Victor Frankenstein's Institutional Review Board Proposal, 1790.

To show how the case of Mary Shelley's Victor Frankenstein brings light to the ethical and moral issues raised in Institutional Review Board (IRB) protocols, we nest an imaginary IRB proposal dated August 1790 by Victor Frankenstein within a discussion of the importance and function of the IRB. Considering the world of science as would have appeared in 1790 when Victor was a student at Ingolstadt, we offer a schematic overview of a fecund moment when advances in comparative anatomy, medical experimentation and theories of life involving animalcules and animal electricity sparked intensive debates about the basic principles of life and the relationship between body and soul. Constructing an IRB application based upon myriad speculations circulating up to 1790, we imagine how Victor would have drawn upon his contemporaries' scientific work to justify the feasibility of his project, as well as how he might have outlined the ethical implications of his plan to animate life from "dead" tissues. In Mary Shelley's Frankenstein, Victor failed to consider his creature's autonomy, vulnerability, and welfare. In this IRB proposal, we show Victor facing those issues of justice and emphasize how the novel can be an important component in courses or workshops on research ethics. Had Victor Frankenstein had to submit an IRB proposal tragedy may have been averted, for he would have been compelled to consider the consequences of his experiment and acknowledge, if not fulfill, his concomitant responsibilities to the creature that he abandoned and left to fend for itself.

Does hospital occupancy impact discharge rates?

OBJECTIVE: To understand what impact hospital inpatient occupancy levels have on patient throughput by analysing one hospital's occupancy levels and the rate of patient discharge. METHODS: A four-stage model was fit to hospital admission and separation data and used to analyse the per-capita separation rate according to the patient load and the impact of hospital over-census actions. RESULTS: Per-capita separation rates are significantly higher on days when the hospital declares an over-census due to emergency department crowding. Per-capita separation rates are also higher or lower on days with 8-10% higher or lower patient loads, respectively, but the response is not nearly as strong as the response to an over-census declaration, and is limited to patients with an elapsed stay of 10 days or more. Within the medical division there is an increase in per-capita separation rates on over-census days, but no significant difference in per-capita release rates for different patient loads. Within the surgical division there is no significant difference in per-capita separation rates on over-census days compared with other days, but the patient load does make a significant difference. CONCLUSION: Staff do discharge a greater proportion of long-stay patients when the hospital is experiencing high demand and a lower proportion when occupancy is low, but the reasons driving those changes remains unclear.

Length of stay and imminent discharge probability distributions from multistage models: variation by diagnosis, severity of illness, and hospital.

Multistage models have been effective at describing length of stay (LOS) distributions for diverse patient groups. Our study objective was to determine whether such models could be used for patient groups restricted by diagnosis, severity of illness, or hospital in order to facilitate comparisons conditioned on these factors. We performed a retrospective cohort study using data from 317,876 hospitalizations occurring over 2 years in 17 hospitals in a large, integrated health care delivery system. We estimated model parameters using data from the first year and validated them by comparing the predicted LOS distribution to the second year of data. We found that 3- and 4-stage models fit LOS data for either the entire hospital cohort or for subsets of patients with specific conditions (e.g. community-acquired pneumonia). Probability distributions were strongly influenced by the degree of physiologic derangement on admission, pre-existing comorbidities, or a summary mortality risk combining these with age, sex, and diagnosis. The distributions for groups with greater severity of illness were shifted slightly to the right, but even more notable was the increase in the dispersion, indicating the LOS is harder to predict with greater severity of illness. Multistage models facilitate computation of the hazard function, which shows the probability of imminent discharge given the elapsed LOS, and provide a unified method of fitting, summarizing, and studying the effects of factors affecting LOS distributions. Future work should not be restricted to expected LOS comparisons, but should incorporate examination of LOS probability distributions.

Addressing physician shortages in New Mexico through a combined BA/MD program.

The University of New Mexico School of Medicine and College of Arts and Sciences developed its combined BA/MD degree program, which will increase the medical school class from 75 students to 100 in the fall of 2010, to address the critical issue of physician shortages in underserved New Mexico. The program, which began operation at the undergraduate (i.e., college) level in 2006, expands opportunities in medical education for New Mexico students, especially those from rural and underserved minority communities, and prepares them to practice in underserved areas of New Mexico. In the BA/MD program, students will earn a bachelor of arts, a medical degree, and a proposed certificate in public health. A challenging liberal arts curriculum introduces the principles of public health. Students have unique rural medicine and public health preceptorship opportunities that begin in the undergraduate years and continue throughout medical school. Students work with a community physician mentor in summer service-learning projects during the undergraduate years, then they return for required rural medicine rotations in the first, third, and fourth years of medical school. Simultaneously, the classroom curriculum for these rural medicine experiences emphasizes the public health perspective. High priority has been placed on supporting students with academic advising and counseling, tutoring, supplemental instruction, on-campus housing, and scholarships. The program has received strong support from communities, the New Mexico state legislature, the New Mexico Medical Society, and the faculties of arts and sciences and the school of medicine. Early results on the undergraduate level demonstrate strong interest from applicants, retention of participants, and enthusiasm of students and faculty alike.

Modelling variability in hospital bed occupancy.

A stochastic version of the Harrison-Millard multistage model of the flow of patients through a hospital division is developed in order to model correctly not only the average but also the variability in occupancy levels, since it is the variability that makes planning difficult and high percent occupancy levels increase the risk of frequent overflows. The model is fit to one year of data from the medical division of an acute care hospital in Adelaide, Australia. Admissions can be modeled as a Poisson process with rates varying by day of the week and by season. Methods are developed to use the entire annual occupancy profile to estimate transition rate parameters when admission rates are not constant and to estimate rate parameters that vary by day of the week and by season, which are necessary for the model variability to be as large as in the data. The final model matches well the mean, standard deviation and autocorrelation function of the occupancy data and also six months of data not used to estimate the parameters. Repeated simulations are used to construct percentiles of the daily occupancy distributions and thus identify ranges of normal fluctuations and those that are substantive deviations from the past, and also to investigate the trade-offs between frequency of overflows and the percent occupancy for both fixed and flexible bed allocations. Larger divisions can achieve more efficient occupancy levels than smaller ones with the same frequency of overflows. Seasonal variations are more significant than day-of-the-week variations and variable discharge rates are more significant than variable admission rates in contributing to overflows.