Deploying Team Science Principles to Optimize Interdisciplinary Lung Cancer Care Delivery: Avoiding the Long and Winding Road to Optimal Care

2016 ◽  
Vol 12 (11) ◽  
pp. 983-991 ◽  
Author(s):  
Raymond U. Osarogiagbon ◽  
Hector P. Rodriguez ◽  
Danielle Hicks ◽  
Raymond S. Signore ◽  
Kristi Roark ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Care ◽  
Performance Monitoring ◽  
Care Delivery ◽  
Multidisciplinary Care ◽  
Team Science ◽  
Coordinated Care ◽  
Optimal Care ◽  
Diverse Range ◽  
Quality And Outcomes

The complexity of lung cancer care mandates interaction between clinicians with different skill sets and practice cultures in the routine delivery of care. Using team science principles and a case-based approach, we exemplify the need for the development of real care teams for patients with lung cancer to foster coordination among the multiple specialists and staff engaged in routine care delivery. Achieving coordinated lung cancer care is a high-priority public health challenge because of the volume of patients, lethality of disease, and well-described disparities in quality and outcomes of care. Coordinating mechanisms need to be cultivated among different types of specialist physicians and care teams, with differing technical expertise and practice cultures, who have traditionally functioned more as coactively working groups than as real teams. Coordinating mechanisms, including shared mental models, high-quality communication, mutual trust, and mutual performance monitoring, highlight the challenge of achieving well-coordinated care and illustrate how team science principles can be used to improve quality and outcomes of lung cancer care. To develop the evidence base to support coordinated lung cancer care, research comparing the effectiveness of a diverse range of multidisciplinary care team approaches and interorganizational coordinating mechanisms should be promoted.

A comparison of two models of multidisciplinary lung cancer care within a community-based healthcare system.

2020 ◽  
Vol 38 (29_suppl) ◽  
pp. 36-36
Author(s):  
Meghan Meadows ◽  
Meredith Ray ◽  
Matthew Smeltzer ◽  
Nicholas Faris ◽  
Carrie Fehnel ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Care ◽  
Cox Regression ◽  
Care Delivery ◽  
Smoking Status ◽  
Multidisciplinary Care ◽  
Chi Square ◽  
Community Healthcare ◽  
Lung Cancer Patients ◽  
Chi Square Test

36 Background: The Multidisciplinary Thoracic Oncology Conference (MTOC) model is easier to implement than the Multidisciplinary Clinic (MDC) model, but does not directly involve patients in decision-making. We compared the processes and outcomes of lung cancer care between patients discussed in a weekly MTOC versus those seen in a MDC. Methods: Prospective observational study of thoroughness of staging, stage confirmation (defined as biopsy of the stage-defining lesion), National Comprehensive Cancer Network guideline-concordant treatment, overall (OS) and event-free (EFS) survival of lung cancer patients in a community healthcare system’s MDC and MTOC from 2014-2019. We used the chi-square test and multivariable logistic regression to evaluate guideline-concordant treatment and stage confirmation; Kaplan-Meier curves and multivariable Cox regression were used to evaluate OS and EFS. We adjusted models for age, sex, race, insurance, smoking status, and histology. Results: 614 patients received care in MDC; 571 in MTOC. MDC patients were older (median age: 69 vs. 67); less likely to be active smokers (44% vs. 47%; p=0.03); more likely to have bimodal (98% v 95%, p=0.02) and trimodal staging (60% v 46%, p<0.0001). The stage-confirmation rate (OR: 1.55; 95% CI: 1.22-1.96) and mediastinal stage confirmation rate (OR: 1.55; 95% CI: 1.23-1.95) were both significantly higher in MDC, even after adjustment (aOR: 1.60; 95% CI: 1.25-2.03); (aOR: 1.58, 95% CI: 1.25-2.00). A higher proportion of patients received guideline-concordant treatment in MDC than in MTOC (82% vs. 73%; OR: 1.63; 95% CI: 1.21-2.20) even after adjustment (aOR: 1.64; 95% CI: 1.20-2.24). However, MTOC patients had significantly better OS (p=0.03) and EFS (p=0.001) than MDC patients and a lower hazard of death (HR: 0.81; 95% CI: 0.67-0.98), even after adjusting for confounding variables (aHR: 0.79 95%CI: 0.66-0.95). Conclusions: Although the processes of lung cancer care delivery were better in MDC than in MTOC, survival was better in MTOC. Patient selection may have played a role in these survival differences. The MTOC model, as implemented, seems competitive with the MDC model and is worthy of further exploration as a more feasible model of multidisciplinary care. [Table: see text]

scholarly journals The Anatomy and Physiology of Teaming in Cancer Care Delivery: A Conceptual Framework

2020 ◽  
Author(s):  
Dana Verhoeven ◽  
Veronica Chollette ◽  
Elizabeth H Lazzara ◽  
Marissa L Shuffler ◽  
Raymond U Osarogiagbon ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Conceptual Framework ◽  
Care Coordination ◽  
Cancer Care ◽  
Care Delivery ◽  
Treatment Options ◽  
Multimodality Treatment ◽  
Clinical Team ◽  
Coordinated Care ◽  
Treatment Regimens

Abstract Care coordination challenges for patients with cancer continue to grow as expanding treatment options, multimodality treatment regimens, and an aging population with comorbid conditions intensify demands for multidisciplinary cancer care. Effective teamwork is a critical, yet understudied, cornerstone of coordinated cancer care delivery. For example, comprehensive lung cancer care involves a clinical “team-of-teams”—or clinical multiteam system (MTS)—coordinating decisions and care across specialties, providers, and settings. The teamwork processes within and between these teams lay the foundation for coordinated care. While the need to work as a team and coordinate across disciplinary, organizational, and geographic boundaries increases, evidence identifying and improving the teamwork processes underlying care coordination and delivery among the multiple teams involved remains sparse. This commentary synthesizes MTS structure characteristics and teamwork processes into a conceptual framework called the cancer Multiteam System (cMTS) Framework to advance future cancer care delivery research addressing evidence gaps in care coordination. Included constructs were identified from published frameworks, discussions at the 2016 NCI-ASCO Teams in Cancer Care Workshop, and expert input. A case example in lung cancer provided practical grounding for framework refinement. The cMTS framework identifies team structure variables and teamwork processes affecting cancer care delivery, related outcomes, and contextual variables hypothesized to influence coordination within and between the multiple clinical teams involved. We discuss how the framework might be used to identify care delivery research gaps, develop hypothesis-driven research examining clinical team functioning, and support conceptual coherence across studies examining teamwork, care coordination, and their impact on cancer outcomes.

Development of cancer care episodes to measure costs for breast, colorectal, and non-small cell lung cancer.

2017 ◽  
Vol 35 (8_suppl) ◽  
pp. 29-29
Author(s):  
Catherine R. Fedorenko ◽  
Karma L. Kreizenbeck ◽  
Laura Panattoni ◽  
Julia Rose Walker ◽  
Cara L. McDermott ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
End Of Life ◽  
Cancer Registry ◽  
Cell Lung Cancer ◽  
Cancer Care ◽  
Care Delivery ◽  
Small Cell ◽  
Small Cell Lung ◽  
Potential Cost

29 Background: Cancer care costs are rising, creating concerns about affordability. As a result, delivery systems are creating alternative payment structures to lower costs while maintaining or improving quality. As cancer care delivery often involves multiple provider systems, measuring cost may be difficult. In response, using commercial insurance claims linked to cancer registry records, we constructed broadly applicable, reproducible, clinically relevant episodes to measure costs. Methods: Cancer registry records for patients diagnosed in Western Washington from January 2007-June 2016 were linked with claims from two regional commercial insurers. Patients are age 18+, diagnosed with breast, colorectal (CRC), or non-small cell lung cancer (NSCLC) and enrolled with a single insurance plan. With oncologist input, we constructed three care phases: diagnosis (30 days before diagnosis to first treatment), initial treatment (first treatment through first 4 month treatment gap), and end of life (last 30 days). Costs include all claims paid within the phase (2016 inflation adjusted). Supportive care includes colony-stimulating factors, blood transfusions, antibiotics, antivirals, antifungals, and antiemetics. Results: This study included 8,727 patients at diagnosis, 7,686 during treatment, and 1,736 at end of life. Diagnosis phase averaged 54 days and cost $6,936 (SD $11,761, median $4,021). Treatment averaged 126 days, with costs of $61,148 (SD $75,432, median $35,750). Average end-of-life costs were $15,829 (SD $30,222, median $2,347). The table below provides an example of the variation in costs during the treatment phase using local-stage tumors. Conclusions: Clinically relevant episodes of care and cost measures can be constructed using claims-registry data. This allows for identification of high-cost care categories and areas with large-cost variability, which may be helpful when designing value-based reimbursement programs or identifying areas for potential cost-reduction.[Table: see text]

Quality improvement and implementation science in cancer care: Identifying areas of synergy and opportunities for further integration.

2019 ◽  
Vol 37 (27_suppl) ◽  
pp. 29-29
Author(s):  
Devon Check ◽  
Leah L. Zullig ◽  
Melinda Davis ◽  
Angela M. Stover ◽  
Louise Davies ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Implementation Science ◽  
Cancer Care ◽  
Performance Monitoring ◽  
Care Delivery ◽  
Evidence Based ◽  
Theoretical Frameworks ◽  
Randomized Design ◽  
Stakeholder Input ◽  
The Impact

29 Background: Efforts to improve cancer care delivery have been driven by two approaches: quality improvement (QI) and implementation science (IS). QI and IS have developed independently but have potential for synergy. To inform efforts to better align these fields, we examined 20 cancer-related QI and IS articles to identify differences and areas of commonality. Methods: We searched PubMed for cancer care studies that used IS or QI methods and were published in the past 5 years in one of 17 leading journals. Through consensus-based discussions, we categorized studies as QI if they evaluated efforts to improve the quality, value, or safety of care, or IS if they evaluated efforts to promote the adoption of evidence-based interventions into practice. We identified the 10 most frequently cited studies from each category (20 total studies), characterizing and comparing their objectives, methods – including use of theoretical frameworks involvement of stakeholders – and terminology. Results: All IS studies (10/10) and half (5/10) of QI studies addressed barriers to uptake of evidence-based practices. The remaining five QI studies sought to improve clinical outcomes, reduce costs, and/or address logistical issues. QI and IS studies employed common approaches to change provider and/or organizational practice (e.g., training, performance monitoring/feedback, decision support). However, the terminology used to describe these approaches was inconsistent within and between IS and QI studies. Fewer than half (8/20) of studies (4 from each category) used a theoretical or conceptual framework and only 4/20 (2 from each category) consulted key stakeholders in developing their approach. Most studies (10/10 IS and 6/10 QI) were multi-site, and most were observational, with only 4/20 studies (2 from each category) using a randomized design to evaluate their approach. Conclusions: Cancer-related QI and IS studies had overlapping objectives and used similar approaches but used inconsistent terminology. The impact of IS and QI on cancer care delivery could be enhanced by greater harmonization of language and by promoting rigor through the use of conceptual frameworks and stakeholder input.

Patterns of healthcare utilization in patients with newly diagnosed advanced lung cancer.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e18386-e18386
Author(s):  
Emily Miller Ray ◽  
Sharon Peacock Hinton ◽  
Katherine Elizabeth Reeder-Hayes
Keyword(s):  
Lung Cancer ◽  
Palliative Care ◽  
Intensive Care ◽  
Healthcare Utilization ◽  
Cancer Care ◽  
Care Delivery ◽  
Small Cell ◽  
Advanced Lung Cancer ◽  
Newly Diagnosed ◽  
Index Hospitalization

e18386 Background: Advanced lung cancer (ALC) is a symptomatic disease that is often diagnosed in the context of hospitalization. The index hospitalization may be a window of opportunity to improve cancer care delivery. We aimed to define the frequency of ALC diagnosis associated with hospitalization and the relationship to subsequent cancer care and readmissions. Methods: We identified patients in the SEER-Medicare database with: ALC (stage IIIB-IV non-small cell or small cell), diagnosed 2007 to 2013; with continuous enrollment in Medicare from 6 months prior to lung cancer diagnosis through death or 12/2014; and an index hospitalization within 7 days of their ALC diagnosis. Our primary outcomes of interest were 30-day re-hospitalization and emergency department (ED) use. We examined: utilization of services during index hospitalization, including intensive care and oncology or palliative care consultation; discharge destination; receipt of systemic therapy; and hospice enrollment. Results: Fifty-four percent (n = 28,976) of ALC patients had an index hospitalization, with 90% of those having their cancer diagnosed while hospitalized. During their index hospitalization, 16% had oncology consultation, and 6% had palliative care (PC) consultation. Thirty-three percent were in the intensive care unit. At discharge, 59% returned home, 8% died, and 11% went to hospice. Of those who survived to discharge, 69% later returned to the ED or were re-hospitalized, with 49% of re-hospitalizations and 35% of ED visits occurring within 30 days of the index hospitalization. Thirty-five percent of these patients eventually received systemic treatment for their cancer. By 180 days post-discharge, 77% had enrolled in hospice with a median of 10 days on hospice care. Conclusions: Newly diagnosed ALC patients are high risk for acute care utilization, and many patients experience a return to the hospital early in their cancer trajectory. These patients may benefit from additional health system support prior to hospital discharge to help prevent high-cost, low-value healthcare utilization.

scholarly journals ESMO Management and treatment adapted recommendations in the COVID-19 era: Lung cancer

ESMO Open ◽  
2020 ◽  
Vol 5 (Suppl 3) ◽  
pp. e000820 ◽  
Author(s):  
Antonio Passaro ◽  
Alfredo Addeo ◽  
Christophe Von Garnier ◽  
Fiona Blackhall ◽  
David Planchard ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Care ◽  
Negative Impact ◽  
Well Being ◽  
Tier 2 ◽  
Optimal Care ◽  
Tier 1 ◽  
Global Spread ◽  
Tier 3 ◽  
The Impact

The COVID-19 pandemic, characterised by a fast and global spread during the first months of 2020, has prompted the development of a structured set of recommendations for cancer care management, to maintain the highest possible standards. Within this framework, it is crucial to ensure no disruption to essential oncological services and guarantee the optimal care.This is a structured proposal for the management of lung cancer, comprising three levels of priorities, namely: tier 1 (high priority), tier 2 (medium priority) and tier 3 (low priority)—defined according to the criteria of the Cancer Care Ontario, Huntsman Cancer Institute and Magnitude of Clinical Benefit Scale.The manuscript emphasises the impact of the COVID-19 pandemic on lung cancer care and reconsiders all steps from diagnosis, staging and treatment.These recommendations should, therefore, serve as guidance for prioritising the different aspects of cancer care to mitigate the possible negative impact of the COVID-19 pandemic on the management of our patients.As the situation is rapidly evolving, practical actions are required to guarantee the best patients’ treatment while protecting and respecting their rights, safety and well-being. In this environment, cancer practitioners have great responsibilities: provide timely, appropriate, compassionate and justified cancer care, while protecting themselves and their patients from being infected with COVID-19. In case of shortages, resources must be distributed fairly. Consequently, the following recommendations can be applied with significant nuances, depending on the time and location for their use, considering variable constraints imposed to the health systems. An exceptional flexibility is required from cancer caregivers.

scholarly journals Quality indicators and excellence requirements for a multidisciplinary lung cancer tumor board by the Spanish Lung Cancer Group

2021 ◽  
Author(s):  
M. Guirado ◽  
A. Sanchez-Hernandez ◽  
L. Pijuan ◽  
C. Teixido ◽  
A. Gómez-Caamaño ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Quality Indicators ◽  
Optimal Strategies ◽  
Multidisciplinary Care ◽  
Tumor Board ◽  
Multidisciplinary Teams ◽  
Key Factors ◽  
Optimal Care ◽  
Cancer Group ◽  
Cancer Tumor

AbstractMultidisciplinary care is needed to decide the best therapeutic approach and to provide optimal care to patients with lung cancer (LC). Multidisciplinary teams (MDTs) are optimal strategies for the management of patients with LC and have been associated with better outcomes, such as an increase in quality of life and survival. The Spanish Lung Cancer Group has promoted this review about the current situation of the existing national LC-MDTs, which also offers a set of excellence requirements and quality indicators to achieve the best care in any patient with LC. Time and sufficient resources; leadership; administrative and institutional support; and recording of activity are key factors for the success of LC-MDTs. A set of excellence requirements in terms of staff, resources and organization of the LC-MDT have been proposed. At last, a list of quality indicators has been agreed to achieve and measure the performance of current LC-MDTs.

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