Intrinsic Capacitiy monitoring by digital biomarkers in Integrated Care for Older People (ICOPE)

2020 ◽  
pp. 1-7
Author(s):  
A. Piau ◽  
Z. Steinmeyer ◽  
M. Cesari ◽  
J. Kornfeld ◽  
Z. Beattie ◽  
...  
Keyword(s):  
Health Status ◽  
Action Plan ◽  
Real Life ◽  
Clinical Practices ◽  
Related Data ◽  
Monitoring Tools ◽  
Health Related ◽  
Status Assessment ◽  
Transient Events ◽  
Digital Biomarkers

The WHO action plan on aging expects to change current clinical practices by promoting a more personalized model of medicine. To widely promote this initiative and achieve this goal, healthcare professionals need innovative monitoring tools. Use of conventional biomarkers (clinical, biological or imaging) provides a health status assessment at a given time once a capacity has declined. As a complement, continuous monitoring thanks to digital biomarkers makes it possible to remotely collect and analyze real life, ecologically valid, and continuous health related data. A seamless assessment of the patient’s health status potentially enables early diagnosis of IC decline (e.g. sub-clinical or transient events not detectable by episodic evaluations) and investigation of its probable causes. This narrative review aims to develop the concept of digital biomarkers and its implementation in IC monitoring.

scholarly journals All Our Data Will Be Health Data One Day: The Need for Universal Data Protection and Comprehensive Consent

10.2196/16879 ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. e16879 ◽  
Author(s):  
Christophe Olivier Schneble ◽  
Bernice Simone Elger ◽  
David Martin Shaw
Keyword(s):  
Health Status ◽  
Data Protection ◽  
Health Data ◽  
Future Health ◽  
Related Data ◽  
Legal Implications ◽  
Health Related ◽  
Behavior Health

Tremendous growth in the types of data that are collected and their interlinkage are enabling more predictions of individuals’ behavior, health status, and diseases. Legislation in many countries treats health-related data as a special sensitive kind of data. Today’s massive linkage of data, however, could transform “nonhealth” data into sensitive health data. In this paper, we argue that the notion of health data should be broadened and should also take into account past and future health data and indirect, inferred, and invisible health data. We also lay out the ethical and legal implications of our model.

scholarly journals All Our Data Will Be Health Data One Day: The Need for Universal Data Protection and Comprehensive Consent (Preprint)

2019 ◽  
Author(s):  
Christophe Olivier Schneble ◽  
Bernice Simone Elger ◽  
David Martin Shaw
Keyword(s):  
Health Status ◽  
Data Protection ◽  
Health Data ◽  
Future Health ◽  
Related Data ◽  
Legal Implications ◽  
Health Related ◽  
Behavior Health

UNSTRUCTURED Tremendous growth in the types of data that are collected and their interlinkage are enabling more predictions of individuals’ behavior, health status, and diseases. Legislation in many countries treats health-related data as a special sensitive kind of data. Today’s massive linkage of data, however, could transform “nonhealth” data into sensitive health data. In this paper, we argue that the notion of health data should be broadened and should also take into account past and future health data and indirect, inferred, and invisible health data. We also lay out the ethical and legal implications of our model.

On-farm udder health monitoring

2011 ◽  
Vol 39 (02) ◽  
pp. 95-100
Author(s):  
J. C. van Veersen ◽  
O. Sampimon ◽  
R. G. Olde Riekerink ◽  
T. J. G. Lam
Keyword(s):  
Management Practices ◽  
Health Management ◽  
Action Plan ◽  
Real Life ◽  
Health Data ◽  
Control Points ◽  
Udder Health ◽  
Critical Control Points ◽  
On Farm ◽  
Clinical Problems

SummaryIn this article an on-farm monitoring approach on udder health is presented. Monitoring of udder health consists of regular collection and analysis of data and of the regular evaluation of management practices. The ultimate goal is to manage critical control points in udder health management, such as hygiene, body condition, teat ends and treatments, in such a way that results (udder health parameters) are always optimal. Mastitis, however, is a multifactorial disease, and in real life it is not possible to fully prevent all mastitis problems. Therefore udder health data are also monitored with the goal to pick up deviations before they lead to (clinical) problems. By quantifying udder health data and management, a farm is approached as a business, with much attention for efficiency, thought over processes, clear agreements and goals, and including evaluation of processes and results. The whole approach starts with setting SMART (Specific, Measurable, Acceptable, Realistic, Time-bound) goals, followed by an action plan to realize these goals.

Mental Health Status and Health-Related Quality of Life among Systemic Lupus Erythematosus (SLE) Patients in Thailand: A Multi-Site Study

2020 ◽  
Vol 103 (11) ◽  
pp. 1185-1193
Keyword(s):  
Quality Of Life ◽  
Mental Health ◽  
Health Status ◽  
Lupus Erythematosus ◽  
Self Esteem ◽  
Mental Health Status ◽  
Health Related Quality ◽  
Related Quality ◽  
Health Related

Background: The systemic lupus erythematosus (SLE) patients oftentimes suffer from both physical and psychosocial challenges that may lead to low health-related quality of life (HRQoL). However, limited research has been done in this area. Objective: To examined mental health status and HRQoL among SLE patients in Thailand. Materials and Methods: The present study was a cross-sectional study conducted at the rheumatology clinic of four major hospitals in Thailand. The paper-based questionnaire consisted of demographic, health history such as depression, anxiety, stress Scale (DASS-21), and the Rosenberg self-esteem scale (RSE), and the disease-specific Lupus Quality of Life scale (LupusQoL). Depending on the variable’s level of measurement such as categorical or continuous, Spearman’s Rho or Pearson’s product moment correlation coefficients were used to explore the relationships among the variables. Hierarchical multiple regression was used to identify the predictors of LupusQoL. Results: Among the 387 participants, many might have experienced depression, anxiety, and stress (30%, 51%, and 29%, respectively). Self-esteem among the participants was good (31.8 out of 40). All eight domains of LupusQoL were affected with intimate relationship domain being impacted the most. The overall LupusQoL was significantly associated with the number of prescribed medications (r=–0.23), depression (r=–0.70), anxiety (r=–0.58), stress (r=–0.67), and self-esteem (r=0.59), p<0.001. Significant predictors of the overall LupusQoL were mental health status (depression, anxiety, and stress) and self-esteem, F (3, 81)=43.10, p<0.001, adjusted R²=0.60. Conclusion: SLE patients should be holistically assessed in both physical and psychological aspects. In addition to proper medical treatments, healthcare providers should use a multidisciplinary team approach to resolve the patients’ psychosocial issues, which in turn, may increase the patients’ quality of life. Self-care education may be necessary to help the patients manage the condition and decrease the number of medications. Keywords: Mental health, Quality of life, SLE, Thailand

Novel Visualization of Large Health Related Data Sets

2015 ◽  
Author(s):  
William E. Hammond ◽  
Vivian L. West ◽  
David Borland ◽  
Igor Akushevich ◽  
Eugenia M. Heinz
Keyword(s):  
Data Sets ◽  
Related Data ◽  
Health Related
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