Literature DB >> 29854271

Sensi-steps: Using Patient-Generated Data to Prevent Post-stroke Falls.

Angela Smith1, Ada Ng1, Eleanor R Burgess1, Noah Weingarten1, Jennifer A Pacheco1.   

Abstract

We present Sensi-steps, an application using patient-generated data (PGD) to prevent falls for geriatric and especially poststroke patients. The Sensi-steps tool incorporates a wearable wrist device, pedometer, pressure and proximity sensors, and tablet. PGD collection occurs through Timed Up and Go (TUG) tests and collection of physiological data, which is integrated into the EHR. Fall risk factor active tracking encourages new ways of shared decision-making between patients, caregivers, and practitioners. PGD will be managed at the primary care nurse or Care Manager level (see 3-tier PGD service proposal), presenting a novel way to incorporate PGD into clinical decision-support systems. We expect our solution to be easier to use routinely by the patient at home than other fall risk tracking solutions. Sensi-steps has the potential to improve patient care, help patients make informed decisions, and help clinicians understand patient-generated, environmental, and lifestyle information to deliver personalized, preventative healthcare.

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Mesh:

Year:  2018        PMID: 29854271      PMCID: PMC5977661     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  14 in total

1.  Recovery of the sit-to-stand movement after stroke: a longitudinal cohort study.

Authors:  Wim Janssen; Johannes Bussmann; Ruud Selles; Peter Koudstaal; Gerard Ribbers; Henk Stam
Journal:  Neurorehabil Neural Repair       Date:  2010-08-10       Impact factor: 3.919

2.  A geriatric-anesthesiologic program to reduce acute confusional states in elderly patients treated for femoral neck fractures.

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Journal:  Am J Phys Med Rehabil       Date:  1989-06       Impact factor: 2.159

4.  Clinical tests performed in acute stroke identify the risk of falling during the first year: postural stroke study in Gothenburg (POSTGOT).

Authors:  Carina U Persson; Per-Olof Hansson; Katharina S Sunnerhagen
Journal:  J Rehabil Med       Date:  2011-03       Impact factor: 2.912

5.  How to identify potential fallers in a stroke unit: validity indexes of 4 test methods.

Authors:  Asa G Andersson; Kitty Kamwendo; Ake Seiger; Peter Appelros
Journal:  J Rehabil Med       Date:  2006-05       Impact factor: 2.912

6.  Predictive risk factors associated with stroke patient falls in acute care settings.

Authors:  V Byers; M E Arrington; K Finstuen
Journal:  J Neurosci Nurs       Date:  1990-06       Impact factor: 1.230

7.  Rating scale analysis of the Berg Balance Scale.

Authors:  Diana L Kornetti; Stacy L Fritz; Yi-Po Chiu; Kathye E Light; Craig A Velozo
Journal:  Arch Phys Med Rehabil       Date:  2004-07       Impact factor: 3.966

8.  The Dynamic Gait Index in healthy older adults: the role of stair climbing, fear of falling and gender.

Authors:  Talia Herman; Noit Inbar-Borovsky; Marina Brozgol; Nir Giladi; Jeffrey M Hausdorff
Journal:  Gait Posture       Date:  2008-10-08       Impact factor: 2.840

9.  The timed "Up & Go": a test of basic functional mobility for frail elderly persons.

Authors:  D Podsiadlo; S Richardson
Journal:  J Am Geriatr Soc       Date:  1991-02       Impact factor: 5.562

10.  Improving transitions in acute stroke patients discharged to home: the Michigan stroke transitions trial (MISTT) protocol.

Authors:  Mathew J Reeves; Anne K Hughes; Amanda T Woodward; Paul P Freddolino; Constantinos K Coursaris; Sarah J Swierenga; Lee H Schwamm; Michele C Fritz
Journal:  BMC Neurol       Date:  2017-06-17       Impact factor: 2.474

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  1 in total

1.  Changes in kinesiostabilogram parameters and movement speed of stroke patients while increasing their physical activity due to the use of biofeedback method.

Authors:  Victoria Zaborova; Anatoly Fesyun; Konstantin Gurevich; Alevtina Oranskaya; Alexey Rylsky; Kira Kryuchkova; Vladimir Malakhovskiy; Dmitry Shestakov
Journal:  Eur J Transl Myol       Date:  2021-10-01
  1 in total

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