Evidence map›Paper›PMID 31615472›Full record

ArticleBMC public health2019

Broadening horizons: the case for capturing function and the role of health informatics in its use.

Denis Newman-Griffis, Julia Porcino, Ayah Zirikly, Thanh Thieu, Jonathan Camacho Maldonado, Pei-Shu Ho, Min Ding, Leighton Chan, Elizabeth Rasch

Abstract read
In one paragraph

Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Prediction of morning fatigue severity in outpatients receiving chemotherapy: less may still be more.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Denis Newman-GriffisRehabilitation Medicine Department, National Institutes of Health, Mark O. Hatfield Clinical Research Center, 6707 Democracy Boulevard, Suite 856, MSC 5493, Bethesda, MD, 20892, USA. denis.griffis@nih.gov.ORCID http://orcid.org/0000-0002-0473-4226
Julia PorcinoRehabilitation Medicine Department, National Institutes of Health, Mark O. Hatfield Clinical Research Center, 6707 Democracy Boulevard, Suite 856, MSC 5493, Bethesda, MD, 20892, USA.
Ayah ZiriklyRehabilitation Medicine Department, National Institutes of Health, Mark O. Hatfield Clinical Research Center, 6707 Democracy Boulevard, Suite 856, MSC 5493, Bethesda, MD, 20892, USA.
Thanh ThieuDepartment of Computer Science, Oklahoma State University, 116-A MSCS, Stillwater, OK, 74078, USA.
Jonathan Camacho MaldonadoRehabilitation Medicine Department, National Institutes of Health, Mark O. Hatfield Clinical Research Center, 6707 Democracy Boulevard, Suite 856, MSC 5493, Bethesda, MD, 20892, USA.
Pei-Shu HoRehabilitation Medicine Department, National Institutes of Health, Mark O. Hatfield Clinical Research Center, 6707 Democracy Boulevard, Suite 856, MSC 5493, Bethesda, MD, 20892, USA.
Min DingInformation Technology Laboratory, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899, USA.
Leighton ChanRehabilitation Medicine Department, National Institutes of Health, Mark O. Hatfield Clinical Research Center, 6707 Democracy Boulevard, Suite 856, MSC 5493, Bethesda, MD, 20892, USA.
Elizabeth RaschRehabilitation Medicine Department, National Institutes of Health, Mark O. Hatfield Clinical Research Center, 6707 Democracy Boulevard, Suite 856, MSC 5493, Bethesda, MD, 20892, USA.

Funding

U.S. Social Security Administration (US) Inter-Agency Agreement
6 · The paper itself

Abstract

backgroundHuman activity and the interaction between health conditions and activity is a critical part of understanding the overall function of individuals. The World Health Organization's International Classification of Functioning, Disability and Health (ICF) models function as all aspects of an individual's interaction with the world, including organismal concepts such as individual body structures, functions, and pathologies, as well as the outcomes of the individual's interaction with their environment, referred to as activity and participation. Function, particularly activity and participation outcomes, is an important indicator of health at both the level of an individual and the population level, as it is highly correlated with quality of life and a critical component of identifying resource needs. Since it reflects the cumulative impact of health conditions on individuals and is not disease specific, its use as a health indicator helps to address major barriers to holistic, patient-centered care that result from multiple, and often competing, disease specific interventions. While the need for better information on function has been widely endorsed, this has not translated into its routine incorporation into modern health systems. PURPOSE: We present the importance of capturing information on activity as a core component of modern health systems and identify specific steps and analytic methods that can be used to make it more available to utilize in improving patient care. We identify challenges in the use of activity and participation information, such as a lack of consistent documentation and diversity of data specificity and representation across providers, health systems, and national surveys. We describe how activity and participation information can be more effectively captured, and how health informatics methodologies, including natural language processing (NLP), can enable automatically locating, extracting, and organizing this information on a large scale, supporting standardization and utilization with minimal additional provider burden. We examine the analytic requirements and potential challenges of capturing this information with informatics, and describe how data-driven techniques can combine with common standards and documentation practices to make activity and participation information standardized and accessible for improving patient care. RECOMMENDATIONS: We recommend four specific actions to improve the capture and analysis of activity and participation information throughout the continuum of care: (1) make activity and participation annotation standards and datasets available to the broader research community; (2) define common research problems in automatically processing activity and participation information; (3) develop robust, machine-readable ontologies for function that describe the components of activity and participation information and their relationships; and (4) establish standards for how and when to document activity and participation status during clinical encounters. We further provide specific short-term goals to make significant progress in each of these areas within a reasonable time frame.

Indexed as

Data CollectionMedical InformaticsHumansClinical informaticsDisability evaluationElectronic health recordsHealth informaticsNatural language processingPublic health informatics

Identifiers

PMID31615472
PMCPMC6794808

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.