A new system could help healthcare providers predict patients with palliative care needs when they are admitted to the hospital.
Although there is a growing need for palliative care to address end-of-life care in an increasingly aging population, the need for palliative care is often overlooked in hospitalized patients, according to a German study in BMC Palliative Care.
The authors concluded that a scoring system they developed helped healthcare providers predict patients with palliative care needs (PCNs) upon their admission to the hospital, allowing physicians to take appropriate therapeutic steps that include pain and symptom management but also attention to psychosocial and spiritual needs.
Palliative care should ideally be implemented as soon as an incurable condition is diagnosed, not only in the imminent terminal phase, the authors point out. The identification of PCNs in hospitalized patients has not been a well-researched area. The goal of the current study was to describe the characteristics of hospitalized patients with PCNs, to identify risk factors for the development of PCNs, to identify risk factors for the development of PCNs, and to develop a score for their identification.
Researchers collected data from 39,849 inpatients for their analysis at the University Medical Center Freiburg. During the study period, 6.9% (2757) of all patients had palliative care needs. Only 56 of them (2%) received palliative treatment. Older patients without relatives who suffered from metastatic cancer and/or liver cirrhosis had the highest risk of developing palliative care needs. The data sampling took place from January 2004 to May 2005, a time period during which the hospital had no specialized palliative care unit.
In order to identify risk factors for developing PCNs and to develop a score to identify the patients with PCNs, the authors conducted a binary logistic regression analysis. The analysis showed that a diagnosis of cancer was the highest risk factor for developing PCNs, with an odds ratio of 3.45. Scoring positive for metastases contributed to an increased risk by a factor of 3.29. The third greatest risk factor was dementia, followed by HIV and liver cirrhosis. A high level of care at admission was a highly significant risk factor for PCNs.
The final model they devised to identify PCNs has a sensitivity of 0.815 and a specificity of 0.640. Thus, approximately 81.5% of all patients with PCNs would be correctly identified as such, and 36% of all patients without PCNs would be incorrectly identified as having PCNs.
“Our predictive score contributes to the identification of palliative care needs in patients with life-limiting diseases, which allows physicians to take the appropriate therapeutic steps,” the authors concluded.