Rapid-Learning System for Cancer Care

Abernethy, Amy P.; Etheredge, Lynn; Ganz, Patricia A.; Wallace, Paul; German, Robert R.; Neti, C.; Bach, Peter B.; Murphy, Sharon B.

doi:10.1200/jco.2010.28.5478

Cited by 327 publications

(223 citation statements)

References 22 publications

(4 reference statements)

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“…Many of our healthcare providers already feel this impatience. But we must find ways to act on this sense through agility and disruptive innovation if we are to demonstrate a rapid learning health system [1,7,26]. The design of an implementation registry that could link together practitioners with common challenges is an enormous undertaking requiring a progressive vision.…”

Section: Discussionmentioning

confidence: 99%

If we only knew what we know: principles for knowledge sharing across people, practices, and platforms

Dearing

Greene

Stewart

et al. 2011

Behav. Med. Pract. Policy Res.

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The improvement of health outcomes for both individual patients and entire populations requires improvement in the array of structures that support decisions and activities by healthcare practitioners. Yet, many gaps remain in how even sophisticated healthcare organizations manage knowledge. Here we describe the value of a trans-institutional network for identifying and capturing how-to knowledge that contributes to improved outcomes. Organizing and sharing on-the-job experience would concentrate and organize the activities of individual practitioners and subject their rapid cycle improvement testing and refinement to a form of collective intelligence for subsequent diffusion back through the network. We use the existing Cancer Research Network as an example of how a loosely structured consortium of healthcare delivery organizations could create and grow an implementation registry to foster innovation and implementation success by communicating what works, how, and which practitioners are using each innovation. We focus on the principles and parameters that could be used as a basis for infrastructure design. As experiential knowledge from across institutions builds within such a system, the system could ultimately motivate rapid learning and adoption of best practices. Implications for research about healthcare IT, invention, and organizational learning are discussed.

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Section: Discussionmentioning

confidence: 99%

If we only knew what we know: principles for knowledge sharing across people, practices, and platforms

Dearing

Greene

Stewart

et al. 2011

Behav. Med. Pract. Policy Res.

View full text Add to dashboard Cite

show abstract

“…It is proposed that health information systems that are more synchronized and adaptable to the pace of increasing evidence will enable real-time implementation of clinical decision support systems, improve the quality of patient care, and enhance clinical research efforts including data mining. Such systems will be dependent on widespread adoption of electronic health records and standardization of terminology related to clinical and laboratory measures across platforms and resolution of issues around data governance and patient confidentiality [22][23][24]. Nevertheless, data emerging from such systems are observational in nature with many of the same limitations, including missing values and confounding by factors related to both treatment selection and clinical outcome.…”

Section: Rapid Learning Health Systemsmentioning

confidence: 99%

Comparative Effectiveness Research in Oncology

Lyman

2013

The Oncologist

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Although randomized controlled trials represent the gold standard for comparative effective research (CER), a number of additional methods are available when randomized controlled trials are lacking or inconclusive because of the limitations of such trials. In addition to more relevant, efficient, and generalizable trials, there is a need for additional approaches utilizing rigorous methodology while fully recognizing their inherent limitations. CER is an important construct for defining and summarizing evidence on effectiveness and safety and comparing the value of competing strategies so that patients, providers, and policymakers can be offered appropriate recommendations for optimal patient care. Nevertheless, methodological as well as political and social challenges for CER remain. CER requires constant and sophisticated methodological oversight of study design and analysis similar to that required for randomized trials to reduce the potential for bias. At the same time, if appropriately conducted, CER offers an opportunity to identify the most effective and safe approach to patient care. Despite rising and unsustainable increases in health care costs, an even greater challenge to the implementation of CER arises from the social and political environment questioning the very motives and goals of CER. Oncologists and oncology professional societies are uniquely positioned to provide informed clinical and methodological expertise to steer the appropriate application of CER toward critical discussions related to health care costs, cost-effectiveness, and the comparative value of the available options for appropriate care of patients with cancer. The Oncologist 2013;18:752-759 Implications for Practice: Escalating health care costs, largely driven by expensive new technologies and therapies, have prompted calls for more rigorous assessment of the effectiveness, safety, and overall value. At the same time, the time and resources required for large randomized controlled trials, as well as their recognized limitations, necessitate consideration of other forms of comparative effectiveness research for evaluating meaningful clinical outcomes. Through the results derived from selective and appropriate use of a range of comparative effectiveness methodological tools, clinicians, patients, payers, and policy makers can make more rationale choices in selecting the most appropriate, efficient, and cost-effective cancer care. At the same time, practicing oncologists and other stakeholders must be aware of the challenges presented by such research approaches as well as the considerable progress that has been made in addressing these limitations in order to appropriately weigh the totality evidence on critical health care issues in every day oncology practice. INTRODUCTIONComparative effectiveness research (CER) attempts to compare the benefits and harms of alternative strategies for diagnosing, treating, or preventing disease in patients. Driven primarily by new therapies and technologies, health care expenditures c...

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“…genomics, blood tests, imaging, and this growing complexity cannot be tackled only by human brain [3]. In addition, with the continuous development of medicine, many therapeutic options are now available.…”

Section: Perspectivesmentioning

confidence: 99%

Personalized Medicine in Prostate Cancer: Future Perspectives for Tailored Treatments

AR¹

2015

JCPCR

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Best future standard of care will be the identification of "tailored" treatments, based on the specific cancer patient's characteristics, race differences and habits or regional backgrounds, or clinical aspects, etc. The development of tools that allow and support the decision-making process to deliver tailored treatment is crucial as medicine and in particular cancer disciplines move towards the era of individualized medicine. This aim is proposed by designing, developing and testing a framework to represent data in a re-usable way for building automatically Decision Support Systems based on extrapolated predictive models.Extracting the main features from classical and innovative data, DSS will be able to provide a practical support to clinical choices in cancer matter. A multidisciplinary integration with different professionalisms beside the clinicians is a necessary step to follow this important issue. Keywords:

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Rapid-Learning System for Cancer Care

Cited by 327 publications

References 22 publications

If we only knew what we know: principles for knowledge sharing across people, practices, and platforms

If we only knew what we know: principles for knowledge sharing across people, practices, and platforms

Comparative Effectiveness Research in Oncology

Personalized Medicine in Prostate Cancer: Future Perspectives for Tailored Treatments

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