Skip to main content

Main menu

  • Home
  • Current Issue
  • Content
    • Current Issue
    • Early Access
    • Multimedia
    • Podcast
    • Collections
    • Past Issues
    • Articles by Subject
    • Articles by Type
    • Supplements
    • Plain Language Summaries
    • Calls for Papers
  • Info for
    • Authors
    • Reviewers
    • Job Seekers
    • Media
  • About
    • Annals of Family Medicine
    • Editorial Staff & Boards
    • Sponsoring Organizations
    • Copyrights & Permissions
    • Announcements
  • Engage
    • Engage
    • e-Letters (Comments)
    • Subscribe
    • Podcast
    • E-mail Alerts
    • Journal Club
    • RSS
    • Annals Forum (Archive)
  • Contact
    • Contact Us
  • Careers

User menu

  • My alerts

Search

  • Advanced search
Annals of Family Medicine
  • My alerts
Annals of Family Medicine

Advanced Search

  • Home
  • Current Issue
  • Content
    • Current Issue
    • Early Access
    • Multimedia
    • Podcast
    • Collections
    • Past Issues
    • Articles by Subject
    • Articles by Type
    • Supplements
    • Plain Language Summaries
    • Calls for Papers
  • Info for
    • Authors
    • Reviewers
    • Job Seekers
    • Media
  • About
    • Annals of Family Medicine
    • Editorial Staff & Boards
    • Sponsoring Organizations
    • Copyrights & Permissions
    • Announcements
  • Engage
    • Engage
    • e-Letters (Comments)
    • Subscribe
    • Podcast
    • E-mail Alerts
    • Journal Club
    • RSS
    • Annals Forum (Archive)
  • Contact
    • Contact Us
  • Careers
  • Follow annalsfm on Twitter
  • Visit annalsfm on Facebook
Research ArticleTheory

Defining Comorbidity: Implications for Understanding Health and Health Services

Jose M. Valderas, Barbara Starfield, Bonnie Sibbald, Chris Salisbury and Martin Roland
The Annals of Family Medicine July 2009, 7 (4) 357-363; DOI: https://doi.org/10.1370/afm.983
Jose M. Valderas
MD, PhD, MPH
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Barbara Starfield
MD, MPH
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Bonnie Sibbald
MSc, PhD
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Chris Salisbury
MB, ChB, MSc, FRCGP
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Martin Roland
CBE, DM, FRCGP, FRCP, FMedSci
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • eLetters
  • Info & Metrics
  • PDF
Loading

Published eLetters

If you would like to comment on this article, click on Submit a Response to This article, below. We welcome your input.

Submit a Response to This Article
Compose eLetter

More information about text formats

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.
Author Information
First or given name, e.g. 'Peter'.
Your last, or family, name, e.g. 'MacMoody'.
Your email address, e.g. higgs-boson@gmail.com
Your role and/or occupation, e.g. 'Orthopedic Surgeon'.
Your organization or institution (if applicable), e.g. 'Royal Free Hospital'.
Statement of Competing Interests
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Image CAPTCHA
Enter the characters shown in the image.

Vertical Tabs

Jump to comment:

  • Defining multiple morbidity
    Martin C Gulliford
    Published on: 20 August 2009
  • DEFINING COMORBIDITY AND UNDERSTANDING PATIENTS�NEEDS
    Hilde Luijks
    Published on: 18 August 2009
  • Faultlines between co-morbidity and multimorbidity
    Tom O'Dowd
    Published on: 19 July 2009
  • A step in the right direction
    Martin Fortin
    Published on: 17 July 2009
  • Published on: (20 August 2009)
    Page navigation anchor for Defining multiple morbidity
    Defining multiple morbidity
    • Martin C Gulliford, London UK

    Dr Jose M Valderas and colleagues present a thoughtful analysis of the concepts of comorbidity and multiple morbidity. They demonstrate several difficulties that impede progress towards a concise system of measurement. Two additional points may be made:

    First, the health care system has an important role in defining multiple morbidity in its clients. In the abstract of the paper, multiple morbidity is defined a...

    Show More

    Dr Jose M Valderas and colleagues present a thoughtful analysis of the concepts of comorbidity and multiple morbidity. They demonstrate several difficulties that impede progress towards a concise system of measurement. Two additional points may be made:

    First, the health care system has an important role in defining multiple morbidity in its clients. In the abstract of the paper, multiple morbidity is defined as the 'coexistence of two or more conditions in a patient'. Conditions are acknowledged to include 'diseases, disorders, conditions, illnesses or health problems' but later sections of the paper refer to co-existent diseases as characterising multiple morbidity. Diseases are defined by diagnoses that may only be conferred on individuals who are able to access medical care. Accessing medical care also leads to the identification and treatment of risk factors such as hypertension and hypercholesterolaemia but it is unclear whether these, and related risk states such as prediabetes, prehypertension or components of the metabolic syndrome, merit classification as 'morbidities'(1). Meanwhile, the perceived relevance of patient-experienced problems, such as back pain or tinnitus, is unclear.

    Secondly, current approaches to defining multiple morbidity commonly utilise counts of the numbers medical diagnoses in each patient (see for example, Fortin et al (2), Figure 1). After a lifetime of interaction with the health care system, most individuals have accumulated a number of diagnoses of long-term conditions, some of which may have trivial present impact. The reviewers point out that the severity, as well as the number of conditions, is an essential component of a useful definition of multiple morbidity. This is exemplified in the scoring of the Cumulative Illness Rating Scale(3) in which conditions affecting each bodily system are rated on a scale where zero represents 'no problem affecting that system' and four represents an 'extremely severe problem, and/or immediate treatment required, and/or organ failure, and/or severe functional impairment'. The Charlson Index(4) is also widely used, but this was developed to predict the one-year mortality of hospital inpatients and may be less suitable for community studies(5). More generally, the meaning of 'severity' and the criteria to be used in defining the severity of co- existing conditions in ways that are relevant to different contexts require clarification.

    Martin Gulliford King's College London, Department of Public Health Sciences

    References
    (1) Starfield B, Hyde J, Gervas J, Heath I. The concept of prevention: a good idea gone astray? Journal of Epidemiology and Community Health 2008; 62:580-583.
    (2) Fortin M, Bravo G, Hudon C, Vanasse A, Lapointe L. Prevalence of Multimorbidity Among Adults Seen in Family Practice. Ann Fam Med 2005; 3:223-228.
    (3) Hudon C, Fortin M, Soubhi H. Abbreviated guidelines for scoring the Cumulative Illness Rating Scale (CIRS) in family practice. Journal of Clinical Epidemiology 2007; 60:212.
    (4) Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. Journal of Chronic Diseases 1987; 40:373-383.
    (5) Harse JD, Holman CD. Charlson's Index was a poor predictor of quality of life outcomes in a study of patients following joint replacement surgery. Journal of Clinical Epidemiology 2005; 58:1142-1149.

    Competing interests:   None declared

    Show Less
    Competing Interests: None declared.
  • Published on: (18 August 2009)
    Page navigation anchor for DEFINING COMORBIDITY AND UNDERSTANDING PATIENTS�NEEDS
    DEFINING COMORBIDITY AND UNDERSTANDING PATIENTS�NEEDS
    • Hilde Luijks, Nijmegen, The Netherlands
    • Other Contributors:

    In ageing populations, there is an increase in the number of patients with more than one important health problem present at the same time: comorbidity or multi morbidity. As a consequence, comorbidity has a profound impact on patient care, and on the planning and structuring of health care services. Valderas et al [1] analyzed the literature of comorbidity and concluded that the concepts and definition of what comorbidi...

    Show More

    In ageing populations, there is an increase in the number of patients with more than one important health problem present at the same time: comorbidity or multi morbidity. As a consequence, comorbidity has a profound impact on patient care, and on the planning and structuring of health care services. Valderas et al [1] analyzed the literature of comorbidity and concluded that the concepts and definition of what comorbidity is, depends on the context in which it is encountered. They distinguish in this respect between clinical care, epidemiology and health services planning.

    In the primary care population and under patients encountered in family practice, a large minority are under treatment for two or more chronic diseases [2, 3]. Currently, in the support of patient care and clinical decisions, a disease-specific approach dominates, with condition- specified quality and outcome criteria [4]. In this approach, ‘comorbidity’ heralds particular facts that may force clinicians to deviate from their disease specific delineation [5]. With ‘comorbidity’ a rule rather than an exception, it is in our view no longer acceptable to apply for patients with more than one chronic disease an ‘opt-out of standard practice’ approach. For that reason, it is important to develop a better understanding of comorbidity, as a universal patient characteristic. This common ground is what would lend importance of comorbidity in the context of patient care, epidemiology and health care services [1].

    A more in-depth exploration of patient care and the underlying clinical decision making may help to get more insight in the nature of comorbidity. Although the research evidence of comorbidity is limited, practitioners demonstrate a systematic difference in their treatment of patients with and without comorbidity – and practice appears to be well ahead of science. An interesting example in this respect is provided by a recent study in the UK of the management of patients with depression [6]. Family physicians (FP) arranged for more care, when the depression was more severe. But this needs dependent approach was less clear in patients with chronic physical comorbid conditions, who in general received less interventions than patients with depression as their only condition. An interpretation of these findings could be that FPs are reluctant to add-on interventions [7]. This is in particular the case in prescribing multiple drugs because of patient compliance and potential interactions [5]. Generic interventions such as empowerment and lifestyle changes may be more attractive because they may treat more than one condition at the same time [8].

    Next to the health problem as such, FPs explore in their encounters patients’ preferences, interests and expectations around their health problems. These patients’ preferences may often conflict with or be incompatible to, plain disease-centered reasoning and this will influence FPs’ clinical decision. Everyday practical examples are the aversion of medication, priority for pain reduction over causal treatment or preference for a non-demanding , non-embarrassing therapy. In reconciling the implications of disease status and patient preferences, the true FP decisions are made. And FPs have a professional opinion on what the disease status demands as well as what patients prefer. The depression study as a case in point stresses the need of gaining better insight in the process in of decision making . Exploration of the practical experience should focus on the aims and objectives patients and FPs have in seeking and prescribing care. This would change the determination of patients’ needs beyond the disease perspective to a patient, or person, centred approach.

    Critical is the notion that a person centered approach is more than just pleasing the patient or merely prescribing his or her expressed preferences. Expectations and perceived needs are formed from patients’ and families’ medical life experience [9] – as different consecutive, or as co-existing, episodes of illness experienced. This is the experience they bring to the practice, and the ‘healing relation’ between patient and FP [10] is determined by the FPs’ responsiveness. That is how, in our view, comorbidity shapes the process and outcome of care. It is time to come to a much better understanding of how the different disease scripts and the individual context interact into clinical decisions that flow from it – on patient care, for the provision of health care services and on the epidemiology.

    References 1. Valderas JM, Starfield B, Sibbold B, Salisbury C, Roland M. Defining Comorbidity: Implications for Understanding Health and Health Systems. AnnFamMed 2009; 7: 357-363.
    2. Weel, C. van. Chronic diseases in general practice: the longitudinal dimension. Eur J Gen Pract 1996 2: 17-21.
    3. Weel C van, Schellevis FG. Comorbidity and guidelines: conflicting interests. Lancet 2006;367:550-1.
    4. Department of Health. Quality and Outcomes Framework. http://www.dh.gov.uk/en/Healthcare/Primarycare/Primarycarecontracting/QOF/index.htm (accessed August 18, 2009)
    5. Boyd CM, Darer J, Boult C, Fried LP, Boult L, Wu AW. Clinical practice guidelines and quality of care for older patients with multiple comorbid diseases: implications for pay for performance JAMA 2005;294:716-24
    6. Kendrick T, Dowrick C, McBride A, Howe A, Clarke P, Maisey S, et al. Management of depression in UK general practice in relation to scores on depression severity questionnaires: analysis of medical record data. BMJ 2009;338:b750
    7. Van Weel C, Van Weel-Baumgarten E, Van Rijswijk E. Treatment of depression in primary care. BMJ 2009;338:b934.
    8. Dijurgeit U, Kruse J, Schmitz N, Stückenschneider P, Sawicki PT. A time -limited, problem-orientated psychotherapeutic intervention in type 1 diabetic patients with complications: a randomized controlled trial. Diabet Med 2002;19:814-21.
    9. Huygen FJA. Family Medicine – the medical life history of families. Nijmegen, Dekker en van der Vegt, 1978.
    10. McWhinney IR, Freeman T. Family Medicine. Oxford, Oxford University Press, 2009, 3rd edition.

    Competing interests:   None declared

    Show Less
    Competing Interests: None declared.
  • Published on: (19 July 2009)
    Page navigation anchor for Faultlines between co-morbidity and multimorbidity
    Faultlines between co-morbidity and multimorbidity
    • Tom O'Dowd, Dublin, Ireland
    • Other Contributors:

    Establishing A Faultline Between Co-Morbidity and Multi-Morbidity

    Valderas et al (Annals of Family Medicine July/August 2009) point out that there is no general agreement on the meaning of the term ‘co-morbidity’ and related constructs such as multi-morbidity. Clinical practice is fraught with definitional difficulties and it is important, especially in the area of international research, that we have a strong conce...

    Show More

    Establishing A Faultline Between Co-Morbidity and Multi-Morbidity

    Valderas et al (Annals of Family Medicine July/August 2009) point out that there is no general agreement on the meaning of the term ‘co-morbidity’ and related constructs such as multi-morbidity. Clinical practice is fraught with definitional difficulties and it is important, especially in the area of international research, that we have a strong conceptual approach and good working definitions for enrolment into managed care programmes and clinical trials.

    The current interest in multimorbidity in primary care represents a focus for academics and researchers anxious to contribute at population and clinical levels. Valderas and colleagues provide an important insight in pointing out that co-morbidity has an emphasis on an index disease which is particularly useful in specialist care which has a strong orientation towards a single disease, or a single diseased system. Multimorbidity on the other hand focuses on the patient as a whole without emphasis on any single condition.

    This insight represents an important difference between specialist and primary care in the approach to chronic disease management. Much of the enthusiasm for multimorbidity in primary care research is that it echoes the reality of clinical practice. In the July issue of the Annals, Stange and Ferrer, point out that primary care is associated with apparently poorer quality of care for individual diseases but paradoxically with similar functional outcomes, better quality health and greater equity for communities and populations than specialist care. They call it the primary care paradox. Is it that ‘good enough’ primary care makes all the difference? The faultline between co-morbidity and multimorbidity is an important one.

    Co-morbidity is intuitive, predictable and can aggregate specialists and technology around it. It can also, to paraphrase Julian Tudor Hart, remain unsullied by community and societal concerns. Multi-morbidity is the reality of clinical life in primary care and the definitional challenges posed by co-morbidity pale are fewer when it comes to multimorbidity. It does however represent intellectual and professional challenges for us to place our mark on the chronic illness map. It provides an opportunity for primary care to outline the scope and scale of our role to payers and patients alike.

    The paper by Valderas et al demonstrates that much more work needs to be done in developing the patient perspective in terms of social, physical and psychological constraints. Outcome measurement is more of a challenge in multimorbidity than in co-morbidity where at least specific diseases can be the focus. Co-morbid conditions share aetiological or risk factors whereas multimorbidity incorporates additional management challenges such as the treatment for one condition exacerbating another.

    We are nonetheless on the way in primary care in explaining the potential of cost-effective, equitable, competent, clinical care for common chronic diseases that affect the majority of our patients.

    Tom O'Dowd & Susan Smith
    Trinity College, Dublin

    Competing interests:   Engaged in research on multimorbidity

    Show Less
    Competing Interests: None declared.
  • Published on: (17 July 2009)
    Page navigation anchor for A step in the right direction
    A step in the right direction
    • Martin Fortin, Saguenay, Canada

    Thank you for this work around the concepts of comorbidity and multimorbidity. This is really a step in the right direction. I believe like you that the lack of a clear consensual definition and measure of comorbidity/multimorbidity and related constructs is an impediment to research and it is particularly important in primary care where the prevalence of multimorbidity is so high in the attending population.1 The conce...

    Show More

    Thank you for this work around the concepts of comorbidity and multimorbidity. This is really a step in the right direction. I believe like you that the lack of a clear consensual definition and measure of comorbidity/multimorbidity and related constructs is an impediment to research and it is particularly important in primary care where the prevalence of multimorbidity is so high in the attending population.1 The concepts still need a bit of disentangling but you did a great work. Several points came to my mind while reading your paper and I will summarize them in the following paragraphs.

    Nature of health conditions. There is still no consensus about what ought to be included in a count of chronic diseases. On an epidemiological perspective, the number of diagnoses accounted for influences enormously the results of prevalence studies. Should we rely on the World Health Organization definition of a “chronic disease” or on a specific classification? How do we handle multiple diagnoses within the same system? Should related conditions be counted separately of be considered as a whole? Anxiety, depression and substance abuse: one mental illness or three? Angina pectoris, previous myocardial infarction, atrial fibrillation and heart failure: one cardiovascular disease or four? No clear consensus on that. How about conditions considered as risk factors but requiring specific management like hyperlipidemia, obesity? Those examples demonstrate the importance of defining precisely the intention behind the simple count of chronic conditions. So I agree with you that from an epidemiological and public health perspective, the measurement approaches should be based on counts but it’s really important to define precisely what is to be counted and for what purpose.

    Severity. I was surprise not to see “severity” as an important construct in the figure 2. Severity may be conceptualized at the disease level or at the patient level. At the disease level, it’s part of the disease process. An example would be a mild hypertension that only requires a small dose of diuretic compared with a more severe hypertension requiring 3 different drugs. At the patient level, it’s also part of the disease process but it’s linked to the impact on function or other outcomes. An example would be mild asthma versus severe asthma with important limitations. You acknowledged that severity contributes to the disease burden and patient’s complexity. In this regard, it could have been included in the figure 2. Maybe instead of frailty that is more specific for elderly and could have been included within the “other health -related individual attributes”.

    This article makes an important contribution to the research field. It clarifies many issues. As the research is moving forward, the attributes and limits of the constructs will have to be adapted and I agree with you that future research would benefit from using explicit definitions of the constructs in conjonction with established classification systems to favour generalizability and precision.

    1. Fortin M, Bravo G, Hudon C, Vanasse A, Lapointe L. Prevalence of multimorbidity among adults seen in family practice. Ann Fam Med 2005;3:223-8.

    Competing interests:   None declared

    Show Less
    Competing Interests: None declared.
PreviousNext
Back to top

In this issue

The Annals of Family Medicine: 7 (4)
The Annals of Family Medicine: 7 (4)
Vol. 7, Issue 4
1 Jul 2009
  • Table of Contents
  • Index by author
  • In Brief
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on Annals of Family Medicine.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Defining Comorbidity: Implications for Understanding Health and Health Services
(Your Name) has sent you a message from Annals of Family Medicine
(Your Name) thought you would like to see the Annals of Family Medicine web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
7 + 5 =
Solve this simple math problem and enter the result. E.g. for 1+3, enter 4.
Citation Tools
Defining Comorbidity: Implications for Understanding Health and Health Services
Jose M. Valderas, Barbara Starfield, Bonnie Sibbald, Chris Salisbury, Martin Roland
The Annals of Family Medicine Jul 2009, 7 (4) 357-363; DOI: 10.1370/afm.983

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Get Permissions
Share
Defining Comorbidity: Implications for Understanding Health and Health Services
Jose M. Valderas, Barbara Starfield, Bonnie Sibbald, Chris Salisbury, Martin Roland
The Annals of Family Medicine Jul 2009, 7 (4) 357-363; DOI: 10.1370/afm.983
Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • INTRODUCTION
    • REVIEWING THE CONCEPT OF COMORBIDITY
    • INTEGRATING THE DIFFERENT CONSTRUCTS
    • DIFFERENT DEFINITIONS FOR DIFFERING USES
    • RELATIONSHIPS BETWEEN COMORBID DISEASES
    • DISCUSSION
    • Footnotes
    • REFERENCES
  • Figures & Data
  • eLetters
  • Info & Metrics
  • PDF

Related Articles

  • PubMed
  • Google Scholar

Cited By...

  • Online media reporting of global mortality rates and causes: a content analysis
  • Deep learning predicts onset acceleration of 38 age-associated diseases from blood and body composition biomarkers in the UK Biobank
  • Proteomics signature of physical activity and risk of multimorbidity of cancer and cardiometabolic diseases
  • Leveraging primary health care data from Estonian Biobank to find novel genetic associations
  • Genesis of concurrent diseases: do diabetes mellitus and idiopathic pulmonary fibrosis have a direct relationship?
  • Sex-specific transcriptome similarity networks elucidate comorbidity relationships
  • Accounting for comorbidity in etiological research
  • Medical complexity in emergency and urgent care settings: a scoping review protocol
  • The first comorbidity networks in companion dogs in the Dog Aging Project
  • Cohort profile: the WHO Child Mortality Risk Stratification Multi-Country Pooled Cohort (WHO-CMRS) to identify predictors of mortality through early childhood
  • Methods for considering equality and equity implications in horizon scanning for medicines and healthcare innovations: a scoping review
  • Network-Based Analysis Identifies Targetable Pathways in Comorbid Type II Diabetes and Neuropsychiatric Disorders
  • COVID-19-Related Treatment Cancellations and Oncology Patients Psychological Health in Nigeria
  • Clinical dimensions of people with co-occurring obsessive-compulsive and related disorders and multiple sclerosis: a scoping review protocol
  • Lung cancer deaths (England 2001-2017)--comorbidities: a national population-based analysis
  • Cohort profile: The WHO Child Mortality Risk Stratification Multi-Country Pooled Cohort (WHO-CMRS) to identify predictors of mortality through early childhood
  • The Scope of Multimorbidity in Family Medicine: Identifying Age Patterns Across the Lifespan
  • Heritability and polygenic load for combined anxiety and depression
  • The role of the clinical pharmacist in the respiratory or sleep multidisciplinary team
  • Critically examining health complexity experienced by urban Indigenous peoples in Canada by exploring the factors that allow health complexity to persist: a qualitative study of Indigenous patients in Calgary, Alberta
  • Multiple long term conditions, multimorbidity, and co-morbidities: we should reconsider the terminology we use
  • Association between spinal and non-spinal health conditions reported in epidemiological studies: a scoping review protocol
  • hART: Deep Learning-Informed Lifespan Heart Failure Risk Trajectories
  • Multicentric validation of a Multimorbidity Adjusted Disability Score to stratify depression-related risks using temporal disease maps
  • Interactions between long-term ambient particle exposures and lifestyle on the prevalence of hypertension and diabetes: insight from a large community-based survey
  • Interactions between long-term ambient particle exposures and lifestyle on the prevalence of hypertension and diabetes: insight from a large community-based survey
  • Multimorbidity of cardiometabolic diseases: a cross-sectional study of patterns, clusters and associated risk factors in sub-Saharan Africa
  • A Novel Mouse Model of Chronic Primary Pain Conditions that Integrates Clinically Relevant Genetic and Environmental Factors
  • Who gets access to an interprofessional team-based primary care programme for patients with complex health and social needs? A cross-sectional analysis
  • Drug-Related Problems and associated factors among hospitalized pediatric patients at the University of Gondar Comprehensive and Specialized Hospital
  • Developing and validating a scoring system for measuring frailty in patients with hip fracture: a novel model for predicting short-term postoperative mortality
  • An eHealth self-management intervention for adults with chronic kidney disease, My Kidneys My Health: a mixed-methods study
  • Impact of multimorbidity on long-term outcomes in older adults with non-ST elevation acute coronary syndrome in the North East of England: a multi-centre cohort study of patients undergoing invasive care
  • Association of multimorbidity and physical activity among older adults in India: an analysis from the Longitudinal Ageing Survey of India (2017-2018)
  • Drug Contraindications in Comorbid Diseases: a Protein Interactome Perspective
  • netCRS: Network-based comorbidity risk score for prediction of myocardial infarction using biobank-scaled PheWAS data
  • Health status of individuals referred to first-line intervention for hip and knee osteoarthritis compared with the general population: an observational register-based study
  • Experiences engaging in a group-based physiotherapist-led exercise programme for adults living with HIV and complex multimorbidity: a qualitative study
  • Patient stratification reveals the molecular basis of disease comorbidities
  • An Explainable Artificial Intelligence Approach for Predicting Cardiovascular Outcomes using Electronic Health Records
  • A Poisson binomial based statistical testing framework for comprehensive comorbidity discovery across massive Electronic Health Record datasets
  • Risk of 30-day hospital readmission associated with medical conditions and drug regimens of polymedicated, older inpatients discharged home: a registry-based cohort study
  • Spoonful of honey or a gallon of vinegar? A conditional COVID-19 vaccination policy for front-line healthcare workers
  • What is the impact of multimorbidity on the risk of hospitalisation in older adults? A systematic review study protocol
  • Interaction of physical activity on the association of obesity-related measures with multimorbidity among older adults: a population-based cross-sectional study in India
  • Influencing factors and their relationships of risk perception and decision-making behaviour of polypharmacy in patients with chronic diseases: a qualitative descriptive study
  • Evaluating access to health and care services during lockdown by the COVID-19 survey in five UK national longitudinal studies
  • Inequality in access to health and care services during lockdown - Findings from the COVID-19 survey in five UK national longitudinal studies
  • Life-course burden of health deficits associates with later-life heart size and function in the 1946 British birth cohort
  • Multimorbidity patterns among COVID-19 deaths: considerations for a better medical practice
  • Prevalence of comorbidities and their associated factors in patients with type 2 diabetes at a tertiary care department in Ningbo, China: a cross-sectional study
  • The architecture of co-morbidity networks of physical and mental health conditions in military veterans
  • Improving continuity of care of patients with respiratory disease at hospital discharge
  • Effect of pre-existing conditions on bladder cancer stage at diagnosis: a cohort study using electronic primary care records in the UK
  • Comorbid disease drives short-term hospitalization outcomes in patients with multiple sclerosis
  • Impact of comorbidity on health outcome after a transport-related injury
  • Screening for comorbidities in COPD
  • Epidemiology of at-risk alcohol use and associated comorbidities of interest among community-dwelling older adults: a protocol for a systematic review
  • Optimising medication management for polymedicated home-dwelling older adults with multiple chronic conditions: a mixed-methods study protocol
  • Sensitivity and robustness of comorbidity network analysis
  • Soft clustering using real-world data for the identification of multimorbidity patterns in an elderly population: cross-sectional study in a Mediterranean population
  • 'Multimorbidity: an acceptable term for patients or time for a rebrand?
  • Genetic analyses of medication-use and implications for precision medicine
  • Comorbidities in the first 2 years after arthroscopic hip surgery: substantial increases in mental health disorders, chronic pain, substance abuse and cardiometabolic conditions
  • Use of latent class analysis to identify multimorbidity patterns and associated factors in Korean adults aged 50 years and older
  • Chromatin interactions and expression quantitative trait loci reveal genetic drivers of multimorbidities
  • Multimorbidity and healthcare utilization: A register-based study in Denmark
  • Predicting Incident Multimorbidity
  • Comparative analysis of methods for identifying multimorbidity patterns: a study of 'real-world data
  • Association between perceived stress, multimorbidity and primary care health services: a Danish population-based cohort study
  • Effectiveness of a complex intervention on Prioritising Multimedication in Multimorbidity (PRIMUM) in primary care: results of a pragmatic cluster randomised controlled trial
  • Factors associated with health literacy in multimorbid patients in primary care: a cross-sectional study in Switzerland
  • Impact of multimorbidity on healthcare professional task shifting potential in patients with type 2 diabetes in primary care: a French cross-sectional study
  • Identifying patient and practice characteristics associated with patient-reported experiences of safety problems and harm: a cross-sectional study using a multilevel modelling approach
  • Comorbidity and outcomes in traumatic brain injury: protocol for a systematic review on functional status and risk of death
  • Investigating asthma comorbidities: a systematic scoping review protocol
  • Understanding HIV-positive patients' preferences for healthcare services: a protocol for a discrete choice experiment
  • Recommendations for observational studies of comorbidity in multiple sclerosis
  • The challenge of comorbidity in clinical trials for multiple sclerosis
  • Inequalities in physical comorbidity: a longitudinal comparative cohort study of people with severe mental illness in the UK
  • Impact of the AYA HOPE Comorbidity Index on Assessing Health Care Service Needs and Health Status among Adolescents and Young Adults with Cancer
  • Multimorbidity and COPD Medication Receipt Among Medicaid Beneficiaries With Newly Diagnosed COPD
  • Impact of the Prevalence of Concordant and Discordant Conditions on the Quality of Diabetes Care in Family Practices in England
  • Ageing and the epidemiology of multimorbidity
  • Multimorbidity, disability, and mortality in community-dwelling older adults
  • Understanding the Context of Health for Persons With Multiple Chronic Conditions: Moving From What Is the Matter to What Matters
  • Causes and patterns of readmissions in patients with common comorbidities: retrospective cohort study
  • Multimorbidity in Patients Attending 2 Australian Primary Care Practices
  • Implications of comorbidity for primary care costs in the UK: a retrospective observational study
  • 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
  • Illness comorbidity as a biomarker?
  • Google Scholar

More in this TOC Section

  • Unhurried Conversations in Health Care Are More Important Than Ever: Identifying Key Communication Practices for Careful and Kind Care
  • Refining Vendor-Defined Measures to Accurately Quantify EHR Workload Outside Time Scheduled With Patients
  • Curricular Interventions in Medical Schools: Maximizing Community Engagement Through Communities of Practice
Show more Theory

Similar Articles

Subjects

  • Domains of illness & health:
    • Chronic illness
  • Other research types:
    • Health services
  • Other topics:
    • Multimorbidity

Content

  • Current Issue
  • Past Issues
  • Early Access
  • Plain-Language Summaries
  • Multimedia
  • Podcast
  • Articles by Type
  • Articles by Subject
  • Supplements
  • Calls for Papers

Info for

  • Authors
  • Reviewers
  • Job Seekers
  • Media

Engage

  • E-mail Alerts
  • e-Letters (Comments)
  • RSS
  • Journal Club
  • Submit a Manuscript
  • Subscribe
  • Family Medicine Careers

About

  • About Us
  • Editorial Board & Staff
  • Sponsoring Organizations
  • Copyrights & Permissions
  • Contact Us
  • eLetter/Comments Policy

© 2025 Annals of Family Medicine