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

A. Ankolekar, B. van der Heijden, A. Dekker, C. Roumen, D. De Ruysscher, B. Reymen, A. Berlanga, C. Oberije, R. Fijten*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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.
Original languageEnglish
Pages (from-to)1342-1351
Number of pages10
JournalHealth Expectations
Volume25
Issue number4
Early online date10 May 2022
DOIs
Publication statusPublished - Aug 2022

Keywords

  • clinical decision support systems
  • lung cancer
  • multidisciplinary tumour board
  • patient-centred care
  • patient preferences
  • shared decision-making
  • TUMOR BOARD
  • PULMONARY NODULES
  • TRAINING-PROGRAM
  • PREDICTION MODEL
  • TEAM MEETINGS
  • QUALITY
  • PATIENT
  • CARE
  • COMMUNICATION
  • RADIOTHERAPY

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