Complexity in the context of palliative care: a systematic review

Introduction

People receiving palliative care have complex, wide-ranging, and changing needs, including not only physical distress, but also psychosocial, practical, and spiritual difficulties (1). Several conceptual models have been proposed that consider these complexities of palliative care (2-4). For example, Pask et al. used Bronfenbrenner’s ecological systems theory to report the physical, psychological, social, and spiritual domains in addition to the social perspective on care, how patients related to their families and professionals, and how services respond to their care needs (2). Hodiamont et al. also used complex adaptive systems to show that complexity in palliative care consists of three subsystems: patient system (physical, psycho-spiritual, and socio-cultural); social system (characteristics of relatives, roles, relations); team system (structural characteristic, characteristics of team-members, relations); and environmental factors (3).

In addition, complexity in palliative care tools has been created and measured (5). For example, The Australian National Subacute and Non-acute Patient Classification (ANSNAP) and The Hexagon of Complexity (HexCom) (6,7). ANSNAP is an Australian casemix classification, consisting of nine items, including the Phase of Illness, the Resource Utilisation Groups-Activities of Daily Living (RUG-ADL), and the Palliative Care Problem Severity Score (6). HexCom assesses the complexity of a patient’s condition in terms of six domains (clinical, psychological, social, and family, spiritual, ethical, and death-related) and resources (7). These measures of palliative care complexity might distinguish the patients who would benefit most from palliative care (3).

On the other hand, the applicability of these models and tools for palliative care complexity is limited (5). Pask et al. have shown that complexity in palliative care changes with the severity of illness and time (2). Furthermore, healthcare providers’ perspectives on complexity in palliative care differ regarding the degree to which it is perceived as actually complex (4). For example, complexity is not merely the patient’s complex symptoms, but also the degree of dissonance and engagement with healthcare between patients, family, and healthcare providers (2). In addition, inexperienced healthcare providers have difficulty recognizing the complexity of patients in palliative care. If healthcare providers can recognize the factors of complexity in palliative care, they can provide timely, appropriate, individualized, and coordinated care (8,9). Therefore, it is important to summarize what influences complexity in palliative care. In this study, we aimed to integrate and consider the influences on complexity in the context of palliative care. We present the following article in accordance with the PRISMA reporting checklist (available at https://apm.amegroups.com/article/view/10.21037/apm-22-623/rc).

Methods

Design

We used an integrative review, which is a method of compiling, summarizing, and analyzing existing insights of studies “to consider the influences on complexity in the context of palliative care” (10).

Search strategy

We conducted first an electronic literature search in MEDLINE (Ovid), PsycINFO (EBSCOhost), Web of Science Core Collection, and CINAHL (EBSCOhost), examining literature from May 1972 to September 2020 (11). We also used Google Scholar to complement our search for eligible articles. Complexity was an abstract term, and many noncompliant references were detected; hence, a comprehensive and systematic search strategy was developed in consultation with the librarian. The keywords and subject heading terms were “palliative care” and “complexity” (Table 1). Publications were included in this review if the following inclusion criteria were met: (I) considering influences on complexity in the context of palliative care; (II) published in peer-reviewed journals; (III) studies published up to December 31, 2020; and (IV) published in English. We excluded publications from poster sessions, conference proceedings, gray literature, protocols, reports, and letters. We only included peer-reviewed journals listed in scientific databases to help increase the quality in our review.

Titles and abstracts were initially screened by the author (HO) to identify potentially eligible papers, and any areas of uncertainty were resolved by co-author (MM). The full manuscripts of potentially eligible papers were screened by two of the authors (HO, MM), who subsequently reached a consensus after discussing uncertainties regarding any article’s eligibility. Moreover, the third author (MA) was consulted if consensus was not reached, and a definitive list of eligible studies was agreed upon. No additional hand-searching was conducted, but references of the included papers were also screened for any other relevant papers.

Data extraction

We reviewed the data to be extracted according to the Joanna Briggs Institute Reviewer’s Manual (12). The author prepared the extraction form and the co-author checked it. We descriptively extracted data based on the country, study design, methods, type of institution, population, the aim of the study, key findings, and influences on the complexity of palliative care. These data were integrated and mapped using tables. The classification of factors that influence the complexity of palliative care needs was classified by the author (HO) and validated by the co-author (MM). Any disagreements that arose in the classification process were resolved through third-party discussions. Furthermore, we used an inductive approach and identified themes of complexity in palliative care.

Charting the data

We created a form describing the characteristics of each article for charting the data. Two authors (HO, MM) extracted and summarized the data for author/publication date, country, study design, methods, type of institution, population (sample size), the aim of the study, key findings, and influences on the complexity of palliative care.

We refrained from applying a quantitative score to assess the quality of the studies, given the diversity of research methods. Assessing the quality of the study not be appropriate for reviews including different types of studies (10).

Results

From 1,615 initial records, we screened 73 papers according to eligibility, of which 32 were included in the full review (Figure 1). A summary of the characteristics of these 32 studies is presented in Table 2.

Figure 1 PRISMA flow diagram for the integrative review process. PRISMA, Preferred Reporting Items for Systematic reviews and Meta-Analyses.

Research population

The year of publication, country, study methods, type of institution, and population of the 32 studies included in our review are summarized in Table 3. Thirteen of the studies were conducted in medical settings such as palliative care units or hospices (2,4,14,15,20,22,26,28,31,33,37-39), nine were conducted by academic societies or professional teams (7,18,19,23,27,29,30,35,40), and two were conducted over the telephone or at health centers for people living in specific areas (25,32). Other publications were reviews or case studies that did not specify the facility where they were conducted. Eighteen studies were conducted with patients; eleven on adult (14,16,22,23,27,29,30,37,39) and pediatric (13,22,31) cancer patients and seven on non-cancer patients with dementia and neurological diseases (some of the participants included cancer patients) (7,15,32,33,35,38,40). Other studies included a mixed population of healthcare providers, such as doctors and nurses, and family members of the patients, such as daughters and sons (2-4,13,20).

Perceptions of complexity in palliative care

The factors influencing complexity in palliative care are shown in Table 4.

Factors influencing complexity in patients

All 32 studies reported the factors influencing complexity in patients. In the background domain of complexity, the factors were sex (35,40), race (30,38), language (2,3), age (2,23,25,28,30,34,37-39), living situation (2,4,25,32), family burden (2,22,25,28,29,32,34), resources (2,13,14,18-21,26,39), treatment (4,15,16,31,36,40), decision-making (2,17,18,21,26,40), communication (2,4,26,39), prognosis (4,20,23,24,26,28,34), disease (2,4,7,25,28,31,32,35,38-40), and comorbidities/multimorbidity (4,22,23,25,26,28,30,31,33,34,37,38). The factor of age influenced the decrease or increase of complexity in palliative care. Pediatric patients showed greater complexity and more frequently the inability to accept their illness (3). In adult patients, older age was reported to decrease complexity and increase likelihood of acceptance of disease progression and deterioration (2,39). However, older patients have been shown to have increased complexity due to an increased number of comorbidities (28). For example, patients with multimorbidity included progressive diseases such as cancer and heart failure, and psychological disorders such as dementia and schizophrenia (2,4,7,15,31,38). In different studies, multimorbidity ranged from two to five or more diseases, with therapeutic complexity including difficulty managing disease and polypharmacy (4,22,23,25,26,28,30,31,33,34,37,38). Furthermore, factors influencing complexity included disease stage, treatment preferences, and polypharmacy in addition to symptoms (15,19).

In the physical domain of complexity, the factors were physical function (19,22,26,33,34,36,37,39,40), pain (2,4,17,19,22,23,27,29,32,37,40), treatment for pain (16), symptoms (excluding pain) (4,19,22,26,40), and symptom burden (17,21,34,36,37,39). Decline in physical function was consistently reported in all relevant studies (19,22,26,33,34,36,37,39,40). The most reported symptom was pain, along with various other factors such as nausea, dyspnea, fatigue, and appetite (2,4,17,19,22,23,26,27,29,32,37,40). Pain included factors such as numeric rating scale >5 pain, refractory pain, and uncontrolled pain (4,23). In addition, Hemming and Maher reported that different mechanisms for different types of pain and the ineffectiveness of analgesics are factors influencing complexity (16).

In the psychological domain of complexity, the factors were anxiety (23,35,40), depression (23,40), and mental health (20,22,23,34-36,38). Anxiety and depression were reported to be factors influencing complexity in their degree of intensity (23,35). Mental health included factors such as emotional distress, mood disorders, and grief (22,34,36).

In the social domain of complexity, the factors were social status (2,4,7,17,23,32,36,37,39) and financial problems (2,36). Social status included factors such as social roles and family roles (7,17,39). For example, financial problems included factors such as the underestimation of the financial burden of cancer patients and the financial difficulties of day-to-day living when patients are homeless or single mothers (2,36).

In the spiritual domain of complexity, the factors were existential problems (23,26,37) and spirituality (18,36). For example, ethical dilemmas were mainly adaptation of treatment, euthanasia, and requests for medically assisted suicide (23). Spirituality was mentioned in terms of the quality-of-life aspect, and tools were used to measure spiritual distress, but it was not clear as to the definition of this factor (18,36).

Factors influencing complexity in healthcare setting

Fourteen studies reported the factors influencing on complexity in healthcare setting (2,4,7,13,18,20,23-26,32,34,38,39). The factors influencing complexity were healthcare providers’ role (4,13,20,24) and the needs assessments of patients and relatives (13,26,32). For example, the role of the healthcare provider is telling the truth when treatment was unlikely to be effective and the inability to advocate for the patient were factors influencing complexity (13). In addition, differences in the expertise and skills of healthcare providers were factors influencing complexity (24,26).

Factors influencing on complexity in socio-cultural setting

Three studies reported the factors influencing complexity in the socio-cultural settings (2-4). The socio-cultural factors of complexity were societal cultures (2-4) and social capital (2,4). The socio-cultural factors of complexity included social systems and social capital, as palliative care is comprised of interacting with each other, such as patients, families, team members, and other care providers (4). In addition, socio-cultural differences among regions and countries were factors influencing complexity (2).

Interaction of the factors influencing complexity in palliative care

Ten studies reported interactions of the factors (2-4,14,16,34,36,37,39,40). In all studies, patient complexity arose from the interaction of physical, psychological, social, and spiritual factors. Similarly, interactions of patient factors as well as healthcare settings and socio-cultural setting factors influencing complexity were also reported (2,4). Pask et al. also reported that providing palliative care effectively requires consideration of pre-existing, cumulative, and invisible factors (2). Further, Hodiamont et al. reported that elements in palliative care interact at all levels to influence complexity (3). Thus, complexity changes based on dynamic interactions, including non-identifying variables (34). On the other hand, interactions among healthcare providers and between healthcare environments reduced complexity factors (2). Tuca et al. reported that defining criteria of complexity for patients receiving palliative care could assist professionals and nonprofessionals in discussing appropriate care in a multidimensional and multidisciplinary approach (37).

Discussion

In this integrative review, we identified considered the integration of influences on complexity in the context of palliative care. The main findings of the review are as follows: (I) we enhanced our understanding of factors influences on complexity in palliative care; (II) we listed the factors influences on complexity in palliative care.

First, we identified a total of 29 detailed influences on complexity in palliative care, 25 perceptions of the patient, including background and physical, psychological, social, and spiritual; two perceptions in the healthcare setting; and two perceptions in the socio-cultural setting. Our results were similar to Schaink et al. five-part classification of factors that influences complexity for patients with chronic diseases: medical/physical health, mental health, demographics, social capital, and health and social experiences (8). For example, our results were similar to those for the experience of two or more chronic diseases and the use of socioeconomic resources, not just factors related to the disease, as factors influence complexity (8). On the other hand, factors that influence complexity in palliative care in our study included younger age, prognosis, and spirituality. Palliative care covers not only end-of-life care, but also symptom management during the treatment phase, care for family members, and many other aspects, all of which influence complexity in palliative care (41,42). Our review included factors that influence complexity extracted from a variety of methods: quantitative studies, qualitative studies, case studies, and reviews. In addition, our review identified factors of complexity in palliative care, not only for cancer patients but also for non-cancer patients and their families. Factors influence complexity in palliative care change because of the different illness trajectories of cancer and non-cancer patients (43). Regardless of the disease, healthcare providers should need indicators to recognize those who need palliative care. Hence, these complexity influencing perceptions are necessary for patients to receive appropriate palliative care at the right time and for health care providers to conduct a multi-disciplinary team approach.

Second, we listed the factors that influence complexity in palliative care. We additionally modeled perceptions that influence complexity in palliative care with reference to the palliative care complexity framework of Carduff et al. which expands on the patient complexity framework of Schaink et al. (4,8) (Figure 2). Using this model would help inexperienced healthcare providers perceive the factors influences on complexity in palliative care. On the other hand, it may be burdensome for healthcare providers to measure the 29 perceptions we identified in clinical practice. Grant et al. reported six tools in a systematic review of classification systems for determining the complexity of patient care in palliative care (5). For example, Instrument Diagnosing Complexity in Palliative Care (IDC-Pal) is assessed by healthcare providers from the perspective of the patient, family and environment, and health care organization (34). However, no tool covered the factors of complexity that we identified. The perspective of complexity in palliative care that we have identified is necessary because influences on complexity vary with the patient’s situation and according to the experience and skills of the health care providers assessing this complexity (3,4).

Figure 2 Model of complexity in palliative care [figure modified with permission from Carduff et al. (3)].

In addition, the factors influence complexity vary from dynamic and fluid interactions (2-4,34). Therefore, multiple tools collecting data on patients in palliative care would reveal factors that influence on complexity and lead to appropriate care. In the United Kingdom, the outcome assessment and complexity collaborative project (OACC) has combined tools in routine practice to identify patient symptoms and problems in palliative care (44). However, the OACC focuses on complexity at the individual level and lacks factors in the healthcare and socio-cultural setting. On the other hand, natural language processing of medical records might be useful in the context of differing perceptions among healthcare providers. Natural language processing of data linked to community health databases and medical records is beginning increasingly available to identify patients with complex needs for palliative care (45,46). Furthermore, longitudinal prospective data are needed to examine the changes and relationships among factors of complexity over time.

Strengths and limitations

This integrative review followed established systematic methods and investigated factors influences on complexity in the context of palliative care. It reviewed included studies from different countries and socio-cultural regions. However, this review had certain limitations. First, the gray literature was not searched as one of the primary objectives was to map the complexity of the palliative care context with peer-reviewed academic research. Given that this was not a full systematic review, the review protocol was not registered. Second, we did not focus on the patterns of interaction of the various factors of complexity, but we acknowledge that these are important areas and will be the focus of future research. Therefore, our identified influences on complexity may not necessarily be reductive factors to complexity. Finally, we added the identified factors to the previous study model. Our model could help inexperienced health care providers recognize the factors that influence complexity in palliative care and provide appropriate care, in addition to helping them understand the common complexities of multidisciplinary team care. Thus, we do not limit the interpretation of complexity in palliative care. In the future, changes in treatment methods and social circumstances might exclude or add new factors to those we have identified.

Conclusions

Our integrative review integrates and describes the factors of complexity in the context of palliative care. We identified 29 factors influencing complexity and developed a model based on the complexity framework in palliative care. The perspective of the complexity in palliative care that we identified is necessary because what is complex differs from person to person who assesses it. Notably, it is necessary for inexperienced healthcare providers to perceive the factors of complexity for appropriate care planning. Furthermore, longitudinal prospective data are needed to examine the changes and relationships among factors of complexity over time.

Acknowledgments

Funding: This work was supported by Ministry of Health, Labour and Welfare (MHLW) Cancer Research Program (grant No. 19EA101 to MM).

Footnote

Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at https://apm.amegroups.com/article/view/10.21037/apm-22-623/rc

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://apm.amegroups.com/article/view/10.21037/apm-22-623/coif). MM serves as an unpaid editorial board member of Annals of Palliative Medicine from February 2022 to January 2024. MM also reports that this work was supported by MHLW Cancer Research Program (grant No. 19EA1011). The other 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/.

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