Hospital admissions for dental disorders in patients with severe mental illness in Southeast London: A register-based cohort study.
Jaya ChaturvediEllie HeidariJennifer Elizabeth GallagherJonathan TurnerCharlotte CurlRobert J StewartPublished in: European journal of oral sciences (2021)
In people with mental disorders, adverse general health is well recognized but dental diseases remain underinvestigated. The objective of this study was to investigate risk factors for hospital admissions for dental disorders in patients with severe mental illness (SMI) and/or depressive disorder. De-identified electronic mental health records from the South London and Maudsley NHS Foundation Trust (SLaM) were linked to national Hospital Episode Statistics (HES) data for analysis. Data were extracted for adults with a diagnosis of SMI (schizophrenia, schizoaffective disorder, bipolar disorder) and/or depression, who had received care at SLaM between 1 January 2010 and 31 March 2017. In the cohort of 18,999 patients thus obtained, the following factors were independently associated with hospital admission for dental disorders: female gender [odds ratio (OR) = 1.48, 95% CI: 1.31-1.68)], Health of the Nation Outcome Scales (HoNOS) problem drinking/drug taking (OR = 1.12, 95% CI: 1.05-1.19), HoNOS physical illness/disability (OR = 1.18, 95% CI: 1.12-.25), diabetes (OR = 1.24, 95% CI: 1.06-1.43), recorded current/past smoking (OR = 1.35, 95% CI: 1.06-1.43), treatment with antidepressant medication (OR = 1.48, 95% CI: 1.31-1.68), and depressive disorder (OR = 1.36, 95% CI: 1.11-1.68). Building on previous research in this population, which indicated a relatively high risk of acute care hospitalizations with dental disorders as discharge diagnoses, a number of demographic and clinical characteristics were found to be independent predictors over a 7-yr period. Further research into these predictors would facilitate a better understanding of how adverse dental outcomes might be prevented.
Keyphrases
- mental health
- mental illness
- bipolar disorder
- oral health
- healthcare
- acute care
- adverse drug
- major depressive disorder
- public health
- quality improvement
- health information
- ejection fraction
- type diabetes
- palliative care
- newly diagnosed
- emergency department
- physical activity
- early onset
- multiple sclerosis
- electronic health record
- depressive symptoms
- adipose tissue
- metabolic syndrome
- cardiovascular disease
- drug induced
- weight loss
- patient reported outcomes
- stress induced
- social media
- climate change
- machine learning
- data analysis
- insulin resistance
- sleep quality
- deep learning