RESUMO
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.
Assuntos
Neoplasias da Mama/diagnóstico , Atenção à Saúde , Equipe de Assistência ao Paciente/organização & administração , Adulto , Idoso , Atenção à Saúde/organização & administração , Atenção à Saúde/normas , Feminino , Humanos , Pessoa de Meia-Idade , Satisfação do Paciente , Avaliação de Programas e Projetos de Saúde , Pesquisa Qualitativa , Estudos Retrospectivos , Adulto JovemRESUMO
OBJECTIVES: Diagnostic assessment programs (daps) appear to improve the diagnosis of cancer, but evidence of their cost-effectiveness is lacking. Given that no earlier study used secondary financial data to estimate the cost of diagnostic tests in the province of Ontario, we explored how to use secondary financial data to retrieve the cost of key diagnostic test services in daps, and we tested the reliability of that cost-retrieving method with hospital-reported costs in preparation for future cost-effectiveness studies. METHODS: We powered our sample at an alpha of 0.05, a power of 80%, and a margin of error of ±5%, and randomly selected a sample of eligible patients referred to a dap for suspected breast cancer during 1 January-31 December 2012. Confirmatory diagnostic tests received by each patient were identified in medical records. Canadian Classification of Health Intervention procedure codes were used to search the secondary financial data Web portal at the Ontario Case Costing Initiative for an estimate of the direct, indirect, and total costs of each test. The hospital-reported cost of each test received was obtained from the host-hospital's finance department. Descriptive statistics were used to calculate the cost of individual or group confirmatory diagnostic tests, and the Wilcoxon signed-rank test or the paired t-test was used to compare the Ontario Case Costing Initiative and hospital-reported costs. RESULTS: For the 191 identified patients with suspected breast cancer, the estimated total cost of $72,195.50 was not significantly different from the hospital-reported total cost of $72,035.52 (p = 0.24). Costs differed significantly when multiple tests to confirm the diagnosis were completed during one patient visit and when confirmatory tests reported in hospital data and in medical records were discrepant. The additional estimated cost for non-salaried physicians delivering diagnostic services was $28,387.50. CONCLUSIONS: It was feasible to use secondary financial data to retrieve the cost of key diagnostic tests in a breast cancer dap and to compare the reliability of the costs obtained by that estimation method with hospital-reported costs. We identified the strengths and challenges of each approach. Lessons learned from this study have to be taken into consideration in future cost-effectiveness studies.