Background: Standardized structured reporting (SSR) improves quality of diagnostic cancer reporting and interdisciplinary communication in multidisciplinary team (MDT) meetings, resulting in more adequate treatment decisions and better health outcomes. However, use of SSR varies widely among pathologists, but might be encouraged by MDT members (MDTMs). Our objectives were to identify barriers and facilitators (influencing factors) for SSR implementation in oncologic pathology from the perspective of MDTMs and their determinants. Methods: In a multimethod design, we identified influencing factors for SSR implementation related to MDT meetings, using 5 domains: (1) innovation factors, (2) individual professional factors, (3) social setting factors, (4) organizational factors, and (5) political and legal factors. Four focus groups with MDTMs in urologic, gynecologic, and gastroenterologic oncology were conducted. We used an eSurvey among MDTMs to quantify the qualitative findings and to analyze determinants affecting these influencing factors. Results: Twenty-three MDTMs practicing in 9 oncology-related disciplines participated in the focus groups and yielded 28 barriers and 28 facilitators in all domains. The eSurvey yielded 211 responses. Main barriers related to lack of readability of SSR: difficulties with capturing nuances (66%) and formulation of the conclusion (43%); lack of transparency in the development (50%) and feedback processes of SSR templates (38%); and lack of information exchange about SSR between pathologists and other MDTMs (45%). Main facilitators were encouragement of pathologists’ SSR use by MDTMs (90%) and expanding the recommendation of SSR use in national guidelines (80%). Oncology-related medical discipline and MDT type were the most relevant determinants for SSR implementation barriers. Conclusions: Although SSR makes diagnostic reports more complete, this study shows important barriers in implementing SSR in oncologic pathology. The next step is to use these factors for developing and testing implementation tools to improve SSR implementation.
Julie E.M. Swillens, Quirinus J.M. Voorham, Iris D. Nagtegaal, and Rosella P.M.G. Hermens
Lydia F.J. van Overveld, Robert P. Takes, Jozé C.C. Braspenning, Robert J. Baatenburg de Jong, Jan P. de Boer, John J.A. Brouns, Rolf J. Bun, Eric A. Dik, Boukje A.C. van Dijk, Robert J.J. van Es, Frank J.P. Hoebers, Barry Kolenaar, Arvid Kropveld, Ton P.M. Langeveld, Hendrik P. Verschuur, Jan G.A.M. de Visscher, Stijn van Weert, Max J.H. Witjes, Ludi E. Smeele, Matthias A.W. Merkx, and Rosella P.M.G. Hermens
Background: Monitoring and effectively improving oncologic integrated care requires dashboard information based on quality registrations. The dashboard includes evidence-based quality indicators (QIs) that measure quality of care. This study aimed to assess the quality of current integrated head and neck cancer care with QIs, the variation between Dutch hospitals, and the influence of patient and hospital characteristics. Methods: Previously, 39 QIs were developed with input from medical specialists, allied health professionals, and patients' perspectives. QI scores were calculated with data from 1,667 curatively treated patients in 8 hospitals. QIs with a sample size of >400 patients were included to calculate reliable QI scores. We used multilevel analysis to explain the variation. Results: Current care varied from 29% for the QI about a case manager being present to discuss the treatment plan to 100% for the QI about the availability of a treatment plan. Variation between hospitals was small for the QI about patients discussed in multidisciplinary team meetings (adherence: 95%, range 88%–98%), but large for the QI about malnutrition screening (adherence: 50%, range 2%–100%). Higher QI scores were associated with lower performance status, advanced tumor stage, and tumor in the oral cavity or oropharynx at the patient level, and with more curatively treated patients (volume) at hospital level. Conclusions: Although the quality registration was only recently launched, it already visualizes hospital variation in current care. Four determinants were found to be influential: tumor stage, performance status, tumor site, and volume. More data are needed to assure stable results for use in quality improvement.