Keywords
home-death rate, medically attended death, end-of-life care, home-visit nursing, primary care, ecological study, Japan, health indicators
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Ishikawa T and Takashima Y. Does the Home-death Rate Reflect Medically Attended Community Deaths in Japan? [version 1; peer review: awaiting peer review]. F1000Research 2025, 14:1272 (https://doi.org/10.12688/f1000research.172900.1)
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Does the Home-death Rate Reflect Medically Attended Community Deaths in Japan?
[version 1; peer review: awaiting peer review]
PUBLISHED 18 Nov 2025
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This article is included in the Health Services gateway.
Abstract
Corresponding author:
Takemasa Ishikawa
Competing interests:
No competing interests were disclosed.
Grant information:
This work was supported by the Japan National Association for Visiting Nursing Care Agencies under the 2025 Research Grant Program.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Copyright:
© 2025 Ishikawa T and Takashima Y.
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to cite: Ishikawa T and Takashima Y. Does the Home-death Rate Reflect Medically Attended Community Deaths in Japan? [version 1; peer review: awaiting peer review]. F1000Research 2025, 14:1272 (https://doi.org/10.12688/f1000research.172900.1)
First published: 18 Nov 2025, 14:1272 (https://doi.org/10.12688/f1000research.172900.1)
Latest published: 18 Nov 2025, 14:1272 (https://doi.org/10.12688/f1000research.172900.1)
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Introduction
In Japan, 17.0% of all deaths in 2023 occurred at home, whereas approximately 70% occurred in medical institutions.1 Globally, an estimated 53.4% (95% uncertainty interval (95%UI) 50.8–55.9) of deaths in low- and middle-income countries occur at home. In high-income countries, the corresponding mean is 27.3% (95%UI 25.2–29.6).2 As home death reflects autonomy and community-based care, the national policy has promoted it as an indicator of integrated community-based care. Accordingly, home-death rate was adopted as the outcome measure. Yoshida et al. demonstrated that the density of home-visit nursing services was positively associated with the proportion of home deaths across Japanese municipalities3; Ishikawa et al. reported similar regional associations between home-death rates and demographic or healthcare resource factors.4
However, the validity of the home-death rate as a proxy for home-based end-of-life care is uncertain because it includes deaths without professional involvement, such as solitary or unexpected cases.1 Consequently, this indicator includes not only medically attended home deaths but also deaths without professional involvement. In Yokohama City, Kakiuchi et al. reported that solitary deaths, defined as deaths discovered long after their occurrence, were frequently classified as home deaths in official records,5 suggesting that the category of “home death” encompasses heterogeneous circumstances. Similar concerns have been raised worldwide. Teno et al. found that more than one-third of individuals who died at home in the USA had received no nursing service6; Gomes et al. noted that home deaths do not necessarily correspond to better palliative outcomes or satisfaction.7
Additionally, the common assumption that most patients prefer to die at home is being increasingly challenged. This belief often justifies policy goals that target higher home-death rates. Hoare et al. found that many studies excluded cases with missing data on patient preferences, leading to an overestimation of the home-death preference.8 Hoare et al. further argued that the place of death has become a default quality metric despite its inability to capture key aspects of care, such as communication, continuity, and patient support.9 Recent consensus research has emphasised that the quality of home-based end-of-life care depends on multiple dimensions, including timely palliative input, coordination, and family preparedness, that cannot be inferred from death location alone.10 Japan maintains universal health coverage through two schemes: medical insurance and long-term care insurance (LTCI). Medical insurance covers physician-supervised home-visit nursing for all citizens, whereas the LTCI provides daily care for older adults with chronic conditions. Depending on patient needs, home-visit nursing may be reimbursed by either system, creating complexity in the organisation and recording of end-of-life care.
Despite the widespread use of the home-death rate in research and policy evaluation, no prior quantitative studies in Japan have verified whether this metric accurately reflects medically attended home-based deaths rather than deaths without professional care. The present study addresses this gap by examining associations between municipal-level home-death rates and indicators of medical and nursing involvement in home deaths and by assessing correlations with prefectural rates of coroner-investigated deaths to explore whether non-medical or solitary deaths may influence regional variation in this commonly used indicator.
Methods
Study design and data sources
This ecological panel study examined whether the home-death rate reflected the actual level of home-based end-of-life care across Japanese municipalities. The unit of analysis was the municipality (shi, cho, or son), and data were collected at three time points (2017, 2020, and 2023), yielding 5,223 observations across 1,741 municipalities. Municipality codes were harmonised across the survey years using the Survey of Municipality Areas from the Geospatial Information Authority of Japan. One municipality was excluded because it reported zero deaths in 2023, resulting in a final analytical sample of 1,740 municipalities.
Data on the medical institutions, home-visit nursing services, population characteristics, and number of home deaths certified by clinics were obtained from the Regional Dataset on Home Medical Care provided by the Ministry of Health, Labour, and Welfare.11 Because the survey on clinically certified home deaths was conducted every three years, data were available only for 2017, 2020, and 2023. Data on deaths under LTCI-reimbursed home-visit nursing were derived from the Survey of Long-Term Care Service Facilities and Providers.12 Geographic boundary data were based on the Survey of Municipality Areas by the Geospatial Information Authority of Japan,13 and prefectural rates of coroner-investigated deaths were obtained from the Statistics on the Handling of Deceased Bodies.14 Because visiting-nursing death data were only available at the prefectural level owing to privacy restrictions, uniform values were applied to all municipalities within each prefecture. This approach captures inter-prefectural differences in care structure but may attenuate within-prefecture variability, likely resulting in conservative estimates. All data and analytical codes supporting this study are available in the Open Science Framework.15
Variables
The dependent variable was the home-death rate, defined as the proportion of deaths occurring at home among all registered deaths in each municipality. This measure is based on physicians’ death certificates, which record the place of death as “home”, “hospital”, “nursing home”, or other categories.1
The main explanatory variables captured indicators of home-based end-of-life care obtained from national surveys of clinics and home-visit nursing agencies. All variables were based on the number of home deaths reported in September of each survey year and were multiplied by 12 to approximate the annual totals.
The following four variables were used:
1. Home deaths certified by home-care support clinics: Deaths at home for which the death certificate was issued by a designated home-care support clinic expressed as the proportion of all deaths in the municipality.
2. Home deaths certified by general clinics: Deaths at home certified by other outpatient clinics, expressed as a proportion of all deaths in the municipality.
3. Deaths under home-visit nursing care (LTCI): Deaths of clients receiving home-visit nursing reimbursed under the LTCI system, measured at the prefectural level and uniformly applied to all municipalities within each prefecture.
4. Deaths under home-visit nursing care (medical insurance): Deaths of patients receiving home-visit nursing reimbursed under the medical insurance system were also measured at the prefectural level.
Clinic-related indicators were standardised by the total deaths in each municipality, and nursing-related indicators were standardised by the total deaths in each prefecture to adjust for population size and reporting coverage.
The following control variables were included to consider regional healthcare resources and demographic characteristics:
1. Number of clinics (log-transformed), representing the availability of primary medical institutions.
2. Number of home-visit nursing agencies (log-transformed), representing the supply of community-based nursing services.
3. Proportion of older adults (aged ≥65 years), reflecting the degree of population aging.
4. Mean per-capita municipal income tax, indicating the socioeconomic status of residents.
The numbers of clinics and home-visit nursing agencies were standardised per 10,000 population to consider population size differences across municipalities.
Statistical analysis
We employed a multilevel fixed-effects panel regression model using the panel ordinary least squares estimator, incorporating municipality and year fixed effects to control for unobserved time-invariant characteristics and nationwide temporal trends.16 Because indicators of home-visit nursing deaths were available only at the prefectural level, the model accounted for a hierarchical data structure, with municipalities nested within prefectures. Cluster-robust standard errors are calculated at the municipal level.
Three nested models were estimated:
1. Model 1 included only indicators of home deaths certified by clinics (both home-care support and general clinics).
2. Model 2 extended Model 1 by adding indicators of home deaths occurring under home-visit nursing care (separately for LTCI and medical insurance services).
3. Model 3 adjusted for regional healthcare resources and demographic factors, including the number of clinics, number of home-visit nursing agencies (both log-transformed), proportion of residents aged ≥65 years, and mean per-capita municipal income tax.
To assess multicollinearity among explanatory variables, variance inflation factors (VIFs) were calculated for Model 3, including all covariates. A VIF exceeding 10 was considered indicative of serious multicollinearity, whereas values below 5 were considered acceptable. Finally, we examined the correlation between residuals from Model 3 (2023 data only) and the prefectural rate of coroner-investigated deaths (per total deaths in 2023) to explore whether the home-death rate reflects deaths without medical involvement, such as solitary deaths.
All analyses were performed in Python (version 3.12.2) using the linearmodels package (version 6.1). Because all data were aggregated and publicly available, ethical approval and informed consent were not required for this study.
Results
In total, 5,222 municipality-year observations (1,741 municipalities in 2017, 2020, and 2023) were included in the analysis. Table 1 presents descriptive statistics for main variables. The mean home-death rate across all observations was 12.8% (standard deviation (SD), 6.2%). Mean proportions of home deaths certified by home-care support and general clinics were 0.058 (SD, 0.109) and 0.018 (SD, 0.058), respectively. Mean proportions of deaths under home-visit nursing care reimbursed by LTCI and medical insurance were 0.028 (SD, 0.016) and 0.045 (SD, 0.021), respectively. Substantial regional variability was observed in these indicators and in the number of clinics and home-visit nursing agencies.
Table 1. Descriptive statistics of main study variables (2017–2023, n=5,222 municipality-years).
Table 2 summarises results of fixed-effects panel regression models. Multicollinearity diagnostics indicated moderately elevated VIFs (approximately six) for the number of clinics and home-visit nursing agencies. However, all values were below the threshold of 10, suggesting that multicollinearity was not a substantive concern. In Model 1, home deaths certified by both home-care support clinics and general clinics were significantly associated with higher home-death rates (β=2.43, p=0.024; β=3.99, p=0.005, respectively). When indicators of home-visit nursing care were added to Model 2, the association with home-care support clinics was attenuated and became statistically nonsignificant (p=0.060). Deaths under medical insurance-reimbursed home-visit nursing care remained significantly associated with the outcome (β=42.48, 95% confidence interval (95%CI) 19.73–65.24, p<0.001), whereas those under LTCI-reimbursed visiting nursing were not (p=0.102). In the fully adjusted model (Model 3), only medical-insurance-reimbursed home-visit nursing deaths and deaths certified by general clinics remained statistically significant (β=31.75, 95% CI 8.14–55.37, p=0.008; β=4.06, 95%CI 1.28–6.85, p=0.004, respectively).
Table 2. Fixed-effects panel regression of home-death rates across Japanese municipalities, 2017–2023 (n=5,222).
Among control variables, the number of home-visit nursing agencies (log-transformed) was significantly associated with higher home-death rates (β=1.22, 95%CI 0.60–1.84, p<0.001). The proportion of older adults and mean per-capita income tax were inversely associated with the home-death rate, although the difference was not significant.
To assess whether home-death rates were related to deaths without medical involvement, mean residuals of Model 3 were correlated with prefecture-level rates of coroner-investigated deaths in 2023. No statistically significant correlation was observed (r=0.09, 95%CI –0.20–0.37, p=0.539; Figure 1).
Figure 1. Association between prefecture-level rate of coroner-investigated deaths and home-death rate residuals (Model 3, 2023).
Discussion
This study found that municipal home-death rates in Japan were positively associated with the number of home deaths certified by general clinics and deaths under medical insurance-reimbursed home-visit nursing care. In contrast, associations between home deaths certified by designated home-care support clinics and deaths under LTCI-reimbursed visiting nursing were not statistically significant. No association was observed between home-death residuals and prefectural rates of medicolegal death investigations. These results highlight the fact that home-death rates are partly shaped by activities of medical and nursing providers, warranting a closer examination of their contextual meaning.
Interpretation of findings in context
The municipal home-death rate partly reflects activities of community-based medical and nursing services, particularly general clinics and medical-insurance-based visiting nursing, which likely capture primary-care contributions to end-of-life care.17,18 In contrast, the association between home deaths certified by home-care support clinics and the overall home-death rate became nonsignificant post-adjustment. This may stem from the fact that the formal designation of “home-care support clinics” does not necessarily correspond to the actual provision of palliative or home-visit services. As of 2023, Japan had 104,894 general clinics and 14,514 designated home-care support clinics, indicating that the latter accounted for approximately 14% of all clinics. Given their relatively small number and uneven regional distribution, the statistical influence of designated home-care support clinics on municipal home-death rates may be inherently limited compared to that of general clinics.19 Furthermore, although home-care support clinics are certified by regulations, their levels of home-visit engagement vary widely.18 Conversely, many general clinics, regardless of designation, actively provide home medical care and play a central role in end-of-life support.18 Fukui et al. along with Ikezaki and Ikegami demonstrated that the involvement of attending or visiting physicians, rather than institutional status, was a key predictor of home deaths.20,21 Together, these findings suggest that the home-death rate reflects the functional strength of community-based clinical activities more than formal institutional categories.
The stronger association observed for deaths under medical-insurance-reimbursed visiting nursing than for those under LTCI-reimbursed visiting nursing is consistent with Japan’s dual insurance structure. LTCI mainly covers daily assistance for older adults with chronic support needs; medical insurance applies when continuous medical supervision or terminal-phase care is required.22 In practice, patients often transition from LTCI to medical insurance once the end-of-life management intensifies. This structural distinction plausibly explains why medical-insurance-reimbursed nursing deaths were more closely aligned with overall home-death rates.
Despite modest effect sizes, the home-death rate only partially represented medically attended deaths. However, the lack of correlation with medicolegal investigation rates suggests that non-medical deaths do not substantially distort the indicator. Thus, the home-death rate retains limited but meaningful interpretability as a proxy for medically attended end-of-life care.
However, conceptually, the place of death alone cannot capture care quality. Dying at home does not always imply better symptom control, communication, or satisfaction.23 Rather than serving as a direct quality metric, home-death rate may be better understood as a contextual indicator of community-based end-of-life care capacity that reflects the accessibility and continuity of home medical and nursing services.
Limitations
This study had several limitations. First, numbers of home deaths by clinics and home-visit nursing agencies were derived from September reports and multiplied by 12 to obtain approximate annual totals. Although this follows national reporting standards, seasonal variations can introduce bias. Second, data on home-visit nursing deaths and medicolegal investigations were only available at the prefectural level, whereas data on other variables were available at the municipal level, potentially reducing within-prefecture variability and attenuating the associations. Third, while fixed-effects models were adjusted for time-invariant heterogeneity and national trends, unobserved confounders, such as regional differences in reporting accuracy or death certification practices, cannot be ruled out; however, these are unlikely to explain the main observed patterns. Despite these limitations, the persistence of key associations, particularly for deaths under medical-insurance-reimbursed visiting nursing and those certified by general clinics, supports the robustness of our main findings.
Implication and conclusion
This study provides empirical evidence that Japan’s home-death rate, derived from physicians’ death certificates, partially reflects medically attended home deaths rather than non-medical or solitary deaths. These findings suggest that this indicator serves as a population-level contextual measure of community-based end-of-life care capacity and captures the extent to which medical and nursing services are integrated into local systems. However, because the place of death alone cannot represent care quality or patient experience, the home-death rate should be interpreted with caution and complemented with other indicators that reflect care involvement, coordination, and symptom management. Future research using individual-level or record-linked data is essential to validate these relationships and to develop more accurate and patient-centred measures for evaluating end-of-life care in the community.
Ethical considerations
This study used only aggregated publicly available data at the municipality and prefecture levels. No individual or identifiable information was included. Therefore, ethical approval and informed consent were not required.
Reporting guidelines
This article followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for Observational Studies. A completed STROBE checklist is available in the same Open Science Framework (OSF) repository as the dataset and analytical code: Ishikawa T. Municipal-level dataset and analytical code on home death and end-of-life care indicators in Japan (2015–2023). 2025. OSF. doi: 10.17605/OSF.IO/5V6BX.15
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how to cite this article
Ishikawa T and Takashima Y. Does the Home-death Rate Reflect Medically Attended Community Deaths in Japan? [version 1; peer review: awaiting peer review]. F1000Research 2025, 14:1272 (https://doi.org/10.12688/f1000research.172900.1)
NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.
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