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Determining the Influence of Psychiatric Comorbidity on Hospital Admissions in Cardiac Patients Through Multilevel
Niranjan Bidargaddi1, Geoffrey Schrader1, Graeme Tucker2
1College of Medicine & Public Health, Flinders University, Adelaide, SA, Australia; Country Health South Australia, Adelaide, SA, Australia.
Insights
Cardiac patients with mental health conditions experienced longer hospital stays and more admissions. This highlights the impact of psychiatric comorbidity on healthcare utilization.
Area of Science:
- Health Services Research
- Clinical Informatics
- Cardiology
Background:
- Big data analytics of hospital records offer clinical insights.
- Psychiatric comorbidity impacts cardiac patient outcomes.
- Routinely collected data can inform healthcare utilization.
Purpose of the Study:
- To determine the impact of psychiatric comorbidity on length of hospital stay.
- To assess the effect of psychiatric comorbidity on the number of hospital admissions in cardiac patients.
- To utilize routinely collected hospitalization records for clinical insights.
Main Methods:
- Utilized routinely collected clinical and socio-demographic data from 37,580 cardiac patients (aged 18-65).
- Employed multi-level models to analyze psychiatric comorbidity's effect on length of stay and hospitalizations.
- Accounted for socioeconomic status, disease burden, and confounders like age, sex, and rural status.
Main Results:
- Psychiatric comorbidity was associated with a 12.5% increase in length of stay for cardiac patients.
- Cardiac patients with mental health diagnoses had a 20.0% increase in the number of hospital admissions.
- Significant impact of mental health diagnoses on healthcare service utilization observed.
Conclusions:
- Routinely collected hospitalisation records are valuable for understanding psychiatric comorbidity's impact.
- Findings demonstrate the significant effect of mental health conditions on cardiac patient healthcare utilization.
- Highlights the need to integrate mental health considerations in cardiac care management.
Background:
Increasingly, big data derived from administrative hospital records can be subject to analytics to provide clinical insights. The aim of this study was to determine the impact of psychiatric comorbidity on length of hospital stay and number of hospital admissions in cardiac patients utilising routinely collected hospitalisation records.
Methods:
We routinely collected clinical and socio-demographic variables extracted from 37,580 cardiac patients, between 18 and 65 years old, admitted to South Australian hospitals between 2001/02 to 2010/11 financial years with cardiac diagnoses used to derive patient level and separation level variables used in the modelling. Multi-level models were constructed to analyse the impact of psychiatric comorbidity on both length of stay and the total number of hospitalisations, allowing for interactions between socioeconomic status and the burden of disease. Possible confounders for these models were, sex, age, indigenous status, country of birth, and rural status.
Results:
For cardiac patients a mental health diagnosis was associated with an increase of 12.5% in the length of stay, and an increase in the number of stays by 20.0%.
Conclusions:
This study demonstrates the potential utility of routinely collected hospitalisation records to demonstrate the impact of psychiatric comorbidity on health service utilisation.
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