In this paper, we introduce a new generalization of the power Lindley distribution referred to as the alpha power transformed power Lindley (APTPL). The APTPL model provides a better fit than the power Lindley distribution. It includes the alpha power transformed Lindley, power Lindley, Lindley, and gamma as special submodels. Various properties of the APTPL distribution including moments, incomplete moments, quantiles, entropy, and stochastic ordering are obtained. Maximum likelihood, maximum products of spacings, and ordinary and weighted least squares methods of estimation are utilized to obtain the estimators of the population parameters. Extensive numerical simulation is performed to examine and compare the performance of different estimates. Two important data sets are employed to show how the proposed model works in practice.

We propose a new distribution with two parameters called the odd Fréchet inverse Rayleigh (OFIR) distribution. The new model can be more flexible. Several of its statistical properties are studied. The maximum likelihood (ML) estimation is used to drive estimators of OFIR parameters. The importance and flexibility of the new model is assessed using one real data set.

Background and Objectives:The general surgeon's robotic learning curve may improve if the experience is classified into categories based on the complexity of the procedures in a small community hospital. The intraoperative time should decrease and the incidence of complications should be comparable to conventional laparoscopy. The learning curve of a single robotic general surgeon in a small community hospital using the da Vinci S platform was analyzed.Methods:Measured parameters were operative time, console time, conversion rates, complications, surgical site infections (SSIs), surgical site occurrences (SSOs), length of stay, and patient demographics.Results:Between March 2014 and August 2015, 101 robotic general surgery cases were performed by a single surgeon in a 266-bed community hospital, including laparoscopic cholecystectomies, inguinal hernia repairs; ventral, incisional, and umbilical hernia repairs; and colorectal, foregut, bariatric, and miscellaneous procedures. Ninety-nine of the cases were completed robotically. Seven patients were readmitted within 30 days. There were 8 complications (7.92%). There were no mortalities and all complications were resolved with good outcomes. The mean operative time was 233.0 minutes. The mean console operative time was 117.6 minutes.Conclusion:A robotic general surgery program can be safely implemented in a small community hospital with extensive training of the surgical team through basic robotic skills courses as well as supplemental educational experiences. Although the use of the robotic platform in general surgery could be limited to complex procedures such as foregut and colorectal surgery, it can also be safely used in a large variety of operations with results similar to those of conventional laparoscopy.

Background Some previous studies have investigated the attitudes of healthcare professionals towards certain aspects of the COVID-19 outbreak. In addition, some general frameworks have been proposed to manage the pandemic. Objective The purpose of this article was to analyze the attitudes of healthcare practitioners in Saudi Arabia towards the treatment of patients with COVID-19, work planning of practitioners, leadership approaches to manage the pandemic, sharing information strategies, medical errors, compliance with procedures, and challenges faced by the practitioners. Furthermore, another objective was to propose a general framework for managing the COVID-19 outbreak in Saudi Arabia. Methods To achieve these purposes, a survey was designed based on an online questionnaire that was initially sent via WhatsApp, Twitter, Facebook, and email to 336 healthcare practitioners working in 7 hospitals in Saudi Arabia. The response rate was 30.4%. Results The outcomes indicated that healthcare practitioners in Saudi Arabia had positive attitudes towards effective communication and interaction between health professionals and patients, leadership and maintenance of team coordination, work planning, communication and cooperation between team members, training and skills development of healthcare professionals, implementing strict procedures to avoid errors and control the spread of the COVID-19 pandemic, maintaining an adequate supply of medicines and medical equipment, and obtaining the support of the government, the community, and the people. Conclusion Based on the findings, it was possible to suggest that the management of health care operations related to the COVID-19 outbreak in Saudi Arabia requires effective collaboration and information sharing among various stakeholders. In this sense, communication, effective leadership, coordination and work planning, adequate treatment for patients, strict compliance with hospital rules and procedures, preventive and regulatory measures, and training and support for health professionals, were parameters considered in the general qualitative framework suggested in this study for managing the COVID-19 pandemic in Saudi Arabia. The propositions presented in this study can help the Saudi Arabian government implement an effective plan to control the spread of the COVID-19 pandemic in this country.