Skip to main content
Log in

Development of a Clinical Tool to Predict Home Death of a Discharged Cancer Patient in Japan: a Case-Control Study

  • Published:
International Journal of Behavioral Medicine Aims and scope Submit manuscript

Abstract

Purpose

The aim of this study was to investigate the predictive value of a clinical tool to predict whether discharged cancer patients die at home, comparing groups of case who died at home and control who died in hospitals or other facilities.

Method

We conducted a nationwide case-control study to identify the determinants of home death for a discharged cancer patient. We randomly selected nurses in charge of 2000 home-visit nursing agencies from all 5813 agencies in Japan by referring to the nationwide databases in January 2013. The nurses were asked to report variables of their patients’ place of death, patients’ and caregivers’ clinical statuses, and their preferences for home death. We used logistic regression analysis and developed a clinical tool to accurately predict it and investigated their predictive values.

Results

We identified 466 case and 478 control patients. Five predictive variables of home death were obtained: patients’ and caregivers’ preferences for home death [OR (95% CI) 2.66 (1.99–3.55)], availability of visiting physicians [2.13 (1.67–2.70)], 24-h contact between physicians and nurses [1.68 (1.30–2.18)], caregivers’ experiences of deathwatch at home [1.41 (1.13–1.75)], and patients’ insights as to their own prognosis [1.23 (1.02–1.50)]. We calculated the scores predicting home death for each variable (range 6–28). When using a cutoff point of 16, home death was predicted with a sensitivity of 0.72 and a specificity of 0.81 with the Harrell’s c-statistic of 0.84.

Conclusion

This simple clinical tool for healthcare professionals can help predict whether a discharged patient is likely to die at home.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. Gomes B, Higginson IJ. Factors influencing death at home in terminally ill patients with cancer: systematic review. BMJ. 2006;332:515–21.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Bell CL, Somogyi-Zalud E, Masaki KH. Methodological review: measured and reported congruence between preferred and actual place of death. Palliat Med. 2009;23:482–90.

    Article  CAS  PubMed  Google Scholar 

  3. Murray MA, Fiset V, Young S, et al. Where the dying live: a systematic review of determinants of place of end-of-life cancer care. Oncol Nurs Forum. 2009;36:69–77.

    Article  PubMed  Google Scholar 

  4. Morita T, Miyashita M, Yamagishi A, et al. Effects of a programme of interventions on regional comprehensive palliative care for patients with cancer: a mixed-methods study. Lancet Oncol. 2013;14(4):638–46.

    Article  PubMed  Google Scholar 

  5. Wright AA, Keating NL, Balboni TA, et al. Place of death: correlations with quality of life of patients with cancer and predictors of bereaved caregivers’ mental health. J Clin Oncol. 2010;28:4457–64.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Fukui S, Fujita J, Tsujimura M, et al. Late referrals to home palliative care service affecting death at home in advanced cancer patients in Japan: a nationwide survey. Ann Oncol. 2011;22:2113–20.

    Article  CAS  PubMed  Google Scholar 

  7. Fukui S, Yoshiuchi K, Fujita J, et al. Japanese people’s preference for place of end-of-life care and death: a population-based nationwide survey. J Pain Symptom Manag. 2011;42:882–92.

    Article  Google Scholar 

  8. Gomes B, Higginson IJ. Where people die (1974-2030): past trends, future projections and implications for care. Palliat Med. 2008;22:33–41.

    Article  PubMed  Google Scholar 

  9. Foreman LM, Hunt RW, Luke CG, et al. Factors predictive of preferred place of death in the general population of South Australia. Palliat Med. 2006;20:447–53.

    Article  PubMed  Google Scholar 

  10. Gwilliam B, Keeley V, Todd C, et al. Development of prognosis in palliative care study (PiPS) predictor models to improve prognostication in advanced cancer: prospective cohort study. BMJ. 2011;25:343–d4920.

    Google Scholar 

  11. Maltoni M, Caraceni A, Brunelli C, et al. Prognostic factors in advanced cancer patients: evidence-based clinical recommendations—a study by the Steering Committee of the European Association for Palliative Care. J Clin Oncol. 2005;23:6240–8.

    Article  PubMed  Google Scholar 

  12. Glare PA, Eychmueller S, McMahon P. Diagnostic accuracy of the palliative prognostic score in hospitalized patients with advanced cancer. J Clin Oncol. 2004;22:4823–8.

    Article  PubMed  Google Scholar 

  13. Maltoni M, Nanni O, Pirovano M, et al. Successful validation of the palliative prognostic score in terminally ill cancer patients. Italian Multicenter Study Group on Palliative Care. J Pain Symptom Manag. 1999;17:240–7.

    Article  CAS  Google Scholar 

  14. Morita T, Tsunoda J, Inoue S, et al. The palliative prognostic index: a scoring system for survival prediction of terminally ill cancer patients. Support Care Cancer. 1999;7:128–33.

    Article  CAS  PubMed  Google Scholar 

  15. Alonso-Babarro A, Bruera E, Varela-Cerdeira M, et al. Can this patient be discharged home? Factors associated with at-home death among patients with cancer. J Clin Oncol. 2011;29:1159–67.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Fukui S. A nationwide survey on the end-of-life care provided by homevisit nursing in Japan. Bull Soc Insur (Shakai Hoken Junpo). In Japanese. 2012;2488:16–23.

    Google Scholar 

  17. Report on home care part 4 of Ministry of Health, Labour and Welfare. Tokyo: Ministry of Health, Labour and Welfare. 2013. [in Japanese] http://www.mhlw.go.jp/file/05-Shingikai-12404000-Hokenkyoku-Iryouka/0000027523.pdf. Accessed 25 Nov 2016.

  18. Bell CL, Somogyi-Zalud E, Masaki KH. Factors associated with congruence between preferred and actual place of death. J Pain Symptom Manag. 2010;39:591–604.

    Article  Google Scholar 

  19. Miyashita M, Matoba K, Sasahara T, et al. Reliability and validity of Japanese version STAS (STAS-J). Palliat Support Care. 2004;2:379–84.

    Article  PubMed  Google Scholar 

  20. Higginson I, McCarthy M. Validity of the support team assessment schedule: do staffs’ rating reflect those made by patients or their families? Palliat Med. 1993;7:219–28.

    Article  CAS  PubMed  Google Scholar 

  21. Miyashita M, Yasuda M, Baba R, et al. Inter-rater reliability of proxy simple symptom assessment scale between physician and nurse: a hospital-based palliative care team setting. Eur J Cancer Care. 2010;19:124–30.

    Article  CAS  Google Scholar 

  22. Hasan O, Meltzer DO, Shaykevich SA, et al. Hospital readmission in general medicine patients: a prediction model. J Gen Intern Med. 2010;25:211–9.

    Article  PubMed  Google Scholar 

  23. Harrell Jr FE, Lee KL, Mark DB. Multivariable prognostic models, issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15:361–87.

    Article  PubMed  Google Scholar 

  24. Steyerberg EW, Harrell Jr FE, Borsboom GJ, et al. Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol. 2001;54:774–81.

    Article  CAS  PubMed  Google Scholar 

  25. Schumacher M, Hollander N, Sauerbrei W. Resampling and cross-validation techniques: a tool to reduce bias caused by model building? Stat Med. 1997;16:2813–27.

    Article  CAS  PubMed  Google Scholar 

  26. Grande G, Ewing G. Death at home unlikely if informal carers prefer otherwise: implications for policy. Palliat Med. 2008;22:971–2.

    Article  CAS  PubMed  Google Scholar 

  27. Fukui S, Fukui N, Kawagoe H. Predictors of place of death for Japanese patients with advanced-stage malignant disease in home care settings: a nationwide survey. Cancer. 2004;101:421–9.

    Article  PubMed  Google Scholar 

  28. Fukui S, Fujita J, Tsujimura M, Sumikawa Y, Hayashi Y. Predictors of home death of home palliative cancer care patients: a cross-sectional nationwide survey. Int J Nur Stud. 2011;48:1393–400.

    Article  Google Scholar 

  29. Report 2008 on survey of end-of-life care in Japan of Ministry of Health, Labour and Welfare. Tokyo: Ministry of Health, Labour and Welfare. 2008. [in Japanese]. http://www.mhlw.go.jp/shingi/2008/10/dl/s1027-12e.pdf. Accessed 25 Nov 2016.

  30. Fukui S, Fujita J, Yoshiuchi K. Associations between Japanese people’s concern about family caregiver burden and preference for end-of-life care location. J Palliat Care. 2013;29:22–8.

    PubMed  Google Scholar 

  31. O’Brien M, Jack B. Barriers to dying at home: the impact of poor co-ordination of community service provision for patients with cancer. Health Soc Care Community. 2010;18(4):337–45.

    PubMed  Google Scholar 

  32. Miyashita M, Morita T, Hirai K. Evaluation of end-of-life cancer care from the perspective of bereaved family members: the Japanese experience. J Clin Oncol. 2008;26:3845–52.

    Article  PubMed  Google Scholar 

  33. Tang ST. When death is imminent: where terminally ill patients with cancer prefer to die and why. Cancer Nurs. 2003;26:245–51.

    Article  PubMed  Google Scholar 

  34. Butler M, Ratner E, McCreedy E, et al. Decision aids for advance care planning: an overview of the state of the science. Ann Intern Med. 2014;161:408–18.

    Article  PubMed  Google Scholar 

  35. Walczak A, Butow PN, Clayton JM, et al. Discussing prognosis and end-of-life care in the final year of life: a randomised controlled trial of a nurse-led communication support programme for patients and caregivers. BMJ Open. 2014;6(4(6)):e005745.

    Article  Google Scholar 

  36. Tang ST, Liu TW, Liu LN, et al. Physician-patient end-of-life care discussions: correlates and associations with end-of-life care preferences of cancer patients—a cross-sectional survey study. Palliat Med. 2014;28:1222–30.

    Article  PubMed  Google Scholar 

  37. Lovell A, Yates P. Advance care planning in palliative care: a systematic literature review of the contextual factors influencing its uptake 2008-2012. Palliat Med. 2014;28:1026–35.

    Article  PubMed  Google Scholar 

  38. Wright AA, Zhang B, Ray A, et al. Associations between end-of-life discussions, patient mental health, medical care near death, and caregiver bereavement adjustment. JAMA. 2008;300:1665–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Fukui S, Yamamoto-Mitani N, Fujita J. Five types of home-visit nursing agencies in Japan based on characteristics of service delivery: cluster analysis of three nationwide surveys. BMC Health Serv Res. 2014;14:644.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Fukui S, Yoshiuchi K, Fujita J, et al. Determinants of financial performance of home-visit nursing agencies in Japan. BMC Health Serv Res. 2014;14:11.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank the home-visiting nurses for their generous cooperation in this study. We are also grateful to Dr. Hiroya Kinoshita, Dr. Junko Fujita, Dr. Yuko Okamoto, and Dr. Yoshiki Ishikawa for their research advices. We also thank Ms. Eiko Kawano, Mr. Toshiya Saito, Mr. Daitaro Misawa, Mr. Oosono Yasufumi, Ms. Takako Ishikawa, Ms. Yumi Yokota, and Ms. Kumi Kaifu for their research assistance.

Contributorship Statement

All authors formulated the study design. SF and KY carried out the statistical analyses. SF wrote the first and successive drafts of the paper. All authors interpreted the results, revised the text for important intellectual content, and approved the final draft of the report.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sakiko Fukui.

Ethics declarations

Funding

This study was funded by a Health and Labor Science Research Grant, Ministry of Health, Labor and Welfare, the Japanese Government (No. H26-51). The funding sources were involved neither in the conduct of the research nor in the preparation of the article.

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

Ethics approval for this study was obtained from the Institutional Review Board of The Japanese Red Cross College of Nursing (No.2012-80). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

Research Involving Human Participants and Informed Consent

Questionnaires were distributed to 2000 home-visit nursing agencies, which were randomly selected from all of 5813 agencies by referring to the nationwide databases, with a cover letter explaining the survey and requesting completion of the questions about eligible patients with the instruction to complete the questionnaire. Ethics approval for this study was obtained from the Institutional Review Board of The Japanese Red Cross College of Nursing (No.2012-80).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fukui, S., Morita, T. & Yoshiuchi, K. Development of a Clinical Tool to Predict Home Death of a Discharged Cancer Patient in Japan: a Case-Control Study. Int.J. Behav. Med. 24, 584–592 (2017). https://doi.org/10.1007/s12529-016-9619-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12529-016-9619-y

Keywords

Navigation