Sustaining the mobile medical units to bring equity in healthcare: a PLS-SEM approach.

BACKGROUND: Equitable access to healthcare for rural, tribal, and underprivileged people has been an emerging area of interest for researchers, academicians, and policymakers worldwide. Improving equitable access to healthcare requires innovative interventions. This calls for clarifying which operational model of a service innovation needs to be strengthened to achieve transformative change and bring sustainability to public health interventions. The current study aimed to identify the components of an operational model of mobile medical units (MMUs) as an innovative intervention to provide equitable access to healthcare. METHODS: The study empirically examined the impact of scalability, affordability, replicability (SAR), and immunization performance on the sustainability of MMUs to develop a framework for primary healthcare in the future. Data were collected via a survey answered by 207 healthcare professionals from six states in India. Partial least squares structural equation modeling (PLS-SEM) was conducted to empirically determine the interrelationships among various constructs. RESULTS: The standardized path coefficients revealed that three factors (SAR) significantly influenced immunization performance as independent variables. Comparing the three hypothesized relationships demonstrates that replicability has the most substantial impact, followed by scalability and affordability. Immunization performance was found to have a significant direct effect on sustainability. For evaluating sustainability, MMUs constitute an essential component and an enabler of a sustainable healthcare system and universal health coverage. CONCLUSION: This study equips policymakers and public health professionals with the critical components of the MMU operational model leading toward sustainability. The research framework provides reliable grounds for examining the impact of scalability, affordability, and replicability on immunization coverage as the primary public healthcare outcome.

Vaccine hesitancy: a structured review from a behavioral perspective (2015-2022).

Vaccine hesitancy, a complex behavioral phenomenon, poses a significant global health threat and has gained renewed attention amidst the COVID-19 pandemic. This paper scrutinized peer-reviewed literature on vaccine hesitancy published from 2015 to 2022, with a specific focus on behavioral perspectives, utilizing a Theories-Constructs-Variables-Contexts-Methods (TCVCM) framework. The study highlighted prominent theoretical approaches, abstract concepts, research variables, global contexts and academic techniques employed across a selected sample of 138 studies. The result is a consolidated overview of research and schematization of the factors influencing vaccine hesitancy and vaccination behaviors. These include individual-level, contextual, vaccine-specific, organizational, and public-policy-related dynamics. The findings corroborated the complexity of vaccine hesitancy and emphasized the difficulties of pursuing vaccine advocacy. The analysis also identified several directions for future research, and the need to conduct more contextual studies in low- and middle-income nations to bring out the cross-cultural nuances of vaccine hesitancy.

Cost analysis of different medical oxygen sources for a healthcare facility in India.

Background and Aims: Multiple sources of medical oxygen, namely liquid medical oxygen (LMO) tanks, pressure swing adsorption (PSA) plants, concentrators, and gaseous cylinders, are available at different healthcare facilities. These sources of oxygen have varying installation and operational costs. In low-resource settings, it is imperative to utilise these assets optimally. This study investigated the operational costs of multiple oxygen sources available at a healthcare facility. Methods: A Microsoft (MS) Excel-based model was developed to analyse and compare the oxygen manufacturing costs (in ₹/m3) using PSA plants and procurement costs (in ₹/m3) of LMO and third-party vendor-refilled cylinders. Results: The oxygen manufacturing costs for PSA plants of different capacities and running times on electricity and diesel generators (DGs) as a power source were calculated. This study highlights the cost-benefit of using PSA plants over LMO and third-party vendor-refilled cylinders as a source of oxygen. PSA plants are most economical when they are of higher capacity and used to their maximum capacity on electricity as the power source. On the contrary, they are most expensive when used on a DG set as a power source. Furthermore, this study provides evidence of PSA plants being more cost-effective for refilling cylinders using a booster compressor unit when compared to third-party vendor-cylinder refilling. Conclusion: Given their cost-effectiveness and low third-party dependence, they should be utilised to their maximum capacity as medical oxygen sources at healthcare facilities.

Reshaping the equitable and inclusive access to healthcare: A qualitative study.

Background: Improving equitable access to healthcare requires innovative interventions and strengthening a service innovation operational model to achieve transformative change and bring sustainability to public health interventions. The current study aims to identify the components of the Mobile Medical Units (MMUs) operational model as an innovative intervention to provide equitable and inclusive access to healthcare. Methods: The study used qualitative research to identify the components of the operational model of MMUs for primary healthcare in future. Data has been collected via semi-structured in-depth interviews with 103 healthcare professionals from six states representing India's Tier I, Tier II, and Tier III regions. A thematic analysis was performed to examine emergent salient themes. Results: The study identified and examined scalability, affordability, replicability, and sustainability as the four critical components of the operational model of MMUs. The findings of the study indicated that MMUs with these four components played a vital role in COVID-19 immunization, especially in resource-limited settings. The study found that MMUs are a cost-effective and scalable healthcare delivery model that can be easily replicated in primary healthcare service delivery. Conclusion: The findings underscore the significant role of MMUs in addressing healthcare disparities, particularly in resource-limited settings. The adaptability and cost-effectiveness of MMUs make them an ideal solution for primary healthcare delivery, especially in Tier I, II, and III regions of India. It lays a foundation for future research and policy-making, emphasizing the need for innovative, equitable, and sustainable healthcare delivery models like MMUs to transform and strengthen healthcare systems globally.

Data analytics and knowledge management approach for COVID-19 prediction and control.

The Coronavirus Disease (COVID-19) caused by SARS-CoV-2, continues to be a global threat. The major global concern among scientists and researchers is to develop innovative digital solutions for prediction and control of infection and to discover drugs for its cure. In this paper we developed a strategic technical solution for surveillance and control of COVID-19 in Delhi-National Capital Region (NCR). This work aims to elucidate the Delhi COVID-19 Data Management Framework, the backend mechanism of integrated Command and Control Center (iCCC) with plugged-in modules for various administrative, medical and field operations. Based on the time-series data extracted from iCCC repository, the forecasting of COVID-19 spread has been carried out for Delhi using the Auto-Regressive Integrated Moving Average (ARIMA) model as it can effectively predict the logistics requirements, active cases, positive patients, and death rate. The intelligence generated through this research has paved the way for the Government of National Capital Territory Delhi to strategize COVID-19 related policies formulation and implementation on real time basis. The outcome of this innovative work has led to the drastic reduction in COVID-19 positive cases and deaths in Delhi-NCR.

Examining the Impact of Key Factors on COVID-19 Vaccination Coverage in India: A PLS-SEM Approach.

During the coronavirus disease 2019 (COVID-19) pandemic, numerous factors determined the performance of COVID-19 vaccination coverage. The purpose of this study is to examine the influence of factors such as government stewardship, planning and implementation, and community participation on COVID-19 vaccination coverage. This study applied partial least square structured equation modeling (PLS-SEM) by analyzing 187 responses from the stakeholders involved in vaccination programs in four select states of India. This study empirically validates a framework for improving vaccination coverage by confirming the significant impact of planning and implementation on vaccination coverage followed by government stewardship and community participation. Additionally, this study highlights the individual impact of each factor on vaccination coverage. Based on the findings, strategic recommendations were proposed that can be utilized for formulating policy-level actions to facilitate the vaccination program.

Modeling a COVID-19 Vaccination Campaign in the State of Madhya Pradesh, India.

COVID-19 vaccination campaigns have been launched across the globe to mitigate the impact of the COVID-19 disease. However, COVID-19 vaccination campaigns (Vaccination campaigns are the complete process of COVID-19 vaccination campaigns beyond just administrating vaccines.) are a complex multi-stakeholder process, and therefore, it is important to understand the key components and drivers of vaccination campaigns to help devise strategies to increase vaccination coverage for existing and future vaccination efforts. A system dynamics modeling approach was used to trace the vaccination campaign for the Indian state of Madhya Pradesh. The results identified the key stakeholders of the vaccination campaign and their inter-linkages, and the diverse perspectives of stakeholders of vaccination campaigns in Madhya Pradesh were collated in a structured format. Further, system dynamics models were developed to capture all aspects of the vaccination campaign in Madhya Pradesh, including the challenges and innovations. The outcomes of the study can assist academicians, practitioners, and policymakers develop vaccination programs at sub-national, national, and global levels. They will guide decision-makers to take preemptive measures to mitigate possible risks and challenges and provide improved services as part of vaccination campaigns. Supplementary Information: The online version contains supplementary material available at 10.1007/s40171-022-00326-9.

Developing an evidence-based TISM: an application for the success of COVID-19 Vaccination Drive.

The study illustrates an application of evidence data for performing Total Interpretive Structural Modeling (TISM). TISM is widely used to analyze the critical success factors or inhibitors and their interlinkages. This study uses learning from evidence data, specifically social media analytics, to identify the relationship between the elements. Thus, it leads to the advancement of the TISM-P methodology with evidence-based TISM (TISM-E). This study uses Twitter as a source of evidence data. Further, 2,60,297 tweets were used to illustrate the process of TISM-E. The paper demonstrates the application of TISM-E for the success of the COVID-19 vaccination drive. The pandemic effects are long-term; therefore, the hierarchical model developed shows a sustainable approach for vaccinating maximum population. Further, the framework developed will ensure the distribution efficacy of vaccines. In addition, it will aid practitioners in developing future vaccination policies. The enhanced model provides evidence for polarity (positive/negative) of relationships and can help to build propositions for theory development. The study contributes to healthcare, modeling research, and graph-theoretic literature.

The Trajectory of Two Decades of Global Journal of Flexible Systems Management and Flexibility Research: A Bibliometric Analysis.

In the year 2020, the Global Journal of Flexible Systems Management (GJFSM) has celebrated its two decades of publication. This study is an attempt to commemorate the two decades of publication by presenting the overview of the GJFSM along with the trajectory of flexibility research in various journals. By using multiple bibliometric tools and indicators, the study finds that the GJFSM has grown over the years in terms of total publications and citations. The contributors are from across the globe, i.e., South America, North America, Asia, Europe, Africa, and the Pacific. The Journal publishes several flexibility areas, including information systems flexibility, financial flexibility, supply chain flexibility, technology management flexibility, marketing flexibility, organizational flexibility, strategic flexibility, and manufacturing flexibility. The GJFSM is cited by authors from various countries across the globe. It has been cited across different Scopus categorizations, including "Strategy and Management," "Business and International Management," "General Business, Management and Accounting," "Industrial and Manufacturing Engineering," and "Management Science and Operations Research." Keyword co-occurrences analysis helps to analyze the various groups of keywords cited together in the GJFSM. Co-citation analysis of references helps to identify crucial clusters of GJFSM, i.e., strategic flexibility, manufacturing flexibility, the conceptual framework of flexibility, supply chain flexibility, modeling flexibility, and application of TISM. Overall, GJFSM has seen an increase in both publications and citations, reflecting its increasing presence among the journals publishing flexibility research. The diversity of flexibility research and its contributions to research under-one-roof make this Journal unique. The paper concludes with the gap areas of flexibility research and the way forward.