How do the characteristics of breast cancer diagnostic assessment programmes influence service delivery: A mixed methods study. (21st June 2017)

• Record Type: Journal Article
• Authors: Gagliardi, A.R.; Honein‐AbouHaidar, G.; Stuart‐McEwan, T.; Smylie, J.; Arnaout, A.; Seely, J.; Wright, F.C.; Dobrow, M.J.; Brouwers, M.C.; Bukhanov, K.; McCready, D.R.
• Is Part Of: European journal of cancer care. Volume 27:Number 2(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-06-21
• Subjects: breast cancer -- diagnostic techniques and procedures -- interprofessional relations -- patient care team -- systems integration; Cancer -- Nursing -- Periodicals; 616.994
• DOI: 10.1111/ecc.12727
• Languages: English
• ISSNs: 0961-5423

Abstract

Abstract : Diagnostic assessment programmes (DAPs) coordinate multidisciplinary teamwork (MDT), and improve wait times and patient satisfaction. No research has established optimal DAP design. This study explored how DAP characteristics influence service delivery. A mixed methods case study of four breast cancer DAPs was conducted including qualitative interviews with health‐care providers and retrospective chart review. Data were integrated using multiple approaches. Twenty‐three providers were interviewed; 411 medical records were reviewed. The number of visits and wait times from referral to diagnosis and consultation were lowest at a one‐stop model. DAP characteristics (rural–remote region, human resources, referral volume, organisation of services, adherence to service delivery targets and one‐stop model) may influence service delivery (number of visits, wait times). MDT, influenced by other DAP characteristics (co‐location of staff, patient navigators, team functioning), may also influence service delivery. While the one‐stop model may be ideal, all sites experienced similar and unique challenges. Further research is needed to understand how to optimise the organisation and delivery of DAP services. Measures reflecting individual, team and patient‐reported outcomes should be used to assess the effectiveness and impact of DAPs in addition to more traditional measures such as wait times.