Borsika A Rabin1, Jennifer L Ellis2, John F Steiner2, Larissa Nekhlyudov2, Eric J Feuer2, Benjamin F Hankey2, Laurie Cynkin2, Elizabeth Bayliss2. 1. Department of Family Medicine and Colorado Health Outcomes Program, School of Medicine, University of Colorado, Denver, CO (BAR); Cancer Research Network Cancer Communication Research Center (BAR), Institute for Health Research (JLE, JFS, EB), Kaiser Permanente Colorado, Denver, CO; Department of Population Medicine, Harvard Medical School, Boston, MA, Department of Medicine, Harvard Vanguard Medical Associates, Boston, MA (JN); Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD (EJF, BFH, LC). borsika.rabin@ucdenver.edu. 2. Department of Family Medicine and Colorado Health Outcomes Program, School of Medicine, University of Colorado, Denver, CO (BAR); Cancer Research Network Cancer Communication Research Center (BAR), Institute for Health Research (JLE, JFS, EB), Kaiser Permanente Colorado, Denver, CO; Department of Population Medicine, Harvard Medical School, Boston, MA, Department of Medicine, Harvard Vanguard Medical Associates, Boston, MA (JN); Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD (EJF, BFH, LC).
Abstract
BACKGROUND: Accurate estimation of the probability of dying of cancer versus other causes is needed to inform goals of care for cancer patients. Further, prognosis may also influence health-care utilization. This paper describes health service utilization patterns of subgroups of prostate cancer and colorectal cancer (CRC) patients with different relative probabilities of dying of their cancer or other conditions. METHODS: A retrospective cohort of cancer patients from Kaiser Permanente Colorado were divided into three groups using the predicted probabilities of dying of cancer and other causes calculated by the nomograms in the National Cancer Institute Surveillance, Epidemiology and End Results Cancer Survival Calculator. Demographic, disease-related characteristics, and health service utilization patterns were described across subgroups. RESULTS: The cohort consisted of 2092 patients (1102 prostate cancer and 990 CRC). A new diagnosis of cancer increased utilization of cancer-related services with rates as high as 9.1/1000 person-days for prostate cancer and 36.2/1000 person-days for CRC. Little change was observed in the number of primary and other specialty care visits from prediagnosis to 1 and 2 years postdiagnosis. CONCLUSIONS: We found that although a new diagnosis of cancer increased utilization of cancer-related services for an extended time period, the timing of cancer diagnosis did not appear to affect other types of utilization. Future research should assess the reason for the lack of impact of cancer and unrelated comorbid conditions on utilization and whether desired outcomes of care were achieved.
BACKGROUND: Accurate estimation of the probability of dying of cancer versus other causes is needed to inform goals of care for cancerpatients. Further, prognosis may also influence health-care utilization. This paper describes health service utilization patterns of subgroups of prostate cancer and colorectal cancer (CRC) patients with different relative probabilities of dying of their cancer or other conditions. METHODS: A retrospective cohort of cancerpatients from Kaiser Permanente Colorado were divided into three groups using the predicted probabilities of dying of cancer and other causes calculated by the nomograms in the National Cancer Institute Surveillance, Epidemiology and End Results Cancer Survival Calculator. Demographic, disease-related characteristics, and health service utilization patterns were described across subgroups. RESULTS: The cohort consisted of 2092 patients (1102 prostate cancer and 990 CRC). A new diagnosis of cancer increased utilization of cancer-related services with rates as high as 9.1/1000 person-days for prostate cancer and 36.2/1000 person-days for CRC. Little change was observed in the number of primary and other specialty care visits from prediagnosis to 1 and 2 years postdiagnosis. CONCLUSIONS: We found that although a new diagnosis of cancer increased utilization of cancer-related services for an extended time period, the timing of cancer diagnosis did not appear to affect other types of utilization. Future research should assess the reason for the lack of impact of cancer and unrelated comorbid conditions on utilization and whether desired outcomes of care were achieved.
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