CoChat
Sign Up
Cited by 225Chronic Disease Management StrategiesHealth Policy Implementation ScienceHealth, psychology, and well-being

The DOI matches its Crossref record; 102 of the 106 references it cites were found in a registry or an index.

Understanding the Context of Health for Persons With Multiple Chronic Conditions: Moving From What Is the Matter to What Matters

Open access
Bayliss, E. A., Bonds, D. E., Boyd, C. M., Davis, M. M., Finke, B., Fox, M. H., Glasgow, R. E., Goodman, R. A., Heurtin-Roberts, S., Lachenmayr, S., Lind, C., Madigan, E. A., Meyers, D. S., Mintz, S., Nilsen, W. J., Okun, S., Ruiz, S., Salive, M. E., Stange, K. C.·2014·The Annals of Family Medicine
DOI 10.1370/afm.1643PMC PMC4018375
Open this paper in CoChat — free accountOpen PDF

Abstract

PURPOSE: An isolated focus on 1 disease at a time is insufficient to generate the scientific evidence needed to improve the health of persons living with more than 1 chronic condition. This article explores how to bring context into research efforts to improve the health of persons living with multiple chronic conditions (MCC). METHODS: Forty-five experts, including persons with MCC, family and friend caregivers, researchers, policy makers, funders, and clinicians met to critically consider 4 aspects of incorporating context into research on MCC: key contextual factors, needed research, essential research methods for understanding important contextual factors, and necessary partnerships for catalyzing collaborative action in conducting and applying research. RESULTS: Key contextual factors involve complementary perspectives across multiple levels: public policy, community, health care systems, family, and person, as well as the cellular and molecular levels where most research currently is focused. Needed research involves moving from a disease focus toward a person-driven, goal-directed research agenda. Relevant research methods are participatory, flexible, multilevel, quantitative and qualitative, conducive to longitudinal dynamic measurement from diverse data sources, sufficiently detailed to consider what works for whom in which situation, and generative of ongoing communities of learning, living and practice. Important partnerships for collaborative action include cooperation among members of the research enterprise, health care providers, community-based support, persons with MCC and their family and friend caregivers, policy makers, and payers, including government, public health, philanthropic organizations, and the business community. CONCLUSION: Consistent attention to contextual factors is needed to enhance health research for persons with MCC. Rigorous, integrated, participatory, multimethod approaches to generate new knowledge and diverse partnerships can be used to increase the relevance of research to make health care more sustainable, safe, equitable and effective, to reduce suffering, and to improve quality of life.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1370/afm.1643

Cites

102 of 102 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 2

  1. Fortin M, Soubhi H, Hudon C, Bayliss EA, van den Akker M. Multi- morbidity's many challenges. BMJ. 2007;334(7602):1016-1017.
  2. National Research Council (US) Committee on A Framework for Developing a New Taxonomy of Disease. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Tax- onomy of Disease. Washington, DC: National Academy Press; 2011.

Cited by

Sorted by citations

See all 225

Related

See all

Metadata

Authors
Bayliss, E. A., Bonds, D. E., Boyd, C. M., Davis, M. M., Finke, B., Fox, M. H., Glasgow, R. E., Goodman, R. A., Heurtin-Roberts, S., Lachenmayr, S., Lind, C., Madigan, E. A., Meyers, D. S., Mintz, S., Nilsen, W. J., Okun, S., Ruiz, S., Salive, M. E., & Stange, K. C.
Affiliations
Centers for Disease Control and Prevention (US)
ORCID
Venue
The Annals of Family Medicine
Publisher
Annals of Family Medicine
Published
2014-05-01
Volume
12
Issue
3
Pages
260-269
ISSN
  • 1544-1709 (ISSN-L)
  • 1544-1717
DOI
10.1370/afm.1643
PMC
PMC4018375
OpenAlex
W2149582914
Cited by
225
References
106
Citations by year
2026: 6 · 2025: 6 · 2024: 6 · 2023: 15 · 2022: 16 · 2021: 25 · 2020: 64 · 2019: 17 · 2018: 11 · 2017: 17 · 2016: 13 · 2015: 15 · 2014: 14
FWCI
14.86
Type
journal article
Language
en
Open access
Locations
  • The Annals of Family Medicine (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • American Cancer Society
  • Centers for Disease Control and Prevention
  • Agency for Healthcare Research and Quality
Topics
  • Health Sciences › Medicine › Epidemiology › Chronic Disease Management Strategies
  • Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
  • Health Sciences › Health Professions › General Health Professions › Health, psychology, and well-being
Keywords
multimorbidity, research collaboration, participatory research, research agenda, health care system, health policy, learning communities, research relevance, quality of life
MeSH terms
Chronic Disease, Cooperative Behavior, Health Services Research, Humans, Research, Comorbidity, Biomedical Research

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review