Predicting Patient Length of Stay Using Artificial Intelligence to Assist Health Care Professionals in Resource Planning and Scheduling Decisions

Artificial Intelligence (AI) significantly revolutionizes and transforms the global healthcare industry by improving outcomes, increasing efficiency, and enhancing resource utilization. The applications of AI impact every aspect of healthcare operation, particularly resource allocation and capacity planning. This study proposes a multi-step AI-based framework and applies it to a real dataset to predict the length of stay (LOS) for hospitalized patients. The results show that the proposed framework can predict the LOS categories with an AUC of 0.85 and their actual LOS with a mean absolute error of 0.85 days. This framework can support decision-makers in healthcare facilities providing inpatient care to make better front-end operational decisions, such as resource capacity planning and scheduling decisions. Predicting LOS is pivotal in today’s healthcare supply chain (HSC) systems where resources are scarce, and demand is abundant due to various global crises and pandemics. Thus, this research’s findings have practical and theoretical implications in AI and HSC management.

Sustainable municipal solid waste management (MSWM) in the smart cities in Indian context

PurposeSmart cities in India are going to be a reality very soon by turning challenges into opportunities for the society. However, due to rapid increase in population burden, fast urbanization and growing demand of advanced services in the smart cities, the quantity of per capita municipal solid waste (MSW) has escalated. Moreover, the COVID-19 pandemic has further challenged the municipal solid waste management (MSWM) system with the increasing amount of infectious wastes coming from households (HHs), quarantine centers, healthcare facilities, vaccination centers, etc. Therefore, the present study attempts to explore and analyze the various dimensions of sustainable MSWM system in the smart cities.Design/methodology/approachThe study identifies 13 factors of sustainable MSWM system from the literature, field surveys and stakeholders' opinions. Thereafter, stakeholders' opinions are collected and analyzed using total interpretive structural modeling (TISM) approach to explore the interrelationships among the factors of sustainable MSWM system. These relationships are further validated through the empirical investigation of the real-life case study of Rourkela Municipal Corporation (RMC), Odisha, India.FindingsThe TISM approach places all 13 factors into six levels in the hierarchical digraph depending upon the inputs received from the various stakeholders on their interrelationships. Study also validates the proposed TISM model by collecting the data of RMC, Odisha, on the development of MSWM system over the period of 2015–2021.Practical implicationsThe study also highlights various implications for the other developing cities and stakeholders to set up the roadmap for developing the sustainable MSWM system. Study defines “IT platform” and “awareness among citizens” as the base of the sustainable MSWM system in any smart city.Originality/valueThe present study is the first of its kind to explore the interrelationships among the factors of sustainable MSWM system by using TISM approach. Moreover, the proposed TISM framework is further validated through the empirical journey of one of the smart cities in India.

Indoor Air Quality in Healthcare Units—A Systematic Literature Review Focusing Recent Research

The adequate assessment and management of indoor air quality in healthcare facilities is of utmost importance for patient safety and occupational health purposes. This study aims to identify the recent trends of research on the topic through a systematic literature review following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology. A total of 171 articles published in the period 2015–2020 were selected and analyzed. Results show that there is a worldwide growing research interest in this subject, dispersed in a wide variety of scientific journals. A textometric analysis using the IRaMuTeQ software revealed four clusters of topics in the sampled articles: physicochemical pollutants, design and management of infrastructures, environmental control measures, and microbiological contamination. The studies focus mainly on hospital facilities, but there is also research interest in primary care centers and dental clinics. The majority of the analyzed articles (85%) report experimental data, with the most frequently measured parameters being related to environmental quality (temperature and relative humidity), microbiological load, CO2 and particulate matter. Non-compliance with the WHO guidelines for indoor air quality is frequently reported. This study provides an overview of the recent literature on this topic, identifying promising lines of research to improve indoor air quality in healthcare facilities.

Determinants of Stillbirth From Two Observational Studies Investigating Deliveries in Kano, Nigeria

Background:Stillbirths are a poignant representation of global inequality. Nigeria is documented to have the second highest rate; yet, the reporting system is inadequate in most Nigerian healthcare facilities. The aim was to identify the determinants of stillbirth among deliveries in the Murtala Muhammad Specialist Hospital (MMSH), Kano, Nigeria.Methods:Two study designs were used: a case-control study (S1) and a prospective cohort study (S2). Both studies were carried out at the MMSH. For S1, stillbirths were retrospectively matched to a livebirth by time (target of 24 hours' time variation) to establish a case-control study with a 1:1 ratio. Eligibility into S2 included all mothers who were presented at the MMSH in labour regardless of birth outcome. Both were based on recruitment durations, not sample sizes (3 months and 2 months, respectively, 2017–2018). The demographic and clinical data were collected through paper-based questionnaires. Univariable logistic regression was used. Multivariable logistic regression was used to explore relationships between area type and other specific factors.Findings:Stillbirth incidence in S2 was 180/1,000 births. Stillbirth was associated with the following factors; no maternal education, previous stillbirth(s), prematurity, living in both semi-rural and rural settings, and having extended time periods between rupture of membranes and delivery. Findings of the multivariable analysis (S1 and S2) indicated that the odds of stillbirth, for those living in a rural area, were further exacerbated in those mothers who had no education, lived in a shack, or had any maternal disease.Interpretation:This research identifies the gravity of this situation in this area and highlights the need for action. Further understanding of some of the findings and exploration into associations are required to inform intervention development.Funding:This collaboration was partially supported by funding from Health and Care Research Wales.

Understanding the role of the bring-your-own-device policy in medical education and healthcare delivery at the University of Botswana’s Faculty of Medicine

Purpose Seeking to leverage on benefits of personal mobile device use, medical schools and healthcare facilities are increasingly embracing the use of personal mobile devices for medical education and healthcare delivery through bring-your-own-device (BYOD) policies. However, empirical research findings that could guide the development of BYOD policies are scarce. Available research is dominated by studies that were guided by technocentric approaches, hence seemingly overlooking the complexities of the interactions of actors in mobile device technologies implementation. The purpose of this study was to use the actor–network theory to explore the potential role of a BYOD policy at the University of Botswana’s Faculty of Medicine. Design/methodology/approach Purposive sampling was used to select the participants and interviews, focus group discussions, observations and document analysis were used to collect data. Data were collected from 27 participants and analysed using grounded theory techniques. Emerging themes were continually compared and contrasted with incoming data to create broad themes and sub-themes and to establish relationships or patterns from the data. Findings The results suggest that the potential roles for BYOD policy include promoting appropriate mobile device use, promoting equitable access to mobile devices and content, and integrating mobile devices into medical education, healthcare delivery and other institutional processes. Research limitations/implications BYOD policy could be conceptualized and researched as a “script” that binds actors/actants into a “network” of constituents (with shared interests) such as medical schools and healthcare facilities, mobile devices, internet/WiFi, computers, software, computer systems, medical students, clinical teachers or doctors, nurses, information technology technicians, patients, curriculum, information sources or content, classrooms, computer labs and infections. Practical implications BYOD is a policy that seeks to represent the interests (presents as a solution to their problems) of the key stakeholders such as medical schools, healthcare facilities and mobile device users. BYOD is introduced in medical schools and healthcare facilities to promote equitable access to mobile devices and content, appropriate mobile device use and ensure distribution of liability between the mobile device users and the institution and address the implication of mobile device use in teaching and learning. Originality/value The BYOD policy is a comprehensive solution that transcends other institutional policies and regulations to fully integrate mobile devices in medical education and healthcare delivery.

Rapid antigen testing as a reactive response to surges in nosocomial SARS-CoV-2 outbreak risk

Healthcare facilities are vulnerable to SARS-CoV-2 introductions and subsequent nosocomial outbreaks. Antigen rapid diagnostic testing (Ag-RDT) is widely used for population screening, but its health and economic benefits as a reactive response to local surges in outbreak risk are unclear. We simulate SARS-CoV-2 transmission in a long-term care hospital with varying COVID-19 containment measures in place (social distancing, face masks, vaccination). Across scenarios, nosocomial incidence is reduced by up to 40-47% (range of means) with routine symptomatic RT-PCR testing, 59-63% with the addition of a timely round of Ag-RDT screening, and 69-75% with well-timed two-round screening. For the latter, a delay of 4-5 days between the two screening rounds is optimal for transmission prevention. Screening efficacy varies depending on test sensitivity, test type, subpopulations targeted, and community incidence. Efficiency, however, varies primarily depending on underlying outbreak risk, with health-economic benefits scaling by orders of magnitude depending on the COVID-19 containment measures in place.

Survival and Transcriptomic Response of Clinically relevant pathogens on Surfaces in Relation to Probiotic and Traditional Cleaning Strategies

Prolonged survival of clinically relevant pathogens on inanimate surfaces represents a major concern in healthcare facilities. Contaminated surfaces can serve as reservoirs of potential pathogens and greatly hinder the prevention of healthcare-associated infections. Probiotic cleaning using environmental microorganisms to promote inter-species competition has been proposed as an alternative to traditional chemical-based cleaning using antimicrobials. Probiotic cleaning seeks to take advantage of ecological principles such as competitive exclusion and utilize benign microorganisms to inhibit viable pathogens on indoor surfaces. However, limited mechanistic study has yielded direct evidence that enables the scientific community to understand the stress response, or microbe-microbe interactions between healthcare-associated pathogens and probiotic bacteria. Therefore, to bridge this knowledge gap, we combined transcriptomics and traditional microbiology techniques to investigate the differential impact of chemical-based and probiotic surface cleaners on the survival of Acinetobacter baumannii and Klebsiella pneumoniae, two clinically important pathogens. Although probiotic Bacillus included in a commercialized All-Purpose Probiotic Cleaner persisted on surfaces for an extended period of time, surfaces contaminated with A. baumannii cleaned using chemical-based detergent with and without probiotic Bacillus showed no statistical difference in the viable colony forming units (CFUs) of A. baumannii. Similarly, for Klebsiella pneumoniae, there were negligible statistical differences in CFUs between probiotic and detergent cleaning scenarios. The transcriptome of A. baumannii with and without probiotic addition shared a high degree of similarity in overall gene expression, while the transcriptome of K. pneumoniae with and without probiotic addition differed in overall gene expression. Together, these results highlight the need to fully understand the underlying biological and ecological mechanisms for different pathogens and practical implications of probiotic indoor cleaning.