My Research Proposal on the Effect of COVID19 Public Health Measures on Admission Rates for.....

A potential Research Proposal idea to investigate the Effect of COVID-19 Public Health Measures on Admission Rate of Adults Treated for Paranoid Schizophrenia. As EPIC is not an entire AHS system wide EMR as of this date, this proposal is scripted for future reference and potential use at a later date.

Abstract

There are many challenges associated with the socialization of adult individuals treated for paranoid schizophrenia. To combat the effects of the COVID-19 pandemic, provincial governments instituted various public health measures including stay-at-home orders. The goal of these stay-at-home measures was to decrease face-to-face human interaction to curb the spread of this virus. However, based on the recommended requirement of rich socialization for adult individuals with paranoid schizophrenia, the likelihood that the COVID-19 stay-at-home measures disproportionately affected this population cohort is high. Without social inclusion adult individuals with paranoid schizophrenia experience barriers to effective treatment resulting in an increased likelihood of relapse and subsequent hospitalization. The goal of this study is to determine if the stay-at-home public health measures instituted over the course of the COVID-19 pandemic (March 2020-Dec 2022) resulted in an increase in admissions to hospital for adults actively treated for paranoid schizophrenia, as compared to historical controls.

Effect of COVID-19 Public Health Measures on Admission Rate of Adults Treated for Paranoid Schizophrenia

Adults treated for paranoid schizophrenia often present with inadequate income, positive and negative symptoms, medication side effects, and limited social skills that can impair their inclusion into social groups and ability to access clinical and natural supports (Kozloff et al., 2020). Without the addition of socialization to augment medication treatment and recovery of paranoid schizophrenia, poor patient outcomes can develop, and subsequently increase the financial demands on our health care system. Moreover, the ability for individuals with paranoid schizophrenia to achieve recovery is compromised (Kozloff et al., 2020).

In March of 2020, COVID-19 virus led to the declaration of a worldwide pandemic, resulting in the introduction of a myriad of social isolation public health measures such as social distancing, suspension of in-person appointments, closing of bars and restaurants to in-person dinning, limiting occupancy in stores and wearing face coverings. All these measures reduced face-to-face contact and social interactions. The intention of limiting social contact was to reduce the spread of the virus and its potential for deleterious consequences on the health and wellness of individuals and the state of the health care system. While these measures were somewhat successful in their purpose to reduce the spread of COVID-19, they may have caused detrimental effects on patients such as adults treated for paranoid schizophrenia whose recovery and treatment relies on socialization (Husain et al., 2021). Standard treatment of these patients to control symptoms and limit hospitalization include the presence of natural supports, medication compliance, attendance at group and individual programing, and routine visits with primary care clinicians (Eisner et al., 2018). In Alberta, Canada for example, COVID-19 public health measures resulted in the canceling in-person sessions and an eventual shift of therapeutic groups and individual face-to-face programming to online sessions. As well they led to a reduction in routine visits to primary care clinicians and put a strain on hospital staffing. Staffing levels were often reduced due to illness caused by COVID-19 increasing demands on the workload of those well enough to work. Health officials limited and sometimes prohibited in-person gatherings to limit the spread of the disease. A review the literature relevant to the effect of socialization on adults treated for paranoid schizophrenia as well as studies that have examined the relationship between COVID-19 and mental health appears below.

Literature Review

Socialization and Schizophrenia

A growing body of research shows that inclusion of socialization and social interaction for adults treated for paranoid schizophrenia adds value to recovery when combined with anti-psychotic medication. Jameel et al. (2020) conducted a cross-sectional survey on 20 female patients, seven psychiatrists and seven psychologists in Pakistan. This study found a positive correlation between social inclusion and willingness for patients to take their medication. This highlights the significance of augmenting traditional antipsychotic medications with socialization to treat paranoid schizophrenia (Szarpak et al., 2021). The study by Jameel et al. (2020) provides evidence that the addition of socialization can increase compliance of adults with paranoid schizophrenia to take their antipsychotic medication, which is essential to their recovery in the community.

In addition to augmenting antipsychotic medications with socialization for treatment of adults with paranoid schizophrenia, it is important to consider psychological and cognitive consequences of social exclusion for adults treated for paranoid schizophrenia. Reddy et al. (2019) investigated the effects of being included and excluded from social groups using a blinded computer game to simulate the feeling of being excluded or included from a group. The researchers studied 34 patients diagnosed with paranoid schizophrenia in Los Angeles, California. The patients were divided into two matched groups where they were made to feel either included or excluded from a group. Following the game, they were tested on psychological need, working memory and social cognition. The results indicated that participants who experienced social exclusion exhibited longer lasting negative emotions and an increase in feelings of paranoia than those in the inclusion group. This increased paranoia is consistent with a general set of symptoms observed in adults with schizophrenia, often referred to as positive symptoms. Positive symptoms are strong indicators adults with paranoid schizophrenia may be at risk of a relapse (Davarinejad et al., 2021). Consequently, hospitalization may be required. These results suggest lack of social inclusion may result in an increase in admission to hospital (Rubio et al., 2020).

The positive influence of family support on the recovery of adults treated for paranoid schizophrenia was identified by Widiyawati et al. (2020). Using separate questionnaires to evaluate family support and adaptation skills, the authors surveyed 101 outpatient adults treated for schizophrenia in Indonesia. The researchers used survey data to look for an association between family support and adaptive response to treatment. The results showed that individuals with high family support also had a high adaptive response. The results of this study suggest that reduced contact with family members during COVID-19 pandemic public health measures may have resulted in maladaptive responses leading to admission to hospital (Widiyawati et al., 2020). COVID-19 Public Health Restrictions and Mental Health

The COVID-19 pandemic response involved the implementation of physical distancing interventions such as public health orders to reduce to spread of the virus. Despite the intentions to reduce spread of the virus, numerous researchers have investigated the deleterious effects some of these measures may have had on people diagnosed with mental health issues. Tull et al. (2020) performed a nationwide survey in the United States with 500 individuals aged 20 to 70 consisting of 47% female, 51.8% men 0.2% transgender, 0.6% non-binary and 0.4% other. The survey sought to address the effect of public health measures on several mental health indicators in a standard cross section of the population; mental health condition status was not indicated. Participants who were under public health measures showed an increase in anxiety, financial worry, and loneliness. The authors highlighted the importance of social connection to mitigate the negative impacts of these public health measures. However, despite this limitation, this study demonstrated how the lockdown measures increased both anxiety and loneliness in this representative cross section of the population.

In another study carried out in the United States, Marroquin et al. (2020) performed a nationwide online sampling of 435 adults to assess the effects of both public health measures and social distancing on mental health indicators. Tull et al. (2020) also found an increase in anxiety disorder, intrusive thoughts, insomnia, and acute stress. The authors found that available social resources alone were not enough of a protective factor to completely reduce effects of public health measures and distancing. In addition, 118 of the participants had participated in a previous study prior to the COVID-19 pandemic public health measures being implemented; when combined with the data collected in the current study this provides a time series. These patients showed an increase in level of depression and anxiety disorder relative to their previous survey, indicating results found cannot be attributed to baseline anxiety or depression. This study further indicates the population likely experienced an increase in disorders such as depression and anxiety due to the public health measures implemented. These disorders are shown to deleteriously affect patients with schizophrenia who are living in the community, often causing relapse and hospitalization (Rubio et al., 2020).

Research specific to adults treated for paranoid schizophrenia and the impact of COVID-19 is a topic that has not been thoroughly studied. The exploration of the literature related to this topic leads to theorize socialization is associated with better treatment outcomes for people with paranoid schizophrenia. Consequently, it is hypothesized that the removal of socialization due to COVID-19 public health measures, had a detrimental effect on the treatment regime of adults with paranoid schizophrenia, resulting in an increased rate of daily hospital admissions.

Methods

Participants

Participants will include all adult residents of Alberta, age 18 to 65 admitted to a psychiatric unit located within a hospital in the province with a diagnosis of paranoid schizophrenia as defined by the Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association, 2013) from March 17, 2016 – March 16, 2018 and March 17, 2020 – March 16, 2022, sorted by day of admission.

Participants will be excluded if they have additional mental health diagnoses, clinically significant neurological disease and/or a history of serious head injury, evidence of substance dependence 6 months prior to admission, history of intellectual and/or developmental disability. Only patients who have previously been treated for paranoid schizophrenia will be included in the study; only patients with an active prescription for antipsychotic medication listed in the Measure section will be included in the data. Patient data is available for the entire population of Alberta; therefore, sampling is not required.

Procedures

All data will be extracted from the Alberta Health Services (AHS) provincial wide electronic health record system, EPIC. EPIC contains selection and filter tools to allow for the tabulation of patient data based on the criteria outlined in the Participants section. To ensure the fidelity of the data extracted through this automated process, a validation subset of data will be verified manually. The validation subset of data will consist of patient data over a one-month period (March 17, 2016, to April 17, 2016) extracted using the same selection criteria as outlined in the Participants section. To confirm the accuracy of this subset of data, a manual cross referencing will be done against the emergency department record at each hospital. Once the data extraction has been validated, the selection tools will be used to tabulate the number of patients admitted per day who meet selection criteria outlined in Participants section above for each two-year period. Data will not have subsequent identifiable information such as name and date of birth since only the number of admissions data will be recorded. The researcher will apply to the Heath Research Ethics Board of Alberta (HREBA) Community Health Committee (Health Research Ethics Board of Alberta, 2022) for an Ethics exemption to remove the requirement for informed consent (Health Research Ethics Board of Alberta, 2022).

Research Design

This research study is exploratory, with the goal to investigate a possible impact of the COVID-19 pandemic’s public health measures. The aim is to generate a foundation for ideas with regard to the COVID-19 pandemic and the effect on adults treated for paranoid schizophrenia (Bhattacherjee, 2012). It is a descriptive quantitative study collecting secondary data retrospectively. The dependent variable of hospital admission rates per capita per day will be determined by dividing the hospital admission rate per day by the mid-point population data of each of the time periods. Independent variables of two distinct time periods will be used, data collected after public health measures were enacted (March 17, 2020, to March 16, 2022) and 2-year period 4 years prior (March 17, 2016 to March 16, 2018) to the implementation of these measures.

Data Analysis

Average hospital admission rate per capita per day will be summarized for each time period using average +/- standard deviation. These two rates will be tested for normality and skewness and tested for significant difference using a two-sample t-test or Mann-Whitney U test depending on if the data is determined to be normal or not. P-values < 0.05 were considered statistically significant (Goel et al., 2021).

Measures

The measure of Age in this research proposal is defined as individuals 18-64 years at the time of admission. The Diagnosis measure is the clinical diagnostic definition of paranoid schizophrenia as per the DSM 5. The measure of Antipsychotic Medication is defined by all antipsychotic medications listed in the Physicians’ Desk Reference (Physicians’ Desk Reference, 2016). The measure of Living in Alberta is defined by an active Alberta Health Care number at time of hospital admission. The measure of Admitted to the Hospital is defined by being admitted to a psychiatric unit at the hospital.

Discussion

This study assumes that the primary end point of care for adults treated for schizophrenia is hospital care. This assumption may be incorrect during an occurrence like the COVID-19 pandemic as patients may have been leery of hospitals and sought help elsewhere. The design of this study does not enable to comment on the ability of patients to seek help by other means.

Grouping the data into a two-year time period assumes that the pandemic restrictions would have a broad lasting effect on hospital admission rates, even though the admission rates may have vacillated for other reasons throughout these 2 years. An additional assumption is that the public health measures had an immediate effect on the data collected in this study. Looking at data in the suggested 4-year interval would allow for some effect of lag to show, however, it may that the effect will be seen at a later time point then we collected the one we used for in this study.

While there are positives of collecting data in a real-world setting it is impossible to control for all possible confounding factors. One such factor would be that the admission and hospitalization rates for the 3 to 4 years prior to the pandemic are not representative of a true historical control due to many factors. This could be re-examined by looking at date further back in history or comparing against other research that has looked at similar data.

Secondary data analysis may be an effective means of research where primary data collection is too costly or infeasible, and secondary data is available at a level of analysis suitable for answering the researcher’s questions. The limitations of this design are that the data might not have been entered into the EMR system in a systematic or scientific manner and hence unsuitable for scientific research. Because the data was recorded for a presumably different purpose, the data may not adequately address the research questions of interest to the researcher. As a further confounding factor to the fidelity of the data entered to the EMR system was the implementation of the COVID-19 public health stay at home measures. During this time, physicians, nurses, and support staff had many additional duties to perform due to policy changes introduced to limit the spread of COVID-19. This may have led to constraints on the time they had to complete documentation impeding the accuracy of the data entered.

A further limitation of this research proposal is examining hospital admissions at a whole since there could be individual factors that influence admission rates that get undetected in global data. A further analysis divided into age brackets and gender brackets could provide further information to the effect of the public health measures on distinct groups. To determine the age brackets to be used for this analysis one would have to investigate the literature to determine preexisting reasons why age may be a factor and this this accordingly to divide the groups for analysis. Additionally, looking at data in finer time points could provide insight into the timing of when a specific public health measure was taken and when an effect on hospitalization rate was seen.

Exploratory research, such as this study, looks for associations between events and outcomes. In this work the root cause of why or how socialization leads to an increase in hospitalizations is not explored, however, this work would form basis for others to examine these issues. The inclusion of variables such as age, race, sex, income source, and place of residence could further provide subsets of information to expand on understanding of identifying variables specific to the problem.

Furthermore, it is assumed patients treated for paranoid schizophrenia that require hospitalization will be subsequently admitted. It is unknown how the effect of an outbreak, such as the COVID-19 pandemic, would affect the availably of hospital beds for patients presenting with mental health issues. For example, a lack of capacity to admit patients to hospital due to staffing shortages, isolation protocols limiting room capacity and other responses to the pandemic may cause a reduction in patients admitted to the hospital for non-COVID-19 causes. Consequently, an increase in hospitalization of patients treated for paranoid schizophrenia because of the COVID-19 public health stay home measures may not be evident in the raw number of hospital admission measured in this study.

Historical data for comparison was chosen to be at a time point close to the enactment of the COVID-19 public health at home measures (within a 4-year period). A benefit of choosing a close time point is to the limit the effect of restructuring and reorganization of the AHS provincial addiction and mental health inpatient hospital beds. Within a provincial health care system there are various external factors, such as pollical changes, funding, and number of available staff, that affect the number and location of hospital beds available for patients presenting with mental health issues. These changes may affect the number of patients admitted to hospital bed at any given time point. As an extension to this study, an examination of the wait times of patients may provide further information to demand for hospital beds that is not captured in looking at the rate of hospital admissions alone.

References

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). https://doi.org/10.1176/appi.books.9780890425596

Bhattacherjee, A. (2012). Social Science Research: principles, methods, and practices. In Book 3. http://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=1002&context=oa_textbooks

Davarinejad, O., Majd, T. M., Golmohammadi, F., Mohammadi, P., Radmehr, F., Alikhani, M., Motaei, T., Moradinazar, M., Brühl, A., Bahmani, D. S., & Brand, S. (2021). Identification of risk factors to predict the occurrences of relapses in individuals with schizophrenia spectrum disorder in Iran. International Journal of Environmental Research and Public Health, 18(2), 1–13. https://doi.org/10.3390/ijerph18020546

Eisner, E., Drake, R., Lobban, F., Bucci, S., Emsley, R., & Barrowclough, C. (2018). Comparing early signs and basic symptoms as methods for predicting psychotic relapse in clinical practice. Schizophrenia Research, 192, 124–130. https://doi.org/10.1016/j.schres.2017.04.050

Goel, V., Chan, R. K., Smibert, O. C., Holmes, N. E., Marhoon, N., Bach, C. A. T., Trubiano, J. A., & Jones, N. R. (2021). Identifying patterns in unplanned hospital admissions during the COVID-19 pandemic: a single-centre retrospective study. Internal Medicine Journal, 51(6), 868–872. https://doi.org/10.1111/imj.15075

Health Research Ethics Board of Alberta. (2022). HREBA Overview. https://hreba.ca/community-health-committee/

Husain, M. O., Gratzer, D., Husain, M. I., & Naeem, F. (2021). Mental illness in the postppandemic world: Digital psychiatry and the future. Frontiers in Psychology, 12, 10–13. https://doi.org/10.3389/fpsyg.2021.567426

Jameel, H. T., Panatik, S. A., Nabeel, T., Sarwar, F., Yaseen, M., Jokerst, T., & Faiz, Z. (2020). Observed social support and willingness for the treatment of patients with schizophrenia. Psychology Research and Behavior Management, 13, 193–201. https://doi.org/10.2147/prbm.s243722

Kozloff, N., Mulsant, B. H., Stergiopoulos, V., & Voineskos, A. N. (2020). The COVID-19 global pandemic: Implications for people with schizophrenia and related disorders. Schizophrenia Bulletin, 46(4), 752–757. https://doi.org/10.1093/schbul/sbaa051

Marroquín, B., Vine, V., & Morgan, R. (2020). Mental health during the COVID-19 pandemic: Effects of stay-at-home policies, social distancing behavior, and social resources. Psychiatry Research, 293(5), 113-119. https://doi.org/10.1016/j.psychres.2020.113419

Physician's Desk Reference (71st ed.). (2016). PDR Network

Reddy, L. F., Irwin, M. R., Breen, E. C., Reavis, E. A., & Green, M. F. (2019). Social exclusion in schizophrenia: Psychological and cognitive consequences. Journal of Psychiatric Research, 114(4), 120–125. https://doi.org/10.1016/j.jpsychires.2019.04.010

Rubio, J. M., Schoretsanitis, G., John, M., Tiihonen, J., Taipale, H., Guinart, D., Malhotra, A. K., Correll, C. U., & Kane, J. M. (2020). Psychosis relapse during treatment with long-acting injectable antipsychotics in individuals with schizophrenia-spectrum disorders: an individual participant data meta-analysis. The Lancet Psychiatry, 7(9), 749–761. https://doi.org/10.1016/S2215-0366(20)30264-9

Szarpak, J., Ciejka, K., Perczyńska, W., Flis, M., & Wróbel-Knybel, P. (2021). When does schizophrenia really begin? - A case report confirming the neurodevelopmental theory of schizophrenia. Current Problems of Psychiatry, 22(1), 26–37. https://doi.org/10.2478/cpp-2021-0003

Tull, M. T., Edmonds, K. A., Scamaldo, K. M., Richmond, J. R., Rose, J. P., & Gratz, K. L. (2020). Psychological outcomes associated with stay-at-home orders and the perceived impact of COVID-19 on daily life. Psychiatry Research, 289(5), 98-113. https://doi.org/10.1016/j.psychres.2020.113098

Widiyawati, W., Yusuf, A., Devy, S. R., & Widayanti, D. M. (2020). Family support and adaptation mechanisms of adult outpatients with schizophrenia. Journal of Public Health Research, 9(2), 219–222. https://doi.org/10.4081/jphr.2020.184