2015
DOI: 10.1161/circoutcomes.115.002068
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Care Trajectories of Veterans in the 12 Months After Hospitalization for Acute Ischemic Stroke

Abstract: Background— Recovery after a stroke varies greatly between individuals and is reflected by wide variation in the use of institutional and home care services. This study sought to classify veterans according to their care trajectories in the 12 months after hospitalization for ischemic stroke. Methods and Results— The sample consisted of 3811 veterans hospitalized for ischemic stroke in Veterans Health Administration facilities in 2007. Three outcomes—nu… Show more

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Cited by 15 publications
(12 citation statements)
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“… 14 15 In a recent study, five subgroups of patients were identified based on the pattern of recovery following stroke, each with a distinct prognosis and risk of mortality. 16 Similar observations are present in patients with other conditions such as surgery and heart failure. 17 18 It has been suggested that more than half of the high-risk users decreased their use of the healthcare visits after 1 year and a smaller proportion of the high-risk patients persistently and increasingly used healthcare services throughout the 4-year follow-up.…”
Section: Introductionsupporting
confidence: 62%
“… 14 15 In a recent study, five subgroups of patients were identified based on the pattern of recovery following stroke, each with a distinct prognosis and risk of mortality. 16 Similar observations are present in patients with other conditions such as surgery and heart failure. 17 18 It has been suggested that more than half of the high-risk users decreased their use of the healthcare visits after 1 year and a smaller proportion of the high-risk patients persistently and increasingly used healthcare services throughout the 4-year follow-up.…”
Section: Introductionsupporting
confidence: 62%
“…However, employing appropriate methods to describe and propose a comprehensive visualization of longitudinal patterns of events, without altering the integrity of real patients' journey through the healthcare system, remains challenging. In recent years, several data mining and statistical approaches have been proposed to extract patterns from sequential data of CTs, such as formal concept analysis [15], latent class analysis [16,17], neural network [18], multi-state Markov model [12] and exponential proportional hazards mixture model [19]. However, getting the picture of complex temporal event sequences is not straightforward for non-experts, despite the variety of strategies available to develop visual analytic tools and graph-based approaches [20][21][22].…”
Section: Introductionmentioning
confidence: 99%
“…Temporal trends of index-stroke hospitalization [ 15 ], recurrent stroke admissions [ 16 , 17 ], inpatient rehabilitation utilization [ 18 ] and associated risk factors [ 19 ] have been described previously, however papers studying post-stroke care trajectories are sparse [ 20 ]. Focusing on the index stroke admission, researchers explored the temporal trends over a decade in UK setting and further explored the influence of patient socio-demographic (race and age) and functional characteristics on inpatient acute care and indicators of provision of rehabilitation [ 21 ].…”
Section: Introductionmentioning
confidence: 99%