Mobile Physiological Sensor Cloud System for Long-term Care

BACKGROUND Long-term care facilities demonstrate low levels of knowledge and care for patients with delirium and are often not properly equipped with an electronic medical record system, thereby hindering systematic approaches to delirium monitoring. OBJECTIVE This study aims to develop a web-based delirium preventive application (app), with an integrated predictive model, for long-term care (LTC) facilities using artificial intelligence (AI). METHODS This methodological study was conducted to develop an app and link it with the Amazon cloud system. The app was developed based on an evidence-based literature review and the validity of the AI prediction model algorithm. Participants comprised 206 persons admitted to LTC facilities. The app was developed in 5 phases. First, through a review of evidence-based literature, risk factors for predicting delirium and non-pharmaceutical contents for preventive intervention were identified. Second, the app, consisting of several screens, was designed; this involved providing basic information, predicting the onset of delirium according to risk factors, assessing delirium, and intervening for prevention. Third, based on the existing data, predictive analysis was performed, and the algorithm developed through this was calculated at the site linked to the web through the Amazon cloud system and sent back to the app. Fourth, a pilot test using the developed app was conducted with 33 patients. Fifth, the app was finalized. RESULTS We developed the Web_DeliPREVENT_4LCF for patients of LTC facilities. This app provides information on delirium, inputs risk factors, predicts and informs the degree of delirium risk, and enables delirium measurement or delirium prevention interventions to be immediately implemented with a verified tool. CONCLUSIONS This web-based application is evidence-based and offers easy mobilization and care to patients with delirium in LTC facilities. Therefore, the use of this app improves the unrecognized of delirium and predicts the degree of delirium risk, thereby helping initiatives for delirium prevention and providing interventions. This would ultimately improve patient safety and quality of care. CLINICALTRIAL none

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Applying DEMATEL to assess TRIZ’s inventive principles for resolving contradictions in the long-term care cloud system

Industrial Management & Data Systems ◽

10.1108/imds-06-2016-0212 ◽

2017 ◽

Vol 117 (6) ◽

pp. 1244-1262 ◽

Cited By ~ 6

Author(s):

Dong-Shang Chang ◽

Shu-Ming Liu ◽

Yi-Chun Chen

Keyword(s):

Information Exchange ◽

Long Term Care ◽

Cloud System ◽

Mining System ◽

Term Care ◽

Content Type ◽

Medical Institutions ◽

The Government ◽

Complex Relationships

Purpose The purpose of this paper is to find the key innovative principles for evaluating the long-term care (LTC) cloud system by exploring contradictory and complex points in its development. Design/methodology/approach The theory of inventive problem solving (TRIZ) and the decision-making trial and evaluation laboratory (DEMATEL) approaches are integrated to resolve complex contradictions in the system. The heuristic reasoning of TRIZ is applied to obtain innovation principles for an LTC cloud mining system. However, the importance and feasibility of these innovative principles require further assessment. In this study, DEMATEL is employed to clarify the complex relationships among the principles and evaluate their key influences. Findings This paper identifies six primary contradictions and derives 25 innovative principles for the resolution of these conflicts. Further analysis confirms three key innovative principles. First, the government should consider the overall planning of the cloud system platform, followed by the participation of other medical and LTC institutions. Second, the information capability of LTC institutions should be unified by recording the pathology data of care recipients to create an information exchange system. Third, LTC institutions should act in cooperation with medical institutions to provide professional medical capabilities. Originality/value The contributions of this paper are two-fold. First, this study provides an integrated methodology integrating the TRIZ and DEMATEL approaches to resolve LTC problems. Second, this research identifies the key innovative principles for developing an LTC cloud system in Taiwan.

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Working With Resistance and Encouraging Buy-In to New Programs

Perspectives on Gerontology ◽

10.1044/gero16.1.18 ◽

2011 ◽

Vol 16 (1) ◽

pp. 18-21

Author(s):

Sara Joffe

Keyword(s):

Long Term Care ◽

Term Care ◽

Optimal Outcomes ◽

Speech Language Pathologist

In order to best meet the needs of older residents in long-term care settings, clinicians often develop programs designed to streamline and improve care. However, many individuals are reluctant to embrace change. This article will discuss strategies that the speech-language pathologist (SLP) can use to assess and address the source of resistance to new programs and thereby facilitate optimal outcomes.

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Feeding Dependency Issues in the Long-Term Care Environment

Perspectives on Swallowing and Swallowing Disorders (Dysphagia) ◽

10.1044/sasd10.1.19 ◽

2001 ◽

Vol 10 (1) ◽

pp. 19-24

Author(s):

Carol Winchester ◽

Cathy Pelletier ◽

Pete Johnson

Keyword(s):

Long Term Care ◽

Term Care ◽

Care Environment

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Communication Disordered: Program Implementation in Long-Term Care

Perspectives of the ASHA Special Interest Groups ◽

10.1044/persp1.sig15.64 ◽

2016 ◽

Vol 1 (15) ◽

pp. 64-67

Author(s):

George Barnes ◽

Joseph Salemi

Keyword(s):

Program Implementation ◽

Long Term Care ◽

Family Satisfaction ◽

Regulatory Compliance ◽

Care Staff ◽

Term Care ◽

Staff Members ◽

Change Policy

The organizational structure of long-term care (LTC) facilities often removes the rehab department from the interdisciplinary work culture, inhibiting the speech-language pathologist's (SLP's) communication with the facility administration and limiting the SLP's influence when implementing clinical programs. The SLP then is unable to change policy or monitor the actions of the care staff. When the SLP asks staff members to follow protocols not yet accepted by facility policy, staff may be unable to respond due to confusing or conflicting protocol. The SLP needs to involve members of the facility administration in the policy-making process in order to create successful clinical programs. The SLP must overcome communication barriers by understanding the needs of the administration to explain how staff compliance with clinical goals improves quality of care, regulatory compliance, and patient-family satisfaction, and has the potential to enhance revenue for the facility. By taking this approach, the SLP has a greater opportunity to increase safety, independence, and quality of life for patients who otherwise may not receive access to the appropriate services.

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