Association between Palliative Care Consultation and Advance Palliative Care Rates: A Descriptive Cohort Study in Patients at Various Stages in the Continuum of Chronic Kidney Disease

Background: Studies report cost-savings from hospital-based palliative care consultation teams compared to usual care only, but drivers of observed differences are unclear. Aim: To analyse cost-differences associated with palliative care consultation teams using two research questions: (Q1) What is the association between early palliative care consultation team intervention, and intensity of services and length of stay, compared to usual care only? (Q2) What is the association between early palliative care consultation team intervention and day-to-day hospital costs, compared to a later intervention? Design: Prospective multi-site cohort study (2007–2011). Patients who received a consultation were placed in the intervention group, those who did not in the comparison group. Intervention group was stratified by timing, and groups were matched using propensity scores. Setting/participants: Adults admitted to three US hospitals with advanced cancer. Principle analytic sample contains 863 patients ( nUC = 637; nPC EARLY = 177; nPC LATE = 49) discharged alive. Results: Cost-savings from early palliative care accrue due to both reduced length of stay and reduced intensity of treatment, with an estimated 63% of savings associated with shorter length of stay. A reduction in day-to-day costs is observable in the days immediately following initial consult but does not persist indefinitely. A comparison of early and late palliative care consultation team cost-effects shows negligible difference once the intervention is administered. Conclusion: Reduced length of stay is the biggest driver of cost-saving from early consultation for patients with advanced cancer. Patient- and family-centred discussions on goals of care and transition planning initiated by palliative care consultation teams may be at least as important in driving cost-savings as the reduction of unnecessary tests and pharmaceuticals identified by previous studies.

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Appointment utilization as a trigger for palliative care introduction: A retrospective cohort study

Palliative Medicine ◽

10.1177/0269216319828602 ◽

2019 ◽

Vol 33 (4) ◽

pp. 457-461

Author(s):

Zlatana Nenova ◽

John Hotchkiss

Keyword(s):

Chronic Kidney Disease ◽

Palliative Care ◽

Cohort Study ◽

High Risk ◽

Kidney Disease ◽

Retrospective Cohort Study ◽

Retrospective Cohort ◽

High Risk Patients ◽

Risk Of Death ◽

Risk Patients

Background: Chronic kidney disease palliative care guidelines would benefit from more diverse and objectively defined health status measures. Aim: The aim is to identify high-risk patients from administrative data and facilitate timely and uniform palliative care involvement. Design: It is a retrospective cohort study. Setting/participants: In total, 45,368 Veterans, with chronic kidney disease Stage 3, 4, or 5, were monitored for up to 6 years and categorized into three groups, based on whether they died, started dialysis, or avoided both outcomes. Results: Patient’s appointment utilization was a significant predictor for both outcomes. It separated individuals into low, medium, and high appointment utilizers. Among the low appointment utilizers, the risk of death did not change significantly, while the risk of dialysis increased. Medium appointment utilizers had a stable risk of death and a decreasing risk of dialysis. Significant appointment utilization (above 31 visits during the baseline year) helped high-risk patients avoid both outcomes of interest—death and dialysis. Conclusion: Our model could justify the creation of a novel palliative care introduction trigger, as patients with medium demand for care may benefit from additional palliative care evaluation. The trigger could facilitate the uniformization of conservative treatment preparations. It could prompt messages to a managing physician when a patient crosses the threshold between low and medium appointment utilization. It may also aid in system-level policy development. Furthermore, our results highlight the benefit of significant appointment utilization among high-risk patients.

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Palliative Performance Scale and survival in patients with cancer and non-cancer diagnoses needing a palliative care consultation: a retrospective cohort study

BMC Palliative Care ◽

10.1186/s12904-021-00773-8 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Patcharaporn Prompantakorn ◽

Chaisiri Angkurawaranon ◽

Kanokporn Pinyopornpanish ◽

Lalita Chutarattanakul ◽

Chanchanok Aramrat ◽

...

Keyword(s):

Palliative Care ◽

Cohort Study ◽

Survival Time ◽

Cancer Patients ◽

Retrospective Cohort Study ◽

Median Survival Time ◽

Retrospective Cohort ◽

Palliative Care Consultation ◽

Care Consultation ◽

Performance Scale

Abstract Background Palliative Performance Scale (PPS) has been frequently used to estimate the survival time of palliative care patients. The objective was to determine the associations between the PPS and survival time among cancer and non-cancer patients in Thailand. Methods This is a retrospective cohort study. All in-patient adults who received a palliative care consultation at Chiang Mai University Hospital between 1 July 2018 to 31 July 2019 were included in the study and were followed-up until 26 June 2020. The Palliative Performance Scale was assessed using the validated Thai-Palliative Performance Scale for Adults. Survival analysis was used to determine the association between the Palliative Performance Scale and survival time among cancer and non-cancer patients. Results Out of 407 patients, 220 were male (54.1%). There were 307 cancer patients (75.4%) and 100 non-cancer patients (24.6%). The PPS and survival time in cancer patients were significantly correlated. Cancer patients with PPS 10, 20, 30, 40–60, and 70–80% had a median survival time of 2, 6, 13, 39, and 95 days, respectively. Non-cancer patients with PPS 10, 20, and 30% had a median survival time of 8, 6, and 24 days, respectively. Conclusions While useful for estimating survival time for cancer patients, other factors should be taken into account in estimating the survival time for non-cancer patients.

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