scholarly journals Diversity, entrepreneurial innovation, and performance of healthcare sector in the COVID ‐19 pandemic period

2022 ◽  
Author(s):  
Hani El Chaarani ◽  
Lukman Raimi
2017 ◽  
Vol 6 (1) ◽  
pp. 52
Author(s):  
Sumathi G N

<span lang="EN-US">The study is aimed to identify various human resource practices in the public healthcare sector and to measure the level of human resource practices. The study adopts the perceptual view of healthcare professionals such as medical officers and staff nurses working in Primary Health Centres of Tamilnadu. A survey using a questionnaire is used to collect data from healthcare professionals. The results indicated that human resource practices such as job autonomy and job security are perceived to be useful and necessary, while training and performance management system are found to provide necessary inputs for carrying job duties and practices such as career growth opportunities and compensation need the attention of the officials of Health and Family Welfare department of Tamilnadu Government for enhancing the utility of these practices</span><span>.</span>


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ginevra Gravili ◽  
Francesco Manta ◽  
Concetta Lucia Cristofaro ◽  
Rocco Reina ◽  
Pierluigi Toma

PurposeThe aim of this paper is to analyze and measure the effects of intellectual capital (IC), i.e. human capital (HC), relational capital (RC) and structural capital (SC), on healthcare industry organizational performance and understanding the role of data analytics and big data (BD) in healthcare value creation (Wang et al., 2018). Through the assessment of determined variables specific for each component of IC, the paper identifies the guidelines and suggests propositions for a more efficient response in terms of services provided to citizens and, specifically, patients, as well as predicting effective strategies to improve the care management efficiency in terms of cost reduction.Design/methodology/approachThe study has a twofold approach: in the first part, the authors operated a systematic review of the academic literature aiming to enquire the relationship between IC, big data analytics (BDA) and healthcare system, which were also the descriptors employed. In the second part, the authors built an econometric model analyzed through panel data analysis, studying the relationship between IC, namely human, relational and structural capital indicators, and the performance of healthcare system in terms of performance. The study has been conducted on a sample of 28 European countries, notwithstanding the belonging to specific international or supranational bodies, between 2011 and 2016.FindingsThe paper proposes a data-driven model that presents new approach to IC assessment, extendable to other economic sectors beyond healthcare. It shows the existence of a positive impact (turning into a mathematical inverse relationship) of the human, relational and structural capital on the performance indicator, while the physical assets (i.e. the available beds in hospitals on total population) positively mediates the relationship, turning into a negative impact of non-IC related inputs on healthcare performance. The result is relevant in terms of managerial implications, enhancing the opportunity to highlight the crucial role of IC in the healthcare sector.Research limitations/implicationsThe relationship between IC indicators and performance could be employed in other sectors, disseminating new approaches in academic research. Through the establishment of a relationship between IC factors and performance, the authors implemented an approach in which healthcare organizations are active participants in their economic and social value creation. This challenges the views of knowledge sharing deeply held inside organizations by creating “new value” developed through a more collaborative and permeated approach in terms of knowledge spillovers. A limitation is given by a fragmented policymaking process which carries out different results in each country.Practical implicationsThe analysis provides interesting implications on multiple perspectives. The novelty of the study provides interesting implications for managers, practitioners and governmental bodies. A more efficient healthcare system could provide better results in terms of cost minimization and reduction of hospitalization period. Moreover, dissemination of new scientific knowledge and drivers of specialization enhances best practices sharing in the healthcare sector. On the other hand, an improvement in preventive medicine practices could help in reducing the overload of demand for curative treatments, on the perspective of sharply decreasing the avoidable deaths rate and improving societal standards.Originality/valueThe authors provide a new holistic framework on the relationship between IC, BDA and organizational performance in healthcare organizations through a systematic review approach and an empirical panel analysis at a multinational level, which is quite a novelty regarding the healthcare. There is little research focussed on healthcare industries' organizational performance, and, specifically, most of the research on IC in healthcare delivered results in terms of theoretical contribution and qualitative analyzes. The authors even contributed to analyze the healthcare industry in the light of the possible existence of synergies and networks among countries.


2018 ◽  
Vol 8 (3) ◽  
pp. 120-125
Author(s):  
Ahmad Alaiad ◽  
Hassan Najadat ◽  
Nusaiba Al-Mnayyis ◽  
Ashwaq Khalil

Data envelopment analysis (DEA) has been widely used in many fields. Recently, it has been adopted by the healthcare sector to improve efficiency and performance of the healthcare organisations, and thus, reducing overall costs and increasing productivity. In this paper, we demonstrate the results of applying the DEA model in Jordanian hospitals. The dataset consists of 28 hospitals and is classified into two groups: efficient and non-efficient hospitals. We applied different association classification data mining techniques (JCBA, WeightedClassifier and J48) to generate strong rules using the Waikato Environment for Knowledge Analysis. We also applied the open source DEA software and MaxDEA software to manipulate the DEA model. The results showed that JCBA has the highest accuracy. However, WeightedClassifier method achieves the highest number of generated rules, while the JCBA method has the minimum number of generated rules. The results have several implications for practice in the healthcare sector and decision makers. Keywords: Component, DEA, DMU, output-oriented model, health care system.


2011 ◽  
pp. 1882-1896
Author(s):  
Nat Natarajan ◽  
Amanda H. Hoffmeister

The healthcare sector is a very important one in many countries and faces numerous quality and performance problems of great significance to all citizens who live there. Although there are many performance parallels between healthcare and other sectors, there are also numerous special issues and terminology, as well. Recent publications on medical errors have put the spotlight on the issue of safety in healthcare. There are opportunities for the healthcare sector to learn from other industries where many techniques and practices for preventing errors have already proved their worth. It is important and beneficial to encourage healthcare specialists to learn from other sectors the concepts, best practices, and tools for preventing errors and improving safety. This chapter addresses the key issues and challenges relating to the management and transfer of such knowledge and places them in the context of quality and knowledge management.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Laura Maran ◽  
Alan Lowe

PurposeThis paper reports an investigation of a hybrid ex-state-owned enterprise (ex-SOE) providing ICT (Information and Communication Technology) services in the Italian healthcare sector (in-house provision). The authors aim to offer a framing that reflects the concerns expressed in the interdisciplinary literature on hybrid SOEs from management, public administration and, more recently, accounting.Design/methodology/approachThis study operationalizes Besharov and Smith’s (2014) theoretical model on multiple logics to analyze institutional structures and organizational outcomes at an ICT in-house provider. It builds on extensive textual analysis of regulatory, archival, survey and interview data.FindingsThe study results show that the combination of hybridity in the form of layering of multiple logics in the health care sector (Polzer et al., 2016) creates problems for the effectiveness of ICT provision. In particular, the hybrid organization the authors study remained stuck in established competing relationships despite a restructure of regional health care governance. The study findings also reflect on the design of organizational control mechanisms when balancing different logics.Research limitations/implicationsThe identified case-study accountability practices and performance system add to the debate on hybrid organizations in the case of ex-SOEs and facilitate the understanding and management of hybrids in the public sector. The authors note policymaking implications.Originality/valueThe authors’ operationalization of Besharov and Smith's (2014) model adds clarity to key elements of their model, notably how to identify evidence in order to disentangle notions of centrality and compatibility. By doing this, the authors’ analysis offers potential insights into both managerial design and policy prescription. The authors provide cautionary tales around institutional reorganization regarding the layered synthesis of logics within these organizations.


2018 ◽  
Vol 49 (6) ◽  
pp. 642-660 ◽  
Author(s):  
Per Backlund ◽  
Hanna Maurin Söderholm ◽  
Henrik Engström ◽  
Magnus Andersson Hagiwara ◽  
Mikael Lebram

Objective.Simulation based training with full-size mannequins is a prominent means of training within the healthcare sector. Prehospital missions include all parts of the healthcare process which take place before a patient is handed over to the receiving hospital. This implies that the context for prehospital care is varied and potentially challenging or dangerous in several ways. In this article we present a study which explores immersion and performance by emergency medical services (EMS) professionals in in a training situation which takes the specifics of prehospital interventions into account. Methods. The study was carried out as a field experiment at an ambulance unit. The experiment was designed to compare the differences between two types of medical scenarios: basic and contextualized. We analyzed the levels of immersion throughout the scenarios and then team performance was evaluated by independent experts. Both analyses were made by observing video recordings from multiple camera angles with a custom made analysis tool. Results. Our results show that the contextualization of a medical scenario increases both immersion as measured by the Immersion Score Rating Instrument (ISRI) and team performance as measured by the Global Rating Scale (GRS). The overall ISRI score was higher in the contextualized condition as compared to the basic condition, with an average team wise difference of 2.94 (sd = 1.45). This difference is significant using a paired, two-tailed t-test (p<.001). The GRS score was higher for overall clinical performance in the contextualized scenario with an average team wise difference of 0.83 (sd = 0.83, p=.005). Conclusions. Full-size mannequin simulation based training for EMS professionals may be enhanced by contextualizing the medical scenarios. The main benefits are that the contextualized scenarios better take prehospital medical challenges into account and allow participants to perform better.


2019 ◽  
Vol 11 (4) ◽  
pp. 954 ◽  
Author(s):  
Jawad Karamat ◽  
Tong Shurong ◽  
Naveed Ahmad ◽  
Sana Afridi ◽  
Shahbaz Khan ◽  
...  

Knowledge management (KM) adoption is crucial to integrating sustainable development within the healthcare sector. Different barriers, enablers, and drivers affect KM adoption. Identifying these barriers, enablers, and drivers and their role in KM adoption is the core of successful KM adoption. However, there is scarcity of studies applying quantitative models and combing barriers, enablers and drivers to check their effect on KM adoption, especially form a developing country’s perspective such as Pakistan. Therefore, this study explores the role of barriers, enablers and drivers on KM adoption in Pakistan. Healthcare professionals participated in the data collection process, and results were analyzed using structural equation modeling. The findings described that: (1) organizational and strategic barriers have significant negative association with KM adoption; (2) government related enablers have significant positive association with KM adoption; (3) healthcare related drivers, and performance-based drivers have significant positive association with KM adoption. This study concludes that government intervention to promote KM adoption is necessary especially in developing countries. These findings will be helpful for the healthcare professionals and policy makers to promote KM adoption in healthcare sector. Current study contributes to the healthcare literature and body of knowledge by providing the empirical evidence of checking the quantitative effect of barriers, enablers and drivers on KM adoption.


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