Siebren Groothuis

Simulation as decision tool for capacity planning

In this paper we demonstrate how discrete event simulation technique can be used to optimise the use of catheterization capacity. The patient flow at the catheterization room is described. A simulation model of the current situation was built in MedModel, a discrete event simulation package, and the model was validated. A short presentation of MedModel is given. To investigate alternative ways to optimise the use of the catheterization room three experiments were formulated, modelled and simulated. Two different scheduling strategies were applied to the current situation and the three experimental situations. The number of patients that can be treated and the duration of a working day were determined as measures of performance. The results of the simulation experiments are discussed. The results of these experiments give the management of the catheterization room valuable information how to optimise the use of the catheterization room.

Predicting capacities required in cardiology units for heart failure patients via simulation

The management of a department of cardiology has to plan the capacity of both elective and non-elective patients. Heart failure (HF) patients are admitted to the hospital in a non-elective way. The precision with which the capacity needed for non-elective patients can be predicted determines the degree of flexibility in planning the admission of elective patients. In this study we want to determine how accurately we can predict the bed occupancy of HF patients using a simulation model. Data of the year 2000 were used to obtain the necessary probability distribution functions. Data from the year 2001 were used for determining the prediction accuracy. The results show that the arrival of new HF patients can be adequately predicted. However, the bed occupancy by new and especially current patients is predicted less accurately. Still in 70% (90%) of the days of a 5-day-prediction interval the error is at most one (two) bed(s). The results may improve if the cardiologist is asked to predict the length of stay of the current patients.

Simulation Studies and the Alignment of Interests

Chemotherapy patients are treated with cytostatic drugs. Cytostatic drugs can be produced if ordered or they can be produced to keep in stock. The time that cytostatic drugs can be kept in stock before being spoiled is limited. It is always possible that the patient cannot receive chemotherapy because he/she is not in the right condition. A simulation model is presented which allows to calculate for each combination of patient type and cytostatic drug type the effects on waiting times and costs. In practice actors will behave not as recommended by the simulation model. The cause of the latter is analyzed and solutions are proposed.

Application of computer simulation analysis to assess the effects of relocating a hospital phlebotomy department

Background This study describes a systematic approach to assess the effects of relocating a hospital department. Methods Using the phlebotomy service as an example, computer simulation was applied to predict changes in performance indicators, such as patient turn-around time (TAT), when planning a procedural and/or architectural redesign. Results Average patient TAT fell from 12 to 8 min, enabling the department to cope with any increase in numbers of patients. Conclusion This type of study can provide useful information in assessing the consequences of future changes in the location of a hospital department.

Does Compliance to Patient Safety Tasks Improve and Sustain when Radiotherapy Treatment Processes are Standardized

PURPOSE To realize safe radiotherapy treatment, processes must be stabilized. Standard operating procedures (SOPs) were expected to stabilize the treatment process and perceived task importance would increase sustainability in compliance. This paper presents the effects on compliance to safety related tasks of a process redesign based on lean principles. METHOD Compliance to patient safety tasks was measured by video recording of actual radiation treatment, before (T0), directly after (T1) and 1.5 years after (T2) a process redesign. Additionally, technologists were surveyed on perceived task importance and reported incidents were collected for three half-year periods between 2007 and 2009. RESULTS Compliance to four out of eleven tasks increased at T1, of which improvements on three sustained (T2). Perceived importance of tasks strongly correlated (0.82) to compliance rates at T2. The two tasks, perceived as least important, presented low base-line compliance, improved (T1), but relapsed at T2. The reported near misses (patient-level not reached) on accelerators increased (P < 0.001) from 144 (2007) to 535 (2009), while the reported misses (patient-level reached) remained constant. CONCLUSIONS Compliance to specific tasks increased after introducing SOPs and improvements sustained after 1.5 years, indicating increased stability. Perceived importance of tasks correlated positively to compliance and sustainability. Raising the perception of task importance is thus crucial to increase compliance. The redesign resulted in increased willingness to report incidents, creating opportunities for patient safety improvement in radiotherapy treatment.

Discrete-choice experiments versus rating scale exercises to evaluate the importance of attributes

Aim: To examine the difference between discrete-choice experiments (DCE) and rating scale exercises (RSE) in determining the most important attributes using a case study. Methods: Undergraduate health sciences students were asked to complete a DCE and a RSE. Six potentially important attributes were identified in focus groups. Fourteen unlabelled choice tasks were constructed using a statistically efficient design. Mixed multinomial logistic regression analysis was used for DCE data analysis. Results: In total, 254 undergraduate students filled out the questionnaire. In the DCE, only four attributes were statistically significant, whereas in the RSE, all attributes except one were rated four or higher. Conclusion: Attribute importance differs between DCE and RSE. The DCE had a differentiating effect on the relative importance of the attributes; however, determining relative importance using DCE should be done with caution as a lack of statistically significant difference between levels does not necessarily imply that the attribute is not important.

Shifting stroke care from the hospital to the nursing home: explaining the outcomes of a Dutch case

RATIONALE, AIMS AND OBJECTIVES Supply chains can contribute to better care for stroke patients and more efficiency. However, such outcomes are hampered when links in the chain are weak. The article aims to further the knowledge about the causes and possible improvements of weak links thereby using theory about rules for action and routines (action patterns). METHOD We executed a single case study of a chain of service delivery to stroke patients by a university hospital and a nursing home in the city of Maastricht, the Netherlands. Methods included document study, interviews, observations, process mapping, use of data matrices and performance of t-tests. RESULTS In the case, the care delivery process in the chain was redesigned to improve the flow of patients and to reduce the length of hospital stay. Length of stay was reduced. However, transfer of patients from the hospital to the nursing home was hampered. At this weak link in the chain, the redesign clashed with the routines of hospital paramedics who did not want to work according to the redesign. CONCLUSIONS The applied theory is useful to understand why a link in a supply chain is weak. Negotiations can be used to strengthen a link.

Compliance to technical guidelines for radiotherapy treatment in relation to patient safety

OBJECTIVE To determine the compliance of radiation technologists to technical guidelines in daily practice for radiotherapy treatment and whether there are differences in compliance across organizational units. DESIGN On the basis of consensus, radiation technologists constructed a flowchart describing the work procedure of the irradiation of patients with breast cancer. Using video recordings, technologists in two units were observed to determine whether treatment was conducted in accordance with the flowchart. SETTING Data have been collected on one linear accelerator at the MAASTRO clinic, a radiotherapy clinic in the Netherlands. PARTICIPANTS Fifty-six treatments for breast cancer were analyzed in two treatment units. MAIN OUTCOME MEASURE Percentage compliance to the most important issues for patient safety. RESULTS An overall compliance of 59% (range: 2-100%) was shown on the 18 most important tasks for patient safety. Between the two units, the compliance varied from 21% to 81%. Tasks considered important by independent assessment had higher levels of compliance. CONCLUSIONS Video-taped observation proved to be an effective tool for determining compliance in daily practice. A large variation in practice within and across units was detected by the video observations suggesting a need for standard operating procedures to improve the safety of radiotherapy.

Turn-around time for chemical and endocrinology analyzers studied using simulation.

Abstract Simulation can be a means for the laboratory management to investigate the effects of proposed changes in the laboratory. Also, when specifications of analyzers are available one can investigate which analyzer should be purchased to fulfill existing needs. The potential of simulation is shown here by simulating the turn-around time of batched samples under several conditions. Three routine analyzers (DAX, AXON and Immuno-1) were modeled. The temporal pattern of the arrival of the samples at the different analyzers was determined. The impact of these patterns and the two batching methods on the turn-around time was investigated. Simulation proved to be a useful method to study the effects of batching and arrival patterns on the turn-around time.

Discrete event simulation to support capacity planning for heart failure patients

Patients with heart failure (HF) are admitted to the hospital in a non-elective way. Receiving intravenous medication, they are very limited in their activities of daily living (ADL), resulting in intensive nursing care. To predict the needed capacity, a distinction is made between currently-admitted patients and patients that will be admitted in the near future. Computer simulation is used to predict when new HF patients can be expected and when they will be discharged. The simulation model also provides information about the ADL status of the patients. Former HF patients are used to predict when current HF patients that have already been admitted into the cardiology department will be discharged. The results of tests of both methods are presented and discussed.