key: cord-0737564-3n5hy106 authors: Jagadheesan, Karuppiah; Danivas, Vijay; Itrat, Annie; Sekharan, Lokesh; Lakra, Assoc. Prof Vinay title: COVID-19 and psychiatric admissions: An observational study of the first six months of lockdown in Melbourne date: 2021-03-23 journal: Psychiatry Res DOI: 10.1016/j.psychres.2021.113902 sha: 61b8ec62d4b6bd8d56215cde12ca541c84ec5e87 doc_id: 737564 cord_uid: 3n5hy106 Research on the effect of a prolonged lockdown on inpatient admissions is limited. In this background, this study was planned, and it included patients admitted to inpatient units of a large mental health network in Melbourne during the lockdown (March 16–September 16, 2020) and a similar time period in 2019. The results showed a 12% decrease in admissions. The lockdown period included patients with lower mean age and more patients with never married status, higher education status, students and patients with home duties, and certain psychiatric diagnoses. Overall, the patients needing inpatient treatment during a prolonged lockdown are different. The COVID-19 pandemic and lockdown have negative effects on the population and mental health services (Fisher et Health (NWMH) network of Melbourne Health. The NWMH provides psychiatric services to more than 1.2 million residents in the north and west of the metropolitan Melbourne. In NWMH, the inpatient units are expected to have a minimum two discharges per day, which is a key performance index (KPI), to maintain bed availability to meet demands. Following the initiation of lockdown in Melbourne, the community teams within the service have changed their model of care by reducing direct contact hours, use of telepsychiatry, reduced home visits and allowing some staff to work from home. We collected socio-demographic and clinical variables, as in table 1, from the hospital databases. All diagnoses were based on ICD-10 AM. Data were de-identified and secured to meet privacy and confidentiality requirements. The Melbourne Health Human Research Ethics Committee approved this study. Descriptive statistics and inferential statistics (Chi-Square test and independent t test) with alpha (significance) level < 0.05 were carried out through SPSS Ver. 27.0. Total sample was 3660 (n = 1843, for the control group; n = 1817, for the lockdown group). After exclusion of patients with no clear diagnosis (2019, n = 356; 2020, n = 510), the final sample included 1487 and 1307 patients with a clear psychiatric diagnosis in the control and lockdown periods, respectively (i.e., a 12.1% reduction). The mean age of the patients admitted during the lockdown was significantly less (37.92 + 11.90 vs 39.54 +11.66, p<0.001). Compared to the control period, the lockdown period included more patients with never married status (p = 0.03), education status higher than years 7-10 (p = 0.019), and studying or home duties (p = 0.044). On clinical variables, the lockdown period included higher rate of psychotic disorders, mood disorders, and personality disorders (p<0.001). Groups were not different in other variables (table 1) . This is the first study to investigate the effect of prolonged lockdown on psychiatric admissions. Within the sample of inpatients with a confirmed psychiatric diagnosis, we found a 12% reduction in the total number of inpatients during the lockdown period, which is lower We found patients who are somewhat younger, not in relationship, better educated and not working due to studies or home duties appeared to need inpatient treatment in the lockdown period. These findings disagree our previous study (Itrat et al. 2020) in which there was no group difference in age and also, more patients had a separated status. Unlike Clerici et al. (2020), we did not notice any reduction or increase in voluntary admissions in our current study, a finding similar to our previous study (Itrat et al., 2020) . It is possible that the effects of hospital setting and longer duration of the lockdown might have contributed to these differences. We noted patients with certain diagnoses such as psychotic disorders, mood disorders, and personality disorders at higher rates during the lockdown. Similarly, increased admissions for patients with personality disorders could be related to their poor tolerance to stress associated with prolonged lockdown (Preti et al., 2020) . The clinical implications of our study are as follows. Firstly, monitoring the rate of inpatient admissions will help adjust intake parameters to meet the needs of local communities as the pandemic and lockdown periods are known risk factors for psychological issues at population level. Secondly, understanding why certain groups of patients are not receiving inpatient treatments can help develop strategies to reach out to these groups of patients, e.g., early identification and treatment through newer approaches such as telehealth. This will help to improve both the mental health and quality of life of the local communities. Our study has limitations of a retrospective database study such as classification bias and missing information. There are strengths to our study, e.g., investigating long duration of lockdown, modest sample size and inclusion of multiple inpatient units. While our findings need replication in a larger prospective study, we conclude that the prolonged lockdown measures can adversely affect help seeking patterns of vulnerable subgroups of population. The Early Impact of the COVID-19 Pandemic on Acute Care Mental Health Services Psychiatric hospitalization rates in Italy before and during COVID-19: did they change? An analysis of register data Mental health of people in Australia in the first month of COVID-19 restrictions: a national survey COVID-19 distresses the depressed while schizophrenic patients are unimpressed: A study on psychiatric inpatients A comparative study of access to inpatient psychiatric treatment in a public mental health service in Melbourne during COVID-19 The COVID-19 global pandemic: implications for people with schizophrenia and related disorders Personality disorders in time of pandemic Patterns of use of secondary mental health services before and during COVID Acknowledgement: The authors thank Sanjit Tisseverasinghe for data extraction. Conflict of interest: None to be declared. Financial disclosure: None to be declared. All authors have equally contributed to the conceptualisation, literature search, methodology, data analysis and interpretation, and writing and revising the manuscript. The authors have no conflict of interest attached to this submission.