Evidence map›Paper›PMID 28401418›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2018

Development of a care guidance index based on what matters to patients.

John H Wasson, Laura Soloway, L Gordon Moore, Paul Labrec, Lynn Ho

Abstract read
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Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Standardized assessment, information, and networking technologies (SAINTs): lessons from three decades of development and testing.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2021
    Article
  2. Article
  3. Introduction to special section: measuring what matters.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2018
    Article
  4. Article
  5. Insights From Organized Crime for Disorganized Health Care.The Journal of ambulatory care management
    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

5 authors.

John H WassonDartmouth Medical School, Hanover, NH, 03755, USA. John.H.Wasson@Dartmouth.edu.
Laura Soloway3 M Health Information Systems Inc, Salt Lake City, UT, USA.
L Gordon Moore3 M Health Information Systems Inc, Salt Lake City, UT, USA.
Paul Labrec3 M Health Information Systems Inc, Salt Lake City, UT, USA.
Lynn Ho, North Kingston Family Practice, North Kingstown, RI, 02852, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionTargeting resources for a designated higher-risk subgroup is a strategy for chronic care management. However, risk-designation has several limitations: it is inaccurate, seldom helpful for care guidance, and potentially misallocates care away from many patients.

methodsTo address limitations of risk designation, we tested a "what matters index" (WMI) in 19,593 adult patients with chronic conditions. The WMI contains five binary measures: insufficient confidence to manage health problems, level of pain, emotional problems, polypharmacy, and adverse medication effects. We examined its sum for association with patient-reported quality of life and prior emergency or hospital use. We compared its accuracy to a prototypic risk-designation model.

resultsThe WMI was a good indicator for quality of life and in three diverse test populations it was strongly associated with the use of hospital and emergency services. For example, a sum of WMI ≥2 was associated with twice as many average uses as none; for ≥3, uses were three times higher. However, since relatively few patients use costly care, both the WMI and a prototypic risk-designation model had comparably low-positive predictive values. The WMI uses the patient voice to identify needs strongly associated with quality of life. Akin to risk designation models, the WMI can be used to place patients into groups associated with levels of costly services, but neither is likely to forecast costly service use for individuals. However, unlike risk-designation models, the WMI is based on measures that will immediately guide care for every patient.

Indexed as

Patient Reported Outcome MeasuresAdolescentAdultAgedChronic DiseaseFemaleHumansMaleMiddle AgedQuality of LifeYoung AdultChronic condition managementClinical prediction rulesHealth confidencePatient engagementPatient-reported measuresRisk models

Identifiers

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Registered trials

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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.