Title: Predicting hospitalisation in heart failure: incorporating dynamic patient-reported measures in a prognostic model to improve outcomes
Funder: Department of Health and Social Care

Abstract: Research question For people with heart failure (HF), what is the utility and feasibility of including dynamic patient-reported measures in a prognostic model for hospitalisation and which statistical approach should be used? BackgroundUK patients with HF experience up to 1-million hospitalisations per year, three quarters of which are for non-cardiovascular causes and up to half may be avoidable. Clinical deterioration prior to admission is poorly recognised by patients and clinicians and there are no HF community-based prognostic models for hospitalisation. In-hospital prognostic models use data and biometrics measured at a single time-point which have poor discrimination for readmissions. Patient-reported outcome measures (PROMs) provide a validated approach to measuring changing symptoms and health in routine care for inclusion into potentially better prognostic models for hospitalisation and for earlier detection of deterioration. Aims and objectivesThe overall aim is to investigate the utility and feasibility of including dynamic PROMs in a prognostic model for hospitalisation and to develop methods for early identification of changing risk in HF patients. The fellowship will address four linked objectives: (i) provide evidence on the consistency of symptoms, health and their change as prognostic indicators among different HF population groups (ii) consensus on which PROMs to use in prognosis (iii) feasibility of routine PROM collection and (iv) evaluation of methods to model PROMs in HF prognosis. Methods and timelines Supported by preparatory project planning, the 4-year fellowship has four linked work-packages (WP): WP1: Investigations using cohort registries in Sweden and Asia, comprising >50,000 HF patients from 12 countries with longitudinal PROM and outcomes data. Patient groups by gender, socioeconomic status and ethnicity will be explored in relation to health and outcomes using linear, survival and meta-analysis (year 1). WP2: Consensus studies with patients and clinicians (N=50) will use Delphi and Nominal Group Techniques to identify generic and HF-specific PROMs that are important prior to hospital admission and reportable and accessible by patients. These PROMs will be incorporated into an electronic platform (with external support already agreed) for ease of use and data collection (ePROHF) (years 1-2).WP3: A feasibility cohort study to test application of ePROHF in routine HF care. Consented patients (N=60) attending an outpatient HF clinic will be asked to complete ePROHF regularly over 6-months. Participation, retention, ePROHF completion, burden and data capture will be evaluated (years 2-3). WP4: Clinical Practice Research Datalink will be used to investigate dynamic change methodologies, aligned with a Masters in Statistics. Routine administration data will be used to define proxy measures of health change to model prediction of unplanned hospitalisations and test contemporary dynamic modelling approaches including Landmark analysis and Joint modelling (years 3-4).Anticipated impact and dissemination The fellowship will lead to innovative approaches to outcomes assessment in HF patients including consensus on PROMs collection in routine care. National and international networks of clinicians and academic researchers focusing on PROMs will deliver better tailored approaches to improving prognosis and outcomes in HF, including methodological and technological innovations. Dissemination will encompass HF patient, clinical, academic and social networks.

Lay abstract: Background: Heart failure (HF) is a serious condition that leads to people experiencing many symptoms, feeling poorly and spending a lot of their time in hospital. Patients with HF are often older and have other conditions that can also cause them to be hospitalised. In the weeks leading up to hospitalisation patients will usually start to feel worse, but they are often confused as to what might be causing their increasing symptoms. They may try to ignore their symptoms and not ask for help from their nurse or doctor early enough. It is thought that over half of hospitalisations could be avoided if we could identify these patients earlier. There are assessment tools to help identify HF patients who might need to be hospitalised but these tools are for patients' already in hospital and not for the majority of patients living at home. Also, most of these assessment tools only include medical information and they are not very accurate. They do not include patients' symptoms or keep regular checks on patients to see if they are getting worse.The overall aim of my fellowship is to develop a better assessment tool for identifying patients with HF who are getting worse before their symptoms become so serious that they need to be hospitalised. Important linked questions to develop a better assessment tool are: Is change in symptoms and health leading up to hospitalisation the same for all patients? We do not routinely record symptoms or health in the UK but I have permission to use two large sets of records about patients with HF in Sweden and Asia to answer this question. These records include multiple assessments of symptoms and health, as well as hospital admissions and death for over 50,000 patients. Which questions should we ask patients regularly?Guided by the results from question 1, I will invite 25 patients with HF from different areas and ethnic groups and 25 of their doctors and nurses to look at questions about symptoms and health that relate to HF and other conditions. I will use emails and a patient meeting to get agreement on the best questions for patients to complete, which identify those who are getting worse. Will patients want and be able to record their symptoms regularly?Guided by the results of question 2, I will ask 60 patients to make a note of their symptoms weekly, using a simple and quick electronic device. I will study how many patients are willing and able to do this and I will ask them and their health professionals about their experiences, using a questionnaire posted to patients' homes and to doctors' surgeries. How should we include symptoms and health into our new assessment tool? I will use a large database of patients with HF in the UK to study different methods for including regular health measures into a new assessment tool to identify which patients are getting worse. As the symptoms and health from questions 2 and 3 are not yet routinely recorded I will use other 'pretend' health measures such as how many times the patient sees their doctor. Patient and public involvement Three groups of patients with HF from different backgrounds helped to shape the questions for this fellowship. The patients talked about their difficulty in understanding their symptoms and knowing when to seek help and suggested the use of an electronic device to record symptoms. Dissemination I will disseminate my findings to patient and clinical groups, policy makers and healthcare services. Journal publications and conference presentations will be communicated more widely by using media, social media and HF websites.

Research activity codes: 4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: CARDIOVASCULAR