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Home Health Care Management & Practice

Survival Analysis and Factors Associated With Mortality Among Elderly in a Homecare Program in Brazil Natalia Aquaroni Ricci, Renata Cereda Cordeiro, Naira Dutra Lemos and Juliana Maria Gazzola Home Health Care Management Practice published online 27 October 2010 DOI: 10.1177/1084822310384695 The online version of this article can be found at:

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Survival Analysis and Factors Associated With Mortality Among Elderly in a Home Care Program

Home Health Care Management & Practice XX(X) 1­–7 © 2010 SAGE Publications Reprints and permission: DOI: 10.1177/1084822310384695

Natalia Aquaroni Ricci, MS1, Renata Cereda Cordeiro, MS1, Naira Dutra Lemos, MS1, Juliana Maria Gazzola, PhD1

Abstract Home care (HC) is directed at older people with high risk of mortality due to clinical, social, and functional vulnerability. The purpose of this study is to analyze the likelihood of survival in a 2-year follow-up of elderly in HC and determine associations between the patient outcome (death/survival) and baseline data. The medical records of 38 elderly in a HC program were analyzed with regard to sociodemographic and clinical data and by the Functional Independence Measure (FIM). After a 2-year period, the records were reanalyzed to determine the patient outcome (death/survival). To determine the mortality rate in the follow-up period, the Kaplan-Meier survival analysis model was used. The Chi square, Fisher exact tests, the Student t and Mann-Whitney tests were used to analyze associations between the baseline variables and program status. The probability of survival was 75.36% and 56.14%, after 1 and 2 years of HC follow-up, respectively. Age, gender, marital status and FIM had no influence on mortality. The elderly who died showed a shorter time of assistance in the HC program, greater number of comorbidities and skin diseases compared to the survivors. Frail and socially vulnerable elderly may benefit from early intervention that focuses on the maintenance of function and the control of clinical complications. Keywords frail elderly, homebound patients, home care services, mortality

Introduction Health care for frail elderly is an enormous challenge throughout the world. Approximately 7.0% of community-dwelling elderly are frail and this prevalence rises to 30.0% among those individuals more than 80 years old (Topinkova, 2008). Frailty is associated with a series of adverse outcomes, such as functional disability, dependence and death (Carey et al., 2008; Fried et al., 2001). A limited data exists concerning long-term interventions involving frail elderly with regard to length of survival and the reversion of or reduction in functional deterioration (Albert, Simone, Brassard, Stern, & Mayeux, 2005). Thus, when dependence has already occurred, social and health policies addressing the elderly seek to alleviate physical and emotional suffering, as well as maintain such individuals within the domiciliary and community context rather than resort to long-term care facilities (Camargos, Perpétuo, & Machado, 2005) and to increase survival without quality of life. In this context, home care (HC) is prominent among service modalities that address the growing demand of elderly individuals who need continuous care. The benefits HC provides to elderly include a welcoming physical environment,

social inclusion, increased family support, reduced health care costs and a reduction in hospital and nursing home admittance (Serra & Moraes, 2000). Information regarding the clinical and functional prognosis of the elderly is essential to the planning and decision making of agencies that provide HC, together with the health care team, family and patient (Lee, Lindquist, Segal, & Covinsky, 2006). The measures often used to detect individuals presenting greater vulnerability include data on survival rates and risk factors for mortality (Kuo, Scandrett, Dave, & Mitchell, 2004; Ramos, Simoes, & Albert, 2001). The lack of such data is the greatest hindrance to establishing preventive measures and appropriate care to frail elderly (Carey et al., 2008). Analysis of mortality among the elderly population is often the subject of studies investigating the hospital setting (Inouye et al., 1998; Saltvedt, Mo, Fayers, Kaasa, & Sletvold, 2002), the community (Hirvensalo, Rantanen, & 1

Federal University of São Paulo (UNIFESP), São Paulo, Brazil

Corresponding Author: Natalia Aquaroni Ricci, Rua Pacaembu 257/602, Sorocaba, SP 18040-710, Brazil Email:

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Home Health Care Management & Practice XX(X)

Heikkinen, 2000; Lee et al., 2006), long-term care facilities (Magaziner et al., 2005) and HC (Albert et al., 2005; Zhao, Tatara, Kuroda, & Takayama, 1993). However, the causes of mortality or illness vary between population groups. Once these factors are identified, they may be treated or modified, thereby changing the course of the illness and fatal events (Maia, Duarte, Lebrao, & Santos, 2006). Thus, in order to provide greater efficiency in HC, it is necessary to contextualize the incidence and factors that contribute toward the occurrence of mortality among the homebound elderly population. The aims of the present study were to analyze the likelihood of survival in a 2-year follow-up of elderly individuals in HC and determine possible associations between the patient outcome (death/survival) and baseline sociodemographic, clinical, and functional data.

Methods A prospective study was conducted with a 2-year follow-up for survival analysis. The study was approved by the Ethics Committee of the institution. The study was conducted in a Home Care Program for Elderly affiliated with a public university in southeastern Brazil. The program aims to care for elderly individuals who do not have the clinical and/or social capability to visit outpatient health care services on a systematic basis. The inclusion criteria for the home care program are as follows: aged 60 years-old and older; presence of chronic disease; need for caregiver for assistance in activities of daily living (ADL); not dependent on monitoring and life support equipment; and a distance of up to 8 km between the patient’s residence and the offices of the program. The program intervention consists of orientation provided to the caregiver and/or patient by the interdisciplinary team, which is composed of a physician, nurse, occupational therapist, physiotherapist, speech therapist, dentist, nutritionist, and social worker. The program also provides assistance regarding the instrumental, social, and emotional needs of caregivers in the form of monthly meetings. Data collection was conducted at the offices of the program using patients’ medical records. In October 2003 were analyzed the records of all elderly individuals in the program (n = 40), independent of the acceptance period, who had undergone the overall evaluation of the program at this time (baseline). The overall evaluation is a standardized process conducted by the program annually to control patient progress. At baseline, sociodemographic, clinical, and functional data were collected. The sociodemographic data analyzed were gender, age, marital status, and relationship to the caregiver. The clinical aspects analyzed were total period of attendance by the program (months) up to 2003, the number of associated comorbidities and clinical diagnoses of diseases. Diseases were

classified according to the chapters of the International Classification of Diseases, 10th Edition (ICD-10) Organização Mundial da Saúde, 2003. Functional capacity was assessed using the Functional Independence Measure (FIM) (Keith, Granger, Hamilton, & Sherwin, 1987; Riberto, Miyazaki, Jorge Filho, Sakamoto, & Battistella, 2001). The FIM evaluates 18 categories scored from 1 to 7 based on the classification regard to the degree of dependence in the performance of different tasks. The categories are grouped into six domains: self-care, sphincter control, mobility, locomotion, communication, and social cognition. The total score ranges from 18 to 126 points, in which lower scores denote a greater degree of dependence. Three analysis categories were stipulated for locomotion: “cane” and “walker” categories, for elderly individuals who required these gait-assistance devices, and a “bedridden” category, which consisted of patients who were unable to walk and whether they used a wheelchair pushed by others for locomotion. After 2 years (October 2005), the patient medical records were reanalyzed for the patient status (under care or death) in the program. For survival analysis, the time (month) of the occurrence of death was recorded. For the second part of the study, the medical records of patients who were excluded from HC because of the absence of a caregiver (n = 1) and/ or change of address to outside the area serviced by the program (n = 1) were not eligible. New cases included in the HC program during the follow-up period were also not eligible.

Statistical Analysis In order to determine the mortality rate in the 2-year followup period, the Kaplan-Meier survival analysis model was used, which provides the accumulated probability of survival (months). The Chi square and Fisher exact tests were used to analyze associations between the categorical variables and program status. The Student t test was used to determine associations between the quantitative variables and program status when the variable exhibited normality; and Mann-Whitney tests were used for variables that did not exhibit normal distribution. The SPSS version 10.0 computational program and Bioestat was used for these analyses. The level of significance for all statistical tests was set at 5.0%.

Results The sample consisted of 38 elderly individuals, 16 (42.1%) of whom died in the 2-year follow-up period. No significant differences were observed regarding gender, marital status and relationship to caregiver between the patients who died and those who survived (Table 1).

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Aquaroni Ricci et al. Table 1. Analysis of Sociodemographic Variables of Elderly in Home Care in Relation to Mortality Frequency N (%)

Gender Marital Status Caregiver

Fisher Exact Test*




p Value

Female Male Single Married Widowed Spouse Son/daughter Other relative Hired help

14 (87.5)   2 (12.5)   2 (12.5)   4 (25.0) 10 (62.5) 1 (6.3)   8 (50.0)   4 (25.0)

16 (66.6)   6 (33.4)   2 (9.1)   7 (31.8) 13 (59.1)   5 (22.7)   8 (36.4) 1 (4.5)


  3 (18.7)

  8 (36.4)

0.874 0.115

*Level of significance a = 0.05.

The patients who died had a mean age of 83.69 ± 7.59 years-old, whereas the survivors had a mean age of 82.69 ± 5.30 years-old; this data were not statistically significant (Student t-test, p = 0.632). A mean of 6.94 ± 2.08 comorbidities was observed among the patients who died and 5.55 ± 1.90 in the survivors; a difference that was statistically significant (Mann-Whitney test, p = 0.039). Table 2 presents the occurrence of disease based on the ICD-10 in relation to program status. No occurrences of immune disorders, blood diseases, hematopoietic organ disease or infectious/parasitic disease were observed. A statistically significant difference (p = 0.028) occurred regarding the presence of skin and/or subcutaneous diseases in relation to program status; the number of deaths was higher in individuals who presented such diseases. Among the six patients with these kinds of diseases, all presented the diagnoses of pressure ulcers. Regarding functional data, no statistically significant differences were observed in the FIM domains or the total FIM score regarding mortality and survival in the program (Table 3). Among the patients who died, 56.2% were bedridden, 25.0% used a cane and 18.8% a walker. No statistically significant differences (p = 0.640) in these factors were observed in relation to the survivors, 40.9% of whom were bedridden, 31.8% used a cane, and 27.3% a walker. Mean time assistance in the program among the patients who died was 37.19 ± 16.98 months, whereas survivors was 47.73 ± 15.85 months; a difference statistically significant (Mann-Whitney test, p = 0.050). Table 4 and Figure 1 display the survival analysis using the Kaplan-Meier estimator for the 38 elderly individuals in home care during the 24-month follow-up period. After 6 months of follow-up, the accumulated probability of survival was 91.89%. This probability dropped to 75.36% after 1 year and 56.14% at 2 years.

Discussion Disability, comorbidity, and frailty are strongly interrelated because of the accumulation of negative events that lead to the emergence of these conditions (Topinkova, 2008). These terms are different constructs, but their manifestations can occur concomitantly in elderly individuals. Disability is described as a limitation in daily activities. Comorbidity is characterized by the presence of two or more associated chronic diseases. Frailty is defined as a state of vulnerability to stressors resulting from a reduction in physiological reserves and dysregulation of multiple systems (Fried, Ferruci, Darer, Williamson, & Anderson, 2004). The sample of the present study exhibited these three conceptual entities, as shown by the presence of more than five associated diseases, FIM scores indicative of assistance in half of the tasks, the high number of bedridden individuals, the need for assistance from multiple health care professionals for a prolonged period of time, restriction to the residential environment and the presence of full-time caregivers. The criteria proposed by Fried et al. (2004) to determine frailty is the most used for research, however requires the patient a certain cognitive level in order to respond to commands and physical capacity for the execution of the tests. Since these requirements were incompatible with the conditions of the patients enrolled in the program, it was not possible to use these criteria. However, this fact does not discharacterize the vulnerability status of the sample. The identification of predictive factors for mortality by evaluations performed in the clinical routine and by any member of the multiprofessional team rather than the use of biochemical and imaging exams reduces costs and facilitates the early detection of complications and deterioration (Ramos et al., 2001). Even more relevant is the fact that efforts at identifying the cause of death from a single pathological process are inadequate when dealing with elderly patients (Lee, Go, Lindquist, Bertenthal, & Covinsky, 2008). For elderly individuals who fulfill the frailty criteria at baseline, mortality in a 3-year period is sixfold greater than among those who do not present this state and threefold greater when considering a period of 7 years (Fried et al., 2001). In the present sample, the likelihood of survival was reduced by half after 2 years. These data reveal the need for preventive interventions concerning deterioration in the health of frail elderly more than efforts at prolonging a life without quality and even avoiding death itself (Maia et al., 2006). Among younger individuals, diseases are more strongly linked to mortality than functional limitations. This pattern is the opposite of that observed in the elderly population, in which functional capacity is a strong predictor (Lee et al., 2008). In an epidemiological study by Ramos et al. (2001) carried out in the same region as in the present study, functional difficulty, cognitive impairment, and hospitalization

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Home Health Care Management & Practice XX(X)

Table 2. Analysis of Frequency of Disease Among Elderly in Home Care in Relation to Mortality Frequency N (%)

Skin and/or subcutaneous tissue diseases Circulatory system diseases Digestive system diseases Genitourinary system diseases Respiratory system diseases Diseases of the eyes and related parts Diseases of the inner ear and mastoid apophysis Nervous system diseases Osteomuscular system and/or conjunctive tissue diseases Endocrine, nutritional and/or metabolic diseases Neoplasms Mental and behavioral disorders



p Value

  5 (31.2) 14 (87.5)   7 (43.7)   4 (25.0)   2 (12.5)   4 (25.0) —   6 (37.5) 14 (87.5) 10 (62.5) 1 (6.2) 12 (75.0)

1 (4.5) 16 (72.7)   7 (31.8)   8 (36.4) 1 (4.5)   5 (22.7) 2 (9.1) 10 (45.5) 17 (77.3)   9 (40.9) — 19 (86.3)

0.028a 0.276a 0.458b 0.463a 0.376a 0.872a 0.221a 0.455b 0.428a 0.195b 0.241a 0.379a

*Level of significance a = 0.05. a. Fisher exact test. b. Chi square test.

Table 3. Analysis of Scores on FIM Domains Among Elderly in Home Care in Relation to Mortality Mean and standard deviation

Self-care Sphincter control Mobility Locomotion Communication Social cognition Total FIM

Mann-Whitney Test*

Variation in Score




6 – 42 2 – 14 3 – 15 2 – 14 2 – 14 3 – 15 18 – 126

23.38 ± 2.99   6.50 ± 1.22   9.81 ± 1.71   4.94 ± 0.81   8.63 ± 1.17   10.0 ± 1.58 63.31 ± 8.53

24.41 ± 2.49   7.23 ± 0.96 12.06 ± 1.51   5.82 ± 0.70   8.95 ± 0.84 10.09 ± 1.13 68.64 ± 6.93

0.778 0.475 0.444 0.356 0.953 0.800 0.690

*Level of significance a = 0.05.

were strong predictors of death in a cohort of communitydwelling elderly over a 2-year follow-up period. Lee et al. (2008) found that functional capacity was strongly predictive of mortality in community-dwelling elderly over a 7-year follow-up period. The present study revealed a pattern that disagreed with the above-cited literature, since comorbidity, rather than functional capacity, was associated with mortality. Managing the degree of dependence is one of the central goals of the HC program investigated here. Since all the patients benefited from HC at baseline, with variation only in the duration of care; and the interventions are directed toward maintaining the greatest possible degree of independence, as determined by the individual functional prognosis, the strength of the association between functional incapacity and mortality may have been reduced. Functional decline in programs with the characteristics described in the present study may be slowed down by periodic multidimensional assessments aimed at detecting new risk factors in loco and initiating early intervention, thereby avoiding hospitalization and postponing the

decision for admission in a long-term care institution (Stuck, Egger, Hammer, Minder, & Beck, 2002). Another possible explanation resides in the fact that the majority of patients were bedridden. According to Maia et al. (2006), this could represent a protective factor for the risk of death, as high dependence requires a greater degree of care and also protects against potentially fatal events, such as falls. However, pressure ulcers are related to high mortality rates and bedridden patients are more predisposed to such condition. Pressure ulcers represent a higher risk of death among the elderly than originally thought. Redelings, Lee, and Sorvillo (2005) analyzed death certificates in which the cause was related to pressure ulcers. Eighty percent of the cases of death associated with pressure ulcers occurred among individuals more than 75 years of age. Neurodegenerative conditions, which are quite common in HC patients, were also frequently reported on death certificates of individuals with pressure ulcers. In a population-based study conducted in Italy involving elderly individuals enrolled in HC programs, the prevalence of at least one pressure ulcer was

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Aquaroni Ricci et al. Table 4. Survival Analysis Based on Kaplan-Meier Estimator for Elderly in Home Care During a 24-Month Follow-Up Period Months Month 1 Month 2 Month 3 Month 4 Month 5 Month 6 Month 7 Month 8 Month 9 Month 10 Month 11 Month 12 Month 13 Month 14 Month 15 Month 16 Month 17 Month 18 Month 19 Month 20 Month 21 Month 22 Month 23 Month 24

Living individuals (n)

Deaths (n)

Survival until time (t) (%)

Standard error (%)

95% CI

37 37 36 35 35 35 33 33 33 32 30 29 29 27 27 27 26 26 25 23 23 22 22 22

1 0 1 1 0 0 2 0 0 1 2 1 0 2 0 0 1 0 1 2 0 1 0 0

97.30 97.30 94.59 91.89 91.89 91.89 86.32 86.32 86.32 83.62 78.05 75.36 75.36 69.78 69.78 69.77 67.09 67.09 64.41 58.81 58.81 56.13 56.13 56.13

2.67 2.67 3.72 4.49 4.49 4.49 5.69 5.69 5.69 6.12 6.86 7.13 7.13 7.62 7.62 7.62 7.78 7.78 7.92 8.16 8.16 8.22 8.22 8.22

92.07-100.0 92.07-100.0 87.31-100.0 83.10-100.0 83.10-100.0 83.10-100.0 75.18-97.47 75.18-97.47 75.18-97.47 71.64-95.61 64.60-91.50 61.38-89.34 61.38-89.34 54.84-84.71 54.84-84.71 54.84-84.71 51.83-82.35 51.83-82.35 48.88-79.93 42.81-74.81 42.81-74.81 40.03-72.24 40.03-72.24 40.03-72.24

Figure 1. Long-term survival probability based on Kaplan-Meier estimator in 24-month interval among elderly in home care

18.0%; the mortality rate among patients with pressure ulcers was 29.0%; more than twice the rate among those without such ulcers (14.0%) (Landi, Onder, Russo, & Bernabei, 2007). Even in analyses adjusted to eliminate diverse confounding variables (age, gender, living alone, incontinence, physical, cognitive, and sensory impairment), the presence of pressure ulcers had an important negative prognostic implication among frail elderly and significantly increased the risk of

death within a 1-year period (Landi et al., 2007). These results corroborate those of the present study, in which 31.2% of the elderly individuals who died had pressure ulcers. This strongly suggests that, among individuals known to be frail, the efforts of multidisciplinary teams should be directed toward the assessment of the risk of developing pressure ulcers, even for milder degrees of manifestation, as well as preventive strategies directed at minimizing morbidities associated with this pathological condition. In-home visits of a preventive nature based on a multidimensional geriatric assessment are generally effective in the prevention of death (among individuals aged 72.7-77.5 years), admission to a long-term care institution (at least five visits, with a 34% reduction in risk for nine visits or more) and functional decline (6.7% reduction for 15 visits) (Stuck et al., 2002). Elderly individuals who received a greater number of weekly HC hours also exhibited a lower risk of death (Albert et al., 2005). Corroborating these findings, the present study found that those individuals assisted by the program for a longer period of time (approximately 10 months difference) at baseline survived during the 2-year follow-up. This permitted the hypothesis that systematic follow-up by interdisciplinary health care teams focused on the prevention of disability among frail elderly for a prolonged period of time may increase the likelihood of survival. It should be stressed, however, that the characteristics of home care programs exhibit considerable variability (paid, free, formal

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Home Health Care Management & Practice XX(X)

or informal caregiver, duration of care, background of multidisciplinary team), which hinders the isolation of characteristics that may affect risk factors for mortality (Albert et al., 2005). The lack of an association with age at baseline and mortality during the follow-up may also suggest that the program had an effect on this result. In population-based studies involving community-dwelling elderly, age is often a strong risk factor for mortality during follow-up periods varying from 2 to 8 years and there is no intervention for such an event (Albert et al., 2005; Carey et al., 2008; Fried et al., 2001; Lee et al., 2006, Ramos et al., 2001; Redelings et al., 2005; Zhao et al., 1993). However, interventions directed at other factors that are equally subject to the effects of ageing, such as functional capacity, hospitalization, cognitive impairment, lifestyle, social isolation, family support, socioeconomic level, negative perception of health and certain diseases, may modify the risk of mortality and even ensure a better quality of life associated with longevity (Maia et al., 2006; Temkin-Greener et al., 2004). Regarding the influence of social support on mortality among elderly individuals with a need for prolonged care, it has previously been demonstrated that having an informal caregiver with a conjugal link to the patient represents a lower risk of death for this frail population (Temkin-Greener et al., 2004). However, data from the present study did not confirm this finding, as the relationship between caregiver and patient did not prove to be associated with mortality within the period studied. This result may be partially explained by the influence of the program on the caregivers, thereby permitting relative homogeneity due to professional orientation regarding the form of providing care. Furthermore, the program is also concerned with the emotional needs of the caregivers themselves, providing periodic meetings for the exchange of experiences and moments of interaction. One contextual factor not considered in the present study was the patient’s housing situation. Since the program admits elderly who are unable to visit traditional health care services, whether for social or physical reasons, restricting the evaluation to strictly functional aspects may have been a limitation of the study. A study carried out in Japan found that worse housing conditions, such as a lack of wheelchair access to rooms, difficulties involved in using a nonadapted bathroom or the absence of a bathroom in the home, increased the incidence of death in a 6-year period (Zhao et al., 1993). Further studies that include these environmental factors are required, as they are clearly a source of possible intervention issues with regard to HC. This pilot study introduced the factors associated with mortality in a specific HC, the power of the sample size is moderated and further investigations are needed to clarify some issues that can contribute to death. In the present study, death in the 2-year follow-up period occurred in nearly half of the elderly individuals.

However, mortality was not associated with factors such as age and functional capacity at baseline. The elderly who survived after the 2-year follow-up had been in the home care program for a longer period of time than those who died. The results of the present study suggest that frail, socially vulnerable elderly may benefit from early intervention focused on the maintenance of functional capacity and the control of clinical complications, such as disease and pressure ulcers, within individual prognostic limits. Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the authorship and/or publication of this article.

Funding The author(s) received no financial support for the research and/or authorship of this article.

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Bios Natalia Aquaroni Ricci, MS, research physiotherapist in the UNIFESP, Brazil. Renata Cereda Cordeiro, MS, physiotherapist, coordinator for Gerontology Rehabilitation at “Lar Escola São Francisco”, Department of Preventive Medicine, UNIFESP, Brazil. Naira Dutra Lemos, MS, social worker, coordinator of the Post Graduation (lato sensu) course in Gerontology, UNIFESP, Brazil. Juliana Maria Gazzola, PhD, physiotherapist, research physiotherapist in the UNIFESP and professor in the Post Graduation Program in Vestibular Rehabilitation and Social Inclusion in the Universidade Bandeirante, Brazil.

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