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Perera R, Stevens R, Aronson JK, Banerjee A, Evans J, Feakins BG, Fleming S, Glasziou P, Heneghan C, Hobbs FDR, Jones L, Kurtinecz M, Lasserson DS, Locock L, McLellan J, Mihaylova B, O’Callaghan CA, Oke JL, Pidduck N, Plüddemann A, Roberts N, Schlackow I, Shine B, Simons CL, Taylor CJ, Taylor KS, Verbakel JY, Bankhead C. Long-term monitoring in primary care for chronic kidney disease and chronic heart failure: a multi-method research programme. PROGRAMME GRANTS FOR APPLIED RESEARCH 2021. [DOI: 10.3310/pgfar09100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Background
Long-term monitoring is important in chronic condition management. Despite considerable costs of monitoring, there is no or poor evidence on how, what and when to monitor. The aim of this study was to improve understanding, methods, evidence base and practice of clinical monitoring in primary care, focusing on two areas: chronic kidney disease and chronic heart failure.
Objectives
The research questions were as follows: does the choice of test affect better care while being affordable to the NHS? Can the number of tests used to manage individuals with early-stage kidney disease, and hence the costs, be reduced? Is it possible to monitor heart failure using a simple blood test? Can this be done using a rapid test in a general practitioner consultation? Would changes in the management of these conditions be acceptable to patients and carers?
Design
Various study designs were employed, including cohort, feasibility study, Clinical Practice Research Datalink analysis, seven systematic reviews, two qualitative studies, one cost-effectiveness analysis and one cost recommendation.
Setting
This study was set in UK primary care.
Data sources
Data were collected from study participants and sourced from UK general practice and hospital electronic health records, and worldwide literature.
Participants
The participants were NHS patients (Clinical Practice Research Datalink: 4.5 million patients), chronic kidney disease and chronic heart failure patients managed in primary care (including 750 participants in the cohort study) and primary care health professionals.
Interventions
The interventions were monitoring with blood and urine tests (for chronic kidney disease) and monitoring with blood tests and weight measurement (for chronic heart failure).
Main outcome measures
The main outcomes were the frequency, accuracy, utility, acceptability, costs and cost-effectiveness of monitoring.
Results
Chronic kidney disease: serum creatinine testing has increased steadily since 1997, with most results being normal (83% in 2013). Increases in tests of creatinine and proteinuria correspond to their introduction as indicators in the Quality and Outcomes Framework. The Chronic Kidney Disease Epidemiology Collaboration equation had 2.7% greater accuracy (95% confidence interval 1.6% to 3.8%) than the Modification of Diet in Renal Disease equation for estimating glomerular filtration rate. Estimated annual transition rates to the next chronic kidney disease stage are ≈ 2% for people with normal urine albumin, 3–5% for people with microalbuminuria (3–30 mg/mmol) and 3–12% for people with macroalbuminuria (> 30 mg/mmol). Variability in estimated glomerular filtration rate-creatinine leads to misclassification of chronic kidney disease stage in 12–15% of tests in primary care. Glycaemic-control and lipid-modifying drugs are associated with a 6% (95% confidence interval 2% to 10%) and 4% (95% confidence interval 0% to 8%) improvement in renal function, respectively. Neither estimated glomerular filtration rate-creatinine nor estimated glomerular filtration rate-Cystatin C have utility in predicting rate of kidney function change. Patients viewed phrases such as ‘kidney damage’ or ‘kidney failure’ as frightening, and the term ‘chronic’ was misinterpreted as serious. Diagnosis of asymptomatic conditions (chronic kidney disease) was difficult to understand, and primary care professionals often did not use ‘chronic kidney disease’ when managing patients at early stages. General practitioners relied on Clinical Commissioning Group or Quality and Outcomes Framework alerts rather than National Institute for Health and Care Excellence guidance for information. Cost-effectiveness modelling did not demonstrate a tangible benefit of monitoring kidney function to guide preventative treatments, except for individuals with an estimated glomerular filtration rate of 60–90 ml/minute/1.73 m2, aged < 70 years and without cardiovascular disease, where monitoring every 3–4 years to guide cardiovascular prevention may be cost-effective. Chronic heart failure: natriuretic peptide-guided treatment could reduce all-cause mortality by 13% and heart failure admission by 20%. Implementing natriuretic peptide-guided treatment is likely to require predefined protocols, stringent natriuretic peptide targets, relative targets and being located in a specialist heart failure setting. Remote monitoring can reduce all-cause mortality and heart failure hospitalisation, and could improve quality of life. Diagnostic accuracy of point-of-care N-terminal prohormone of B-type natriuretic peptide (sensitivity, 0.99; specificity, 0.60) was better than point-of-care B-type natriuretic peptide (sensitivity, 0.95; specificity, 0.57). Within-person variation estimates for B-type natriuretic peptide and weight were as follows: coefficient of variation, 46% and coefficient of variation, 1.2%, respectively. Point-of-care N-terminal prohormone of B-type natriuretic peptide within-person variability over 12 months was 881 pg/ml (95% confidence interval 380 to 1382 pg/ml), whereas between-person variability was 1972 pg/ml (95% confidence interval 1525 to 2791 pg/ml). For individuals, monitoring provided reassurance; future changes, such as increased testing, would be acceptable. Point-of-care testing in general practice surgeries was perceived positively, reducing waiting time and anxiety. Community heart failure nurses had greater knowledge of National Institute for Health and Care Excellence guidance than general practitioners and practice nurses. Health-care professionals believed that the cost of natriuretic peptide tests in routine monitoring would outweigh potential benefits. The review of cost-effectiveness studies suggests that natriuretic peptide-guided treatment is cost-effective in specialist settings, but with no evidence for its value in primary care settings.
Limitations
No randomised controlled trial evidence was generated. The pathways to the benefit of monitoring chronic kidney disease were unclear.
Conclusions
It is difficult to ascribe quantifiable benefits to monitoring chronic kidney disease, because monitoring is unlikely to change treatment, especially in chronic kidney disease stages G3 and G4. New approaches to monitoring chronic heart failure, such as point-of-care natriuretic peptide tests in general practice, show promise if high within-test variability can be overcome.
Future work
The following future work is recommended: improve general practitioner–patient communication of early-stage renal function decline, and identify strategies to reduce the variability of natriuretic peptide.
Study registration
This study is registered as PROSPERO CRD42015017501, CRD42019134922 and CRD42016046902.
Funding
This project was funded by the National Institute for Health Research (NIHR) Programme Grants for Applied Research programme and will be published in full in Programme Grants for Applied Research; Vol. 9, No. 10. See the NIHR Journals Library website for further project information.
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Affiliation(s)
- Rafael Perera
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Richard Stevens
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Jeffrey K Aronson
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Amitava Banerjee
- Institute of Health Informatics, University College London, London, UK
| | - Julie Evans
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Benjamin G Feakins
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Susannah Fleming
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Paul Glasziou
- Institute for Evidence-Based Healthcare, Faculty of Health Sciences & Medicine, Bond University, Gold Coast, QLD, Australia
| | - Carl Heneghan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - FD Richard Hobbs
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Louise Jones
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Milena Kurtinecz
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Daniel S Lasserson
- Institute of Applied Health Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Louise Locock
- Health Services Research Unit, University of Aberdeen, Aberdeen, UK
| | - Julie McLellan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Borislava Mihaylova
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Institute of Population Health Sciences, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | | | - Jason L Oke
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Nicola Pidduck
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Annette Plüddemann
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Nia Roberts
- Bodleian Health Care Libraries, Knowledge Centre, University of Oxford, Oxford, UK
| | - Iryna Schlackow
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Brian Shine
- Department of Clinical Biochemistry, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Claire L Simons
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Clare J Taylor
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Kathryn S Taylor
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Jan Y Verbakel
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
- Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium
- National Institute for Health Research (NIHR) Community Healthcare MedTech and In Vitro Diagnostics Co-operative (MIC), Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
| | - Clare Bankhead
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
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Di Tanna GL, Urbich M, Wirtz HS, Potrata B, Heisen M, Bennison C, Brazier J, Globe G. Health State Utilities of Patients with Heart Failure: A Systematic Literature Review. PHARMACOECONOMICS 2021; 39:211-229. [PMID: 33251572 PMCID: PMC7867520 DOI: 10.1007/s40273-020-00984-6] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/10/2020] [Indexed: 05/07/2023]
Abstract
BACKGROUND AND OBJECTIVES New treatments and interventions are in development to address clinical needs in heart failure. To support decision making on reimbursement, cost-effectiveness analyses are frequently required. A systematic literature review was conducted to identify and summarize heart failure utility values for use in economic evaluations. METHODS Databases were searched for articles published until June 2019 that reported health utility values for patients with heart failure. Publications were reviewed with specific attention to study design; reported values were categorized according to the health states, 'chronic heart failure', 'hospitalized', and 'other acute heart failure'. Interquartile limits (25th percentile 'Q1', 75th percentile 'Q3') were calculated for health states and heart failure subgroups where there were sufficient data. RESULTS The systematic literature review identified 161 publications based on data from 142 studies. Utility values for chronic heart failure were reported by 128 publications; 39 publications published values for hospitalized and three for other acute heart failure. There was substantial heterogeneity in the specifics of the study populations, methods of elicitation, and summary statistics, which is reflected in the wide range of utility values reported. EQ-5D was the most used instrument; the interquartile limit for mean EQ-5D values for chronic heart failure was 0.64-0.72. CONCLUSIONS There is a wealth of published utility values for heart failure to support economic evaluations. Data are heterogenous owing to specificities of the study population and methodology of utility value elicitation and analysis. Choice of value(s) to support economic models must be carefully justified to ensure a robust economic analysis.
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Affiliation(s)
- Gian Luca Di Tanna
- Statistics Division, The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
- The George Institute for Global Health, Level 5, 1 King St, Newtown, NSW, 2042, Australia.
| | - Michael Urbich
- Amgen (Europe) GmbH, Global Value & Access, Modeling Center of Excellence, Rotkreuz, Switzerland
| | - Heidi S Wirtz
- Amgen Inc, Global Health Economics, Thousand Oaks, CA, USA
| | - Barbara Potrata
- Pharmerit - an OPEN Health company, Rotterdam, The Netherlands
| | - Marieke Heisen
- Pharmerit - an OPEN Health company, Rotterdam, The Netherlands
| | | | - John Brazier
- Health Economics and Decision Science, University of Sheffield, Sheffield, UK
| | - Gary Globe
- Amgen Inc, Global Health Economics, Thousand Oaks, CA, USA
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Takeda A, Martin N, Taylor RS, Taylor SJC, Cochrane Heart Group. Disease management interventions for heart failure. Cochrane Database Syst Rev 2019; 1:CD002752. [PMID: 30620776 PMCID: PMC6492456 DOI: 10.1002/14651858.cd002752.pub4] [Citation(s) in RCA: 64] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND Despite advances in treatment, the increasing and ageing population makes heart failure an important cause of morbidity and death worldwide. It is associated with high healthcare costs, partly driven by frequent hospital readmissions. Disease management interventions may help to manage people with heart failure in a more proactive, preventative way than drug therapy alone. This is the second update of a review published in 2005 and updated in 2012. OBJECTIVES To compare the effects of different disease management interventions for heart failure (which are not purely educational in focus), with usual care, in terms of death, hospital readmissions, quality of life and cost-related outcomes. SEARCH METHODS We searched CENTRAL, MEDLINE, Embase and CINAHL for this review update on 9 January 2018 and two clinical trials registries on 4 July 2018. We applied no language restrictions. SELECTION CRITERIA We included randomised controlled trials (RCTs) with at least six months' follow-up, comparing disease management interventions to usual care for adults who had been admitted to hospital at least once with a diagnosis of heart failure. There were three main types of intervention: case management; clinic-based interventions; multidisciplinary interventions. DATA COLLECTION AND ANALYSIS We used standard methodological procedures expected by Cochrane. Outcomes of interest were mortality due to heart failure, mortality due to any cause, hospital readmission for heart failure, hospital readmission for any cause, adverse effects, quality of life, costs and cost-effectiveness. MAIN RESULTS We found 22 new RCTs, so now include 47 RCTs (10,869 participants). Twenty-eight were case management interventions, seven were clinic-based models, nine were multidisciplinary interventions, and three could not be categorised as any of these. The included studies were predominantly in an older population, with most studies reporting a mean age of between 67 and 80 years. Seven RCTs were in upper-middle-income countries, the rest were in high-income countries.Only two multidisciplinary-intervention RCTs reported mortality due to heart failure. Pooled analysis gave a risk ratio (RR) of 0.46 (95% confidence interval (CI) 0.23 to 0.95), but the very low-quality evidence means we are uncertain of the effect on mortality due to heart failure. Based on this limited evidence, the number needed to treat for an additional beneficial outcome (NNTB) is 12 (95% CI 9 to 126).Twenty-six case management RCTs reported all-cause mortality, with low-quality evidence indicating that these may reduce all-cause mortality (RR 0.78, 95% CI 0.68 to 0.90; NNTB 25, 95% CI 17 to 54). We pooled all seven clinic-based studies, with low-quality evidence suggesting they may make little to no difference to all-cause mortality. Pooled analysis of eight multidisciplinary studies gave moderate-quality evidence that these probably reduce all-cause mortality (RR 0.67, 95% CI 0.54 to 0.83; NNTB 17, 95% CI 12 to 32).We pooled data on heart failure readmissions from 12 case management studies. Moderate-quality evidence suggests that they probably reduce heart failure readmissions (RR 0.64, 95% CI 0.53 to 0.78; NNTB 8, 95% CI 6 to 13). We were able to pool only two clinic-based studies, and the moderate-quality evidence suggested that there is probably little or no difference in heart failure readmissions between clinic-based interventions and usual care (RR 1.01, 95% CI 0.87 to 1.18). Pooled analysis of five multidisciplinary interventions gave low-quality evidence that these may reduce the risk of heart failure readmissions (RR 0.68, 95% CI 0.50 to 0.92; NNTB 11, 95% CI 7 to 44).Meta-analysis of 14 RCTs gave moderate-quality evidence that case management probably slightly reduces all-cause readmissions (RR 0.92, 95% CI 0.83 to 1.01); a decrease from 491 to 451 in 1000 people (95% CI 407 to 495). Pooling four clinic-based RCTs gave low-quality and somewhat heterogeneous evidence that these may result in little or no difference in all-cause readmissions (RR 0.90, 95% CI 0.72 to 1.12). Low-quality evidence from five RCTs indicated that multidisciplinary interventions may slightly reduce all-cause readmissions (RR 0.85, 95% CI 0.71 to 1.01); a decrease from 450 to 383 in 1000 people (95% CI 320 to 455).Neither case management nor clinic-based intervention RCTs reported adverse effects. Two multidisciplinary interventions reported that no adverse events occurred. GRADE assessment of moderate quality suggested that there may be little or no difference in adverse effects between multidisciplinary interventions and usual care.Quality of life was generally poorly reported, with high attrition. Low-quality evidence means we are uncertain about the effect of case management and multidisciplinary interventions on quality of life. Four clinic-based studies reported quality of life but we could not pool them due to differences in reporting. Low-quality evidence indicates that clinic-based interventions may result in little or no difference in quality of life.Four case management programmes had cost-effectiveness analyses, and seven reported cost data. Low-quality evidence indicates that these may reduce costs and may be cost-effective. Two clinic-based studies reported cost savings. Low-quality evidence indicates that clinic-based interventions may reduce costs slightly. Low-quality data from one multidisciplinary intervention suggested this may be cost-effective from a societal perspective but less so from a health-services perspective. AUTHORS' CONCLUSIONS We found limited evidence for the effect of disease management programmes on mortality due to heart failure, with few studies reporting this outcome. Case management may reduce all-cause mortality, and multidisciplinary interventions probably also reduce all-cause mortality, but clinic-based interventions had little or no effect on all-cause mortality. Readmissions due to heart failure or any cause were probably reduced by case-management interventions. Clinic-based interventions probably make little or no difference to heart failure readmissions and may result in little or no difference in readmissions for any cause. Multidisciplinary interventions may reduce the risk of readmission for heart failure or for any cause. There was a lack of evidence for adverse effects, and conclusions on quality of life remain uncertain due to poor-quality data. Variations in study location and time of occurrence hamper attempts to review costs and cost-effectiveness.The potential to improve quality of life is an important consideration but remains poorly reported. Improved reporting in future trials would strengthen the evidence for this patient-relevant outcome.
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Affiliation(s)
- Andrea Takeda
- University College LondonInstitute of Health Informatics ResearchLondonUK
| | - Nicole Martin
- University College LondonInstitute of Health Informatics ResearchLondonUK
| | - Rod S Taylor
- University of Exeter Medical SchoolInstitute of Health ResearchSouth Cloisters, St Luke's Campus, Heavitree RoadExeterUKEX2 4SG
| | - Stephanie JC Taylor
- Barts and The London School of Medicine and Dentistry, Queen Mary University of LondonCentre for Primary Care and Public Health and Asthma UK Centre for Applied ResearchYvonne Carter Building58 Turner StreetLondonUKE1 2AB
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