Surveying Stroke Rehabilitation in Texas: Capturing Geographic Disparities in Outpatient Clinic Availability

Wozny, Joseph; Parker, Dorothea; Sonawane, Kalyani; Russell, Mary E.; Savitz, Sean I; Zamin, Syed; Zhu, Yenan

doi:10.1016/j.apmr.2021.07.544

Cited by 2 publications

(2 citation statements)

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“…6 In Texas, for example, the geographic disparities between rural and urban America are apparent; 71% of rural counties lack outpatient rehabilitation clinics for stroke patients, whereas only 19% of urban counties share the same issue. 7 Parekh and Barton 8 describe other contributing factors and the complications of healthcare delivery to an aging and increasingly disabled population, citing 75 million people who have multiple chronic conditions. These comorbidities reduce patient compliance and stand in the way of treatment that is best realized by active participation.…”

Section: Introductionmentioning

confidence: 99%

aBnormal motION capture In aCute Stroke (BIONICS): A Low-Cost Tele-Evaluation Tool for Automated Assessment of Upper Extremity Function in Stroke Patients

Zamin,

Tang,

Stevens

et al. 2023

Neurorehabil Neural Repair

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Background The incidence of stroke and stroke-related hemiparesis has been steadily increasing and is projected to become a serious social, financial, and physical burden on the aging population. Limited access to outpatient rehabilitation for these stroke survivors further deepens the healthcare issue and estranges the stroke patient demographic in rural areas. However, new advances in motion detection deep learning enable the use of handheld smartphone cameras for body tracking, offering unparalleled levels of accessibility. Methods In this study we want to develop an automated method for evaluation of a shortened variant of the Fugl-Meyer assessment, the standard stroke rehabilitation scale describing upper extremity motor function. We pair this technology with a series of machine learning models, including different neural network structures and an eXtreme Gradient Boosting model, to score 16 of 33 (49%) Fugl-Meyer item activities. Results In this observational study, 45 acute stroke patients completed at least 1 recorded Fugl-Meyer assessment for the training of the auto-scorers, which yielded average accuracies ranging from 78.1% to 82.7% item-wise. Conclusion In this study, an automated method was developed for the evaluation of a shortened variant of the Fugl-Meyer assessment, the standard stroke rehabilitation scale describing upper extremity motor function. This novel method is demonstrated with potential to conduct telehealth rehabilitation evaluations and assessments with accuracy and availability.

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Section: Introductionmentioning

confidence: 99%

aBnormal motION capture In aCute Stroke (BIONICS): A Low-Cost Tele-Evaluation Tool for Automated Assessment of Upper Extremity Function in Stroke Patients

Zamin,

Tang,

Stevens

et al. 2023

Neurorehabil Neural Repair

Self Cite

View full text Add to dashboard Cite

show abstract

“… 4 Geographic location substantially affects access to rehabilitation care as demonstrated by the 71% of all‐rural, US counties that do not have outpatient clinics that provide stroke rehabilitation services compared with 19% of nonrural counties. 5 Among patients receiving inpatient rehabilitation services post stroke, women—along with Black patients—were less likely to achieve optimal improvements according to the Functional Independence Measure, an 18‐item clinician reported scale that assesses functional capacity in six domains—mobility, transfers, self‐care, continence, cognition, and communication. 6 Survivors of stroke from lower‐income groups have also demonstrated poorer outcomes when attempting to reintegrate back into the community, which has devastating impacts on survivors' ability to return to key functional activities, such as securing and maintaining employment.…”

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confidence: 99%