How is the quality of the patient of life affected, affects the burden of care? It is often determined using care carers. However, a paper by Jiao et al. (2025) The aim is to use a data -based approach to help in estimating care of care. They
The author uses data from the 2010-2018 Health and Retirement Survey (HRS). HRS data was selected because information on functional status including activities of daily life (ADLS;
For example, in a room, dressing, bathing, toilets, food and out of bed/exit) and daily life’s musical activities (such as IADLS; such as, manage money, taking medicines, taking groan items, preparing food, using a map, and using the phone). They use 2000 data to map ADL and IADLS in health utilities index [HUI] Mark 3; And 2002 data to ADL and IADLS to map for visual analog scale (VAS). Then, using this mapping, Adls/IADL is used to estimate HUI utilities.
Then, the authors performed the regression analysis to examine the relationship between the time of informal care and the recipients of Care Recruitors. Result variables, informal care time. Not only family members, but also friends, or other non -profit carers were among the informal carers. For each respondent and survey year, the authors calculated the total monthly hours of informal care provided by all carers. More especially, 6 models were developed on how utilities were measured: (1), (2) ADL with HUI, (3) HUI ADL and IADL, (4) Vas Alone, (5) ADL with Vas, and (6) ADL and IADL with VAS.
If you read the entire paper, you will be able to see that as long as you have the following information, you can predict the time of care:
- Utility (HUI/VAS, optionally ADL/IADL)
- age
- gender
- Race
- Education
- Money quintal
- Urban/rural status
- Did the patient receive formal care
Perhaps most auxiliary, paper has a table that explains how to apply this algorithm in cost effectiveness analysis or other modeling approaches.
You can read full paper Here,
