Evidence map›Paper›PMID 35535474›Full record

ArticleHealth expectations : an international journal of public participation in health care and health policy2022

Clinician perspectives on clinical decision support systems in lung cancer: Implications for shared decision-making.

Anshu Ankolekar, Britt van der Heijden, Andre Dekker, Cheryl Roumen, Dirk De Ruysscher, Bart Reymen, Adriana Berlanga, Cary Oberije, Rianne Fijten

Open access · goldAbstract read
In one paragraph

Article in Health expectations : an international journal of public participation in health care and health policy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
7.5field-weighted citation impact, top 2% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

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  16. Clinician perspectives on clinical decision support systems in lung cancer: Implications for shared decision-making.Health expectations : an international journal of public participation in health care and health policy · 2022
    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 at 2 institutions in 1 country.

Anshu AnkolekarDepartment of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.ORCID 0000-0001-7681-1254
Britt van der HeijdenDepartment of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.
Andre DekkerDepartment of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.ORCID 0000-0002-0422-7996
Cheryl RoumenDepartment of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.ORCID 0000-0002-2941-4632
Dirk De RuysscherDepartment of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.ORCID 0000-0001-9269-6567
Bart ReymenDepartment of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.ORCID 0000-0003-1709-8414
Adriana BerlangaDepartment of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.ORCID 0000-0002-3216-2085
Cary OberijeThe D-Lab, GROW School for Oncology, Maastricht University Medical Center+, Maastricht University, Maastricht, The Netherlands.ORCID 0000-0003-0749-5117
Rianne FijtenDepartment of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.ORCID 0000-0002-1964-6317
Maastricht University · NLMaastricht University Medical Centre · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung cancer treatment decisions are typically made among clinical experts in a multidisciplinary tumour board (MTB) based on clinical data and guidelines. The rise of artificial intelligence and cultural shifts towards patient autonomy are changing the nature of clinical decision-making towards personalized treatments. This can be supported by clinical decision support systems (CDSSs) that generate personalized treatment information as a basis for shared decision-making (SDM). Little is known about lung cancer patients' treatment decisions and the potential for SDM supported by CDSSs. The aim of this study is to understand to what extent SDM is done in current practice and what clinicians need to improve it.

objectiveTo explore (1) the extent to which patient preferences are taken into consideration in non-small-cell lung cancer (NSCLC) treatment decisions; (2) clinician perspectives on using CDSSs to support SDM.

designMixed methods study consisting of a retrospective cohort study on patient deviation from MTB advice and reasons for deviation, qualitative interviews with lung cancer specialists and observations of MTB discussions and patient consultations. SETTING AND

participantsNSCLC patients (N = 257) treated at a single radiotherapy clinic and nine lung cancer specialists from six Dutch clinics.

resultsWe found a 10.9% (n = 28) deviation rate from MTB advice; 50% (n = 14) were due to patient preference, of which 85.7% (n = 12) chose a less intensive treatment than MTB advice. Current MTB recommendations are based on clinician experience, guidelines and patients' performance status. Most specialists (n = 7) were receptive towards CDSSs but cited barriers, such as lack of trust, lack of validation studies and time. CDSSs were considered valuable during MTB discussions rather than in consultations.

conclusionLung cancer decisions are heavily influenced by clinical guidelines and experience, yet many patients prefer less intensive treatments. CDSSs can support SDM by presenting the harms and benefits of different treatment options rather than giving single treatment advice. External validation of CDSSs should be prioritized. PATIENT OR PUBLIC CONTRIBUTION: This study did not involve patients or the public explicitly; however, the study design was informed by prior interviews with volunteers of a cancer patient advocacy group. The study objectives and data collection were supported by Dutch health care insurer CZ for a project titled 'My Best Treatment' that improves patient-centeredness and the lung cancer patient pathway in the Netherlands.

Indexed as

Carcinoma, Non-Small-Cell LungDecision Support Systems, ClinicalLung NeoplasmsArtificial IntelligenceDecision MakingHumansPatient ParticipationQualitative ResearchRetrospective Studiesclinical decision support systemslung cancermultidisciplinary tumour boardpatient-centred carepatient preferencesshared decision-making

Identifiers

PMID35535474
PMCPMC9327823
OpenAlexW4229455789

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.