Question

Review and summarize two published journal articles about “patient itinerary optimization” in a table. Pick two of these models and describe them in detail. The summary should be limited to 1-2 pages pet article.

Answer 1

Article 1: Capacity Distribution Optimization Technique

Destination medical centers are comprised of an integrated suite of specialist services that provide care for a heterogeneous population of patients with different time sensitivities to completing diagnosis and treatment planning, which is called an itinerary of care. In collaboration with one such organization, we develop an earmarked capacity plan that ensures patient itineraries complete before priority-specific deadlines. We develop methods for designing a time-varying capacity allocation scheme for optimizing itinerary completion delays based on patient type and priority. The stochastic optimization that drives this scheme has a large state space, as well as an objective and constraints that are probabilistic and non-convex. We develop tractable solution approaches by decomposing the problem into two stages and then transforming non-linear stochastic patient flow network models into a tractable deterministic optimizations and applying new linearizing approximations. The methodology is demonstrated through an application to improving on-time service completion for national and international patients at a destination medical center. This is a significant factor in these high priority patients’ satisfaction with their visits.

As health care moves toward more consolidation, the resulting outpatient healthcare networks will serve a diverse patient population in terms of conditions treated but also in terms of geography and medical urgency. The Mayo Clinic is an example of such a destination clinic, where patients travel from all over the world to receive diagnosis and treatment from an integrated suite of specialty services. This growing business model leads to new considerations for access to care, as different patients have different time sensitivities to completing all the steps in their diagnosis and treatment process. The care process of diagnosing and developing a treatment plan, often involving several different specialist services, is typically called the patient’s itinerary. Managing itinerary completion deadlines that are differentiated by patient type creates a need for a more sophisticated approach to managing capacity that transcends the first-come-first-served approach that is the prevailing standard in the outpatient environment.

We contribute to the literature by indigenizing the itinerary completion metric as a function of the capacity allocated across the queueing network. By doing so, the objective of maximizing itinerary completion becomes non-linear in the capacity decision variable. This non-linearity, combined with the large state space of the queueing network problem, makes traditional optimization methods intractable. As will be demonstrated, capturing the full distribution on the discrete-time itinerary completion times in a queueing network with time-varying arrivals and capacities is challenging in itself. In this work, we contribute to the literature by developing a phase-type representation of these sojourn times and presenting an alternate, compact form of the traditional phase-type generator that ensures computational tractability. To handle the non-linearity, we develop a heuristic decomposition method and accompanying linearizing approximations that enable the application of linear programming for determining optimal capacities at each service by day of the week.

Article 2: Internet Fitness Organization

Only a handful of the leading medical facilities in the country are equipped to do this type of coordinated scheduling. Even this scenario is only possible if the organization has a centralized scheduling function; otherwise, each appointment is scheduled locally within each practice, which adds an additional layer of overhead for the patient.

If you’ve ever been to a destination wedding, you know that in addition to the schedule itself, there is a significant amount of ancillary information provided to guests, whether it be pre-registration instructions for entertainment options, or driving directions to and from each venue. The same applies to clinical appointments – each visit in a linked appointment set may have pre-visit instructions that the patient needs to follow, such as taking a shower before a Holter monitor placement, since the device needs to stay dry for the duration of the study. The path between visit locations may be non-trivial, so the patient might benefit from simple visuals or instructions for navigating the medical center campus. Typically those instructions are provided to the patient over the phone; a text-based email or snail mail packet might be sent ahead of the visit as well, but often the patient is left to her own devices.

Many disease states and procedures require the coordination of multiple clinical resources, whether human or non-human. For instance, an initial diagnostic visit to a cancer center might involve a set of visits with a medical oncologist, radiologist, and surgical oncologist, as well as multiple tests administered by a nurse using special equipment.

Sometimes there are logistical issues to coordinate, such as the availability of a technician to operate a specific machine, or simply the patient’s physical requirements. For Jane’s mom, she likely had to change into a gown for her electrocardiogram as well as the Holter monitor fitting; instead of changing twice and visiting a lab for a blood draw in between, perhaps she could have been seen in the same consult room by two different clinicians.