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.
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.
Authors: Annemieke Kok; Carlijn van der Lugt; Marja J Leermakers-Vermeer; Nicole M de Roos; Caroline M Speksnijder; Remco de Bree Journal: Eur J Cancer Care (Engl) Date: 2021-10-12 Impact factor: 2.328
Authors: Robert P Takes; Gyorgy B Halmos; John A Ridge; Paolo Bossi; Matthias A W Merkx; Alessandra Rinaldo; Alvaro Sanabria; Ludi E Smeele; Antti A Mäkitie; Alfio Ferlito Journal: Curr Oncol Rep Date: 2020-07-10 Impact factor: 5.075