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Randomized Trial of Intelligent Sensor System for Early Illness Alerts in Senior Housing.
Rantz, Marilyn; Phillips, Lorraine J; Galambos, Colleen; Lane, Kari; Alexander, Gregory L; Despins, Laurel; Koopman, Richelle J; Skubic, Marjorie; Hicks, Lanis; Miller, Steven; Craver, Andy; Harris, Bradford H; Deroche, Chelsea B.
Afiliación
  • Rantz M; Sinclair School of Nursing, University of Missouri, Columbia, MO. Electronic address: rantzm@missouri.edu.
  • Phillips LJ; Sinclair School of Nursing, University of Missouri, Columbia, MO.
  • Galambos C; School of Social Work, University of Missouri, Columbia, MO.
  • Lane K; Sinclair School of Nursing, University of Missouri, Columbia, MO.
  • Alexander GL; Sinclair School of Nursing, University of Missouri, Columbia, MO.
  • Despins L; Sinclair School of Nursing, University of Missouri, Columbia, MO.
  • Koopman RJ; Department of Family and Community Medicine, School of Medicine, University of Missouri, Columbia, MO.
  • Skubic M; Electrical and Computer Engineering, University of Missouri, Columbia, MO.
  • Hicks L; Health Management and Informatics, School of Medicine, University of Missouri, Columbia, MO.
  • Miller S; Sinclair School of Nursing, University of Missouri, Columbia, MO.
  • Craver A; Sinclair School of Nursing, University of Missouri, Columbia, MO.
  • Harris BH; Electrical and Computer Engineering, University of Missouri, Columbia, MO.
  • Deroche CB; Biostatistics & Research Design Unit, Health Management & Informatics, School of Medicine, University of Missouri, Columbia, MO.
J Am Med Dir Assoc ; 18(10): 860-870, 2017 Oct 01.
Article en En | MEDLINE | ID: mdl-28711423
ABSTRACT

OBJECTIVES:

Measure the clinical effectiveness and cost effectiveness of using sensor data from an environmentally embedded sensor system for early illness recognition. This sensor system has demonstrated in pilot studies to detect changes in function and in chronic diseases or acute illnesses on average 10 days to 2 weeks before usual assessment methods or self-reports of illness.

DESIGN:

Prospective intervention study in 13 assisted living (AL) communities of 171 residents randomly assigned to intervention (n=86) or comparison group (n=85) receiving usual care.

METHODS:

Intervention participants lived with the sensor system an average of one year. MEASUREMENTS Continuous data collected 24 hours/7 days a week from motion sensors to measure overall activity, an under mattress bed sensor to capture respiration, pulse, and restlessness as people sleep, and a gait sensor that continuously measures gait speed, stride length and time, and automatically assess for increasing fall risk as the person walks around the apartment. Continuously running computer algorithms are applied to the sensor data and send health alerts to staff when there are changes in sensor data patterns.

RESULTS:

The randomized comparison group functionally declined more rapidly than the intervention group. Walking speed and several measures from GaitRite, velocity, step length left and right, stride length left and right, and the fall risk measure of functional ambulation profile (FAP) all had clinically significant changes. The walking speed increase (worse) and velocity decline (worse) of 0.073 m/s for comparison group exceeded 0.05 m/s, a value considered to be a minimum clinically important difference. No differences were measured in health care costs.

CONCLUSIONS:

These findings demonstrate that sensor data with health alerts and fall alerts sent to AL nursing staff can be an effective strategy to detect and intervene in early signs of illness or functional decline.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Estado de Salud / Instituciones de Vida Asistida / Tecnología de Sensores Remotos Tipo de estudio: Clinical_trials / Observational_studies Límite: Female / Humans / Male Idioma: En Revista: J Am Med Dir Assoc Asunto de la revista: HISTORIA DA MEDICINA / MEDICINA Año: 2017 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Estado de Salud / Instituciones de Vida Asistida / Tecnología de Sensores Remotos Tipo de estudio: Clinical_trials / Observational_studies Límite: Female / Humans / Male Idioma: En Revista: J Am Med Dir Assoc Asunto de la revista: HISTORIA DA MEDICINA / MEDICINA Año: 2017 Tipo del documento: Article