Additional resources are required in the care of complex palliative patients

With the expansion of palliative care programs over the course of the last 3 decades comes better access to highly individualized complex end of life care. The majority of United States hospitals now offer specialized palliative care programs, including 72% of hospitals with over 50 beds and 90% of hospitals with over 300 beds, indicating that many complex end of life patients can now be offered a whole host of dynamic and supportive services (1,2). In properly selected patients, a palliative care consultation results in a highly valuable and high impact intervention (3,4). In fact, early palliative care in metastatic non-small cell lung cancer patients has been demonstrated to result in not only improved quality of life but also prolonged overall survival (5). However, palliative care providers are a finite resource, and in many instances a patient’s primary practitioners are adept at providing end of life care (6). Given the limited resource of specialized palliative providers, it is imperative to identify which patients require the care of a specialized palliative team, and which patients may be at risk for disengagement from these specialized services.

Cerullo et al. aimed to explore the definition of complexity and the available instruments that can be utilized to objectively identify complex end of life patients (7). A better understanding of patient complexity as it relates to end of life care can ultimately lead to early identification of those patient that require highly specialized palliative care as well as those patients that will necessitate special resources and attention in order to reap the benefits of that care. The authors included 15 studies examining 13 instruments to define patient complexity. These instruments explore the interplay between patient, family, healthcare system, and socio-culture domains and how they affect the delivery of end of life care. The study highlights how end of life patient’s needs are dynamic and as such provides must maintain high degree of plasticity to meet the needs of complex patients.

Identifying complex patients is especially critical when considering operative intervention to address especially severe symptoms of advanced cancers. Here, the risk profile is such that in the incorrectly identified patient, a palliative intervention could easily result in a significant determinant to the patient’s quality of life (8). We have previously explored this particular patient population looking for predictors of poor patient satisfaction following palliative intent operations (9). Approximately 18% of patients reported poor satisfaction following their operation, despite 92% of these patients achieving symptom improvement and 75% of patients recovering from surgery without complication. Comparatively, of those patients with good satisfaction, only 85% achieved symptom improvement with a comparable morbidity profile. Only about a quarter of these patients had palliative care consults, with the majority of patients receiving primary palliative care from their surgeon.

Interestingly, poor family engagement and the resulting lack of social support were independently correlated with poor patient satisfaction following their operation (9). These results are congruent with the current authors’ findings that family domains play a critical role in determining patient complexity (7). Consistent with these data is the concept of the palliative triangle, a long-established tool in optimizing patient selection and counseling for palliative surgery (10). The three points of the triangle are the patient, the family, and the surgeon. This model establishes that optimal patient and procedural selection can be achieved by weighing the patient and their family’s symptoms, goals, and values against the medical and surgical options available (11). In essence, palliative surgeons have de facto identified complex patients requiring special attention and counseling for the past 20 years. However, they have lacked the objective measures to approach the situation more analytically.

The authors point out that perhaps objective screening tools tracked over time to recognize highly complex patients could be implemented to aid in the recognition of patients who will require additional support around their palliative intervention in the form of a palliative care consult (7). This strategy would be in line with other efforts that have been successful to this point in identifying at-risk patients through patient-reported outcome measures (12).

While identification of these patient is a necessary step, it is important to recognize that simply distinguishing a distinct patient population is not enough. Dividing patients into cohorts alone will not achieve any meaningful change without a predetermined intervention, though unfortunately this is the trend in the current research landscape. Chen et al. performed a systematic review of articles investigating the routine use of patient-reported outcome measures in cancer patients (13). They included 27 articles in their analysis. They note that there is a strong body of evidence that routine screening tools improves communication, patient satisfaction, and the detection of unrecognized problems. However, the evidence for change in patient management, improvement in health outcomes, effect on quality improvement, and better system performance is either poor or not reported. In fact, 10 of the 27 studies did not mention changes in patient management at all. Once complex patients are identified, through patient or provider report metrics, it will be important that providers take the next step in studying interventions in a systematic and evidence-based manner to ensure a change in clinical outcomes.

In summary, Cerullo et al. (7) provide an interesting and comprehensive review of the tools available for objectively identifying complex end of life patients that may require additional interventions and support. They point out that it is critical to be able to dynamically track patient complexity in order to optimize the intensity of palliative interventions to best match with the patient current condition. These concepts would be of particular importance for patients undergoing palliative surgery where surgeons often provide primary palliative care and can be used as a trigger for engaging a more multidisciplinary approach. In order to fully realize the potential of defining patient complexity, the investigators will need to study interventions to improve outcomes in highly complex patients.

Acknowledgments

Funding: None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Annals of Palliative Medicine. The article did not undergo external peer review.

Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at https://apm.amegroups.com/article/view/10.21037/apm-23-281/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Dumanovsky T, Augustin R, Rogers M, et al. The Growth of Palliative Care in U.S. Hospitals: A Status Report. J Palliat Med 2016;19:8-15. [Crossref] [PubMed]
2. Rogers M, Meier DE, Morrison RS, et al. Hospital Characteristics Associated with Palliative Care Program Prevalence. J Palliat Med 2020;23:1296-9. [Crossref] [PubMed]
3. Cohen JT, Fallon EA, Charpentier KP, et al. Improving the value of palliative surgery by optimizing patient selection The role of long-term survival on high impact palliative intent operations. Am J Surg 2021;221:1018-23. [Crossref] [PubMed]
4. Cohen JT, Miner TJ. Patient selection in palliative surgery: Defining value. J Surg Oncol 2019;120:35-44. [Crossref] [PubMed]
5. Temel JS, Greer JA, Muzikansky A, et al. Early palliative care for patients with metastatic non-small-cell lung cancer. N Engl J Med 2010;363:733-42. [Crossref] [PubMed]
6. Thomay AA, Jaques DP, Miner TJ. Surgical palliation: getting back to our roots. Surg Clin North Am 2009;89:27-41. vii-viii. [Crossref] [PubMed]
7. Cerullo G, Videira-Silva A, Carrancha M, et al. Complexity of patient care needs in palliative care: a scoping review. Ann Palliat Med 2023;12:791-802. [Crossref] [PubMed]
8. Hofmann FO, Miksch RC, Weniger M, et al. Outcomes and risks in palliative pancreatic surgery: an analysis of the German StuDoQ|Pancreas registry. Bmc Surg 2022;22:389. [Crossref] [PubMed]
9. Cohen JT, Beard RE, Cioffi WG, et al. Was It Worth It? Critical Evaluation of a Novel Outcomes Measure in Oncologic Palliative Surgery. J Am Coll Surg 2023;236:1156-62. [Crossref] [PubMed]
10. Miner TJ, Jaques DP, Shriver CD. A prospective evaluation of patients undergoing surgery for the palliation of an advanced malignancy. Ann Surg Oncol 2002;9:696-703. [Crossref] [PubMed]
11. Miner TJ, Cohen J, Charpentier K, et al. The palliative triangle: improved patient selection and outcomes associated with palliative operations. Arch Surg 2011;146:517-22. [Crossref] [PubMed]
12. Tjong MC, Doherty M, Tan H, et al. Province-wide analysis of patient reported outcomes for stage IV non-small cell lung cancer. Oncologist 2021;26:e1800-11. [Crossref] [PubMed]
13. Chen J, Ou L, Hollis SJ. A systematic review of the impact of routine collection of patient reported outcome measures on patients, providers and health organisations in an oncologic setting. BMC Health Serv Res 2013;13:211. [Crossref] [PubMed]