Using Models to Validate Changes to Healthcare Processes
Written by: Kristyna Culp, Freeman White and Michelle Mader, Freeman White
A model in its simplest form is a preview of coming construction. Chefs model their meals with menus and recipes. Software teams use flowcharts as models for applications that may entail hundreds of thousands of lines of code. Architects, who once modeled their buildings with foam board, continue today with 3D renderings and building information modeling (BIM) applications that provide exquisitely detailed visualizations of projects. Models are critical to decision making because they provide a focus for discussion and analysis before an organization commits its future to an expensive and time-consuming project. However, models can do much more than show a static preview.
In the healthcare world, static modeling of buildings can help architects anticipate construction costs and manage schedules, but this type of modeling does not necessarily create the most efficient workspaces for doctors and nurses, as well as inpatients, outpatients and emergency room patients. To add this dynamic capability, design teams are expanding their toolkits to include a new kind of modeling. Process modeling creates interactive simulations that incorporate the behavior and procedures of the staff who work in the physical environment as well as the behaviors of the patients and families they serve.
What Insights Can Be Learned From a Model?
Hospital administrators and boards have been adapting to change for decades. Today, more than ever before, their industry faces a cascade of astounding advances in medical technology, new trends in patient preferences, and changes in public policy, such as the Affordable Care Act. To survive in a competitive market, the question is not whether to change, but how to change. Should the planners renovate an existing facility floor by floor or department by department? Should they add new wings to accommodate new services? Or should they rebuild from the ground up? Is the real bottleneck a process issue rather than a physical design issue? In making these decisions, a model is their first line of defense because it helps them evaluate the benefits and the risks of each strategy.
Compiling a Baseline
A process modeling team first builds a model of existing processes so that it can then intelligently evaluate the range of changes that will be proposed. Modeling applications can represent any kind of health care facility whether it is an emergency department, inpatient units or ambulatory medical home care. Models are as useful for planning outpatient surgery and ambulatory care as they are for family waiting rooms. Because process models are dynamic, they can show a patient’s entire journey throughout a given course of diagnosis or treatment. They tell the story that begins when the patient enters a department and checks in, waits for services, registers, undergoes an examination or treatment, interacts with clinicians, transfers to other departments, and exits the facility.
Modeling begins by compiling a baseline of data obtained from a particular site. In this first phase, its input must include a thorough and accurate description of how a facility and its staff work in the present-day world: current patient volumes, types of patients, staffing levels, shift times for physicians, nurses, and support staff. Equally important for the baseline are sequences and durations. How long does it take for a patient arriving at the emergency room door to move through triage, see a doctor, receive treatment, and leave the emergency room for an in-patient bed? How much time does it take to conduct lab tests or to move a patient to and from an imaging department? Any of these stops on the patient’s journey, which might involve delays today, could become an opportunity to improve tomorrow’s operational flow and facility procedures.
From As Is to What If?
After incorporating into the baseline model all of the standard diagnostic and treatment procedures along with their sequences and average durations, the modeler is ready to create the baseline simulation model, which will explain how a change of a single quantity or duration could affect the functionality of the facility assuming that other conditions remain unchanged from their baseline values. Suppose that an emergency department typically serves 50,000 patients per year. At this site hospital administrators have projected that the demand for emergency department services will increase to 75,000 patients per year. The simulation plugs the forecasted numbers into the model and calculates their effect on emergency department operations. It will illustrate the stress on hospital efficiency and quality as the patient volume increases.
Emergency departments also depend on other departments. The simulation will also show the cascading effect of the change on these other areas. With 25,000 more patients per year arriving in the emergency department, the model will calculate the increasing number of patients requiring procedures in the imaging department and the lab and requiring in-patient beds.
Process Modeling Builds Consensus
A process model’s credibility absolutely depends on the accuracy of its baseline depiction of present operations. Before looking at simulations, the stakeholders must confirm that the model “understands” how their current hospital system actually works, as opposed to how it might be imagined to work in an ideal world. If they cannot agree on the model’s picture of present-day reality, any simulations based on that picture will be unconvincing. Thus, stakeholder buy-in on the baseline model is critical.
After baseline signoff is achieved, the stakeholders can begin to visualize the realities of change. A simulation allows them to see a realistic representation of how changes in physical layout, placement of services, staffing, and procedures—in isolation or in any logical combination—will alter the world in which they and their staff and patients have been working. When the realities of the simulation results begin to sink in, the model emphasizes the need for training programs that help the staff and physicians to make the transition to a new work culture. Cultural resistance is a stumbling block that can defeat even the most brilliant improvements in hospital operations. Years of habit formation inevitably generate a natural fear of cultural change. Fortunately, medical personnel are trained to respect and accept information based on facts. However, they may need to be reminded of the assumptions they signed off on at the beginning. They will, with fact-based encouragement, eventually embrace changes that clearly promote their own job satisfaction and the wellbeing of their patients. This fact leads to the third strong suit of process modeling.
Process modeling also quantifies the effects of change. Because it systematically introduces into its simulations the most reliable information about future trends in technology, patient preferences, and public policy, its depictions of the future are believable to even the most skeptical of stakeholders, especially when the model shows quantifiable evidence of shorter travel times, fewer frustrating delays, and less time spent on non-patient care.
Most effectively, process modeling incorporates repeated (or iterative) cycles of data compilation and simulation based on a consensus of future trends and needs, and reality testing of new structures and processes as they are put into practice. Does the new world, as built, match the forecasts of the simulated world? If there is no practical way to overcome obstacles, the model can be updated as many times as necessary. Do certain staff members refuse to change their behavior? The model can simulate alternative paths to work around them.
Correlations Reveal Surprising Discoveries
Most administrators know their data from a bird’s eye view, but important correlations often go unnoticed and are still typically ignored by many analyst consultants. Finding and quantifying correlations can lead to higher productivity and job satisfaction. To take an obvious example, allowing a physician to focus on the most critical patients and channeling less critical patients to practitioners or nurses can increase the physician’s satisfaction, productivity and overall efficiency.
A more subtle case is that of “frequent fliers”—patients who show up consistently. A process model can document how each aspect of these patients’ treatment impacts others. By correlating a set of related statistics—number of visits, lack of communication, time between visits, triage of patient calls to nurses, repeat visits to the pharmacy after each visit, and lack of medication reconciliation—it was found that patients get healthier faster and stay healthier longer when clinics use an operational model that treats the entire disease in a preventive way rather than by addressing acute episodic symptoms and effects in isolation as they arise.
Disease-based focus, which is emphasized by the Affordable Care Act, will drive costs down and improve patient outcomes because this operational model frames its treatment plans around systemic disorder. Diabetes offers a convincing case study. A diabetic patient typically sees several different doctors within the same system each month. By collocating these physicians in a diabetes treatment center, communication about procedures and prescriptions is improved. The frequency of visits goes down because that patient can be seen by all the necessary providers during a single visit. The repercussions of the disease—a patient’s gangrenous foot or loss of vision—are no longer treated on a piecemeal basis. Instead, the patient is encouraged to make lifestyle changes that will ultimately lower the risks of these repercussions. Time and money are saved and the patient’s health outlook improves.
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