Jose M Valderas

Bio: Jose M Valderas is an academic researcher from University of Exeter. The author has contributed to research in topics: Health care & Population. The author has an hindex of 48, co-authored 213 publications receiving 11493 citations. Previous affiliations of Jose M Valderas include University of Oxford & London School of Economics and Political Science.

Defining Comorbidity: Implications for Understanding Health and Health Services

Abstract: Comorbidity is associated with worse health outcomes, more complex clinical management, and increased health care costs. There is no agreement, however, on the meaning of the term, and related constructs, such as multimorbidity, morbidity burden, and patient complexity, are not well conceptualized. In this article, we review definitions of comorbidity and their relationship to related constructs. We show that the value of a given construct lies in its ability to explain a particular phenomenon of interest within the domains of (1) clinical care, (2) epidemiology, or (3) health services planning and financing. Mechanisms that may underlie the coexistence of 2 or more conditions in a patient (direct causation, associated risk factors, heterogeneity, independence) are examined, and the implications for clinical care considered. We conclude that the more precise use of constructs, as proposed in this article, would lead to improved research into the phenomenon of ill health in clinical care, epidemiology, and health services.

Prevalence, Determinants and Patterns of Multimorbidity in Primary Care: A Systematic Review of Observational Studies

Abstract: 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.

Epidemiology and impact of multimorbidity in primary care: a retrospective cohort study

Abstract: Background In developed countries, primary health care increasingly involves the care of patients with multiple chronic conditions, referred to as multimorbidity. Aim To describe the epidemiology of multimorbidity and relationships between multimorbidity and primary care consultation rates and continuity of care. Design of study Retrospective cohort study. Setting Random sample of 99 997 people aged 18 years or over registered with 182 general practices in England contributing data to the General Practice Research Database. Method Multimorbidity was defined using two approaches: people with multiple chronic conditions included in the Quality and Outcomes Framework, and people identified using the Johns Hopkins University Adjusted Clinical Groups (ACG®) Case-Mix System. The determinants of multimorbidity (age, sex, area deprivation) and relationships with consultation rate and continuity of care were examined using regression models. Results Sixteen per cent of patients had more than one chronic condition included in the Quality and Outcomes Framework, but these people accounted for 32% of all consultations. Using the wider ACG list of conditions, 58% of people had multimorbidity and they accounted for 78% of consultations. Multimorbidity was strongly related to age and deprivation. People with multimorbidity had higher consultation rates and less continuity of care compared with people without multimorbidity. Conclusion Multimorbidity is common in the population and most consultations in primary care involve people with multimorbidity. These people are less likely to receive continuity of care, although they may be more likely to gain from it.

The impact of measuring patient-reported outcomes in clinical practice: a systematic review of the literature.

Abstract: The purpose of this paper is to summarize the best evidence regarding the impact of providing patient-reported outcomes (PRO) information to health care professionals in daily clinical practice. Systematic review of randomized clinical trials (Medline, Cochrane Library; reference lists of previous systematic reviews; and requests to authors and experts in the field). Out of 1,861 identified references published between 1978 and 2007, 34 articles corresponding to 28 original studies proved eligible. Most trials (19) were conducted in primary care settings performed in the USA (21) and assessed adult patients (25). Information provided to professionals included generic health status (10), mental health (14), and other (6). Most studies suffered from methodologic limitations, including analysis that did not correspond with the unit of allocation. In most trials, the impact of PRO was limited. Fifteen of 23 studies (65%) measuring process of care observed at least one significant result favoring the intervention, as did eight of 17 (47%) that measured outcomes of care. Methodological concerns limit the strength of inference regarding the impact of providing PRO information to clinicians. Results suggest great heterogeneity of impact; contexts and interventions that will yield important benefits remain to be clearly defined.

2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS).

Abstract: Supplementary Table 9, column 'Edoxaban', row 'eGFR category', '95 mL/min' (page 15). The cell should be coloured green instead of yellow. It should also read "60 mg"instead of "60 mg (use with caution in 'supranormal' renal function)."In the above-indicated cell, a footnote has also been added to state: "Edoxaban should be used in patients with high creatinine clearance only after a careful evaluation of the individual thromboembolic and bleeding risk."Supplementary Table 9, column 'Edoxaban', row 'Dose reduction in selected patients' (page 16). The cell should read "Edoxaban 60 mg reduced to 30 mg once daily if any of the following: creatinine clearance 15-50 mL/min, body weight <60 kg, concomitant use of dronedarone, erythromycin, ciclosporine or ketokonazole"instead of "Edoxaban 60 mg reduced to 30 mg once daily, and edoxaban 30 mg reduced to 15mg once daily, if any of the following: creatinine clearance of 30-50 mL/min, body weight <60 kg, concomitant us of verapamil or quinidine or dronedarone."

Standards of Medical Care in Diabetes—2012

Abstract: D iabetes mellitus is a chronic illness that requires continuing medical care and ongoing patient self-management education and support to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payers, and other interested individuals with the components of diabetes care, general treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. Specifically titled sections of the standards address children with diabetes, pregnant women, and people with prediabetes. These standards are not intended to preclude clinical judgment or more extensive evaluation and management of the patient by other specialists as needed. For more detailed information about management of diabetes, refer to references 1–3. The recommendations included are screening, diagnostic, and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A large number of these interventions have been shown to be cost-effective (4). A grading system (Table 1), developed by the American Diabetes Association (ADA) andmodeled after existingmethods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E. These standards of care are revised annually by the ADA’s multidisciplinary Professional Practice Committee, incorporating new evidence. For the current revision, committee members systematically searched Medline for human studies related to each subsection and published since 1 January 2010. Recommendations (bulleted at the beginning of each subsection and also listed in the “Executive Summary: Standards of Medical Care in Diabetesd2012”) were revised based on new evidence or, in some cases, to clarify the prior recommendation or match the strength of the wording to the strength of the evidence. A table linking the changes in recommendations to new evidence can be reviewed at http:// professional.diabetes.org/CPR_Search. aspx. Subsequently, as is the case for all Position Statements, the standards of care were reviewed and approved by the ExecutiveCommittee of ADA’s Board ofDirectors, which includes health care professionals, scientists, and lay people. Feedback from the larger clinical community was valuable for the 2012 revision of the standards. Readers who wish to comment on the “Standards of Medical Care in Diabetesd2012” are invited to do so at http://professional.diabetes.org/ CPR_Search.aspx. Members of the Professional Practice Committee disclose all potential financial conflicts of interest with industry. These disclosures were discussed at the onset of the standards revisionmeeting. Members of the committee, their employer, and their disclosed conflicts of interest are listed in the “Professional PracticeCommitteeMembers” table (see pg. S109). The AmericanDiabetes Association funds development of the standards and all its position statements out of its general revenues and does not utilize industry support for these purposes.

Network Medicine: A Network-Based Approach to Human Disease

Abstract: Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular and intercellular network that links tissue and organ systems. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships among apparently distinct (patho)phenotypes. Advances in this direction are essential for identifying new disease genes, for uncovering the biological significance of disease-associated mutations identified by genome-wide association studies and full-genome sequencing, and for identifying drug targets and biomarkers for complex diseases.

Multiple Imputation for Nonresponse in Surveys

Abstract: 25. Multiple Imputation for Nonresponse in Surveys. By D. B. Rubin. ISBN 0 471 08705 X. Wiley, Chichester, 1987. 258 pp. £30.25.