Dataset Information

Development and validation of a casemix classification to predict costs of specialist palliative care provision across inpatient hospice, hospital and community settings in the UK: a study protocol.

ABSTRACT:

Introduction

Provision of palliative care is inequitable with wide variations across conditions and settings in the UK. Lack of a standard way to classify by case complexity is one of the principle obstacles to addressing this. We aim to develop and validate a casemix classification to support the prediction of costs of specialist palliative care provision.

Methods and analysis

Phase I: A cohort study to determine the variables and potential classes to be included in a casemix classification. Data are collected from clinicians in palliative care services across inpatient hospice, hospital and community settings on: patient demographics, potential complexity/casemix criteria and patient-level resource use. Cost predictors are derived using multivariate regression and then incorporated into a classification using classification and regression trees. Internal validation will be conducted by bootstrapping to quantify any optimism in the predictive performance (calibration and discrimination) of the developed classification. Phase II: A mixed-methods cohort study across settings for external validation of the classification developed in phase I. Patient and family caregiver data will be collected longitudinally on demographics, potential complexity/casemix criteria and patient-level resource use. This will be triangulated with data collected from clinicians on potential complexity/casemix criteria and patient-level resource use, and with qualitative interviews with patients and caregivers about care provision across difference settings. The classification will be refined on the basis of its performance in the validation data set.

Ethics and dissemination

The study has been approved by the National Health Service Health Research Authority Research Ethics Committee. The results are expected to be disseminated in 2018 through papers for publication in major palliative care journals; policy briefs for clinicians, commissioning leads and policy makers; and lay summaries for patients and public.

Trial registration number

ISRCTN90752212.

SUBMITTER: Guo P

PROVIDER: S-EPMC5879599 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development and validation of a casemix classification to predict costs of specialist palliative care provision across inpatient hospice, hospital and community settings in the UK: a study protocol.

Guo Ping P Dzingina Mendwas M Firth Alice M AM Davies Joanna M JM Douiri Abdel A O'Brien Suzanne M SM Pinto Cathryn C Pask Sophie S Higginson Irene J IJ Eagar Kathy K Murtagh Fliss E M FEM

BMJ open 20180317 3

<h4>Introduction</h4>Provision of palliative care is inequitable with wide variations across conditions and settings in the UK. Lack of a standard way to classify by case complexity is one of the principle obstacles to addressing this. We aim to develop and validate a casemix classification to support the prediction of costs of specialist palliative care provision.<h4>Methods and analysis</h4>Phase I: A cohort study to determine the variables and potential classes to be included in a casemix cla ...[more]

PMID: 29550781

Similar Datasets

Project description:Objective To assess the effect of specialist palliative care on quality of life and additional outcomes relevant to patients in those with advanced illness.Design Systematic review with meta-analysis.Data sources Medline, Embase, Cochrane Central Register of Controlled Trials, PsycINFO, and trial registers searched up to July 2016.Eligibility criteria for selecting studies Randomised controlled trials with adult inpatients or outpatients treated in hospital, hospice, or community settings with any advanced illness. Minimum requirements for specialist palliative care included the multiprofessional team approach. Two reviewers independently screened and extracted data, assessed the risk of bias (Cochrane risk of bias tool), and evaluated the quality of evidence (GRADE tool).Data synthesis Primary outcome was quality of life with Hedges' g as standardised mean difference (SMD) and random effects model in meta-analysis. In addition, the pooled SMDs of the analyses of quality of life were re-expressed on the global health/QoL scale (item 29 and 30, respectively) of the European Organization for Research and Treatment of Cancer QLQ-C30 (0-100, high values=good quality of life, minimal clinically important difference 8.1).Results Of 3967 publications, 12 were included (10 randomised controlled trials with 2454 patients randomised, of whom 72% (n=1766) had cancer). In no trial was integration of specialist palliative care triggered according to patients' needs as identified by screening. Overall, there was a small effect in favour of specialist palliative care (SMD 0.16, 95% confidence interval 0.01 to 0.31; QLQ-C30 global health/QoL 4.1, 0.3 to 8.2; n=1218, six trials). Sensitivity analysis showed an SMD of 0.57 (-0.02 to 1.15; global health/QoL 14.6, -0.5 to 29.4; n=1385, seven trials). The effect was marginally larger for patients with cancer (0.20, 0.01 to 0.38; global health/QoL 5.1, 0.3 to 9.7; n=828, five trials) and especially for those who received specialist palliative care early (0.33, 0.05 to 0.61, global health/QoL 8.5, 1.3 to 15.6; n=388, two trials). The results for pain and other secondary outcomes were inconclusive. Some methodological problems (such as lack of blinding) reduced the strength of the evidence.Conclusions Specialist palliative care was associated with a small effect on QoL and might have most pronounced effects for patients with cancer who received such care early. It could be most effective if it is provided early and if it identifies though screening those patients with unmet needs.Systematic review registration PROSPERO CRD42015020674.

Project description:INTRODUCTION:Compared with fee-for-service systems, prospective payment based on casemix classification is thought to promote more efficient, needs-based care provision. We aim to develop a casemix classification to predict the costs of home care in the Netherlands. METHODS AND ANALYSIS:The research is designed as a multicentre, cross-sectional cohort study using quantitative methods to identify the relative cost predictors of home care and combine these into a casemix classification, based on individual episodes of care. The dependent variable in the analyses is the cost of home care utilisation, which is operationalised through various measures of formal and informal care, weighted by the relative wage rates of staff categories. As independent variables, we will use data from a recently developed Casemix Short-Form questionnaire, combined with client information from participating home care providers' (nursing) classification systems and data on demographics and care category (ie, a classification mandated by health insurers). Cost predictors are identified using random forest variable importance measures, and then used to build regression tree models. The casemix classification will consist of the leaves of the (pruned) regression tree. Internal validation is addressed by using cross-validation at various stages of the modelling pathways. The Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis statement was used to prepare this study protocol. ETHICS AND DISSEMINATION:The study was classified by an accredited Medical Research Ethics Committee as not subject to the Dutch Medical Research Involving Human Subjects Act. Findings are expected in 2020 and will serve as input for the development of a new payment system for home care in the Netherlands, to be implemented at the discretion of the Dutch Ministry of Health, Welfare and Sports. The results will also be published in peer-reviewed publications and policy briefs, and presented at (inter)national conferences.

Project description:BackgroundHigh adiposity is associated with higher risks for a variety of adverse health outcomes, including higher rates of age-adjusted mortality and increased morbidity. This has important implications for the management of healthcare systems, since the endocrinal, cardiometabolic and other changes associated with increased adiposity may be associated with substantial healthcare costs.MethodsWe studied the association between various measures of adiposity and inpatient hospital costs through record linkage between UK Biobank and records of inpatient care in England and Wales. UK Biobank is a large prospective cohort study that aimed to recruit men and women aged between 40 and 69 from 2006 to 2010. We applied generalised linear models to cost per person year to estimate the marginal effect of adiposity, and average adjusted predicted costs of adiposity.ResultsValid cost and body mass index (BMI) data from 457,689 participants were available for inferential analysis. Some 54.4% of individuals included in the analysis sample had positive inpatient healthcare costs over the period of follow-up. Median hospital costs per person-year of follow-up were £89, compared to mean costs of £481. Mean BMI overall was 27.4 kg/m2 (standard deviation 4.8). The marginal effect of a unit increase in BMI was £13.61 (99% confidence interval £12.60-£14.63) per person-year of follow up. The marginal effect of a standard deviation increase in BMI was £69.20 (99% confidence interval £64.98-£73.42). The marginal effect of becoming obese was £136.35 (99% confidence interval £124.62-£148.08). Average adjusted predicted inpatient hospital costs increased almost linearly when modelled using continuous measure of adiposity. Sensitivity analysis of different scenarios did not substantially change these conclusions, although there was some evidence of attenuation of the effects of adiposity when controlling for waist-hip ratios, and when individuals who self-reported any pre-existing conditions were excluded from analysis.ConclusionsHigher adiposity is associated with higher inpatient hospital costs. Further scrutiny using causal inferential methods is warranted to establish if further public health investments are required to manage the large healthcare costs observationally associated with overweight and obesity.

Project description:BackgroundCaring for individuals and their families with a life-limiting, symptomatic illness and those who are dying has long been an integral role of palliative care nurses. Yet, over the last two decades, the specialty of palliative care has undergone significant changes in technology and medical treatments which have altered both the disease trajectory and the delivery of palliative care. To date, there is little evidence as to the impact of these medical and nursing advancements on the role of nurses working in palliative care and how in clinical practice these nurses continue to uphold their nursing values and the philosophy of palliative care.MethodsAn integrative review was conducted searching seven academic databases from the time period of January 2010 - December 2019 for studies identifying research relating to the role of the palliative care nurse working in specialist palliative care units and hospices. Research articles identified were screened against the inclusion criteria. Data extraction was completed on all included studies and the Crowe Critical Appraisal Tool was utilized to appraise the methodological quality and thematic analysis was performed guided by Braun and Clarke's framework. The review was conducted and reported in lines with PRISMA guidelines.ResultsThe search yielded 22,828 articles of which 7 were included for appraisal and review. Four themes were identified: (1) enhancing patient-centred care (2) being there (3) exposure to suffering and death (4) nursing values seen but not heard. The findings highlight that while palliative care nurses do not articulate their nurse values, their actions and behaviors evident within the literature demonstrate care, compassion, and commitment.ConclusionThese findings suggest that there is a need for nurses working in specialist palliative care units to articulate, document, and audit how they incorporate the values of nursing into their practice. This is pivotal not only for the future of palliative nursing within hospice and specialist palliative care units but also to the future of palliative care itself. To make visible the values of nursing further practice-based education and research is required.

Dataset Information

Development and validation of a casemix classification to predict costs of specialist palliative care provision across inpatient hospice, hospital and community settings in the UK: a study protocol.

Introduction

Methods and analysis

Ethics and dissemination

Trial registration number

Publications

Development and validation of a casemix classification to predict costs of specialist palliative care provision across inpatient hospice, hospital and community settings in the UK: a study protocol.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets