) | 4th Lockdown (29/7–27/11) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
|
| Visits | 265 | 308.3 | 256 | 255 | 342 | 332 | 1079 | 979 | ||||
| Daily visits | 7.1 ± 3.2 | 8.3 ± 3.6 |
0.03 (1650) |
8.2 ± 3.1 | 8.2 ± 3.3 | 0.49 (1439) |
8.1 ± 3.1 | 7.9 ± 3.3 | 0.43 (2602) |
8.8 ± 3.2 | 8.1 ± 3.2 |
0.01 (25,493) |
| Admissions | 110 | 135.7 | 117 | 98.3 | 165 | 128 | 435 | 391.5 | ||||
| Daily Admis. | 2.9 ± 2.2 | 3.7 ± 2.2 |
0.03 (1643) |
3.8 ± 2.2 | 3.2 ± 1.6 |
0.05 (1151) |
3.9 ± 2.5 | 3.1 ± 1.9 |
0.02 (2079) |
3.6 ± 2.1 | 3.2 ± 1.8 |
0.05 (26,653) |
| Admis. Rate | 41.5% | 44% | 0.52 (0.42) |
45.7% | 38.5% |
0.05 (3.8) |
48.2% | 38.5% |
<0.01 (9.5) |
40.3% | 40% | 0.85 (0.0) |
| Age | 36.6 ± 6.5 | 39.5 ± 6 |
0.01 (1543) |
40.3 ± 7.1 | 40.9 ± 6.2 | 0.34 (1368) |
38.6 ± 6.8 | 39.2 ± 8.1 | 0.34 (2534) |
40.8 ± 6.3 | 40.5 ± 7.1 | 0.28 (28,708) |
| Male | 46% | 41.6% | 0.71 (0.1) |
47.7% | 46.7% | 0.96 (0.0) |
48.8% | 43.6% | 0.15 (2.1) |
47.5% | 45.1% | 0.07 (3.2) |
| Involuntary | 9.1% | 6.7% | 0.19 (1.7) |
13.3% | 4.5% |
<0.01 (20.2) |
10.6% | 6% |
<0.01 (16.3) |
10.1% | 7% |
<0.01 (12.2) |
We now turn to consider the periods between the lockdowns. As before, we compare each period to the averaged corresponding pre-pandemic periods between 2017 and 2019 as shown in Table 2 . Starting with the period between the first and second lockdowns, we see that the number of visits and admissions, as well as the patients’ admission rate and sex distribution, has not changed significantly compared to the control periods. However, as was the case for the first lockdown, visiting patients were significantly younger by an average of 2 years (38.8 vs 40.8 years), at p < 0.01. Turing to the period between the second and third lockdowns, we find no significant differences in any of the examined measurements other than the involuntary rate, which increased significantly (10.1% vs 7.8%) at p < 0.01. The period between the third and fourth lockdowns have demonstrated a significant increase in the number of admissions (645 vs 585.5), in the admission rate (44% vs 40.3%) and in the involuntary rate (12.5% vs 4.5%), all significant at p < 0.01. No significant differences were observed in terms of the number of visits and patients’ age and sex distribution.
Table 2.
Between-lockdown periods compared to the averaged pre-Covid19 control periods between 2017 and 2019. Results in bold are significant at p < 0.05.
| Between 1st-2nd Lockdowns (25/4–17/9) |
Between 2nd-3rd Lockdowns (19/10- 26/12) | Between 3rd-4th Lockdowns (6/2–28/7) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
|
| Visits | 1263 | 1221.3 | 570 | 537.3 | 1467 | 1451.8 | |||
| Daily visits | 8.5 ± 3.4 | 8.3 ± 3.5 | 0.14 (30,774) |
8 ± 3.3 | 7.6 ± 3 | 0.09 (6766) |
8.4 ± 3.2 | 8.3 ± 3.5 | 0.33 (59,230) |
| Admissions | 514 | 473.7 | 251 | 233 | 645 | 585.5 | |||
| Daily Admis. | 3.5 ± 2 | 3.2 ± 1.9 | 0.07 (30,131) |
3.6 ± 1.9 | 3.4 ± 1.9 | 0.32 (7278) |
3.7 ± 1.8 | 3.3 ± 2 | <0.01 (52,391) |
| Admis. Rate | 40.7% | 38.7% | 0.24 (1.4) |
44% | 43.3% | 0.11 (2.4) |
44% | 40.3% |
0.01 (6.3) |
| Age | 38.8 ± 6.3 | 40.8 ± 7 | <0.01 (27,271) | 41±6.7 | 39.7 ± 6.8 | 0.06 (6597) |
40.1 ± 6.1 | 40±6.6 | 0.37 (59,583) |
| Male | 43.6% | 45.6% | 0.49 (0.5) |
44% | 45.8% | 0.45 (0.6) |
48.5% | 44.9% | 0.16 (1.9) |
| Involuntary | 8.4% | 5.7% |
<0.01 (12.7) |
10.1% | 7.8% |
<0.01 (10.2) |
12.2% | 4.5% |
<0.01 (52.9) |
In Table 3 we summarize all of the above results across both lockdowns and between lockdown periods. We report the relative change observed in each of these periods compared to the averaged control periods while focusing on the four key measures which have resulted in most of the significant differences in Tables 1 and 2: number of visits, number of admissions, admission rate and involuntary rate. The summarized results indicate that the significant decrease in the number of visits and admissions (−14% and −18.9%, respectively), which was recorded during the first lockdown was quickly overturned with both measures returning to (and even surpassing) their pre-pandemic levels in the period between the first and second lockdowns (+3.4% and +8.5%, respectively). In addition, the elevated admission rate and involuntary rate during the first lockdown (+2.5% and +2.4%, respectively) seems to continue to the period between the first and second lockdowns, with the latter becoming statistically significant (+1.9% and +2.7%, respectively). Similarly, during the second lockdown period, a significant increase in the number of admissions (+19%), in the admission rate (+7.1%) and in the involuntary rate (+8.8%) were recorded while the number of visits remained roughly the same (+0.4%). During the period between the second and third lockdowns we still encounter elevated levels in the number of visits, admissions and in the admission rate measures (+6.1%, +7.7% and +0.7%, respectively), yet the differences are not statistically significant. Nevertheless, the elevated level of the involuntary rate (+2.3%) is, indeed, significant. The third lockdown shows a very sharp and significant increase in the number of admissions (+28.9%), which was accompanied by a non-significant increase in the number of visits (+3%), resulting in a significant increase in the admission rate (+9.7%). During the same period, a significant increase in the involuntary rate is also observed (+4.6%). Similar results are observed during the period between the third and fourth lockdowns where a significant increase in the number of admissions (+10.2%), the admission rate (+3.6%) and involuntary rate (+7.7%) were observed alongside a non-significant increase in the number of visits (+1.1%). Finally, the fourth lockdown presents a significant increase in the number of visits (+10.4%), admissions (+11.1%) and involuntary rate (+3.1%), which resulted in a non-significant yet slightly elevated admission rate (+0.3%).
Table 3.
Relative changes during each examined lockdown (LD) and between-lockdown periods with respect to the control periods between 2017 and 2019. Results in bold are significant at p < 0.05.
| LD1 | Between 1–2 LDs |
LD2 | Between 2–3 LDs |
LD3 | Between 3–4 LDs |
LD4 | |
|---|---|---|---|---|---|---|---|
| Visitations | −14% | +3.4% | +0.4% | +6.1% | +3% | +1.1% | +10.2% |
| Admissions | −18.9% | +8.5% | +19% | +7.7% | +28.9% | +10.2% | +11.1% |
| Admission Rate | +2.5% | +1.9% | +7.1% | +0.7% | +9.7% | +3.6% | +0.3% |
| Involuntary Rate | +2.4% | +2.7% | +8.8% | +2.3% | +4.6% | +7.7% | +3.1% |
Given the consistently elevated involuntary rate across all examined periods, we repeated the above analysis by considering the voluntary and involuntary visits separately.
Starting with the voluntary ED visits, which constituted about 84.5% of the visits during the pre-pandemic 2017–2019 period, we observe slightly different patterns compared to the analysis presented above. Starting with Table 4 , as was the case before, we see that during the first lockdown period a significant decrease in the number of visits (240 vs 287.3) and admissions (85 vs 114.7) was recorded. Similarly, visiting patients during the first lockdown were significantly younger by an average of 3.4 years (36.1 vs 39.5 years). Interestingly, during the second, third and fourth lockdowns, no significant differences were encountered other than a single one which was not observed before – during the third lockdown, the rate of male patients was significantly higher (50.6% vs 44.4%). Similarly, when considering the periods between lockdowns (Table 5 ), only two results are significant – during the period between the first and second lockdowns, visiting patients were younger by an average of 2 years (38.9 vs 40.9 years), and during the period between the third and fourth lockdowns the rate of male patient visits was significantly higher (50.6% vs 46.2%).
Table 4.
Voluntary patient data during lockdown periods compared to the pre-Covid19 control periods between 2017 and 2019.
| 1st Lockdown (19/3–24/4) |
2nd Lockdown (18/9–18/10) |
3rd Lockdown (27/12–6/2) |
4th Lockdown (29/7–27/11) |
|||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
|
| Visits | 240 | 287.3 | 224 | 244 | 296 | 311 | 969 | 911.5 | ||||
| Daily visits | 7.5 ± 3.1 | 7.8 ± 3.6 |
0.02 (1589) |
7.2 ± 3 | 7.9 ± 3.1 | 0.21 (1257) |
7.1 ± 2.3 | 7.4 ± 3.1 | 0.21 (2425) |
7.9 ± 3 | 7.5 ± 3.2 | 0.06 (27,117) |
| Admissions | 85 | 114.7 | 85 | 87.3 | 119 | 107.3 | 325 | 324 | ||||
| Daily Admis. | 2.3 ± 2.2 | 3.1 ± 2.1 |
0.01 (1537) |
2.7 ± 2.1 | 2.8 ± 1.5 | 0.34 (1369) |
2.8 ± 1.5 | 2.6 ± 1.8 | 0.07 (2263) |
2.7 ± 1.8 | 2.7 ± 1.7 | 0.43 (29,406) |
| Admis. Rate | 35.4% | 39.9% | 0.24 (1.4) |
37.9% | 35.4% | 0.65 (0.2) |
40% | 34.5% | 0.09 (2.9) |
33.5% | 35.5% | 0.29 (1.3) |
| Age | 36.1 ± 7.1 | 39.5 ± 6.4 |
0.01 (1553) |
40±7.3 | 41±6.4 | 0.2 (1294) |
38.8 ± 7.5 | 39.1 ± 8.3 | 0.34 (2535) |
40.9 ± 7 | 40.6 ± 7.4 | 0.31 (28,825) |
| Male | 47.1% | 42.4% | 0.66 (0.2) |
50.5% | 47.6% | 0.71 (0.1) |
50.6% | 44.4% |
0.05 (3.9) |
48.8% | 46.6% | 0.14 (2.2) |
Table 5.
Voluntary patient data between lockdown periods compared to the pre-Covid19 control periods between 2017 and 2019.
| Between 1st-2nd Lockdowns (25/4–17/9) |
Between 2nd-3rd Lockdowns (19/10- 26/12) | Between 3rd-4th Lockdowns (6/2–28/7) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
|
| Visits | 1155 | 1152.3 | 507 | 496 | 1288 | 1357.3 | |||
| Daily visits | 7.8 ± 3.2 | 7.8 ± 3.4 | 0.35 (32,034) |
7.5 ± 2.6 | 7.4 ± 3.2 | 0.52 (8263) |
7.4 ± 3 | 7.9 ± 3.3 | 0.1 (56,869) |
| Admissions | 406 | 405 | 188 | 192.3 | 467 | 491 | |||
| Daily Admis. | 2.7 ± 1.6 | 2.7 ± 1.7 | 0.42 (32,349) |
2.5 ± 1.5 | 2.7 ± 1.8 | 0.3 (7224) |
2.7 ± 1.6 | 2.8 ± 1.9 | 0.27 (58,799) |
| Admis. Rate | 35.1% | 35.1% | 0.97 (0.0) |
37.1% | 38.8% | 0.69 (0.2) |
36.3% | 36.2% | 0.99 (0.0) |
| Age | 38.9 ± 6.8 | 40.9 ± 7.2 | <0.01 (27,379) | 41.2 ± 7.1 | 39.9 ± 7.2 | 0.06 (6592) |
40.4 ± 6.9 | 40.1 ± 6.9 | 0.31 (59,049) |
| Male | 45.3% | 47% | 0.87 (0.0) |
46.2% | 47.9% | 0.47 (0.5) |
50.6% | 46.2% |
0.05 (4.0) |
Turning to involuntary ED visits, in Tables 6 and 7 , we provide the same analysis as performed above. Unlike the voluntary visits, during the first lockdown, an increase in the volume of visits and admissions was observed, albeit non-significant compared to the control period. However, that is not the case for the second, third and fourth lockdowns and all periods between the lockdowns. During all of these periods, without exception, we witness a sharp and significant increase in the number of visits and admissions with no significant changes in age, sex distribution, admission rate and involuntary rate. It is important to note that the admission rate of involuntary visits was extremely high even before the COVID19 outbreak (admission rate of more than 99% between 2017 and 2019) and therefore, no significant changes were expected for that measurement.
Table 6.
Involuntary patient data during lockdown periods compared to the averaged pre-pandemic control periods between 2017 and 2019. Results in bold are significant at p < 0.05.
| 1st Lockdown (19/3–24/4) |
2nd Lockdown (18/9–18/10) |
3rd Lockdown (27/12–6/2) |
4th Lockdown (29/7–27/11) |
|||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
|
| Visits | 25 | 21 | 32 | 11 | 46 | 21 | 110 | 68 | ||||
| Daily visits | 0.7 ± 0.4 | 0.6 ± 0.4 | 0.3 (312) |
1 ± 0.4 | 0.7 ± 0.5 | 0.02 (185) | 1.1 ± 0.7 | 0.5 ± 0.5 | 0.04 (355) | 0.9 ± 0.8 | 0.6 ± 0.6 |
0.05 (5258) |
| Admissions | 25 | 21 | 32 | 11 | 46 | 20.7 | 110 | 67.5 | ||||
| Daily admis. | 0.7 ± 0.4 | 0.6 ± 0.4 | 0.3 (312) |
1 ± 0.4 | 0.7 ± 0.5 | 0.02 (185) | 1.1 ± 0.7 | 0.5 ± 0.5 | 0.04 (343) | 0.9 ± 0.8 | 0.6 ± 0.6 |
0.05 (5207) |
| Admis. Rate | 100% | 100% | 1 (-) |
100% | 100% | 1 (-) |
100% | 95% | 0.87 (0.0) |
100% | 99% | 0.9 (0.0) |
| Age | 39.8 ± 15.7 | 38.1 ± 11.1 | 0.45 (332) |
42±16.2 | 41.6 ± 14.6 | 0.49 (259) |
36.9 ± 10.1 | 38.5 ± 12 | 0.34 (433) |
41.7 ± 13.1 | 40.1 ± 14.1 | 0.15 (5939) |
| Male | 33.3% | 32.1% | 0.93 (0.0) |
36.6% | 30.8% | 0.85 (0.0) |
31.8% | 26.4% | 0.85 (0.0) |
35.5% | 26.4% | 0.21 (1.6) |
Table 7.
Involuntary patient data between lockdown periods compared to the averaged pre-pandemic control periods between 2017 and 2019. Results in bold are significant at p < 0.05.
| Between 1st-2nd Lockdowns (25/4–17/9) | Between 2nd-3rd Lockdowns (19/10- 26/12) | Between 3rd-4th Lockdowns (6/2–28/7) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
Covid19 | Control | p (stat.) |
|
| Visits | 108 | 69 | 63 | 41.3 | 179 | 94.5 | |||
| Daily visits | 1.6 ± 0.7 | 1.4 ± 0.6 |
0.05 (3665) |
1.7 ± 0.8 | 1.4 ± 0.7 |
0.05 (1376) |
1.7 ± 0.8 | 1.4 ± 0.6 | <0.01 (11,915) |
| Admissions | 108 | 68.7 | 63 | 40.7 | 178 | 94 | |||
| Daily admis. | 1.6 ± 0.7 | 1.4 ± 0.6 |
0.05 (3645) |
1.7 ± 0.8 | 1.4 ± 0.7 |
0.05 (1351) |
1.7 ± 0.8 | 1.4 ± 0.6 | <0.01 (11,861) |
| Admis. Rate | 100% | 100% | 1 (-) |
100% | 100% | 1 (-) |
100% | 100% | 1 (-) |
| Age | 38.8 ± 11.7 | 39.1 ± 13.6 | 0.42 (4918) |
39±14.6 | 38.7 ± 12.7 | 0.42 (1594) |
39.8 ± 11.6 | 38.8 ± 12.8 | 0.16 (12,931) |
| Male | 22.1% | 22.7% | 0.74 (0.1) |
27.2% | 21.4% | 0.28 (1.1) |
34.4% | 27.7% | 0.17 (1.8) |
Table 8 summarizes the above results across lockdowns and between lockdown periods, again, in relative terms to the averaged control periods. The results indicate that the significant decrease in the number of voluntary visits and admissions during the first lockdown (−16.5% and −25.9%, respectively) was accompanied by a non-significant yet non-negligible increase in the number of involuntary visits and admissions (+19%). From the conclusion of the first lockdown, a very consistent pattern has been observed in which the number of involuntary visits has risen significantly and remains significantly higher compared to the control periods (ranging between +54.4% to +190.9%), whereas the voluntary visits present similar measures to those observed in the control periods. The increase in involuntary visits and admissions culminated during the second lockdown (+190.9% in both visits and admissions) and during the third lockdown (+119% in visits and +122.6% in admissions), which is accompanied by a non-significant decrease in the number of voluntary visits during the same lockdown periods (−8.2% and −4.8%, respectively). As such, any decrease in the number of voluntary visits should be carefully interpreted as it could imply that some potentially voluntary visits have resulted in involuntary visits. We discuss this point further in Section 4.
Table 8.
Relative changes in voluntary and involuntary visits during each examined lockdown (LD) and between lockdown periods with respect to the control periods between 2017 and 2019. Results in bold are significant at p < 0.05.
| LD1 | Between 1–2 | LD2 | Between 2–3 | LD3 | Between 3–4 | LD4 | ||
|---|---|---|---|---|---|---|---|---|
| Voluntary | Visitations Admissions |
−16.5% −25.9% |
+0.3% +0.2% |
−8.2% −2.7% |
−2.2% −7.6% |
−4.8% +10.9% | −5.1% −5% |
+6.3% +0.3% |
| Admission Rate | −4.4% | 0% | +2.2% | +1.1% | +5.7% | 0% | −2% | |
| Involuntary | Visitations Admissions | +19% +19% |
+56.5% +57.3% |
+190.9% +190.9% |
+52.4% +54.9% |
+119% +122.6% |
+89.4% +89.4% |
+61.8% +63% |
| Admission Rate | 0% | +0.5% | 0% | +1.6% | +1.6% | 0% | +0.7% |
In order to get a more nuanced understanding of the temporal association between governmental COVID-19 restrictions and the examined ED measures, we further perform a regression-based analysis with two independent variables: the OxGR stringy index and the time elapsed since the start of the pandemic in Israel (days elapsed since the first occurrence of COVID-19 in Israel, time for short). As dependent variables we consider the four main metrics which were found to be most significant in the analysis above: daily number of visits, daily number of admissions, admission rate and involuntary rate. For each dependent variable a separate Log-Linear regression model was fitted.
Table 9 summarizes the results of the four fitted models. The results indicate that the level of governmental restrictions, as captured by the OxGR index, is significantly associated with all four measures when time is controlled. Specifically, OxGR is negatively associated with the daily number of visits (a change in OxGR from 0 to 100 is associated with 11.4% less visits), and positively associated with the daily number of admissions (the same change in OxGR is associated with 4.1% more admissions), the admission rate (the same change is associated with an increase by a factor of 1.139) and the involuntary rate (the same change is associated with an increase by a factor of 1.874). The results further indicate that time is significantly associated with three of the four measures. Specifically, it is positively associated with the daily number of visits and admissions (every 100 days that pass since the first occurrence of COVID-19 in Israel are associated with about 1% more visits and admissions) and with the involuntary rate (the same change is associated with an increase by a factor of 1.062). The association between time and the admission rate is not statistically significant, yet all other examined associations are statistically significant at p < 0.05.
Table 9.
Log-linear regression results with the dependent variables presented in rows and the independent variables presented in columns. Each coefficient represents the expected multiplicative change in the dependent variable given that the independent variable is increased by 1 unit (i.e., 1 point in the OxGR index or 1 day past the first occurrence of COVID-19 in Israel). Results in bold are significant at p < 0.05.
| OxGR | time | |||
|---|---|---|---|---|
| coefficient [95% CI] | p | coefficient [95% CI] | p | |
| Visitations | 0.9988[0.998,0.9996] | 0.04 | 1.0001[1.0000,1.0001] | 0.02 |
| Admissions | 1.0004[1.0001,1.0003] | 0.04 | 1.0001[1.0000,1.0001] | 0.02 |
| Admission Rate | 1.0013[1.0001,1.0025] | 0.05 | 1.0000[1.0000,1.0000] | 0.77 |
| Involuntary Rate | 1.0063 [1.004,1.009] | <0.01 | 1.0006 [1.0001,1.0011] | <0.01 |
4. Discussion
Prior work has extensively documented the collateral effects of COVID-19 on the public's mental health both within and outside the scope of psychiatric ED visitations (see Robinson et al. (2022) for a recent systematic review and meta-analysis). Focusing on the former, these works have primarily considered the effects of strict lockdowns on the volume and characteristics of psychiatric ED visits. To the best of our knowledge, this study is the first to examine the possible association between both strict lockdowns as well as other, milder, restrictions on psychiatric ED visits over time.
Our results suggest that, while no trend or seasonality existed in the pre-pandemic volume and characteristics of ED visitations, COVID-19 has brought about major changes on both accounts, especially when considering the most acute and urgent psychiatric conditions – i.e., involuntary ED visits, as shown in Table 8.
Starting with the first lockdown, our results are very much aligned with prior work, demonstrating an overall decline in the volume of visits and admissions. This decline is likely due to a confluence of factors, led by the fear of contracting COVID-19, as documented by public pools in Israel (Bitan et al., 2020) and abroad (American College of Emergency Physicians, 2020). Interestingly, this reduction in the volume of ED visits should be attributed solely to voluntary ED visits, whereas the number of involuntary ED visits has not presented any decline and, in fact, increased compared to the control periods, aligning once more with prior literature (Ambrosetti et al., 2021a). From the conclusion of the first lockdown, we see no significant differences in the volume and characteristics of voluntary ED visits, other than a few minor differences in patient age (the first lockdown and the first between-lockdowns period) and sex distribution (last between-lockdowns period). In sharp contrast, since the conclusion of the first lockdown, the volume of involuntary ED visits and admissions has dramatically increased, with the most striking changes observed during the second and third lockdowns. That is not the case for the fourth lockdown, which presented an increase in volume of involuntary ED visits that is similar to that experienced in the between-lockdown periods. Taken jointly, the results seem to suggest that mild restrictions may result in a reduced strain on psychiatric emergency services compared to strict lockdowns, especially considering the most acute and urgent psychiatric conditions and symptoms which require involuntary ED visitations. We find further support for this outcome through a regression analysis, indicating a significant increase in the volume of ED visits, admissions, admission rate and involuntary rate as a result of an increase in restriction levels and the time elapsed since the beginning of the pandemic in Israel. Specifically, as time elapses since the first occurrence of COVID-19 in Israel, the results suggest a significantly higher volume of ED visits, admissions and involuntary visits. While controlling for these temporal changes, we further find a significant positive associated between the level of governmental restrictions (as captured by the OxGR stingy index) and the volume of ED visits and admissions, and the admission and involuntary rates.
The surge in involuntary ED visits and admissions can be explained in a number of complementary ways. First, it is reasonable to assume that at least some patients requiring consented hospitalization were reluctant to visit the ED voluntarily or to adhere to medical advice due to fear of contagion in hospital settings, governmental restrictions and other pandemic-related concerns. Similarly, community-based, outpatient and ambulatory mental health services, which normally should be appropriate for a large portion of patients admitted to adult psychiatric EDs (Costanza et al., 2020), were, in-part, limited and overwhelmed with requests for help (World Health Organization, 2020). As such, some may not have had sufficient access to much needed timely mental health services, resulting in mental deterioration. For example, the Israeli Association for Emotional First Aid has reported that emergency calls more than tripled during the first months of the pandemic (Kleinerman et al., 2022). Indeed, the World Health Organization (WHO) has reported that certain acute psychiatric conditions are more likely to be triggered or significantly exacerbated as a result of the severe psychological reactions to the pandemic and to the measures taken to contain it (World Health Organization, 2022). These conditions, including suicidal thoughts, attempts and self-harming behaviors (Dub´e et al., 2021), first-onset psychosis (Segev et al., 2021) and major affective disorders (Santomauro et al., 2021), to name a few, are likely to result in involuntary ED visits if not appropriately managed. Additionally, there is growing evidence suggesting that individuals are at significantly increased risk of various severe psychiatric sequelae after a COVID-19 diagnosis (Taquet et al., 2021; Coleman et al., 2022). With the increased prevalence of COVID-19 in the general population (Israeli Ministry of Health, 2022), severe mental conditions may also be triggered following COVID-19 contagion.
4.1. A wider Israeli perspective
Existing knowledge on COVID-19 effects on psychiatric ED visitations in Israel is very limited. The most closely related work to ours is Pikkel Igal et al. (2021) and Dvorak et al. (2021), who examined the effects of the first Israeli lockdown on mental health-related ED visits to a general hospital (the former study was conducted at Rambam Health Care Campus and the latter at Sourasky Medical Center). Similarly, Schreiber et al. (2021) have examined the number of psychiatric consultations on a monthly basis during 2020 for the Sourasky Medical Center. In this respect, our work extends the existing knowledge in three major aspects: First, as prior work has relied on data from two general hospitals, it need not necessarily align with that of a designated mental healthcare center. Specifically, as fear of contagion is likely to play a major role in an individual's decision to visit an ED or not, it is possible that approaching a general hospital's ED would be perceived as more risky since individuals with respiratory symptoms or complaints are expected to approach that ED as well. Consequently, our results are roughly aligned with those observed in prior work, at least for the first lockdown. Second, as this work examines the four lockdowns implemented in Israel thus far, we provide a longitudinal, more up-to-date, perspective on the matter in question. Lastly, as both strict lockdowns and other restrictions are considered in this study, we provide a much needed investigation as to the potential association between governmental restriction levels and the volume and characteristics of ED visits.
Focusing on the issue of involuntary ED visitations in Israel, the rate and volume of involuntary ED visitations has varied significantly over the past decades. In the 90′s, a significant upward trend was recorded (Bauer et al., 2007). However, since the 2000′s, a non-consistent pattern has been observed, with the most recent pre-pandemic data presenting an opposite declining trend since 2015 (Youngmann et al., 2021). Against this background, the outstanding increase in involuntary ED visitations and admission observed and analysed in this work is especially remarkable.
4.2. Strengths and limitations
This work has several strengths. Most importantly, it provides a rigorous and detailed analysis of psychiatric visitations and admissions trends over a course of four lockdowns with different degrees of restriction as well as between lockdown periods. It further relies on extensive pre-COVID-19 data as control and provides a large sample size. However, it also has some important limitations which offer additional fruitful avenues of future research. First, our sample is taken from a single mental healthcare center. Official data from the Israeli Ministry of Health (Israeli Ministry of Health, 2019) shows that Shalvata is roughly representative of the Israeli mental healthcare system in almost every examined measure (e.g., patient characteristics, hospitalization outcome, etc.) for at least the last decade. As such, we plan to extend our investigation outside of Israel in the future. Second, we plan to examine the specific diagnostic categories for both voluntary and involuntary ED visits (e.g., substance use, mood disorders, psychosis). Such an investigation, which presumably requires different levels of “grouping” by different diagnosis codes, dealing with multiple diagnoses and special attention to the issue of first on-set vs. relapse, could help reveal which psychiatric conditions are more likely to be triggered, an issue outside the scope of this work. Lastly, while our results do show major changes in the volume and characteristics of ED visits, they need not necessarily indicate that other major changes have occurred during the hospitalization period (e.g., hospitalization duration, treatment plans, violent incidences, mechanical restraint and insulation). We plan to address this issue in future work.
5. Conclusions
In this work, a staggering increase in the volume of involuntary ED visits and admissions is recorded following the conclusion of the first Israeli lockdown, peaking during strict lockdown periods. In parallel, a rather stable volume of voluntary ED visits is documented with no major changes in their characteristics. In addition, a temporal increase in the total number of ED visitations, regardless of governmental restrictions, is identified. Consequently, it is unreasonable to expect the volume of ED visits, especially of involuntary ED visits, to return to its pre-pandemic levels in the near future. On the contrary, with the prospect of reimposed restrictions in the future given new variants of COVID-19 or other extreme eventualities, the strain on psychiatric emergency services may substantially increase.
Above all, our results highlight some of the severe mental health consequences associated with the pandemic over time and, most importantly, with the measures taken to control it. Specifically, optimistic projections suggesting that the general population will “soon learn to live side-by-side with the pandemic” has proven false thus far, at least when considering the acute and urgent mental conditions in the population which have reached unprecedented levels. In order to partially mitigate this phenomena, alternatives to strict restrictions should be favored when possible and mental health services should be strengthened.
CRediT authorship contribution statement
Amit Yaniv-Rosenfeld: Conceptualization, Data curation, Methodology, Software, Validation, Investigation, Formal analysis, Resources, Project administration, Writing – original draft, Writing – review & editing. Ariel Rosenfeld: Conceptualization, Software, Formal analysis, Visualization, Writing – review & editing. Efrat Hirsch Klein: Conceptualization, Methodology, Investigation, Supervision, Project administration, Writing – review & editing.
Footnotes
More information can be found on the hospital's official website at https://hospitals.clalit.co.il/shalvata/
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