Healthcare utilisation in the last year of life in internal medicine, young-old versus old-old

Abstract

Background With increasing cost of healthcare in our aging society, a consistent pain point is that of end-of-life care. It is particularly difficult to prognosticate in non-cancer patients, leading to more healthcare utilisation without improving quality of life. Additionally, older adults do not age homogenously. Hence, we seek to characterise healthcare utilisation in young-old and old-old at the end-of-life. Methods We conducted a single-site retrospective review of decedents under department of Advanced Internal Medicine (AIM) over a year. Young-old is defined as 65–79 years; old-old as 80 years and above. Data collected was demographic characteristics; clinical data including Charlson Comorbidity Index (CCI), FRAIL-NH and advance care planning (ACP); healthcare utilisation including days spent in hospital, hospital admissions, length of stay of terminal admission and clinic visits; and quality of end-of-life care including investigations and symptomatic control. Documentation was individually reviewed for quality of communication. Results One hundred eighty-nine older adult decedents. Old-old decedents were mostly females (63% vs. 42%, p = 0.004), higher CCI scores (7.7 vs 6.6, p = 0.007), similarly frail with lower polypharmacy (62.9% vs 71.9%, p = 0.01). ACP uptake was low in both, old-old 15.9% vs. young-old 17.5%. Poor prognosis was conveyed to family, though conversation did not result in moderating extent of care. Old-old had less healthcare utilisation. Adjusting for sex, multimorbidity and frailty, old-old decedents had 7.3 ± 3.5 less hospital days in their final year. Further adjusting for cognition and residence, old-old had 0.5 ± 0.3 less hospital admissions. When accounted for home care services, old-old spent 2.7 ± 0.8 less hospital days in their last admission. Conclusion There was high healthcare utilisation in older adults, but especially young-old. Enhanced education and goal-setting are needed in the acute care setting. ACP needs to be reinforced in acute care with further research to evaluate if it reduces unnecessary utilisation at end-of-life.

The FRAIL-NH Scale: Systematic Review of the Use, Validity and Adaptations for Frailty Screening in Nursing Homes

“…The FRAIL-NH scale was applied in studies across 20 countries; the majority in Australia (n=14) ( 21 – 34 ), followed by China (n=6) ( 35 – 40 ), Spain (n=3) ( 41 – 43 ), United States (US) (n=3) ( 44 – 46 ), Brazil (n=2) ( 47 , 48 ), Japan (n=2) ( 49 , 50 ), Singapore (n=2) ( 51 , 52 ), Belgium (n=1) ( 53 ), Canada (n=1) ( 54 ), England (n=1) ( 50 ), Europe and Israel (n=1) ( 55 ), France (n=1) ( 56 ), Hong Kong (n=1) ( 57 ), Italy (n=1) ( 58 ), South Korea (n=1) ( 59 ), and Taiwan (n=1) ( 60 ). One study was an international multicenter study based on data from the Services and Health for Elderly in Long TERm care (SHELTER) study, conducted in 8 countries including Czech Republic, England, Finland, France, Germany, Israel, Italy, and the Netherlands ( 55 ).…”

“…Conversely, among non-users of statins, fall-related hospitalizations were lowest in the frailest subset ( 26 ). Five studies reported contrasting outcomes whereby FRAIL-NH scores did not predict falls ( 53 ), hospitalization ( 44 , 51 ), and mortality ( 41 , 53 ).…”

“…Cross-sectional associations with frailty were not investigated in seven studies ( 24 , 36 – 38 , 40 , 48 , 54 ), therefore criteria related to confounding factors were not assessed in these studies. Residents with different frailty status were recruited from the same population, free of outcomes at the start of study, and follow-up time was reported in all 14 outcome studies (Table S4) ( 25 , 26 , 30 , 39 , 41 , 44 , 47 , 51 – 53 , 56 – 59 ). Confounding factors were identified and adjusted for in 13 outcome studies ( 25 , 26 , 30 , 39 , 44 , 47 , 51 – 53 , 56 – 59 ).…”

“…Residents with different frailty status were recruited from the same population, free of outcomes at the start of study, and follow-up time was reported in all 14 outcome studies (Table S4) ( 25 , 26 , 30 , 39 , 41 , 44 , 47 , 51 – 53 , 56 – 59 ). Confounding factors were identified and adjusted for in 13 outcome studies ( 25 , 26 , 30 , 39 , 44 , 47 , 51 – 53 , 56 – 59 ). Overall, two studies did not provide adequate information on how FRAIL-NH was computed, which precluded assessment on whether the measurement was valid ( 48 , 53 ).…”

Antioxidant Effect of Lactobacillus fermentum CQPC04-Fermented Soy Milk on D-Galactose-Induced Oxidative Aging Mice

“…The United Nations (UN) predicted that there would be an average annual increase rate of 2.5% in the elderly population from 1990 to 2020, and over the same period, the proportion of the world's aging population has risen from 6.6% in 1995 to 9.3% in 2020 (1). Aging causes a decline in physical function, but also can induce a variety of diseases, such as diabetes, osteoarthritis, cataracts, and cancer (2).…”