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A nested case-control study was conducted in two trials of prophylaxis for Mycobacterium avium complex (MAC) infection to describe the specific signs, symptoms, and laboratory abnormalities of MAC disease in AIDS. Patients had < or =200/mm3 CD4 cells and a prior AIDS-defining illness. Of 571 patients, 102 (17.9%) developed MAC bacteremia during a mean follow-up of 256 days. Among cases of MAC disease, 90 were compared with 180 matched controls. Patients with MAC disease were more likely than controls to have lower weights (66.3 vs. 71.1 kg, P = .001) and Karnofsky scores (74.3 vs. 84.4, P < .001); a higher proportion had fever (48% vs. 26%, P = .003), abdominal pain (23% vs. 13%, P =.05), decreased hemoglobin levels (10.9 vs. 12.1 g/dL, P < .001), and elevated alkaline phosphatase (203 vs. 138 U/L, P=.04) and lactate dehydrogenase (334 vs. 280 U/L, P = .02) levels. Characteristics of MAC disease that occurred before bacteremia were weight loss (3 months prior), fever (2 months), and anemia and elevated lactate dehydrogenase (1 month). These data suggest that patients have symptomatic MAC disease for several months prior to the occurrence of bacteremia. [ABSTRACT FROM AUTHOR]

We consider the problem of setting appropriate patient-to-nurse ratios in a hospital, an issue that is both complex and widely debated. There has been only limited effort to take advantage of the extensive empirical results from the medical literature to help construct analytical decision models for developing upper limits on patient-to-nurse ratios that are more patient- and nurse-oriented. For example, empirical studies have shown that each additional patient assigned per nurse in a hospital is associated with increases in mortality rates, length-of-stay, and nurse burnout. Failure to consider these effects leads to disregarded potential cost savings resulting from providing higher quality of care and fewer nurse turnovers. Thus, we present a nurse staffing model that incorporates patient length-of-stay, nurse turnover, and costs related to patient-to-nurse ratios. We present results based on data collected from three participating hospitals, the American Hospital Association (AHA), and the California Office of Statewide Health Planning and Development (OSHPD). By incorporating patient and nurse outcomes, we show that lower patient-to-nurse ratios can potentially provide hospitals with financial benefits in addition to improving the quality of care. Furthermore, our results show that higher policy patient-to-nurse ratio upper limits may not be as harmful in smaller hospitals, but lower policy patient-to-nurse ratios may be necessary for larger hospitals. These results suggest that a "one ratio fits all" patient-to-nurse ratio is not optimal. A preferable policy would be to allow the ratio to be hospital-dependent., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Performance modeling of hospitals using data envelopment analysis (DEA) has received steadily increasing attention in the literature. As part of the traditional DEA framework, hospitals are generally assumed to be functionally similar and therefore homogenous. Accordingly, any identified inefficiency is supposedly due to the inefficient use of inputs to produce outputs. However, the disparities in DEA efficiency scores may be a result of the inherent heterogeneity of hospitals. Additionally, traditional DEA models lack predictive capabilities despite having been frequently used as a benchmarking tool in the literature. To address these concerns, this study proposes a framework for analyzing hospital performance by combining two complementary modeling approaches. Specifically, we employ a self-organizing map artificial neural network (SOM-ANN) to conduct a cluster analysis and a multilayer perceptron ANN (MLP-ANN) to perform a heterogeneity analysis and a best practice analysis. The applicability of the integrated framework is empirically shown by an implementation to a large dataset containing more than 1,100 hospitals in Germany. The framework enables a decision-maker not only to predict the best performance but also to explore whether the differences in relative efficiency scores are ascribable to the heterogeneity of hospitals., (© 2022. The Author(s).)

When scheduling surgeries in the operating theater, not only the resources within the operating theater have to be considered but also those in downstream units, e.g., the intensive care unit and regular bed wards of each medical specialty. We present an extension to the master surgery schedule, where the capacity for surgeries on ICU patients is controlled by introducing downstream-dependent block types - one for both ICU and ward patients and one where surgeries on ICU patients must not be performed. The goal is to provide better control over post-surgery patient flows through the hospital while preserving each medical specialty's autonomy over its operational surgery scheduling. We propose a mixed-integer program to determine the allocation of the new block types within either a given or a new master surgery schedule to minimize the maximum workload in downstream units. Using a simulation model supported by seven years of data from the University Hospital Augsburg, we show that the maximum workload in the intensive care unit can be reduced by up to 11.22% with our approach while maintaining the existing master surgery schedule. We also show that our approach can achieve up to 79.85% of the maximum workload reduction in the intensive care unit that would result from a fully centralized approach. We analyze various hospital setting instances to show the generalizability of our results. Furthermore, we provide insights and data analysis from the implementation of a quota system at the University Hospital Augsburg., (© 2022. The Author(s).)

Lack of rapidly available neurological expertise, especially in rural areas, is one of the key obstacles in stroke care. Stroke care networks attempt to address this challenge by connecting hospitals with specialized stroke centers, stroke units, and hospitals of lower levels of care. While the benefits of stroke care networks are well-documented, travel distances are likely to increase when patients are transferred almost exclusively between members of the same network. This is particularly important for patients who require mechanical thrombectomy, an increasingly employed treatment method that requires equipment and expertise available in specialized stroke centers. This study aims to analyze the performance of the current design of stroke care networks in Bavaria, Germany, and to evaluate the improvement potential when the networks are redesigned to minimize travel distances. To this end, we define three fundamental criteria for assessing network design performance: 1) average travel distances, 2) the populace in the catchment area relative to the number of stroke units, and 3) the ratio of stroke units to lower-care hospitals. We generate several alternative stroke network designs using an analytical approach based on mathematical programming and clustering. Finally, we evaluate the performance of the existing networks in Bavaria via simulation. The results show that the current network design could be significantly improved concerning the average travel distances. Moreover, the existing networks are unnecessarily imbalanced when it comes to their number of stroke units per capita and the ratio of stroke units to lower-care hospitals., (© 2021. The Author(s).)

Background: Since operating rooms are a major bottleneck resource and an important revenue driver in hospitals, it is important to use these resources efficiently. Studies estimate that between 60 and 70% of hospital admissions are due to surgeries. Furthermore, staffing cannot be changed daily to respond to changing demands. The resulting high complexity in operating room management necessitates perpetual process evaluation and the use of decision support tools. In this study, we evaluate several management policies and their consequences for the operating theater of the University Hospital Augsburg., Methods: Based on a data set with 12,946 surgeries, we evaluate management policies such as parallel induction of anesthesia with varying levels of staff support, the use of a dedicated emergency room, extending operating room hours reserved as buffer capacity, and different elective patient sequencing policies. We develop a detailed simulation model that serves to capture the process flow in the entire operating theater: scheduling surgeries from a dynamically managed waiting list, handling various types of schedule disruptions, rescheduling and prioritizing postponed and deferred surgeries, and reallocating operating room capacity. The system performance is measured by indicators such as patient waiting time, idle time, staff overtime, and the number of deferred surgeries., Results: We identify significant trade-offs between expected waiting times for different patient urgency categories when operating rooms are opened longer to serve as end-of-day buffers. The introduction of parallel induction of anesthesia allows for additional patients to be scheduled and operated on during regular hours. However, this comes with a higher number of expected deferrals, which can be partially mitigated by employing additional anesthesia teams. Changes to the sequencing of elective patients according to their expected surgery duration cause expectable outcomes for a multitude of performance indicators., Conclusions: Our simulation-based approach allows operating theater managers to test a multitude of potential changes in operating room management without disrupting the ongoing workflow. The close collaboration between management and researchers in the design of the simulation framework and the data analysis has yielded immediate benefits for the scheduling policies and data collection efforts at our practice partner.

Background: There are limited quantitative approaches for evaluating rare safety outcomes from controlled clinical trials in either a blinded or unblinded setting. This manuscript demonstrates an application of three statistical methods for quantitative safety monitoring that can be implemented during any phase of a clinical trial, including open-label extension studies., Methods: An interactive safety monitoring (iSM) tool was developed using R language in the publicly available R-Shiny app and was implemented for three statistical methods of quantitative safety monitoring. These methods are sequential probability ratio test (SPRT), maximized SPRT (MaxSPRT), and Bayesian posterior probability threshold (BPPT). The iSM tool evaluated specific safety signals that incorporated pre-specified background rates or reference risk ratios., Results: Two sets of blinded clinical trial data were used for case studies to demonstrate the use the iSM tool. Two particular adverse events, myocardial infarction (MI) and serious infection, were monitored. Monte Carlo simulation was conducted to evaluate the operating characteristics of pre-specified parameters. It showed that after adjusting for exposure, the BPPT and MaxSPRT yielded similar results in identifying a pre-specified signals while the SPRT method failed to detect such signals., Conclusion: Statistical methods shown for the case studies, as well as the application of the user-friendly iSM tool, greatly enhance the quantitative monitoring of safety events of interest in ongoing clinical trials The BPPT and MaxSPRT methods seem more sensitive in picking-up early signals than the SPRT method when the number of safety events is small.

The original version of this article unfortunately contained errors. The first column of Tables 5 and 6 in the Appendix section should contain the year of publication instead of the reference number in brackets. The reference citations were then placed in the second column.

The healthcare sector in general and hospitals in particular represent a main application area for Data Envelopment Analysis (DEA). This paper reviews 262 papers of DEA applications in healthcare with special focus on hospitals and therefore closes a gap of over ten years that were not covered by existing review articles. Apart from providing descriptive statistics of the papers, we are the first to examine the research purposes of the publications. These research goals can be grouped into four distinct clusters according to our proposed framework. The four clusters are (1) "Pure DEA efficiency analysis", i.e. performing a DEA on hospital data, (2) "Developments or applications of new methodologies", i.e. applying new DEAy approaches on hospital data, (3) "Specific management question", i.e. analyzing the effects of managerial specification, such as ownership, on hospital efficiency, and (4) "Surveys on the effects of reforms", i.e. researching the impact of policy making, such as reforms of health systems, on hospital efficiency. Furthermore, we analyze the methodological settings of the studies and describe the applied models. We analyze the chosen inputs and outputs as well as all relevant downstream techniques. A further contribution of this paper is its function as a roadmap to important methodological literature and publications, which provide crucial information on the setup of DEA studies. Thus, this paper should be of assistance to researchers planning to apply DEA in a hospital setting by providing information on a) what has been published between 2005 and 2016, b) possible pitfalls when setting up a DEA analysis, and c) possible ways to apply the DEA analysis in practice. Finally, we discuss what could be done to advance DEA from a scientific tool to an instrument that is actually utilized by managers and policymakers.

Methodologies employing LC-MS/MS have been increasingly used for characterization and identification of residual host cell proteins (HCPs) in biopharmaceutical products to ensure their consistent product quality and safety for patients. To improve the sensitivity and reliability for HCP detection, we developed a high pH-low pH two-dimensional reversed phase LC-MS/MS approach in conjunction with offline fraction concatenation. Proof-of -concept was established using a model in which seven proteins spanning a size range of 29-78 kDa are spiked into a purified antibody product to simulate the presence of low-level HCPs. By incorporating a tandem column configuration and a shallow gradient through the second-dimension, all seven proteins were consistently identified at 10 ppm with 100% success rate following LC-MS/MS analysis of six concatenated fractions across multiple analysts, column lots and injection loads. Using the more complex Universal Proteomic Standard 1 (UPS-1) as an HCP model, positive identification was consistently achieved for 19 of the 22 proteins in 8-12 ppm range (10 ppm ±20%). For the first time, we demonstrate an effective LC-MS/MS strategy that not only has high sensitivity but also high reliability for HCP detection. The method performance has high impact on pharmaceutical company practices in using advanced LC-MS/MS technology to ensure product quality and patient safety.

The intensive care unit (ICU) is a crucial and expensive resource largely affected by uncertainty and variability. Insufficient ICU capacity causes many negative effects not only in the ICU itself, but also in other connected departments along the patient care path. Operations research/management science (OR/MS) plays an important role in identifying ways to manage ICU capacities efficiently and in ensuring desired levels of service quality. As a consequence, numerous papers on the topic exist. The goal of this paper is to provide the first structured literature review on how OR/MS may support ICU management. We start our review by illustrating the important role the ICU plays in the hospital patient flow. Then we focus on the ICU management problem (single department management problem) and classify the literature from multiple angles, including decision horizons, problem settings, and modeling and solution techniques. Based on the classification logic, research gaps and opportunities are highlighted, e.g., combining bed capacity planning and personnel scheduling, modeling uncertainty with non-homogenous distribution functions, and exploring more efficient solution approaches.

Progressive kidney diseases affect approximately 500 million people worldwide. Podocytes are terminally differentiated cells of the kidney filter, the loss of which leads to disease progression and kidney failure. To date, there are no therapies to promote podocyte survival. Drug repurposing may therefore help accelerate the development of cures in an area of tremendous unmet need. In a newly developed high-throughput screening assay of podocyte viability, we identified the BRAF V600E inhibitor GDC-0879 and the adenylate cyclase agonist forskolin as podocyte-survival-promoting compounds. GDC-0879 protects podocytes from injury through paradoxical activation of the MEK/ERK pathway. Forskolin promotes podocyte survival by attenuating protein biosynthesis. Importantly, GDC-0879 and forskolin are shown to promote podocyte survival against an array of cellular stressors. This work reveals new therapeutic targets for much needed podocyte-protective therapies and provides insights into the use of GDC-0879-like molecules for the treatment of progressive kidney diseases., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

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.

Despite the recent progress in psychiatric genetics, very few studies have focused on genetic risk factors in glial cells that, compared to neurons, can manifest different molecular pathologies underlying psychiatric disorders. In order to address this issue, we studied the effects of mutant disrupted in schizophrenia 1 (DISC1), a genetic risk factor for schizophrenia, in cultured primary neurons and astrocytes using an unbiased mass spectrometry-based proteomic approach. We found that selective expression of mutant DISC1 in neurons affects a wide variety of proteins predominantly involved in neuronal development (e.g., SOX1) and vesicular transport (Rab proteins), whereas selective expression of mutant DISC1 in astrocytes produces changes in the levels of mitochondrial (GDPM), nuclear (TMM43) and cell adhesion (ECM2) proteins. The present study demonstrates that DISC1 variants can perturb distinct molecular pathways in a cell type-specific fashion to contribute to psychiatric disorders through heterogenic effects in diverse brain cells.

Objective: To evaluate the 5-year safety and efficacy of adjunctive 0.005% latanoprost once daily., Methods: Patients with primary open-angle or exfoliation glaucoma who completed a 3-year, open-label, uncontrolled, prospective trial could enter a 2-year extension phase. High-resolution color photographs of irides were taken at baseline and at 14 subsequent visits. Photographs were assessed for change in iris pigmentation compared with baseline. Intraocular pressures and adverse events were recorded., Main Outcome Measure: Development and progression of increased iris pigmentation over 5 years., Results: Of the 519 original patients, 380 enrolled in the extension phase with approximately 89% having an eye color known to be susceptible to color change. After 5 years, most patients had no increase in iris pigmentation, but certain colored irides exhibited notably greater susceptibility than others. For those whose irides did change, onset occurred during the first 8 months in 74% and during the first 24 months in 94%. No patient developed an increase in pigmentation after month 36; the rate of progression decreased over time. Adverse event profiles were similar for patients with and without increased pigmentation. The overall mean intraocular pressure reduction from baseline of 25% was sustained with no need for change in intraocular pressure-lowering treatment in 70% of the eyes., Conclusion: Latanoprost therapy is safe and well tolerated for long-term treatment of open-angle glaucoma.

Analysis of geographic risk was performed for Mycobacterium avium complex (MAC) bacteremia among North American patients with AIDS. Monthly mycobacterial blood cultures were taken from patients who were placebo recipients in a prospective evaluation of MAC prophylaxis. Of 571 patients, 102 (17.9%) acquired MAC bacteremia during an average follow-up of 256 days. The area with the highest risk for MAC was the South Central region (27.9%; P < 0.02), whereas the area with the lowest risk was Canada (11.3%; P = 0.12). When the southern states were combined and compared with the northern states and Canada, the incidence of MAC bacteremia was higher in the southern states (21.6% versus 14.0%, P < 0.03). Proportional hazards analysis was performed for the difference between the North and South and controlled for baseline CD4 cell count. In this analysis, time to MAC was significantly longer in the North (hazard ratio = 0.587, 95% confidence interval 0.390 to 0.883, P = 0.01). Although overall variation in seasonality was not marked, there was a significant decrease in cases in the North during the summer months (P < 0.01). We conclude that geographic location is a risk factor for MAC bacteremia in patients with advanced AIDS, with decreased risk in northern North America.

When conducting inferential and epidemiologic studies, researchers are often interested in the distribution of time until the occurrence of some specified event, a form of incidence calculation. Furthermore, this interest often extends to the effects of intervening factors on this distribution. In this paper we impose the assumption that the phenomena being investigated are governed by a stationary Markov chain and review how one may estimate the above distribution. We then introduce and relate two different methods of investigating the effects of intervening factors. In particular, we show how an investigator may evaluate the effect of potential intervention programs. Finally, we demonstrate the proposed methodology using data from a population study.