Home Health Smart TVBringing E-Health Closer to Elders

Author(s):  
Ronald Buyl ◽  
Marcin Zaremba ◽  
Marc Nyssen ◽  
Sandrine Kaze ◽  
Adrianna Nizinska ◽  
...  
Keyword(s):  
2020 ◽  
Author(s):  
Abdulaziz A Alodhayani ◽  
Marwah Mazen Hassounah ◽  
Fatima R Qadri ◽  
Noura A Abouammoh ◽  
Zakiuddin Ahmed ◽  
...  

BACKGROUND There is growing evidence of the need to consider cultural factors in the design and implementation of digital health interventions. However, there is still inadequate knowledge pertaining to what aspects of the Saudi Arabian culture need to be considered in the design and implementation of digital health programs, especially in the context of home health care services for chronically and terminally ill patients. OBJECTIVE This study aims to explore the specific cultural factors relating to patients and their caregivers from the perspective of physicians, nurses, and trainers that have influenced the pilot implementation of Remotely Accessible Healthcare At Home (RAHAH); a connected health program in the Home Health Care Department at King Saud University Medical City, Riyadh, Saudi Arabia. METHODS A qualitative study design was adopted to conduct a focus group discussion (FGD) in July 2019 using a semi-structured interview guide with 3 female and 4 male participants working as nurses, family physicians, and information technologists. Qualitative data obtained were analyzed using a thematic framework analysis. RESULTS Two categories emerged from the FGD that influenced the experiences of digital health program intervention: (1) culture-related factors including language and communication, cultural views on using cameras during consultation, non-adherence to online consultations, and family role and commitment (2) caregiver characteristics in telemedicine that includes their skills and education and electronic literacy. Participants of this study revealed that indirect contact with the patients and their family members may work as a barrier to proper communication through RAHAH. CONCLUSIONS We recommend exploring the use of interpreters in digital health, creating awareness among the local population regarding privacy in digital health, and actively involving the direct family members with the healthcare providers.


2019 ◽  
Vol 7 (4) ◽  
pp. 561-569
Author(s):  
Jo-Ana D Chase ◽  
David Russell ◽  
Meridith Rice ◽  
Carmen Abbott ◽  
Kathryn H Bowles ◽  
...  

Background: Post-acute home health-care (HHC) services provide a unique opportunity to train and support family caregivers of older adults returning home after a hospitalization. To enhance family-focused training and support strategies, we must first understand caregivers’ experiences. Objective: To explore caregivers’ experiences regarding training and support for managing older adults’ physical functioning (PF) needs in the post-acute HHC setting. Method: We conducted a qualitative descriptive study using semi-structured telephone interviews of 20 family caregivers. Interviews were recorded, transcribed, and analyzed using conventional content analysis. Results: We identified the following primary categories: facilitators to learning (eg, past experience, learning methods), barriers to learning (eg, learning on their own, communication, timing/logistics, preferred information and timing of information delivery), and interactions with HHC providers (eg, positive/negative interactions, provider training and knowledge). Conclusion: Caregivers were responsive to learning strategies to manage older adults’ PF needs and, importantly, voiced ideas to improve family-focused training and support. HHC providers can use these findings to tailor training and support of family caregivers in the post-acute HHC setting.


2021 ◽  
pp. 108482232199038
Author(s):  
Elizabeth Plummer ◽  
William F. Wempe

Beginning January 1, 2020, Medicare’s Patient-Driven Groupings Model (PDGM) eliminated therapy as a direct determinant of Home Health Agencies’ (HHAs’) reimbursements. Instead, PDGM advances Medicare’s shift toward value-based payment models by directly linking HHAs’ reimbursements to patients’ medical conditions. We use 3 publicly-available datasets and ordered logistic regression to examine the associations between HHAs’ pre-PDGM provision of therapy and their other agency, patient, and quality characteristics. Our study therefore provides evidence on PDGM’s likely effects on HHA reimbursements assuming current patient populations and service levels do not change. We find that PDGM will likely increase payments to rural and facility-based HHAs, as well as HHAs serving greater proportions of non-white, dual-eligible, and seriously ill patients. Payments will also increase for HHAs scoring higher on quality surveys, but decrease for HHAs with higher outcome and process quality scores. We also use ordinary least squares regression to examine residual variation in HHAs’ expected reimbursement changes under PDGM, after accounting for any expected changes related to their pre-PDGM levels of therapy provision. We find that larger and rural HHAs will likely experience residual payment increases under PDGM, as will HHAs with greater numbers of seriously ill, younger, and non-white patients. HHAs with higher process quality, but lower outcome quality, will similarly benefit from PDGM. Understanding how PDGM affects HHAs is crucial as policymakers seek ways to increase equitable access to safe and affordable non-facility-provided healthcare that provides appropriate levels of therapy, nursing, and other care.


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