Variation in the costs of dying and the role of different health services, socio-demographic characteristics, and preceding health care expenses

International comparison of spending and utilization at the end of life for hip fracture patients

OBJECTIVE

To identify and explore differences in spending and utilization of key health services at the end of life among hip fracture patients across seven developed countries.

DATA SOURCES

Individual-level claims data from the inpatient and outpatient health care sectors compiled by the International Collaborative on Costs, Outcomes, and Needs in Care (ICCONIC).

STUDY DESIGN

We retrospectively analyzed utilization and spending from acute hospital care, emergency department, outpatient primary care and specialty physician visits, and outpatient drugs. Patterns of spending and utilization were compared in the last 30, 90, and 180 days across Australia, Canada, England, Germany, New Zealand, Spain, and the United States. We employed linear regression models to measure age- and sex-specific effects within and across countries. In addition, we analyzed hospital-centricity, that is, the days spent in hospital and site of death.

DATA COLLECTION/EXTRACTION METHODS

We identified patients who sustained a hip fracture in 2016 and died within 12 months from date of admission.

PRINCIPAL FINDINGS

Resource use, costs, and the proportion of deaths in hospital showed large variability being high in England and Spain, while low in New Zealand. Days in hospital significantly decreased with increasing age in Canada, Germany, Spain, and the United States. Hospital spending near date of death was significantly lower for women in Canada, Germany, and the United States. The age gradient and the sex effect were less pronounced in utilization and spending of emergency care, outpatient care, and drugs.

CONCLUSIONS

Across seven countries, we find important variations in end-of-life care for patients who sustained a hip fracture, with some differences explained by sex and age. Our work sheds important insights that may help ongoing health policy discussions on equity, efficiency, and reimbursement in health care systems.

Impact of socioeconomic status on end-of-life costs: a systematic review and meta-analysis

BACKGROUND

Socioeconomic inequalities in access to, and utilization of medical care have been shown in many jurisdictions. However, the extent to which they exist at end-of-life (EOL) remains unclear.

METHODS

Studies in MEDLINE, EMBASE, CINAHL, ProQuest, Web of Science, Web of Knowledge, and OpenGrey databases were searched through December 2019 with hand-searching of in-text citations. No publication date or language limitations were set. Studies assessing SES (e.g. income) in adults, correlated to EOL costs in last year(s) or month(s) of life were selected. Two independent reviewers performed data abstraction and quality assessment, with inconsistencies resolved by consensus.

RESULTS

A total of twenty articles met eligibility criteria. Two meta-analyses were performed on studies that examined total costs in last year of life - the first examined costs without adjustments for confounders (n = 4), the second examined costs that adjusted for confounders, including comorbidities (n = 2). Among studies which did not adjust for comorbidities, SES was positively correlated with EOL costs (standardized mean difference, 0.13 [95% confidence interval, 0.03 to 0.24]). However, among studies adjusting for comorbidities, SES was inversely correlated with EOL expenditures (regression coefficient, -$150.94 [95% confidence interval, -$177.69 to -$124.19], 2015 United States Dollars (USD)). Higher ambulatory care and drug expenditure were consistently found among higher SES patients irrespective of whether or not comorbidity adjustment was employed.

CONCLUSION

Overall, an inequality leading to higher end-of-life expenditure for higher SES patients existed to varying extents, even within countries providing universal health care, with greatest differences seen for outpatient and prescription drug costs. The magnitude and directionality of the relationship in part depended on whether comorbidity risk-adjustment methodology was employed.

Clinically useful prediction of hospital admissions in an older population

Background

The healthcare for older adults is insufficient in many countries, not designed to meet their needs and is often described as disorganized and reactive. Prediction of older persons at risk of admission to hospital may be one important way for the future healthcare system to act proactively when meeting increasing needs for care. Therefore, we wanted to develop and test a clinically useful model for predicting hospital admissions of older persons based on routine healthcare data.

Methods

We used the healthcare data on 40,728 persons, 75–109 years of age to predict hospital in-ward care in a prospective cohort. Multivariable logistic regression was used to identify significant factors predictive of unplanned hospital admission. Model fitting was accomplished using forward selection. The accuracy of the prediction model was expressed as area under the receiver operating characteristic (ROC) curve, AUC.

Results

The prediction model consisting of 38 variables exhibited a good discriminative accuracy for unplanned hospital admissions over the following 12 months (AUC 0.69 [95% confidence interval, CI 0.68–0.70]) and was validated on external datasets. Clinically relevant proportions of predicted cases of 40 or 45% resulted in sensitivities of 62 and 66%, respectively. The corresponding positive predicted values (PPV) was 31 and 29%, respectively.

Conclusion

A prediction model based on routine administrative healthcare data from older persons can be used to find patients at risk of admission to hospital. Identifying the risk population can enable proactive intervention for older patients with as-yet unknown needs for healthcare.

Health and social care costs at the end of life: a matched analysis of linked patient records in East London

BACKGROUND

care in the final year of life accounts for 10% of inpatient hospital costs in UK. However, there has been little analysis of costs in other care settings. We investigated the publicly funded costs associated with the end of life across different health and social care settings.

METHOD

we performed cross-sectional analysis of linked electronic health records of residents aged over 50 in a locality in East London, UK, between 2011 and 2017. Those who died during the study period were matched to survivors on age group, sex, deprivation, number of long-term conditions and time period. Mean costs were calculated by care setting, age and months to death.

RESULTS

across 8,720 matched patients, the final year of life was associated with £7,450 (95% confidence interval £7,086-£7,842, P < 0.001) of additional health and care costs, 57% of which related to unplanned hospital care. Whilst costs increased sharply over the final few months of life in emergency and inpatient hospital care, in non-acute settings costs were less concentrated in this period. Patients who died at older ages had higher social care costs and lower healthcare costs than younger patients in their final year of life.

CONCLUSIONS

the large proportion of costs relating to unplanned hospital care suggests that end-of-life planning could direct care towards more appropriate settings and lead to system efficiencies. Death at older ages results in an increasing proportion of care costs relating to social care than to healthcare, which has implications for an ageing society.

Cost of hospital care for the older adults according to their level of frailty. A cohort study in the Lazio region, Italy

Background

The increasing burden of chronic diseases associated with the ageing of the European population constitutes one of the main challenges for the welfare systems in developed western countries, especially through its impact on the use of hospital services and the cost of care. This study aims at evaluating the cost of hospital care for older adults living in the Lazio Region, Italy, according to their level of frailty.

Methods

Since 2014 a longitudinal randomized cohort study has been carried out on a sample consisting of 1280 older adults aged over 64 years resident in the Lazio region (Italy), with their being evaluated for multidimensional frailty. Accesses to Hospital Services (acute care and Day Hospital care admissions and Emergency Room accesses) during the first year after enrolment, as well as the related costs have been recorded through a regional database. Costs have been stratified on the basis of the state of frailty.

Results

The analysis of hospital services and costs highlights the role played by pre-frail individuals who generated 49.3% of the hospital care cumulative costs. Hospital Admission (HA) costs arising from robust and pre-frail subjects are 70% of the total HA costs. Pre-frail individuals also showed the highest average HA cost per person/year (7062.89 Euros). The main determinant of the highest HA costs was given by the number of HAs during the follow-up (multivariate linear regression, ß coefficient = 0.319; p<0.001), which was higher among pre-frail individuals than in any other group of patients.

Conclusions

Pre-frail individuals generated the highest cost for hospital care in a sample of representative subjects living in an Italian Region with a low rate of community care services, as is the case in the Lazio region. Assessment of the multidimensional frailty of older adults permits a better definition of the important target of the pre-frail population as the main category within which interventions to prevent or mitigate frailty should be carried out.

Frailty as a predictor of mortality and hospital services use in older adults: a cluster analysis in a cohort study

Background

Lowering mortality and hospitalization of older adults is one of the main goals of public health to improve both health systems’ sustainability and older adults’ quality of life. The aim of this study is to identify the determinants associated with mortality and the use of hospital services in the population older than 64 years of age.

Methods

A randomized sample from the population of the Lazio region (Italy) above the age of 64 was enrolled in 2014 by the administration of a questionnaire to assess frailty; the rates of use of hospital services and mortality in the year following the enrolment have been retrieved by the regional database. Univariable and multivariable analyses addressed the association of health status, social and economic variables with health outcomes.

Results

One thousand two hundred and eighty persons were recruited; 52 deaths were reported at 1 year of follow-up (robust 1.8%, frail 10.1% and very frail 19.1%, P < 0.001). The mean rate of use of hospital services was 692.2 per 1000 observation/year (robust 589.5, frail 1191.1 and very frail 848.4, P < 0.001). In the multivariate analysis, the higher rate of use of hospital services was independently associated with functional status, social support, psychological/psychiatric discomfort, availability of home care services and physical health.

Conclusions

Frailty, as a multidimensional issue, is also a strong predictor of survival in the short term. The use of the hospital services by older adults is associated mainly with functional status, social resources, psycho-physical status and health service organization factors.

Inpatient care expenditure of the elderly with chronic diseases who use public health insurance: Disparity in their last year of life

The Thai elderly are eligible for the Civil Servant Medical Benefit Scheme (CS) or Universal Coverage Scheme (UCS) depending on their pre-retirement or their children work status. This study aimed to investigate the disparity in inpatient care expenditures in the last year of life among Thai elderly individuals who used the two public health insurance schemes. Using death registration and inpatient administrative data from 2007 to 2011, our subpopulation group included the elderly with four chronic disease groups: diabetes mellitus, hypertension and cardiovascular disease, heart disease, and cancer. Among 1,242,150 elderly decedents, about 40% of them had at least one of the four chronic disease conditions and were hospitalized in their last year of life. The results showed that the means of inpatient care expenditures in the last year of life paid by CS and UCS per decedent were 99,672 Thai Baht and 52,472 Thai Baht, respectively. On average, UCS used higher healthcare resources by diagnosis-related group relative weight measure per decedent compared with CS. In all cases, the rates of payment for inpatient treatment per diagnosis-related group adjusted relative weight were higher for CS than UCS. This study found that the disparities in inpatient care expenditures in the last year of life stemmed mainly from the difference in payment rates. To mitigate this disparity, unified payment rates for various types of treatment that reflect costs of hospital care across insurance schemes were recommended.

Exploring the determinants that influence end-of-life hospital costs of the elderly in Shanghai, China

The aim of this study was to use data from the Information Center of the Shanghai Municipal Commission of Health and Family Planning (SMCHFP) to determine the factors affecting end-of-life hospital costs of patients. A total number of 43,806 decedents who died in medical facilities in 2015 were examined. These individuals, accounted for 34.85% of all deaths in 2015 in Shanghai. Descriptive analysis and multiple linear regression analysis were performed using STATA 13.0. Results indicated that 88.94% of the decedents who died in medical facilities were over age 60. Males accounted for 55.57% of decedents, and the insured were mostly covered by Urban Employee Basic Medical Insurance (UEBMI) (81.93%). Cancer and circulatory disease were the main causes of death, causing 34.53% and 26.19% of deaths. Hospital costs were higher for males (male vs. female: 9,013 USD vs. 7,844 USD), individuals insured by UEBMI (8,784 USD), and individuals with cancer (10,156USD). Twenty-nine-point-zero-three percent of admissions occurred in the month before death and accounted for 37.82% of costs. Multiple linear regression analysis indicated that hospital costs were correlated with gender, cause of death (cancer, circulatory disease, or respiratory disease), time-to-death, insurance schemes, level of medical facilities, and length of stay (LOS) (p < 0.05 for all). After controlling for other factors, age was not a significant factor (p > 0.05). A proximity-to-death (PTD) phenomenon was evident in Shanghai. This study suggested that the PTD should be considered when predicting medical cost. Primary medical care should be enhanced and gaps in insurance coverage should be reduced to improve the efficiency and equity of medical funding. More attention should be paid to the population with a heavier disease burden.

Relating cause of death with place of care and healthcare costs in the last year of life for patients who died from cancer, chronic obstructive pulmonary disease, heart failure and dementia: A descriptive study using registry data

BACKGROUND

The four main diagnostic groups for palliative care provision are cancer, chronic obstructive pulmonary disease, heart failure and dementia. But comparisons of costs and care in the last year of life are mainly directed at cancer versus non-cancer or within cancer patients.

AIM

Our aim is to compare the care and expenditures in their last year of life for Dutch patients with cancer, chronic obstructive pulmonary disease, heart failure or dementia.

DESIGN

Data from insurance company Achmea (2009-2010) were linked to information on long-term care at home or in an institution, the National Hospital Registration and Causes of Death-Registry from Statistics Netherlands. For patients who died of cancer ( n = 8658), chronic obstructive pulmonary disease ( n = 1637), heart failure ( n = 1505) or dementia ( n = 3586), frequencies and means were calculated, Lorenz curves were drawn up and logistic regression was used to compare patients with high versus low expenditures.

RESULTS

For decedents with cancer and chronic obstructive pulmonary disease, the highest costs were for hospital admissions. For decedents with heart failure, the highest costs were for the care home (last 360 days) and hospital admissions (last 30 days). For decedents with dementia, the highest costs were for the nursing home.

CONCLUSION

Patients with dementia had the highest expenditures due to nursing home care. The number of dementia patients will double by the year 2030, resulting in even higher economic burdens than presently. Policy regarding patients with chronic conditions should be informed by research on expenditures within the context of preferences and needs of patients and carers.

Seasonal Variation in Mortality, Medical Care Expenditure and Institutionalization in Older People: Evidence from a Dutch Cohort of Older Health Insurance Clients

Background

The mortality rates of older people changes with the seasons. However, it has not been properly investigated whether the seasons affect medical care expenditure (MCE) and institutionalization. Seasonal variation in MCE is plausible, as MCE rises exponentially before death. It is therefore important to investigate the impact of the seasons on MCE both mediated and unmediated by mortality.

Methods

Data on mortality, MCE and institutionalization from people aged 65 and older in a region in the Netherlands from July 2007 through 2010 were retrieved from a regional health care insurer and were linked with data from the Netherlands Institute for Social Research, and Statistics Netherlands (n = 61,495). The Seasonal and Trend decomposition using Loess (STL) method was used to divide mortality rates, MCE, and institutionalization rates into a long-term trend, seasonal variation, and remaining variation. For every season we calculated the 95% confidence interval compared to the long-term trend using Welch’s t-test.

Results

The mortality rates of older people differ significantly between the seasons, and are 21% higher in the winter compared to the summer. MCE rises with 13% from the summer to the winter; this seasonal difference is higher for the non-deceased than for the deceased group (14% vs. 6%). Seasonal variation in mortality is more pronounced in men and people in residential care. Seasonal variation in MCE is more pronounced in women. Institutionalization rates are significantly higher in the winter, but the other seasons show no significant impact.

Conclusions

Seasonal changes affect mortality and the level of MCE of older people; institutionalization rates peak in the winter. Seasonal variation in MCE exists independently from patterns in mortality. Seasonal variation in mortality is similar for both institutionalized and community-dwelling elderly. Policy-makers, epidemiologists and health economists are urged to acknowledge and include the impact of the seasons in future policy and research.

Involvement of a Case Manager in Palliative Care Reduces Hospitalisations at the End of Life in Cancer Patients; A Mortality Follow-Back Study in Primary Care

Background

Case managers have been introduced in primary palliative care in the Netherlands; these are nurses with expertise in palliative care who offer support to patients and informal carers in addition to the care provided by the general practitioner (GP) and home-care nurse.

Objectives

To compare cancer patients with and without additional support from a case manager on: 1) the patients’ general characteristics, 2) characteristics of care and support given by the GP, 3) palliative care outcomes.

Methods

This article is based on questionnaire data provided by GPs participating in two different studies: the Sentimelc study (280 cancer patients) and the Capalca study (167 cancer patients). The Sentimelc study is a mortality follow-back study amongst a representative sample of GPs that monitors the care provided via GPs to a general population of end-of-life patients. Data from 2011 and 2012 were analysed. The Capalca study is a prospective study investigating the implementation and outcome of the support provided by case managers in primary palliative care. Data were gathered between March 2011 and December 2013.

Results

The GP is more likely to know the preferred place of death (OR 7.06; CI 3.47-14.36), the place of death is more likely to be at the home (OR 2.16; CI 1.33-3.51) and less likely to be the hospital (OR 0.26; CI 0.13-0.52), and there are fewer hospitalisations in the last 30 days of life (none: OR 1.99; CI 1.12-3.56 and one: OR 0.54; CI 0.30-0.96), when cancer patients receive additional support from a case manager compared with patients receiving the standard GP care.

Conclusions

Involvement of a case manager has added value in addition to palliative care provided by the GP, even though the role of the case manager is ‘only’ advisory and he or she does not provide hands-on care or prescribe medication.