Application of a revised model for coping with advanced cancer to qualitatively explore lung cancer survivors' experiences of ongoing physical effects, novel treatments, uncertainty, and coping.

PURPOSE: Lung cancer remains underrepresented in cancer survivorship research. This study aimed to understand survivors' physical/psychological challenges, experiences of immunotherapy (IO) and targeted therapy (TT), and psychological adjustment through application of the Roberts et al. (2017) advanced cancer adaptation of Folkman and Greer's appraisal and coping model. METHODS: Adults 6-24 months post-initial treatment completion were recruited via an Australian cohort study. Participant demographic, clinical, quality of life, and distress data were obtained through the cohort database. Qualitative interviews were conducted and analyzed using Framework methods. Roberts et al. (2017)'s model informed data interpretation and presentation. RESULTS: Twenty interviews were conducted (10 females; average age 69 years). Participants' diagnostic stages varied (stage I = 2, stage II = 4, stage III = 8, stage IV = 6); most had received IO/TT (n = 14) and were on average 17 months (range 10-24) post-diagnosis. Three themes were identified and mapped to the Roberts' framework: (1) Ongoing illness events: most participants reported functioning well despite ongoing physical effects. Those on IO/TT reported side effects; some were unexpected/serious. (2) Adjusting to life with lung cancer: most expressed hope for the future while simultaneously preparing for disease progression. Those receiving IO/TT experienced uncertainty given limited survival information. (3) Learning to live with lung cancer: participants described emotion, problem, and meaning based on coping strategies. CONCLUSIONS: Findings may guide development of supportive care resources/interventions focused on uncertainty, IO/TT communication and decision-making, and coping. IMPLICATIONS FOR CANCER SURVIVORS: Many people with lung cancer are living well with their ongoing illness. Despite challenges, many survivors are adapting to issues as they arise and are maintaining a sense of hope and optimism.

Urologists' referral and radiation oncologists' treatment patterns regarding high-risk prostate cancer patients receiving radiotherapy within 6 months after radical prostatectomy: A prospective cohort analysis.

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.

Development and validation of a survey to measure features of clinical networks.

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.

The effectiveness of clinical networks in improving quality of care and patient outcomes: a systematic review of quantitative and qualitative studies.

BACKGROUND: Reorganisation of healthcare services into networks of clinical experts is increasing as a strategy to promote the uptake of evidence based practice and to improve patient care. This is reflected in significant financial investment in clinical networks. However, there is still some question as to whether clinical networks are effective vehicles for quality improvement. The aim of this systematic review was to ascertain the effectiveness of clinical networks and identify how successful networks improve quality of care and patient outcomes. METHODS: A systematic search was undertaken in accordance with the PRISMA approach in Medline, Embase, CINAHL and PubMed for relevant papers between 1 January 1996 and 30 September 2014. Established protocols were used separately to examine and assess the evidence from quantitative and qualitative primary studies and then integrate findings. RESULTS: A total of 22 eligible studies (9 quantitative; 13 qualitative) were included. Of the quantitative studies, seven focused on improving quality of care and two focused on improving patient outcomes. Quantitative studies were limited by a lack of rigorous experimental design. The evidence indicates that clinical networks can be effective vehicles for quality improvement in service delivery and patient outcomes across a range of clinical disciplines. However, there was variability in the networks' ability to make meaningful network- or system-wide change in more complex processes such as those requiring intensive professional education or more comprehensive redesign of care pathways. Findings from qualitative studies indicated networks that had a positive impact on quality of care and patients outcomes were those that had adequate resources, credible leadership and efficient management coupled with effective communication strategies and collaborative trusting relationships. CONCLUSIONS: There is evidence that clinical networks can improve the delivery of healthcare though there are few high quality quantitative studies of their effectiveness. Our findings can provide policymakers with some insight into how to successfully plan and implement clinical networks by ensuring strong clinical leadership, an inclusive organisational culture, adequate resourcing and localised decision-making authority.

Clinician-led improvement in cancer care (CLICC)--testing a multifaceted implementation strategy to increase evidence-based prostate cancer care: phased randomised controlled trial--study protocol.

BACKGROUND: Clinical practice guidelines have been widely developed and disseminated with the aim of improving healthcare processes and patient outcomes but the uptake of evidence-based practice remains haphazard. There is a need to develop effective implementation methods to achieve large-scale adoption of proven innovations and recommended care. Clinical networks are increasingly being viewed as a vehicle through which evidence-based care can be embedded into healthcare systems using a collegial approach to agree on and implement a range of strategies within hospitals. In Australia, the provision of evidence-based care for men with prostate cancer has been identified as a high priority. Clinical audits have shown that fewer than 10% of patients in New South Wales (NSW) Australia at high risk of recurrence after radical prostatectomy receive guideline recommended radiation treatment following surgery. This trial will test a clinical network-based intervention to improve uptake of guideline recommended care for men with high-risk prostate cancer. METHODS/DESIGN: In Phase I, a phased randomised cluster trial will test a multifaceted intervention that harnesses the NSW Agency for Clinical Innovation (ACI) Urology Clinical Network to increase evidence-based care for men with high-risk prostate cancer following surgery. The intervention will be introduced in nine NSW hospitals over 10 months using a stepped wedge design. Outcome data (referral to radiation oncology for discussion of adjuvant radiotherapy in line with guideline recommended care or referral to a clinical trial of adjuvant versus salvage radiotherapy) will be collected through review of patient medical records. In Phase II, mixed methods will be used to identify mechanisms of provider and organisational change. Clinicians' knowledge and attitudes will be assessed through surveys. Process outcome measures will be assessed through document review. Semi-structured interviews will be conducted to elucidate mechanisms of change. DISCUSSION: The study will be one of the first randomised controlled trials to test the effectiveness of clinical networks to lead changes in clinical practice in hospitals treating patients with high-risk cancer. It will additionally provide direction regarding implementation strategies that can be effectively employed to encourage widespread adoption of clinical practice guidelines. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12611001251910.