BACKGROUND: Early referral to palliative care (PC) services has been shown to improve quality of life in advanced cancer. However, limitations in trained PC workforce raise issues with the sustainability of delivering PC with early PC referral. Classifying PC into generalist and specialist components could be one approach to sustainable PC delivery models but a quantitative guide for this classification is presently lacking in the literature. OBJECTIVE: To undertake a retrospective examination of clinical data obtained from a PC benchmarking project to develop a quantitative framework guiding classification of PC services into specialist and generalist components. DESIGN: A descriptive retrospective study of data from 2726 hospitalized inpatients under the care of a tertiary consultative PC service over a 2-year period was conducted. Daily categorical symptom, overall psychological and social distress scores at the start and end of 3392 palliative care episodes as well as the number of visits made by the PC team to patients were extracted for analysis. RESULTS: More than 50% of patients had symptom, overall psychological or social distress scores of nil or mild severity at episode start and end. Approximately 20% of all 2726 patients accounted for approximately half of all visits made by the team regardless of the reasons for review. This patient percentage minority had more PC episodes starting with moderate or severe pain. These findings suggest a Pareto-like distribution in the occurrence of moderate/severe PC problems and the intensity of PC input. CONCLUSIONS: Large-scale clinical data supports the use of a Pareto-based quantitative framework for a workforce comprising of mainly generalist PC staff supported by smaller numbers of PC specialists.
BACKGROUND: Early referral to palliative care (PC) services has been shown to improve quality of life in advanced cancer. However, limitations in trained PC workforce raise issues with the sustainability of delivering PC with early PC referral. Classifying PC into generalist and specialist components could be one approach to sustainable PC delivery models but a quantitative guide for this classification is presently lacking in the literature. OBJECTIVE: To undertake a retrospective examination of clinical data obtained from a PC benchmarking project to develop a quantitative framework guiding classification of PC services into specialist and generalist components. DESIGN: A descriptive retrospective study of data from 2726 hospitalized inpatients under the care of a tertiary consultative PC service over a 2-year period was conducted. Daily categorical symptom, overall psychological and social distress scores at the start and end of 3392 palliative care episodes as well as the number of visits made by the PC team to patients were extracted for analysis. RESULTS: More than 50% of patients had symptom, overall psychological or social distress scores of nil or mild severity at episode start and end. Approximately 20% of all 2726 patients accounted for approximately half of all visits made by the team regardless of the reasons for review. This patient percentage minority had more PC episodes starting with moderate or severe pain. These findings suggest a Pareto-like distribution in the occurrence of moderate/severe PC problems and the intensity of PC input. CONCLUSIONS: Large-scale clinical data supports the use of a Pareto-based quantitative framework for a workforce comprising of mainly generalist PC staff supported by smaller numbers of PC specialists.