Evidence map›Paper›PMID 37837325›Full record

ReviewMedical decision making : an international journal of the Society for Medical Decision Making

Collecting Physicians' Preferences on Medical Devices: Are We Doing It Right? Evidence from Italian Orthopedists Using 2 Different Stated Preference Methods.

Patrizio Armeni, Michela Meregaglia, Ludovica Borsoi, Giuditta Callea, Aleksandra Torbica, Francesco Benazzo, Rosanna Tarricone

Open access · greenAbstract readReview
In one paragraph

Review in Medical decision making : an international journal of the Society for Medical Decision Making. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 7% of its field
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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. 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

7 authors at 2 institutions in 1 country.

Patrizio ArmeniResearch Centre on Health and Social Care Management (CERGAS), SDA Bocconi School of Management, Milan, Italy.
Michela MeregagliaResearch Centre on Health and Social Care Management (CERGAS), SDA Bocconi School of Management, Milan, Italy.ORCID 0000-0003-0092-5970
Ludovica BorsoiResearch Centre on Health and Social Care Management (CERGAS), SDA Bocconi School of Management, Milan, Italy.
Giuditta CalleaResearch Centre on Health and Social Care Management (CERGAS), SDA Bocconi School of Management, Milan, Italy.
Aleksandra TorbicaResearch Centre on Health and Social Care Management (CERGAS), SDA Bocconi School of Management, Milan, Italy.
Francesco BenazzoScuola Universitaria di Istruzione Superiore (IUSS), Pavia, Italy.ORCID 0000-0001-5152-1082
Rosanna TarriconeResearch Centre on Health and Social Care Management (CERGAS), SDA Bocconi School of Management, Milan, Italy.
Bocconi University · ITIstituto Universitario di Studi Superiori di Pavia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesPhysician preference items (PPIs) are high-cost medical devices for which clinicians express firm preferences with respect to a particular manufacturer or product. This study aims to identify the most important factors in the choice of new PPIs (hip or knee prosthesis) and infer about the existence of possible response biases in using 2 alternative stated preference techniques.

methodsSix key attributes with 3 levels each were identified based on a literature review and clinical experts' opinions. An online survey was administered to Italian hospital orthopedists using type 1 best-worst scaling (BWS) and binary discrete choice experiment (DCE). BWS data were analyzed through descriptive statistics and conditional logit model. A mixed logit regression model was applied to DCE data, and willingness-to-pay (WTP) was estimated. All analyses were conducted using Stata 16.

resultsA sample of 108 orthopedists were enrolled. In BWS, the most important attribute was "clinical evidence," followed by "quality of products," while the least relevant items were "relationship with the sales representative" and "cost." DCE results suggested instead that orthopedists prefer high-quality products with robust clinical evidence, positive health technology assessment recommendation and affordable cost, and for which they have a consolidated experience of use and a good relationship with the sales representative.

conclusionsThe elicitation of preferences for PPIs using alternative methods can lead to different results. The BWS of type 1, which is similar to a ranking exercise, seems to be more affected by acquiescent responding and social desirability than the DCE, which introduces tradeoffs in the choice task and is likely to reveal more about true preferences. HIGHLIGHTS: Physician preference items (PPIs) are medical devices particularly exposed to physicians' choice with regard to type of product and supplier.Some established techniques of collecting preferences can be affected by response biases such as acquiescent responding and social desirability.Discrete choice experiments, introducing more complex tradeoffs in the choice task, are likely to mitigate such biases and reveal true physicians' preferences for PPIs.

Indexed as

Orthopedic SurgeonsPhysiciansChoice BehaviorDecision MakingHumansPatient PreferenceSurveys and Questionnairesbest-worst scalingdiscrete choice experimenthealth technology assessmentItalyorthopaedicsphysician preference itemspreference elicitationresponse bias

Identifiers

PMID37837325
PMCPMC10848602
OpenAlexW4387640312

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.