Nikky Kortbeek

Taxonomic classification of planning decisions in health care: a structured review of the state of the art in OR/MS

We provide a comprehensive overview of the typical decisions to be made in resource capacity planning and control in health care, and a structured review of relevant articles from the field of Operations Research and Management Sciences (OR/MS) for each planning decision. The contribution of this paper is twofold. First, to position the planning decisions, a taxonomy is presented. This taxonomy provides health care managers and OR/MS researchers with a method to identify, break down and classify planning and control decisions. Second, following the taxonomy, for six health care services, we provide an exhaustive specification of planning and control decisions in resource capacity planning and control. For each planning and control decision, we structurally review the key OR/MS articles and the OR/MS methods and techniques that are applied in the literature to support decision making.

Master surgery scheduling with consideration of multiple downstream units

We consider a master surgery scheduling (MSS) problem in which block operating room (OR) time is assigned to different surgical specialties. While many MSS approaches in the literature consider only the impact of the MSS on operating theater and operating staff, we enlarge the scope to downstream resources, such as the intensive care unit (ICU) and the general wards required by the patients once they leave the OR. We first propose a stochastic analytical approach, which calculates for a given MSS the exact demand distribution for the downstream resources. We then discuss measures to define downstream costs resulting from the MSS and propose exact and heuristic algorithms to minimize these costs.

Erlang loss bounds for OT---ICU systems

In hospitals, patients can be rejected at both the operating theater (OT) and the intensive care unit (ICU) due to limited ICU capacity. The corresponding ICU rejection probability is an important service factor for hospitals. Rejection of an ICU request may lead to health deterioration for patients, and for hospitals to costly actions and a loss of precious capacity when an operation is canceled.There is no simple expression available for this ICU rejection probability that takes the interaction with the OT into account. With c the ICU capacity (number of ICU beds), this paper proves and numerically illustrates a lower bound by an M|G|c|c system and an upper bound by an M|G|c-1|c-1 system, hence by simple Erlang loss expressions.The result is based on a product form modification for a special OT–ICU tandem formulation and proved by a technically complicated Markov reward comparison approach. The upper bound result is of particular practical interest for dimensioning an ICU to secure a prespecified service quality. The numerical results include a case study.

ORchestra: an online reference database of OR/MS literature in health care

We introduce the categorized reference database ORchestra, which is available online at http://www.utwente.nl/choir/orchestra/.

Platelet pool inventory management: theory meets practice

BACKGROUND: The shelf life of platelet concentrates (PCs) is a matter of days. Simultaneously, the demand is highly variable, shortages are not allowed, and producing too many results in outdating. Concurrently, younger PCs, implying an extended time till outdating (TTO), are preferred. Common PC inventory management relies on experience‐based order‐up‐to rules. This study aimed at minimizing outdating and shortages, while extending the TTO through a theoretical approach. It focuses on PCs processed from whole blood donations.

Integral Resource Capacity Planning for Inpatient Care Services Based on Bed Census Predictions by Hour

The design and operations of inpatient care facilities are typically largely historically shaped. A better match with the changing environment is often possible, and even inevitable due to the pressure on hospital budgets. Effectively organizing inpatient care requires simultaneous consideration of several interrelated planning issues. Also, coordination with upstream departments like the operating theatre and the emergency department is much-needed. We present a generic analytical approach to predict bed census on nursing wards by hour, as a function of the Master Surgical Schedule and arrival patterns of emergency patients. Along these predictions, insight is gained on the impact of strategic (ie, case mix, care unit size, care unit partitioning), tactical (ie, allocation of operating room time, misplacement rules), and operational decisions (ie, time of admission/discharge). The method is used in the Academic Medical Center Amsterdam as a decision-support tool in a complete redesign of the inpatient care operations.

Quality-driven efficiency in healthcare

During the upcoming decades, healthcare organizations face the challenge to deliver more patient care, of higher quality, and with less financial and human resources. The goal of this thesis is to help and guide healthcare professionals making their organizations future-proof. Building on techniques from Operations Research, a subfield of applied mathematics, and focusing on the management of operations, the research presented contributes to a better understanding and functioning of healthcare delivery. The outcomes support decision makers in realizing the best possible use of available resources. The work presented intends to make healthcare professionals more aware of the added value of taking an integral perspective on logistical decision making. First, the problems addressed emphasize the importance of integrality in terms of objectives: healthcare must be safe, effective, patient-centered, timely, efficient, and equitable. While the traditional belief is that quality and efficiency always confront each other, we demonstrate that they often can, and must, go hand in hand. Second, the research outcomes show the value of integrality in planning and control: performance is enhanced by aligning long-, medium-, and shortterm decision making and by realizing coordination and collaboration between the various care chain actors. The thesis is organized in six parts. Part I provides a general introduction. Part II provides an overview of the field of resource capacity planning and control in healthcare and a review of the state of the art in Operations Research. It sets up the conceptual framework within which several specific decision problems are studied in the following parts. Part III focuses on facilitating combination appointments during single outpatient visits, and Part IV on multidisciplinary treatments requiring a series of outpatient visits. Part V supports the design and operations of inpatient care services. Part VI builds a theoretical framework to model entire care pathways. In Part III–Part VI, a diversity of operations research techniques (often in combination) is applied: computer simulation, heuristics, Markov processes, mathematical programming, queueing theory, and stochastic Petri nets. Based on the obtained results, in the epilogue we claim that Operations Research can play a key role in addressing the tough logistical challenges healthcare organizations face.

On Dimensioning Intensive Care Units

Due to a limited ICU capacity patients can be rejected at both the Operating Theater (OT) and at the Intensive Care Unit (ICU) within hospitals. The corresponding ICU-rejection probability is an important service factor for hospitals. A simple expression for this probability is not available. With c the ICU capacity (number of ICU beds), this paper provides analytic support for: (i) An M|G|c|c-approximation. (ii) A secure M|G|c−1|c−1 upper bound. The upper bound can be of practical interest so as to dimension the size of an ICU to secure a sufficiently small rejection probability.

A P- and T-invariant characterization of product form and decomposition in stochastic Petri nets

Structural product form and decomposition results for stochastic Petri nets are surveyed, unified and extended. The contribution is threefold. First, the literature on structural results for product form over the number of tokens at the places is surveyed and rephrased completely in terms of T-invariants. Second, based on the underlying concept of group-local-balance, the product form results for stochastic Petri nets are demarcated and an intuitive explanation is provided of these results based on T-invariants, only. Third, a decomposition result is provided that is completely formulated in terms of both T-invariantsandP-invariants.

Organizing multidisciplinary care for children with neuromuscular diseases at the Academic Medical Center, Amsterdam

The Academic Medical Center (AMC) in Amsterdam, The Netherlands, recently opened the ‘Children’s Muscle Center Amsterdam’ (CMCA). The CMCA diagnoses and treats children with neuromuscular diseases. The patients with such diseases require care from a variety of clinicians. Through the establishment of the CMCA, children and their parents will generally visit the hospital only once a year, while previously they used to visit on average six times a year. This is a major improvement, because the hospital visits are both physically and psychologically demanding for the patients. This paper describes how quantitative modelling supports the design and operations of the CMCA. First, an integer linear program is presented that selects which patients are to be invited for a treatment day and schedules the required combination of consultations, examinations and treatments on one day. Second, the integer linear program is used as input to a simulation study to estimate the capacity of the CMCA, expressed in terms of the distribution of the number patients that can be seen on one diagnosis day. Finally, a queueing model is formulated to predict the access time distributions based upon the simulation outcomes under various demand scenarios. Its contribution on the case under study is twofold. First, we design highly constrained appointment schedules for multiple patients that require service from multiple disciplines’ resources. Second, we study the effect of the trade-offs between scheduling constraints and access times. As such, the contribution of this case study paper is that it illustrates the value of applying Operations Research techniques in complex healthcare settings, by designing context-specific combinations of mathematical models, thereby improving delivery of the highly-constrained multidisciplinary care.