American Journal of Respiratory and Critical Care Medicine

In order for patients to reap the benefits of bench and clinical research, we must develop effective strategies that translate this knowledge into clinical practice. Delivering quality care to patients has two goals: increasing the likelihood of desired health outcomes and ensuring concordance with current evidence (1). Quality improvement is the scientific discipline that accompanies this so-called T3 activity, focusing on the structures, processes, and outcomes of healthcare delivery (2). A primary motivator of quality improvement is the reduction of medical error, which has emerged as a major problem in modern healthcare, estimated to cause up to 98,000 preventable hospital deaths in the United States each year at a cost of $17–29 billion (3). The ICU poses unique challenges to effective healthcare delivery and is an ideal setting for rigorous quality improvement inquiry.

Changes in the structure of care, such as the institution of an intensivist model for critical care, and improvements in the process of care have led to significant improvements in health care outcomes (4). These strategies need not be complex. For example, a checklist is a simplification tool that coalesces a large slice of the ICU (e.g., central venous catheter insertion techniques, physician education, nurse–physician communication, data collection systems) into an actionable problem. Despite their apparent simplicity, checklists have proven remarkably effective at improving multiple healthcare outcomes, from reducing catheter-related bloodstream infections to enhancing provider communication (5).

While the randomized controlled trial (RCT) is widely given the highest grade of evidence, RCTs in the ICU may be impractical, and data derived from them are often lacking (6). Indeed, most published quality improvement research employs an observational design (7). Even when the evidence is strong, widespread implementation of a quality improvement intervention is often suboptimal. Clinical practice guidelines are meant to standardize medical care according to the best available evidence, yet compliance with these guidelines in clinical settings is poor (8). As a result, many opportunities to improve outcomes in critically ill patients are missed (9).

One approach to improve healthcare delivery in the intensive care unit is to adopt quality improvement strategies that have proven effective in industry. One of the fathers of modern industrial quality improvement, W. Edwards Deming, employed an early form of complex system analysis to generate the Plan-Do-Study-Act cycle for understanding and improving the performance of organizations and processes (10). This and other industry-derived approaches, such as Six-Sigma and Toyota Production Systems' LEAN thinking, have been employed successfully in many healthcare settings (11).

Healthcare, however, differs from industrial settings in several fundamental ways, including its global scale and complexity, the importance placed on experimental evidence, and clinical and experiential—as opposed to operational—value (12). We contend that complex system analysis offers one promising approach to address these problems. In general, a complex system contains a vast number of interrelated and interacting elements with fluid governing rules, and displays organization without an organizing principle (13). Complex system analysis has been used to model far-ranging systems such as human correspondence activity (14).

In healthcare, complex system research has led to significant new insights in areas such as ICU monitoring (15). For example, investigators have used complex system analysis to generate bioinformatics systems that detect variations in a system of clinical variables from their steady-state values to more promptly identify clinically meaningful changes (16). Clinical decision support is another area in which complex system analysis can lead to improvements in critical care quality. Recently, investigators have focused not only on data integration but on its transmission to the appropriate decision maker (17).

Properly addressing these challenges will require the commitment of substantial resources. Unfortunately, funding for quality improvement research in healthcare is low compared with that of other industries. The Federal Aviation Administration (FAA) levies a 7.5% tax on airline tickets, a significant proportion of which is spent on air traffic control and safety (18). With annual U.S. healthcare spending amounting to approximately $2.3 trillion, the equivalent investment in safety would be on the order of $170 billion (19). The recently increased budget request of the Agency for Healthcare Research and Quality (AHRQ) is $611 million, with only $479 million devoted to the Research on Health Care Costs, Quality, and Outcomes program (20). Health care advocates and legislators have considered tying reimbursements to quality outcomes, notifying consumers of standardized outcomes by hospital or provider, federally mandated safety standards, and increased federal funding for quality research as mechanisms to encourage the industry to fully fund and implement quality improvement programs.

In summary, the ICU is a complex system that must be considered more than the sum of its parts. With an aging population and an explosion of data, the ICU will become ever more complex, and the critically ill more susceptible to medical error. While quality improvement science has led to significant advances, significant limitations persist. Innovative points of view such as a complex system approach, a renewed focus on implementation, and increased funding will be needed to advance the field. The implementation of new knowledge gained from the bench and from clinical trials requires a high-performance healthcare delivery system that can rapidly and efficiently bring these advances to the bedside.

1. Lohr KN, Donaldson MS, Harris-Wehling J. Medicare: a strategy for quality assurance. V: Quality of care in a changing health care environment. QRB Qual Rev Bull 1992;18:120–126.
2. Dougherty D, Conway PH. The “3T's” road map to transform US health care: the “how” of high-quality care. JAMA 2008;299:2319–2321.
3. Kohn LT, Corrigan JM, Donaldson MS. To err is human: building a safer health system. Washington, DC: National Academy Press; 1999.
4. Pronovost PJ, Angus DC, Dorman T, Robinson KA, Dremsizov TT, Young TL. Physician staffing patterns and clinical outcomes in critically ill patients: a systematic review. JAMA 2002;288:2151–2162.
5. Hales BM, Pronovost PJ. The checklist–a tool for error management and performance improvement. J Crit Care 2006;21:231–235.
6. Vincent JL. We should abandon randomized controlled trials in the intensive care unit. Crit Care Med 2010;38:S534–S538.
7. Alexander JA, Hearld LR. What can we learn from quality improvement research? A critical review of research methods. Med Care Res Rev 2009;66:235–271.
8. Cabana MD, Rand CS, Powe NR, Wu AW, Wilson MH, Abboud PA, Rubin HR. Why don't physicians follow clinical practice guidelines? A framework for improvement. JAMA 1999;282:1458–1465.
9. Sinuff T, Cook D, Giacomini M, Heyland D, Dodek P. Facilitating clinician adherence to guidelines in the intensive care unit: a multicenter, qualitative study. Crit Care Med 2007;35:2083–2089.
10. Best M, Neuhauser D. W. Edwards Deming: father of quality management, patient and composer. Qual Saf Health Care 2005;14:310–312.
11. Varkey P, Reller MK, Resar RK. Basics of quality improvement in health care. Mayo Clin Proc 2007;82:735–739.
12. Young TP, McClean SI. A critical look at lean thinking in healthcare. Qual Saf Health Care 2008;17:382–386.
13. Amaral LAN, Ottino JM. Complex networks: augmenting the framework for the study of complex systems. Eur Phys J B 2004;38:147–162.
14. Malmgren RD, Stouffer DB, Campanharo AS, Amaral LA. On universality in human correspondence activity. Science 2009;325:1696–1700.
15. Seely AJ, Macklem PT. Complex systems and the technology of variability analysis. Crit Care 2004;8:R367–R384.
16. Goldberger AL, Amaral LA, Hausdorff JM, Ivanov P, Peng CK, Stanley HE. Fractal dynamics in physiology: alterations with disease and aging. Proc Natl Acad Sci USA 2002;99:2466–2472.
17. Hristoskova A, Moeyersoon D, Van Hoecke S, Verstichel S, Decruyenaere J, De Turck F. Dynamic composition of medical support services in the ICU: platform and algorithm design details. Comput Methods Programs Biomed 2010;100:248–264.
18. Federal Aviation Administration. Airport and Airway Trust Fund (accessed October 25, 2010). Available from:
19. Centers for Medicare and Medicaid Services. National Health Expenditure Data (accessed October 25, 2010). Available from:
20. Agency for Healthcare Research and Quality. Budget Estimates for Appropriations Committees, Fiscal Year 2011 (accessed October 25, 2010). Available from:


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