India’s rural healthcare systems: structural modeling

2018 ◽  
Vol 31 (7) ◽  
pp. 757-774 ◽  
Author(s):  
Dinesh Kumar
Keyword(s):  
Structural Model ◽  
Healthcare Services ◽  
Healthcare Systems ◽  
Climatic Conditions ◽  
Healthcare Management ◽  
Driving Factors ◽  
Rural Healthcare ◽  
Content Type ◽  
Rural Health Center ◽  
Interpretive Structural Model

Purpose The purpose of this paper is to identify factors related to rural healthcare services and establish a hierarchical model for the effective rural healthcare management in India. Design/methodology/approach A questionnaire survey identified and correlated numerous factors related to the Uttarakhand rural healthcare systems. Experts opinion were translated into a reachability matrix and an interpretive structural model. A fuzzy matriced impacts croises-multiplication applique and classment (FMICMAC) analysis arranged the factors as hierarchical stages using their driving power. Findings The interpretive structural and FMICMAC hierarchical models suggest four key driving factors: diseases, climatic conditions, population growth and political pressure. Practical implications Despite numerous issues, rural healthcare services can be improved by considering key driving factors that could be used as a prediction tool for policy makers. Originality/value Results demonstrate that population control, coordinating services with local bodies and rural health center annual maintenance can be game changers toward better healthcare services.

Big data analytics based enablers of supply chain capabilities and firm competitiveness: a fuzzy-TISM approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nisha Bamel ◽  
Umesh Bamel
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Data Analytics ◽  
Structural Model ◽  
Big Data Analytics ◽  
Integrated Approach ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
People Skills ◽  
Interpretive Structural Model

PurposeThis paper aims to identify the big data analytics (BDAs) based enablers of supply chain capabilities (SCCs) and competitiveness of firms. This paper also models the interaction among identified enablers and thus projects the relationship strength of these enablers with SCC and a firm's competitiveness.Design/methodology/approachIn order to achieve the research objectives of this paper, we employed fuzzy total interpretive structural modeling (TISM), an integrated approach of an interpretive structural model and TISM.FindingsResults suggest that BDA-based enablers namely, IT infrastructure for BDA; leadership commitment; people skills for use of BDA and financial support for BDA significantly enable SCC and enhance firm competitiveness.Practical implicationsResults of the present study have implications for researchers and practitioners; the results will enable them to design policies around identified enablers of BDA initiatives.Originality/valueThe present paper is one of a few early efforts that address the role of BDA in augmenting SCC and subsequently a firm's competitiveness from a resource-dynamic capability perspective.

Building a learning health system using clinical registers: a non-technical introduction

2016 ◽  
Vol 30 (7) ◽  
pp. 1105-1118 ◽  
Author(s):  
John Ovretveit ◽  
Eugene Nelson ◽  
Brent James
Keyword(s):  
Health Systems ◽  
Computer Literacy ◽  
Patient Empowerment ◽  
Healthcare Services ◽  
Healthcare Systems ◽  
Digital Data ◽  
Content Type ◽  
Daily Work ◽  
Effective Use ◽  
Unpublished Research

Purpose The purpose of this paper is to describe how clinical registers were designed and used to serve multiple purposes in three health systems, in order to contribute practical experience for building learning healthcare systems. Design/methodology/approach Case description and comparison of the development and use of clinical registries, drawing on participants’ experience and published and unpublished research. Findings Clinical registers and new software systems enable fact-based decisions by patients, clinicians, and managers about better care, as well as new and more economical research. Designing systems to present the data for users’ daily work appears to be the key to effective use of the potential afforded by digital data. Research limitations/implications The case descriptions draw on the experience of the authors who were involved in the development of the registers, as well as on published and unpublished research. There is limited data about outcomes for patients or cost-effectiveness. Practical implications The cases show the significant investments which are needed to make effective use of clinical register data. There are limited skills to design and apply the digital systems to make the best use of the systems and to reduce their disadvantages. More use can be made of digital data for quality improvement, patient empowerment and support, and for research. Social implications Patients can use their data combined with other data to self-manage their chronic conditions. There are challenges in designing and using systems so that those with lower health and computer literacy and incomes also benefit from these systems, otherwise the digital revolution may increase health inequalities. Originality/value The paper shows three real examples of clinical registers which have been developed as part of their host health systems’ strategies to develop learning healthcare systems. The paper gives a simple non-technical introduction and overview for clinicians, managers, policy-advisors and improvers of what is possible and the challenges, and highlights the need to shape the design and implementation of digital infrastructures in healthcare services to serve users.

scholarly journals Interpretive structural model of trust factors in construction virtual project teams

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sukhwant Kaur Sagar ◽  
Olugbenga Timo Oladinrin ◽  
Mohammed Arif ◽  
Muhammad Qasim Rana
Keyword(s):  
Structural Model ◽  
Matrix Multiplication ◽  
Virtual Team ◽  
Project Teams ◽  
Content Type ◽  
Team Members ◽  
Virtual Project ◽  
Interpretive Structural Model ◽  
Trust Factors ◽  
Virtual Project Teams

Purpose Organisational dependence on virtual project teams (VPTs) is growing dramatically due to the substantial benefits they offer, such as efficiently achieving objectives and improving organisational performance. One of the major issues that influence the effectiveness of VPTs is trust building. This study aims to determine the key factors of trust in VPTs and design a model by identifying the interrelationships among the trust factors. Design/methodology/approach Focus group discussion was used to gather data on factors affecting trust in VPTs and their interrelationships. Interpretive structural modelling (ISM) was used to establish the relationship among the factors. Cross-impact matrix multiplication applied to classification analysis was conducted to identify the driving power and the dependence power towards effective VPTs in the construction sector. Findings The finding revealed that “characteristics of team members” (such as ability, integrity, benevolence, competence, reliability and professionalism) is the most significant factor for building trust in virtual team members. Some factors were further identified as having high driving power, while others were defined as having high dependence variables. Practical implications The findings will assist construction managers and practitioners dealing with VPTs identify the factors influencing trust among team members. Taking cognisance of the factors that influence trust will enable them to design more effective virtual team arrangements. Originality/value As the first research of its kind using ISM technique, the study offers insights into interrelationships between trust factors in the construction VPTs. It provides guides for construction managers on the effective management of trustworthy VPTs.

The sequence of strategies when establishing Taiwanese restaurant in Thailand

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Tzong-Ru Lee ◽  
Nirote Sinnarong ◽  
Yi-Hsiang Hsu ◽  
Hsiang-Ying Lan ◽  
Ching-Hua Yeh ◽  
...  
Keyword(s):  
Structural Model ◽  
Gray Relational Analysis ◽  
Content Type ◽  
Analytic Process ◽  
Perception Of Quality ◽  
Set Up ◽  
Construction Operation ◽  
Interpretive Structural Model ◽  
Restaurant Owners ◽  
Three Phases

Purpose The purpose of this paper is to investigate the problem faced by many Taiwanese restaurant owners who trying to set up their shops in Thailand. Design/methodology/approach Two surveys were conducted in this study. The first interview questionnaire was designed using the factors proposed by Parasuraman et al. (1988, 1991) and given to restaurant owners/managers who successfully set up shops in Thailand. The second questionnaire was constructed specifically for Thai consumers. Findings Gray relational analysis (GRA), theory of inventive problem-solving (teoriya resheniya izobreatatelskikh zadatch, TRIZ) and interpretive structural model (ISM) were used to identify potential difficulties and to determine the key factors impacting the shop establishment and development in Thailand. The results provide a set of strategic sequence when launching restaurant in Thailand. Originality/value A result of GRA determined 14 important factors that influence customer perception of quality service. A TRIZ analytic process provided 17 strategies when setting up overseas shop and the ISM class diagram shown the three phases needed to be considered before restaurant owners can set up shops abroad. The three phases are construction, operation and competition phases. These set of strategies sequence when launching a restaurant in Thailand.

Modeling the Big Data challenges in context of smart cities – an integrated fuzzy ISM-DEMATEL approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohd Imran Khan ◽  
Shahbaz Khan ◽  
Urfi Khan ◽  
Abid Haleem
Keyword(s):  
Big Data ◽  
Structural Model ◽  
Smart Cities ◽  
Integrated Approach ◽  
Fuzzy Decision Making ◽  
Fuzzy Dematel ◽  
Content Type ◽  
Use Of Resources ◽  
Implementation Level ◽  
Interpretive Structural Model

PurposeBig Data can be utilised for efficient use of resources and to provide better services to the resident in order to enhance the delivery of urban services and create sustainable build environment. However, the adoption of Big Data faces many challenges at the implementation level. Therefore, the purpose of this paper is to identify the challenges towards the efficient application of Big Data in smart cities development and analyse the inter-relationships.Design/methodology/approachThe 14 Big Data challenges are identified through the literature review and validated with the expert’s feedback. After that the inter-relationships among the identified challenges are developed using an integrated approach of fuzzy Interpretive Structural Modelling (fuzzy-ISM) and fuzzy Decision-Making Trial and Evaluation Laboratory (fuzzy-DEMATEL).FindingsEvaluation of interrelationships among the challenges suggests that diverse population in smart cities and lack of infrastructure are the significant challenges that impede the integration of Big Data in the development of smart cities.Research limitations/implicationsThis study will enable practitioners, policy planners involved in smart city projects in tackling the challenges in an optimised manner for the hindrance free and accelerated development of smart cities.Originality/valueThis research is an initial effort to develop an interpretive structural model of Big Data challenges for smart cities development which gives a clearer picture of how the identified challenges interact with each other.

Healthcare under pressure: modelling COVID-19 fatalities with multiscale geographically weighted regressions

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zizi Goschin ◽  
Gina Cristina Dimian
Keyword(s):  
Local Level ◽  
Age Distribution ◽  
Case Fatality ◽  
Healthcare Services ◽  
Healthcare Systems ◽  
Content Type ◽  
Case Fatality Ratio ◽  
Factors Of Influence ◽  
The Impact ◽  
Local Healthcare

PurposeThe paper aims to disentangle the factors behind territorial disparities in the coronavirus disease 2019 (COVID-19) case fatality ratio, focusing on the pressure put by the pandemic on healthcare services and adopting a spatial perspective.Design/methodology/approachMultiscale geographically weighted regression (MGWR) models have been used for uncovering the spatial variability in the impact of healthcare services on COVID-19 case fatality ratio, allowing authors to better capture the real spatial patterns at local level. The authors proved that this approach yields better results, and the MGWR model outperforms traditional regression methods. The selected case studies are two of the biggest UE countries, among the first affected by a high incidence of COVID-19 cases, namely Italy and Germany.FindingsThe authors found sizeable regional differences in COVID-19 mortality rates within each of the analysed countries, and the stress borne by local healthcare systems seems to be the most powerful factor in explaining them. In line with other studies, the authors found additional factors of influence, such as age distribution, gender ratio, population density and regional development.Originality/valueThis research clearly indicated that COVID-19 related deaths are strongly associated with the degree of resilience of the local healthcare systems. The authors supply localized results on the factors of influence, useful for assisting the decision-makers in prioritizing limited healthcare resources. The authors provide a scientific argument in favour of the decentralization of the pandemic management towards local authorities not neglecting, however, the necessary regional or national coordination.

Managing the essential medicines stock at rural healthcare systems in India

2018 ◽  
Vol 31 (8) ◽  
pp. 950-965 ◽  
Author(s):  
Dinesh Kumar ◽  
D. Kumar
Keyword(s):  
Supply Chain ◽  
Lead Time ◽  
Stock Assessment ◽  
Healthcare Systems ◽  
Essential Medicines ◽  
Rural Healthcare ◽  
Content Type ◽  
One Year ◽  
Medicine Supply ◽  
Practical Implications

Purpose The purpose of this paper is to eliminate the medicine stock-out problem by building an optimum medicine stock in rural healthcare centers in India. Design/methodology/approach Data associated with inflow and outflow of a specific medicine (folic acid tablets) arer collected from all consecutive supply chain stages during the survey. While conducting the survey, it is found that several medicines are out of stock owing to uncertain lead time and demand. Integrating with quantity discount and min–max (s, S) inventory policy, two models are developed using system dynamics: one is Model 1 with constant lead time and uncertain demand, and the other is Model 2 with both uncertain lead time and demand. Findings Both models are simulated for a period of one year on Stella 9.1 platform. The results are compared with actual data, and the comparison shows significant improvement of the medicine stock at all downstream stages, while maintaining a certain safety stock. Further, Model 2 suggests a larger stock than Model 1 at each point of time. Practical implications Despite numerous issues, the stocks of medicine in rural healthcare systems can be improved as suggested by the models. The models depict the behavior of inventory stock at each stage of the supply chain and act as a function of time that could be used in the form of a prediction tool for the policymakers. Originality/value This paper is one of the first papers that had developed the model of the medicine supply chain in rural parts of a developing country. It provides a generic framework for the stock assessment and improvement throughout the supply chain.

Modeling drivers for successful adoption of environmentally conscious manufacturing

2014 ◽  
Vol 9 (2) ◽  
pp. 127-140 ◽  
Author(s):  
Varinder Kumar Mittal ◽  
Kuldip Singh Sangwan
Keyword(s):  
Structural Model ◽  
Review Of Literature ◽  
Interpretive Structural Modeling ◽  
Environmentally Conscious ◽  
Policy Makers ◽  
Content Type ◽  
Environmentally Conscious Manufacturing ◽  
The Government ◽  
Dependence Relationship ◽  
Interpretive Structural Model

Purpose – This paper aims at developing an interpretive structural model of drivers for environmentally conscious manufacturing (ECM). It will demonstrate how interpretive structural modeling (ISM) supports policy makers in the government and industry in identifying and understanding interdependencies among drivers for ECM. Interdependencies among drivers will be derived and structured into a hierarchy to derive subsystems of interdependent elements with corresponding driving power and dependency. Design/methodology/approach – ISM has been used to identify hierarchy and inter-relationships among drivers for ECM adoption and to classify the drivers according to their driving and dependence power using MICMAC analysis. The drivers for ECM adoption are identified through the review of literature followed by developing a model of drivers using ISM. Findings – The main findings of the paper include the development of an ISM model of drivers for ECM adoption. The developed model divided the identified drivers into five levels of hierarchies showing their inter-relationship and depicting the driving-dependence relationship. These five levels have been classified into four categories – awareness, external, organizational and benefits. Originality/value – The developed ISM model is expected to provide a direction to the policy makers in the government and industry and the top management of the organizations to leverage their resources in a timely manner to adopt ECM successfully.

Benchmarking model for management education in India

2017 ◽  
Vol 24 (3) ◽  
pp. 666-693 ◽  
Author(s):  
Swati Yeravdekar ◽  
Abhishek Behl
Keyword(s):  
Higher Education ◽  
Public Sector ◽  
Literature Review ◽  
Private Sector ◽  
Structural Model ◽  
Management Education ◽  
Public And Private ◽  
Content Type ◽  
Education In India ◽  
Interpretive Structural Model

Purpose Management education has assumed phenomenal prominence in India in recent years, with branding being a prime factor used as a yardstick, rather a benchmark or point of reference, for one institution having an edge over the other. The purpose of this paper is to explore the factors leading to branding of management education in India. It proposes two frameworks using Total Interpretive Structural Model (TISM) for public and private sector management colleges. For this purpose, variables are extracted using systematic literature review, which play a crucial role in changing the dynamics of college rankings. The inquiry distinctly examines the nature of relationship between them for public and private colleges offering higher education. The study further proposes strategies for improvement of rankings by discussing the hierarchy and interrelationship among the enablers. Design/methodology/approach The study uses Interpretive Structural Model (ISM) to ascertain the linkages between the variables, and employs TISM to validate the reasons of association. The model was fabricated by consulting the experts from various spheres closely allied to branding and higher education, including the private agencies and decision makers in the selected colleges. The variables were furthermore structured for classification using Matrice d’Impacts Croises-Multiplication Appliqué an Classment Analysis. Findings It was observed that the variables behave differently when studied from the perspective of private sector colleges and public sector colleges; the former have seven levels of arrangement while it is only four for the latter. Quality of Faculty and Research were the key areas of concern for private sector colleges while infrastructure featured as a focal point for those in public sector. It was also evident that the placement of variables and their flow were different. Rankings should thus be premeditated differently for both the sectors and different weights should be assigned to rank the colleges. Research limitations/implications The study is confined to branding of management education institutes in India, without considering other important disciplines for generalizing the framework. It is based on literature review followed by ISM, while other approaches such as ethnographic research methods and appreciative inquiry could have been possible alternatives as well. Practical implications The paper helps in developing different frameworks for private and public sector institutes, which would assist them to have a homogenous completion within their respective sectors. The study can be used to measure the performance of colleges on various parameters and gives them linking variables to enhance their productivity. Originality/value The paper discusses the need for developing a different barometer to measure the performance of private sector and public sector colleges offering higher education.

Refining case management for dementia using insights from operations management

2014 ◽  
Vol 15 (3) ◽  
pp. 162-170 ◽  
Author(s):  
Bert Meijboom ◽  
Laurens Van den Bosch ◽  
René Schalk
Keyword(s):  
Case Management ◽  
Operations Management ◽  
Cost Containment ◽  
Customer Orientation ◽  
Disease Process ◽  
Healthcare Services ◽  
Healthcare Management ◽  
Dementia Care ◽  
Content Type ◽  
New Model

Purpose – Providers of healthcare services face increasing performance demands in terms of cost-efficiency as well as client centeredness. Dementia care is an illustrative example in this respect. Due to the aging society, the number of dementia clients is expected to grow significantly, which implies increasing costs. At the same time, demands in terms of coherent and high-quality care for dementia clients are increasing, putting a stronger emphasis on demand driven, responsive care and service processes. Literature shows that case management in dementia care is beneficial for persons with dementia and caregivers, but costly. Using insights from operations management (OM), the purpose of this paper is to develop a new model for case management in dementia care. Design/methodology/approach – To address both cost containment and customer orientation, insights from OM, in particular front/back office (FO/BO) configuration and modularity theory, are used to develop an innovative conceptual model for case management in dementia care. Findings – This framework offers a new way of conceptualizing care provision throughout the different phases of a chronic disease process. Linking FO/BO configurations and modular organizing with case management makes it possible to create a cost-effective and client-centered system of healthcare management. Originality/value – A new model is developed to address both cost containment and customer orientation based on insights from OM, in particular FO/BO configuration and modularity theory.

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