Cost-saving prediction model of transfer to palliative care for terminal cancer patients in a Japanese general hospital
Background Although medical costs need to be controlled, there are no easily applicable cost prediction models of transfer to palliative care (PC) for terminal cancer patients.Objective Construct a cost-saving prediction model based on terminal cancer patients’ data at hospital admission.Study desig...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Journal of Market Access & Health Policy |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/20016689.2022.2057651 |
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| author | Yuki Hashimoto Akitoshi Hayashi Takashi Tonegawa Lida Teng Ataru Igarashi |
| author_facet | Yuki Hashimoto Akitoshi Hayashi Takashi Tonegawa Lida Teng Ataru Igarashi |
| author_sort | Yuki Hashimoto |
| collection | DOAJ |
| description | Background Although medical costs need to be controlled, there are no easily applicable cost prediction models of transfer to palliative care (PC) for terminal cancer patients.Objective Construct a cost-saving prediction model based on terminal cancer patients’ data at hospital admission.Study design Retrospective cohort study.Setting A Japanese general hospital.Patients A total of 139 stage IV cancer patients transferred to PC, who died during hospitalization from April 2014 to March 2019.Main outcome measure Patients were divided into higher (59) and lower (80) total medical costs per day after transfer to PC. We compared demographics, cancer type, medical history, and laboratory results between the groups. Stepwise logistic regression analysis was used for model development and area under the curve (AUC) calculation.Results A cost-saving prediction model (AUC = 0.78, 95% CI: 0.70, 0.85) with a total score of 13 points was constructed as follows: 2 points each for age ≤ 74 years, creatinine ≥ 0.68 mg/dL, and lactate dehydrogenase ≤ 188 IU/L; 3 points for hemoglobin ≤ 8.8 g/dL; and 4 points for potassium ≤ 3.3 mEq/L.Conclusion Our model contains five predictors easily available in clinical settings and exhibited good predictive ability. |
| format | Article |
| id | doaj-art-e62b2a07278d44cf8113373b04b80878 |
| institution | OA Journals |
| issn | 2001-6689 |
| language | English |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Market Access & Health Policy |
| spelling | doaj-art-e62b2a07278d44cf8113373b04b808782025-08-20T02:04:05ZengMDPI AGJournal of Market Access & Health Policy2001-66892022-12-0110110.1080/20016689.2022.2057651Cost-saving prediction model of transfer to palliative care for terminal cancer patients in a Japanese general hospitalYuki Hashimoto0Akitoshi Hayashi1Takashi Tonegawa2Lida Teng3Ataru Igarashi4Department of Health Economics and Outcomes Research, Graduate School of Pharmaceutical Sciences, the University of Tokyo, Tokyo, JapanPalliative Care Department, St. Luke’s International Hospital, Tokyo, JapanMedical Affairs Department, St. Luke’s International Hospital, Tokyo, JapanDepartment of Health Economics and Outcomes Research, Graduate School of Pharmaceutical Sciences, the University of Tokyo, Tokyo, JapanDepartment of Health Economics and Outcomes Research, Graduate School of Pharmaceutical Sciences, the University of Tokyo, Tokyo, JapanBackground Although medical costs need to be controlled, there are no easily applicable cost prediction models of transfer to palliative care (PC) for terminal cancer patients.Objective Construct a cost-saving prediction model based on terminal cancer patients’ data at hospital admission.Study design Retrospective cohort study.Setting A Japanese general hospital.Patients A total of 139 stage IV cancer patients transferred to PC, who died during hospitalization from April 2014 to March 2019.Main outcome measure Patients were divided into higher (59) and lower (80) total medical costs per day after transfer to PC. We compared demographics, cancer type, medical history, and laboratory results between the groups. Stepwise logistic regression analysis was used for model development and area under the curve (AUC) calculation.Results A cost-saving prediction model (AUC = 0.78, 95% CI: 0.70, 0.85) with a total score of 13 points was constructed as follows: 2 points each for age ≤ 74 years, creatinine ≥ 0.68 mg/dL, and lactate dehydrogenase ≤ 188 IU/L; 3 points for hemoglobin ≤ 8.8 g/dL; and 4 points for potassium ≤ 3.3 mEq/L.Conclusion Our model contains five predictors easily available in clinical settings and exhibited good predictive ability.https://www.tandfonline.com/doi/10.1080/20016689.2022.2057651cost-savingpalliative careterminal cancerprediction modelhealth economicsend-of-life |
| spellingShingle | Yuki Hashimoto Akitoshi Hayashi Takashi Tonegawa Lida Teng Ataru Igarashi Cost-saving prediction model of transfer to palliative care for terminal cancer patients in a Japanese general hospital Journal of Market Access & Health Policy cost-saving palliative care terminal cancer prediction model health economics end-of-life |
| title | Cost-saving prediction model of transfer to palliative care for terminal cancer patients in a Japanese general hospital |
| title_full | Cost-saving prediction model of transfer to palliative care for terminal cancer patients in a Japanese general hospital |
| title_fullStr | Cost-saving prediction model of transfer to palliative care for terminal cancer patients in a Japanese general hospital |
| title_full_unstemmed | Cost-saving prediction model of transfer to palliative care for terminal cancer patients in a Japanese general hospital |
| title_short | Cost-saving prediction model of transfer to palliative care for terminal cancer patients in a Japanese general hospital |
| title_sort | cost saving prediction model of transfer to palliative care for terminal cancer patients in a japanese general hospital |
| topic | cost-saving palliative care terminal cancer prediction model health economics end-of-life |
| url | https://www.tandfonline.com/doi/10.1080/20016689.2022.2057651 |
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