Episode detection based on personalized intensity of care thresholds: a schizophrenia case study

Schizophrenia Spectrum Disorder (SSD) is characterized by its chronic, episodic nature. The clear definition of such episodes is essential for various clinical and research purposes. Most current definitions of episodes in SSD are based on either hospitalizations or on symptom scales. Both have drawbacks; symptom scales are measured infrequently, while hospitalization rates are often affected by policy. This study presents an approach for defining episodes in healthcare data that does not suffer such drawbacks.

Healthcare use of 13,155 SSD patients in the Northern Netherlands with up to 12 years of follow-up was available. Patient-level structural changes in the trend of healthcare use costs were determined using Exponentially Weighted Moving Average (EWMA) control charts. Control charts restart with updated parameters after a detected structural change. Episodes were defined using these structural changes. The resulting episodes were validated by investigating their association with the Global Assessment of Functioning (GAF) scale.

The mean number of episodes was 0.61 (sd: 0.60) per patient per year. For the sub-group without hospitalizations this was 0.51 (sd: 0.71). Average episode duration of the sub-group (147 days, sd: 309.4) was similar to that of the full sample (150 days, sd: 305.5). A significant inverse association was identified between GAF scores and the episode-state indicator.

The repeated application of EWMA control charts based on healthcare-intensity is a feasible and promising tool for quantifying patient-level healthcare episodes. The validation using GAF scores indicates that our episode indicator is associated with lower levels of global functioning. Results for individuals without hospitalizations indicate that the method is robust with regard to changes in healthcare policy.