Socioeconomic Aspects of Postacute Care for Patients with Brain Infarction in France

Abstract

Background: In France, the socioeconomic aspects of stroke have never been addressed. Such analyses are essential for health authorities to justify the establishment of new stroke units when resources are low, provided it can be shown that stroke units are effective in reducing both the morbidity and mortality of stroke. Only 6 dedicated stroke services exist for 60 million inhabitants in France. Our aim was to study acute and postacute pathways and to determine the factors that influence destination after discharge, handicap evolution and costs. Methods: In a cohort of 494 consecutive patients with brain infarction, we collected information on medical and socioeconomic variables, handicap and its evolution using the modified Rankin scale and Mini-Mental Status score at the 10th day, 6th month and 18th–40th month. These data were recorded during the initial hospital stay, at the follow-up clinic visit and in a home interview done 18–40 months after discharge by research nurses. We used multiple logistic regression for analyses. Results: The most important factor for not returning home was having a Rankin score greater than 3 with an odds ratio of 41.7 (95% confidence interval 19.2–90.0; p = 0.001). Multivariate analysis showed that when the Rankin score was 0, 1 or 2, the main factors for not returning home were socioeconomic variables and serious medical disorders. When the Rankin score was 4 or 5, the main reason for not being sent for rehabilitation was medical status. After adjustment for the Rankin score, patients who returned home or were transferred to rehabilitation were quite similar regarding socioeconomic and medical variables. Other patients transferred to a geriatric ward, nursing home or new housing were more frequently living alone, 60 years of age or older, had less than 2 children, low level of education, dementia or cancer. Overall, the mean cost was 19,513 Euros over an 18-month period and was mainly driven by the level of the Rankin score (e.g. 10,530 vs. 34,809 Euros for Rankin scores of 0–1 and 4–5, respectively). Conclusion: These data showed that not only handicap level but also socioeconomic variables are important in determining the destination of stroke patients after discharge. They may help health authorities to make decisions to establish new approaches to treat stroke. This study can also serve as a basis for future cost-effectiveness studies of new drugs being evaluated in therapeutic trials or of new management strategies of stroke patients.

Estimating the Cost-Effectiveness of Stroke Units in France Compared With Conventional Care

“…If the number of new strokes is increased from the 124 000 new cases per year, calculated from data in the Dijon stroke registry, to 144 000 new cases per year, from the data of Hankey and Warlow, 3 Reducing the duration of the simulation in the Markov model from 5 years to 18 months generates an overall cost of 2800 million € for 150 000 patients treated initially in conventional care. This estimate corresponds, with Ͻ5% error, to the results obtained by Spieler et al 21 (2900 million €) from an observational study carried out in 12 centers on 435 patients with ischemic stroke. This convergence is an important argument in favor of the pertinence of the assumptions made in our Markov model.…”

Lifetime Cost of Stroke Subtypes in Australia

“…1 However, few investigators have detailed costs for stroke subtypes. [2][3][4][5][6][7] Costs of the major stroke subtypes are likely to differ, given that they have different risk factors, average age of onset, incidence rates, treatments, and outcomes. There is also some evidence that the cost of care varies with stroke subtype.…”

The Mobility Scale for Acute Stroke predicts discharge destination after acute hospitalization

“…None of the other covariants added value to the MSAS score for prediction of discharge destination. The literature on the role of sex (4,5,24,(26)(27)(28)(29)(30)(31)(32)(33)(34)(35), age (4, 5, 23, 24, 26-28, 31, 32, 35, 36), type of stroke (23,24,26,31,32), length of acute hospitalization (26,37,38) and number of days spent in the intensive care unit (31) is mixed on these factors' association with discharge destination from the acute care setting. The findings based on the current sample suggest that activity, as measured by the MSAS, is a more important factor in determining discharge destination from the acute setting.…”