Rapid-learning system for cancer care

Abstract

Compelling public interest is propelling national efforts to advance the evidence base for cancer treatment and control measures and to transform the way in which evidence is aggregated and applied. Substantial investments in health information technology, comparative effectiveness research, health care quality and value, and personalized medicine support these efforts and have resulted in considerable progress to date. An emerging initiative, and one that integrates these converging approaches to improving health care, is "rapid-learning health care." In this framework, routinely collected real-time clinical data drive the process of scientific discovery, which becomes a natural outgrowth of patient care. To better understand the state of the rapid-learning health care model and its potential implications for oncology, the National Cancer Policy Forum of the Institute of Medicine held a workshop entitled "A Foundation for Evidence-Driven Practice: A Rapid-Learning System for Cancer Care" in October 2009. Participants examined the elements of a rapid-learning system for cancer, including registries and databases, emerging information technology, patient-centered and -driven clinical decision support, patient engagement, culture change, clinical practice guidelines, point-of-care needs in clinical oncology, and federal policy issues and implications. This Special Article reviews the activities of the workshop and sets the stage to move from vision to action.

Fig 1.

Cycle of evidence in rapid-learning health care. In a patient-centered system of rapid-learning health care, patient-level data are aggregated to achieve population-based change, and results are applied to care of individual patients to achieve meaningful patient-level practice change.

Fig 2.

Increase in data required for medical decision making relative to human cognitive capacity. PB, petabytes; Yr, year; SNPs, single-nucleotide polymorphisms.

Fig 3.

Health care optimization through use of technology.