Limits...
Social determinants of duration of last nursing home stay at the end of life in Switzerland: a retrospective cohort study.

Hedinger D, Hämmig O, Bopp M, Swiss National Cohort Study Gro - BMC Geriatr (2015)

Bottom Line: Conversely, a high educational level, being homeowner, being married as well as a high care level at the admission time decreased the risk for longer stays.The support of elderly people at the admission time of a presumably following nursing home stay should be improved and better evaluated in order to reduce unnecessary and undesired long terminal nursing home stays.Health policy should aim at diminishing the role of situational, non-health-related factors in order to empower people to spend the last years before death according to individual needs and preferences.

View Article: PubMed Central - PubMed

Affiliation: Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001, Zurich, Switzerland. damian.hedinger@uzh.ch.

ABSTRACT

Background: Due to demographic ageing and increasing life expectancy, a growing demand for long-term nursing home care can be expected. Stays in nursing homes appear to be more socially determined than hospital stays. We therefore looked at the impact of socio-demographic and health care variables on the length of the last nursing home stay.

Methods: Nationwide individual data from nursing homes and hospitals in Switzerland were linked with census and mortality records. Gender-specific negative binomial regression models were used to analyze N = 35,739 individuals with an admission age of at least 65 years and deceased in 2007 or 2008 in a nursing home.

Results: Preceding death, men spent on average 790 days and women 1250 days in the respective nursing home. Adjusted for preceding hospitalizations, care level, cause of death and multimorbidity, a low educational level, living alone or being tenant as well as a low care level at the admission time increased the risk for longer terminal stays. Conversely, a high educational level, being homeowner, being married as well as a high care level at the admission time decreased the risk for longer stays.

Discussion: The length of the last nursing home stay before death was not only dependent on health-related factors alone, but also substantially depended on socio-demographic determinants such as educational level, homeownership or marital status. The support of elderly people at the admission time of a presumably following nursing home stay should be improved and better evaluated in order to reduce unnecessary and undesired long terminal nursing home stays.

Conclusions: Health policy should aim at diminishing the role of situational, non-health-related factors in order to empower people to spend the last years before death according to individual needs and preferences.

No MeSH data available.


Related in: MedlinePlus

Examples of two persons with the corresponding time windows of different health variables. Data source: Swiss Federal Statistical Office, MedStat, SOMED, SNC
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4591584&req=5

Fig1: Examples of two persons with the corresponding time windows of different health variables. Data source: Swiss Federal Statistical Office, MedStat, SOMED, SNC

Mentions: The independent variables were grouped into individual, familial/housing and structural/regional attributes. As control variables we included age (at the time of admission) and nationality (Swiss or foreign) as well as cause of death: malignant neoplasms (ICD 10: C00-C99), coronary heart disease (I20-I25), stroke (I60-I69), chronic obstructive pulmonary disease (COPD, J40-J47), dementia (F01, F03, G30) and all other causes combined. The care level was assessed at time of admission and can be grouped into four categories: unknown or no care needed, low (max. 40 min per day), medium (between 41 and 80 min per day) and high (more than 81 min per day). Please note that Switzerland has no homogenous care level classification for the whole country and respective information was not always complete. However, we had no alternative health variable for nursing home residents. From MedStat we derived information about multimorbidity (2+ chronic conditions), assessed from inpatient diagnoses 2–6 years before death. We defined chronic conditions using ICPC-2, of which 129 rubrics were classified as chronic conditions [26]. Additionally, we included a dummy to control for hospitalizations in the last 365 days preceding death. We used specific time windows in order to test the different impact of health indicators which are more close or more distant from death. For better understanding of our health variables, Fig. 1 presents examples of two persons with the corresponding time windows. From the 2000 census we derived the educational level according to the International Standard Classification of Education (ISCED), version 1997: no or low secondary education completed (ISCED 0–2), post-secondary non-tertiary (“medium”, ISCED 3–4), and tertiary education (“high”, ISCED 5). Also from the 2000 census we extracted information on homeownership (owner-occupier household yes vs. no) and having had children (assessed on an individual level for men and women, i.e., not necessarily the same for all couples). Marital status was assessed at the time of home admission (never married, married, widowed and divorced). Place of residence was categorized into the three main language areas of Switzerland, namely the German, French and Italian speaking parts. In order to account for geographical variation in nursing home bed availability, we included a variable with the density of nursing home beds per 100 inhabitants aged 65 years or older in 2010 on the level of 106 quite homogenous regions.Fig. 1


Social determinants of duration of last nursing home stay at the end of life in Switzerland: a retrospective cohort study.

Hedinger D, Hämmig O, Bopp M, Swiss National Cohort Study Gro - BMC Geriatr (2015)

Examples of two persons with the corresponding time windows of different health variables. Data source: Swiss Federal Statistical Office, MedStat, SOMED, SNC
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4591584&req=5

Fig1: Examples of two persons with the corresponding time windows of different health variables. Data source: Swiss Federal Statistical Office, MedStat, SOMED, SNC
Mentions: The independent variables were grouped into individual, familial/housing and structural/regional attributes. As control variables we included age (at the time of admission) and nationality (Swiss or foreign) as well as cause of death: malignant neoplasms (ICD 10: C00-C99), coronary heart disease (I20-I25), stroke (I60-I69), chronic obstructive pulmonary disease (COPD, J40-J47), dementia (F01, F03, G30) and all other causes combined. The care level was assessed at time of admission and can be grouped into four categories: unknown or no care needed, low (max. 40 min per day), medium (between 41 and 80 min per day) and high (more than 81 min per day). Please note that Switzerland has no homogenous care level classification for the whole country and respective information was not always complete. However, we had no alternative health variable for nursing home residents. From MedStat we derived information about multimorbidity (2+ chronic conditions), assessed from inpatient diagnoses 2–6 years before death. We defined chronic conditions using ICPC-2, of which 129 rubrics were classified as chronic conditions [26]. Additionally, we included a dummy to control for hospitalizations in the last 365 days preceding death. We used specific time windows in order to test the different impact of health indicators which are more close or more distant from death. For better understanding of our health variables, Fig. 1 presents examples of two persons with the corresponding time windows. From the 2000 census we derived the educational level according to the International Standard Classification of Education (ISCED), version 1997: no or low secondary education completed (ISCED 0–2), post-secondary non-tertiary (“medium”, ISCED 3–4), and tertiary education (“high”, ISCED 5). Also from the 2000 census we extracted information on homeownership (owner-occupier household yes vs. no) and having had children (assessed on an individual level for men and women, i.e., not necessarily the same for all couples). Marital status was assessed at the time of home admission (never married, married, widowed and divorced). Place of residence was categorized into the three main language areas of Switzerland, namely the German, French and Italian speaking parts. In order to account for geographical variation in nursing home bed availability, we included a variable with the density of nursing home beds per 100 inhabitants aged 65 years or older in 2010 on the level of 106 quite homogenous regions.Fig. 1

Bottom Line: Conversely, a high educational level, being homeowner, being married as well as a high care level at the admission time decreased the risk for longer stays.The support of elderly people at the admission time of a presumably following nursing home stay should be improved and better evaluated in order to reduce unnecessary and undesired long terminal nursing home stays.Health policy should aim at diminishing the role of situational, non-health-related factors in order to empower people to spend the last years before death according to individual needs and preferences.

View Article: PubMed Central - PubMed

Affiliation: Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, 8001, Zurich, Switzerland. damian.hedinger@uzh.ch.

ABSTRACT

Background: Due to demographic ageing and increasing life expectancy, a growing demand for long-term nursing home care can be expected. Stays in nursing homes appear to be more socially determined than hospital stays. We therefore looked at the impact of socio-demographic and health care variables on the length of the last nursing home stay.

Methods: Nationwide individual data from nursing homes and hospitals in Switzerland were linked with census and mortality records. Gender-specific negative binomial regression models were used to analyze N = 35,739 individuals with an admission age of at least 65 years and deceased in 2007 or 2008 in a nursing home.

Results: Preceding death, men spent on average 790 days and women 1250 days in the respective nursing home. Adjusted for preceding hospitalizations, care level, cause of death and multimorbidity, a low educational level, living alone or being tenant as well as a low care level at the admission time increased the risk for longer terminal stays. Conversely, a high educational level, being homeowner, being married as well as a high care level at the admission time decreased the risk for longer stays.

Discussion: The length of the last nursing home stay before death was not only dependent on health-related factors alone, but also substantially depended on socio-demographic determinants such as educational level, homeownership or marital status. The support of elderly people at the admission time of a presumably following nursing home stay should be improved and better evaluated in order to reduce unnecessary and undesired long terminal nursing home stays.

Conclusions: Health policy should aim at diminishing the role of situational, non-health-related factors in order to empower people to spend the last years before death according to individual needs and preferences.

No MeSH data available.


Related in: MedlinePlus