Impacting healthcare outcomes: Connecting digital health within the Veteran's Health Administration Home-Based Primary Care (HBPC) program

Campbell, Colleen; Besselli, Carmen

doi:10.1016/b978-0-12-819008-1.00004-3

Cited by 3 publications

(1 citation statement)

References 54 publications

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“…Campbell & Besselli [9] defined "digital healthcare" as the use of digital technologies to gather, share, and analyze data on health and wellness, which helps improve people's health and raise the standard of healthcare.…”

Section: Introductionmentioning

confidence: 99%

Ethics of Digital Health in Islamic Perspective

Gamon

2023

JST

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Promoting digital health has the potential to significantly enhance healthcare delivery and improve the overall health of the populations. However, it raises ethical concerns such as the breach of personal privacy, risk of misdiagnosis to a larger group of population and potential bias to certain population. Technology should be used in a way to that promotes the well-being of patients and not to be used to exploit or manipulate people. Respect for individual dignity and autonomy, the promotion of social justice, ensuring patient safety and the appropriate use of technology are all ethical values that apply to digital health ethics from an Islamic perspective. These guidelines can direct the creation and application of digital health technologies in a morally righteous manner that enhances the welfare of people and communities.

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Section: Introductionmentioning

confidence: 99%

Ethics of Digital Health in Islamic Perspective

Gamon

2023

JST

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Machine learning-based analysis of multiple simultaneous disturbances applied on a transmission-reflection analysis based distributed sensor using a nanoparticle-doped fiber

et al. 2023

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Photonic technology combined with artificial intelligence plays a key role in the development of the latest smart system trends, integrating cutting-edge technology with machine learning models. This paper proposes a transmission-reflection analysis based system using dielectric nanoparticle-doped fiber combined with artificial intelligence to address one of the major problems in the distributed sensing approach: reducing the cost while maintaining high spatial resolution to close the gap between distributed sensors and the general public. Machine learning-based models are designed to classify the perturbed positions when the same force is used and force regression when different forces are applied on each position. The results show an accuracy of 99.43% in the position classification of multiple disturbances and an rms error of 1.53 N in the force regression, which represents 5% of the force range. In addition, a smart environment using the current system is proposed, which presented 100% accuracy in identifying the positions of different persons in the environment. This smart environment enables remote home care of patients with high reliability, intelligent decision-making, and a predictive capability.

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Clinical Effectiveness and Cost-effectiveness of Videoconference-Based Integrated Cognitive Behavioral Therapy for Chronic Pain: Randomized Controlled Trial (Preprint)

Taguchi¹,

Numata²,

Takanashi³

et al. 2021

Preprint

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BACKGROUND Cognitive behavioral therapy is known to improve the management of chronic pain. However, the components of this therapy are still being investigated and debated. OBJECTIVE This study aimed to examine the effectiveness of an integrated cognitive behavioral therapy program with new components (attention-shift, memory work, video feedback, and image training) delivered via videoconferencing. METHODS This study was unblinded and participants were recruited and assessed face-to-face in the outpatient department. We conducted a randomized controlled trial for chronic pain to compare 16 weekly videoconference-based cognitive behavioral therapy (vCBT) sessions provided by a therapist with treatment as usual (TAU). Thirty patients (age range, 22-75 years) with chronic pain were randomly assigned to either vCBT (n=15) or TAU (n=15). Patients were evaluated at week 1 (baseline), week 8 (midintervention), and week 16 (postintervention). The primary outcome was the change in pain intensity, which was recorded using the numerical rating scale at 16 weeks from the baseline. Secondary outcomes were pain severity and pain interference, which were assessed using the Brief Pain Inventory. Additionally, we evaluated disability, pain catastrophizing cognition, depression, anxiety, quality of life, and cost utility. RESULTS In the eligibility assessment, 30 patients were eventually randomized and enrolled; finally, 15 patients in the vCBT and 14 patients in the TAU group were analyzed. Although no significant difference was found between the 2 groups in terms of changes in pain intensity by the numerical rating scale scores at week 16 from baseline (P=.36), there was a significant improvement in the comprehensive evaluation of pain by total score of Brief Pain Inventory (–1.43, 95% CI –2.49 to –0.37, df=24; P=.01). Further, significant improvement was seen in pain interference by using the Brief Pain Inventory (–9.42, 95% CI –14.47 to –4.36, df=25; P=.001) and in disability by using the Pain Disability Assessment Scale (–1.95, 95% CI –3.33 to –0.56, df=24; P=.008) compared with TAU. As for the Medical Economic Evaluation, the incremental cost-effectiveness ratio for 1 year was estimated at 2.9 million yen (about US $25,000) per quality-adjusted life year gained. CONCLUSIONS The findings of our study suggest that integrated cognitive behavioral therapy delivered by videoconferencing in regular medical care may reduce pain interference but not pain intensity. Further, this treatment method may be cost-effective, although this needs to be further verified using a larger sample size. CLINICALTRIAL University Hospital Medical Information Network UMIN000031124; https://tinyurl.com/2pr3xszb

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Impacting healthcare outcomes: Connecting digital health within the Veteran's Health Administration Home-Based Primary Care (HBPC) program

Cited by 3 publications

References 54 publications

Ethics of Digital Health in Islamic Perspective

Ethics of Digital Health in Islamic Perspective

Machine learning-based analysis of multiple simultaneous disturbances applied on a transmission-reflection analysis based distributed sensor using a nanoparticle-doped fiber

Clinical Effectiveness and Cost-effectiveness of Videoconference-Based Integrated Cognitive Behavioral Therapy for Chronic Pain: Randomized Controlled Trial (Preprint)

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