Loading content

Professor Jose Valderas

Professor of Health Services and Policy Research

2755

Smeall building

Smeall Building, University of Exeter, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, UK

I am an Academic General Practitioner, with a commitment to research on patient centred care that is relevant for decision making in clinical practice and health policy. I lead the Health Services & Policy Research Group at the University of Exeter Medical School. I also lead on the patient-centred care theme of the Exeter Collaboration for Academic Primary Care (APEx).

My current research interests focus on the use of patient reports on their own health for decision making in clinical practice and health policy, and the improvement of processes of care (quality and safety), with a particular interest in patients with multiple conditions. I have been awarded a Clinician Scientist Award awarded by the National Institute of Health Research (NIHR), UK, for a research programme on the use of patient reported outcome measures (PROMs) in improving primary care for people with multi-morbidity. I have participated in over 30 research projects and have authored over 100 publications, including papers, books and book chapters, editorials, letters, and scientific communications, and I am an author of the open blog on Health Policy HP Snippets. I serve as an Associate Editor for the European Journal of General Practice.

Since completing my training as a General Practitioner I have maintained active clinical practice in different countries and in a variety of environments, including developing countries for very brief periods. I am also devoted to postgraduate teaching, particularly in areas where research meets clinical practice (Clinical Epidemiology and Evidence Based Practice).

Broad Research Specialisms

My main areas of expertise are in patient centred care, with a particular focus on the use of measures of Patient Reported Outcomes and Experiences (development, adaptation, application, interpretation and clinical applications of PROMs, qualitative methods for content generation, psychometrics and quantitative analyses (classical test theory and Item Response Theory Models), and appraisal of instruments), multi- and co-morbidity, and quality and safety in Primary Care.

Qualifications

• BMBS (University of Barcelona, Spain)
• General Practitioner (Department of Education, Spain)
• MPH (Pompeu Fabra University, Spain)
• PhD (Pompeu Fabra University, Spain)

Career

After combining my PhD (IMIM-Hospital del Mar and Pompeu Fabra University) and my training as a General Practitioner in Barcelona, Spain, I started my post-doctoral research at the Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health under the supervision of the late Prof. Barbara Starfield. I then joined the National Primary Care Research and Development Centre, University of Manchester led by Prof. Martin Roland, and in 2010 arrived at the Nuffield Department of Primary Care Health Sciences at the University of Oxford to set up and lead the Health Services and Policy Research Group. In September 2013, I was appointed Chair in Health Services and Policy Research at the University of Exeter Medical School.

For a list of publications with citations, please see here

Research

Research interests

Jose's main interest is in the further development of models of care that ensure that care is truly centred around the patients. To that aim his current interests are in Patient Reported Outcomes and Experiences Measurement (with a particular focus on the combined use of individualised and standardized measures), models of care for chronic conditions (with a focus on multi- and co-morbidity), and quality and safety in Primary Care.

Research projects

Improving the management of long term conditions with the clinical use of patient reported outcome measures in Primary Care
National Institute for Health Research, £996,226.00; 1 March 2011-28 February 2016
Role: Principal Investigator (PI)

Functionality and feedback: A realist synthesis of the collation, intepretation and utilisation of PROMs data to improve patient care
NIHR Service Delivery and Organization Programme, £202,881.6, Sart Date 1/1/2014-1/7/2015.
Role: Co-Applicant (PI: Prof. J Greenhalgh, University of Leeds, UK)

Information and value-based commissioning
NIHR Service Delivery and Organization Programme, £518,247, Support period: 2012-2014
Role: Co-applicant (PI: Dr. Barry MacCormick, University of Oxford, UK)

Introducing standardised and evidence based thresholds for hip and knee replacement surgery - the arthroplasty candidacy help engine (the ACHE tool).
National Institute for Health Research, Health Technology Assessment Programme, UK. £799,189 Support period: 1 September 2013-31 August 2016
Role: Co-applicant (PI: Prof. Andrew Price, University of Oxford, UK)

Systems of care and outcomes in TIA and minor stroke in the Hunter Valley, New South Wales
National Health and Medical Research Council, Australia APP1027794; AU$ 1,173,380 (ap. £750K)
Period: 1 January 2012-31 December 2015
Role: Co-applicant (PI: Christopher Levi, University of Newcastle, Australia)

Primary Care Prevention and Health Promotion Research Network
Carlos III Research Institute, Spain: €3,022,478.53
Role: Co-Investigator (PI: Bolivar B, IDIAP Primary Care Research Institute)

Quality and Outcomes of Care for Chronic Conditions in Older Patients Diagnosed with Breast, Colorectal, or Prostate Cancer Compared to Non-Cancer Controls: An Observational Study Using the Clinical Practice Research Datalink (CPRD).
Funder: Cancer Research UK (£296,000.0)
Support period: 1 July 2013-31 December 2015
Role: PI

Prioritising and optimising multiple medications in elderly multi-morbid patients in general practice (PRIMUM). - A pragmatic cluster-randomised controlled trial.
BundesMinisterium fuer Bildung und Forschung, €500,860.00
Period: 1 March 2010-28 February 2012
Role: Scientific Advisory Board (PI: Dr C Muth, Johann Wolfgang Goethe University, Frankfurt am Main, Germany)
Web: http://clinicaltrials.gov/ct2/show/NCT01171339

Developing, testing and implementing the NSPCR Patient Safety Toolkit in general practices in England.
NIHR School for Primary Care Research, England; £569,740.0; 1 October 2011-31 Dec. 2013
Role: Co-applicant (PI: Prof. Tony Avery, University of Nottingham, UK)

Patients’ perspectives and understanding of high-performing, safety conscious general practice: an exploratory study
Support period: 2012-2013, £139,959
NIHR School for Primary Care Research
Role: Co-applicant (PI: Dr. Stephen Campbell, University of Manchester, UK)

An investigation of the Quality and Outcomes Framework (QOF) using the General Practice Research Database (GPRD)
Support period: 2012-2014, £55,523.0
NIHR School for Primary Care Research
Role: Co-applicant (PI: Dr. Evan Kontopantelis, University of Manchester, UK)

Grants/Funding

Patterns of co-morbidity and poly-pharmacy in Primary Care in Catalonia, Spain
Instituto de Salud Carlos III, Spain (PI12/00427): €48,400.00
Period: 1 October 2011-31 December 2012.
Role: Co-Applicant (PI: Dr. Quinti Foguet, IDIAP Jordi Gol, Barcelona, Spain

BiblioPRO: virtual library of patient reported outcomes
RecerCaixa, €99,732.25; 1 January 2011-31 December 2012
Role: Co-Applicant (PI: Prof. J Alonso, Universitat Pompeu Fabra, Spain)
Web: http://bibliopro.imim.es

Safety netting to improve early cancer diagnosis in primary care: development of consensus guidelines.
Department of Health, £19,990.00
Period: 1 January 2011-1 June 2011
Role: Co-Applicant (PI: Dr. C Bankhead, University of Oxford, UK)

Attribution of Patient Reported Outcomes to the effects of care providers
Medical Research Council, £337,675.00; 1 April 2010-31 March 2013
Role: Co-Applicant (PI: Prof. M Sutton, University of Manchester, UK)

Patient and professional experience of managing co-morbid long-term conditions in primary care
NIHR School of Primary Care Research, £200,206.00.
Support period: 2010-2013
Role: Co-applicant (PI: Prof C Salisbury, University of Bristol, UK)
Web: http://www.nspcr.ac.uk/rP3.43

Health status evaluation of the general Spanish population using the International Classification of Functioning, Disability and Health (ICF)
Fondo de Investigación Sanitaria, Spain (PI 061579 and PI 051542)
Role: Co-Applicant (PI: Dr. Montse Ferrer, IMIM-Hospital del Mar, Spain)
Web: http://www.imim.es/programesrecerca/epidemiologia/en_cifrecerca.html

Trajectories of perceived health and use of health care services in a Spanish population sample of children and adolescents 8 to 18 years old.
Instituto de Salud Carlos III, Spain (Red IRYSS G03/202) and Fondo de Investigación Sanitaria (PI042504 y PI042315)
Role: Co- Applicant (Co-PI: Prof. Jordi J Alonso, Universitat Pompeu Fabra, Spain; Dr. Luis Rajmil, Agència d’Avaluació de Tecnologia Mèdica, Spain)

Development, application, and validation of a new tool for the standardized evaluation of patient reported outcome measures (EMPRO)
Instituto de Salud Carlos III, Spain (Red de Investigación Cooperativa IRYSS, G03/202 and CM 300118), PI06/90483 and ETE06/450104884), CIBERESP – MET010)
Role: Co-Applicant (PI: Dr. Montse Ferrer, IMIM-Hospital del Mar, Spain)

RED IRYSS (Health and Health Services Outcomes Research Network)
Instituto de Salud Carlos III, Spain (G03/202)
Support period: 2002-2006
Role: Co-Applicant (PI: Dr JMV Pons, Agència d’Avaluació de Tecnologia Mèdica, Spain)

Developing priority criteria for patients on waiting lists for cataract surgery and hip and knee arthroplasty in Catalonia, Spain
Fondo de Investigación Sanitaria, Spain (01/0921)
Period: 1999-2002
Role: Co-Applicant (PI: Dr. M Espallargues, Agència d’Avaluació de Tecnologia Mèdica, Spain).

Key publications | Publications by category | Publications by year

Publications by category

Journal articles

Close J, Valderas JM, Byng R, Britten N, Lloyd H (In Press). Adapting QOF to focus on wellbeing and health. BMJ, 359 Author URL.

Kontopantelis E, Springate DA, Ashcroft DM, Valderas JM, van der Veer SN, Reeves D, Guthrie B, Doran T (In Press). Associations between exemption and survival outcomes in the UK's primary care pay-for-performance programme: a retrospective cohort study. BMJ Qual Saf, 25(9), 657-670.

OBJECTIVES: the UK's Quality and Outcomes Framework permits practices to exempt patients from financially-incentivised performance targets. To better understand the determinants and consequences of being exempted from the framework, we investigated the associations between exception reporting, patient characteristics and mortality. We also quantified the proportion of exempted patients that met quality targets for a tracer condition (diabetes). DESIGN: Retrospective longitudinal study, using individual patient data from the Clinical Practice Research Datalink. SETTING: 644 general practices, 2006/7 to 2011/12. PARTICIPANTS: Patients registered with study practices for at least one year over the study period, with at least one condition of interest (2 460 341 in total). MAIN OUTCOME MEASURES: Exception reporting rates by reason (clinical contraindication, patient dissent); all-cause mortality in year following exemption. Analyses with logistic and Cox proportional-hazards regressions, respectively. RESULTS: the odds of being exempted increased with age, deprivation and multimorbidity. Men were more likely to be exempted but this was largely attributable to higher prevalence of conditions with high exemption rates. Modest associations remained, with women more likely to be exempted due to clinical contraindication (OR 0.90, 99% CI 0.88 to 0.92) and men more likely to be exempted due to informed dissent (OR 1.08, 99% CI 1.06 to 1.10). More deprived areas (both for practice location and patient residence) were non-linearly associated with higher exception rates, after controlling for comorbidities and other covariates, with stronger associations for clinical contraindication. Compared with patients with a single condition, odds ratios for patients with two, three, or four or more conditions were respectively 4.28 (99% CI 4.18 to 4.38), 16.32 (99% CI 15.82 to 16.83) and 68.69 (99% CI 66.12 to 71.37) for contraindication, and 2.68 (99% CI 2.63 to 2.74), 4.02 (99% CI 3.91 to 4.13) and 5.17 (99% CI 5.00 to 5.35) for informed dissent. Exempted patients had a higher adjusted risk of death in the following year than non-exempted patients, regardless of whether this exemption was for contraindication (hazard ratio 1.37, 99% CI 1.33 to 1.40) or for informed dissent (1.20, 99% CI 1.17 to 1.24). On average, quality standards were met for 48% of exempted patients in the diabetes domain, but there was wide variation across indicators (ranging from 8 to 80%). CONCLUSIONS: Older, multimorbid and more deprived patients are more likely to be exempted from the scheme. Exception reported patients are more likely to die in the following year, whether they are exempted by the practice for a contraindication or by themselves through informed dissent. Further research is needed to understand the relationship between exception reporting and patient outcomes.

Abstract. Author URL. Full text.

Catalá-López F, Hutton B, Driver JA, Page MJ, Ridao M, Valderas JM, Alonso-Arroyo A, Forés-Martos J, Martínez S, Gènova-Maleras R, et al (In Press). Cancer and central nervous system disorders: protocol for an umbrella review of systematic reviews and updated meta-analyses of observational studies. Syst Rev, 6(1).

BACKGROUND: the objective of this study will be to synthesize the epidemiological evidence and evaluate the validity of the associations between central nervous system disorders and the risk of developing or dying from cancer. METHODS/DESIGN: We will perform an umbrella review of systematic reviews and conduct updated meta-analyses of observational studies (cohort and case-control) investigating the association between central nervous system disorders and the risk of developing or dying from any cancer or specific types of cancer. Searches involving PubMed/MEDLINE, EMBASE, SCOPUS and Web of Science will be used to identify systematic reviews and meta-analyses of observational studies. In addition, online databases will be checked for observational studies published outside the time frames of previous reviews. Eligible central nervous system disorders will be Alzheimer's disease, anorexia nervosa, amyotrophic lateral sclerosis, autism spectrum disorders, bipolar disorder, depression, Down's syndrome, epilepsy, Huntington's disease, multiple sclerosis, Parkinson's disease and schizophrenia. The primary outcomes will be cancer incidence and cancer mortality in association with a central nervous system disorder. Secondary outcome measures will be site-specific cancer incidence and mortality, respectively. Two reviewers will independently screen references identified by the literature search, as well as potentially relevant full-text articles. Data will be abstracted, and study quality/risk of bias will be appraised by two reviewers independently. Conflicts at all levels of screening and abstraction will be resolved through discussion. Random-effects meta-analyses of primary observational studies will be conducted where appropriate. Parameters for exploring statistical heterogeneity are pre-specified. The World Cancer Research Fund (WCRF)/American Institute for Cancer Research (AICR) criteria and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach will be used for determining the quality of evidence for cancer outcomes. DISCUSSION: Our study will establish the extent of the epidemiological evidence underlying the associations between central nervous system disorders and cancer and will provide a rigorous and updated synthesis of a range of important site-specific cancer outcomes. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42016052762.

Abstract. Author URL. Full text.

Roso-Llorach A, Violán C, Foguet-Boreu Q, Rodriguez-Blanco T, Pons-Vigués M, Pujol-Ribera E, Valderas JM (In Press). Comparative analysis of methods for identifying multimorbidity patterns: a study of 'real-world' data. BMJ Open, 8(3).

OBJECTIVE: the aim was to compare multimorbidity patterns identified with the two most commonly used methods: hierarchical cluster analysis (HCA) and exploratory factor analysis (EFA) in a large primary care database. Specific objectives were: (1) to determine whether choice of method affects the composition of these patterns and (2) to consider the potential application of each method in the clinical setting. DESIGN: Cross-sectional study. Diagnoses were based on the 263 corresponding blocks of the International Classification of Diseases version 10. Multimorbidity patterns were identified using HCA and EFA. Analysis was stratified by sex, and results compared for each method. SETTING AND PARTICIPANTS: Electronic health records for 408 994 patients with multimorbidity aged 45-64 years in 274 primary health care teams from 2010 in Catalonia, Spain. RESULTS: HCA identified 53 clusters for women, with just 12 clusters including at least 2 diagnoses, and 15 clusters for men, all of them including at least two diagnoses. EFA showed 9 factors for women and 10 factors for men. We observed differences by sex and method of analysis, although some patterns were consistent. Three combinations of diseases were observed consistently across sex groups and across both methods: hypertension and obesity, spondylopathies and deforming dorsopathies, and dermatitis eczema and mycosis. CONCLUSIONS: This study showed that multimorbidity patterns vary depending on the method of analysis used (HCA vs EFA) and provided new evidence about the known limitations of attempts to compare multimorbidity patterns in real-world data studies. We found that EFA was useful in describing comorbidity relationships and HCA could be useful for in-depth study of multimorbidity. Our results suggest possible applications for each of these methods in clinical and research settings, and add information about some aspects that must be considered in standardisation of future studies: spectrum of diseases, data usage and methods of analysis.

Abstract. Author URL.

Muth C, Uhlmann L, Haefeli WE, Rochon J, van den Akker M, Perera R, Güthlin C, Beyer M, Oswald F, Valderas JM, et al (In Press). Effectiveness of a complex intervention on Prioritising Multimedication in Multimorbidity (PRIMUM) in primary care: results of a pragmatic cluster randomised controlled trial. BMJ Open, 8(2).

OBJECTIVES: Investigate the effectiveness of a complex intervention aimed at improving the appropriateness of medication in older patients with multimorbidity in general practice. DESIGN: Pragmatic, cluster randomised controlled trial with general practice as unit of randomisation. SETTING: 72 general practices in Hesse, Germany. PARTICIPANTS: 505 randomly sampled, cognitively intact patients (≥60 years, ≥3 chronic conditions under pharmacological treatment, ≥5 long-term drug prescriptions with systemic effects); 465 patients and 71 practices completed the study. INTERVENTIONS: Intervention group (IG): the healthcare assistant conducted a checklist-based interview with patients on medication-related problems and reconciled their medications. Assisted by a computerised decision support system, the general practitioner optimised medication, discussed it with patients and adjusted it accordingly. The control group (CG) continued with usual care. OUTCOME MEASURES: the primary outcome was a modified Medication Appropriateness Index (MAI, excluding item 10 on cost-effectiveness), assessed in blinded medication reviews and calculated as the difference between baseline and after 6 months; secondary outcomes after 6 and 9 months' follow-up: quality of life, functioning, medication adherence, and so on. RESULTS: at baseline, a high proportion of patients had appropriate to mildly inappropriate prescriptions (MAI 0-5 points: n=350 patients). Randomisation revealed balanced groups (IG: 36 practices/252 patients; CG: 36/253). Intervention had no significant effect on primary outcome: mean MAI sum scores decreased by 0.3 points in IG and 0.8 points in CG, resulting in a non-significant adjusted mean difference of 0.7 (95% CI -0.2 to 1.6) points in favour of CG. Secondary outcomes showed non-significant changes (quality of life slightly improved in IG but continued to decline in CG) or remained stable (functioning, medication adherence). CONCLUSIONS: the intervention had no significant effects. Many patients already received appropriate prescriptions and enjoyed good quality of life and functional status. We can therefore conclude that in our study, there was not enough scope for improvement. TRIAL REGISTRATION NUMBER: ISRCTN99526053. NCT01171339; Results.

Abstract. Author URL.

Prados-Torres A, Del Cura-González I, Prados-Torres D, López-Rodríguez JA, Leiva-Fernández F, Calderón-Larrañaga A, López-Verde F, Gimeno-Feliu LA, Escortell-Mayor E, Pico-Soler V, et al (In Press). Effectiveness of an intervention for improving drug prescription in primary care patients with multimorbidity and polypharmacy: study protocol of a cluster randomized clinical trial (Multi-PAP project). Implement Sci, 12(1).

BACKGROUND: Multimorbidity is associated with negative effects both on people's health and on healthcare systems. A key problem linked to multimorbidity is polypharmacy, which in turn is associated with increased risk of partly preventable adverse effects, including mortality. The Ariadne principles describe a model of care based on a thorough assessment of diseases, treatments (and potential interactions), clinical status, context and preferences of patients with multimorbidity, with the aim of prioritizing and sharing realistic treatment goals that guide an individualized management. The aim of this study is to evaluate the effectiveness of a complex intervention that implements the Ariadne principles in a population of young-old patients with multimorbidity and polypharmacy. The intervention seeks to improve the appropriateness of prescribing in primary care (PC), as measured by the medication appropriateness index (MAI) score at 6 and 12 months, as compared with usual care. METHODS/DESIGN: Design: pragmatic cluster randomized clinical trial. Unit of randomization: family physician (FP). Unit of analysis: patient. SCOPE: PC health centres in three autonomous communities: Aragon, Madrid, and Andalusia (Spain). POPULATION: patients aged 65-74 years with multimorbidity (≥3 chronic diseases) and polypharmacy (≥5 drugs prescribed in ≥3 months). SAMPLE SIZE: n = 400 (200 per study arm). INTERVENTION: complex intervention based on the implementation of the Ariadne principles with two components: (1) FP training and (2) FP-patient interview. OUTCOMES: MAI score, health services use, quality of life (Euroqol 5D-5L), pharmacotherapy and adherence to treatment (Morisky-Green, Haynes-Sackett), and clinical and socio-demographic variables. STATISTICAL ANALYSIS: primary outcome is the difference in MAI score between T0 and T1 and corresponding 95% confidence interval. Adjustment for confounding factors will be performed by multilevel analysis. All analyses will be carried out in accordance with the intention-to-treat principle. DISCUSSION: it is essential to provide evidence concerning interventions on PC patients with polypharmacy and multimorbidity, conducted in the context of routine clinical practice, and involving young-old patients with significant potential for preventing negative health outcomes. TRIAL REGISTRATION: Clinicaltrials.gov, NCT02866799.

Abstract. Author URL.

Ricci-Cabello I, Avery AJ, Reeves D, Kadam UT, Valderas JM (In Press). Measuring Patient Safety in Primary Care: the Development and Validation of the "Patient Reported Experiences and Outcomes of Safety in Primary Care" (PREOS-PC). Ann Fam Med, 14(3), 253-261. Abstract. Author URL.

Ricci-Cabello I, Pons-Vigués M, Berenguera A, Pujol-Ribera E, Slight SP, Valderas JM (In Press). Patients' perceptions and experiences of patient safety in primary care in England. Fam Pract, 33(5), 535-542. Abstract. Author URL.

Muth C, Harder S, Uhlmann L, Rochon J, Fullerton B, Güthlin C, Erler A, Beyer M, van den Akker M, Perera R, et al (In Press). Pilot study to test the feasibility of a trial design and complex intervention on PRIoritising MUltimedication in Multimorbidity in general practices (PRIMUMpilot). BMJ Open, 6(7).

OBJECTIVE: to improve medication appropriateness and adherence in elderly patients with multimorbidity, we developed a complex intervention involving general practitioners (GPs) and their healthcare assistants (HCA). In accordance with the Medical Research Council guidance on developing and evaluating complex interventions, we prepared for the main study by testing the feasibility of the intervention and study design in a cluster randomised pilot study. SETTING: 20 general practices in Hesse, Germany. PARTICIPANTS: 100 cognitively intact patients ≥65�
years with ≥3 chronic conditions, ≥5 chronic prescriptions and capable of participating in telephone interviews; 94 patients completed the study. INTERVENTION: the HCA conducted a checklist-based interview with patients on medication-related problems and reconciled their medications. Assisted by a computerised decision-support system (CDSS), the GPs discussed medication intake with patients and adjusted their medication regimens. The control group continued with usual care. OUTCOME MEASURES: Feasibility of the intervention and required time were assessed for GPs, HCAs and patients using mixed methods (questionnaires, interviews and case vignettes after completion of the study). The feasibility of the study was assessed concerning success of achieving recruitment targets, balancing cluster sizes and minimising drop-out rates. Exploratory outcomes included the medication appropriateness index (MAI), quality of life, functional status and adherence-related measures. MAI was evaluated blinded to group assignment, and intra-rater/inter-rater reliability was assessed for a subsample of prescriptions. RESULTS: 10 practices were randomised and analysed per group. GPs/HCAs were satisfied with the interventions despite the time required (35/45�
min/patient). In case vignettes, GPs/HCAs needed help using the CDSS. The study made no patients feel uneasy. Intra-rater/inter-rater reliability for MAI was excellent. Inclusion criteria were challenging and potentially inadequate, and should therefore be adjusted. Outcome measures on pain, functionality and self-reported adherence were unfeasible due to frequent missing values, an incorrect manual or potentially invalid results. CONCLUSIONS: Intervention and trial design were feasible. The pilot study revealed important limitations that influenced the design and conduct of the main study, thus highlighting the value of piloting complex interventions. TRIAL REGISTRATION NUMBER: ISRCTN99691973; Results.

Abstract. Author URL. Full text.

Evans JP, Smith C, Gangannagaripalli J, Goodwin V, Valderas JM (2018). Clinical Rating Systems in Elbow Research -. A Systematic Review Exploring Trends and Distributions of Use. Journal of Shoulder and Elbow Surgery Full text.

Greenhalgh J, Dalkin S, Gibbons E, Wright J, Valderas JM, Meads D, Black N (2018). How do aggregated patient-reported outcome measures data stimulate health care improvement? a realist synthesis. J Health Serv Res Policy, 23(1), 57-65.

Objectives Internationally, there has been considerable debate about the role of data in supporting quality improvement in health care. Our objective was to understand how, why and in what circumstances the feedback of aggregated patient-reported outcome measures data improved patient care. Methods We conducted a realist synthesis. We identified three main programme theories underlying the use of patient-reported outcome measures as a quality improvement strategy and expressed them as nine 'if then' propositions. We identified international evidence to test these propositions through searches of electronic databases and citation tracking, and supplemented our synthesis with evidence from similar forms of performance data. We synthesized this evidence through comparing the mechanisms and impact of patient-reported outcome measures and other performance data on quality improvement in different contexts. Results Three programme theories were identified: supporting patient choice, improving accountability and enabling providers to compare their performance with others. Relevant contextual factors were extent of public disclosure, use of financial incentives, perceived credibility of the data and the practicality of the results. Available evidence suggests that patients or their agents rarely use any published performance data when selecting a provider. The perceived motivation behind public reporting is an important determinant of how providers respond. When clinicians perceived that performance indicators were not credible but were incentivized to collect them, gaming or manipulation of data occurred. Outcome data do not provide information on the cause of poor care: providers needed to integrate and interpret patient-reported outcome measures and other outcome data in the context of other data. Lack of timeliness of performance data constrains their impact. Conclusions Although there is only limited research evidence to support some widely held theories of how aggregated patient-reported outcome measures data stimulate quality improvement, several lessons emerge from interventions sharing the same programme theories to help guide the increasing use of these measures.

Abstract. Author URL.

Ricci-Cabello I, Stevens S, Dalton ARH, Griffiths RI, Campbell JL, Valderas JM (2018). Identifying Primary Care Pathways from Quality of Care to Outcomes and Satisfaction Using Structural Equation Modeling. Health Services Research, 53(1), 430-449. Abstract.

Fischer F, Gibbons C, Coste J, Valderas JM, Rose M, Leplège A (2018). Measurement invariance and general population reference values of the PROMIS Profile 29 in the UK, France, and Germany. Qual Life Res, 27(4), 999-1014. Abstract. Author URL.

Lloyd H, Wheat H, Horrell J, Sugavanam T, Fosh B, Valderas JM, Close J (2018). Patient-Reported Measures for Person-Centered Coordinated Care: a Comparative Domain Map and Web-Based Compendium for Supporting Policy Development and Implementation. J Med Internet Res, 20(2).

BACKGROUND: Patient-reported measure (PRM) questionnaires were originally used in research to measure outcomes of intervention studies. They have now evolved into a diverse family of tools measuring a range of constructs including quality of life and experiences of care. Current health and social care policy increasingly advocates their use for embedding the patient voice into service redesign through new models of care such as person-centered coordinated care (P3C). If chosen carefully and used efficiently, these tools can help improve care delivery through a variety of novel ways, including system-level feedback for health care management and commissioning. Support and guidance on how to use these tools would be critical to achieve these goals. OBJECTIVE: the objective of this study was to develop evidence-based guidance and support for the use of P3C-PRMs in health and social care policy through identification of PRMs that can be used to enhance the development of P3C, mapping P3C-PRMs against an existing model of domains of P3C, and integration and organization of the information in a user-friendly Web-based database. METHODS: a pragmatic approach was used for the systematic identification of candidate P3C-PRMs, which aimed at balancing comprehensiveness and feasibility. This utilized a number of resources, including existing compendiums, peer-reviewed and gray literature (using a flexible search strategy), and stakeholder engagement (which included guidance for relevant clinical areas). A subset of those candidate measures (meeting prespecified eligibility criteria) was then mapped against a theoretical model of P3C, facilitating classification of the construct being measured and the subsequent generation of shortlists for generic P3C measures, specific aspects of P3C (eg, communication or decision making), and condition-specific measures (eg, diabetes, cancer) in priority areas, as highlighted by stakeholders. RESULTS: in total, 328 P3C-PRMs were identified, which were used to populate a freely available Web-based database. of these, 63 P3C-PRMs met the eligibility criteria for shortlisting and were classified according to their measurement constructs and mapped against the theoretical P3C model. We identified tools with the best coverage of P3C, thereby providing evidence of their content validity as outcome measures for new models of care. Transitions and medications were 2 areas currently poorly covered by existing measures. All the information is currently available at a user-friendly web-based portal (p3c.org.uk), which includes all relevant information on each measure, such as the constructs targeted and links to relevant literature, in addition to shortlists according to relevant constructs. CONCLUSIONS: a detailed compendium of P3C-PRMs has been developed using a pragmatic systematic approach supported by stakeholder engagement. Our user-friendly suite of tools is designed to act as a portal to the world of PRMs for P3C, and have utility for a broad audience, including (but not limited to) health care commissioners, managers, and researchers.

Abstract. Author URL. Full text.

Catalá-López F, Hutton B, Driver JA, Ridao M, Valderas JM, Gènova-Maleras R, Forés-Martos J, Alonso-Arroyo A, Saint-Gerons DM, Vieta E, et al (2017). Anorexia nervosa and cancer: a protocol for a systematic review and meta-analysis of observational studies. Syst Rev, 6(1).

BACKGROUND: Anorexia nervosa is characterized by a severe restriction of caloric intake, low body weight, fear of gaining weight or of becoming fat, and disturbance of body image. Pathogenesis of the disorder may include genetic predisposition, hormonal changes and a combination of environmental, psychosocial, and cultural factors. Cancer is the second leading cause of death worldwide. At present, no systematic reviews and meta-analyses have evaluated the risk of cancer in people with anorexia nervosa. The objective of this study will be to evaluate the association between anorexia nervosa and the risk of developing or dying from cancer. METHODS/DESIGN: This study protocol is part of a systematic collection and assessment of multiple systematic reviews and meta-analyses (umbrella review) evaluating the association of cancer and multiple central nervous system disorders. We designed a specific protocol for a new systematic review and meta-analysis of observational studies of anorexia nervosa with risk of developing or dying from any cancer. Data sources will be PubMed, Embase, Scopus, Web of Science, and manual screening of references. Observational studies (case-control and cohort) in humans that examined the association between anorexia nervosa and risk of developing or dying from cancer will be sought. The primary outcomes will be cancer incidence and cancer mortality in association with anorexia nervosa. Secondary outcomes will be site-specific cancer incidence and mortality, respectively. Screening of abstracts and full texts, and data abstraction will be performed by two team members independently. Conflicts at all levels of screening and abstraction will be resolved through discussion. The quality of studies will be assessed by using the Ottawa-Newcastle scale by two team members independently. Random effects models will be conducted where appropriate. Subgroup and additional analyses will be conducted to explore the potential sources of heterogeneity. The World Cancer Research Fund (WCRF)/American Institute for Cancer Research (AICR) criteria and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach will be used for determining the quality of evidence for cancer outcomes. DISCUSSION: Findings from this systematic review will inform an ongoing umbrella review on cancer and central nervous system disorders. Our systematic review and meta-analysis of observational studies will establish the extent of the epidemiological evidence underlying the association between anorexia nervosa and cancer. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42017067462.

Abstract. Author URL. Full text.

Lloyd HM, Pearson M, Sheaff R, Asthana S, Wheat H, Sugavanam TP, Britten N, Valderas J, Bainbridge M, Witts L, et al (2017). Collaborative action for person-centred coordinated care (P3C): an approach to support the development of a comprehensive system-wide solution to fragmented care. Health Res Policy Syst, 15(1).

BACKGROUND: Fragmented care results in poor outcomes for individuals with complexity of need. Person-centred coordinated care (P3C) is perceived to be a potential solution, but an absence of accessible evidence and the lack of a scalable 'blue print' mean that services are 'experimenting' with new models of care with little guidance and support. This paper presents an approach to the implementation of P3C using collaborative action, providing examples of early developments across this programme of work, the core aim of which is to accelerate the spread and adoption of P3C in United Kingdom primary care settings. METHODS: Two centrally funded United Kingdom organisations (South West Collaboration for Leadership in Applied Health Research and Care and South West Academic Health Science Network) are leading this initiative to narrow the gap between research and practice in this urgent area of improvement through a programme of service change, evaluation and research. Multi-stakeholder engagement and co-design are core to the approach. A whole system measurement framework combines outcomes of importance to patients, practitioners and health organisations. Iterative and multi-level feedback helps to shape service change while collecting practice-based data to generate implementation knowledge for the delivery of P3C. The role of the research team is proving vital to support informed change and challenge organisational practice. The bidirectional flow of knowledge and evidence relies on the transitional positioning of researchers and research organisations. RESULTS: Extensive engagement and embedded researchers have led to strong collaborations across the region. Practice is beginning to show signs of change and data flow and exchange is taking place. However, working in this way is not without its challenges; progress has been slow in the development of a linked data set to allow us to assess impact innovations from a cost perspective. Trust is vital, takes time to establish and is dependent on the exchange of services and interactions. If collaborative action can foster P3C it will require sustained commitment from both research and practice. This approach is a radical departure from how policy, research and practice traditionally work, but one that we argue is now necessary to deal with the most complex health and social problems.

Abstract. Author URL. Full text.

Mounce LTA, Price S, Valderas JM, Hamilton W (2017). Comorbid conditions delay diagnosis of colorectal cancer: a cohort study using electronic primary care records. Br J Cancer, 116(12), 1536-1543. Abstract. Author URL. Full text.

Close J, Valderas JM, Byng R, Britten N, Lloyd H (2017). FUTURE OF QUALITY AND OUTCOMES FRAMEWORK Adapting QOF to focus on wellbeing and health. BMJ-BRITISH MEDICAL JOURNAL, 359 Author URL. Full text.

Ricci-Cabello I, Reeves D, Bell BG, Valderas JM (2017). Identifying patient and practice characteristics associated with patient-reported experiences of safety problems and harm: a cross-sectional study using a multilevel modelling approach. BMJ Qual Saf, 26(11), 899-907.

OBJECTIVE: to identify patient and family practice characteristics associated with patient-reported experiences of safety problems and harm. DESIGN: Cross-sectional study combining data from the individual postal administration of the validated Patient Reported Experiences and Outcomes of Safety in Primary Care (PREOS-PC) questionnaire to a random sample of patients in family practices (response rate=18.4%) and practice-level data for those practices obtained from NHS Digital. We built linear multilevel multivariate regression models to model the association between patient-level (clinical and sociodemographic) and practice-level (size and case-mix, human resources, indicators of quality and safety of care, and practice safety activation) characteristics, and outcome measures. SETTING: Practices distributed across five regions in the North, Centre and South of England. PARTICIPANTS: 1190 patients registered in 45 practices purposefully sampled (maximal variation in practice size and levels of deprivation). MAIN OUTCOME MEASURES: Self-reported safety problems, harm and overall perception of safety. RESULTS: Higher self-reported levels of safety problems were associated with younger age of patients (beta coefficient 0.15) and lower levels of practice safety activation (0.44). Higher self-reported levels of harm were associated with younger age (0.13) and worse self-reported health status (0.23). Lower self-reported healthcare safety was associated with lower levels of practice safety activation (0.40). The fully adjusted models explained 4.5% of the variance in experiences of safety problems, 8.6% of the variance in harm and 4.4% of the variance in perceptions of patient safety. CONCLUSIONS: Practices' safety activation levels and patients' age and health status are associated with patient-reported safety outcomes in English family practices. The development of interventions aimed at improving patient safety outcomes would benefit from focusing on the identified groups.

Abstract. Author URL.

Ricci-Cabello I, Saletti-Cuesta L, Slight SP, Valderas JM (2017). Identifying patient-centred recommendations for improving patient safety in General Practices in England: a qualitative content analysis of free-text responses using the Patient Reported Experiences and Outcomes of Safety in Primary Care (PREOS-PC) questionnaire. Health Expect, 20(5), 961-972. Abstract. Author URL. Full text.

Griffiths RI, Valderas JM, McFadden EC, Bankhead CR, Lavery BA, Khan NF, Stevens RJ, Keating NL (2017). Outcomes of preexisting diabetes mellitus in breast, colorectal, and prostate cancer. Journal of Cancer Survivorship, 11(5), 604-613. Abstract.

Ricci-Cabello I, Marsden KS, Avery AJ, Bell BG, Kadam UT, Reeves D, Slight SP, Perryman K, Barnett J, Litchfield I, et al (2017). Patients' evaluations of patient safety in English general practices: a cross-sectional study. Br J Gen Pract, 67(660), e474-e482. Abstract. Author URL.

Foguet-Boreu Q, Violán C, López Jiménez T, Pons-Vigués M, Rodríguez-Blanco T, Valderas JM, Guisado Clavero M, Pujol-Ribera E (2017). Pharmacological control of diabetes and hypertension comorbidity in the elderly: a study of "real world" data. Prim Care Diabetes, 11(4), 348-359. Abstract. Author URL.

Gibbons C, Richards S, Valderas JM, Campbell J (2017). Supervised Machine Learning Algorithms can Classify Open-Text Feedback of Doctor Performance with Human-Level Accuracy. Journal of Medical Internet Research, 19(3), e65-e65. Full text.

Stevens S, Valderas JM, Doran T, Perera R, Kontopantelis E (2016). Analysing indicators of performance, satisfaction, or safety using empirical logit transformation. BMJ, 352 Author URL.

Gibbons C, Bower P, Lovell K, Valderas J, Skevington S (2016). Electronic Quality of Life Assessment Using Computer-Adaptive Testing. Journal of Medical Internet Research, 18(9), e240-e240.

Porter I, Gonçalves-Bradley D, Ricci-Cabello I, Gibbons C, Gangannagaripalli J, Fitzpatrick R, Black N, Greenhalgh J, Valderas JM (2016). Framework and guidance for implementing patient-reported outcomes in clinical practice: evidence, challenges and opportunities. J Comp Eff Res, 5(5), 507-519. Abstract. Author URL.

Black N, Burke L, Forrest CB, Sieberer UHR, Ahmed S, Valderas JM, Bartlett SJ, Alonso J (2016). Patient-reported outcomes: pathways to better health, better services, and better societies. Qual Life Res, 25(5), 1103-1112. Abstract. Author URL.

Violán C, Foguet-Boreu Q, Roso-Llorach A, Rodriguez-Blanco T, Pons-Vigués M, Pujol-Ribera E, Valderas JM (2016). [Multimorbidity patterns in young adults in Catalonia: an analysis of clusters]. Aten Primaria, 48(7), 479-492. Abstract. Author URL.

Verstappen W, Gaal S, Bowie P, Parker D, Lainer M, Valderas JM, Wensing M, Esmail A (2015). A research agenda on patient safety in primary care. Recommendations by the LINNEAUS collaboration on patient safety in primary care. EUROPEAN JOURNAL OF GENERAL PRACTICE, 21, 72-77. Author URL.

Ble A, Masoli JAH, Barry HE, Winder RE, Tavakoly B, Henley WE, Kuchel GA, Valderas JM, Melzer D, Richards SH, et al (2015). Any versus long-term prescribing of high risk medications in older people using 2012 Beers Criteria: results from three cross-sectional samples of primary care records for 2003/4, 2007/8 and 2011/12. BMC Geriatr, 15

BACKGROUND: High risk medications are commonly prescribed to older US patients. Currently, less is known about high risk medication prescribing in other Western Countries, including the UK. We measured trends and correlates of high risk medication prescribing in a subset of the older UK population (community/institutionalized) to inform harm minimization efforts. METHODS: Three cross-sectional samples from primary care electronic clinical records (UK Clinical Practice Research Datalink, CPRD) in fiscal years 2003/04, 2007/08 and 2011/12 were taken. This yielded a sample of 13,900 people aged 65 years or over from 504 UK general practices. High risk medications were defined by 2012 Beers Criteria adapted for the UK. Using descriptive statistical methods and regression modelling, prevalence of 'any' (drugs prescribed at least once per year) and 'long-term' (drugs prescribed all quarters of year) high risk medication prescribing and correlates were determined. RESULTS: While polypharmacy rates have risen sharply, high risk medication prevalence has remained stable across a decade. A third of older (65+) people are exposed to high risk medications, but only half of the total prevalence was long-term (any = 38.4 % [95 % CI: 36.3, 40.5]; long-term = 17.4 % [15.9, 19.9] in 2011/12). Long-term but not any high risk medication exposure was associated with older ages (85 years or over). Women and people with higher polypharmacy burden were at greater risk of exposure; lower socio-economic status was not associated. Ten drugs/drug classes accounted for most of high risk medication prescribing in 2011/12. CONCLUSIONS: High risk medication prescribing has not increased over time against a background of increasing polypharmacy in the UK. Half of patients receiving high risk medications do so for less than a year. Reducing or optimising the use of a limited number of drugs could dramatically reduce high risk medications in older people. Further research is needed to investigate why the oldest old and women are at greater risk. Interventions to reduce high risk medications may need to target shorter and long-term use separately.

Abstract. Author URL. Full text.

Klemp K, Dovey S, Valderas JM, Rohe J, Godycki-Cwirko M, Elliott P, Beyer M, Ferdin MG, Hoffmann B (2015). Developing a patient safety incident classification system for primary care. A literature review and Delphi-survey by the LINNEAUS collaboration on patient safety in primary care. EUROPEAN JOURNAL OF GENERAL PRACTICE, 21, 35-38. Author URL.

Esmail A, Valderas JM, Verstappen W, Godycki-Cwirko M, Wensing M (2015). Developing a research agenda for patient safety in primary care. Background, aims and output of the LINNEAUS collaboration on patient safety in primary care. Eur J Gen Pract, 21 Suppl, 3-7. Abstract. Author URL.

Porter I, Valderas JM (2015). Development of a feedback form for routine clinical use of PROs in primary care for patients with multimorbidity. QUALITY OF LIFE RESEARCH, 24, 181-182. Author URL.

Greenhalgh J, Dalkin S, Gibbons E, Black N, Valderas JM, Wright J, Meads D, Lingard L, Wood L, Jackson J, et al (2015). How do health care providers respond to PROMs data to improve patient care? a realist synthesis. QUALITY OF LIFE RESEARCH, 24, 117-117. Author URL.

Ricci-Cabello I, Violán C, Foguet-Boreu Q, Mounce LTA, Valderas JM (2015). Impact of multi-morbidity on quality of healthcare and its implications for health policy, research and clinical practice. A scoping review. Eur J Gen Pract, 21(3), 192-202. Abstract. Author URL.

Ricci-Cabello I, Stevens S, Kontopantelis E, Dalton ARH, Griffiths RI, Campbell JL, Doran T, Valderas JM (2015). Impact of the Prevalence of Concordant and Discordant Conditions on the Quality of Diabetes Care in Family Practices in England. Ann Fam Med, 13(6), 514-522. Abstract. Author URL.

Trier H, Valderas JM, Wensing M, Martin HM, Egebart J (2015). Involving patients in patient safety programmes: a scoping review and consensus procedure by the LINNEAUS collaboration on patient safety in primary care. EUROPEAN JOURNAL OF GENERAL PRACTICE, 21, 56-61. Author URL.

Parker D, Wensing M, Esmail A, Valderas JM (2015). Measurement tools and process indicators of patient safety culture in primary care. A mixed methods study by the LINNEAUS collaboration on patient safety in primary care. Eur J Gen Pract, 21 Suppl, 26-30. Abstract. Author URL.

Ricci-Cabello I, Gonçalves DC, Rojas-García A, Valderas JM (2015). Measuring experiences and outcomes of patient safety in primary care: a systematic review of available instruments. Fam Pract, 32(1), 106-119. Abstract. Author URL.

Foguet-Boreu Q, Violán C, Rodriguez-Blanco T, Roso-Llorach A, Pons-Vigués M, Pujol-Ribera E, Cossio Gil Y, Valderas JM (2015). Multimorbidity Patterns in Elderly Primary Health Care Patients in a South Mediterranean European Region: a Cluster Analysis. PLoS One, 10(11). Abstract. Author URL. Full text.

Valderas JM (2015). Multimorbidity, not a health condition or complexity by another name. Eur J Gen Pract, 21(4), 213-214. Author URL.

Magin P, Dunbabin J, Goode S, Valderas JM, Levi C, D'Souza M, Marshall M, Barker D, Lasserson D (2015). Patients' responses to transient ischaemic attack symptoms: a cross-sectional questionnaire study in Australian general practices. Br J Gen Pract, 65(630), e24-e31. Abstract. Author URL.

Gonçalves Bradley DC, Gibbons C, Ricci-Cabello I, Bobrovitz NJ, Gibbons EJ, Kotzeva A, Alonso J, Fitzpatrick R, Bower P, van der Wees PJ, et al (2015). Routine provision of information on patient-reported outcome measures to healthcare providers and patients in clinical practice. Cochrane Database of Systematic Reviews, 2015(4). Abstract.

Islam MM, McRae IS, Yen L, Jowsey T, Valderas JM (2015). Time spent on health-related activities by senior Australians with chronic diseases: what is the role of multimorbidity and comorbidity?. Aust N Z J Public Health, 39(3), 277-283. Abstract. Author URL.

Porter I, Valderas JM (2015). Use of PROs in clinical guidance for the management of chronic conditions in primary care in the United Kingdom. QUALITY OF LIFE RESEARCH, 24, 75-76. Author URL.

Le Reste J, Nabbe P, Lingner H, Kasuba Lazic D, Assenova R, Munoz M, Sowinska A, Lygidakis C, Doerr C, Czachowski S, et al (2015). What research agenda could be generated from the European General Practice Research Network concept of Multimorbidity in Family Practice?. BMC Family Practice, 16(1).

Catala-Lopez F, Crespo-Facorro B, Vieta E, Valderas JM, Valencia A, Tabares-Seisdedos R (2014). Alzheimer's Disease and Cancer: Current Epidemiological Evidence for a Mutual Protection. NEUROEPIDEMIOLOGY, 42(2), 121-122. Author URL.

O′Neill B, Gonçalves D, Ricci-Cabello I, Ziebland S, Valderas J (2014). An Overview of Self-Administered Health Literacy Instruments. PLoS ONE, 9(12), e109110-e109110.

Garin O, Herdman M, Vilagut G, Ferrer M, Ribera A, Rajmil L, Valderas JM, Guillemin F, Revicki D, Alonso J, et al (2014). Assessing health-related quality of life in patients with heart failure: a systematic, standardized comparison of available measures. HEART FAILURE REVIEWS, 19(3), 359-367. Author URL.

Schmidt S, Garin O, Pardo Y, Valderas JM, Alonso J, Rebollo P, Rajmil L, Garcia-Forero C, Ferrer M, Grp EMPRO, et al (2014). Assessing quality of life in patients with prostate cancer: a systematic and standardized comparison of available instruments. QUALITY OF LIFE RESEARCH, 23(8), 2169-2181. Author URL.

Mavaddat N, Valderas JM, van der Linde R, Khaw KT, Kinmonth AL (2014). Association of self-rated health with multimorbidity, chronic disease and psychosocial factors in a large middle-aged and older cohort from general practice: a cross-sectional study. BMC FAMILY PRACTICE, 15 Author URL. Full text.

Violan C, Foguet-Boreu Q, Roso-Llorach A, Rodriguez-Blanco T, Pons-Vigues M, Pujol-Ribera E, Angel Munoz-Perez M, Valderas JM (2014). Burden of multimorbidity, socioeconomic status and use of health services across stages of life in urban areas: a cross-sectional study. BMC PUBLIC HEALTH, 14 Author URL. Full text.

Valderas JM, Avery A, Ricci-Cabello I (2014). Development of a measure of Patient-reported Experiences and Outcomes of Patient Safety in Primary Care: the PREOS-PC instrument. QUALITY OF LIFE RESEARCH, 23, 38-38. Author URL.

Schmidt S, Ferrer M, González M, González N, Valderas JM, Alonso J, Escobar A, Vrotsou K, EMPRO Group (2014). Evaluation of shoulder-specific patient-reported outcome measures: a systematic and standardized comparison of available evidence. J Shoulder Elbow Surg, 23(3), 434-444. Abstract. Author URL.

Greenhalgh J, Dalkin S, Wright J, Black N, Valderas JM, Gibbons EJ, Meads D, Wood L, Mills C, Pawson R, et al (2014). Functionality and feedback: a protocol for a realist synthesis of the collation, interpretation and utilisation of PRO data to improve patient care. QUALITY OF LIFE RESEARCH, 23, 181-181. Author URL.

Greenhalgh J, Pawson R, Wright J, Black N, Valderas JM, Meads D, Gibbons E, Wood L, Wood C, Mills C, et al (2014). Functionality and feedback: a protocol for a realist synthesis of the collation, interpretation and utilisation of PROMs data to improve patient care. BMJ Open, 4(7).

INTRODUCTION: the feedback and public reporting of PROMs data aims to improve the quality of care provided to patients. Existing systematic reviews have found it difficult to draw overall conclusions about the effectiveness of PROMs feedback. We aim to execute a realist synthesis of the evidence to understand by what means and in what circumstances the feedback of PROMs data leads to the intended service improvements. METHODS AND ANALYSIS: Realist synthesis involves (stage 1) identifying the ideas, assumptions or 'programme theories' which explain how PROMs feedback is supposed to work and in what circumstances and then (stage 2) reviewing the evidence to determine the extent to which these expectations are met in practice. For stage 1, six provisional 'functions' of PROMs feedback have been identified to structure our review (screening, monitoring, patient involvement, demand management, quality improvement and patient choice). For each function, we will identify the different programme theories that underlie these different goals and develop a logical map of the respective implementation processes. In stage 2, we will identify studies that will provide empirical tests of each component of the programme theories to evaluate the circumstances in which the potential obstacles can be overcome and whether and how the unintended consequences of PROMs feedback arise. We will synthesise this evidence to (1) identify the implementation processes which support or constrain the successful collation, interpretation and utilisation of PROMs data; (2) identify the implementation processes through which the unintended consequences of PROMs data arise and those where they can be avoided. ETHICS AND DISSEMINATION: the study will not require NHS ethics approval. We have secured ethical approval for the study from the University of Leeds (LTSSP-019). We will disseminate the findings of the review through a briefing paper and dissemination event for National Health Service stakeholders, conferences and peer reviewed publications.

Abstract. Author URL. Full text.

Foguet-Boreu Q, Violan C, Roso-Llorach A, Rodriguez-Blanco T, Pons-Vigues M, Munoz-Perez MA, Pujol-Ribera E, Valderas JM (2014). Impact of multimorbidity: acute morbidity, area of residency and use of health services across the life span in a region of south Europe. BMC FAMILY PRACTICE, 15 Author URL. Full text.

Griffiths RI, Gleeson ML, Valderas JM, Danese MD (2014). Impact of undetected comorbidity on treatment and outcomes of breast cancer. Int J Breast Cancer, 2014 Abstract. Author URL. Full text.

Catala-Lopez F, Suarez-Pinilla M, Suarez-Pinilla P, Valderas JM, Gomez-Beneyto M, Martinez S, Balanza-Martinez V, Climent J, Valencia A, McGrath J, et al (2014). Inverse and Direct Cancer Comorbidity in People with Central Nervous System Disorders: a Meta-Analysis of Cancer Incidence in 577,013 Participants of 50 Observational Studies. PSYCHOTHERAPY AND PSYCHOSOMATICS, 83(2), 89-105. Author URL. Full text.

Islam MM, Valderas JM, Yen L, Dawda P, Jowsey T, McRae IS (2014). Multimorbidity and comorbidity of chronic diseases among the senior Australians: prevalence and patterns. PLoS One, 9(1). Abstract. Author URL. Full text.

Muth C, Beyer M, Fortin M, Rochon J, Oswald F, Valderas JM, Harder S, Glynn LG, Perera R, Freitag M, et al (2014). Multimorbidity's research challenges and priorities from a clinical perspective: the case of 'Mr Curran'. EUROPEAN JOURNAL OF GENERAL PRACTICE, 20(2), 139-147. Author URL.

Islam MM, Yen L, Valderas JM, McRae IS (2014). Out-of-pocket expenditure by Australian seniors with chronic disease: the effect of specific diseases and morbidity clusters. BMC PUBLIC HEALTH, 14 Author URL. Full text.

Violan C, Foguet-Boreu Q, Flores-Mateo G, Salisbury C, Blom J, Freitag M, Glynn L, Muth C, Valderas JM (2014). Prevalence, determinants and patterns of multimorbidity in primary care: a systematic review of observational studies. PLoS One, 9(7).

INTRODUCTION: Multimorbidity is a major concern in primary care. Nevertheless, evidence of prevalence and patterns of multimorbidity, and their determinants, are scarce. The aim of this study is to systematically review studies of the prevalence, patterns and determinants of multimorbidity in primary care. METHODS: Systematic review of literature published between 1961 and 2013 and indexed in Ovid (CINAHL, PsychINFO, Medline and Embase) and Web of Knowledge. Studies were selected according to eligibility criteria of addressing prevalence, determinants, and patterns of multimorbidity and using a pretested proforma in primary care. The quality and risk of bias were assessed using STROBE criteria. Two researchers assessed the eligibility of studies for inclusion (Kappa= 0.86). RESULTS: We identified 39 eligible publications describing studies that included a total of 70,057,611 patients in 12 countries. The number of health conditions analysed per study ranged from 5 to 335, with multimorbidity prevalence ranging from 12.9% to 95.1%. All studies observed a significant positive association between multimorbidity and age (odds ratio [OR], 1.26 to 227.46), and lower socioeconomic status (OR, 1.20 to 1.91). Positive associations with female gender and mental disorders were also observed. The most frequent patterns of multimorbidity included osteoarthritis together with cardiovascular and/or metabolic conditions. CONCLUSIONS: Well-established determinants of multimorbidity include age, lower socioeconomic status and gender. The most prevalent conditions shape the patterns of multimorbidity. However, the limitations of the current evidence base means that further and better designed studies are needed to inform policy, research and clinical practice, with the goal of improving health-related quality of life for patients with multimorbidity. Standardization of the definition and assessment of multimorbidity is essential in order to better understand this phenomenon, and is a necessary immediate step.

Abstract. Author URL. Full text.

Griffiths RI, Lindquist KJ, O'Malley CD, Gleeson ML, Duryea JL, Valderas JM, Danese MD (2014). Undiagnosed diabetes in breast, colorectal, lung, and prostate cancer: incidence and risk factors. ISRN Oncol, 2014 Abstract. Author URL.

O'Neill B, Ziebland S, Valderas J, Lupiáñez-Villanueva F (2014). User-Generated Online Health Content: a Survey of Internet Users in the United Kingdom. Journal of Medical Internet Research, 16(4), e118-e118.

Kontopantelis E, Springate D, Reeves D, Ashcroft DM, Valderas JM, Doran T (2014). Withdrawing performance indicators: retrospective analysis of general practice performance under UK Quality and Outcomes Framework. BMJ, 348

OBJECTIVES: to investigate the effect of withdrawing incentives on recorded quality of care, in the context of the UK Quality and Outcomes Framework pay for performance scheme. DESIGN: Retrospective longitudinal study. SETTING: Data for 644 general practices, from 2004/05 to 2011/12, extracted from the Clinical Practice Research Datalink. PARTICIPANTS: all patients registered with any of the practices over the study period-13,772,992 in total. INTERVENTION: Removal of financial incentives for aspects of care for patients with asthma, coronary heart disease, diabetes, stroke, and psychosis. MAIN OUTCOME MEASURES: Performance on eight clinical quality indicators withdrawn from a national incentive scheme: influenza immunisation (asthma) and lithium treatment monitoring (psychosis), removed in April 2006; blood pressure monitoring (coronary heart disease, diabetes, stroke), cholesterol concentration monitoring (coronary heart disease, diabetes), and blood glucose monitoring (diabetes), removed in April 2011. Multilevel mixed effects multiple linear regression models were used to quantify the effect of incentive withdrawal. RESULTS: Mean levels of performance were generally stable after the removal of the incentives, in both the short and long term. For the two indicators removed in April 2006, levels in 2011/12 were very close to 2005/06 levels, although a small but statistically significant drop was estimated for influenza immunisation. For five of the six indicators withdrawn from April 2011, no significant effect on performance was seen following removal and differences between predicted and observed scores were small. Performance on related outcome indicators retained in the scheme (such as blood pressure control) was generally unaffected. CONCLUSIONS: Following the removal of incentives, levels of performance across a range of clinical activities generally remained stable. This indicates that health benefits from incentive schemes can potentially be increased by periodically replacing existing indicators with new indicators relating to alternative aspects of care. However, all aspects of care investigated remained indirectly or partly incentivised in other indicators, and further work is needed to assess the generalisability of the findings when incentives are fully withdrawn.

Abstract. Author URL. Full text.

Violan C, Foguet-Boreu Q, Hermosilla-Perez E, Valderas JM, Bolibar B, Fabregas-Escurriola M, Brugulat-Guiteras P, Angel Munoz-Perez M (2013). Comparison of the information provided by electronic health records data and a population health survey to estimate prevalence of selected health conditions and multimorbidity. BMC PUBLIC HEALTH, 13 Author URL. Full text.

Ricci-Cabello I, Goncalves DC, Valderas JM (2013). Development of a measure of patient reported experiences and outcomes of patient safety in general practices in England: the PREOS-PC instrument. QUALITY OF LIFE RESEARCH, 22 Author URL.

Villalonga Olives E, Garcia Forero C, Maydeu-Olivares A, Almansa J, Palacio Vieira JA, Valderas JM, Ferrer M, Rajmil L, Alonso J (2013). Environmental risk and protective factors of adolescents' and youths' mental health: differences between parents' appraisal and self-reports. QUALITY OF LIFE RESEARCH, 22(3), 613-622. Author URL.

Villalonga-Olives E, Forero CG, Maydeu-Olivares A, Almansa J, Palacio Vieira JA, Valderas JM, Ferrer M, Rajmil L, Alonso J (2013). Erratum: Environmental risk and protective factors of adolescents' and youths' mental health: Differences between parents' appraisal and self-reports (Quality of Life Research DOI: 10.1007/s11136-012-0167-x). Quality of Life Research, 22(3).

Valderas JM (2013). Getting impatient about person-centred health care. Eur J Gen Pract, 19(3), 141-142. Author URL.

Valderas JM (2013). Increasing clinical, community, and patient-centered health research for preventing and managing multimorbidity. J Comorb, 3(Spec Issue), 41-44. Abstract. Author URL.

Palacio-Vieira J-A, Villalonga-Olives E, Maria Valderas J, Herdman M, Alonso J, Rajmil L (2013). Predictors of the use of healthcare services in children and adolescents in Spain. INTERNATIONAL JOURNAL OF PUBLIC HEALTH, 58(2), 207-215. Author URL.

Kontopantelis E, Reeves D, Valderas JM, Campbell S, Doran T (2013). Recorded quality of primary care for patients with diabetes in England before and after the introduction of a financial incentive scheme: a longitudinal observational study. BMJ QUALITY & SAFETY, 22(1), 53-64. Author URL.

Alonso J, Bartlett SJ, Rose M, Aaronson NK, Chaplin JE, Efficace F, Leplege A, Lu A, Tulsky DS, Raat H, et al (2013). The case for an international patient-reported outcomes measurement information system (PROMIS (R)) initiative. HEALTH AND QUALITY OF LIFE OUTCOMES, 11 Author URL. Full text.

Salisbury C, Procter S, Stewart K, Bowen L, Purdy S, Ridd M, Valderas J, Blakeman T, Reeves D (2013). The content of general practice consultations: cross-sectional study based on video recordings. British Journal of General Practice, 63(616), 751-759.

Jowsey T, McRae IS, Valderas JM, Dugdale P, Phillips R, Bunton R, Gillespie J, Banfield M, Jones L, Kljakovic M, et al (2013). Time's Up. Descriptive Epidemiology of Multi-Morbidity and Time Spent on Health Related Activity by Older Australians: a Time Use Survey. PLOS ONE, 8(4). Author URL. Full text.

Castellvi P, Ferrer M, Alonso J, en nombre del Comité Científico de BiblioPRO (2013). [The patient-reported outcomes in research: definition, impact, classification, measurement and assessment]. Med Clin (Barc), 141(8), 358-365. Author URL.

Harrison M, Reeves D, Harkness E, Valderas J, Kennedy A, Rogers A, Hann M, Bower P (2012). A secondary analysis of the moderating effects of depression and multimorbidity on the effectiveness of a chronic disease self-management programme. Patient Education and Counseling, 87(1), 67-73.

Goncalves DC, Gibbons EJ, Fitzpatrick R, Valderas JM (2012). A systematic review and narrative review of qualitative studies about the use of PROs in clinical practice. QUALITY OF LIFE RESEARCH, 21, 25-25. Author URL.

Valderas JM, Ferrer M, Mendivil J, Garin O, Rajmil L, Herdmann M, Alonso J, Goncalves DC (2012). Development and testing of standards for individualization of patient reported outcome (PRO) measures using EMPRO. QUALITY OF LIFE RESEARCH, 21, 43-43. Author URL.

Griffiths RI, Danese MD, Gleeson ML, Valderas JM (2012). Epidemiology and outcomes of previously undiagnosed diabetes in older women with breast cancer: an observational cohort study based on SEER-Medicare. BMC CANCER, 12 Author URL. Full text.

Doran T, Kontopantelis E, Fullwood C, Lester H, Valderas JM, Campbell S (2012). Exempting dissenting patients from pay for performance schemes: retrospective analysis of exception reporting in the UK Quality and Outcomes Framework. BRITISH MEDICAL JOURNAL, 344 Author URL. Full text.

Goncalves DC, Ricci-Cabello I, Valderas JM (2012). Identification and classification of individualized patient-reported outcome measures. QUALITY OF LIFE RESEARCH, 21, 113-114. Author URL.

Huntley AL, Johnson R, Purdy S, Valderas JM, Salisbury C (2012). Measures of Multimorbidity and Morbidity Burden for Use in Primary Care and Community Settings: a Systematic Review and Guide. ANNALS OF FAMILY MEDICINE, 10(2), 134-141. Author URL.

Valderas JM, Goncalves DC, Alonso J (2012). Patient reported outcome measures: a revised model-based classification system for research and clinical practice. QUALITY OF LIFE RESEARCH, 21, 104-105. Author URL.

Valderas JM, Fitzpatrick R, Roland M (2012). Using health status to measure NHS performance: another step into the dark for the health reform in England. BMJ Qual Saf, 21(4), 352-353. Abstract. Author URL.

Doran T, Kontopantelis E, Valderas JM, Campbell S, Roland M, Salisbury C, Reeves D (2011). Effect of Financial Incentives on Incentivized and Nonincentivized Clinical Activities: Longitudinal Analysis of Data from the UK Quality and Outcomes Framework EDITORIAL COMMENT. OBSTETRICAL & GYNECOLOGICAL SURVEY, 66(11), 677-679. Author URL.

Doran T, Kontopantelis E, Valderas JM, Campbell S, Roland M, Salisbury C, Reeves D (2011). Effect of financial incentives on incentivised and non-incentivised clinical activities: longitudinal analysis of data from the UK Quality and Outcomes Framework. BRITISH MEDICAL JOURNAL, 342 Author URL.

Salisbury C, Johnson L, Purdy S, Valderas JM, Montgomery AA (2011). Epidemiology and impact of multimorbidity in primary care: a retrospective cohort study. BRITISH JOURNAL OF GENERAL PRACTICE, 61(582). Author URL.

Bower P, Macdonald W, Harkness E, Gask L, Kendrick T, Valderas JM, Dickens C, Blakeman T, Sibbald B (2011). Multimorbidity, service organization and clinical decision making in primary care: a qualitative study. Fam Pract, 28(5), 579-587. Abstract. Author URL.

Tabares-Seisdedos R, Dumont N, Baudot A, Valderas JM, Climent J, Valencia A, Crespo-Facorro B, Vieta E, Gomez-Beneyto M, Martinez S, et al (2011). No paradox, no progress: inverse cancer comorbidity in people with other complex diseases. LANCET ONCOLOGY, 12(6), 604-608. Author URL.

Pueyo M, Baranda L, Valderas J, Starfield B, Rajmil L (2011). Papel del pediatra de atención primaria y coordinación con atención especializada. Anales de Pediatría, 75(4), 247-252.

Villalonga-Olives E, Forero CG, Erhart M, Palacio-Vieira JA, Valderas JM, Herdman M, Ferrer M, Rajmil L, Ravens-Sieberer U, Alonso J, et al (2011). Relationship Between Life Events and Psychosomatic Complaints During Adolescence/Youth: a Structural Equation Model Approach. JOURNAL OF ADOLESCENT HEALTH, 49(2), 199-205. Author URL.

Valderas JM, Mercer SW, Fortin M (2011). Research on patients with multiple health conditions: different constructs, different views, one voice. J Comorb, 1, 1-3. Author URL.

Almansa J, Luis Ayuso-Mateos J, Garin O, Chatterji S, Kostanjsek N, Alonso J, Maria Valderas J, Cieza A, Raggi A, Svestkova O, et al (2011). The International Classification of Functioning, Disability and Health: development of capacity and performance scales. JOURNAL OF CLINICAL EPIDEMIOLOGY, 64(12), 1400-1411. Author URL.

Glynn LG, Valderas JM, Healy P, Burke E, Newell J, Gillespie P, Murphy AW (2011). The prevalence of multimorbidity in primary care and its effect on health care utilization and cost. FAMILY PRACTICE, 28(5), 516-523. Author URL.

Palacio-Vieira J, Villalonga-Olives E, Alonso J, Valderas J, Herdman M, Espallargues M, Berra S, Rajmil L (2010). Brief report: the KIDSCREEN follow-up study on Health-related Quality of Life (HRQoL) in Spanish children and adolescents. Pilot test and representativeness. Journal of Adolescence, 33(1), 227-231.

Campbell SM, Kontopantelis E, Reeves D, Valderas JM, Gaehl E, Small N, Roland MO (2010). Changes in Patient Experiences of Primary Care During Health Service Reforms in England Between 2003 and 2007. ANNALS OF FAMILY MEDICINE, 8(6), 499-506. Author URL.

Reeves D, Doran T, Valderas JM, Kontopantelis E, Trueman P, Sutton M, Campbell S, Lester H (2010). How to identify when a performance indicator has run its course. BMJ (Online), 340(7752), 899-901.

Reeves D, Doran T, Valderas JM, Kontopantelis E, Trueman P, Sutton M, Campbell S, Lester H (2010). How to identify when a performance indicator has run its course. BMJ, 340 Author URL.

Harkness E, Macdonald W, Valderas J, Coventry P, Gask L, Bower P (2010). Identifying Psychosocial Interventions That Improve Both Physical and Mental Health in Patients with Diabetes: a systematic review and meta-analysis. Diabetes Care, 33(4), 926-930.

Villalonga-Olives E, Rojas-Farreras S, Vilagut G, Palacio-Vieira JA, Maria Valderas J, Herdman M, Ferrer M, Rajmil L, Alonso J (2010). Impact of recent life events on the health related quality of life of adolescents and youths: the role of gender and life events typologies in a follow-up study. HEALTH AND QUALITY OF LIFE OUTCOMES, 8 Author URL.

Feeny D, Valderas JM, Fayers P, Santana MJ (2010). Overview of Existing and Novel Methodologies for Testing the Effectiveness of Using Patient Reported Outcomes in Clinical Practice. QUALITY OF LIFE RESEARCH, 19, 11-11. Author URL.

Villalonga-Olives E, Forero CG, Erhart M, Palacio-Vieira JA, Valderas JM, Herdman M, Ferrer M, Rajmil L, Ravens-Sieberer U, Alonso J, et al (2010). RELATIONSHIP BETWEEN LIFE EVENTS AND PSYCHOSOMATIC COMPLAINTS DURING ADOLESCENCE/YOUTH: a STRUCTURAL EQUATION MODEL APPROACH. EPIDEMIOLOGIA & PREVENZIONE, 34(5-6), 52-53. Author URL.

Garin O, Ayuso-Mateos J, Almansa J, Nieto M, Chatterji S, Vilagut G, Alonso J, Cieza A, Svetskova O, Burger H, et al (2010). Validation of the "World Health Organization Disability Assessment Schedule, WHODAS-2" in patients with chronic diseases. Health and Quality of Life Outcomes, 8(1), 51-51.

Herdman M, Garin O, Vilagut G, Ribera A, Permanyer-Miralda G, Ferrer M, Rajmil L, Valderas JM, Alonso J (2009). ASSESSING THE QUALITY OF QUALITY OF LIFE MEASURES IN HEART FAILURE: a COMPARISON OF AVAILABLE INSTRUMENTS. VALUE IN HEALTH, 12(7), A340-A340. Author URL.

Valderas JM, Starfield B, Forrest CB, Sibbald B, Roland M (2009). Ambulatory Care Provided by Office-Based Specialists in the United States. ANNALS OF FAMILY MEDICINE, 7(2), 104-111. Author URL.

Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M (2009). Defining Comorbidity: Implications for Understanding Health and Health Services. ANNALS OF FAMILY MEDICINE, 7(4), 357-363. Author URL.

Rajmil L, Palacio-Vieira JA, Herdman M, Lopez-Aguila S, Villalonga-Olives E, Valderas JM, Espallargues M, Alonso J (2009). Effect on Health-related Quality of Life of changes in mental health in children and adolescents. HEALTH AND QUALITY OF LIFE OUTCOMES, 7 Author URL.

Valderas JM (2009). Identifying studies in Spanish population in PubMed. GACETA SANITARIA, 23(1), 82-82. Author URL.

Villalonga Olives E, Maydeu-Olivares A, Palacio-Vieira J, Valderas JM, Rajmil L, Alonso J (2009). RISK FACTORS THAT AFFECT MENTAL HEALTH IN YOUNGSTERS: STRUCTURAL EQUATION MODELING. GACETA SANITARIA, 23, 57-58. Author URL.

Valderas JM, Starfield B, Forrest CB, Rajmil L, Roland M, Sibbald B (2009). Routine care provided by specialists to children and adolescents in the United States (2002-2006). BMC Health Serv Res, 9 Abstract. Author URL. Full text.

Garin O, Nieto-Moreno M, Almansa J, Vilagut G, Villalonga-Olives E, Alonso J, Valderas JM, Ayuso JL, Ferrer M (2009). VALIDATION OF THE "WORLD HEALTH ORGANIZATION DISABILITY ASSESSMENT SCHEDULE, WHODAS-II". GACETA SANITARIA, 23, 53-54. Author URL.

Valderas JM, Kotzeva A, Espallargues M, Guyatt G, Ferrans CE, Halyard MY, Revicki DA, Symonds T, Parada A, Alonso J, et al (2008). A relevant study was missed in our systematic review on the impact of patient-reported outcomes in clinical practice. QUALITY OF LIFE RESEARCH, 17(6), 965-966. Author URL.

Palacio-Vieira JA, Villalonga-Olives E, Valderas JM, Espallargues M, Herdman M, Berra S, Alonso J, Rajmil L (2008). Changes in health-related quality of life (HRQoL) in a population-based sample of children and adolescents after 3 years of follow-up. QUALITY OF LIFE RESEARCH, 17(10), 1207-1215. Author URL.

Valderas JM, Ferrer M, Mendívil J, Garin O, Rajmil L, Herdman M, Alonso J, Scientific Committee on "Patient-Reported Outcomes" of the IRYSS Network (2008). Development of EMPRO: a tool for the standardized assessment of patient-reported outcome measures. Value Health, 11(4), 700-708. Abstract. Author URL.

Vilagut G, Maria Valderas J, Ferrer M, Garin O, Lopez-Garcia E, Alonso J (2008). Interpretation of SF-36 and SF-12 questionnaires in Spain: physical and mental components. MEDICINA CLINICA, 130(19), 726-735. Author URL.

Valderas JM, Alonso J, Guyatt GH (2008). Measuring patient-reported outcomes: moving from clinical trials into clinical practice. MEDICAL JOURNAL OF AUSTRALIA, 189(2), 93-94. Author URL.

Valderas JM, Alonso J (2008). Patient reported outcome measures: a model-based classification system for research and clinical practice. Qual Life Res, 17(9), 1125-1135. Abstract. Author URL.

Villalonga-Olives E, Valderas JM, Palacio-Vieira JA, Herdman M, Rajmil L, Alonso J (2008). The adaptation into Spanish of the Coddington Life Events Scales (CLES). QUALITY OF LIFE RESEARCH, 17(3), 447-452. Author URL.

Valderas JM, Kotzeva A, Espallargues M, Guyatt G, Ferrans CE, Halyard MY, Revicki DA, Symonds T, Parada A, Alonso J, et al (2008). The impact of measuring patient-reported outcomes in clinical practice: a systematic review of the literature. Qual Life Res, 17(2), 179-193. Abstract. Author URL.

Valderas JM (2008). Treatment intensification does not always lead to better quality of care in patients with hypertension. ANNALS OF INTERNAL MEDICINE, 149(5), 362-362. Author URL.

Morcillo C, Valderas JM, Roca JM, Oliveró R, Núñez C, Sánchez M, Bechich S (2007). Computed Tomographic Measurement of Coronary Artery Calcification in the Assessment of Cardiovascular Risk: a Descriptive Study. Revista Española de Cardiología (English Edition), 60(3), 268-275.

Valderas JM, Starfield B, Salisbury C (2007). Definitions of chronic health conditions in childhood. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 298(14), 1636-1636. Author URL.

Guyatt GH, Ferrans CE, Halyard MY, Revicki DA, Symonds TL, Varricchio CG, Kotzeva A, Valderas JM, Alonso J, Clinical Significance Consensus Meeting Group, et al (2007). Exploration of the value of health-related quality-of-life information from clinical research and into clinical practice. Mayo Clin Proc, 82(10), 1229-1239. Abstract. Author URL.

Valderas Martinez JM (2007). Geographic filters for PubMed. REVISTA ESPANOLA DE SALUD PUBLICA, 81(4), 421-422. Author URL.

Morcillo C, Valderas JM, Roca JM, Oliveró R, Núñez C, Sánchez M, Bechich S (2007). La determinación de calcio coronario con tomografía computarizada en la evaluación del riesgo cardiovascular: un estudio descriptivo. Revista Española de Cardiología, 60(3), 268-275.

Valderas JM (2007). Measurement of health and disability. LANCET, 370(9586), 483-484. Author URL.

Valderas JM, Starfield B, Roland M (2007). Multimorbidity's many challenges - a research priority in the UK. BRITISH MEDICAL JOURNAL, 334(7604), 1128-1128. Author URL.

Balagué M, María Valderas J, Bolíbar B (2007). Oportunidades y aspectos organizativos de la investigación en atención primaria. Medicina Clínica, 128(18), 711-714.

Codina García F, Morató I, Valderas JM, Rajmil L (2007). Rendimiento escolar y salud en adolescentes de Lloret de Mar (Girona). Atención Primaria, 39(11), 623-624.

Valderas JM, Alonso J (2007). Response to Cella et al, May 2006 - Supplement 1 medical care. MEDICAL CARE, 45(10), 1008-1008. Author URL.

Valderas JM (2007). Why do team-authored papers get cited more?. SCIENCE, 317(5844), 1496-1496. Author URL.

García FC, Morató I, Valderas JM, Rajmil L (2007). [School performance and health in adolescents in Lloret de Mar (Girona)]. Aten Primaria, 39(11), 623-624. Author URL.

Valderas Martínez JM (2007). [Use of geographic restrictions in PubMed]. Rev Esp Salud Publica, 81(4), 421-422. Author URL.

Valderas JM, Mendivil J, Parada A, Losada-Yáñez M, Alonso J (2006). Construcción de un filtro geográfico para la identificación en PubMed de estudios realizados en España. Revista Española de Cardiología, 59(12), 1244-1251.

Valderas JM, Mendivil J, Parada A, Losada-Yanez M, Alonso J (2006). Development of a geographic filter for PubMed to identify studies performed in Spain. REVISTA ESPANOLA DE CARDIOLOGIA, 59(12), 1244-1251. Author URL.

Tarrado X, Castañón M, Thió M, Valderas JM, Garcia Aparicio L, Morales L (2005). Comparative Study between Isolated Intestinal Perforation and Necrotizing Enterocolitis. European Journal of Pediatric Surgery, 15(2), 88-94.

Vilagut G, Ferrer M, Rajmil L, Rebollo P, Permanyer-Miralda G, Quintana JM, Santed R, Valderas JM, Ribera A, Domingo-Salvany A, et al (2005). El Cuestionario de Salud SF-36 español: una década de experiencia y nuevos desarrollos. Gaceta Sanitaria, 19(2), 135-150.

Morcillo C, Valderas JM, Aguado O, Delás J, Sort D, Pujadas R, Rosell F (2005). Evaluación de una intervención domiciliaria en pacientes con insuficiencia cardíaca. Resultados de un estudio aleatorizado. Revista Española de Cardiología, 58(6), 618-625.

Morcillo C, Valderas JM, Aguado O, Delas J, Sort D, Pujadas R, Rosell F (2005). Evaluation of a home-based intervention in heart failure patients. Results of a randomized study. REVISTA ESPANOLA DE CARDIOLOGIA, 58(6), 618-625. Author URL.

Rebollo P, Valderas JM, Ortega F (2005). Evolución en España de los impedimentos descritos para la utilización, en la práctica clínica, de las mediciones del estado de salud percibido. Medicina Clínica, 125(18), 703-705.

Valderas JM, Ferrer M, Alonso J (2005). Health-related quality of life instruments and other patient-reported outcomes. Medicina Clinica, 125(SUPPL. 1), 56-60. Abstract.

María Valderas J, Ferrer M, Alonso J (2005). Instrumentos de medida de calidad de vida relacionada con la salud y de otros resultados percibidos por los pacientes. Medicina Clínica, 125, 56-60.

Antoñanzas F, Rodríguez R, Antonio Sacristán J, Illa R (2005). Los medicamentos en la Unión Europea: el tándem comercio-salud. Gaceta Sanitaria, 19(2), 151-167.

Valderas JM, Rue M, Guyatt G, Alonso J (2005). The impact of the VF-14 index, a perceived visual function measure, in the routine management of cataract patients. Quality of Life Research, 14(7), 1743-1753.

Valderas JM, Ferrer M, Alonso J (2005). [Health-related quality of life instruments and other patient-reported outcomes]. Med Clin (Barc), 125 Suppl 1, 56-60. Abstract. Author URL.

Vilagut G, Ferrer M, Rajmil L, Rebollo P, Permanyer-Miralda G, Quintana JM, Santed R, Valderas JM, Ribera A, Domingo-Salvany A, et al (2005). [The Spanish version of the Short Form 36 Health Survey: a decade of experience and new developments]. Gac Sanit, 19(2), 135-150. Abstract. Author URL.

Sampietro-Colom L, Espallargues M, Reina MD, Marsó E, Valderas JM, Estrada MD (2004). Citizen's opinions, experiences and perceptions around cataract and hip and knee replacement surgical waiting lists. Atencion Primaria, 33(2), 84-94. Abstract.

Valderas J, Alonso J, Prieto L, Espallargues M, Castells X (2004). Content-based interpretation aids for health-related quality of life measures in clinical practice. An example for the visual function index (VF-14). Quality of Life Research, 13(1), 35-44.

Sampietro-Colom L, Espallargues M, Reina M, Marsó E, Valderas J, Estrada M (2004). Opiniones, vivencias y percepciones de los ciudadanos en torno a las listas de espera para cirugía electiva de catarata y artroplastia de cadera y rodilla. Atención Primaria, 33(2), 86-94.

Valderas Martínez JM, Ferrer Menduiña X (2004). The Difficult Measurement of Inhalation Technique [1]. Atencion Primaria, 33(4).

Sampietro-Colom L, Espallargues M, Reina MD, Marsó E, Valderas JM, Estrada MD (2004). [Citizens opinions, experiences and perceptions about waiting lists for elective cataract surgery and hip and knee replacement. ]. Aten Primaria, 33(2), 86-94. Abstract. Author URL.

Valderas Martínez JM, Ferrer Menduiña X (2004). [The difficult measurement of inhalation technique]. Aten Primaria, 33(4). Author URL.

Espallargues M, Valderas JM, Alonso J (2000). Provision of Feedback on Perceived Health Status to Health Care Professionals. Medical Care, 38(2), 175-186.

Valderas JM, Espallargues M, Alonso J (2000). Provision of feedback on perceived health status to health care professionals - Response. MEDICAL CARE, 38(8), 878-879. Author URL.

Conferences

Palmer K, Marengoni A, Forjaz MJ, Jureviciene E, Laatikainen T, Mammarella F, Muth C, Navickas R, Prados-Torres A, Rijken M, et al (2018). Multimorbidity care model: Recommendations from the consensus meeting of the Joint Action on Chronic Diseases and Promoting Healthy Ageing across the Life Cycle (JA-CHRODIS). Abstract.

Klapproth CM, Leplege A, Gibbons C, Coste J, Valderas JM, Rose M, Fischer F (2017). PREDICTING EQ-5D INDEX SCORES FROM PROMIS PROFILE 29 IN THE UNITED KINGDOM, FRANCE, AND GERMANY. Author URL.

Gibbons C, Valderas JM, Skevington SM (2016). Adaptive tests for long term conditions (ATLanTiC): supporting patient centred care for patients with long term conditions. Author URL.

Gangannagaripalli J, Porter I, Bramwell C, Evans J, Lopez JRG, Valderas JM (2016). Estimating minimum important difference (MID) for chronic disease-specific patient reported outcome measures (PROMs): a systematic review. Author URL.

Porter I, Gangannagaripalli J, Bramwell C, Valderas JM (2016). Integrating Patient Reported Outcome Measures (PROMs) into routine primary care for patients with multimorbidity: a feasibility study. Author URL.

Porter I, Valderas JM (2016). Patient reported outcomes (PROMs) based recommendation in clinical guidance for the management of chronic conditions in the United Kingdom. Author URL.

Porter I, Evans P, Valderas JM (2016). Routine individualized PRO feedback for the management of patients with multimorbidity in primary care: a pilot study in General Practice in England. Author URL.

Valderas JM, Kotzeva A, Alonso J (2010). Assessing the impact of routinely measuring patient-reported outcomes in clinical practice: critical appraisal of 34 randomized clinical trials. Author URL.

Garcia-Duran Huet M, Ferrer M, Herdman MJ, Ignacio Arraras J, Escobar A, Garcia-Altes A, Lucas R, Ochoa S, Permanyer G, Quintana JM, et al (2010). BiblioPRO: online library of PRO instruments in Spanish. Author URL.

Valderas JP, Irribarra V, Moreno M, Liberona Y, Acosta AM, Rubio L, De La Cruz R, Yolito M, Escalona M, Perez G, et al (2008). Different effects of roux-en-y gastric bypass (RGYB), sleeve gastrectomy (SG), and medical treatment (MED) of obesity on PYY, hunger and satiety, for similar magnitudes of weight loss: a preliminary report. Author URL.

Perez S, Losada G, Piqueras M, Vila MA, Dalfo A, Valderas JM (2003). Diagnosis and management of hipertension in primary care: Difference between intervention. Author URL.

Valderas JM, Alonso J, Prieto L, Valderas JM (2000). Assessing the psychometric properties of the visual function index VF-14. Author URL.

Reports

Valderas Martinez JM, Ricci-Cabello N, Prasopa-Plazier N, Wensing M, Santana MJ, Kaitiritimba R, Vazquez Curiel E, Murphy M (2016). Patient Engagement: WHO Technical Series on Safer Primary Care. World Health Organisation, Geneva, World Health Organisation. 25 pages. Full text.

Publications by year

In Press

Close J, Valderas JM, Byng R, Britten N, Lloyd H (In Press). Adapting QOF to focus on wellbeing and health. BMJ, 359 Author URL.

Abstract. Author URL. Full text.

Abstract. Author URL.

Abstract. Author URL. Full text.

2018

Abstract. Author URL.

Abstract. Author URL. Full text.

2017

Abstract. Author URL. Full text.

Abstract. Author URL.

Klapproth CM, Leplege A, Gibbons C, Coste J, Valderas JM, Rose M, Fischer F (2017). PREDICTING EQ-5D INDEX SCORES FROM PROMIS PROFILE 29 IN THE UNITED KINGDOM, FRANCE, AND GERMANY. Author URL.

2016

Gibbons C, Valderas JM, Skevington SM (2016). Adaptive tests for long term conditions (ATLanTiC): supporting patient centred care for patients with long term conditions. Author URL.

Stevens S, Valderas JM, Doran T, Perera R, Kontopantelis E (2016). Analysing indicators of performance, satisfaction, or safety using empirical logit transformation. BMJ, 352 Author URL.

Gibbons C, Bower P, Lovell K, Valderas J, Skevington S (2016). Electronic Quality of Life Assessment Using Computer-Adaptive Testing. Journal of Medical Internet Research, 18(9), e240-e240.

Porter I, Valderas JM (2016). Patient reported outcomes (PROMs) based recommendation in clinical guidance for the management of chronic conditions in the United Kingdom. Author URL.

2015

Abstract. Author URL. Full text.

Valderas JM (2015). Multimorbidity, not a health condition or complexity by another name. Eur J Gen Pract, 21(4), 213-214. Author URL.

Porter I, Valderas JM (2015). Use of PROs in clinical guidance for the management of chronic conditions in primary care in the United Kingdom. QUALITY OF LIFE RESEARCH, 24, 75-76. Author URL.

2014

O′Neill B, Gonçalves D, Ricci-Cabello I, Ziebland S, Valderas J (2014). An Overview of Self-Administered Health Literacy Instruments. PLoS ONE, 9(12), e109110-e109110.

Abstract. Author URL. Full text.

2013

Valderas JM (2013). Getting impatient about person-centred health care. Eur J Gen Pract, 19(3), 141-142. Author URL.

Valderas JM (2013). Increasing clinical, community, and patient-centered health research for preventing and managing multimorbidity. J Comorb, 3(Spec Issue), 41-44. Abstract. Author URL.

2012

Goncalves DC, Ricci-Cabello I, Valderas JM (2012). Identification and classification of individualized patient-reported outcome measures. QUALITY OF LIFE RESEARCH, 21, 113-114. Author URL.

2011

Pueyo M, Baranda L, Valderas J, Starfield B, Rajmil L (2011). Papel del pediatra de atención primaria y coordinación con atención especializada. Anales de Pediatría, 75(4), 247-252.

Valderas JM, Mercer SW, Fortin M (2011). Research on patients with multiple health conditions: different constructs, different views, one voice. J Comorb, 1, 1-3. Author URL.

2010

Reeves D, Doran T, Valderas JM, Kontopantelis E, Trueman P, Sutton M, Campbell S, Lester H (2010). How to identify when a performance indicator has run its course. BMJ, 340 Author URL.

2009

Valderas JM (2009). Identifying studies in Spanish population in PubMed. GACETA SANITARIA, 23(1), 82-82. Author URL.

2008

Valderas JM, Alonso J, Guyatt GH (2008). Measuring patient-reported outcomes: moving from clinical trials into clinical practice. MEDICAL JOURNAL OF AUSTRALIA, 189(2), 93-94. Author URL.

Valderas JM, Alonso J (2008). Patient reported outcome measures: a model-based classification system for research and clinical practice. Qual Life Res, 17(9), 1125-1135. Abstract. Author URL.

Valderas JM (2008). Treatment intensification does not always lead to better quality of care in patients with hypertension. ANNALS OF INTERNAL MEDICINE, 149(5), 362-362. Author URL.

2007