Visualizing healthcare system variability and resilience: a longitudinal study of patient movements following discharge from a Swedish psychiatric clinic

BACKGROUND: As healthcare becomes increasingly complex, new methods are needed to identify weaknesses in the system that could lead to increased risk. Traditionally, the focus for patient safety is to study incident reports and adverse events, but that starting point has been contested with a new era of safety investigations: the analysis of everyday clinical work, and the resilient healthcare. This study introduces a new approach of system monitoring as a way to strengthen patient safety and has focused on discharge in psychiatry as a risk for adverse outcomes. The aim was to analyse a psychiatric clinic’s everyday ‘normal’ performance variability of discharge from inpatient psychiatric care to outpatient care. METHOD: A retrospective longitudinal correlation study with a strategic selection. Data consist of 70,797 patient visits within one psychiatric clinic, and the visits were compared between 81 different wards in Stockholm County by using a model of time-lapse visualization. RESULTS: The time-lapse visualization shows a discrepancy in types of visits and the proportion of cancelled visits to the outward units. 42% of all patients that were scheduled as an outward patient, did not complete this transition, but instead, they revisit the clinics’ emergency ward and did not receive the planned care treatment. The patients who visit the emergency ward instead of their planned outpatient visit did this within 20 days. CONCLUSIONS: The findings show a potential increased demand for emergency psychiatric care from 2010 to 2018 within the clinic. It also suggests that the healthcare system creates a space of temporal as well as functional variability, and that patients use this space to adapt to their changing conditions. This understanding can assist management in prioritising allocation of resources and thereby strengthen patient safety. Today’s incident reporting systems in healthcare are ineffective in monitoring patterns of more cancelled visits in outward units and sooner visit to the emergency ward. By using time-lapse visualization of patient interactions, stakeholders might analyse current-, and estimate future, stressors within the system to identify and understand potential system migration towards risk in healthcare. This could help healthcare management understand where resources should be prioritized.