A healthcare integration system for disease assessment and safety monitoring of dementia patients.
Elderly dementia patients often get lost due to lack of a sense of direction. This may put them at risk and cause their families much worry. The goal of this study is to use information technology to enhance the professional judgment of caregivers, strengthen internal safety monitoring at care organizations, and improve the quality of care for dementia patients. An eXtensible-Markup-Language-based dementia assessment system combining program code and assessment content is used to provide caregivers with better flexibility and real-time response ability. Beyond establishing long-term case files, the system can also perform data consistency analysis, strengthen caregivers' continuing education, improve caregivers' case judgment skills, and reduce the incidence of accidents due to neglect. This study also applies radio frequency identification (RFID) technology to the development of an indoor and outdoor active safety monitoring mechanism. The system can automatically remind caregivers whenever an elderly person approaches a dangerous area or strays too far. Apart from the use of different size tags, the realization of the system also employs the tame transformation signatures (TTS) algorithm to encrypt tag IDs and protect personal privacy. Clinical testing of the system showed that the indoor RFID reader has a response time of 0.5 s when sensing 40 tags, while the outdoor reader has a sensing time of approximately 5 s due to the need to save power. In the latter case, the system can ensure that elderly patients stay less than 15 m away from their caregivers. Patients were relatively willing to wear light tags. We also found that irritable patients with strong mobility were less compliant and often removed their own tags. Caregivers must provide active care and adopt various safety measures to protect the type of patients.
Lin
Chung-Chih
CC
Department of Computer Science and Information Engineering, Center for Healthy Aging Research, Chang Gung University (CGU), Kwei-Shan 333, Taiwan, ROC. cclin@mail.cgu.edu.tw
Lin
Ping-Yeh
PY
Lu
Po-Kuan
PK
Hsieh
Guan-Yu
GY
Lee
Wei-Lun
WL
Lee
Ren-Guey
RG
D020000:Decision Support Systems, Clinical; D019033:Delivery of Health Care, Integrated / Q000379:methods*; D003704:Dementia / Q000175:diagnosis* / Q000451:nursing*; D008991:Monitoring, Physiologic / Q000379:methods*; D017751:Safety Management / Q000379:methods*; D013624:Taiwan; D017216:Telemedicine / Q000379:methods*