Integrating Mental and Physical healthcare: Research Training and Services (IMPARTS)

Integrating Mental and Physical healthcare: Research Training and Services (IMPARTS) was a King’s Health Partners initiative designed to join up mental and physical healthcare in general hospital settings.

The IMPARTS Research and Education team sat within the Department of Psychological Medicine. Research focused on the interface between mental and physical health, in particular the link between depression and anxiety and long-term physical health conditions, and how to better connect mental and physical healthcare.

Research and education

The routine collection of patient-reported outcomes in services across King’s Health Partners provided exciting audit and research opportunities. Data was routinely collected, covering various aspects of mental and physical health outcomes, including depression; anxiety; alcohol and drug misuse; smoking; adherence; physical function; fatigue; illness perceptions; quality of life; and sleep quality. This provided broad scope for cross-sectional research examining prevalence of variables of interest, and assessment of the factors associated with these. Furthermore, we were able to link IMPARTS data with information held in Electronic Patient Records, meaning that demographic and disease variables could also be examined in relation to IMPARTS data.

The frequent follow-up of patients screened using IMPARTS also provided scope for longitudinal study designs. These could then examine the trajectory of mental health concerns, examine the impact of mental health on long-term physical health outcomes, or examine the impact of certain medical interventions on well-being.

Ethical approval was granted for IMPARTS-collected data to be used for research purposes. This enabled the audit of clinical practice against local and national standards of care; evaluations of patterns of service usage and demographic trends to inform commissioning of services; and hypothesis-driven observational research using pseudonymised data.