Demand analysis of an intelligent medication administration system for older adults with chronic diseases based on the Kano model

Abstract Recent research has documented increasing education inequality in life expectancy among U.S. adults; however, much is unknown about other health status changes. The objective of study is to assess how healthy and unhealthy life expectancies, as classified by common chronic diseases, has changed for older adults across education groups. Data come from the Health and Retirement Study and National Vital Statistics. We created prevalence-based life tables using the Sullivan method to assess sex-specific life expectancies for stroke, heart disease, cancer, and arthritis by education group. In general, unhealthy life expectancy increased with each condition across education groups. However, the increases in unhealthy life expectancy varied greatly. While stroke increased by half a year across education groups, life expectancy with diabetes increased by 3 to 4 years. In contrast, the evidence for healthy life expectancy provides mixed results. Across chronic diseases, healthy life expectancy decreased by 1 to 3 years for respondents without a 4-year degree. Conversely, healthy life expectancy increased for the college educated by .5 to 3 years. While previous research shows increases in life expectancy for the most educated, trends in life expectancy with chronic conditions is less positive: not all additional years are in lived in good health. In addition to documenting life expectancy changes across education groups, research assessing health of older adults should consider the changing inequality across a variety of health conditions, which will have broad implications for population aging and policy intervention.

Download Full-text

Source of Purchased Medications and Its Impact on Medication Mistakes and Hospitalizations: The NHATS 2017

Innovation in Aging ◽

10.1093/geroni/igaa057.2875 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 793-793

Author(s):

Martha Coates ◽

Janeway Granche ◽

Rose Ann DiMaria-Ghalili

Keyword(s):

Older Adults ◽

Hospital Stay ◽

Chronic Diseases ◽

Community Dwelling ◽

Hospital Stays ◽

Related Harm

Abstract Older adults self-administer prescribed medication regimens to treat chronic diseases which can lead to mismanagement, medication related harm and hospitalizations. We examined the extent to which source of purchased medications influenced the occurrence of self-reported medication mistakes and hospitalizations in community-dwelling participants who managed medications independently (N= 3899). The majority (65%) picked-up medications, 18% had medications delivered, and 17% used both (picked-up and delivery). Compared to those picking up their medications, those using delivery only were less likely to have a hospital stay (OR=0.691 [95% CI 0.507-0.943]) and no difference in odds of medication mistakes (OR=1.051 [95% CI 0.764-1.445]), while those using both methods were more likely to report hospital stays (OR=1.429 [95% CI 1.106-1.846]) and medication mistakes (OR = 1.576[95% CI 1.078-2.304]). Older adults who picked-up medications from a local pharmacy and had medications delivered were more likely to report medication mistakes and hospitalizations.

Download Full-text

The ‘loneliness pandemic’: implications for gerontological nursing

British Journal of Nursing ◽

10.12968/bjon.2021.30.11.652 ◽

2021 ◽

Vol 30 (11) ◽

pp. 652-655

Author(s):

Carlos Laranjeira

Keyword(s):

Mental Health ◽

Older Adults ◽

Older People ◽

Chronic Diseases ◽

Old Age ◽

Social Isolation ◽

Social Relationships ◽

Vulnerable Groups ◽

Negative Consequences ◽

Gerontological Nursing

The COVID-19 pandemic compelled states to limit free movement, in order to protect at-risk and more vulnerable groups, particularly older adults. Due to old age or debilitating chronic diseases, this group is also more vulnerable to loneliness (perceived discrepancy between actual and desired social relationships) and social isolation (feeling that one does not belong to society). This forced isolation has negative consequences for the health of older people, particularly their mental health. This is an especially challenging time for gerontological nursing, but it is also an opportunity for professionals to combat age stereotypes reinforced with COVID-19, to urge the measurement of loneliness and social isolation, and to rethink how to further adjust interventions in times of crisis, such as considering technology-mediated interventions in these uncertain times.

Download Full-text

Long-Term Effects on Loneliness of a Computer-Tailored Intervention for Older Adults With Chronic Diseases: A Randomized Controlled Trial

Journal of Aging and Health ◽

10.1177/08982643211015027 ◽

2021 ◽

pp. 089826432110150

Author(s):

Janet M. Boekhout ◽

Esmee Volders ◽

Catherine A. W. Bolman ◽

Renate H. M. de Groot ◽

Lilian Lechner

Keyword(s):

Older Adults ◽

Randomized Controlled Trial ◽

Chronic Diseases ◽

Controlled Trial ◽

Social Activity ◽

Time Frame ◽

Future Research ◽

Long Term Effects ◽

Randomized Controlled ◽

Social Loneliness

Objectives: This study explores the effects of the Active Plus intervention aiming to decrease loneliness among older adults (>65 years) with chronic diseases. Methods: A randomized controlled trial (RCT) was performed (N = 585; age: M = 74.5 years, SD = 6.4), assessing loneliness at baseline, 6 months and 12 months. Outcome measures in the multilevel linear regression analyses were total, social and emotional loneliness. Results: At 12 months, significant decreases in total ( B = −.37, p = .01) and social loneliness ( B = −.24, p = .02) were found. Age was a significant moderator for total and social loneliness; however, the intervention was effective only for participants aged 80 years and older. Discussion: The Active Plus intervention showed a significant decrease in total and social loneliness and was especially beneficial for the vulnerable age group of 80 years and older. A more comprehensive tool for measuring social activity and mobility impairments, and using a longer time frame to detect loneliness changes, may form interesting future research.

Download Full-text