Three Essays On Appointment Scheduling In Healthcare Services

The global healthcare systems are facing great challenges.The growing population,improved life quality and aging phenomenon have increased the demand for healthcare resources,making access to healthcare services more difficult.In contrast,the supply of physicians,nurses,hospital beds,and other healthcare resources has been relatively stagnant,and even potentially reduced.Moreover,healthcare systems in many countries often face budget constraints and financing difficulties.Facing the dilemma of the rapid increase in healthcare expenditures,the growth of demand for healthcare services and the shortages of resource supplies,operations management provides numerous methodologies and solution techniques to simultaneously reduce costs and improve access to healthcare services.Among the major areas of operations management in healthcare industry,appointment management lies at the intersection of efficiency and timely access to services.It is in the very essential part to relieve issues like patients’ waiting,providers’ overtime working,medical resources wasting and space congestion.This thesis is motivated by these challenges and opportunities,studying three distinct but highly related problems in appointment management.First,we take a data analytics approach and develop the first optimization model to determine the optimal appointment schedule in the presence of potential walk-ins.Our model is the first known approach that can jointly handle general walk-in processes and heterogeneous,time-dependent no-show behaviors.We demonstrate that,with walk-ins,the optimal schedules are fundamentally different from those without.Our numerical study reveals that walk-ins introduce a new source of uncertainties to the system and cannot be viewed as a simple solution to compensate for patient no-shows.Scheduling,however,is an effective way to counter some of the negative impact from uncertain patient behaviors.Using data from practice,we predict a significant cost reduction(42%-73% on average)if the providers were to switch from current practice(which tends to overlook walk-ins in planning)to our proposed schedules.After solving the first problem,it is natural to consider what if the walk-in behavior is not exogenous.And the second part of this thesis is to study appointment capacity management problem with strategic(i.e.,endogenous)patient walk-in behavior.We develop the first stylized model where a strategic patient has three choices: schedule an appointment,walk in,or leave and seek care elsewhere(i.e.,balk).The objective of the provider is to minimize the expected total daily costs,by reserving the right level of daily capacity for both appointments and walk-ins,respectively,in anticipation for patient strategic choice behaviors.By analyzing the equilibrium patients’ behaviors and optimal provider’s decisions,we investigate the value of delay information and the value of staffing a triage nurse.We show that if it is costly(economic)for unobservable queue to attract all patients to schedule,then it is better to reveal(hide)delay information.We also suggest that if the lost demand cost is large,staffing a triage nurse is valueless,while when the overtime cost is large,we may need such a gate-keeper.The last research problem considers coordinating appointments in a tandem system.We model daily operations of the multi-stage service process explicitly as a transient tandem queueing system,which fully captures the detailed dynamics in a multi-stage service process.The objective in our model is to minimize the total expected costs,by properly choosing the scheduled arrival times of patients at different stages.And an efficient optimal algorithm and a heuristic with provable performance guarantees are designed along with the model reformulations.We demonstrate that when scheduling appointments in a tandem system,the connections between stages need to be considered.Our analysis also indicates that,for tandem services,some appointments in later stages may need to be strategically postponed to reduce the leisure waiting and some subsequent stations should open late to reduce the idling.Though this work is motivated by healthcare,our models and insights can also be applied to general appointment-based services.