Using routine data to improve palliative and end of life care

Characterising trends in the initiation, timing, and completion of recommended summary plan for emergency care and treatment (ReSPECT) plans: Retrospective analysis of routine data from a large UK hospital trust

AIM

To assess patient socio-demographic and disease characteristics associated with the initiation, timing, and completion of emergency care and treatment planning in a large UK-based hospital trust.

METHODS

Secondary retrospective analysis of data across 32 months extracted from digitally stored Recommended Summary Plan for Emergency Care and Treatment (ReSPECT) plans within the electronic health record system of an acute hospital trust in England, UK.

RESULTS

Data analysed from ReSPECT plans (n = 23,729), indicate an increase in the proportion of admissions having a plan created from 4.2% in January 2019 to 6.9% in August 2021 (mean = 8.1%). Forms were completed a median of 41 days before death (a median of 58 days for patients with capacity, and 21 days for patients without capacity). Do not attempt cardiopulmonary resuscitation was more likely to be recorded for patients lacking capacity, with increasing age (notably for patients aged over 74 years), being female and the presence of multiple disease groups. 'Do not attempt cardiopulmonary resuscitation' was less likely to be recorded for patients having ethnicity recorded as Asian or Asian British and Black or Black British compared to White. Having a preferred place of death recorded as 'hospital' led to a five-fold increase in the likelihood of dying in hospital.

CONCLUSION

Variation in the initiation, timing, and completion of ReSPECT plans was identified by applying an evaluation framework. Digital storage of ReSPECT plan data presents opportunities for assessing trends and completion of the ReSPECT planning process and benchmarking across sites. Further research is required to monitor and understand any inequity in the implementation of the ReSPECT process in routine care.

Quality of palliative and end-of-life care: a qualitative study of experts' recommendations to improve indicators in Quebec (Canada)

BACKGROUND

In 2021, the National Institute of Public Health (INSPQ) (Quebec, Canada), published an update of the palliative and end-of-life care (PEoLC) indicators. Using these updated indicators, this qualitative study aimed to explore the point of view of PEoLC experts on how to improve access and quality of care as well as policies surrounding end-of-life care.

METHODS

Semi-directed interviews were conducted with palliative care and policy experts, who were asked to share their interpretations on the updated indicators and their recommendations to improve PEoLC. A thematic analysis method was used.

RESULTS

The results highlight two categories of interpretations and recommendations pertaining to: (1) data and indicators and (2) clinical and organizational practice. Participants highlight the lack of reliability and quality of the data and indicators used by political and clinical stakeholders in evaluating PEoLC. To improve data and indicators, they recommend: improving the rigour and quality of collected data, assessing death percentages in all healthcare settings, promoting research on quality of care, comparing data to EOL care directives, assessing use of services in EOL, and creating an observatory on PEoLC. Participants also identified barriers and disparities in accessing PEoLC as well as inconsistency in quality of care. To improve PEoLC, they recommend: early identification of palliative care patients, improving training for all healthcare professionals, optimizing professional practice, integrating interdisciplinary teams, and developing awareness on access disparities.

CONCLUSIONS

Results show that PEoLC is an important aspect of public health. Recommendations issued are relevant to improve PEoLC in and outside Quebec.

The effectiveness of out-of-hours palliative care telephone advice lines: A rapid systematic review

BACKGROUND

People with palliative care needs and their carers often rely on out-of-hours services to remain at home. Policymakers have recommended implementing telephone advice lines to ensure 24/7 access to support. However, the impact of these services on patient and carer outcomes, as well as the health care system, remains poorly understood.

AIM

To evaluate the clinical- and cost-effectiveness of out-of-hours palliative care telephone advice lines, and to identify service characteristics associated with effectiveness.

DESIGN

Rapid systematic review (PROSPERO ID: CRD42023400370) with narrative synthesis.

DATA SOURCES

Three databases (Medline, EMBASE and CINAHL) were searched in February 2023 for studies of any design reporting on telephone advice lines with at least partial out-of-hours availability. Study quality was assessed using the Mixed Methods Appraisal Tool, and quantitative and qualitative data were synthesised narratively.

RESULTS

Twenty-one studies, published 2000-2022, were included. Most studies were observational, none were experimental. While some evidence suggested that telephone advice lines offer guidance and reassurance, supporting care at home and potentially reducing avoidable emergency care use in the last months of life, variability in reporting and poor methodological quality across studies limit our understanding of patient/carer and health care system outcomes.

CONCLUSION

Despite their increasing use, evidence for the clinical- and cost-effectiveness of palliative care telephone advice lines remains limited, primarily due to the lack of robust comparative studies. There is a need for more rigorous evaluations incorporating experimental or quasi-experimental methods and longer follow-up, and standardised reporting of telephone advice line models and outcomes, to guide policy and practice.

Predicting Patient Mortality for Earlier Palliative Care Identification in Medicare Advantage Plans: Features of a Machine Learning Model

BACKGROUND

Machine learning (ML) can offer greater precision and sensitivity in predicting Medicare patient end of life and potential need for palliative services compared to provider recommendations alone. However, earlier ML research on older community dwelling Medicare beneficiaries has provided insufficient exploration of key model feature impacts and the role of the social determinants of health.

OBJECTIVE

This study describes the development of a binary classification ML model predicting 1-year mortality among Medicare Advantage plan members aged ≥65 years (N=318,774) and further examines the top features of the predictive model.

METHODS

A light gradient-boosted trees model configuration was selected based on 5-fold cross-validation. The model was trained with 80% of cases (n=255,020) using randomized feature generation periods, with 20% (n=63,754) reserved as a holdout for validation. The final algorithm used 907 feature inputs extracted primarily from claims and administrative data capturing patient diagnoses, service utilization, demographics, and census tract-based social determinants index measures.

RESULTS

The total sample had an actual mortality prevalence of 3.9% in the 2018 outcome period. The final model correctly predicted 44.2% of patient expirations among the top 1% of highest risk members (AUC=0.84; 95% CI 0.83-0.85) versus 24.0% predicted by the model iteration using only age, gender, and select high-risk utilization features (AUC=0.74; 95% CI 0.73-0.74). The most important algorithm features included patient demographics, diagnoses, pharmacy utilization, mean costs, and certain social determinants of health.

CONCLUSIONS

The final ML model better predicts Medicare Advantage member end of life using a variety of routinely collected data and supports earlier patient identification for palliative care.

The association between social care expenditure and multiple-long term conditions: A population-based area-level analysis

Background

Multiple long-term health conditions (MLTCs) are common and increasing among older people, yet there is limited understanding of their prevalence and association with social care expenditure.

Aim

To estimate the prevalence of MTLCs and association with English social care expenditure.

Methods

Our study population included those aged ≥ 65 who died in England in the year 2018 with any of the following long-term conditions recorded on their death certificate: diabetes; cardiovascular diseases (CVDs) including hypertension; dementia; stroke; respiratory; and chronic kidney diseases (CKDs). Prevalence was based on the proportion of death reported for older people with MTLCs (≥ 2) in each of the 152 English Local Authorities (LAs). Ordinary least square regression (OLS) was used to assess the relationship between prevalence of MTLCs and adult social care expenditure, adjusting for LA characteristics.

Results

Of the 409551 deaths reported, 19.9% (n = 81395) had ≥ 2 MTLCs, of which the combination of CVDs-diabetes was the most prevalent. Hospitals were the leading place of death for those with MTLCs. Results from the OLS regression model showed that an increased prevalence of MLTCs is associated with higher LA social care expenditure. A percentage point increase in prevalence of MLTCs is associated with an increase of about £8.13 in per capita LA social care expenditure.

Conclusion

Our findings suggest that the increased prevalence of MTLCs is associated with increased LA social care expenditure. It is important for future studies to further explore the mechanisms or link between LA social care expenditure and the prevalence of MTLCs.

Verification of administrative data to measure palliative care at terminal hospital stays

BACKGROUND

Administrative data and clinician documentation have not been directly compared for reporting palliative care, despite concerns about under-reporting.

OBJECTIVE

The aim of this study was to verify the use of routinely collected administrative data for reporting in-hospital palliation and to examine factors associated with coded palliative care in hospital administrative data.

METHOD

Hospital administrative data and inpatient palliative care activity documented in medical records were compared for patients dying in hospital between 1 July 2017 and 31 December 2017. Coding of palliative care in administrative data is based on hospital care type coded as "palliative care" and/or assignment of the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) palliative care diagnosis code Z51.5. Medical records were searched for specified keywords, which, read in context, indicated a palliative approach to care. The list of keywords (palliative, end of life, comfort care, cease observations, crisis medications, comfort medications, syringe driver, pain or symptom management, no cardiopulmonary resuscitation, advance medical plan/resuscitation plan, deteriorating, agitation, restless and delirium) was developed in consultation with seven local clinicians specialising in palliative care or geriatric medicine.

RESULTS

Of the 576 patients who died in hospital, 246 were coded as having received palliative care, either solely by the ICD-10-AM diagnosis code Z51.5 (42%) or in combination with a "palliative care" care type (58%). Just over one-third of dying patients had a palliative care specialist involved in their hospital care. Involvement of a palliative care specialist and a cancer diagnosis substantially increased the odds of a Z51.5 code (odds ratio = 11 and 4, respectively). The majority of patients with a "syringe driver" or identified as being at the "end of life" were assigned a Z51.5 code (73.5% and 70.5%, respectively), compared to 53.8% and 54.7%, respectively, for "palliative" or "comfort care." For each keyword indicating a palliative approach to care, the Z51.5 code was more likely to be assigned if the patient had specialist palliative care input or if they had cancer.

CONCLUSION

Our results suggest administrative data under-represented in-hospital palliative care, at least partly due to medical record documentation that failed to meet ICD-10-AM coding criteria. Collaboration between clinicians and coders can enhance the quality of records and, consequently, administrative data.

The use of routine data from primary care practices in Germany to analyze the impact of the outbreak of SARS-CoV-2 on the utilization of primary care services for patients with type 2 diabetes mellitus

BACKGROUND

Routinely collected health data from ambulatory care providers offer a wide range of research opportunities. However, the access is often (e.g., technically) hindered, particularly in Germany. In the following, we describe the development of an infrastructure for the analysis of pseudonymized routine data extracted from primary care practices in Germany. Further, we analyze the impact of the outbreak of SARS-CoV-2 on the utilization of primary care services for patients with type 2 diabetes mellitus (DM type 2).

METHODS

In this retrospective cohort study, routine data were extracted from nine private primary care practices before and since the outbreak of SARS-CoV-2 in Germany. The sample consisted of patients who were treated between 2016 and 2022 in one of the participating practices. The effects of the outbreak on the frequency of practice visits and the disease course of DM type 2 patients were analyzed by means of bivariate and multivariate analyses.

RESULTS

The developed infrastructure offers an analysis of routine data from outpatient care within 24 h. In total, routine data of 30,734 patients could be processed for the analyses with 4182 (13.6%) patients having a diagnosed DM type 2 and 59.0% of these patients were enrolled in a disease management program (DMP). In the multivariate analysis, there was a significant negative effect of the SARS-CoV-2 outbreak on utilization of outpatient services of patients with DM type 2 disease. This decrease was less pronounced among DMP patients. The glycated haemoglobin level (HbA1c) has not changed significantly.

CONCLUSIONS

The study showed that the analysis of routine data from outpatient care in Germany is possible in a timely manner using a special developed electronic health record system and corresponding software. The significantly negative effect of the SARS-CoV-2 outbreak on utilization of outpatient services of patients with DM type 2 disease was less pronounced among DMP patients. Two years after the start of the Covid pandemic a significantly worsened course of illness cannot be observed. However, it must be taken into account that the observation period for clinically relevant outcomes is still relatively short.

Researching minoritised communities in palliative care: An agenda for change

BACKGROUND

Palliative care access, experiences and outcomes of care disadvantage those from ethnically diverse, Indigenous, First nation and First people communities. Research into this field of inquiry raises unique theoretical, methodological, and moral issues. Without the critical reflection of methods of study and reporting of findings, researchers may inadvertently compromise their contribution to reducing injustices and perpetuating racism.

AIM

To examine key evidence of the place of minoritised communities in palliative care research to devise recommendations that improve the precision and rigour of research and reporting of findings.

METHODS

Narrative review of articles identified from PubMed, CINAHL and Google Scholar for 10 years augmented with supplementary searches.

RESULTS

We identified and appraised 109 relevant articles. Four main themes were identified (i) Lack of precision when working with a difference; (ii) 'black box epidemiology' and its presence in palliative care research; (iii) the inclusion of minoritised communities in palliative care research; and (iv) the potential to cause harm. All stymie opportunities to 'level up' health experiences and outcomes across the palliative care spectrum.

CONCLUSIONS

Based on the findings of this review palliative care research must reflect on and justify the classification of minoritised communities, explore and understand intersectionality, optimise data quality, decolonise research teams and methods, and focus on reducing inequities to level up end-of-life care experiences and outcomes. Palliative care research must be forthright in explicitly indentifying instances of structural and systemic racism in palliative care research and engaging in non-judgemental debate on changes required.

End-of-life care quality measures: beyond place of death

BACKGROUND

How quality in healthcare is measured shapes care provision, including how and what care is delivered. In end-of-life care, appropriate measurement can facilitate effective care and research, and when used in policy, highlight deficits and developments in provision and endorse the discipline necessity. The most prevalent end-of-life quality metric, place of death, is not a quality measure: it gives no indication of the quality of care or patient experience in the place of death.

AIM

To evaluate alternative measures to place of death for assessing quality of care in end-of-life provision in all settings.

METHOD

We examine current end-of-life care quality measures for use as metrics for quality in end-of-life care. We categorise approaches to measurement as either: clinical instruments, mortality follow-back surveys or organisational data. We review each category using four criteria: care setting, patient population, measure feasibility, care quality.

RESULTS

While many of the measure types were highly developed for their specific use, each had limitations for measuring quality of care for a population. Measures were deficient because they lacked potential for reporting end-of-life care for patients not in receipt of specialist palliative care, were reliant on patient-proxy accounts, or were not feasible across all care settings.

CONCLUSION

None of the current end-of-life care metric categories can currently be feasibly used to compare the quality of end-of-life care provision for all patients in all care settings. We recommend the development of a bespoke measure or judicious selection and combination of existing measures for reviewing end-of-life care quality.

Rapid systematic review to identify key barriers to access, linkage, and use of local authority administrative data for population health research, practice, and policy in the United Kingdom

BACKGROUND

Improving data access, sharing, and linkage across local authorities and other agencies can contribute to improvements in population health. Whilst progress is being made to achieve linkage and integration of health and social care data, issues still exist in creating such a system. As part of wider work to create the Cambridge Child Health Informatics and Linked Data (Cam-CHILD) database, we wanted to examine barriers to the access, linkage, and use of local authority data.

METHODS

A systematic literature search was conducted of scientific databases and the grey literature. Any publications reporting original research related to barriers or enablers of data linkage of or with local authority data in the United Kingdom were included. Barriers relating to the following issues were extracted from each paper: funding, fragmentation, legal and ethical frameworks, cultural issues, geographical boundaries, technical capability, capacity, data quality, security, and patient and public trust.

RESULTS

Twenty eight articles were identified for inclusion in this review. Issues relating to technical capacity and data quality were cited most often. This was followed by those relating to legal and ethical frameworks. Issue relating to public and patient trust were cited the least, however, there is considerable overlap between this topic and issues relating to legal and ethical frameworks.

CONCLUSIONS

This rapid review is the first step to an in-depth exploration of the barriers to data access, linkage and use; a better understanding of which can aid in creating and implementing effective solutions. These barriers are not novel although they pose specific challenges in the context of local authority data.

Trends in end-of-life decisions among patients dying in a university hospital oncology ward after implantation of a palliative outpatient clinic

BACKGROUND

The need for high quality palliative care at end-of-life has been increasingly recognized while regional differences exist in its quality and availability. Basic palliative care is given by oncologists at any stage of the disease, but this does not cover the high need for specialized palliative care. The aim of this study was to assess the trends in end-of-life decisions among patients dying in a university hospital oncology ward before and after the implementation of a palliative outpatient clinic.

MATERIAL AND METHODS

The study population consists of all patients who died in the Kuopio University Hospital oncology ward between 1.1.2010-31.10.2011 and 1.1.2012-31.12.2018. The palliative outpatient clinic was established and set up in November - December 2011. Data on inpatient stays, cancer treatments, treatment decisions, and some background factors were retrieved from electronic records.

RESULTS

The study population totaled 644 patients dying in the oncology ward at KUH (57.8% males; 42.2% females). The deaths comprise 17.2% (191/1108) of all cancer deaths in 2010-2011 and 11.1% (461/4049) in 2012-2018 in the KUH catchment area (North-Savo Health Care District). In years 2012-2018, 14.1% of patients treated at KUH oncology clinic visited the palliative outpatient clinic. The percentage of DNR (do-not-resuscitate), palliative care, and end-of-life (EOL) care decisions increased significantly in the later period. The decisions were mainly made during the last week of life. The proportion of patients receiving chemotherapy during the last two weeks of life remained stable.

CONCLUSION

The proportion of patients receiving DNR, palliative care and EOL care decisions increased after the implementation of the palliative outpatient clinic, but the decisions were still made rather late, mainly during the last days of life.

Using routine databases to evaluate Electronic Palliative Care Co-ordination Systems (EPaCCS)

In response to the government's drive to expand Electronic Palliative Care Co-ordination Systems (EPaCCS) across England by 2020, further evidence for this intervention needs to be established quickly. With palliative and end-of-life care research being an underfunded area, the availability and lower costs of routine databases make it an attractive resource to integrate into studies evaluating EPaCCS without jeopardising research quality. This article describes how routine databases can be used to address the current paucity of high-quality evidence; they can be used in a range of study designs, including randomised controlled trials and quasi-experimental designs, and may also be able to contribute quality of life or patient-reported outcome measures.

Early positive approaches to support for families of young children with intellectual disability: the E-PAtS feasibility RCT

Background

Parents of children with intellectual disability are 1.5–2 times more likely than other parents to report mental health difficulties. There is a lack of clinically effective and cost-effective group well-being interventions designed for family carers of young children with intellectual disability.

Aim

To examine the feasibility of a randomised controlled trial of the clinical effectiveness and cost-effectiveness of the Early Positive Approaches to Support (E-PAtS) intervention.

Design

A feasibility study (including randomisation of families into a two-arm trial), questionnaires to assess the feasibility of proposed outcome measures (including resource use and health-related quality of life) and practitioner/family carer interviews. An additional question was included in an online UK survey of families, conducted by the research team to assess usual practice, and a survey of provider organisations.

Setting

Families recruited from community contexts (i.e. third sector, local authority services, special schools) and self-referral. The E-PAtS intervention was delivered by trained community-based providers.

Participants

Families with at least one child aged 1.5–5 years with an intellectual disability. At least one parent had to have English-language ability (spoken) for E-PAtS programme participation and participants had to provide informed consent.

Interventions

E-PAtS intervention – two caregivers from each family invited to eight 2.5-hour group sessions with usual practice. Usual practice – other support provided to the family, including other parenting support.

Objectives

To assess randomisation willingness/feasibility, recruitment of providers/parents, retention, usual practice, adherence, fidelity and feasibility of proposed outcome measures (including the Warwick–Edinburgh Mental Well-Being Scale as the proposed primary outcome measure, and parent anxiety/depression, parenting, family functioning/relationships, child behavioural/emotional problems and adaptive skills, child and parent quality of life, and family services receipt as the proposed secondary outcome measures).

Results

Seventy-four families (95 carers) were recruited from three sites (with 37 families allocated to the intervention). From referrals, the recruitment rate was 65% (95% confidence interval 56% to 74%). Seventy-two per cent of families were retained at the 12-month follow-up (95% confidence interval 60% to 81%). Exploratory regression analysis showed that the mean Warwick–Edinburgh Mental Well-Being Scale well-being score was 3.96 points higher in the intervention group (95% confidence interval –1.39 to 9.32 points) at 12 months post randomisation. High levels of data completeness were achieved on returned questionnaires. Interviews (n = 25) confirmed that (1) recruitment, randomisation processes and the intervention were acceptable to family carers, E-PAtS facilitators and community staff; (2) E-PAtS delivery were consistent with the logic model; and (3) researchers requesting consent in future for routine data would be acceptable. Recorded E-PAtS sessions demonstrated good fidelity (96% of components present). Adherence (i.e. at least one carer from the family attending five out of eight E-PAtS sessions) was 76%. Health-related quality-of-life and services receipt data were gathered successfully. An online UK survey to assess usual practice (n = 673) showed that 10% of families of young children with intellectual disability received any intervention over 12 months. A provider survey (n = 15) indicated willingness to take part in future research.

Limitations

Obtaining session recordings for fidelity was difficult. Recruitment processes need to be reviewed to improve diversity and strategies are needed to improve primary outcome completion.

Conclusions

Study processes were feasible. The E-PAtS intervention was well received and outcomes for families were positive. A barrier to future organisation participation is funding for intervention costs. A definitive trial to test the clinical effectiveness and cost-effectiveness of E-PAtS would be feasible.

Trial registration

Current Controlled Trials ISRCTN70419473.

Funding

This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme and will be published in full in Public Health Research; Vol. 10, No. 2. See the NIHR Journals Library website for further project information.

Combining Multiple Decedent Data Sources for a Population-Based Picture of End-of-Life Healthcare Utilization

CONTEXT

Although health systems need to track utilization and mortality, it can be difficult to obtain reliable information on patients who die outside of the health system. This leads to missing data and introduces the potential for bias.

OBJECTIVES

To evaluate the linkage of patient death data sources with a tertiary health system electronic health record (EHR) to increase the accuracy of health system end-of-life healthcare utilization data in the last month and six months of life.

METHODS

The federal Death Master File (DMF) and North Carolina Department of Health and Human Services (NC DHHS) decedent files from 2017 and 2018 were linked to a health system EHR. Descriptive statistics and chi-square tests were utilized to define impact of additional data sources with demographic data and end-of-life utilization.

RESULTS

A total of 65,935 patient deaths were identified through our multi-step data integration process. Approximately a quarter of patients (28.3%) had at least one inpatient or outpatient health system encounter in the last six months of life. Of these, patient deaths identified only in the NC DHHS file were less likely (OR 0.45 [95%CI 0.39-0.52]) to be hospitalized in the last month of life.

CONCLUSION

We describe a method to supplement EHR data with decedent information across data sources. While additional decedent data improves the accuracy of death data in the health system, patient healthcare utilization is biased towards those who use the health system at the end of life.

AI-based clinical decision-making systems in palliative medicine: ethical challenges

BACKGROUND

Improving palliative care (PC) is demanding due to the increase in people with PC needs over the next few years. An early identification of PC needs is fundamental in the care approach: it provides effective patient-centred care and could improve outcomes such as patient quality of life, reduction of the overall length of hospitalisation, survival rate prolongation, the satisfaction of both the patients and caregivers and cost-effectiveness.

METHODS

We reviewed literature with the objective of identifying and discussing the most important ethical challenges related to the implementation of AI-based data processing services in PC and advance care planning.

RESULTS

AI-based mortality predictions can signal the need for patients to obtain access to personalised communication or palliative care consultation, but they should not be used as a unique parameter to activate early PC and initiate an ACP. A number of factors must be included in the ethical decision-making process related to initiation of ACP conversations, among which are autonomy and quality of life, the risk of worsening healthcare status, the commitment by caregivers, the patients' psychosocial and spiritual distress and their wishes to initiate EOL discussions CONCLUSIONS: Despite the integration of artificial intelligence (AI)-based services into routine healthcare practice could have a positive effect of promoting early activation of ACP by means of a timely identification of PC needs, from an ethical point of view, the provision of these automated techniques raises a number of critical issues that deserve further exploration.

Evidence on the economic value of end-of-life and palliative care interventions: a narrative review of reviews

BACKGROUND

As the demand for palliative care increases, more information is needed on how efficient different types of palliative care models are for providing care to dying patients and their caregivers. Evidence on the economic value of treatments and interventions is key to informing resource allocation and ultimately improving the quality and efficiency of healthcare delivery. We assessed the available evidence on the economic value of palliative and end-of-life care interventions across various settings.

METHODS

Reviews published between 2000 and 2019 were included. We included reviews that focused on cost-effectiveness, intervention costs and/or healthcare resource use. Two reviewers extracted data independently and in duplicate from the included studies. Data on the key characteristics of the studies were extracted, including the aim of the study, design, population, type of intervention and comparator, (cost-) effectiveness resource use, main findings and conclusions.

RESULTS

A total of 43 reviews were included in the analysis. Overall, most evidence on cost-effectiveness relates to home-based interventions and suggests that they offer substantial savings to the health system, including a decrease in total healthcare costs, resource use and improvement in patient and caregivers' outcomes. The evidence of interventions delivered across other settings was generally inconsistent.

CONCLUSIONS

Some palliative care models may contribute to dual improvement in quality of care via lower rates of aggressive medicalization in the last phase of life accompanied by a reduction in costs. Hospital-based palliative care interventions may improve patient outcomes, healthcare utilization and costs. There is a need for greater consistency in reporting outcome measures, the informal costs of caring, and costs associated with hospice.

Using administrative health data for palliative and end of life care research in Ireland: potential and challenges

Background: This study aims to examine the potential of currently available administrative health and social care data for palliative and end-of-life care (PEoLC) research in Ireland. Objectives include to i) identify data sources for PEoLC research ii) describe the challenges and opportunities of using these and iii) evaluate the impact of recent health system reforms and changes to data protection laws.

Methods: The 2017 Health Information and Quality Authority catalogue of health and social care datasets was cross-referenced with a recognised list of diseases with associated palliative care needs. Criteria to assess the datasets included population coverage, data collected, data dictionary and data model availability, and mechanisms for data access.

Results: Nine datasets with potential for PEoLC research were identified, including death certificate data, hospital episode data, pharmacy claims data,  one national survey, four disease registries (cancer, cystic fibrosis, motor neurone and interstitial lung disease) and a national renal transplant registry.  The ad hoc development of the health system in Ireland has resulted in i) a fragmented information infrastructure resulting in gaps in data collections particularly in the primary and community care sector where much palliative care is delivered, ii) ill-defined data governance arrangements across service providers, many of whom are not part of the publically funded health service and iii) systemic and temporal issues that affect data quality. Initiatives to improve data collections include introduction of i) patient unique identifiers, ii) health entity identifiers and iii) integration of the Eircode postcodes. Recently enacted general data protection and health research regulations will clarify legal and ethical requirements for data use.

Conclusions: Ongoing reform initiatives and recent changes to data privacy laws combined with detailed knowledge of the datasets, appropriate permissions, and good study design will facilitate future use of administrative health and social care data for PEoLC research in Ireland.

Acute care utilisation towards the end of life and the place of death for patients with serious mental disorders: a register-based cohort study in South London

OBJECTIVES

The aim of the study was to explore acute care utilisation towards end of life by and the place of death for patients with serious mental disorders and to demonstrate any inequalities in end-of-life care faced by this patient group.

STUDY DESIGN

This is a retrospective cohort study using linked, routinely collected data.

METHODS

This study used linked data extracted from mental health records, Hospital Episode Statistics and mortality data. Adult cases (≥18 years old) were included if they had a serious mental disorder and died between 2007 and 2015. Multiple imputation was used to manage missing data, and generalised linear models were used to assess multiple adjusted associations between sociodemographic and clinical explanatory variables and acute service use at the end of life and in-hospital deaths.

RESULTS

A cohort of 1350 adults was analysed. More than half visited the accident and emergency (A&E) department in the last 90 days of life, and a third had a burdensome transition (multiple hospital admissions in the last 90 days of life or at least one in the last three days); the median number of days spent in the hospital was 4 (range: 0-86). Having more comorbidities was a strong correlate of more A&E visits (adjusted odds ratio [OR] = 1.03 [95% confidence interval = 1.02-1.04]), burdensome transitions (adjusted OR = 1.06 [1.04-1.08]) and days spent in the hospital (adjusted OR = 1.04 [1.03-1.05]). Having a diagnosis of schizophrenia spectrum disorder, compared with other serious mental disorder diagnoses, was associated with fewer A&E visits (adjusted OR = 0.78 [0.71-0.88]) and fewer days in the hospital (adjusted OR = 0.77 [0.66-0.89]). Younger age was associated with more A&E visits (adjusted OR = 1.28 [1.07-1.53]) and fewer days spent in the hospital (adjusted OR = 0.70 [0.52-0.95]). Hospital deaths were high (51%), and in a fully adjusted model, they were associated with having more comorbidities (adjusted OR = 1.02 [1.01-1.03]) and accessing acute care at the end of life (including more A&E visits; adjusted OR = 1.07 [1.05-1.10]), burdensome transitions (adjusted OR = 1.53 [1.37-1.71]) and days spent in the hospital (adjusted OR = 2.05 [1.70-247]).

CONCLUSION

People with comorbidities are more likely to use more burdensome acute health care at the end of life and are more likely to die in the hospital. Hospital deaths could be reduced, and end-of-life care could be improved by targeting patients with comorbidities and who are accessing more acute healthcare services.

Using linked administrative health data for palliative and end of life care research in Ireland: potential and challenges

Background: This study aims to examine the potential of currently available administrative health data for palliative and end-of-life care (PEoLC) research in Ireland. Objectives include to i) identify administrative health data sources for PEoLC research ii) describe the challenges and opportunities of using these and iii) estimate  the impact of recent health system reforms and changes to data protection laws.  Methods: The 2017 Health Information and Quality Authority catalogue of health and social care datasets was cross-referenced with a recognised list of diseases with associated palliative care needs. Criteria to assess the datasets included population coverage, data collected, data dictionary and data model availability and mechanisms for data access. Results: Eight datasets with potential for PEoLC research were identified, including four disease registries, (cancer, cystic fibrosis, motor neurone and interstitial lung disease), death certificate data, hospital episode data, community prescription data and one national survey. The ad hoc development of the health system in Ireland has resulted in i) a fragmented information infrastructure resulting in gaps in data collections particularly in the primary and community care sector where much palliative care is delivered, ii) ill-defined data governance arrangements across service providers, many of whom are not part of the publically funded health service and iii) systemic and temporal issues that affect data quality. Initiatives to improve data collections include introduction of i) patient unique identifiers, ii) health entity identifiers and iii) integration of the eircode postcodes. Recently enacted general data protection and health research regulations will clarify legal and ethical requirements for data  use. Conclusions: With appropriate permissions, detailed knowledge of the datasets and good study design currently available administrative health data can be used for PEoLC research. Ongoing reform initiatives and recent changes to data privacy laws will facilitate future use of administrative health data for PEoLC research.

Healthcare trajectories and costs in the last year of life: a retrospective primary care and hospital analysis

OBJECTIVES

To analyse healthcare utilisation and costs in the last year of life in England, and to study variation by cause of death, region of patient residence and socioeconomic status.

METHODS

This is a retrospective cohort study. Individuals aged 60 years and over (N=108 510) who died in England between 2010 and 2017 were included in the study.

RESULTS

Healthcare utilisation and costs in the last year of life increased with proximity to death, particularly in the last month of life. The mean total costs were higher among males (£8089) compared with females (£6898) and declined with age at death (£9164 at age 60-69 to £5228 at age 90+) with inpatient care accounting for over 60% of total costs. Costs decline with age at death (0.92, 95% CI 0.88 to 0.95, p<0.0001 for age group 90+ compared with to the reference category age group 60-69) and were lower among females (0.91, 95% CI 0.90 to 0.92, p<0.0001 compared with males). Costs were higher (1.09, 95% CI 1.01 to 1.14, p<0.0001) in London compared with other regions.

CONCLUSIONS

Healthcare utilisation and costs in the last year of life increase with proximity to death, particularly in the last month of life. Finer geographical data and information on healthcare supply would allow further investigating whether people receiving more planned care by primary care and or specialist palliative care towards the end of life require less acute care.

Unscheduled and out-of-hours care for people in their last year of life: a retrospective cohort analysis of national datasets

OBJECTIVES

To analyse patterns of use and costs of unscheduled National Health Service (NHS) services for people in the last year of life.

DESIGN

Retrospective cohort analysis of national datasets with application of standard UK costings.

PARTICIPANTS AND SETTING

All people who died in Scotland in 2016 aged 18 or older (N=56 407).

MAIN OUTCOME MEASURES

Frequency of use of the five unscheduled NHS services in the last 12 months of life by underlying cause of death, patient demographics, Continuous Unscheduled Pathways (CUPs) followed by patients during each care episode, total NHS and per-patient costs.

RESULTS

53 509 patients (94.9%) had at least one contact with an unscheduled care service during their last year of life (472 360 contacts), with 34.2% in the last month of life. By linking patient contacts during each episode of care, we identified 206 841 CUPs, with 133 980 (64.8%) starting out-of-hours. People with cancer were more likely to contact the NHS telephone advice line (63%) (χ² (4)=1004, p<0.001) or primary care out-of-hours (62%) (χ² (4)=1924,p<0.001) and have hospital admissions (88%) (χ² (4)=2644, p<0.001). People with organ failure (79%) contacted the ambulance service most frequently (χ² (4)=584, p<0.001). Demographic factors associated with more unscheduled care were older age, social deprivation, living in own home and dying of cancer. People dying with organ failure formed the largest group in the cohort and had the highest NHS costs as a group. The cost of providing services in the community was estimated at 3.9% of total unscheduled care costs despite handling most out-of-hours calls.

CONCLUSIONS

Over 90% of people used NHS unscheduled care in their last year of life. Different underlying causes of death and demographic factors impacted on initial access and subsequent pathways of care. Managing more unscheduled care episodes in the community has the potential to reduce hospital admissions and overall costs.

Developing an ontology for representing the domain knowledge specific to non-pharmacological treatment for agitation in dementia

INTRODUCTION

A large volume of clinical care data has been generated for managing agitation in dementia. However, the valuable information in these data has not been used effectively to generate insights for improving the quality of care. Application of artificial intelligence technologies offers us enormous opportunities to reuse these data. For health data science to achieve this, this study focuses on using ontology to coding clinical knowledge for non-pharmacological treatment of agitation in a machine-readable format.

METHODS

The resultant ontology-Dementia-Related Agitation Non-Pharmacological Treatment Ontology (DRANPTO)-was developed using a method adopted from the NeOn methodology.

RESULTS

DRANPTO consisted of 569 concepts and 48 object properties. It meets the standards for biomedical ontology.

DISCUSSION

DRANPTO is the first comprehensive semantic representation of non-pharmacological management for agitation in dementia in the long-term care setting. As a knowledge base, it will play a vital role to facilitate the development of intelligent systems for managing agitation in dementia.

Role of Hospice Care at the End of Life for People With Cancer

Patient-defined factors that are important at the end of life include being physically independent for as long as possible, good symptom control, and spending quality time with friends and family. Hospice care adds to the quality of care and these patient-centered priorities for people with cancer and their families in the last weeks and days of life. Evidence from large observational studies demonstrate that hospice care can improve outcomes directly and support better and more appropriate health care use for people in the last stages of cancer.

Team-based community hospice care has measurable benefits for patients, their family caregivers, and health services. In addition to improved symptom control for patients and a greater likelihood of time spent at home, caregiver outcomes are better when hospice care is accessed: informational needs are better met, and caregivers have an improved ability to move on with life after the patient’s death compared with people who did not have access to these services.

Hospice care continues to evolve as its reach expands and the needs of patients continue to broaden. This is reflected in the transition from hospice being based on excellence in nursing to teams with a broad range of health professionals to meet the complex and changing needs of patients and their families. Additional integration of cancer services with hospice care will help to provide more seamless care for patients and supporting family caregivers during their caregiving and after the death of the patient.

End-of-life care in general practice: clinic-based data collection

BACKGROUND

There are no processes that routinely assess end-of-life care in Australian general practice. This study aimed to develop a data collection process which could collect observational data on end-of-life care from Australian general practitioners (GPs) via a questionnaire and clinical data from general practice software.

METHODS

The data collection process was developed based on a modified Delphi study, then pilot tested with GPs through online surveys across three Australian states and data extraction from general practice software, and finally evaluated through participant interviews.

RESULTS

The developed data collection process consisted of three questionnaires: Basic Practice Descriptors (32 items), Clinical Data Query (32 items) and GP-completed Questionnaire (21 items). Data extraction from general practice software was performed for 97 decedents of 10 GPs and gathered data on prescriptions, investigations and referral patterns. Reports on care of 272 decedents were provided by 63 GPs. The GP-completed Questionnaire achieved a satisfactory level of validity and reliability. Our interviews with 23 participating GPs demonstrated the feasibility and acceptability of this data collection process in Australian general practice.

CONCLUSIONS

The data collection process developed and tested in this study is feasible and acceptable for Australian GPs, and comprehensively covers the major components of end-of-life care. Future studies could develop an automated data extraction tool to reduce the time and recall burden for GPs. These findings will help build a nationwide integrated information network for primary end-of-life care in Australia.

Novel Data Linkages to Characterize Palliative and End-Of-Life Care: Challenges and Considerations

CONTEXT

Working groups have called for linkages of existing and diverse databases to improve quality measurement in palliative and end-of-life (EOL) care, but limited data are available on the challenges of using different data sources to measure such care.

OBJECTIVES

To assess concordance of data obtained from different sources in a novel linkage of death certificates, electronic health records (EHRs), cancer registry data, and insurance claims for patients who died with cancer.

METHODS

We joined a database of Washington State death certificates and EHR to a data repository of commercial health plan enrollment and claims files linked to registry records from Puget Sound Cancer Surveillance System. We assessed care in the last month including hospitalizations, intensive care unit (ICU) admissions, emergency department visits, imaging scans, radiation, and hospice, plus chemotherapy in the last 14 days. We used a Chi-squared test to compare differences between health care in EHR and claims.

RESULTS

Records of hospitalization, ICU use, and emergency department use were 33%, 15%, and 33% lower in EHR versus claims, respectively. Radiation, hospice, and imaging were 6%, 14%, and 28% lower, respectively, in EHR, but chemotherapy was 4% higher than that in claims. These differences were statistically different for hospice (P < 0.02), hospitalization, ICU, ER, and imaging (all P < 0.01) but not radiation (P = 0.12) or chemotherapy (P = 0.29).

CONCLUSION

We found substantial variation between EHR and claims for EOL health-care use. Reliance on EHR will miss some health-care use, while claims will not capture the complex clinical details in EHR that can help define the quality of palliative care and EOL health-care utilization.

Improving palliative and end-of-life care with machine learning and routine data: a rapid review

Introduction: Improving end-of-life (EOL) care is a priority worldwide as this population experiences poor outcomes and accounts disproportionately for costs. In clinical practice, physician judgement is the core method of identifying EOL care needs but has important limitations. Machine learning (ML) is a subset of artificial intelligence advancing capacity to identify patterns and make predictions using large datasets.  ML approaches have the potential to improve clinical decision-making and policy design, but there has been no systematic assembly of current evidence. Methods: We conducted a rapid review, searching systematically seven databases from inception to December 31st, 2018: EMBASE, MEDLINE, Cochrane Library, PsycINFO, WOS, SCOPUS and ECONLIT.  We included peer-reviewed studies that used ML approaches on routine data to improve palliative and EOL care for adults.  Our specified outcomes were survival, quality of life (QoL), place of death, costs, and receipt of high-intensity treatment near end of life.  We did not search grey literature and excluded material that was not a peer-reviewed article. Results: The database search identified 426 citations. We discarded 162 duplicates and screened 264 unique title/abstracts, of which 22 were forwarded for full text review.  Three papers were included, 18 papers were excluded and one full text was sought but unobtainable.  One paper predicted six-month mortality, one paper predicted 12-month mortality and one paper cross-referenced predicted 12-month mortality with healthcare spending.  ML-informed models outperformed logistic regression in predicting mortality but poor prognosis is a weak driver of costs.  Models using only routine administrative data had limited benefit from ML methods. Conclusion: While ML can in principle help to identify those at risk of adverse outcomes and inappropriate treatment near EOL, applications to policy and practice are formative.  Future research must not only expand scope to other outcomes and longer timeframes, but also engage with individual preferences and ethical challenges.

Improving palliative and end-of-life care with machine learning and routine data: a rapid review

Introduction: Improving end-of-life (EOL) care is a priority worldwide as this population experiences poor outcomes and accounts disproportionately for costs. In clinical practice, physician judgement is the core method of identifying EOL care needs but has important limitations. Machine learning (ML) is a subset of artificial intelligence advancing capacity to identify patterns and make predictions using large datasets.  ML approaches have the potential to improve clinical decision-making and policy design, but there has been no systematic assembly of current evidence. Methods: We conducted a rapid review, searching systematically seven databases from inception to December 31st, 2018: EMBASE, MEDLINE, Cochrane Library, PsycINFO, WOS, SCOPUS and ECONLIT.  We included peer-reviewed studies that used ML approaches on routine data to improve palliative and EOL care for adults.  Our specified outcomes were survival, quality of life (QoL), place of death, costs, and receipt of high-intensity treatment near end of life.  We did not search grey literature and excluded material that was not a peer-reviewed article. Results: The database search identified 426 citations. We discarded 162 duplicates and screened 264 unique title/abstracts, of which 22 were forwarded for full text review.  Three papers were included, 18 papers were excluded and one full text was sought but unobtainable.  One paper predicted six-month mortality, one paper predicted 12-month mortality and one paper cross-referenced predicted 12-month mortality with healthcare spending.  ML-informed models outperformed logistic regression in predicting mortality but poor prognosis is a weak driver of costs.  Models using only routine administrative data had limited benefit from ML methods. Conclusion: While ML can in principle help to identify those at risk of adverse outcomes and inappropriate treatment near EOL, applications to policy and practice are formative.  Future research must not only expand scope to other outcomes and longer timeframes, but also engage with individual preferences and ethical challenges.

Socioeconomic position and use of healthcare in the last year of life: A systematic review and meta-analysis

BACKGROUND

Low socioeconomic position (SEP) is recognized as a risk factor for worse health outcomes. How socioeconomic factors influence end-of-life care, and the magnitude of their effect, is not understood. This review aimed to synthesise and quantify the associations between measures of SEP and use of healthcare in the last year of life.

METHODS AND FINDINGS

MEDLINE, EMBASE, PsycINFO, CINAHL, and ASSIA databases were searched without language restrictions from inception to 1 February 2019. We included empirical observational studies from high-income countries reporting an association between SEP (e.g., income, education, occupation, private medical insurance status, housing tenure, housing quality, or area-based deprivation) and place of death, plus use of acute care, specialist and nonspecialist end-of-life care, advance care planning, and quality of care in the last year of life. Methodological quality was evaluated using the Newcastle-Ottawa Quality Assessment Scale (NOS). The overall strength and direction of associations was summarised, and where sufficient comparable data were available, adjusted odds ratios (ORs) were pooled and dose-response meta-regression performed. A total of 209 studies were included (mean NOS quality score of 4.8); 112 high- to medium-quality observational studies were used in the meta-synthesis and meta-analysis (53.5% from North America, 31.0% from Europe, 8.5% from Australia, and 7.0% from Asia). Compared to people living in the least deprived neighbourhoods, people living in the most deprived neighbourhoods were more likely to die in hospital versus home (OR 1.30, 95% CI 1.23-1.38, p < 0.001), to receive acute hospital-based care in the last 3 months of life (OR 1.16, 95% CI 1.08-1.25, p < 0.001), and to not receive specialist palliative care (OR 1.13, 95% CI 1.07-1.19, p < 0.001). For every quintile increase in area deprivation, hospital versus home death was more likely (OR 1.07, 95% CI 1.05-1.08, p < 0.001), and not receiving specialist palliative care was more likely (OR 1.03, 95% CI 1.02-1.05, p < 0.001). Compared to the most educated (qualifications or years of education completed), the least educated people were more likely to not receive specialist palliative care (OR 1.26, 95% CI 1.07-1.49, p = 0.005). The observational nature of the studies included and the focus on high-income countries limit the conclusions of this review.

CONCLUSIONS

In high-income countries, low SEP is a risk factor for hospital death as well as other indicators of potentially poor-quality end-of-life care, with evidence of a dose response indicating that inequality persists across the social stratum. These findings should stimulate widespread efforts to reduce socioeconomic inequality towards the end of life.

Place of death in a small island state: a death certificate population study

OBJECTIVES

Low/middle-income countries, particularly Small Island Developing States, face many challenges including providing good palliative care and choice in place of care and death, but evidence of the circumstances of dying to inform policy is often lacking. This study explores where people die in Trinidad and Tobago and examines and describes the factors associated with place of death.

METHODS

A population-level analysis of routinely collected death certificate and supplementary health data where the unit of analysis was the recorded death. We followed the Reporting of Studies Conducted Using Observational Routinely Collected Health Data reporting guidelines, an extension of Strengthening the Reporting of Observational Studies in Epidemiology, on a deidentified data set on decedents (n=10 221) extracted from International Statistical Classification of Diseases version 10 coded death records for the most recent available year, 2010.

RESULTS

Of all deaths, 55.4% occurred in a government hospital and 29.7% in a private home; 65.3% occurred in people aged 60 years and older. Cardiovascular disease (23.6%), malignancies (15.5%) and diabetes mellitus (14.7%) accounted for over half of all deaths. Dying at home becomes more likely with increasing age (70-89 years (OR 1.91, 95% CI 1.73 to 2.10) and 90-highest (OR 3.63, 95% CI 3.08 to 4.27)), and less likely for people with malignancies (OR 0.85, 95% CI 0.74 to 0.97), cerebrovascular disease (OR 0.61, 95% CI 0.51 to 0.72) and respiratory disease (OR 0.74, 95% CI 0.59 to 0.91).

CONCLUSION

Place of death is influenced by age, sex, race/ethnicity, underlying cause of death and urbanisation. There is inequality between ethnic groups regarding place of care and death; availability, affordability and access to end-of-life care in different settings require attention.

A Population-Based Conceptual Framework for Evaluating the Role of Healthcare Services in Place of Death

BACKGROUND

There is a significant geographical disparity in place of death. Socio-demographic and disease-related variables only explain less than a quarter of the variation. Healthcare service factors may account for some (or much) of the remaining variation but their effects have never been systematically evaluated, partly due to the lack of a conceptual framework. This study aims to propose a population-based framework to guide the evaluation of the role of the healthcare service factors in place of death.

METHODS

Review and synthesis of health service models that include the impact of a service component on either place of death/end of life care outcomes or service access/utilization.

RESULTS

The framework conceptualizes the impact of healthcare services on the place of death as starting from the end of life care policies that in turn influence service commissioning and shape healthcare service characteristics, including service type, service capacity-facilities, service location, and workforce, through which service utilization and ultimately place of death are affected. Patient socio-demographics, disease-related variables, family and community support and social care also influence place of death, but they are not the focus of this framework and therefore are grouped as needs and other environmental factors. Information on service utilization, together with the place of death, creates loop feedback to inform policy and service commission.

CONCLUSIONS

The framework provides guidance for analysis aiming to understand the role of healthcare services in place of death. It aids the interpretation of results in the light of existing knowledge and potentially identifies service factors that can be addressed to improve end of life care.

How We Should Assess the Delivery of End-Of-Life Care in General Practice? A Systematic Review

BACKGROUND

The majority of end-of-life (EOL) care occurs in general practice. However, we still have little knowledge about how this care is delivered or how it can be assessed and supported.

AIM

(i) To review the existing evaluation tools used for assessment of the delivery of EOL care from the perspective of general practice; (ii) To describe how EOL care is provided in general practice; (iii) To identify major areas of concern in providing EOL care in this context.

DESIGN

A systematic review.

DATA SOURCES

Systematic searches of major electronic databases (Medline, EMBASE, PsycINFO, and CINAHL) from inception to 2017 were used to identify evaluation tools focusing on organizational structures/systems and process of end-of-life care from a general practice perspective.

RESULTS

A total of 43 studies representing nine evaluation tools were included. A relatively restricted focus and lack of validation were common limitations. Key general practitioner (GP) activities assessed by the evaluation tools were summarized and the main issues in current GP EOL care practice were identified.

CONCLUSIONS

The review of evaluation tools revealed that GPs are highly involved in management of patients at the EOL, but there are a range of issues relating to the delivery of care. An EOL care registration system integrated with electronic health records could provide an optimal approach to address the concerns about recall bias and time demands in retrospective analyses. Such a system should ideally capture the core GP activities and any major issues in care provision on a case-by-case basis.

Death at no cost? Persons with no health insurance claims in the last year of life in Switzerland

Background

Lack of health insurance claims (HIC) in the last year of life might indicate suboptimal end-of-life care, but reasons for no HIC are not fully understood because information on causes of death is often missing. We investigated association of no HIC with characteristics of individuals and their place of residence.

Methods

We analysed HIC of persons who died between 2008 and 2010, which were obtained from six providers of mandatory Swiss health insurance. We probabilistically linked these persons to death certificates to get cause of death information and analysed data using sex-stratified, multivariable logistic regression. Supplementary analyses looked at selected subgroups of persons according to the primary cause of death.

Results

The study population included 113,277 persons (46% males). Among these persons, 1199 (proportion 0.022, 95% CI: 0.021–0.024) males and 803 (0.013, 95% CI: 0.012–0.014) females had no HIC during the last year of life. We found sociodemographic and health differentials in the lack of HIC at the last year of life among these 2002 persons. The likelihood of having no HIC decreased steeply with older age. Those who died of cancer were more likely to have HIC (adjusted odds ratio for males 0.17, 95% CI: 0.13–0.22; females 0.19, 95% CI: 0.12–0.28) whereas those dying of mental and behavioural disorders (AOR males 1.83, 95% CI:1.42–2.37; females 1.65, 95% CI: 1.27–2.14), and males dying of suicide (AOR 2.15, 95% CI: 1.72–2.69) and accidents (AOR 2.41, 95% CI: 1.96–2.97) were more likely to have none. Single, widowed, and divorced persons also were more likely to have no HIC (AORs in range of 1.29–1.80). There was little or no association between the lack of HIC and characteristics of region of residence. Patterns of no HIC differed across main causes of death. Associations with age and civil status differed in particular for persons who died of cancer, suicide, accidents and assaults, and mental and behavioural disorders.

Conclusions

Particular groups might be more likely to not seek care or not report health insurance costs to insurers. Researchers should be aware of this aspect of health insurance data and account for persons who lack HIC.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-2984-2) contains supplementary material, which is available to authorized users.

Indicators for early assessment of palliative care in lung cancer patients: a population study using linked health data

BACKGROUND

Analysing linked, routinely collected data may be useful to identify characteristics of patients with suspected lung cancer who could benefit from early assessment for palliative care. The aim of this study was to compare characteristics of newly diagnosed lung cancer patients dying within 30 days of diagnosis (short term survivors) with those surviving more than 30 days. To identify indicators for early palliative care assessment we distinguished between characteristics available at diagnosis (age, gender, smoking status, marital status, comorbid disease, admission type, tumour stage and histology) from those available post diagnosis. A second aim was to examine the association between receiving any tumour-directed treatment, place of death and survival time.

METHODS

A retrospective observational population based study comparing lung cancer patients who died within 30 days of diagnosis (short term survivors) with those who survived longer using Chi-squared tests and logistic regression. Incident lung cancer (ICD-03:C34) patients diagnosed 2005-2012 inclusive who died before 01-01-2014 (n = 14,228) were identified from the National Cancer Registry of Ireland linked to death certificate data and acute hospital episode data.

RESULTS

One in five newly diagnosed lung cancer patients died within 30 days of diagnosis. After adjusting for stage and histology, death within 30 days was higher in patients who were aged 80 years or older (adjusted OR 2.46; 95%CI 2.05-3.96; p < 0.001), patients with emergency admissions at diagnosis (adjusted OR 2.96; 95%CI 2.61-3.37; p < 0.001) and patients with any comorbidities at diagnosis (adjusted OR 1.32 95%CI 1.15-1.52; p < 0.001). Overall, 75% of those who died within 30 days died in hospital compared to 43% of longer term survivors.

CONCLUSIONS

We have shown a high proportion of lung cancer patients who die within 30 days of diagnosis are older, have comorbidities and are admitted through the emergency department. These characteristics, available at diagnosis, may be useful prognostic factors to guide decisions on early assessment for palliative care for lung cancer patients. Patients who die shortly after diagnosis are more likely to die in hospital so reporting place of death by survival time may be useful to evaluate interventions to reduce deaths in acute hospitals.

Phase of Illness in palliative care: Cross-sectional analysis of clinical data from community, hospital and hospice patients

BACKGROUND

Phase of Illness describes stages of advanced illness according to care needs of the individual, family and suitability of care plan. There is limited evidence on its association with other measures of symptoms, and health-related needs, in palliative care.

AIMS

The aims of the study are as follows. (1) Describe function, pain, other physical problems, psycho-spiritual problems and family and carer support needs by Phase of Illness. (2) Consider strength of associations between these measures and Phase of Illness.

DESIGN AND SETTING

Secondary analysis of patient-level data; a total of 1317 patients in three settings. Function measured using Australia-modified Karnofsky Performance Scale. Pain, other physical problems, psycho-spiritual problems and family and carer support needs measured using items on Palliative Care Problem Severity Scale.

RESULTS

Australia-modified Karnofsky Performance Scale and Palliative Care Problem Severity Scale items varied significantly by Phase of Illness. Mean function was highest in stable phase (65.9, 95% confidence interval = 63.4-68.3) and lowest in dying phase (16.6, 95% confidence interval = 15.3-17.8). Mean pain was highest in unstable phase (1.43, 95% confidence interval = 1.36-1.51). Multinomial regression: psycho-spiritual problems were not associated with Phase of Illness ( χ² = 2.940, df = 3, p = 0.401). Family and carer support needs were greater in deteriorating phase than unstable phase (odds ratio (deteriorating vs unstable) = 1.23, 95% confidence interval = 1.01-1.49). Forty-nine percent of the variance in Phase of Illness is explained by Australia-modified Karnofsky Performance Scale and Palliative Care Problem Severity Scale.

CONCLUSION

Phase of Illness has value as a clinical measure of overall palliative need, capturing additional information beyond Australia-modified Karnofsky Performance Scale and Palliative Care Problem Severity Scale. Lack of significant association between psycho-spiritual problems and Phase of Illness warrants further investigation.

Future cancer research priorities in the USA: a Lancet Oncology Commission

We are in the midst of a technological revolution that is providing new insights into human biology and cancer. In this era of big data, we are amassing large amounts of information that is transforming how we approach cancer treatment and prevention. Enactment of the Cancer Moonshot within the 21st Century Cures Act in the USA arrived at a propitious moment in the advancement of knowledge, providing nearly US$2 billion of funding for cancer research and precision medicine. In 2016, the Blue Ribbon Panel (BRP) set out a roadmap of recommendations designed to exploit new advances in cancer diagnosis, prevention, and treatment. Those recommendations provided a high-level view of how to accelerate the conversion of new scientific discoveries into effective treatments and prevention for cancer. The US National Cancer Institute is already implementing some of those recommendations. As experts in the priority areas identified by the BRP, we bolster those recommendations to implement this important scientific roadmap. In this Commission, we examine the BRP recommendations in greater detail and expand the discussion to include additional priority areas, including surgical oncology, radiation oncology, imaging, health systems and health disparities, regulation and financing, population science, and oncopolicy. We prioritise areas of research in the USA that we believe would accelerate efforts to benefit patients with cancer. Finally, we hope the recommendations in this report will facilitate new international collaborations to further enhance global efforts in cancer control.

Electronic Support for Retrospective Analysis in the Field of Radiation Oncology: Proof of Principle Using an Example of Fractionated Stereotactic Radiotherapy of 251 Meningioma Patients

Introduction

The purpose of this study is to verify the possible benefit of a clinical data warehouse (DWH) for retrospective analysis in the field of radiation oncology.

Material and methods

We manually and electronically (using DWH) evaluated demographic, radiotherapy, and outcome data from 251 meningioma patients, who were irradiated from January 2002 to January 2015 at the Department of Radiation Oncology of the Erlangen University Hospital. Furthermore, we linked the Oncology Information System (OIS) MOSAIQ^® to the DWH in order to gain access to irradiation data. We compared the manual and electronic data retrieval method in terms of congruence of data, corresponding time, and personal requirements (physician, physicist, scientific associate).

Results

The electronically supported data retrieval (DWH) showed an average of 93.9% correct data and significantly (p = 0.009) better result compared to manual data retrieval (91.2%). Utilizing a DWH enables the user to replace large amounts of manual activities (668 h), offers the ability to significantly reduce data collection time and labor demand (35 h), while simultaneously improving data quality. In our case, work time for manually data retrieval was 637 h for the scientific assistant, 26 h for the medical physicist, and 5 h for the physician (total 668 h).

Conclusion

Our study shows that a DWH is particularly useful for retrospective analysis in the radiation oncology field. Routine clinical data for a large patient group can be provided ready for analysis to the scientist and data collection time can be significantly reduced. Furthermore, linking multiple data sources in a DWH offers the ability to improve data quality for retrospective analysis, and future research can be simplified.

Reporting of clinically diagnosed dementia on death certificates: retrospective cohort study

BACKGROUND

mortality statistics are a frequently used source of information on deaths in dementia but are limited by concerns over accuracy.

OBJECTIVE

to investigate the frequency with which clinically diagnosed dementia is recorded on death certificates, including predictive factors.

METHODS

a retrospective cohort study assembled using a large mental healthcare database in South London, linked to Office for National Statistics mortality data. People with a clinical diagnosis of dementia, aged 65 or older, who died between 2006 and 2013 were included. The main outcome was death certificate recording of dementia.

RESULTS

in total, 7,115 people were identified. Dementia was recorded on 3,815 (53.6%) death certificates. Frequency of dementia recording increased from 39.9% (2006) to 63.0% (2013) (odds ratio (OR) per year increment 1.11, 95% CI 1.07-1.15). Recording of dementia was more likely if people were older (OR per year increment 1.02, 95% CI 1.01-1.03), and for those who died in care homes (OR 1.89, 95% CI 1.50-2.40) or hospitals (OR 1.14, 95% CI 1.03-1.46) compared with home, and less likely for people with less severe cognitive impairment (OR 0.95, 95% CI 0.94-0.96), and if the diagnosis was Lewy body (OR 0.30, 95% CI 0.15-0.62) or vascular dementia (OR 0.79, 95% CI 0.68-0.93) compared with Alzheimer's disease.

CONCLUSIONS

changes in certification practices may have contributed to the rise in recorded prevalence of dementia from mortality data. However, mortality data still considerably underestimate the population burden of dementia. Potential biases affecting recording of dementia need to be taken into account when interpreting mortality data.