Factors contributing to health care utilization and costs after stroke. Secondary results from the LAST study

Abstract

Background The result from the Life After Stroke (LAST) study showed that an 18-month follow up program as part of the primary health care, did not improve maintenance of motor function for stroke survivors. In this study we evaluated whether the follow-up program could lead to a reduction in the use of health care compared to standard care. Furthermore, we analyse to what extent differences in health care costs for stroke patients could be explained by individual need factors (such as physical disability, cognitive impairment, age, gender and marital status), and we tested whether a generic health related quality of life (HRQoL) is able to predict the utilisation of health care services for patients post-stroke as well as more disease specific indexes.

Methods The Last study was a multicentre, pragmatic, single-blinded, randomized controlled trial. Adults (age ≥ 18 years) with first-ever or recurrent stroke, community dwelling, with modified Rankin Scale < 5. The study included 380 persons recruited 10 to 16 weeks post-stroke, randomly assigned to individualized coaching for 18 months (n = 186) or standard care (n = 194). Individual need was measured by the Motor assessment scale (MAS), Barthel Index, Hospital Anxiety and Depression Scale (HADS), modified Rankin Scale (mRS) and Gait speed. HRQoL was measured by EQ-5D-5 L. Health care costs were estimated for each person based on individual information of health care use. Multivariate regression analysis was used to analyse cost differences between the groups and the relationship between individual costs and determinants of health care utilisation.

Results There were higher total costs in the intervention group. MAS, Gait speed, HADS and mRS were significant identifiers of costs post-stroke, as was EQ-5D-5 L.

Conclusion Long term, regular individualized coaching did not reduce health care costs compared to standard care. We found that MAS, Gait speed, HADS and mRS were significant predictors for future health care use. The generic EQ-5D-5 L performed equally well as the more detailed battery of outcome measures, suggesting that HRQoL measures may be a simple and efficient way of identifying patients in need of health care after stroke and targeting groups for interventions.