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Biomedical subjects

F Dexter

Publications and source records attributed to F Dexter.

At least 37 records · Page 2Linked to original sources
PubMed2000

What is the relative frequency of uncommon ambulatory surgery procedures performed in the United States with an anesthesia provider?

UNLABELLED: Between 1994 and 1996, the National Center for Health Statistics used sophisticated sampling methods to measure the number and types of ambulatory surgery cases performed in the United States. We reanalyzed raw data obtained from this National Survey of Ambulatory Surgery to select cases with an anesthesia provider and here report characteristics of these 228,332 cases (e.g., patient age, anesthetic type). The goal of our study was to estimate what percentage of cases, of a specified surgical procedure or combination of procedures, may have been performed less than once per year per facility. Previous studies suggest the most important source of scheduling inaccuracy can be the absence of recently performed cases on which to base predictions of case duration. We found that 36% +/- 1% (SE) of all cases in the United States were a type of procedure or combination of procedures that occurred <6984 times per year (the number of surgery facilities performing ambulatory surgery in the United States). Approximately one third of all ambulatory cases were of a procedure or combination of procedures that may have been performed as infrequently as once per year per facility. This could impair the effectiveness of predicting the durations of ambulatory cases by using historical case-duration data. IMPLICATIONS: Approximately one third of all ambulatory cases were a procedure or combination of procedures possibly performed as infrequently as once per year per facility. This could impair the effectiveness of predicting the durations of ambulatory cases by using historical case-duration data.

Adolescent↗
PubMed2000

Economic analysis of linking operating room scheduling and hospital material management information systems for just-in-time inventory control.

UNLABELLED: Operating room (OR) scheduling information systems can decrease perioperative labor costs. Material management information systems can decrease perioperative inventory costs. We used computer simulation to investigate whether using the OR schedule to trigger purchasing of perioperative supplies is likely to further decrease perioperative inventory costs, as compared with using sophisticated, stand-alone material management inventory control. Although we designed the simulations to favor financially linking the information systems, we found that this strategy would be expected to decrease inventory costs substantively only for items of high price ($1000 each) and volume (>1000 used each year). Because expensive items typically have different models and sizes, each of which is used by a hospital less often than this, for almost all items there will be no benefit to making daily adjustments to the order volume based on booked cases. We conclude that, in a hospital with a sophisticated material management information system, OR managers will probably achieve greater cost reductions from focusing on negotiating less expensive purchase prices for items than on trying to link the OR information system with the hospital's material management information system to achieve just-in-time inventory control. IMPLICATIONS: In a hospital with a sophisticated material management information system, operating room managers will probably achieve greater cost reductions from focusing on negotiating less expensive purchase prices for items than on trying to link the operating room information system with the hospital's material management information system to achieve just-in-time inventory control.

Computer Simulation↗
PubMed2000

A strategy to decide whether to move the last case of the day in an operating room to another empty operating room to decrease overtime labor costs.

UNLABELLED: We examined how to program an operating room (OR) information system to assist the OR manager in deciding whether to move the last case of the day in one OR to another OR that is empty to decrease overtime labor costs. We first developed a statistical strategy to predict whether moving the case would decrease overtime labor costs for first shift nurses and anesthesia providers. The strategy was based on using historical case duration data stored in a surgical services information system. Second, we estimated the incremental overtime labor costs achieved if our strategy was used for moving cases versus movement of cases by an OR manager who knew in advance exactly how long each case would last. We found that if our strategy was used to decide whether to move cases, then depending on parameter values, only 2.0 to 4.3 more min of overtime would be required per case than if the OR manager had perfect retrospective knowledge of case durations. The use of other information technologies to assist in the decision of whether to move a case, such as real-time patient tracking information systems, closed-circuit cameras, or graphical airport-style displays can, on average, reduce overtime by no more than only 2 to 4 min per case that can be moved. IMPLICATIONS: The use of other information technologies to assist in the decision of whether to move a case, such as real-time patient tracking information systems, closed-circuit cameras, or graphical airport-style displays, can, on average, reduce overtime by no more than only 2 to 4 min per case that can be moved.

Algorithms↗
PubMed2000

The lack of systematic month-to-month variation over one-year periods in ambulatory surgery caseload -application to anesthesia staffing.

Anesthesia groups forecast future workload so that staffing and future hiring can be adjusted. Statistical methods have been developed to estimate the number of anesthesia providers needed to minimize labor costs during regularly scheduled hours, second-shifts, and weekends. These methods are simple, in that they assume that, on this medium-range (11-mo) basis, workload varies irregularly around a mean workload. To test whether this assumption is likely to hold for many anesthesia groups nationwide, raw data from the 1994 to 1996 National Survey of Ambulatory Surgery were reanalyzed. To assure that month-to-month systematic variation in workload (e.g., seasonal variation) could be detected if it were present, the average number of myringotomy tubes inserted each day in ambulatory surgery centers of the United States was also examined. The average number of ambulatory surgery cases performed with an anesthesia provider each day in the United States per 10,000 population was found to have not varied systematically month to month on a medium-range (11-mo) basis. In contrast, the average number of tubes inserted each day varied systematically among months for all 26 of the overlapping 11-mo periods in the 36 mo of the survey. These findings suggest that the relatively simple statistical methods that are available to estimate future anesthesia workload will work for many anesthesia groups.

Ambulatory Surgical Procedures↗
PubMed2000

Statistical method for predicting when patients should be ready on the day of surgery.

BACKGROUND: Previously, mathematical theory was developed for determining when a patient should be ready for surgery on the day of surgery. To apply this theory, a method is needed to predict the earliest start time of the case. METHODS: The authors calculated a time estimate such that the probability is 0.05 that the preceding case in the patient's operating room (OR) will be finished before the patient is ready for surgery. This implies there will be a 5% risk of OR personnel being idle and waiting for the patient. This 0. 05 value was chosen by considering the relative cost valuation of an average patient's time to that of an average surgical team based on national salary data. Case duration data from a surgical services information system were used to test different statistical methods to estimate earliest start times. RESULTS: Simulations found that 0.05 prediction bounds, calculated assuming case durations followed log-normal distributions, achieved actual risks for the OR staff to wait for patients of 0.050 to 0.053 (SEM = 0.001). Nonparametric prediction bounds performed no better than the parametric method. Having patients ready a fixed number of hours before the scheduled starts of their operations is not reliable. If the preceding case in an OR had been underway for 0.5 to 1.5 h, the parametric 0.05 prediction bounds for the time remaining achieved actual risks for OR staff waiting of 0.055 to 0.058 (SEM = 0.001). CONCLUSION: The earliest start time of a case can be estimated using the 0.05 prediction bound for the duration of the preceding case. The authors show 0.05 prediction bounds can be estimated accurately assuming that case durations follow log-normal distributions.

Appointments and Schedules↗
PubMed2000

Acute cord occlusion increases blood ionized magnesium concentration in preterm fetal sheep during maternal magnesium sulfate exposure.

This study tested the hypothesis that a pathophysiologic insult to the fetus that decreases pH (umbilical cord occlusion) produces an increase in physiologically active (i.e., ionized) magnesium concentration. Preterm pregnant sheep (n = 7) were instrumented with maternal and fetal catheters and an inflatable vascular occluder was placed around the umbilical cord. After a 2-day recovery period, each ewe received a 4-g loading dose, followed by continuous intravenous infusion of 1 g magnesium sulfate/h. After 48 h, an episode of acute fetal distress was produced by inflation of the umbilical occluder for 10 min. Maternal and fetal arterial blood samples were collected at regular intervals to quantitate ionized magnesium concentration and monitor physiologic status. Magnesium sulfate infusion increased maternal and fetal blood ionized magnesium concentration. In vitro blood analysis demonstrated that there was a linear inverse correlation (r2 = 0.99) between fetal sheep blood pH and ionized magnesium concentration. In vivo, 10 min of umbilical cord occlusion produced an increase in fetal blood ionized magnesium concentration in all animals (P = 0.02) that was temporally related to the decrease in fetal blood pH. Whether this increase in physiologically active magnesium concentration is beneficial (via neuroprotection) or deleterious (via suppression of stress response) to the distressed fetus remains to be determined.

Animals↗
PubMed2000

Statistical method using operating room information system data to determine anesthetist weekend call requirements.

We present a statistical method that uses data from surgical services information systems to determine the minimum number of anesthetists to be scheduled for weekend call in an operating room suite. The staffing coverage is predicted that provides for sufficient anesthetists to cover each hour of a 24-hour weekend period, while satisfying a specified risk for being understaffed. The statistical method incorporates shifts of varying start times and durations, as well as historical weekend operating room caseload data. By using this method to schedule weekend staff, an anesthesia group can assure as few anesthetists are on call as possible, and for as few hours as possible, while maintaining the level of risk of understaffing that the anesthesia group is willing to accept. An anesthesia group also can use the method to calculate its risk of being understaffed in the surgical suite based on its existing weekend staffing plan.

Data Interpretation, Statistical↗
PubMed2000

Determining staffing requirements for a second shift of anesthetists by graphical analysis of data from operating room information systems.

Some operating room (OR) managers face the dilemma whereby all cases in a surgical suite are not completed during a regularly scheduled (e.g., 8-hour) day. If the anesthesia group at the surgical suite plans for its employed anesthetists to work a fixed number of hours each day, then more than 1 shift of anesthetists may be needed to care for the patients in the ORs. We developed a graphical statistical method that anesthetists and anesthesiologists can use to determine how many anesthesia providers are required on the second shift to minimize labor costs. The method uses data from surgical services information systems or hospital information systems to compensate for seasonality or seasonal variation in the number of ORs running at different times of the day. We also consider application of our method to scheduling surgical nurses with multiple overlapping shifts throughout the day.

Computer Graphics↗
PubMed1999

Relying solely on historical surgical times to estimate accurately future surgical times is unlikely to reduce the average length of time cases finish late.

STUDY OBJECTIVE: To determine whether using only previous cases' surgical times for predicting accurately surgical times of future cases is likely to reduce the average length of time cases finish late (after their scheduled finish times). DESIGN: Computer simulation. MEASUREMENTS AND MAIN RESULTS: Data from an operating room (OR) information system for two surgical suites were analyzed. For each case performed in fiscal year 1996, we searched backward for 1 year and counted the number of previous cases that were the same type of procedure performed by the same surgeon. Then, for each suite, surgical times were fitted to a statistical model estimating the effect of the type of procedure and who the surgeon was on surgical time. The estimated "variance components" were used in Monte-Carlo computer simulations to evaluate whether a hypothetical increase in the number of previous cases available to estimate the next case's surgical time would improve scheduling accuracy. Predictions of how long newly scheduled cases should take were impaired because 36.5% +/- 0.4% (mean +/- SE) of cases at a tertiary surgical suite and 28.6% +/- 0.7% of cases at an ambulatory surgery center did not have any cases in the previous year with the same procedure type and surgeon. Computer simulation was used to generate additional hypothetical cases. Using this data, even having many previous cases on which to base predictions of future surgical times would only decrease the average length of time that cases finish late by a few minutes. CONCLUSION: An OR manager considering using only historical surgical times to estimate future surgical times should first investigate, using data from their own surgical suite, what percentage of cases do not have historical data. Even if there are sufficient historical data to estimate future surgical times accurately, relying solely on historical times is probably an ineffective strategy to have future cases finish on time.

Ambulatory Surgical Procedures↗
PubMed1999

What can the postanesthesia care unit manager do to decrease costs in the postanesthesia care unit?

The economic structure of the PACU dictates whether a cost-reducing intervention (e.g., reducing the length of time patients stay in the PACU) is likely to decrease hospital costs. Cost-reducing interventions, such as changes in medical practice patterns (e.g., to reduce PACU length of stay), only impact variable costs. How PACU nurses are paid (e.g., salaried v hourly) affects which strategies to decrease PACU staffing costs will actually save money. For example, decreases in PACU labor costs resulting from increases in the number of patients that bypass the PACU vary depending on how the staff is compensated. The choice of anesthetic drugs and the elimination of low morbidity side effects of anesthesia, such as postoperative nausea, are likely to have little effect on the peak numbers of patients in a PACU and PACU staffing costs. Because the major determinant of labor productivity in the PACU is hour-to-hour and day-to-day variability in the timing of admissions from the operating room, a more even inflow of patients into the PACU could be attained by appropriate sequencing of cases in the operating room suite (e.g., have long cases scheduled at the beginning of the day). However, this mathematically proven solution may not be desirable. Surgeons, for example, may not want to lose control over the order of their cases. Guidelines for analysis of past daily peak numbers of patients are provided that will provide data to predict the minimum adequate number of nurses needed. Though many managers already do this manually on an ad hoc basis statistical methods summarized in this article may increase the accuracy.

Cost Control↗
PubMed1999

Optimal sequencing of urgent surgical cases. Scheduling cases using operating room information systems.

Optimal sequencing of urgent cases (i.e., selecting which urgent case should be performed first and which second) may enhance patient safety, increase patient satisfaction with timeliness of surgery, and minimize surgeons' complaints. Before determining the optimal sequence of urgent cases, an operating room (OR) suite must identify the primary scheduling objective to be satisfied when prioritizing pending urgent cases. These scheduling objectives may include: 1) perform the cases in the sequence that minimizes the average length of time each surgeon and patient waits; 2) perform the cases in the order that they were submitted; or 3) perform the cases based on medical priority, as prioritized by an OR director, or surgeons discussing the cases among themselves. We provide mathematical structure which can be used to program a computerized surgical services information system to assist in optimizing the sequence of urgent cases. We use an example to illustrate that the optimal sequence varies depending on the scheduling objective chosen.

Algorithms↗
PubMed1999

Comparison of statistical methods to predict the time to complete a series of surgical cases.

We present a statistical model for predicting the time to complete a series of successive, elective surgical cases. The use of sample means of case times and turnover times when scheduling cases does not minimize the operating room labor costs associated with errors in predicting times to complete series of cases. The problem of minimizing associated labor costs (both under and over utilization) can be converted to the problem of least absolute deviation regression. The dependent variables are the times to complete series of cases. The independent variables are the numbers of cases in each series that are in various categories (i.e., combinations of scheduled procedures and surgeons). Although the computational method is preferred on theoretical grounds to that involving sample means, application of both methods shows that the more practical method is to use the sample means of previous case times and turnovers.

Elective Surgical Procedures↗