Auditing improvements to physical health in the acute psychiatric inpatient setting

AimsWhilst patient psychiatric health is the primary focus in the acute psychiatric inpatient setting, there has been a recent focus on ensuring a greater integration with physical health to address the physical health outcome inequalities between patients with psychiatric conditions and those without. Despite the ward having a robust physical health clerking proforma, there were issues with its completion; at initial clerking patients often aren't able, or refuse, to consent to physical examination or investigations. This lead to the trust's electronic physical health form, designed to collate these results, not always being completed. Our aim was to increase the rates of completion.MethodChanges to ward handover sheets were made in an effort to increase rates of physical health form completion and improve 24 and 72 hour completion rates. Columns were added delineating which parts of the physical clerking were outstanding, ensuring the MDT were aware of which jobs needed actioning. Data for two months prior and post intervention were analysed.Result266 admissions were analysed for the two months prior and post the intervention. Form completion rose from July (88%) to October (100%), with 24 and 72 hour completion rate increasing from 47% & 55% respectively, to 84% & 96%, during the same time period. Greater completion rates of physical health forms led to increased knowledge of patients’ physical health issues. Having 96% of patients physical health issues within three days of admission (cf. 55%, July), led to a 'physical health huddle' being held during the MDT. This provided a platform to discuss relevant physical health treatment plans with the whole team. These findings were summarised under a new column on the handover sheet and updated biweekly during the MDT meeting. Placement on the handover sheet ensured daily visibility to all staff.ConclusionSimple structural changes can bring physical health to the fore in psychiatric care. Timely and more complete physical health data enabled biweekly reviews of physical health issues and allowed input across the MDT. Increased knowledge and awareness of physical health issues led to an increase in medical review requests. These are currently performed on an ad hoc basis, which can be quite disorganised and inefficient. The results above, of improved physical health outcomes based on a structured approach, have led to a recommendation of a biweekly physical health clinic, with specific staffing allocation, to ensure a more thorough and efficient way to address physical health.

Children's activity and transportation choices: exploring socio-demographic correlates and health outcomes

Using data gathered from children aged 9-12 from Toronto (n=628), a cluster analysis was performed seeking to identify children's lifestyle activity and transportation choices, and associated physical activity accumulation. This research sought to identify whether activity and transportation choices could be combined in the same analysis and produce a composite profile. It also sought to determine if specific choice profiles could be associated with children's health outcomes as measured by Moderate to Vigorous Physical Activity (MVPA). A two-step cluster analysis was performed which identified five distinct clusters, namely Screeners, Artists, Athletes, Scholars and Mobiles. Athletes, with a high amount of sports participation had the best physical health outcome while Screeners, with little active activity engagement, had the worst. Socio-economic analyses were performed on all resultant clusters, identifying statistically significant patterns in household income, built form and gender.

Children's activity and transportation choices: exploring socio-demographic correlates and health outcomes

Using data gathered from children aged 9-12 from Toronto (n=628), a cluster analysis was performed seeking to identify children's lifestyle activity and transportation choices, and associated physical activity accumulation. This research sought to identify whether activity and transportation choices could be combined in the same analysis and produce a composite profile. It also sought to determine if specific choice profiles could be associated with children's health outcomes as measured by Moderate to Vigorous Physical Activity (MVPA). A two-step cluster analysis was performed which identified five distinct clusters, namely Screeners, Artists, Athletes, Scholars and Mobiles. Athletes, with a high amount of sports participation had the best physical health outcome while Screeners, with little active activity engagement, had the worst. Socio-economic analyses were performed on all resultant clusters, identifying statistically significant patterns in household income, built form and gender.

The Effects of Adverse Childhood Experiences on Self-Reported Physical and Mental Health Outcomes in Adulthood

The number of physically and mentally unhealthy days as a measure of health-related quality of life (HRQOL) is used to examine the different effects of the adverse childhood experiences (ACEs) on physical and mental health outcomes. The data, a cross-sectional state-level survey, is obtained from the Behavioral Risk Factor Surveillance System (BRFSS) collected by the Centers for Disease Control and Prevention (CDC) in 2012. Multiple regression analyses are conducted for the study. The results indicate that all individual ACE categories are inversely associated with both physical and mental health, as respondents who exposed to any adverse childhood experience are likely to have physically- and mentally-related poor HRQOL in adulthood. The estimated coefficients for individual ACEs in magnitude on the mental health outcome are, in overall, greater than the estimated coefficients on the physical health outcome. The regression results with accumulative ACE scores indicate that higher levels of the ACE score would affect higher negative health outcomes, such as the dosage effects that appear again in this study. The estimated coefficients of accumulative ACE scores on the mental health outcome exceed the coefficients of ACE scores on physical health outcome for an ACE score of 2 and above. The gap in the estimated coefficients of ACE scores between physically and mentally unhealthy days increases as the ACE score rises. The estimated coefficient at the score ACE8 for the mentally unhealthy days becomes almost twice as large as the coefficient for the physically unhealthy days. Importantly, the negative effects of ACEs on mental health outcomes are significantly greater than the negative effects on physical health outcomes.