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Objective. Lung cancer is commonly diagnosed and is the leading cause of cancer-related death, morbidity, and burden of disease globally. There is an ongoing need to ensure patients receive optimal evidence-based care and to identify and reduce unwarranted clinical variation to achieve best possible outcomes. The EnRICH program has developed evidence-based clinical quality indicators to measure processes and outcomes of lung cancer care, and a feedback dashboard to report comparative performance data, which highlight variation in both care and outcomes. The aims of this study were to evaluate the acceptability and utility of the quality indicators and feedback dashboard and identify benchmarks for performance monitoring and priorities for future quality improvement interventions to address observed clinical variation. Method. Clinicians from lung cancer multidisciplinary teams (MDTs) at six tertiary clinical sites across regional and metropolitan NSW were invited to participate in evaluation interviews. Interviews were conducted via videoconference and recorded with consent. Data were analysed thematically using framework methods. Results. Thirteen clinicians participated in interviews, with representation from each clinical site and specialty. All participants considered the quality indicators to be clinically meaningful. Three main themes were identified: (i) the importance of timely, local, quality data; (ii) implementable versus nonimplementable clinical practice changes; and (iii) the need for ongoing performance monitoring. Clinicians prioritised two areas of unwarranted clinical variation that could be immediately addressed through easily implementable quality improvement interventions to positively impact patient care: (i) a process to ensure that all stage III patients are discussed by a multidisciplinary team prior to commencing treatment; (ii) a referral pathway to palliative care within eight weeks for patients diagnosed with stage IV disease. The importance of lung cancer nurse specialists for improved care coordination was highlighted. Conclusion. Clinicians would like to continue to receive close-to-real-time quality data for ongoing performance monitoring to identify and address unwarranted clinical variation. [ABSTRACT FROM AUTHOR]

Abstract Background Clinical networks are increasingly being viewed as an important strategy for increasing evidence-based practice and improving models of care, but success is variable and characteristics of networks with high impact are uncertain. This study takes advantage of the variability in the functioning and outcomes of networks supported by the Australian New South Wales (NSW) Agency for Clinical Innovation's non-mandatory model of clinical networks to investigate the factors that contribute to the success of clinical networks. Methods/Design The objective of this retrospective study is to examine the association between external support, organisational and program factors, and indicators of success among 19 clinical networks over a three-year period (2006-2008). The outcomes (health impact, system impact, programs implemented, engagement, user perception, and financial leverage) and explanatory factors will be collected using a web-based survey, interviews, and record review. An independent expert panel will provide judgements about the impact or extent of each network's initiatives on health and system impacts. The ratings of the expert panel will be the outcome used in multivariable analyses. Following the rating of network success, a qualitative study will be conducted to provide a more in-depth examination of the most successful networks. Discussion This is the first study to combine quantitative and qualitative methods to examine the factors that contribute to the success of clinical networks and, more generally, is the largest study of clinical networks undertaken. The adaptation of expert panel methods to rate the impacts of networks is the methodological innovation of this study. The proposed project will identify the conditions that should be established or encouraged by agencies developing clinical networks and will be of immediate use in forming strategies and programs to maximise the effectiveness of such networks.

Introduction: Previous studies have observed low rates of adjuvant radiotherapy after radical prostatectomy (RP) for high-risk prostate cancer patients. However, it is not clear the extent to which these low rates are driven by urologists' referral and radiation oncologists' treatment patterns.Method: The Clinician-Led Improvement in Cancer Care (CLICC) implementation trial was conducted in nine public hospitals in New South Wales, Australia. Men who underwent RP for prostate cancer during 2013-2015 and had at least one high-risk pathological feature of extracapsular extension, seminal vesicle invasion and/or positive surgical margins were included in these analyses. Outcomes were as follows: (i) referral to a radiation oncologist within 4 months after RP ('referred'); (ii) commencement of radiotherapy within 6 months after RP among those who consulted a radiation oncologist ('radiotherapy after consultation').Results: Three hundred and twenty-five (30%) of 1071 patients were 'referred', and 74 (61%) of 121 patients received 'radiotherapy after consultation'. Overall, the probability of receiving radiotherapy within 6 months after RP was 15%. The probability of being 'referred' increased according to higher 5-year risk of cancer-recurrence (P < 0.001).Conclusion: Only 30% of patients with high-risk features are referred to a radiation oncologist with the likelihood of referral being influenced by the perceived risk of cancer-recurrence as well as the urologist's institutional/personal preference. When patients are seen by a radiation oncologist, 61% receive radiotherapy within 6 months after RP with the likelihood of receiving radiotherapy not being heavily influenced by increasing risk of recurrence. This suggests many suitable patients would receive radiotherapy if referred and seen by a radiation oncologist. [ABSTRACT FROM AUTHOR]

Background: Networks of clinical experts are increasingly being implemented as a strategy to improve health care processes and outcomes and achieve change in the health system. Few are ever formally evaluated and, when this is done, not all networks are equally successful in their efforts. There is a need to formatively assess the strategic and operational management and leadership of networks to identify where functioning could be improved to maximise impact. This paper outlines the development and psychometric evaluation of an Internet survey to measure features of clinical networks and provides descriptive results from a sample of members of 19 diverse clinical networks responsible for evidence-based quality improvement across a large geographical region. Methods: Instrument development was based on: a review of published and grey literature; a qualitative study of clinical network members; a program logic framework; and consultation with stakeholders. The resulting domain structure was validated for a sample of 592 clinical network members using confirmatory factor analysis. Scale reliability was assessed using Cronbach's alpha. A summary score was calculated for each domain and aggregate level means and ranges are reported. Results: The instrument was shown to have good construct validity across seven domains as demonstrated by a high level of internal consistency, and all Cronbach's α coefficients were equal to or above 0.75. In the survey sample of network members there was strong reported commitment and belief in network-led quality improvement initiatives, which were perceived to have improved quality of care (72.8 %) and patient outcomes (63.2 %). Network managers were perceived to be effective leaders and clinical co-chairs were perceived as champions for change. Perceived external support had the lowest summary score across the seven domains. Conclusions: This survey, which has good construct validity and internal reliability, provides a valid instrument to use in future research related to clinical networks. The survey will be of use to health service managers to identify strengths and areas where networks can be improved to increase effectiveness and impact on quality of care and patient outcomes. Equally, the survey could be adapted for use in the assessment of other types of networks. [ABSTRACT FROM AUTHOR]