Complex Systems and Dynamic Complexity

This blog post is a writing assignment for HIMT 2200: Performance Improvement, part of the Health Information Management Technology (HI13) Associate of Applied Science Degree program at Georgia Northwestern Technical College.

“Instructions: Describe how the following example illustrates one or more of the system characteristics that contribute to dynamic complexity.

Example: Medical Associates is a for-profit medical group of 40 physicians that operates two facilities and offers services in several medical specialties, including cardiology; ear, nose, and throat; family medicine; gastroenterology; general surgery; pediatrics; and obstetrics and gynecology. Medical Associates is open six days a week in each location from 8:00 am until 6:00 pm. Plans are being developed to extend its hours to 9:00 pm two days a week. For several years, Medical Associates discounted its listed fees by 3 percent to 5 percent for its managed care contracts, but a few years ago, it had to accept larger discounts to remain in the networks of health plans. Lower reimbursement led Medical Associates to change its staffing from relying solely on registered nurses (RNs) to hiring medical assistants (MAs) as well. Currently, all physicians assigned to primary care service are assigned one RN or MA to assist with patient care. Physicians assigned to surgery are assigned one RN for every two physicians. As RNs retire or reassign, they have been replaced with MAs. On five recent occasions, when an RN assigned to a junior physician resigned, the senior physician demanded that the RN assigned to a junior physician be reassigned to him and that a new MA be hired to fill the vacancy with the junior physician. This ad hoc system of job switching has caused turmoil between the senior and junior physicians and has led to the subsequent resignation of two RNs who did not want to be reassigned…Confusion exists around staff reporting relationships and who has the authority to change job assignments” (Spath, 2017, p. 44-45).

Medical Associates, a medical practice providing various services, including surgery, began receiving lower reimbursements for medical services. Management made staffing changes by hiring lower-paid medical assistants to replace nurses and save money due to the decreased reimbursements. This management decision demonstrates change, trade-offs, tight coupling, and nonlinearity which are characteristics of dynamic complexity.

The Medical Associates staffing scenario includes change as a characteristic of dynamic complexity. The decision had immediate effects, but this staffing change will continue to be a longer-term issue as staffing changes continue to occur. As nurses retire or resign, the management continues to replace them with lower-paid workers. Also, internal shifts continue as nurses get reassigned to different doctors. The administration created a working environment of continuous change (Spath, 2017, p. 38-39).

The management decided to hire lower-paid medical assistants to reap the benefit of saving money, but this decision has trade-offs. The practice gives up more knowledgeable and experienced nurses for less-skilled workers. In return, the medical practice can use the money it saves to cover other expenses. Some trade-offs are negative and lead to additional problems like a higher turnover rate as nurses began resigning. The practice also risks losing senior doctors who do not want a medical assistant to replace their nurses. According to a survey in 2013, 78 percent of hospitals indicated a shortage of doctors. Sixty-six percent reported a shortage of nurses, while 50 percent reported a lack of physician assistants and nurse practitioners. This survey suggests that a more significant shortage exists for doctors than all levels of nurses. Medical Associates caters to the doctors’ needs and desires over the nurses’ needs because retaining the doctors are more critical than retaining nurses. The issue is ongoing, and the practice will continue to have hiring changes and receive more trade-offs from this decision over time (Spath, 2017, p. 34, 39-41).

The decision to make staffing changes is also an example of tight coupling. When a nurse assigned to a senior physician decides to leave, that doctor is immediately affected by the nurse’s decision. The negative reaction of the senior physician causes a domino effect amongst the staff. The nursing reassignments affected the senior and junior physicians and all the nurses. Tight coupling could be more evident in one department than another, such as those involving surgery and higher skill (Spath, 2017, p. 42-43).

Medical Associates’ decision to cut costs by hiring lower-paid personnel is also an example of nonlinearity. The desired result was to save money by having lower-paid staff. The money then could be used in other ways to offset the loss of income through lower reimbursements. However, some of the consequences of the decision were negative and had a more considerable impact than anticipated. The scale and unpredictability of these consequences make them nonlinear. The staffing choice caused a shift within the practice with nursing reassignments in reaction to the senior physicians’ demands. Some staff became angry, which led to a higher turnover rate. The remaining nurses are likely to have more difficult and stressful jobs as they pick up the slack as other nurses resign and less knowledgeable staff replace them. The medical assistants cannot perform all the nurses’ tasks and duties. The remaining nurses are less likely to remain with lower job satisfaction (Spath, 2017, p. 43-44).

The Medical Associates scenario is a disastrous situation. The characteristics of dynamic complexity like change, trade-offs, tight coupling, and nonlinearity found in this scenario demonstrate how complex the medical environment is and how difficult any decision can be for a healthcare manager.

References

Spath, P. L., & Kelly, D. L. (2017). Applying Quality Management in Healthcare: A Systems Approach. (4th ed.). Chicago, IL: Health Administration Press.

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