How to juggle priorities? An interactive tool to provide quantitative support for strategic patient-mix decisions: an ophthalmology case

Case-Mix Moderation of the Relationship Between OR Performance Metrics and Utilization

We investigated the impact of the case-mix ratio of inpatients to outpatients on the relationships between OR utilization and late starts, turnover time, delays, cancellations, and idle time at an academic medical center in the southeastern United States. After extracting 55 months of data from the surgical repository, we used simple and multiple linear regression models to analyze the data and determine the strength and direction of the relationships among the variables. We compared models comprising proportionally more inpatients to models comprising proportionally more outpatients for each metric to ascertain the effects of case mix on OR utilization. Idle time had the greatest effect on OR utilization, followed by late starts and turnover time. Case mix moderated the relationship between OR utilization and the metrics of cancellations and turnover time. Perioperative leaders may enhance OR utilization by monitoring and addressing idle time and late starts and scheduling an appropriate mix of inpatients and outpatients.

Allocation scheduling leads to optimum utilization of operation theater time

Background

Cancellation of surgeries is a regular phenomenon in any hospital, and reasons may vary from clinical to managerial ones. The aim of the study is to suggest scheduling to address the problem of time over run related cancellations. This is an observational and descriptive study conducted in a tertiary care hospital with ophthalmology facilities. The sample size is calculated with 95% confidence interval using Epi Info 6 from the total surgeries performed in the last 5 years (n = 380). Simple random sampling technique was used.

Methods

Surgical time for all types of ophthalmic surgeries (n = 582) was observed. Allocation of listed cases to the available operating rooms (ORs) was carried out using the observed time using LEKIN software.

Results

The time over-run of 2 h and 6 h was noted for two units, whereas idle OR time was observed in other units. An average idle time of 19% was noted on each day. Reallocation of the cases to the ORs was carried out taking all the planned cases (of both the operating units of the day) as the number of jobs and all the available ORs as parallel machines using LEKIN software. All the planned cases could be accommodated; still, an average of 17% of the total available operation theater (OT) time was found idle on each day.

Conclusions

Planning of cases using procedure time and scheduling on a daily basis using allocation models with simple algorithms can provide optimal utilization of OTs and can address the time over-run and related cancellations.

A two-stage robust optimization approach for the master surgical schedule problem under uncertainty considering downstream resources

This paper addresses a planning decision for operating rooms (ORs) that aim at supporting hospital management. Focusing on elective patients, we determined the master surgical schedule (MSS) on a one-week time horizon. We assigned the specialties to available sessions and allocated surgeries to them while taking into consideration the priorities of the outpatients in the ambulatory surgical discipline. Surgeries were selected from the waiting lists according to their priorities. The proposed approach considered operating theater (OT) restrictions, patients' priorities and accounted for the availability of both intensive care unit (ICU) beds and post-surgery beds. Since the management decisions of hospitals are usually made in an uncertain environment, our approach considered the uncertainty of surgery duration and availability of ICU bed. Two robust optimization approaches that kept the model computationally tractable are described and applied to deal with uncertainty. Computational results based on a medium-sized French hospital archives have been presented to compare the robust models to the deterministic counterpart and to demonstrate the price of robustness.

Case mix planning in hospitals: a review and future agenda

The case mix planning problem deals with choosing the ideal composition and volume of patients in a hospital. With many countries having recently changed to systems where hospitals are reimbursed for patients according to their diagnosis, case mix planning has become an important tool in strategic and tactical hospital planning. Selecting patients in such a payment system can have a significant impact on a hospital's revenue. The contribution of this article is to provide the first literature review focusing on the case mix planning problem. We describe the problem, distinguish it from similar planning problems, and evaluate the existing literature with regard to problem structure and managerial impact. Further, we identify gaps in the literature. We hope to foster research in the field of case mix planning, which only lately has received growing attention despite its fundamental economic impact on hospitals.

A framework to analyze hospital-wide patient flow logistics: evidence from an Italian comparative study

Through a comparative study of six Italian hospitals, the paper develops and tests a framework to analyze hospital-wide patient flow performance. The framework adopts a system-wide approach to patient flow management and is structured around three different levels: (1) the hospital, (2) the pipelines (possible patient journeys within the hospital) and (3) the production units (physical spaces, such as operating rooms, where service delivery takes places). The focus groups and the data analysis conducted within the study support that the model is a useful tool to investigate hospital-wide implications of patient flows. The paper provides also evidence about the causes of hospital patient flow problems. Particularly, while shortage of capacity does not seem to be a relevant driver, our data shows that patient flow variability caused by inadequate allocation of capacity does represent a key problem. Results also show that the lack of coordination between different pipelines and production units is critical. Finally, the problem of overlapping between elective and unscheduled cases can be solved by setting aside a certain level of capacity for unexpected peaks.