Organizing Multidisciplinary Care for Children with Neuromuscular Diseases

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. These patients 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 visited 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 article describes how quantitative modelling supports the design and operations of the CMCA. First, an integer linear program is presented that selects which patients to invite 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 to study to estimate the capacity of the CMCA, expressed in 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

Flexible nurse staffing based on hourly bed census predictions

Workload on nursing wards depends highly on patient arrivals and patient lengths of stay, which are both inherently variable. Predicting this workload and staffing nurses accordingly is essential for guaranteeing quality of care in a cost effective manner. This paper introduces a stochastic method that uses hourly census predictions to derive efficient nurse staffing policies. The generic analytic approach minimizes staffing levels while satisfying so-called nurse-to-patient ratios. In particular, we explore the potential of flexible staffing policies which allow hospitals to dynamically respond to their fluctuating patient population by employing float nurses. The method is applied to a case study of the surgical inpatient clinic of the Academic Medical Center (AMC) Amsterdam. This case study demonstrates the method's potential to study the complex interaction between staffing requirements and several interrelated planning issues such as case mix, care unit partitioning and size, and surgical block planning. Inspired by the numerical results, the AMC decided that this flexible nurse staffing methodology will be incorporated in the redesign of the inpatient care operations during the upcoming years

Integral resource capacity planning for inpatient care services based on hourly bed census predictions

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 theater 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 (MSS) and arrival patterns of emergency patients. Along these predictions, insight is gained on the impact of strategic (i.e., case mix, care unit size, care unit partitioning), tactical (i.e., allocation of operating room time, misplacement rules), and operational decisions (i.e., 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

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.\ud 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.\ud 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.\u

Patient flow analysis in pain rehabilitation care

Background: Rehabilitation Care is a treatment process that involves multiple disciplines, which are affiliated with different departments and use different planning horizons. This often results in planning difficulties and long waiting lists. In order to increase efficiency the Rehabilitation Centre "Het Roessingh" in the Netherlands has introduced the concept of treatment plans. Purposes: We support Het Roessingh to make their organizational process ready for implementation of treatment plans with the managerial purpose to prospectively assess the consequences of various interventions, without experimenting on the real-world system. Methods: We use mathematical models based on techniques from Operations Research and Management Science. A simulation model is used to analyze the integral impact of proposed organizational solutions on the patient flows. Findings: First, given the number of referrals per week, a necessary number of intake slots is determined in order to satisfy the access time requirements. Second, we quantify capacity losses resulting from cancellations of interdisciplinary meetings,. Third, we conclude that several disciplines are going to form bottlenecks in patient flow once the treatment plans are implemented. Fourth, a balanced staffing rule is computed for each discipline, by which bottlenecks will be avoided and higher efficiency will be achieved,. Finally, we show that the system cannot function at demand/capacity ratios close to 100% because disciplines affect each other. Practice Implications: A sufficient number of intake slots must be planned weekly. The interdisciplinary meetings are of great importance and must have top priority for practitioners. When the treatment plans are implemented, the proposed balanced staffing rule enables a higher efficiency than the current staffing rule. It must be accepted by the management that multidisciplinary care cannot function with 100% efficiency, because of the necessity to buffer for variation in demand, and the interdependency between the disciplines in each patient treatment

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

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

Gastroenteritis in sentinel general practices,The Netherlands.

From 1996 to 1999, the incidence of gastroenteritis in general practices and the role of a broad range of pathogens in the Netherlands were studied. All patients with gastroenteritis who had visited a general practitioner were reported. All patients who had visited a general practitioner for gastroenteritis (cases) and an equal number of patients visiting for nongastrointestinal symptoms (controls) were invited to participate in a case-control study. The incidence of gastroenteritis was 79.7 per 10,000 person years. Campylobacter was detected most frequently (10% of cases), followed by Giardia lamblia (5%), rotavirus (5%), Norwalk-like viruses (5%) and Salmonella (4%). Our study found that in the Netherlands (population 15.6 million), an estimated 128,000 persons each year consult their general practitioner for gastroenteritis, slightly less than in a comparable study in 1992 to 1993. A pathogen could be detected in almost 40% of patients (bacteria 16%, viruses 15%, parasites 8%)

NUMERIČKO INTEGRIRANJE KOD IZRAČUNA VOLUMENA NEPRAVILNIH ANTIKLINALA

The volume of geological structures is often calculated by using the definite integral. Though in some cases the integral can be solved analytically, in practice we usually approximate its value by numerical integration techniques. The application of definite integral in volume calculation is illustrated by two examples. The volume of Mount Fuji, the world-known “conic” geomorphological structure, is calculated by analytical integration. Two basic numerical integration methods, that is, the trapezoidal and Simpson’s rule are applied to subsurface hydrocarbon reservoir volume calculation, where irregular anticline is approximated by a frustum of a right circular cone.Pri izračunavanju volumena geoloških struktura često se koristi određeni integral. Iako se u nekim slučajevima integral može riješiti analitički, u praksi se njegova vrijednost obično procjenjuje koristeći tehnike numeričke integracije. Primjena određenog integrala u izračunavanju volumena ilustrirana je dvama primjerima. Volumen planine Fuji, koja je svjetski poznati geomorfološki primjer “stožaste” strukture, izračunat je analitičkom integracijom. Dvije temeljne metode numeričkog integriranja, tj. trapezno i Simpsonovo pravilo, primijenjene su na izračun volumena ležišta ugljikovodika, gdje je struktura nepravilne antiklinale aproksimirana pravilnim krnjim stošcem