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Clinician perspectives on clinical decision support systems in lung cancer: Implications for shared decision-making.
Ankolekar, Anshu; van der Heijden, Britt; Dekker, Andre; Roumen, Cheryl; De Ruysscher, Dirk; Reymen, Bart; Berlanga, Adriana; Oberije, Cary; Fijten, Rianne.
Afiliação
  • Ankolekar A; Department of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.
  • van der Heijden B; Department of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.
  • Dekker A; Department of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.
  • Roumen C; Department of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.
  • De Ruysscher D; Department of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.
  • Reymen B; Department of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.
  • Berlanga A; Department of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.
  • Oberije C; The D-Lab, GROW School for Oncology, Maastricht University Medical Center+, Maastricht University, Maastricht, The Netherlands.
  • Fijten R; Department of Radiation Oncology (MAASTRO), GROW School for Oncology, Maastricht University Medical Center+, Maastricht, The Netherlands.
Health Expect ; 25(4): 1342-1351, 2022 08.
Article em En | MEDLINE | ID: mdl-35535474
ABSTRACT

BACKGROUND:

Lung 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.

OBJECTIVE:

To 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.

DESIGN:

Mixed 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

PARTICIPANTS:

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

RESULTS:

We 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.

CONCLUSION:

Lung 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carcinoma Pulmonar de Células não Pequenas / Sistemas de Apoio a Decisões Clínicas / Neoplasias Pulmonares Tipo de estudo: Guideline / Observational_studies / Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Revista: Health Expect Assunto da revista: PESQUISA EM SERVICOS DE SAUDE / SAUDE PUBLICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carcinoma Pulmonar de Células não Pequenas / Sistemas de Apoio a Decisões Clínicas / Neoplasias Pulmonares Tipo de estudo: Guideline / Observational_studies / Prognostic_studies / Qualitative_research Limite: Humans Idioma: En Revista: Health Expect Assunto da revista: PESQUISA EM SERVICOS DE SAUDE / SAUDE PUBLICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Holanda