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National Academy of Engineering (US) and Institute of Medicine (US) Committee on Engineering and the Health Care System; Reid PP, Compton WD, Grossman JH, et al., editors. Building a Better Delivery System: A New Engineering/Health Care Partnership. Washington (DC): National Academies Press (US); 2005.

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Building a Better Delivery System: A New Engineering/Health Care Partnership.

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Designing Caregiver- and Patient-Centered Health Care Systems

H. Kent Bowen

Harvard Business School

The engineering discipline, with its proclivity for seeing the world as it really is and then designing systems to make things better, offers a good perspective for addressing the dilemma facing our health care systems. Like many people, I was not aware of the chaos on the front lines of the health care system until my 14-year-old son suddenly became gravely ill. Because of a brain aneurysm, he went from an active, vibrant young man to a paralyzed boy within minutes. My wife and I essentially lived at Massachusetts General Hospital for three weeks while a team of “the best of the best” worked to save his life. During that time, I observed how the actual practice of medicine affects patients, and it became clear to me that the system was not designed to prevent errors and defects. At one point, because important information was not communicated, a grievous mistake (not directly related to the aneurysm) nearly cost my son his leg. Even though the medical team corrected the error, after I caught it, I wondered how such a mistake could have occurred in the first place. After much thought, I came to the conclusion that the nurses, physicians, and technicians were not at fault. Our ad hoc system for delivering health care conspires against the best intentions of care providers, making it extremely difficult for them to provide patient-centered, defect-free care.

Many industries have revolutionized their approaches to deliver products and services that are more customer centered, high quality, and cost effective. The automotive industry, for example, has made dramatic improvements to avoid both design and production failures. Toyota, in particular, has an operating system that delivers award-winning quality year after year. Toyota's system is designed to bring problems to light, resolve them, and improve the system to ensure that the problems are not repeated and that the organization learns. Toyota's approach helps frontline workers (as well as all others) be successful, as defined by the customer's (or patient's) needs. The goal is “defect-free operations” and learning (Spear and Bowen, 1999).

Based on examples from industry, a young colleague of mine, Professor Steven Spear, developed a case study to determine the applicability of systems-thinking to health care. He engaged a former medical administrator and surgeon, Dr. John Kenagy, to work with leaders of a small community hospital in the Boston area. Like most people in the medical profession, the dedicated hospital staff wanted to provide the best care. He initially focused on a system for the administration of medications using the Toyota production system (TPS) as a model for defect-free operations. First, he taught Dr. Kenagy to look at the hospital through the TPS lens. Early on, he discovered that not only does the medical staff itself not fully understand its system for providing care, but also that the staff was not equipped with the tools, processes, or organizational structure to solve problems (Spear, 2001; Spear and Kenagy, 2000a,b).

Anita Tucker, a doctoral student at the time (now an assistant professor at the Wharton School, University of Pennsylvania), expanded the initial findings with studies of nursing care in 20 additional hospitals. Her studies revealed that nurses' care of patients was constantly interrupted because of system failures (Tucker, 2003). Nurses are trained to evaluate and diagnose patients and administer a care plan based on a physician's recommendation. Over the course of a shift, however, nurses spent only 33 to 50 percent of their time caring for patients. The rest of the time, they were searching for information, equipment, or materials or correcting mistakes. Thus, they spent most of their time compensating for the faulty system, becoming frustrated and cynical of management's work design and rules.

The current design of most hospital work systems is disrespectful to both patients and frontline caregivers, as evidenced by the high turnover of nurses and the complaints of patients. Think about the service you receive at the best commercial establishments and compare that with the service you receive when you are admitted to a hospital. One reason for the difference is the constant and conflicting demands on hospital service personnel and caregivers. For example, a typical nurse, in a single hour, works in eight different physical locations, makes 22 location changes among those eight places, has conversations with 15 partners on 25 different topics, while taking care of five patients in three rooms (Spear and Kenagy, 2000a). If one of the patients requires critical care, which means following strict care guidelines, it is nearly impossible for the nurse to follow the care plan. The critical-care routines are constantly interrupted because of wrong medications, faulty equipment, poor information, or requests to assist colleagues.

Observations of the flow of information necessary to patient care revealed other problems. Information that originates at the patient (e.g., the patient's insurance provider, family history, medications, medical history, symptoms, etc.) flows along many pathways to physicians, nurses, and pharmacies. In spite of large investments in information technology, getting the correct information to the people who need it when they need it is very problematic. Any of the pathways over which critical information flows can be blocked, and there is a high probability that this will happen on a daily basis. If the medication-administration pathway breaks down, for example, the medication will not be administered in the right dose at the right time under the right conditions. The medication error rate has been shown to be in the parts-per-hundred range (Bates et al., 1995). The most frequent failures occur between shifts.

Most hospitals do not have defect-free standards for exchanges of information. Anita Tucker identified the best hospitals from her pool of 20 for more detailed analysis of this problem. Her study showed that even at facilities renowned for the high quality of their nursing care, the work of a frontline caregiver is filled with interruptions and poor information flow. When she asked why health care workers “live this way,” she concluded that most of them actually expect the work system to be defective. Because problems often cross organizational boundaries or are so complex a single person cannot hope to eliminate the root cause, they expect to have to “work around” problems (Tucker et al., 2002).

In hospital after hospital, because no resources have been allocated for solving problems, health care workers confront the same problems every day. At this point, the health care system is incapable of fixing itself. This is a significant contrast to a Toyota factory where improvements are made continuously in the course of accomplishing daily work, crossing organizational boundaries if necessary, sending problems to the appropriate management level (Spear and Schmidhofer, 2005).

We did find some medical facilities that have designed systems to reduce defects, improve the work systems of frontline caregivers, and improve the patient experience. For example, we studied an eye surgery clinic in Boston with 18 top ophthalmic surgeons (Miguel and Bowen, 1997). One of the surgeons, Dr. Barry Shingleton, was three times as productive as other surgeons in terms of time spent performing similar surgeries. When Dr. Shingleton was designing his diagnostic and surgical procedures, he had turned to the business literature for guidance. His service model is centered on the patient experience, from the first encounter through post-surgical follow-ups. In addition, he collects outcomes data much more rigorously than his colleagues as feedback for improving procedures and processes. He developed his own patient scheduling algorithm to improve service and efficiency, and he schedules simpler procedures earlier in the day to minimize disruptions and delays. He also eliminated unnecessary variabilities during surgery by standardizing procedures. For example, to reduce changeover time between surgeries, he maintains contact with the anesthesiologist prepping the next patient; in this way, he has been able to reduce the time between the administration of the drug and the beginning of surgery by as much as 50 percent. More important, as a result of his efficiency, his patients experience less surgical trauma, which speeds the healing process.

In a more recent study, we looked at Intermountain Health Care, where doctors, under the leadership of Dr. Brent James, have applied the entire quality-management concept to the hospital's functions (Bohmer et al., 2002). The study was focused on two intensive care units (ICUs) located next to each other in LDS Hospital in Salt Lake City (Tucker et al., in progress). We found that, even though the hospital had developed an overarching quality system, frontline care was administered differently in the two units. In addition to some structural differences, the medical directors of each ICU had different design models for operating their units. In one ICU, problem solving was more prevalent, especially root-cause elimination (much like Toyota's TPS). This ICU also stressed patient-centered care: the number of admitting physicians was small; interns spent more time on the rotation; a nurse manager was available to assist in problem solving and problem prevention; and the unit developed and used more medical protocols. In the second ICU, the quality of care was also very high, but operations were more physician centered: because there was a different set of patients, there were more admitting physicians; by design, interns spent less time on this rotation; no nurse manager was available for problem solving; the unit had fewer protocols and did not generate any of its own. To further learning at LDS, the two ICU medical directors have now exchanged positions, which should provide a wonderful natural test of how much the differences relate to design choices and how much they relate to differences in the patient mix, structure, etc.

A recent study at the Pittsburgh Regional Health Initiative demonstrates what can be achieved with a systematic approach to redesigning work systems. In one study, the goal was to eliminate central-line-associated bloodstream infections using techniques like those practiced at Toyota. By implementing simple but elegant tools and devices, transmissions of infection were reduced dramatically. In 2003, Allegheny General Hospital's MICU and CCC (Cardiac Critical Care) Units had 37 patients who suffered central-line-associated bloodstream infections, 19 of whom died. In 2004, there were six infected patients, one of whom died (Shannon et al., in progress).

Solutions to the health care problem are being offered from many directions. Our own suggestions are based on the perspectives of the patient and frontline caregiver. We can summarize what we learned through direct observation of how frontline caregivers do their work:

  • Most hospitals have evolved complex work systems that conspire against defect-free health care.
  • Caregivers have come up with “work arounds” and other ineffective approaches to solving problems. Frontline workers spend a significant fraction of their time doing nonvalue-added work caused by fundamental failures in the design of work systems.
  • The delivery of patient-centered care by nurses and other frontline caregivers is limited under current work systems designs.
  • Systems approaches perfected by industrial corporations (e.g., Toyota's TPS) appear to provide useful models for improving health care work systems.

The challenge for engineers and managers outside the health care system is to bring the lessons learned in other settings to clinics and hospitals.

REFERENCES

  1. Bates DW, Boyle DL, Vander Vliet MB, Schneider J, Leape L. Relationship between medication errors and adverse drug events. Journal of General Internal Medicine. 1995;10(4):199–205. [PubMed: 7790981]
  2. Bohmer R, Edmondson AC, Feldman LR. Cambridge, Mass: Harvard Business School Publishing; 2002. Intermountain Health Care. HBS Case No. 603-066.
  3. Miguel MF, Bowen HK. Cambridge, Mass: Harvard Business School Publishing; 1997. Ophthalmic Consultants of Boston and Dr. Bradford J. Shingleton. HBS Case No. 697-080.
  4. Shannon RP, et al. Cambridge, Mass: Harvard Business School Publishing; Eliminating Central Line Infections in Two Intensive Care Units: Results of Real-time Investigation of Individual Problems. In progress. Harvard Business School Working Paper.
  5. Spear S. Cambridge, Mass: Harvard Business School Publishing; 2001. Deaconess-Glover Hospital (C) HBS Case No. 602-028.
  6. Spear SJ, Bowen HK. Decoding the DNA of the Toyota Production System. Harvard Business Review. 1999 September-October:96–106. HBS Case No. 99509.
  7. Spear S, Kenagy J. Cambridge, Mass: Harvard Business School Publishing; 2000a. Deaconess-Glover Hospital (A) HBS Case No. 601-022.
  8. Spear S, Kenagy J. Cambridge, Mass: Harvard Business School Publishing; 2000b. Deaconess-Glover Hospital (B) HBS Case No. 601-023.
  9. Spear SJ, Schmidhofer M. Ambiguity and workarounds as contributors to medical error. Annals of Internal Medicine. 2005;142(8):627–630. [PubMed: 15838069]
  10. Tucker AL. Harvard University; Cambridge, Massachusetts: 2003. Organizational Learning from Operational Failures. Unpublished dissertation.
  11. Tucker A, Bowen HK, LaPierre BC. Cambridge, Mass: Harvard Business School Publishing; Quality Improvement in Intensive Care at LDS Hospital. In progress. HBS Case No. 604-071.
  12. Tucker AL, Edmondson AC, Spear SJ. When problem solving prevents organizational learning. Journal of Organizational Change Management. 2002;15(2):122–137.
Copyright © 2005, National Academy of Sciences.
Bookshelf ID: NBK22860
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