Validation of a questionnaire to assess complexity of palliative care needs in primary care in Malaga, Spain: a study protocol

Abstract

Introduction

The needs of patients in palliative care (PC) are multiple and changing. Several tools assess them, but there is a lack of homogeneity among them. A specific diagnostic tool to assess complexity in PC (IDC-Pal: Instrumento Diagnóstico de la Complejidad en Cuidados Paliativos, in Spanish) was created in community and hospital settings with 36 items to diagnose PC complexity, but its application in primary care is difficult.

Aims

(1) To generate an adapted version to primary care of the IDC-Pal tool to identify and stratify PC complexity in the adult population. (2) To determine face, content, criterion and construct validity and reliability of the new instrument.

Methods and analysis

There are three phases of clinimetric cross-sectional observational validation study: Phase 0: Review of the original tool structure suitability for its use in primary care setting by a committee (researchers and the original developer team). Phase 1: Expert consensus phase by Delphi technique with physicians, nurses and social workers from primary care and PC. Phase 2: Empirical validation of the resulting tool in primary care using a cross-sectional descriptive design involving physicians and case manager nurses from across Andalucia, who will recruit adult patients with PC needs from healthcare centres that accept to participate in the study. Reliability (Cronbach’s alpha, McDonald’s omega, interclass correlation coefficient) and construct validity (exploratory factor analysis) analysis will be carried out; convergent criterion validity will be assessed with the NEC-PAL (Necesidades Paliativas Questionnaire, in Spanish) instrument. Differences by gender, type of professional and place where it is administered will be explored. Interobserver reliability analyses will be carried out using intraclass correlation coefficient, Bland-Altman plots and concordance analysis. Phase 0–1 results were expected by 2025 and Phase 2 results by 2026. Reporting method: CRISP checklist. This protocol was conducted without patient or public participation.

Ethics and dissemination

This study evaluates a novel, co-designed tool to diagnose PC complexity to inform practice recommendations for a more efficient allocation of resources that may be included in future clinical practice guidelines. The study has been approved by the Provincial Research Ethics Committee of Málaga as of July 2023 and will be conducted in accordance with the principles established in the Declaration of Helsinki, the Council of Europe Convention on Human Rights and Biomedicine, and the requirements established in Spanish legislation. The study conforms to the norms of good clinical practice. All participants in the Delphi study must express their agreement to participate in the survey by providing informed consent (IC) before beginning the questionnaire. For the development of Phase 2, the primary care professionals who agree to participate will sign a researcher commitment, and the patients included in the study will sign a written IC before the data collection. Dissemination of the results will inform future research on the appropriate diagnosis of PC complexity in the primary care setting, which is of paramount importance due to its gatekeeper position. Dissemination will be aimed at academics and healthcare professionals through publications, presentations and training workshops on the use of the diagnostic tool.

STRENGTHS AND LIMITATIONS OF THIS STUDY.

• Adapting an existing tool to the primary care context will help physicians better identify patients eligible for palliative care (PC).

• The developed instrument will not be limited to cancer patients, which will open the spectrum to any patient eligible for PC.

• Because of the very nature of the palliative population, it is expected to find a wide variety of clinical situations in the descriptive study.

• The descriptive cross-sectional study of the empirical validation will prevent the evaluation of responsiveness.

Introduction

Palliative care (PC), according to the consensus definition of the International Association for Hospice and Palliative Care (IAHPC)¹ and the National Consensus Project for Quality Palliative Care,² is the active, holistic and comprehensive care of people of any age, diagnosed with a serious illness, oncological or non-oncological in nature, and those nearing the end of life. This definition is in line with the one offered by the WHO.³

Nearly 57 million people have palliative needs and, of these, 25.7 million are in their last year of life.⁴ Increased life expectancy, changing causes and conditions leading to death, as well as improved living conditions in developed countries, have led to a change in the epidemiology of disease and death. In addition, changing family structure, economic crisis, unequal distribution of resources and rising health costs are resulting in vulnerable social groups with limited access to clinical care.⁵

Most patients in PC also have multimorbidity. It is estimated to be 30% prevalent in people under 65 years of age and 55% to 98% prevalent in people over 65 years of age.⁶ Such patients often require prolonged follow-up for symptom control, which is carried out in the primary care setting. This continuum of care, due to multimorbidity, poses a major challenge for health systems around the world.⁷

One of the main challenges is related to the identification of patients with advanced diseases and unmet needs who could benefit from access to specialised PC. The primary care setting would seem the best place to carry out this screening due to its accessibility.⁸ In many countries, primary healthcare (PHC) acts as the gatekeeper of the healthcare system. Professionals working at this level treat patients in the most diverse clinical situations and have the responsibility of detecting patients eligible for PC. Several screening tools for the identification of patients with advanced progressive diseases who are likely to have PC needs in PHC have been described⁹; most of them use the prediction of death or deterioration of the patient, or both, to extrapolate the identification of people with unmet palliative needs (online supplemental table 1).

Nevertheless, knowing that diseases follow different trajectories of decline,¹⁰ the needs that arise may be very different. Therefore, identification cannot be based on predicting mortality or deterioration alone but requires refining tools to detect changes when they occur.

Complexity, in the field of PC, has been the subject of study for more than a decade, and although numerous authors have tried to synthesise and analyse the existing definitions, there is no unified definition yet. Consequently, complexity has been considered as a dynamic state in which clinical, personal and social aspects interact to hinder care, with accumulation of these factors over time, interacting in an incipient and cyclical manner.¹¹ Some authors point out a mismatch between the needs of the patient with multimorbidity and the capacity of health services to respond to them.¹² More recently, complexity has been considered as a trait or attribute that implies greater tendency to clinical instability, uncertainty in the outcome of a health intervention and need for intensified support measures from specialised PC teams.¹³

Zullig et al¹⁴ analysed six conceptual frameworks that addressed the construct of patients’ complexity, considering different health determinants (medium and long-term health outcomes, hospital admission episodes or acute health crises) to shape the concept. But all these models show knowledge gaps, and the authors propose a new approach named the Cycle of Complexity. This new model includes interpersonal, organisational and community factors with a concrete value at the present time and considering that each of them can change over time.

In the process of defining the complexity construct, several tools have also emerged to identify and stratify this attribute in both hospital and PHC settings. However, there is a lack of homogeneity in terms of variables included, objective of their prediction (deterioration of the patient, death) and clinimetric characteristics. Furthermore, they have very wide ranges in both sensitivity and specificity, demonstrating that the validation and standardisation process is not robust.

Grant et al¹⁵ analysed six tools. All seek to stratify patients, although some focus on complexity of care, others on resource utilisation or the need for referral to a specialised PC team (online supplemental table 1).

Currently, there are no instruments adapted to be used in the PHC setting with proven stratification capacity and adequate predictive validity. The availability of a standardised tool, with a robust validation process, capable of properly identifying patients with PC needs would increase the probability of receiving timely and individualised care.

The IDC-Pal instrument (Instrumento Diagnóstico de la Complejidad en Cuidados Paliativos, in Spanish) was developed to assess complexity in PC in 2008 in Andalucia16,18 and has been included in the Andalusian clinical protocol of care for patients in PC situation since 2019.¹⁹ This instrument consists of 36 items, grouped into six domains, three related to the patient’s situation (background, clinical situation and psycho-emotional situation), two related to the health organisation (professional/team and resources) and one regarding the family and environment. Each of them is categorised as complex or highly complex, recommending different levels of service provision, according to the resulting complexity level of the case (non-complex, complex or highly complex).²⁰

The IDC-Pal tool has been validated on a national basis and has shown high usability and accuracy to inform decision-making in different settings of the health service, mainly regarding the PC support teams.21,26 Along with it, this tool has also been translated and adapted to other languages in European countries.^{27 28} For all of the above reasons, this instrument is considered to be an excellent starting point to generate a tool adapted to the PHC context.

The objectives of this study are as follows: (1) to generate an adapted version of the original IDC-Pal tool for its use in PHC setting (IDC-PAL-AP) to identify and stratify complexity in adult population candidates to receive PC; (2) to determine the face and content validity of the new instrument; and (3) to evaluate reliability, criterion and construct validity of the resulting tool.

Methods analysis

The checklist from the Consensus Reporting Items for Studies in Primary Care (CRISP Statement) will be used to guide the reporting of the study²⁹ (online supplemental table 2).

Study design

This clinimetric, cross-sectional observational validation study comprised the following phases (figure 1): Phase 0: The review and consensus phase on the structure of the original IDC-Pal tool is planned as a series of synchronous online meetings between the developers of the original tool (IDC-Pal) and the current research team in charge of the development of the PHC version of the tool. The participants in these meetings are all experts in the field of knowledge of PC and PHC research methodology. This type of meeting between experts allows them to discuss previous ideas/statements (wording of the items of the original IDC-Pal tool and the corresponding glossary), to modify them, to create new ones if deemed necessary and to decide/vote on the final composition of the contents of the tool that will continue to be refined in the following phases of the study. As many meetings as necessary will be planned to arrive at a consensus version of the new version of the IDC-Pal diagnostic tool for application in the adult population in the PHC setting.^{30 31} The measurement scale, the glossary and the option of unifying existing items and/or creating new ones will be reviewed. The resulting tool will be named the IDC-Pal-AP tool. Phase 1: Expert consensus phase, by means of a panel of experts (professionals from PHC and PC specialised teams) and Delphi technique. The Delphi technique will be done in two preplanned consecutive rounds through the online platform LimeSurvey V.5.3.26. Each round will be followed with the corresponding feedback from the previous round. Invitation to participate will be sent by email, after telephone contact with the experts. The system allows for monitoring of responses with the possibility of periodic reminders in case of non-response. Experts will be asked to give their judgement on the pertinence of each element of the IDC-Pal-AP tool and their explanatory glossary. They shall also assess the comprehensibility (clarity) of the wording of each element of the tool. Consensus in each round will be established by identifying median scores and dispersion through IQRs.³² Phase 2: Empirical validation phase of the proposed version (IDC-Pal-AP) in a sample of patients with chronic conditions from healthcare centres, by PHC professionals using a cross-sectional descriptive design.

Figure 1. Flow diagram of the study phases. IDC-Pal-AP, adapted version of the original IDC-Pal (Instrumento Diagnóstico de la Complejidad en Cuidados Paliativos, in Spanish).

Eligibility criteria

Study subjects

Phase 0: Members of the multidisciplinary research team of the IDC-Pal project (PC physicians, nurses and researchers, including professionals from the team that developed the original IDC-Pal tool) will be included as experts in PC, in the diagnostic tool under study and in the application of consensus techniques in the field of research. Phase 1: PHC professionals with a minimum of 5 years of healthcare experience will be recruited, proportionally balanced by their representation in PHC teams between physicians, family nurses, case management nurses and social workers. The selection will be made by opportunistic sampling among the health centres of the province of Málaga (Spain). They will be invited to participate by the CUDECA Foundation, the Multiprofessional Teaching Unit of Family and Community Care of the Primary Care Malaga-Guadalhorce District and the Faculty of Health Sciences of the University of Malaga. Professionals with expertise in PC (clinical practice in PC units for at least a period of 2 years, complemented or not with specialised health training, Master’s or University specialisation) will also be invited, also balanced between physicians, nurses and social workers. Phase 2: Family physicians working in the health centres of the province of Málaga (Spain) will be contacted. Those who sign the researcher’s commitment will recruit patients treated in the Primary Care Service portfolio; on the one hand, those identified in the electronic medical records to receive PC according to the criteria defined in the Andalusian PC Integrated Care Process,¹⁹ and on the other hand, patients included in Home Care provided by PHC teams. Also, patients are seen in consultations on demand. Recruitment of primary care professionals is planned for 2025. A training session on complexity in PC and the study protocol will be held on 27 May. Patient data collection will last approximately 1 year, from June 2025 to June 2026. In this phase, family physicians will be recruited to participate as clinical researchers in this project, so they must sign their commitment to participate with the research team. Each physician will decide which of their patients will be included in the study considering the following criteria. The inclusion criteria will be as follows: male and female patient over 18 years of age, with a diagnosis of an oncological or non-oncological disease (advanced chronic non-cancer-related disease with non-reversible progression, limited life prognosis and complex needs affecting their quality of life, eg, advanced heart failure, chronic obstructive pulmonary disease, chronic end-stage renal disease and degenerative neurological diseases),³³ attended in the Primary Care Service portfolio (PC Integrated Care Process, Home Care, consultation on demand). Patients who do not agree to participate in the study, institutionalised patient (as institutionalisation has been associated with several negative outcomes such as increased mortality, reduced quality of life; thus, producing a heterogeneous sample to validate the tool³⁴), or those with insufficient data in their clinical records to complete the variables required in the study, will be excluded.

Once included, patients will be evaluated only one time to assess their clinical, personal, family and social situation at that time and apply the IDC-Pal-AP tool, based on the most recent consultation done by their family physician.

An interobserver validity will be conducted in the first subset of 60 study subjects by performing a blinded-parallel assessment by a case management nurse. If the inter-rater agreement is over accepted values, these nurses will also recruit successive patients. Each patient will be informed about the study objectives and characteristics, and if they agree to participate, they will be asked to sign a written informed consent (IC).

Study sample

Phase 0: The sample size consisted of the current research team (seven professionals) and the complete developer team (three professionals) of the original IDC-Pal tool. Phase 1: The target sample size for the Delphi study has been defined as a total of 50 professionals with a majority distribution of end users of the tool in PHC, and with representation of the main professional roles that integrate the teams in the health centres and in the multidisciplinary PC teams. The recommended number of panellists depends on the objectives of the study, with a general recommendation of 10 to 15 participants or higher depending on the study objectives.^{30 35} In our case, the team decided on a higher number of participants, in line with studies such as the one developed for the ACCORD guideline,^{31 35} and taking into account the potential loss of subjects during the rounds necessary to reach consensus. Phase 2: The sample size for PC patients has been calculated considering a power of 90%, an alpha error of 5% and an average size of the cluster of 5 patients per physician. Considering the degree of correlation between the individuals in the cluster (intraclass correlation coefficient (ICC)),³⁶ a design effect of 1.08 and a loss rate of 8%, the final sample size required is 300 patients.

Data collection procedure

Phase 0: Meetings of the research and development team with a working script for the exhaustive review of each item originating from the IDC-PAL tool, with decisions taken by consensus regarding its elimination, modification, change of the measurement scale and change of the glossary corresponding to the item. Phase 1: Expert consensus by means of a panel of experts (professionals from PHC and PC specialist teams) and Delphi technique. The Delphi technique³² will be done through the online platform LimeSurvey V.5.3.26. The method of rounds described above will be followed with the corresponding feedback in each round. Invitation to participate will be sent by email, after telephone contact with the experts. The system allows for monitoring of responses with the possibility of periodic reminders in case of non-response. Phase 2: Family physicians and nurse case managers working in the health centres of the province of Málaga (Spain) will be contacted. They will be informed of the study and invited to participate. The professionals who accept will sign the researcher’s commitment and will receive training on the development of the study and on Good Research Practices. Then, each physician (and nurse case managers if inter-rater reliability is optimal) will recruit patients within his or her quota of PC patients who meet the inclusion criteria and will fill in the IC. The healthcare professionals will carry out an assessment of the patient’s clinical situation (at the time and place of recruitment or at a deferred time of no more than 4 weeks since the clinical encounter, due to the potentially changing situation of these patients) and, together with the data from a patient’s electronic medical record, will complete the items of the IDC-Pal-AP tool and the rest of the variables.

Outcomes measures

In Phase 0, a consensus methodology will be carried out through discussion and debate on potential changes to be included in the original complexity assessment tool, IDC-Pal. The expected outcome will be a questionnaire with a smaller number of items and with modifications and actualisations of the initial glossary. For Phase 1, pertinence (on a scale of 1 to 9) and comprehensibility/clarity (on a scale of 1 to 5) will be considered as outcome measures, and in Phase 2, different outcome measures will be considered according to the aims established (table 1).

Table 1. Outcome measures for Phase 2.

Variable	Values	Data source
IDC-Pal-AP tool content	Each question, according to final scale	At the time of filling in tool
Place of IDC-Pal-AP’s administration	1. Healthcare centre; 2. Home; 3. Other
Time of administration	Measured in minutes
Age	Years at the time of data collection	Medical records
Gender	1. Male; 2. Female; 3. Others
Civil status	1. Single; 2. Married; 3. Divorced; 4. Widowed; 5. Other
Country of origin	1. Spain; 2. European Union (EU); 3. UK; 4. Non-EU countries
Level of education	1. No education; 2. Primary education; 3. Secondary education; 4. Higher education
Profession	1. Healthcare professional; 2. Non-healthcare professional
Spoken language	1. Native Spanish; 2. Fluent Spanish; 3. Does not understand Spanish
Family structure	1. Lives alone; 2. Lives with family member (caregiver); 3. Lives with family (non-caregiver)
Informal caregiver	1. Yes; 2. No	At the time of filling in tool
Patient with previous caregiver role	1. Yes; 2. No	Medical records
Comorbidities	Recording of diseases in medical records and subsequent categorisation
Multimorbidity	Recording the number of simultaneous chronic conditions
Previous mental illness	1. Yes; 2. No
Addictions	1. Active addition; 2. Ex-addict; 3. No previous addictions
Current patient treatment	Recording of medicines in medical records and subsequent categorisation
Condition that generates the situation of PC	1. Cancer; 2. Respiratory disease; 3. Liver disease; 4. Heart disease; 5. Neurological disease; 6. Degenerative condition; 7. Other
Level of patient autonomy	Barthel Scale48
NEC-PAL Surprise Question	1. Yes; 2. No	At the time of filling in tool
Advanced care directive	1. Yes; 2. No	Question the family directly
Has the patient been hospitalised in the last 6 months?	1. Yes; 2. No	Medical records
Reason for hospitalisation	1. Flare-up of known symptom; 2. Emergence of new symptom; 3. Flare-up of known chronic condition; 4. Acute event (fall, accident, stroke); 5. Other; 6. Not applicable

IDC-Pal-AP, adapted version of the original IDC-Pal (Instrumento Diagnóstico de la Complejidad en Cuidados Paliativos, in Spanish); NEC-PAL, Necesidades Paliativas Questionnaire, in Spanish; PC, palliative care.

Two main aspects will be used for the Delphi study, pertinence and comprehensibility (clarity). Each panellist will be asked to rate the pertinence of the item to be included in the tool on a scale from 1 (strongly disagree) to 9 (strongly agree) and to rate the comprehensibility (clarity) of the statement on a scale from 1 (totally incomprehensible) to 5 (very easy to understand). The glossary agreed on in Phase 0 will be available by hovering over each item to help the panellist better understand each element of the IDC-Pal-AP tool.

In Phase 2, the family physician will collect the final items of the IDC-Pal-AP questionnaire according to the decided scale, which will lead to a classification of the complexity of each of the patients included in the study. Information will also be collected on other sociodemographic variables of the patient such as age, gender, country of origin and native language, civil status, level of education, profession, family structure, the existence of a current informal caregiver, whether the patient had a caregiving role before becoming ill, the illness that has motivated the need for PC, clinical history (comorbidities, multimorbidity, mental health problems, addictions, previous hospitalisations in the last 6 months and reasons for these), current treatment and level of autonomy using the Barthel Index score. The existence of an Advance Care Directives document will also be assessed. The professional will be asked to answer the NEC-PAL Surprise Question³⁷ (Would you be surprised if this patient died within the next year?) regarding the expected evolution of the patient, as well as the place and time of administration of the IDC-Pal-AP tool.

Analytical methods

Phase 0: Modifications to the IDC-PAL tool and the creation of the first version of the IDC-PAL-AP tool will be adopted by debate and consensus during meetings of the research group and the original tool development group. Phase 1: As for consensus and stability, among the different quantitative measures reported, we will select the IQRs as a measure of choice, due to their robustness as a statistical measure.³⁵ Analysis of the median scores of the experts will be carried out, together with the IQR obtained. Percentiles above 75% will be considered as agreement in median ranges 1–3 or 7–9 in the case of pertinence; and 1–2 or 4–5 in the case of comprehensibility (clarity); and those medians included in range 4–6 for pertinence or 3 for comprehensibility (clarity) will be submitted to a new round of consensus, with the corresponding feedback. IQRs above 3 will also be considered as a measure of dissent, and those items will be submitted to a new round. Phase 2: Descriptive statistics will be used with measures of central tendency and dispersion and exploratory analysis to assess the normality of distributions, in addition to the Kolmogorov-Smirnov test. Reliability analysis will be carried out using Cronbach’s alpha and McDonald’s omega, as well as interobserver reliability using the ICC. The homogeneity index and the corrected homogeneity index in the case of problematic items will also be calculated. These calculations will be carried out differentiated by each subscale of the instrument. Construct validity will be assessed by means of exploratory factor analysis, with principal axis analysis approach due to a likely non-linear distribution and orthogonal and non-orthogonal rotations, after checking for sphericity and Kaiser-Meyer-Olkin. Since we expected a polytomous scale with three values, factor analyses will be carried out using polychoric correlation matrices. Confirmatory structural analysis will be carried out to test the final construct structure and the following adjustment indices will be used: penalising function ($x^2$/df) >3; RMSEA (root mean square error of approximation) <0.08 and its 90% CI; CFI (Comparative Fit Index) and TLI (Tucker-Lewis Index), with minimum values of good fit ≥0.90. Multivariate normality and kurtosis will also be calculated. Convergent criterion validity will be assessed with the NEC-PAL Surprise Question. Bivariate analyses will be carried out according to the nature and distribution of the variables, to evaluate possible differences by gender, type of professional, place where it is administered, etc. To this end, parametric or non-parametric mean difference tests will be carried out, depending on the distributions and groups compared (Student’s t, Mann-Whitney U, ANOVA (analysis of variance), Kruskal-Wallis), χ² test for qualitative variables, as well as Spearman’s correlations for quantitative variables. Interobserver reliability analyses will be carried out using ICC, Bland-Altman plots and concordance analysis.

Ethics and dissemination

The study has been approved by the Provincial Research Ethics Committee of Malaga (27 July 2023) and will be conducted in accordance with the principles established in the Declaration of Helsinki, the Council of Europe Convention on Human Rights and Biomedicine, and the requirements established in Spanish legislation. The study conforms to the norms of good clinical practice (art. 34 RD 223/2004; Community Directive 2001/20/CE) and the provisions of Regulation 2016/679 of the European Parliament and of the Council of April 27, 2016 on Data Protection (GDPR). All participants in the Delphi study must express their agreement to participate in the survey by providing IC before beginning the questionnaire. For the development of Phase 2, the Primary Care professionals who accept to participate will sign a researcher commitment, and the patients included in the study will sign a written IC before the data collection.

As part of our results dissemination plan, the research team will participate in congresses and scientific conferences to share the results of phases 0 and 1 during the year 2025, and as part of the start of Phase 2, a kick-off conference will be organised for clinicians participating in the study, where the results will be disseminated and an information pill on Good Research Practices will be given. During 2026, the team will continue its efforts to disseminate the results of Phase 2 once recruitment and data analysis are completed. The team is also considering organising workshops for primary care professionals at the end of Phase 2 to disseminate the final study results and to train them in the use of the new tool to obtain further results in real settings that allow refining the tool’s clinimetric parameters.

Discussion

This article describes the development and validation procedure of a diagnostic tool to identify and stratify the complexity of PC adult patients in the PHC setting, based on a previous tool widely used in the field of specialised PC in Spain.

It has been established that an early PC intervention can improve the quality of life of patients living with advanced disease,^{9 38} and it is even more relevant in the last year of life.³⁹ Thus, PC is an essential activity within the work of the PHC team. The working group of the Spanish Society of Family and Community Medicine has published a working document⁴⁰ in which they define 14 actions that should not be neglected by the PHC team in this field, like establishing a training plan in PC for the PHC team; systematically identifying patients with palliative needs and carrying out a multidimensional assessment; planning adequate symptom control; considering the appropriateness of prescribing and deprescribing when necessary; initiating advanced decision planning; or following up with the family during the grieving process.

PHC seems the adequate setting for an early detection of important milestones in the continuum of PC, such as the identification of patients who are candidates for PC, and trigger assessment and care planning.⁴¹ To that end, the PHC professional must have a good classification tool with sufficient capacity for a correct categorisation of patients, ideally with high sensitivity and specificity. In 2013, Maas et al⁴² conducted a study to document identification tools available in scientific literature and to ascertain how PHC professionals in Europe identified PC patients. The authors concluded that none of the tools identified at the time were validated or widely implemented in Europe.

A systematic review carried out by ElMokhallalati et al in 2020⁹ identified 10 screening tools to be applied in the PHC setting, but only 5 reported accuracy data; and among them, the sensitivity and specificity values varied considerably, ranging from 3.2% to 94% and 26.4% to 99%, respectively, depending on the study population, with higher values in studies that enrolled participants with advanced progressive diseases.

Another important aspect of effective and quality PC is addressing the elements that modify the complexity of the clinical situation. These elements result from the interaction of multiple factors and include the personal, social and institutional environment in which patients live and receive clinical care. Again, the PHC professional will need accurate instruments to be able to identify and stratify complexity. This is even more challenging due to the ever-changing nature of the palliative patient. As several authors have pointed out, refining tools to detect changes when they occur and predict the rate and trajectory of functional decline is urgently needed. The correct assessment of complexity would lead to patients receiving care in an appropriate timeframe.^{10 15 20}

Providing quality care to patients with PC needs is a major challenge that PHC professionals must face, so it is essential to identify situations in which the level of difficulty exceeds their skills, so that a more specialised PC team can get involved.

Patient and caregiver preferences also play an important role in the stratification of PC. A systematic review conducted in 2018 concluded that patients and carers preferred a holistic approach to care and considered PHC professionals to have an important role in advanced care planning, improving all aspects of care, including planning and communicating about end of life and dying in their place of choice.⁴³ More recently, in a qualitative study with data collection through in-depth interviews with 13 patients receiving home-based PC, patients reported their preferences, with shared decision-making as a central element of the care received.⁴⁴

This study has several strengths. The preceding instrument IDC-Pal has already been evaluated in the context of the Spanish health system in a large sample of patients with PC needs. Its validation procedure has followed a strict process of review of content and face validity with the participation of all professionals usually involved in the care of these patients, as that of the IDC-Pal-AP will follow. The empirical validation in real clinical practice conditions of the new instrument in all environments in which PHC provides services (consultation and home) will pave the way to transfer the research results to daily practice. Besides, this is an instrument not limited to patients with cancer, which opens the spectrum to any patient eligible for PC. The IDC-Pal-AP questionnaire will be validated in the Andalusian Health Service, specifically, in the PHC setting, which has the characteristics of a National Health System with universal coverage and standardised procedures for interlevel care through agreed protocols known as integrated care processes, including that relating to shared PC. This specific care process was developed in 2002, and since then it has been updated to incorporate new available evidence, including the use of the IDC-Pal tool by both specialised PC teams and PHC professionals. Following the roadmap of the original tool, the research team will also promote further validation of the instrument in other national and international geographic areas in the PHC field.

This study also has limitations.

For the development of the Delphi Technique in Phase 1, it was decided to select a sample of local experts by opportunistic sampling. This decision could introduce bias, but the research team considers this panel sufficient to carry out a first adaptation of the IDC-Pal tool in the PHC setting as the components of this panel have been selected based on explicit criteria for the selection of experts with dilated experience in the field of PC or PHC, in which the new diagnostic tool is to be developed, in order to obtain a valid instrument with adequate clarity and pertinence for the end-users. There are no standardised recommendations about the criteria selection of the panel of experts for a Delphi technique, but there is consensus that these criteria should be predefined as it has been done in our study.

Among the possible limitations or biases of the study, we highlight that due to the chosen design in Phase 2, a descriptive cross-sectional study, it will not be possible to detect changes that may occur over time that could modify the level of complexity. This means that it is not possible to test the tool’s responsiveness, which is considered one of the essential clinimetric properties,⁴⁵ but this will be addressed in subsequent longitudinal studies. Another limitation of this design is that we cannot assess test-retest reliability either.

Because of the very nature of the palliative population, which covers a wide range of ages, social and economic situations and family structures, as well as the multidisciplinary care inherent to this discipline, it is possible to find a wide variety of clinical situations in the descriptive study. This is considered by the research team; however, as a good opportunity to test the tool in a multitude of different scenarios which represent, in short, the conditions of real clinical practice.

Other limitations are circumstances that may interfere with the detection of the variables to be measured: patients who are being monitored by PC without the knowledge of the PHC team, patients with palliative situations not detected by the PHC professional, complex socio-family situations not known (conflicts at home, dysfunctional family, absence of a main caregiver, etc), among others. All these scenarios would add complexity to the patient and make it more difficult to meet their needs. However, they are not always reflected in the electronic medical record.

The existence of patients with double insurance (public and private insurance) versus patients who always use the public health service may lead to differences in the assessment of certain areas of the IDC-Pal-AP tool, due, in part, to the time it takes a patient to access specialised healthcare, the resources available to them, or the circuit of services through which they must pass in order to have their needs met.

The under-recording of mental illness in the clinical history^{46 47} is another limitation that the research team takes into account, since it is a variable that is collected and analysed as part of the sociodemographic profile of the sample and is also an item of the tool itself.

Another limitation of the study could be the lack of recording of variables to be measured in the electronic medical record, other than the one mentioned above.

All these limitations, along with the specific characteristics of the PHC setting in which the tool will be validated, should be taken into account when considering the applicability to other PHC settings.

Implications for research

Following the development of this study, a tool will be derived from IDC-Pal, adapted to the PHC field, with a smaller number of items and more efficient in its application. Further studies are needed with longitudinal designs to assess other clinimetric indicators such as test-retest reliability and responsiveness in the PC population. With a validated complexity diagnostic tool, we could move on to the next stage to develop and test intervention strategies that allow for a more efficient allocation of healthcare resources to meet the needs of PC patients. Finally, it would also be possible to evaluate how this different allocation of resources could produce improvements in the care provided to this population in a timely manner.

Implications for practice and policy

One of the main characteristics of PHC is the accessibility of patients, their families and caregivers to the health system. This places this level of care and its professionals in an exceptional position to be able to identify early on the needs in PC patients.

To accomplish this important work at PHC, resources such as time and appropriate tools are required to enable professionals to carry out their work efficiently. This implies a continuous updating of the existing care protocols with the incorporation of scientific innovations, as has been done in our region.

Training strategies should also be implemented to ensure that PHC professionals are up to date with cutting-edge knowledge in PC and learn to correctly use tools such as IDC-Pal-AP. This will allow professionals to carry out a more informed and efficient shared decision-making process. For this training experience to be effective, delving into the experience of PC professionals would allow the training programmes to be designed in response to the identified needs, which would help to address real challenges and make learning more effective.