Evidence map›Paper›PMID 28806143›Full record

ArticleMedical decision making : an international journal of the Society for Medical Decision Making2018

Whose Preferences Matter? A Patient-Centered Approach for Eliciting Treatment Goals.

Nananda F Col, Andrew J Solomon, Vicky Springmann, Calvin P Garbin, Carolina Ionete, Lori Pbert, Enrique Alvarez, Brenda Tierman, Ashli Hopson, Christen Kutz and 4 more

3 registry-linked trialsAbstract read
In one paragraph

Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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.

NCT03425266 nacompletednot on this map

Incorporating Patient Preferences Into Decisions About Chronic Pain Management (The Pain APP Study)

TypeinterventionalSponsorShared Decision Making ResourcesRan2018 to 2018Enrolled80ConditionsChronic PainArmsInteractive decision support tool
NCT04122989 nacompletednot on this mapstarted 2019, after this paper: background citation

Validation of a Shared Decision-Making Tool, MS-SUPPORT, to Improve Decisions About Disease Modifying Therapies (DMT) for Multiple Sclerosis

TypeinterventionalSponsorShared Decision Making ResourcesRan2019 to 2021Enrolled501ConditionsMultiple SclerosisArmsMS-SUPPORT
NCT04755426 completednot on this mapstarted 2020, after this paper: background citation

Understanding Patient Goals and Preferences to Facilitate Shared Decision Making for Symptomatic Aortic Stenosis

TypeobservationalSponsorShared Decision Making ResourcesRan2020 to 2022Enrolled99ConditionsAortic Stenosis SymptomaticArmsAVITA--Aortic Valve Improved Treatment Approaches
3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

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  9. The prototype of a preference-based index of weight-related quality of life: demonstrating the possibilities.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2022
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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

14 authors.

Nananda F ColFive Islands Consulting LLC, Georgetown, ME (NFC, VS, BT, AH).
Andrew J SolomonNeurological Sciences, University of Vermont College of Medicine, Burlington, VT (AJS).
Vicky SpringmannFive Islands Consulting LLC, Georgetown, ME (NFC, VS, BT, AH).
Calvin P GarbinDepartment of Psychology, University of Nebraska-Lincoln, Lincoln, Nebraska (CPG).
Carolina IoneteNeurology, University of Colorado, Aurora, CO (CI, EA).
Lori PbertUniversity of Massachusetts Medical School, Worcester, MA (LP).
Enrique AlvarezNeurology, University of Colorado, Aurora, CO (CI, EA).
Brenda TiermanFive Islands Consulting LLC, Georgetown, ME (NFC, VS, BT, AH).
Ashli HopsonFive Islands Consulting LLC, Georgetown, ME (NFC, VS, BT, AH).
Christen KutzColorado Springs Neurological Associates, Colorado Springs, CO (CK).
Idanis Berrios MoralesUniversity of Massachusetts Memorial Medical Center, Worcester, MA (LP, IBM, CPG).
Carolyn GriffinBiogen Inc., Weston, MA, USA, Cambridge, MA (CK, GH).
Glenn PhillipsBiogen Inc., Weston, MA, USA, Cambridge, MA (CK, GH).
Long H NgoHarvard Medical School, Boston, MA (LPN).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients facing a high-stakes clinical decision are often confronted with an overwhelming array of options. High-quality decisions about treatment should reflect patients' preferences as well as their clinical characteristics. Preference-assessment instruments typically focus on pre-selected clinical outcomes and attributes chosen by the investigator.

objectiveWe sought to develop a patient-centered approach to elicit and compare the treatment goals of patients with multiple sclerosis (MS) and healthcare providers (HCPs).

methodsWe conducted five nominal group technique (NGT) meetings to elicit and prioritize treatment goals from patients and HCPs. Five to nine participants in each group responded silently to one question about their treatment goals. Responses were shared, consolidated, and ranked to develop a prioritized list for each group. The ranked lists were combined. Goals were rated and sorted into categories. Multidimensional scaling and hierarchical cluster analysis were used to derive a visual representation, or cognitive map, of the data and to identify conceptual clusters, reflecting how frequently items were sorted into the same category.

resultsFive NGT groups yielded 34 unique patient-generated treatment goals and 31 unique HCP-generated goals. There were differences between patients and HCPs in the goals generated and how they were clustered. Patients' goals tended to focus on the impact of specific symptoms on their day-to-day lives, whereas providers' goals focused on slowing down the course of disease progression.

conclusionsDifferences between the treatment goals of patients and HCPs underscore the limitations of using HCP- or investigator-identified goals. This new adaptation of cognitive mapping is a patient-centered approach that can be used to generate and organize the outcomes and attributes for values clarification exercises while minimizing investigator bias and maximizing relevance to patients.

Indexed as

Decision MakingPatient Care PlanningAdultAgedClinical Decision-MakingCluster AnalysisFemaleFocus GroupsHealth PersonnelHumansMaleMiddle AgedMultiple SclerosisPatient-Centered CarePatient ParticipationPatient Preferenceclinical decision makingcognitive mappinghierarchical cluster analysismultidimensional scalingmultiple sclerosisnominal group techniquepreference assessmentpreference sensitive careshared decision makingvalues clarification

Identifiers

PMID28806143
PMCPMC5929460

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

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.