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Biomedical subjects

Franklin Dexter

Publications and source records attributed to Franklin Dexter.

At least 19 recordsLinked to original sources

Quantifying effect of a hospital's caseload for a surgical specialty on that of another hospital using multi-attribute market segments.

Inpatient and outpatient data were used to create market segments consisting of hierarchical combinations of surgical procedure, then type of payer, and then location of patients' residences. The competitive effect of one hospital's caseload for a given surgical specialty on the caseload of another hospital was determined from the numbers of patients in each segment. Earlier methods for estimating surgical competition that ignored market segments over-estimated the competitive effects of one hospital on another. Thus, results differed from those obtained previously for all types of hospital admissions. When actual market segments with homogeneous groups of patients are used, competitive effects of hospitals in the same market area are far less than expected.

Catchment Area, Health↗

Strategies to reduce delays in admission into a postanesthesia care unit from operating rooms.

The authors performed a systematic review of strategies to reduce delays in admission into PACUs from ORs. The purpose of this article was to evaluate for managers how to choose interventions based on effectiveness and practicality. The authors discuss optimization methods that can be used to sequence consecutive cases in the same OR, by the same surgeon, on the same day, based on the objective of reducing delays in PACU admission due to the unavailability of unfilled PACU beds. Although effective, such methods can be impractical because of large organizational change required and limited equipment or personnel availability. When all physical beds are not full, PACU nurse staffing can be adjusted. Statistical methods can be used to ensure that nursing schedules closely match the times that minimize delays in PACU admission. These methods are effective and practical. Explicit criteria can be applied to assist in deciding when to assign other qualified nurses to the PACU, when to ask PACU nurses to work late, and/or when to make a decision on the day before surgery to add more PACU nurses for the next day (if available). The latter would be based on statistical forecasts of the timing of patients' admissions into the PACU. Whether or not all physical beds are full, the risk of delays in PACU admission is relatively insensitive to economically feasible reductions in PACU length of stay. Such interventions should be considered only if statistical analysis, performed by using computer simulation, has established that reducing PACU length of stay will reduce delays in admission at a manager's facility.

Algorithms↗

Criteria for identification of comprehensive pediatric hospitals and referral regions.

OBJECTIVE: To identify comprehensive pediatric hospitals on the basis of publicly available data. STUDY DESIGN: We developed identification criteria for comprehensive pediatric hospitals, then evaluated the number of hospitals meeting these selection criteria. Criteria for a comprehensive pediatric hospital included pediatric residency accreditation, pediatric inpatient volume, and diversity of pediatric disorders at each hospital. New York State hospital administrative discharge data were analyzed for patients 0 to 14 years of age, excluding neonatal diagnoses. RESULTS: Infants and children (n = 125,588) with 375 different diagnosis-related groups were discharged from 230 hospitals in 2000. Through the use of higher selective criteria (educational accreditation plus both high volume and diversity in the top decile), 11 comprehensive pediatric hospitals were identified. These hospitals serve populations of 1.7 +/- 0.3 million (mean +/- SD) each, with 8 referral regions throughout the state, collectively providing care for 29% of all pediatric statewide hospitalizations. CONCLUSIONS: Comprehensive pediatric hospitals serve the population of New York widely and evenly. The ability to identify pediatric hospitals will permit evaluation of the relative quality of care and suggest appropriate regulatory interventions to improve pediatric hospital utilization.

Accreditation↗

Estimating the incidence of prolonged turnover times and delays by time of day.

BACKGROUND: Prolonged turnover times cause frustration and can thereby reduce professional satisfaction and the workload surgeons bring to a hospital. METHODS: The authors analyzed 1 yr of operating room information system data from two academic, tertiary hospitals and Monte-Carlo simulations of a 15-operating room hospital surgical suite. RESULTS: Confidence interval widths for the mean turnover times at the hospitals were negligible when compared with the variation in sample mean turnover times among 31 hospitals. The authors developed a statistical method to estimate the proportion of all turnovers that were prolonged (> 15 min beyond mean) and that occurred during specified hours of the day. Confidence intervals for the proportions corrected for the effect of multiple comparisons. Statistical assumptions were satisfied at the two studied hospitals. The confidence intervals achieved family-wise type I error rates accurate to within 0.5% when applied to between five and nineteen 4-week periods of data. The diurnal pattern in the proportions of all turnovers that were prolonged provided different, more managerially relevant information than the time course throughout the day in the percentage of turnovers at each hour that were prolonged. CONCLUSIONS: Benchmarking sample mean turnover times among hospitals, without the use of confidence intervals, can be valid and useful. The authors successfully developed and validated a statistical method to estimate the percentage of turnover times at a surgical suite that are prolonged and occur at specified times of the day. Managers can target their quality improvement efforts on times of the day with the largest percentages of prolonged turnovers.

Academic Medical Centers↗

Financial implications of a hospital's specialization in rare physiologically complex surgical procedures.

BACKGROUND: The authors previously identified a hospital that has a unique role in its region for surgical care. In children aged 0-2 yr, the hospital performed 64% of all physiologically complex procedures statewide (>or= 8 American Society of Anesthesiologists Relative Value Guide basic units). For all age groups combined, 48% of the physiologically complex procedures performed at that hospital were rare, defined as < 1/workday statewide. METHODS: The authors tested the hypothesis that financially important differences can result from performing relatively large numbers of such specialized procedures. Methods were developed to compare contribution margin (revenue from facility and professional fees minus variable costs) per operating room hour (CM/OR hour) between patient groups and different types of surgical procedures. RESULTS: CM/OR hour was significantly larger by a financially important amount (> 250 dollars/OR hour) for pediatric versus geriatric patients (P <or= 0.002), primarily because of higher professional reimbursements, with no difference in hospital reimbursements. Unexpectedly, CM/OR hour was also significantly greater by at least 250 dollars when a rare procedure was involved (P < 0.001 for all ages combined), primarily because of greater hospital reimbursements. For cases involving implant charges of 10,000 dollars or greater, overall CM/OR hour was negative because increased revenues did not compensate for the high variable costs. CONCLUSIONS: Other hospitals can use these methods to perform a similar analysis of the financial impact of those patient populations or surgical procedures that are unique to their own roles in their regional healthcare systems, and to identify the sources of financial losses and gains experienced by the hospital.

Child↗

Tactical decision making for selective expansion of operating room resources incorporating financial criteria and uncertainty in subspecialties' future workloads.

We considered the allocation of operating room (OR) time at facilities where the strategic decision had been made to increase the number of ORs. Allocation occurs in two stages: a long-term tactical stage followed by short-term operational stage. Tactical decisions, approximately 1 yr in advance, determine what specialized equipment and expertise will be needed. Tactical decisions are based on estimates of future OR workload for each subspecialty or surgeon. We show that groups of surgeons can be excluded from consideration at this tactical stage (e.g., surgeons who need intensive care beds or those with below average contribution margins per OR hour). Lower and upper limits are estimated for the future demand of OR time by the remaining surgeons. Thus, initial OR allocations can be accomplished with only partial information on future OR workload. Once the new ORs open, operational decision-making based on OR efficiency is used to fill the OR time and adjust staffing. Surgeons who were not allocated additional time at the tactical stage are provided increased OR time through operational adjustments based on their actual workload. In a case study from a tertiary hospital, future demand estimates were needed for only 15% of surgeons, illustrating the practicality of these methods for use in tactical OR allocation decisions.

Decision Making↗

How do we sequence urgent cases?

Because the medical deadline is determined in hours, there is a precise mathematical definition for OR efficiency, and the impact on patient delays can be estimated. The priorities described above will give a single answer to a sequence of urgent cases.

Appointments and Schedules↗

Market capture of inpatient perioperative services using DEA.

We develop and validate a method to measure "market capture" of inpatient, elective surgery. Data envelopment analysis (DEA) is used to measure the efficiency of the market capture for Perioperative Services at 53 non-metropolitan Pennsylvania hospitals. Eight procedures are studied, representing a wide spectrum of elective, scheduled, inpatient surgery (e.g., abdominal aortic aneurysm resection and hip replacement). Our results address issues in operating room management, such as: How should additional resources be allocated to each surgical specialty? Given existing market conditions, for which specialties can we expect to be able to increase our current workloads? Our results demonstrate DEA's potential as a valuable tool for operating room managers' strategic decision-making.

Benchmarking↗

Using length of stay data from a hospital to evaluate whether limiting elective surgery at the hospital is an inappropriate decision.

STUDY OBJECTIVE: At hospitals without detailed managerial accounting data but with overall longer than average diagnosis-related groups (DRG)-adjusted lengths of stays (LOS), some administrators do not aggressively hire the nurses needed to maintain surgical hospital capacity. The consequence of this (long-term) decision is that day-of-surgery admit cases are delayed or cancelled from a lack of beds. The anesthesiologists suffer financially. In this paper, we show how publicly released national LOS data can be applied specifically to these cases. DESIGN: We applied the method to 1 year of data from two academic hospitals. Each case's LOS was compared to the United States national average LOS for cases with the same DRG. MEASUREMENTS AND MAIN RESULTS: A total of 8,050 and 10,099 hospitalizations, respectively. Among all surgical admissions, mean LOS was 2.5 days longer than the national average for Hospital #1 (95% confidence interval [CI], 2.1 to 2.8) and 3.1 days longer for Hospital #2 (95% CI, 2.8 to 3.4). Among patients undergoing elective, scheduled surgery with day of surgery admission, mean LOS was 0.7 days less than average for Hospital #1 (0.6 to 0.9) and 1.2 days less than average for Hospital #2 (1.1 to 1.4). CONCLUSIONS: This method can be used by anesthesiologists to show that LOS are not longer than average among patients whose surgeries may be cancelled or delayed for a lack of hospital ward staff.

Anesthesia Department, Hospital↗

Quantifying net staffing costs due to longer-than-average surgical case durations.

BACKGROUND: Anesthesiology departments incur staffing costs that are not covered by revenue because the operating room (OR) time allocation and case scheduling are not done to maximize OR efficiency and because surgical durations are longer than average. The purpose of this article is to demonstrate a method to quantify net anesthesia staffing costs due to longer-than-average surgical durations and evaluate the factors that influence staffing costs. METHODS: Data collected from two anesthesiology departments in academic hospitals for 1 yr included date of surgery, time that patients entered the OR, time that patients exited the OR, surgical service, and the Current Procedural Terminology code for the primary surgical procedure. Anesthesia care performed outside the main surgical suite and services not billed with American Society of Anesthesiologists units were excluded. National average surgical durations were determined from the Current Procedural Terminology code from the Centers for Medicare and Medicaid Services' database. Actual surgical durations were then used to determine staffing solutions to maximize OR efficiency; national average surgical durations were then used to determine a second solution. The difference in staffing costs between these two staffing solutions represented the staffing costs attributable to longer surgical durations. Costs were converted to dollar amounts using compensation values reported in a national compensation survey. The differences in revenue were determined by applying conversion factors to the differences in surgical durations. The annual net cost attributable to longer surgical durations equaled the staffing costs minus the revenue produced by longer durations. Net staffing costs were estimated for two hospitals using median staffing compensation and median payer mix. Net staffing costs were then recalculated by varying the parameters (conversion factors, limits on differences between actual and average surgical duration, levels of compensation, surgical service size of OR allocation). RESULTS: Using the median compensation of staff and an average conversion factor, the net annual staffing costs attributable to longer surgical durations were $672,100 for the first hospital. However, if staff members were highly compensated and the payer mix was unfavorable, the net staffing costs were $1,688,000. Reducing the difference between actual and average duration resulted in lower staffing costs. Net staffing costs were less in a second hospital studied that had many low-volume surgical services. CONCLUSIONS: Longer-than-average surgical durations can increase net staffing costs for anesthesiology groups. The increase is dependent on factors such as staffing compensation and payer mix.

Anesthesia Department, Hospital↗

Differentiating among hospitals performing physiologically complex operative procedures in the elderly.

BACKGROUND: The authors previously showed how a statewide discharge abstract database could be used to quantify for stakeholders how surgical practices differ among hospitals. The two pediatric hospitals in Iowa differ from other hospitals in Iowa based on their providing a more diverse, comprehensive, and physiologically complex selection of procedures in younger patients. Physiologically complex surgery performed in children aged 0-2 yr has been regionalized to a few high-volume facilities. METHODS: The same inpatient discharge abstract database was used to quantify physiologically complex operative procedures performed throughout Iowa in patients aged 80 yr and older during January through June 2001. RESULTS: In contrast to earlier results with pediatric patients using the same database, hospitals performing physiologically complex procedures in the elderly could not readily be differentiated from one another based on the numbers and types of procedures performed (P < 0.001 when comparing geriatrics vs. pediatrics in terms of the distributions of numbers of procedures, the distributions of numbers of different types of procedures, or the distributions of numbers of rare procedures performed at different hospitals). Additional analyses showed that one hospital did perform relatively more rare procedures in geriatric patients and had a relatively larger percentage of patients who traveled beyond their local county to reach it. CONCLUSIONS: Results observed for geriatric patients provide further evidence of the validity of these methods and the usefulness of discharge abstract data for comparing surgical practices among facilities. A hospital can use discharge abstract data to assist governmental agencies, charitable organizations, philanthropists, insurers, etc., in appreciating the unique contributions of individual hospitals to surgical care.

Aged↗

Making management decisions on the day of surgery based on operating room efficiency and patient waiting times.

The authors review the scientific literature on operating room management operational decision making on the day of surgery. (1) Some decisions should rely on the expected (mean) duration of the scheduled case. Other decisions should use upper prediction bounds, lower prediction bounds, and other measures reflecting the uncertainty of case duration estimates. One single number cannot be used for good decision making, because durations are uncertain. (2) Operational decisions can be made on the day of surgery based on four ordered priorities. (3) Decisions to reduce overutilized operating room time rely on mean durations. Limited additional data are needed to make these decisions well, specifically, whether a patient is in each operating room and which cases are about to finish. (4) Decisions involving reducing patient (and surgeon) waiting times rely on quantifying uncertainties in case durations, which are affected highly by small sample sizes. Future studies should focus on using real-time display of data to reduce patient waiting.

Appointments and Schedules↗

When to release allocated operating room time to increase operating room efficiency.

UNLABELLED: We studied when allocated, but unfilled, operating room (OR) time of surgical services should be released to maximize OR efficiency. OR time was allocated for two surgical suites based on OR efficiency. Then, we analyzed real OR schedules. We added new hypothetical cases lasting 1, 2, or 3 h into OR time of the service that had the largest difference between allocated and scheduled cases (i.e., the most unfilled OR time) 5 days before the day of surgery. The process was repeated using the updated OR schedule available the day before surgery. The pair-wise difference in resulting overutilized OR time was calculated for n = 754 days of data from each of the two surgical suites. We found that postponing the decision of which service gets the new case until early the day before surgery reduces overutilized OR time by <15 min per OR per day as compared to releasing the allocated OR time 5 days before surgery. These results show that when OR time is released has a negligible effect on OR efficiency. This is especially true for ambulatory surgery centers with brief cases or large surgical suites with specialty-specific OR teams. What matters much more is having the correct OR allocations and, if OR time needs to be released, making that decision based on the scheduled workload. IMPLICATIONS: Provided operating room (OR) time is allocated and cases are scheduled based on maximizing OR efficiency, then whether OR time is released five days or one day before the day of surgery has a negligible effect on OR efficiency.

Ambulatory Surgical Procedures↗

Data envelopment analysis to determine by how much hospitals can increase elective inpatient surgical workload for each specialty.

We apply data envelopment analysis to discharge data from the 115 hospitals in the rural state of a study hospital to answer three questions. We use a case study to investigate the usefulness and limitations of data envelopment analysis for assessing three common questions regarding hospital market capture for elective inpatient surgery. (i) The hospital studied in this paper performs 40% of the neurosurgery and 25% of the inpatient urology surgery in its state. Workloads are twice that of the hospitals with the next largest workloads. In contrast, the hospital performs 9% of its state's cardiac surgery and has a workload half that of the largest volume hospital. The cardiac surgeons want more operating room time, faster turnovers, and capital investment for minimally invasive equipment. Controlling for the distance patients would need to travel for care, would increasing capacity likely increase cardiac surgery workload? (ii) The study hospital has fewer hospitalizations for thoracic surgery than for any other specialty. Is thoracic surgery inpatient workload of 121 lung resections large or small compared with those of orthopedics' 213 hip replacements, urology's 132 nephrectomies, and cardiac surgery's 304 coronary artery bypass grafts? (iii) The hospital's busiest specialty by discharges is orthopedics. How sensitive is the hospital's orthopedic workload to changes in decision making at nearby competing hospitals?

Craniotomy↗

Optimizing second shift OR staffing.

In surgical suites when ORs sometimes run late, nurse anesthetists or perioperative nurses may be scheduled to work a second shift to cover procedures. Nurse anesthetists' OR workload in the afternoons can differ from that of perioperative nurses. At the end of long procedures, times to transport and stabilize patients can be considerable. This article shows that optimal second-shift OR staffing is the same for nurse anesthetists and perioperative nurses when assessed using anesthesia billing data and OR information systems data respectively. Managers do not need hospital information systems staff members to provide data from both anesthesia billing and OR information systems to make second-shift staffing decisions. One or the other is adequate.

Hospital Costs↗