COVID-19 and psychiatry: can electronic medical records provide the answers?

The COVID-19 pandemic has posed unprecedented challenges for health-care professionals, researchers, and policy makers, particularly in the area of serious mental illness. From the beginning of the pandemic, psychiatric symptoms have complicated medical care and contributed to morbidity and mortality.¹ Conversely, individuals with serious mental illness are known to have a high prevalence of comorbid conditions associated with symptomatic COVID-19, including obesity, hypertension, smoking, and diabetes.² Many individuals with psychiatric disorders also live in social conditions that result in high exposure to respiratory viruses, including seasonal coronaviruses.³ The sheer size and changing nature of the pandemic poses problems for investigators and policy planners investigating COVID-19 exposure and psychiatric disorders. This is particularly true in the USA, where the response to the pandemic has been hampered by the lack of a national medical care system and a patchwork of state and local public health agencies responsible for data collection and disease surveillance.

The electronic medical record has become a part of many medical practices in the USA. Although this system has been approached with trepidation by many US health-care providers,⁴ data generated by electronic medical records has proven a useful tool for the analysis of somatic and mental health outcomes.⁵ In The Lancet Psychiatry, Maxime Taquet and colleagues⁶ report data collated from electronic medical records by the TriNetX Analytics Network from more than 69 million individuals who received care at 54 US health-care organisations between Jan 20, and Aug 1, 2020. This report provides evidence for what the authors characterise as a bidirectional association between COVID-19 and psychiatric disorders.⁶ The first association relates to an increase in newly recognised psychiatric disorders in individuals with COVID-19, with relative risks in the range of 2–3 for anxiety disorders, insomnia, and dementia. The other association characterises an increase in COVID-19 in individuals with pre-existing psychiatric disorders, with an overall relative risk of 1·65.⁶ The latter results are largely congruent with a previous study based on another electronic medical record database,⁷ although there are some differences in the reported relative risks associated with different psychiatric diagnoses and populations.

Although potentially valuable for population-based studies, data derived from electronic medical records in the USA have limitations, most of which are noted in the report. Distinct from datasets based on national health-care systems, data derived from available electronic medical record-derived databases only capture events that occur in participating health-care organisations. Since the identity of participating health-care organisations and their relative contributions to the dataset are not disclosed, the generalisability of data derived from this population is difficult to assess. In this regard, although the 62 354 COVID-19 cases presented in this report is a large study population,⁶ they represent only a fraction of the number of cases reported in the USA during the same time period.⁸ In terms of psychiatric disorders, it is possible that the first entry of a diagnosis into the database might not represent the first occurrence of the condition, but rather the first time it is recognised by a health-care provider at a participating health-care organisation, making the timing of symptom onset relating to COVID-19 difficult to evaluate. Furthermore, data from electronic medical records are often lacking in information relevant to COVID-19. These data include detailed information relating to housing density, family size, current employment and immigration status, specific geographic location, and contact with others with COVID-19. Therefore, it is imperative that data derived from electronic medical records be supported by cohort studies that prospectively collect relevant information and biological samples

The changing nature of the COVID-19 pandemic presents a moving target for clinicians, investigators, readers of medical literature, and the general public. Infection rates in different areas are frequently changing. Additionally, new cases, clinical data, and analytic functionalities are being added to available databases. Conclusions based on any one dataset thus require frequent re-examination and re-interpretation. The recent retraction of articles on COVID-19 based on another database⁹ highlights the necessity of data sharing and transparency.

More than 100 years have passed since the worldwide influenza pandemic that resulted in a markedly increased rate of neurological and psychiatric sequelae.¹⁰ Despite great advances in medical science, we are faced with some of the same issues relating to the characterisation of a rapidly changing pandemic occurring in different geopolitical environments. Learning to use new tools, such as electronic medical records efficiently should provide some of the essential information needed to understand and control the psychiatric consequences of this pandemic and plan for future ones. In these efforts, we should keep in mind the words of Sir William Osler that, “the best preparation for tomorrow is to do today's work superbly well.”

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