Hospital Executive Succession Planning Strategies

Approximately 50% of New York City hospitals lack succession planning as baby boomers transition out of the workforce into retirement. The potential loss of knowledge capital could affect leadership development and corporate stability. Guided by the transformational leadership theory, the purpose of this single site case study was to explore successful strategies executive-level leaders used to facilitate succession planning within their hospital. Three hospital executive-level leaders from a single site location participated in a semistructured face-to-face interview and provided data that assisted the analysis. Four themes emerged from the data analysis through a word cloud format that showed the most commonly used words and phrases from participants\u27 responses to interview questions and review of company succession planning documents. The themes were organizational strategies used to promote executive-level succession planning, encouraging peer-mentorship, knowledge sharing strategies, and talent management. The findings revealed that the participants\u27 organization lacked formal succession planning strategies, but policies were in place that promoted in-house training and development to prepare the next generation of executive-level leaders. The findings of this study can contribute to positive social change by providing a work-related environment that embraces knowledge sharing and leadership development to increase leadership performance, income, and productivity, to ensure a better quality of life for employees and to improve the healthcare of patients and the community served

Root Cause of Medication Errors In a Pediatric Intensive Care Unit

Five to 27% of all pediatric medication orders lead to errors and play a significant role in the morbidity and mortality of the pediatric patients admitted to hospitals. The practice problem explored the high rate of medication errors in the pediatric intensive care unit (PICU) of the project site, where the population is particularly vulnerable due to their acute illnesses. The purpose of this project was to analyze the root causes of all cases of medication error in this hospital\u27s PICU during the last 2 years. The literature review was used to categorize secondary data extracted from the hospital\u27s quality assurance database. An analysis of the 41 total medication errors showed that 49% of the medication errors made in the PICU were due to the nurse administering the incorrect dose of medication. Most (60%) occurred on the day shift when the unit was busy and the patient\u27s medication orders were constantly being changed. Missed doses\u27 mostly due to oversight and ineffective follow-up by clinical staff, pharmacy, and providers accounted for 27% of the medication errors. There were instances in which the physician and the pharmacy did not properly order and verify a medication. The summary of the root cause analysis and recommendations from the literature for improved clinical practice will be presented through the hospital\u27s quality assurance structure. Recommendations include implementing computerized physician order entry, regular education of staff, involvement of the pharmacist in new medication orders, updated nursing protocols, and support systems for decision making. The implications of this project for positive social change include the impact of improved practices on decreasing medication errors and improving health outcomes in the PICU population

Mimetic Isomorphism and TechnologyEvaluation: Does Imitation TranscendJudgment?

Although contemporary technology adoption theories incorporate societal norms or peer references, it is unclear to what extent these factors influence choices. In this research, we apply institutional theory and the concept of mimetic isomorphism as peer influences to the technology evaluation process to determine the degree to which managers conform when selecting between competing information technologies. More specifically, we test if peer influence is sufficient to overcome a product evaluation where the choice is believed to be inferior. An experiment is conducted using the World Wide Web and a national sample of 348 senior information technology and business decision makers. Significant effects are found where inferior technologies are selected if respondents are informed that competitors have selected them. Further research is warranted to investigate the presence and extent of these effects but overall implications are that product evaluations may be more ornamental than substantive

PNN-based Rockburst Prediction Model and Its Applications

Rock burst is one of main engineering geological problems significantly threatening the safety of construction. Prediction of rock burst is always an important issue concerning the safety of workers and equipment in tunnels. In this paper, a novel PNN-based rock burst prediction model is proposed to determine whether rock burst will happen in the underground rock projects and how much the intensity of rock burst is. The probabilistic neural network (PNN) is developed based on Bayesian criteria of multivariate pattern classification. Because PNN has the advantages of low training complexity, high stability, quick convergence, and simple construction, it can be well applied in the prediction of rock burst. Some main control factors, such as rocks’ maximum tangential stress, rocks’ uniaxial compressive strength, rocks’ uniaxial tensile strength, and elastic energy index of rock are chosen as the characteristic vector of PNN. PNN model is obtained through training data sets of rock burst samples which come from underground rock project in domestic and abroad. Other samples are tested with the model. The testing results agree with the practical records. At the same time, two real-world applications are used to verify the proposed method. The results of prediction are same as the results of existing methods, just same as what happened in the scene, which verifies the effectiveness and applicability of our proposed work.El fracturamiento o explosión de rocas es uno de los principales problemas en ingeniería geológica que amenaza significativamente la seguridad de una construcción. La predicción del fracturamiento de rocas es importante para la seguridad de los trabajadores y el equipamiento en túneles. En este artículo se propone un nuevo modelo de predicción de fracturamiento de rocas basado en una red neuronal probabilística (PNN por sus siglas en inglés) para determinar la posible ocurrencia e intensidad de uno de estos eventos en proyectos subterráneos. La PNN se desarrolló con base en un criterio Bayesiano para la clasificación multivariada de patrones. Debido a que la PNN tiene las ventajas de una menor complejidad de adiestramiento, estabilidad, rápida convergencia y simplicidad en su construcción, se puede adecuar en la predicción del fracturamiento de rocas. Algunos factores principales de control, como la fuerza máxima tangencial de rocas, la resistencia de compresión uniaxial, la fuerza de tensión uniaxial, y el índice de energía elástica de las rocas fueron escogidos como los vectores característicos de la PNN. El modelo se obtuvo a través del adiestramiento de datos sobre fracturamiento de rocas en proyectos subterráneos en diferentes localidades. Otras datos también se analizaron con el modelo. Los resultados de la evaluación se ajustan a los registros observados. Simultáneamente, se utilizaron dos aplicaciones prácticas para verificar el método propuesto. Los resultados de la predicción son similares a los de métodos existentes, un factor que además se presentó en las pruebas de campo, lo que demuestra la efectividad y la aplicabilidad de la metodología propuesta

Association between functional capacity and motivation to engage in physical activity before surgery

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Ethanol induces cell-cycle activity and reduces stem cell diversity to alter both regenerative capacity and differentiation potential of cerebral cortical neuroepithelial precursors

BACKGROUND: The fetal cortical neuroepithelium is a mosaic of distinct progenitor populations that elaborate diverse cellular fates. Ethanol induces apoptosis and interferes with the survival of differentiating neurons. However, we know little about ethanol's effects on neuronal progenitors. We therefore exposed neurosphere cultures from fetal rat cerebral cortex, to varying ethanol concentrations, to examine the impact of ethanol on stem cell fate. RESULTS: Ethanol promoted cell cycle progression, increased neurosphere number and increased diversity in neurosphere size, without inducing apoptosis. Unlike controls, dissociated cortical progenitors exposed to ethanol exhibited morphological evidence for asymmetric cell division, and cells derived from ethanol pre-treated neurospheres exhibited decreased proliferation capacity. Ethanol significantly reduced the numbers of cells expressing the stem cell markers CD117, CD133, Sca-1 and ABCG2, without decreasing nestin expression. Furthermore, ethanol-induced neurosphere proliferation was not accompanied by a commensurate increase in telomerase activity. Finally, cells derived from ethanol-pretreated neurospheres exhibited decreased differentiation in response to retinoic acid. CONCLUSION: The reduction in stem cell number along with a transient ethanol-driven increase in cell proliferation, suggests that ethanol promotes stem to blast cell maturation, ultimately depleting the reserve proliferation capacity of neuroepithelial cells. However, the lack of a concomitant change in telomerase activity suggests that neuroepithelial maturation is accompanied by an increased potential for genomic instability. Finally, the cellular phenotype that emerges from ethanol pre-treated, stem cell depleted neurospheres is refractory to additional differentiation stimuli, suggesting that ethanol exposure ablates or delays subsequent neuronal differentiation

Age-Related Effects on MSC Immunomodulation, Macrophage Polarization, Apoptosis, and Bone Regeneration Correlate with IL-38 Expression

Mesenchymal stem cells (MSCs) are known to promote tissue regeneration and suppress excessive inflammation caused by infection or trauma. Reported evidence indicates that various factors influence the expression of MSCs' endogenous immunomodulatory properties. However, the detailed interactions of MSCs with macrophages, which are key cells involved in tissue repair, and their regulatory mechanisms are not completely understood. We herein investigated how age-related immunomodulatory impairment of MSCs alters the interaction of MSCs with macrophages during bone healing using young (5-week old) and aged (50-week old) mice. To clarify the relationship between inflammatory macrophages (M1) and MSCs, their spatiotemporal localization at the bone healing site was investigated by immunostaining, and possible regulatory mechanisms were analyzed in vitro co-cultures. Histomorphometric analysis revealed an accumulation of M1 and a decrease in MSC number at the healing site in aged mice, which showed a delayed bone healing. In in vitro co-cultures, MSCs induced M1 apoptosis through cell-to-cell contact but suppressed the gene expression of pro-inflammatory cytokines by soluble factors secreted in the culture supernatant. Interestingly, interleukin 38 (Il-38) expression was up-regulated in M1 after co-culture with MSCs. IL-38 suppressed the gene expression of inflammatory cytokines in M1 and promoted the expression of genes associated with M1 polarization to anti-inflammatory macrophages (M2). IL-38 also had an inhibitory effect on M1 apoptosis. These results suggest that MSCs may induce M1 apoptosis, suppress inflammatory cytokine production by M1, and induce their polarization toward M2. Nevertheless, in aged conditions, the decreased number and immunomodulatory function of MSCs could be associated with a delayed M1 clearance (i.e., apoptosis and/or polarization) and consequent delayed resolution of the inflammatory phase. Furthermore, M1-derived IL-38 may be associated with immunoregulation in the tissue regeneration site

CD24 Expression Identifies Teratogen-Sensitive Fetal Neural Stem Cell Subpopulations: Evidence from Developmental Ethanol Exposure and Orthotopic Cell Transfer Models

Ethanol is a potent teratogen. Its adverse neural effects are partly mediated by disrupting fetal neurogenesis. The teratogenic process is poorly understood, and vulnerable neurogenic stages have not been identified. Identifying these is a prerequisite for therapeutic interventions to mitigate effects of teratogen exposures.We used flow cytometry and qRT-PCR to screen fetal mouse-derived neurosphere cultures for ethanol-sensitive neural stem cell (NSC) subpopulations, to study NSC renewal and differentiation. The identity of vulnerable NSC populations was validated in vivo, using a maternal ethanol exposure model. Finally, the effect of ethanol exposure on the ability of vulnerable NSC subpopulations to integrate into the fetal neurogenic environment was assessed following ultrasound guided, adoptive transfer.Ethanol decreased NSC mRNAs for c-kit, Musashi-1and GFAP. The CD24(+) NSC population, specifically the CD24(+)CD15(+) double-positive subpopulation, was selectively decreased by ethanol. Maternal ethanol exposure also resulted in decreased fetal forebrain CD24 expression. Ethanol pre-exposed CD24(+) cells exhibited increased proliferation, and deficits in cell-autonomous and cue-directed neuronal differentiation, and following orthotopic transplantation into naïve fetuses, were unable to integrate into neurogenic niches. CD24(depleted) cells retained neurosphere regeneration capacity, but following ethanol exposure, generated increased numbers of CD24(+) cells relative to controls.Neuronal lineage committed CD24(+) cells exhibit specific vulnerability, and ethanol exposure persistently impairs this population's cell-autonomous differentiation capacity. CD24(+) cells may additionally serve as quorum sensors within neurogenic niches; their loss, leading to compensatory NSC activation, perhaps depleting renewal capacity. These data collectively advance a mechanistic hypothesis for teratogenesis leading to microencephaly

The Sociology of a Market Analysis Tool: How Industry Analysts Sort Vendors and Organize Markets

The information technology (IT) marketplace appears to be shaped by new kinds of specialist industry analysts that link technology supply and use through offering a commodified form of knowledge and advice. We focus on the work of one such organisation, the Gartner Group, and with how it produces a market analysis tool called the ‘Magic Quadrant’. Widely circulated amongst the IT community, the device compares and sorts vendors according to a number of more or less intangible properties (such as vendor ‘competence’ and ‘vision’). Given that potential adopters of IT systems are drawn to assess the reputation and likely behaviour of vendors, these tools play an important role in mediating choice during procurement. Our interest is in understanding how such objects are constructed as well as how they wield influence. We draw on the recent ‘performativity’ debate in Economic Sociology and the Sociology of Finance to show how Magic Quadrants are not simply describing but reshaping aspects of the IT arena. Importantly, in sketching this sociology of a market analysis tool, we also attend to the contested nature of the Magic Quadrant. Whilst Gartner attempt to establish this device as an ‘impartial’ and ‘legitimate’ arbiter of vendor performance, it is often viewed sceptically on the grounds that industry analysts are not always independent of the vendors they are assessing. Paradoxically these devices remain influential despite these sceptical assessments