You are here

  • Home
  • Archive
  • Volume 15, Issue 3
  • Evaluation of Electronic Palliative Care Coordination Systems to support advance care planning for people living with life-threatening conditions (PREPARE): protocol for a multicentre observational study using routinely collected primary and secondary ca…

Article Text

Article menu

Download PDFPDF

Palliative care
Protocol
Evaluation of Electronic Palliative Care Coordination Systems to support advance care planning for people living with life-threatening conditions (PREPARE): protocol for a multicentre observational study using routinely collected primary and secondary care data in England
  1. Marcel Alied1,
  2. Sophie Law-Clucas2,
  3. Matthew J Allsop3,
  4. Christina Ramsenthaler2,
  5. Peter May4,
  6. Alastair Bearne5,
  7. Margaret Powell5,
  8. John Rosling5,
  9. Rashmi Kumar5,
  10. Lisa Scerri6,
  11. Rebekah Williams6,
  12. Katherine E Sleeman4,
  13. Diane Laverty7,
  14. Denzil James6,
  15. Julia Verne8,
  16. Kavitha Saravanakumar9,
  17. Ceire E Costelloe1,10,
  18. Joanne Droney6,10,
  19. Jonathan Koffman2
  1. 1 Health Informatics, Division of Clinical Studies, The Institute of Cancer Research, London, UK
  2. 2 Wolfson Palliative Care Research Centre, Hull York Medical School, University of Hull, Hull, UK
  3. 3 Academic Unit of Palliative Care, Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
  4. 4 Cicely Saunders Institute of Palliative Care, Policy and Rehabilitation, King’s College London, London, UK
  5. 5 Patient and Public Involvement Contributor, London, UK
  6. 6 The Royal Marsden NHS Foundation Trust, London, UK
  7. 7 Nurse Consultant, London, UK
  8. 8 Office for Health Improvement and Disparities, London, Greater London, UK
  9. 9 Director of Business Intelligence, NHS North West London, London, London, UK
  10. 10 Imperial College London, London, UK
  1. Correspondence to Dr Joanne Droney; joanne.droney{at}rmh.nhs.uk

Abstract

Introduction Electronic Palliative Care Coordination Systems (EPaCCS) are electronic registers that aim to facilitate documentation and sharing of up-to-date information about patients’ end-of-life preferences and plans for care among different health services. They aim to improve patients’ experiences and outcomes and mitigate costs linked to undesired aggressive care. However, evidence on the equitable delivery of EPaCCS and the extent to which advance care planning (ACP) enhances end-of-life care remains sparse. This study aims to explore the effect of EPaCCS on healthcare outcomes, service utilisation, and costs. It will also estimate the association between social determinants of health and the content and use of EPaCCS.

Methods and analysis The PREPARE project is a retrospective observational cohort study conducted in two phases. We will analyse routinely collected data from three EPaCCS registers from London, Bradford and Leeds. The first phase will use descriptive analysis to describe the completeness of EPaCCS, the content of EPaCCS, and socio-demographic and clinical characteristics of individuals with EPaCCS, and will model the relationship between social determinants of health and completion of ACP components and the creation of EPaCCS. The second phase will use a natural experiment to compare quality indicators (place of death and hospital use) between individuals with EPaCCS and those without. The control groups will be identified through the Leeds decedent dataset and through linking the London EPaCCS register to an electronic record used in North West London. Also, we will quantify healthcare costs and outcomes.

Ethics and dissemination Research approval has been secured from the Health Research Authority (ref 24/LO/0194), London - South East Research Ethics Committee (ref 24/LO/0194) and Confidentiality Advisory Group (ref 24/CAG/0046). Dissemination of findings will occur through peer-reviewed publications, knowledge exchange events and collaborative efforts with patient and public involvement partners.

  • PALLIATIVE CARE
  • Decision Making
  • Digital Technology
  • Electronic Health Records
  • EPIDEMIOLOGIC STUDIES
  • Health Services for the Aged

Data availability statement

Data are available upon reasonable request. Data may be obtained from a third party and are not publicly available. At the end of this study, we will make anonymised aggregate data from this study available through the Health Data Research UK (HDR-UK) Innovation Gateway (https://www.hdruk.ac.uk/about-us/). Data sharing requests and access to the protocol and supplementary information would be available on reasonable request after completion of existing studies and whenever legally and ethically possible. Data access requests should be directed to Dr Joanne Droney joanne.droney@rmh.nhs.uk.

https://creativecommons.org/licenses/by/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

https://doi-org.ezproxy.u-pec.fr/10.1136/bmjopen-2024-093175

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    STRENGTHS AND LIMITATIONS OF THIS STUDY

    • Inclusion of all Electronic Palliative Care Coordination Systems (EPaCCS) records in London (2010–2022), Leeds (2015–2023) and Bradford (2015–2023) with an additional cohort of patients without EPaCCs for Leeds (2021–2023) and London makes this the largest collection of data sources in an EPaCCS UK study.

    • Following the ‘nothing about us without us’ philosophy, there is strong patient and public involvement collaboration at every stage of the project.

    • A natural experiment aims to provide credible causal estimates of EPaCCS effects on end-of-life outcomes, which will strengthen the evidence base.

    • Recommendations to key stakeholders based on the findings will inform future EPaCCS use.

    • Challenges comparing EPaCCS due to the interoperability of the data may limit the generalisability of the findings to other EPaCCs within the UK.

    Introduction

    Over 530 000 people die each year in the UK1 and this number is increasing.2 Many of these deaths are associated with people living with multiple morbidities and complex end-of-life care issues.3 The National Health Service (NHS) should provide high-quality, safe, person-centred end-of-life care consistent with their wishes.4 Most people wish to die at home.5 6 Additionally, hospital was the least preferred place of death for patients receiving palliative care in three countries.6 However, more than half of UK people currently die in hospital2 and many experience unplanned hospital admissions, including emergency department visits and unwanted and futile aggressive treatment.2 7–9 Failure to address these critical issues undermines the realisation of benchmarks that define a good death, as perceived by individuals, their families and healthcare providers alike.10–12

    Advance care planning (ACP) is a voluntary process that supports adults in considering and sharing their values, goals and preferences regarding future care, including location of death so that if they lose mental capacity to make informed decisions for themselves, health professionals and their families can provide care consistent with their wishes.13 In the UK, ACP is endorsed in national policy.14 Despite scepticism of its value,15–17 an intrinsic logic of ACP underpins its use in practice and justifies continued research. Potential ACP benefits include providing important opportunities for discussion of diagnosis and prognosis so care and treatment are aligned with individuals’ preferences, improving symptom discussions and treatment adherence and reducing misunderstandings and conflict between medical staff and families.18 ACP may also lead to fewer interventions of limited or futile clinical value, earlier access to palliative care, reduced inappropriate emergency hospital admissions, fewer hospital deaths and increased rates of hospice admission or appropriate care at home.19–21 ACP is thought to help families prepare for the death of a loved one, resolve family conflict and help with bereavement.22 Although primarily concerned with improving the appropriateness and quality of care, ACP may contribute to controlling important health spending and making more appropriate and considered use of scarce resources in end-of-life.18 23

    The NHS Long Term Plan advises building a ‘digital front door’ connecting health professionals to people24 to improve access, coordination, health outcomes and efficiency.25 In line with this, ACP records need to be accessible to healthcare professionals across different settings.

    Electronic Palliative Care Coordination Systems (EPaCCS) have been specifically designed to facilitate seamless electronic information sharing and enable ACP and end-of-life care decision-making to increase the likelihood of delivering end-of-life care following patient wishes and priorities.26–28 EPaCCS records are intended for creation by trained healthcare professionals with input from patients and their carers to enable patients to discuss and make decisions about their preferences for end-of-life care such as preferred place of death, the ceiling of treatment and resuscitation status. Once stored, it is expected that information should be shared electronically with different professionals across different settings to inform decision-making, especially in times of crisis (emergency services (NHS 111 and 999), general practice, specialist palliative care services, hospices, etc).26 27 Nationally, 175 (83%) clinical commissioning groups (CCGs), now Integrated Care Boards (ICBs), have either implemented EPaCCS or started planning for their implementation.29 The Department of Health’s National Commitment for End-of-Life Care has recommended continued EPaCCS roll-out30 and they have been endorsed in the ‘Palliative and End-of-Life Care: Statutory Guidance for Integrated Care Boards (ICBs)’.31

    While EPaCCS offer potential merits, no UK research has yet evidenced (1) to what extent EPaCCS support advance care planning, (2) to what extent EPaCCS have been offered equitably to all those who stand to benefit from them, (3) the effect of EPaCCS on patients’ place of death, and (4) if EPaCCS are associated with the use of health resources at the end of life where care costs are high.32

    The PREPARE study therefore aims to (a) describe the characteristics of people who receive EPaCCS to support decision-making at the end of life and to estimate the association between social determinants of health and the content of ACP contained within EPaCCS and (b) explore EPaCCS effect on healthcare outcomes, use and costs. Based on our findings, we will synthesise recommendations on the use of EPaCCS to support end-of-life care for people living with life-limiting illnesses and their families.

    The study objectives are the following:

    • 1A. To describe and categorise the data fields and completeness of data contained within each EPaCCS register.

    • 1B. To describe the creation and content of EPaCCS records and elements relating to end-of-life decision-making preferences and ACP (ceiling of treatment, preferred place of care, and death and resuscitation status) in different regions across England.

    • 1C. To describe the socio-demographic and clinical characteristics of individuals who have created EPaCCS records in different regions across England.

    • 1D. To estimate associations between social determinants of health (socioeconomic position, ethnicity, age and gender) and the completion of elements of ACP within EPaCCS.

    • 1E. To estimate associations between social determinants of health (socioeconomic position, ethnicity, age and gender) and the creation of EPaCCS.

    • 2A. To explore the effect of EPaCCS on place of death and hospital use in the last 90 days of life.

    • 2B. To explore the effect of an EPaCCS record on healthcare costs in the last 90 days of life.

    This HRA-approved protocol (V.1.1; January 2025) outlines in detail the motivation for this study, data sources, analysis plan, public and patient involvement, and ethical considerations.

    Methods and analysis

    Study design

    Objectives 1A–1C will be addressed using descriptive statistics, objectives 1D and 1E using multivariable regression and objectives 2A and 2B using a natural experiment framework, which will allow us ultimately to make conclusions and recommendations about the continued use of EPaCCS.33 34 Descriptive statistics and multivariable regression are key tools in quantitative end-of-life research where there is a high reliance on routine data.35 However, these methods are not always reliable for generating credible causal estimates of treatment effects.36 Provided underlying assumptions are met,37 natural experiments can generate causal evidence from observational data, including routinely collected data. These have been little used in end-of-life care research to date,38 but may be particularly impactful in a field where randomised trials are infrequent and methodologically challenging,39 reliance on routine data is paramount40 and selection bias in routine data is a persistent concern.41

    This evaluation of EPaCCS encompasses two distinct work packages that draw upon data from various routinely collected sources, and it is planned to be completed between 2024 and 2025. The first work package (WP1) will enable a comprehensive evaluation of the structure and completeness of three EPaCCS registers (London, Leeds and Bradford), the creation and content of EPaCCS records, exploring the social determinants of health of individuals with EPaCCS records and their association with the completion of elements of ACP within EPaCCS, and exploring the association of social determinants of health with EPaCCS creation. The second work package (WP2) will evaluate the benefits of care for individuals with EPaCCS records against those without. Additionally, it will investigate to what extent EPaCCS lead to better utilisation of scarce health resources. While the analysis of the two work packages will be conducted separately, understanding the content and structure of the datasets and the completeness of the data fields for the WP1 objectives will inform further analyses in WP2. Additionally, understanding which social determinants of health are associated with the creation of EPaCCS records will improve the analysis of WP2 by understanding how these variables should be treated in the statistical models. Together, the findings of WP1 and WP2 will provide evidence as to whether EPaCCS offer benefits to patients at the end of life, their families and the NHS. The study will derive high-quality evidence on factors influencing the uptake of EPaCCS, as well as the effect of EPaCCS on the costs and quality of end-of-life care.42

    Data sources

    The study will use non-identifiable data from three EPaCCS across three distinct geographical locations in the UK, namely London, Leeds and Bradford, which combined have a population of 10.4 million people. These EPaCCS were introduced at different times within the same city and across different cities. This has led to natural variation in exposure, resulting in datasets that cover varying time periods: 2010–2022 in London, and 2015–2023 in Leeds and Bradford. Nonetheless, these EPaCCS are well established and contain a sufficient number of records, as illustrated in table 1, to enable meaningful individual site analyses and answer our research questions. Additional anonymised EPaCCS data from different regions will be considered if made available during the study. The sample size will be determined by the data available in the three datasets and will vary depending on the analysis.

    View this table:
    Table 1

    EPaCCS and data availability

    Figure 1
    Figure 1

    The data flow and the linkage of the Coordinate My Care dataset to the Whole System Integrated Care dataset. CAG, Confidentiality Advisory Group; CCR, Committee for Clinical Research; CMC, Coordinate My Care; DARS, Data Access Request Service; EOL, end-of-life; HRA, Health Research Authority; RM, Royal Marsden; SDE, secure data environment; WSIC, Whole Systems Integrated Care.

    Work package 1: exploration of EPaCCS records and association of social determinants of health in decision-making at the end of life (objectives 1A–1E)

    In the first work package, a retrospective observational study, we hypothesise that this exploratory work package will help us understand the implementation of EPaCCS in terms of who creates EPaCCS and how EPaCCS are used, identify variation in their use and uptake, and clarify what information is included in these records.

    The study will describe how EPaCCS are used, specifically who creates EPaCCS records and what information they encompass regarding individuals’ preferences for end-of-life care. The study will describe data fields across each of the three datasets and evaluate their completeness. Additionally, a descriptive analysis of the three EPaCCS datasets will be undertaken to describe the creation and content of the records across the three regions. These specific regions were chosen for being large metropolitan areas with varied levels of material deprivation and a high concentration of ethnic minority groups. This analysis will focus on the elements of ACP used to support decision-making at the end of life, which include documentation of the ceiling of treatment, resuscitation status, preferred place of care and preferred place of death. The study will also explore if changes are made to decision-making over time for each of these elements. As the three EPaCCS in the study contain data from different periods in time, we will take into account the different timescales during the analyses. The uptake of EPaCCS will be evaluated by describing the number of records created across different time periods and locations. The study will also investigate the setting of the initial record creation (hospital care, primary care, community care). Furthermore, the study will describe the clinical characteristics of patients such as their diagnosis, performance status, capacity for decision-making, living arrangements and expected prognosis. The study will also describe their socio-demographic characteristics with a particular emphasis on social determinants of health such as age, gender, socioeconomic position and ethnicity. The socioeconomic position will be defined using the Index of Multiple Deprivation (IMD), a standard scoring system based on a range of economic, social and housing data, creating a single deprivation score for each small area of the country. Using methodology previously employed in studies by the research team,43 44 an IMD score will be created for each patient based on their postcode which will reflect the deprivation data for the Lower-layer Super Output Area (LSOA) within which the postcode falls. Moreover, the study will investigate across sites the association between social determinants of health and the completion of each of the four previously mentioned ACP elements. Table 2 shows the mapping of the study objectives to data sources and eligibility criteria. Exclusion criteria for all data sources are participants who have chosen National Data Opt-Out and those who have withdrawn consent.

    View this table:
    Table 2

    Mapping study objectives to data sources and eligibility to be included in analyses

    Analysis

    The data from each of the three distinct EPaCCS will be analysed separately. Individual patient-level EPaCCS data will be accessed and cleaned for each of the three systems. The study will categorise the data into social determinants of health (age, gender, ethnicity, social deprivation), clinical characteristics and elements relating to ACP. The social determinants of health have been identified from existing literature for being associated with poor health experiences and outcomes. The study will assess the completeness of variables in the data, examining patterns of missing data at the individual level and identifying any outlier records. Based on the characteristics of missing data, the study will adopt an appropriate approach to treating missing data for statistical analysis. Several methods will be considered that are appropriate for missing at random and not missing at random data. Though, it is assumed that the missing mechanism will be missing not at random. However, no robust methods of imputing missingness in the independent variables with a missing not at random mechanism have been identified. If imputation was carried out, a sensitivity analysis will be conducted to compare parameter estimates with/without imputation. Missing values for key outcomes will be imputed using gender, age, comorbidity, cause of death, IMD and/or study area.45 For each ACP element, documented decisions will be categorised to create an outcome (binary or ordinal) variable for inclusion in logistic regression modelling of the relationship between each of these outcomes, as distinct analyses, and social determinants of health, adjusting for major confounding variables and consideration of random effects/fixed effects (eg, comorbidity). Confounders will be selected using expert knowledge, existing literature, and the completeness and availability of the data. Using the London and Leeds datasets, a dichotomised binary outcome of whether or not a patient has an EPaCCS record will be created for logistic regression, modelling the association between the creation of EPaCCS records and social determinants of health. The study will identify both similarities and differences between the creation, use and content of EPaCCS records in the three EPaCCS cohorts. Mindful of the reported challenges associated with the interoperability of EPaCCS data,46 the comparison of datasets will be cautiously approached. We will examine the impact of the significant increase in EPaCCS records in London,47 and potentially the two other cities, following the outbreak of COVID-19 in March 2020 in terms of the documentation and completeness of ACP elements within the EPaCCS records. We will carry out a secondary analysis (sensitivity analysis) excluding individuals whose records were created during the COVID-19 pandemic after examining the data and the trend in the creation of EPaCCS records.

    Work package 1 outputs

    WP1 will provide evidence of the variation in the uptake of EPaCCS across the three regions in the UK and will identify factors associated with unequal EPaCCS access. The study will describe similarities and differences in the content and creation of EPaCCS which will inform the development of standardised EPaCCS in the future. We will work with key stakeholders (EPaCCS providers, ICBs and health professionals) and in close collaboration with local populations to ensure those who promote end-of-life care decision-making facilitated by EPaCCS are more accessible and acceptable to individuals across the social strata. This will also include bespoke training for health professionals in culturally competent and literate care to enable end-of-life care discussions and decision-making.

    Work package 2: evaluation of the effect of EPaCCS on place of death and secondary healthcare use at end of life and cost minimisation analysis of EPaCCS (objectives 2A and 2B)

    The second work package will adopt a retrospective cohort design under a natural experiment framework to evaluate the effects of EPaCCS on quality indicators of end-of-life care. The quality indicators used in this work package include the place of death (primary outcome) and time spent in hospital in the last 90 days of life (secondary outcome).48 The hypothesis for work package 2 is that people with EPaCCS records are less likely to die in hospital and more likely to spend less time in hospital in the last 90 days of life compared with people without EPaCCS records. An EPaCCS record may address one or both sides of the cost-effectiveness ratio; reducing futile or unwanted treatments will save hospital resources while improving goal-concordant care realises more utility. However, there is also the potential for increased costs, notably through substitution effects, for example, if people die in a hospice instead of in a hospital. We therefore hypothesise that EPaCCS improve the cost-effectiveness of care near the end of life.

    Using the CMC-WSIC linked dataset and the Leeds dataset, the study will use a natural experiment approach33 and establish cohorts of patients who have died having EPaCCS (case) or not having an EPaCCS (control) in each dataset separately. Place of death will be coded as a binary variable for individual-level analysis, indicating whether death occurred in a hospital or elsewhere. For ecological analysis, rates of hospital deaths per year will be calculated for each one of the eight health boroughs (previously called CCGs) in North West London. Time spent in hospital will be derived as a continuous variable measuring the number of days between admission and discharge within the last 90 days of life, or between admission and death for patients who died in hospitals. Rates of time spent in hospital within the last 90 days of life per year will also be calculated. The cost analysis will use the patient-level cost data available in WSIC. Formal costs will be estimated by combining utilisation frequencies in the data with unit costs for different services.49 Informal care hours will be estimated from the literature on end-of-life care populations and associated costs using the substitution method (primary analysis) and opportunity cost method (sensitivity analysis). Intervention costs will be estimated using NHS data.50 We will model costs after diagnostic testing of different modelling approaches in the context of distributional characteristics.51

    Creating comparative cohorts

    This study will take an inclusive approach to defining the cohorts for inclusion in the individual-level analysis, identifying deceased patients who had mention of one of the four main disease-related causes of death in their clinical records within the last year of life (cancer, dementia, heart or lung disease). Based on previous analyses52 and publicly available national data,53 we hypothesise that 22–30% of the EPaCCS cohort will die in the hospital compared with 45–50% in the non-EPaCCS group. The inverse probability of treatment weighting will be used to account for the confounding resulting from the non-random allocation of EPaCCS to the groups and balance characteristics between cohorts.54 First, a multivariable logistic regression will be used to determine the propensity score weights. Factors included in the model to estimate propensity scores will include the confounders selected to be included in the main outcome analysis (such as age, sex, ethnicity, deprivation and primary diagnosis). These confounders will be cautiously selected based on thorough discussions with our team, which includes experts in palliative care, input from the patient and public involvement group with lived experience in end-of-life care, and a comprehensive literature search. Then, for each patient inpatient encounter, a weight defined as the inverse of the probability of the treatment they had received will be calculated. The balance of patients’ characteristics will be assessed visually and by examining the standardised mean differences.55

    Ecological analysis

    Treating the regions covered within the North West London ICBs as a random effect, mixed effects regression will be used to examine the effect of the rate of patients who died having EPaCCS on the annual rates of hospital deaths and time spent in hospital within the last 90 days of life, calculated, respectively, as the number of deaths with EPaCCS over total deaths, the number of in-hospital deaths over total deaths, and the aggregate time spent in hospital within the last 90 days of life over total deaths.56 Other approaches will be considered upon examining the data and the annual number of patients who died having EPaCCS.33

    Individual patient-level analyses

    Mixed effects logistic regression will be used to assess the effect of EPaCCS on the primary and secondary outcome measures adjusting for covariates associated with these outcomes such as the availability of carers, social determinants of health (age, gender, ethnicity, social deprivation), marital status, living circumstances, place of care and comorbidity. To account for the time-varying nature of implementation, the season/financial quarter will also be included in the model. Marginal ORs for each of the outcomes based on weighted logistic regression will be reported.

    Missing data considerations

    Individual-level missing data of the primary outcome variable (place of death) will be excluded from the multivariable analysis. However, in handling missing data related to covariates, those with incomplete data will be identified for a thorough characterisation of the missingness. Depending on the type of data and the level and mechanism of missingness, individual patients without matching covariate data may be excluded from the multivariable modelling. In doing so, we would also be mindful that by excluding such patients, modelling could be subject to biases, for example, due to under-reporting. Hence, we may consider imputing missing data, with sensitivity analysis to determine the effectiveness of imputation on the model outputs.

    Sensitivity analysis

    We will consider a number of approaches in terms of sensitivity analyses, which will be informed by the availability and completeness of the data.57 Sensitivity analyses will be conducted on the cohort identification strategy and our choice of covariates used for estimating the propensity scores.58 We will also consider several approaches and sensitivity analysis techniques to deal with unobserved confounding, the implementation of new policies and the effect of the COVID-19 pandemic on both the intervention and the outcomes of interest.33 59 In terms of the COVID-19 pandemic, we will build on our previous evaluation,47 identify the records created during the pandemic and, if appropriate, perform a sensitivity analysis by potentially excluding these records to assess the impact of this period on our findings.

    Outputs from work package 2

    The second work package will provide novel insight into the effect and value of EPaCCS and ACP on end-of-life care quality outcome measures. We will derive high-quality evidence on how the intervention affects costs in a context where a trial is unfeasible. Secondary analysis will provide insights into how end-of-life care interventions may address or exacerbate inequities in the context of systematic gaps.

    Reporting guidelines

    The data analysis in this study will be guided by the Reporting of Studies Conducted using Observational Routinely-Collected Health Data extension to the Strengthening the Reporting of Observational Studies in Epidemiology guidelines.60 A full statistical analysis plan will be developed.

    Patient and public involvement

    The study places a significant emphasis on patient and public involvement (PPI) to ensure its relevance for individuals with life-limiting conditions and their families. Key contributors include patients, caregivers and those with prior PPI roles, who have actively participated in various stages of previous research projects. Their involvement has extended from project conception to data analysis and dissemination. PPI coapplicants will improve this study by promoting accountability, appropriateness and advocacy, and alerting networks to findings. They played a role in presenting the study to a patient and carer research forum, receiving endorsement for its significance. Their ongoing participation expands from contributions to study development to interpretation and dissemination of findings. Tailored training and support will be provided for our PPI colleagues to ensure their meaningful contributions to the interpretation of the findings and the formulation of clinical and research-based recommendations.

    Ethics and dissemination

    Ethical considerations

    The PREPARE study adheres to the principles of Good Clinical Practice, Data Protection Regulations, the Data Protection Act 2018 and other regulatory requirements in handling confidential patient information. The Leeds and Bradford datasets are de-identified patient-level data from GP practices with data sharing agreements in place for the use of this information in research to improve overall patient care. Explicit consent for Leeds and Bradford is not obtained, as there is an existing data agreement with all GP practices in those regions to use patient data to improve overall care, which covers the data used in this study. The use of both datasets is exempt from the Research Ethics Committee (REC) review, as these use only anonymised patient data routinely collected in the course of normal care.61 However, the use of identifiable patient information without consent in the linkage of CMC and WSIC data requires approval from both the REC and the Confidentiality Advisory Group (CAG). Research approval has been secured from the Health Research Authority (ref 24/LO/0194), London - South East REC (ref 24/LO/0194) and CAG (ref 24/CAG/0046). Patients actively consented to the use of their anonymised information for research at the time of creating a CMC record. Since the individual patients are deceased, explicit consent for linking the CMC and WSIC data is not possible. Nonetheless, given the cost of delivering EPaCCS and the need for evidence to support their roll-out, the public interest in the outcome of this research justifies the controlled use of individuals’ confidential information without gaining their consent. The flow of EPaCCS data to North West London ICB for data linkage will be carried out by the Royal Marsden Information Team, a trusted third party. Stringent measures, including secure file transfer protocols, Data Protection Impact Assessment and encryption are in place to protect the confidentiality of data. Subsequently, the linked datasets will be de-identified, ensuring the separation of Personal Identifying Information from analysis variables. Data will not be made available to the researchers until all necessary approvals are in place. The data will only be accessible by MA, SL-C, MJA, CR, PM, LS, CEC, JD and JK through Trusted Research Environments (TRE). TREs are secure research platforms that are designed to store and protect sensitive data, guaranteeing data privacy.62 Anonymised data for Leeds and Bradford will be stored and analysed in LASER (the Leeds Analytic Secure Environment for Research63), for London CMC in the Royal Marsden BRIDgE TRE (Biomedical Research Informatics Digital Environment62) and for the linked CMC-WSIC data in WSIC TRE (Whole Systems Integrated Care Trusted Research Environment aka Discover Now SDE (Secure Data Environment)64).

    We carried out an Equality Impact Assessment with our PPI colleagues, where we acknowledged the importance of ensuring adequate diversity within our research team (including PPI team) and having adequate diversity of interests within the team. Based on the results, we will work with targeted community connectors to shape our patient-facing outputs and disseminate the findings.

    The study has been peer-reviewed as part of the sponsorship approval process by the Royal Marsden and Institute of Cancer Research Committee for Clinical Research, which ensures the validity of our research. The study also benefited from expert input from senior researchers. Amendments to the original protocol will be subject to the sponsor’s approval and determination of whether amendments are substantial or not. Substantial amendments that require approval will only be implemented after approval. Any deviation from the protocol will be documented and reported.

    Dissemination plan

    Our dissemination strategy aims to reach diverse audiences, engaging patients, caregivers, healthcare professionals, policymakers and researchers to influence clinical care and health policy nationally and internationally. Through collaboration with our PPI representatives, lay summaries of the research findings will be generated to engage a broad audience. We are also mindful of sharing the findings with lay, non-professional audiences and among ethnically diverse communities where data were collected. The findings will be shared electronically and through presentations to patient and caregiver groups. We will use social media platforms and actively participate in annual research open days and public engagement events to present aspects of the study. We anticipate the study findings will be of considerable interest to policymakers, particularly since EPaCCS are a proposed model to improve integration and personalised care, a feature central to Integrated Care Systems. Policymakers will receive findings through evidence summaries, policy briefings and participation in relevant conferences. Health professionals will be engaged through virtual workshops, offering insights into study findings and sharing ‘study finding briefs’ to stimulate discussions. Academic contributions will be made through publications in reputable journals and presentations at conferences. The ‘EPaCCS Research Network (ERN)’ will also be well placed to explore collaboration through follow-on funding to address gaps in evidence and to develop interventions for optimising engagement with EPaCCS identified during this current study. At the end of this study, we will make the anonymised CMC and linked anonymised CMC-WSIC data used in this study available through the Health Data Research UK (HDR-UK) Innovation Gateway to enable the preservation, sharing and reuse of data in other studies.

    Data availability statement

    Data are available upon reasonable request. Data may be obtained from a third party and are not publicly available. At the end of this study, we will make anonymised aggregate data from this study available through the Health Data Research UK (HDR-UK) Innovation Gateway (https://www.hdruk.ac.uk/about-us/). Data sharing requests and access to the protocol and supplementary information would be available on reasonable request after completion of existing studies and whenever legally and ethically possible. Data access requests should be directed to Dr Joanne Droney joanne.droney@rmh.nhs.uk.

    Ethics statements

    Patient consent for publication

    References

    1. ↵
      1. Office for National Statistics
      . Deaths registered in england and wales: 2019: office for national statistics. 2020. Available: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/deathsregistrationsummarytables/2019
    2. ↵
      2. Bone AE ,
      3. Gomes B ,
      4. Etkind SN , et al
      . What is the impact of population ageing on the future provision of end-of-life care? Population-based projections of place of death. Palliat Med 2018;32:329–36. doi:10.1177/0269216317734435
      OpenUrlCrossRefPubMed
    3. ↵
      2. Etkind SN ,
      3. Bone AE ,
      4. Gomes B , et al
      . How many people will need palliative care in 2040? Past trends, future projections and implications for services. BMC Med 2017;15:102. doi:10.1186/s12916-017-0860-2
    4. ↵
      1. National Palliative and End of Life Care Partnership
      . Ambitions for Palliative and End of Life Care: A National Framework for Local Action 2021-2026. 50.2021.
    5. ↵
      2. Pinto S ,
      3. Lopes S ,
      4. de Sousa AB , et al
      . Patient and Family Preferences About Place of End-of-Life Care and Death: An Umbrella Review. J Pain Symptom Manage 2024;67:e439–52. doi:10.1016/j.jpainsymman.2024.01.014
      OpenUrlCrossRefPubMed
    6. ↵
      2. Higginson IJ ,
      3. Daveson BA ,
      4. Morrison RS , et al
      . Social and clinical determinants of preferences and their achievement at the end of life: prospective cohort study of older adults receiving palliative care in three countries. BMC Geriatr 2017;17:271. doi:10.1186/s12877-017-0648-4
    7. ↵
      2. Sallnow L ,
      3. Smith R ,
      4. Ahmedzai SH , et al
      . Report of the Lancet Commission on the Value of Death: bringing death back into life. The Lancet 2022;399:837–84. doi:10.1016/S0140-6736(21)02314-X
      OpenUrl
    8. ↵
      2. Henson LA ,
      3. Higginson IJ ,
      4. Gao W , et al
      . What factors influence emergency department visits by patients with cancer at the end of life? Analysis of a 124,030 patient cohort. Palliat Med 2018;32:426–38. doi:10.1177/0269216317713428
      OpenUrlCrossRefPubMed
    9. ↵
      2. Henson LA ,
      3. Gomes B ,
      4. Koffman J , et al
      . Factors associated with aggressive end of life cancer care. Support Care Cancer 2016;24:1079–89. doi:10.1007/s00520-015-2885-4
      OpenUrlPubMed
    10. ↵
      2. Steinhauser KE ,
      3. Clipp EC ,
      4. McNeilly M , et al
      . In search of a good death: observations of patients, families, and providers. Ann Intern Med 2000;132:825–32. doi:10.7326/0003-4819-132-10-200005160-00011
      OpenUrlCrossRefPubMedWeb of Science
    11. ↵
      2. Meier EA ,
      3. Gallegos JV ,
      4. Thomas LPM , et al
      . Defining a Good Death (Successful Dying): Literature Review and a Call for Research and Public Dialogue. Am J Geriatr Psychiatry 2016;24:261–71. doi:10.1016/j.jagp.2016.01.135
      OpenUrlCrossRefPubMed
    12. ↵
      2. Henson LA ,
      3. Edmonds P ,
      4. Johnston A , et al
      . Population-Based Quality Indicators for End-of-Life Cancer Care. JAMA Oncol 2020;6:142. doi:10.1001/jamaoncol.2019.3388
      OpenUrlPubMed
    13. ↵
      2. Rietjens JAC ,
      3. Sudore RL ,
      4. Connolly M , et al
      . Definition and recommendations for advance care planning: an international consensus supported by the European Association for Palliative Care. Lancet Oncol 2017;18:e543–51. doi:10.1016/S1470-2045(17)30582-X
      OpenUrlCrossRefPubMed
    14. ↵
      1. National institute for health and care excellence (nice)
      . Advance Care Planning 2019, Available: https://www.nice.org.uk/about/nice-communities/social-care/quick-guides/advance-care-planning [Accessed 30 Aug 2023].
    15. ↵
      2. Malhotra C ,
      3. Shafiq M ,
      4. Batcagan-Abueg APM
      . What is the evidence for efficacy of advance care planning in improving patient outcomes? A systematic review of randomised controlled trials. BMJ Open 2022;12:e060201. doi:10.1136/bmjopen-2021-060201
    16. ↵
      2. Borgstrom E
      . Planning for an (un)certain future: Choice within English end-of-life care. Current Sociology 2015;63:700–13. doi:10.1177/0011392115590084
      OpenUrlCrossRef
    17. ↵
      2. Morrison RS ,
      3. Meier DE ,
      4. Arnold RM
      . What’s Wrong With Advance Care Planning? JAMA 2021;326:1575–6. doi:10.1001/jama.2021.16430
      OpenUrlCrossRefPubMed
    18. ↵
      2. Zwakman M ,
      3. Jabbarian LJ ,
      4. van Delden J , et al
      . Advance care planning: A systematic review about experiences of patients with a life-threatening or life-limiting illness. Palliat Med 2018;32:1305–21. doi:10.1177/0269216318784474
      OpenUrlCrossRefPubMed
    19. ↵
      2. Brinkman-Stoppelenburg A ,
      3. Rietjens JAC ,
      4. van der Heide A
      . The effects of advance care planning on end-of-life care: a systematic review. Palliat Med 2014;28:1000–25. doi:10.1177/0269216314526272
      OpenUrlCrossRefPubMed
    20. ↵
      2. Mack JW ,
      3. Weeks JC ,
      4. Wright AA , et al
      . End-of-life discussions, goal attainment, and distress at the end of life: predictors and outcomes of receipt of care consistent with preferences. J Clin Oncol 2010;28:1203–8. doi:10.1200/JCO.2009.25.4672
      OpenUrlAbstract/FREE Full Text
    21. ↵
      2. Nicholas R ,
      3. Nicholas E ,
      4. Hannides M , et al
      . Influence of individual, illness and environmental factors on place of death among people with neurodegenerative diseases: a retrospective, observational, comparative cohort study. BMJ Support Palliat Care 2024;14:e1032–40. doi:10.1136/bmjspcare-2021-003105
      OpenUrlAbstract/FREE Full Text
    22. ↵
      2. Falzarano F ,
      3. Prigerson HG ,
      4. Maciejewski PK
      . The Role of Advance Care Planning in Cancer Patient and Caregiver Grief Resolution: Helpful or Harmful? Cancers (Basel) 2021;13:1977. doi:10.3390/cancers13081977
    23. ↵
      2. Marckmann G ,
      3. in der Schmitten J
      . THE ECONOMICS OF ADVANCE CARE PLANNING: EMPIRICAL DATA AND ETHICAL IMPLICATIONS. BMJ Support Palliat Care 2013;3:241. doi:10.1136/bmjspcare-2013-000491.43
      OpenUrlAbstract/FREE Full Text
    24. ↵
      1. National Health Service
      . The nhs long term plan. 2019. Available: https://www.longtermplan.nhs.uk/wp-content/uploads/2019/08/nhs-long-term-plan-version-1.2.pdf
    25. ↵
      2. Wachter R , Making IT Work: Harnessing the Power of Health Information Technology to Improve Care in England
      . 71. Report to the national advisory group on health information technology in england. London The Stationery Office; 2016.
    26. ↵
    27. ↵
      2. Petrova M ,
      3. Riley J ,
      4. Abel J , et al
      . Crash course in EPaCCS (Electronic Palliative Care Coordination Systems): 8 years of successes and failures in patient data sharing to learn from. BMJ Support Palliat Care 2018;8:447–55. doi:10.1136/bmjspcare-2015-001059
      OpenUrlAbstract/FREE Full Text
    28. ↵
      2. Birtwistle J ,
      3. Millares-Martin P ,
      4. Evans CJ , et al
      . Mapping and characterising electronic palliative care coordination systems and their intended impact: A national survey of end-of-life care commissioners. PLoS ONE 2022;17:e0275991. doi:10.1371/journal.pone.0275991
    29. ↵
      1. National End of Life Intelligence Network
      . Electronic Palliative Care Co-Ordination Systems (EPaCCS) in England - Survey of Clinical Commissioning Groups . 2013.
    30. ↵
      1. NHS Finance and Operations
      . Our Commitment to You for End of Life Care: The Government Response to the Review of Choice in End of Life Care. 2016.
    31. ↵
      1. National Health Service (NHS)
      . Palliative and End of Life Care Statutory Guidance for Integrated Care Boards (ICBs). 2020.
    32. ↵
      2. May P ,
      3. Morrison RS ,
      4. Murtagh FEM
      . Current state of the economics of palliative and end-of-life care: A clinical view. Palliat Med 2017;31:293–5. doi:10.1177/0269216317695680
      OpenUrlPubMed
    33. ↵
      2. Craig P ,
      3. Katikireddi SV ,
      4. Leyland A , et al
      . Natural Experiments: An Overview of Methods, Approaches, and Contributions to Public Health Intervention Research. Annu Rev Public Health 2017;38:39–56. doi:10.1146/annurev-publhealth-031816-044327
      OpenUrlCrossRefPubMed
    34. ↵
      2. Hernán MA ,
      3. Hsu J ,
      4. Healy B
      . A Second Chance to Get Causal Inference Right: A Classification of Data Science Tasks. Chance (N Y) 2019;32:42–9. doi:10.1080/09332480.2019.1579578
      OpenUrl
    35. ↵
      2. Earle CC ,
      3. Ayanian JZ
      . Looking Back From Death: The Value of Retrospective Studies of End-of-Life Care. JCO 2006;24:838–40. doi:10.1200/JCO.2005.03.9388
      OpenUrlFREE Full Text
    36. ↵
      2. Starks H ,
      3. Diehr P ,
      4. Curtis JR
      . The challenge of selection bias and confounding in palliative care research. J Palliat Med 2009;12:181–7. doi:10.1089/jpm.2009.9672
      OpenUrlCrossRefPubMed
    37. ↵
      2. Khullar D ,
      3. Jena AB
      . 'Natural Experiments' in Health Care Research. JAMA Health Forum 2021;2:e210290. doi:10.1001/jamahealthforum.2021.0290
    38. ↵
      2. Jiang J ,
      3. Kim N ,
      4. Garrido MM , et al
      . Effectiveness and cost-effectiveness of palliative care in natural experiments: a systematic review. BMJ Support Palliat Care 2023;18. doi:10.1136/spcare-2022-003993
    39. ↵
      2. Higginson IJ ,
      3. Evans CJ ,
      4. Grande G , et al
      . Evaluating complex interventions in end of life care: the MORECare statement on good practice generated by a synthesis of transparent expert consultations and systematic reviews. BMC Med 2013;11:111. doi:10.1186/1741-7015-11-111
    40. ↵
      2. Luta X ,
      3. Ottino B ,
      4. Hall P , et al
      . Evidence on the economic value of end-of-life and palliative care interventions: a narrative review of reviews. BMC Palliat Care 2021;20:89. doi:10.1186/s12904-021-00782-7
    41. ↵
      2. Jacobson M ,
      3. May P ,
      4. Morrison RS
      . Improving Care of People With Serious Medical Illness-An Economic Research Agenda for Palliative Care. JAMA Health Forum 2022;3:e214464. doi:10.1001/jamahealthforum.2021.4464
    42. ↵
      2. Carroll C ,
      3. Patterson M ,
      4. Wood S , et al
      . A conceptual framework for implementation fidelity. Implement Sci 2007;2:40. doi:10.1186/1748-5908-2-40
      OpenUrlCrossRefPubMed
    43. ↵
      2. Koffman J ,
      3. Burke G ,
      4. Dias A , et al
      . Demographic factors and awareness of palliative care and related services. Palliat Med 2007;21:145–53. doi:10.1177/0269216306074639
      OpenUrlCrossRefPubMedWeb of Science
    44. ↵
      2. Koffman J ,
      3. Ho YK ,
      4. Davies J , et al
      . Does ethnicity affect where people with cancer die? A population-based 10 year study. PLoS ONE 2014;9:e95052. doi:10.1371/journal.pone.0095052
    45. ↵
      2. Luta X ,
      3. Diernberger K ,
      4. Bowden J , et al
      . Intensity of care in cancer patients in the last year of life: a retrospective data linkage study. Br J Cancer 2022;127:712–9. doi:10.1038/s41416-022-01828-0
      OpenUrlPubMed
    46. ↵
      2. Millares Martin P
      . Electronic palliative care coordination system (EPaCCS) in practice: A useful tool? BMJ Support Palliat Care 2021;11:146–8. doi:10.1136/bmjspcare-2019-001897
      OpenUrlAbstract/FREE Full Text
    47. ↵
      2. McFarlane PG ,
      3. Bunc C ,
      4. Sleeman KE
      . Advance care planning before and during COVID-19: evaluation of 73,675 patients’ records. BJGP Open 2024. doi:10.3399/BJGPO.2023.0145
    48. ↵
      End of life care for adults (qs13): national institute for health and care excellence (nice). 2011.
    49. ↵
      2. Jones KC ,
      3. Birch S ,
      4. Dargan A , et al
      . Unit Costs of Health and Social Care 2022Manual. 2023. doi:10.22024/unikent/01.02.100519
    50. ↵
      Economic evaluation of the electronic palliative care coordination system (epaccs) early implementer sites: whole systems partnership. 2013.
    51. ↵
      2. Deb P ,
      3. Norton EC ,
      4. Manning W
      . Stata Press.2017:264.
    52. ↵
      2. Orlovic M ,
      3. Callender T ,
      4. Riley J , et al
      . Impact of advance care planning on dying in hospital: Evidence from urgent care records. PLoS ONE 2020;15:e0242914. doi:10.1371/journal.pone.0242914
    53. ↵
      Palliative and end of life care profiles: fingertips public health data: office for health improvement & disparities. In: Public Health Profiles: Palliative and End of Life Care Profiles: OHID. 2024. Available: https://fingertips.phe.org.uk/profile/end-of-life/data#page/4/gid/1938132883/ati/223/iid/93474/age/1/sex/4/cat/-1/ctp/-1/yrr/1/cid/4/tbm/1/page-options/tre-do-1
    54. ↵
      2. Austin PC ,
      3. Stuart EA
      . Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies. Stat Med 2015;34:3661–79. doi:10.1002/sim.6607
      OpenUrlCrossRefPubMed
    55. ↵
      2. Chesnaye NC ,
      3. Stel VS ,
      4. Tripepi G , et al
      . An introduction to inverse probability of treatment weighting in observational research. Clin Kidney J 2022;15:14–20. doi:10.1093/ckj/sfab158
      OpenUrlCrossRefPubMed
    56. ↵
      2. Pring A ,
      3. Verne J
      . Palliative and end of life care profile December 2023 update: Statistical commentary. Office for Health Improvement & Disparities 2023.
    57. ↵
      2. Thabane L ,
      3. Mbuagbaw L ,
      4. Zhang S , et al
      . A tutorial on sensitivity analyses in clinical trials: the what, why, when and how. BMC Med Res Methodol 2013;13:92. doi:10.1186/1471-2288-13-92
    58. ↵
      2. Daw JR ,
      3. Hatfield LA
      . Matching and Regression to the Mean in Difference-in-Differences Analysis. Health Serv Res 2018;53:4138–56. doi:10.1111/1475-6773.12993
      OpenUrlPubMed
    59. ↵
      2. D’Agostino McGowan L
      . Sensitivity Analyses for Unmeasured Confounders. Curr Epidemiol Rep 2022;9:361–75. doi:10.1007/s40471-022-00308-6
      OpenUrl
    60. ↵
      2. Elm E von ,
      3. Altman DG ,
      4. Egger M , et al
      . Strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. BMJ 2007;335:806–8. doi:10.1136/bmj.39335.541782.AD
      OpenUrlFREE Full Text
    61. ↵
      1. Do I need NHS Ethnics approval?
      National health service (nhs) health research authority. Available: https://www.hra-decisiontools.org.uk/ethics/ [Accessed 3 Jul 2024].
    62. ↵
      NIHR | biomedical research centre at the royal marsden and the icr. In: BRIDgE [Internet] Biomedical Research Centre for Cancer. 2020. Available: https://www.cancerbrc.org/BRIDgE
    63. ↵
      Leeds Institute for Data Analytics; Leeds Institute for Data Analytics. What is LASER, 2024. Available: https://lida.leeds.ac.uk/what-is-laser/
    64. ↵
      Whole systems integrated care (wsic). City of Westminster; 2023. Available: https://www.westminster.gov.uk/data-protection/adult-social-care-privacy-notice/whole-systems-integrated-care-wsic
    65. Whole systems integrated care (wsic): north west london integrated care system. Available: https://www.nwlondonicb.nhs.uk/professionals/whole-systems-integrated-care-wsic [Accessed 10 May 2024].
      2. Bottle A ,
      3. Cohen C ,
      4. Lucas A , et al
      . How an electronic health record became a real-world research resource: comparison between London’s Whole Systems Integrated Care database and the Clinical Practice Research Datalink. BMC Med Inform Decis Mak 2020;20:71. doi:10.1186/s12911-020-1082-7
    67. Leeds planning ahead report (end of life): leeds palliative care network. 2021.
      2. Wilson L
      . Goldline service year end report. 2018.

    Footnotes

    • MA and SL-C are joint first authors.

    • X @matthewallsop, @kesleeman

    • Contributors MA, SL-C, JK and JD drafted this manuscript based on a grant proposal and HRA-approved protocol which was devised and written by JD, JK, PM, CR, CEC, MJA, LS, KES, JV, DJ, MP, DL, AB, JR, RK and KS. All coauthors also contributed to the writing of the manuscript. MA and SL-C subsequently prepared a final version of the manuscript based on coauthor contributions and contributed equally to this paper. JK and JD hold joint last authorship. JD is the guarantor of the study. All authors then read the final version, approved it for submission for publication and agree to be accountable for all aspects of the work.

    • Funding This project represents independent research supported by the National Institute for Health and Care Research (NIHR) Biomedical Research Centre at The Royal Marsden NHS Foundation Trust and the Institute of Cancer Research, London. This work was supported by the BMA Foundation Helen H Lawson (2023) grant, the Royal Marsden Cancer Charity grant and Royal Marsden/ICR National Institute of Health Biomedical Research Centre grant. The funders do not have a role in the study design, data collection, management or analysis. KES is the Laing Galazka Chair in palliative care at King’s College London, funded by an endowment from Cicely Saunders International and the Kirby Laing Foundation

    • Competing interests None declared.

    • Patient and public involvement Patients and/or the public were involved in the design, conduct, reporting or dissemination plans of this research. Refer to the Methods section for further details.

    • Provenance and peer review Not commissioned; externally peer reviewed.