Palliative care organization and staffing models in residential hospices: Which makes the difference?. (February 2022)

• Record Type: Journal Article
• Authors: Artico, Marco; Piredda, Michela; D'Angelo, Daniela; Di Nitto, Marco; Giannarelli, Diana; Marchetti, Anna; Facchinetti, Gabriella; De Chirico, Cosimo; De Marinis, Maria Grazia
• Is Part Of: International journal of nursing studies. Volume 126(2022)
• Publication Date: 2022-02
• Subjects: Hospice -- Palliative care -- Staffing -- Workforce -- Quality of health care -- Prospective studies -- Terminally ill patients -- Logistic models; Nursing -- Periodicals; Nursing -- Periodicals; Soins infirmiers -- Périodiques; Nursing; Periodicals; 610.73
• DOI: 10.1016/j.ijnurstu.2021.104135
• Languages: English
• ISSNs: 0020-7489

Abstract

Abstract: Background: The number of patients using palliative care services, particularly residential hospices, is increasing. Policymakers are urging these services to reflect on the most effective organizational strategies for meeting patients' complex care needs. Aim: To analyze the predictive power of staffing, structure and process indicators towards optimal control of patients' clinically significant symptoms over time. Design: Secondary analysis of data from a multicentre prospective longitudinal observational study (PRELUdiHO) collected between November 2017 and September 2018. Setting/participants: Adult patients ( n = 992) enrolled in 13 Italian residential hospices. Methods: Two generalized estimating equations logistic models were built, both with number of hospice beds and length of stay as independent variables as well as, in one case, patient-to-healthcare worker ratios, and, in the other, health professionals' qualification levels. Dependent variables were six not clinically significant (score<4) symptoms: pain, nausea, shortness of breath, feeling sad, feeling nervous, and 'how you feel overall', according to the Edmonton Symptom Assessment System revised (ESAS-r) scale. Results: The generalized estimating equations indicators on staff revealed the following 'optimal' model: Patient-to-Physician ratio (5.5:1–6.5:1); Patient-to-Nurse ratio (1.5:1–2.7:1); Patient-to-Nurse-Assistant ratio (4.1:1–6.3:1); with the most balanced staff composition including 19% physicians, 23% nurse assistants, and 58% registered nurses; hospice beds (12–25); length of stay (median = 12 days). This model predicted an up to four times greater likelihood of controlling all six ESAS-r symptoms over time. The generalized estimating equations model on the educational level of physicians and registered nurses showed that it was significantly associated with optimal patients' symptom control during the entire hospice stay. Conclusions: This study showed the exact skill-mix composition and proportions of palliative care team able to ensure optimal control of patients' symptoms. The added value of physicians and nurses with a qualification in palliative care in terms of better patient outcomes reaffirmed the importance of education in guaranteeing quality care. Hospices with 12–25 beds, and recruitment methods guaranteeing at least 12-day stay ensured the most propitious organizational environment for optimal management of clinically significant symptoms. The transferability of these results mainly depends on whether the skills of health professionals in our `ideal' model are present in other contexts. Our results provide policymakers and hospice managers with specific, evidence-based information to support decision-making processes regarding hospice staffing and organization. Further prospective studies are needed to confirm the positive impact of this 'optimal' organizational framework on patient outcomes.