Abstract
Abstract
Background and Purpose—
Home-time (HT) is a stroke outcome measure based on time spent at home after stroke. We hypothesized that HT assessment would be feasible and valid using national data.
Methods—
We linked the Scottish Stroke Care Audit to routine healthcare data and calculated 90-day HT for all strokes, 2005 to 2017. We described prognostic validity (Spearman rank correlation) of HT to baseline factors.
Results—
We were able to calculate HT for 101 969 strokes (99.3% of total Scottish strokes). Mean HT was 46 days (95% CI, 45.8–46.2; range, 0–90). HT showed consistent correlation with our prespecified prognostic factors: age: ρ, −0.35 (95% CI, −0.35 to −0.36); National Institutes of Health Stroke Scale, −0.54 (95% CI, −0.52 to −0.55); and 6 simple variables (ordinal), −0.61 (95% CI, −0.61 to −0.62).
Conclusions—
HT can be derived at scale using routine clinical data and appears to be a valid proxy measure of functional recovery. Other national databases could use HT as a time and cost efficient measure of medium and longer-term outcomes.
Background and Purpose—
Home-time (HT) is a stroke outcome measure based on time spent at home after stroke. We hypothesized that HT assessment would be feasible and valid using national data.
Methods—
We linked the Scottish Stroke Care Audit to routine healthcare data and calculated 90-day HT for all strokes, 2005 to 2017. We described prognostic validity (Spearman rank correlation) of HT to baseline factors.
Results—
We were able to calculate HT for 101 969 strokes (99.3% of total Scottish strokes). Mean HT was 46 days (95% CI, 45.8–46.2; range, 0–90). HT showed consistent correlation with our prespecified prognostic factors: age: ρ, −0.35 (95% CI, −0.35 to −0.36); National Institutes of Health Stroke Scale, −0.54 (95% CI, −0.52 to −0.55); and 6 simple variables (ordinal), −0.61 (95% CI, −0.61 to −0.62).
Conclusions—
HT can be derived at scale using routine clinical data and appears to be a valid proxy measure of functional recovery. Other national databases could use HT as a time and cost efficient measure of medium and longer-term outcomes.
Original language | English |
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Pages (from-to) | 1282-1285 |
Number of pages | 4 |
Journal | Stroke |
Volume | 50 |
Issue number | 5 |
Early online date | 21 Mar 2019 |
DOIs | |
Publication status | Published - 1 May 2019 |
Keywords
- length of stay
- morbidity
- quality improvement
- stroke
- survivors
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Mary MacLeod
- School of Medicine, Medical Sciences & Nutrition, Centre for Health Data Science
- School of Medicine, Medical Sciences & Nutrition, Applied Medicine - Senior Clinical Lecturer
- Institute of Medical Sciences
Person: Clinical Academic