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R P Sundarraj
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R P Sundarraj
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R P Sundarraj
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Sundarraj, Rangaraja
Sundarraj, R. P.
Sundarraj, Rangaraja P.
P Sundarraj, Rangaraja
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7 results
Now showing 1 - 7 of 7
- PublicationOn integrating an IS success model and multicriteria preference analysis into a system for cloud-computing investment decisions(01-01-2015)
; Venkatraman, SathyanarayananInvesting in cloud computing technology is one of the latest trends in IT. This is a multi criteria investment decision involving many stakeholders and a sequence of coordinated assessment activities that are strategic, qualitative (technical) and quantitative (financial) in nature. This paper integrates an information system (IS) success model with preference elicitation techniques drawn from the multi-criteria decision-making literature. We also show how this decision model can be extended as a vendor negotiation tool. Finally, we describe a prototype Decision Support System (DSS) featuring this model. - PublicationHealthcare analytics adoption-decision model: A case study(01-01-2015)
;Venkatraman, Sathyanarayanan; Seethamraju, RaviHealthcare organizations (HCO) are under pressure to adopt emerging solutions with a view to improving the quality and efficiency of their operations, patient care and clinical decisions. In the literature, while recommendations have been put forth to follow an organizational approach to the adoption and implementation of analytics, there is a paucity of research into what specifically constitutes healthcare-analytics (HA), as well the antecedents that can explain and predict its adoption-decisions. In this paper, we fill this gap, by first proposing a typology for HA and an adoption-decision model that integrates the TOE framework with DeLone and McLean IS Success Model. We use a case study for the initial validation of the typology and the model. Our study reveals that the HCO studied has the same types of the data proposed in our typology, although the usage of the data and current/future adoption of analytics depends on many factors beyond simply technology. - PublicationAssessing organizational health-analytics readiness: artifacts based on elaborated action design method(27-01-2023)
;Venkatraman, SathyanarayananPurpose: While the adoption of health-analytics (HA) is expanding, not every healthcare organization understands the factors impacting its readiness for HA. An assessment of HA-readiness helps guide organizational strategy and the realization of business value. Past research on HA has not included a comprehensive set of readiness-factors and assessment methods. This study’s objective is to design artifacts to assess the HA-readiness of hospitals. Design/methodology/approach: The information-systems (IS) theory and methodology entail the iterative Elaborated Action Design Research (EADR)method, combined with cross-sectional field studies involving 14 healthcare organizations and 27 participants. The researchers determine factors and leverage multi-criteria decision-making techniques to assess HA-readiness. Findings: The artifacts emerging from this research include: (1) a map of readiness factors, (2) multi-criteria decision-making techniques that assess the readiness levels on the factors, the varying levels of factor-importance and the inter-factor relationships and (3) an instantiated system. The in-situ evaluation shows how these artifacts can provide insights and strategic direction to an organization through collective knowledge from stakeholders. Originality/value: This study finds new factors influencing HA-readiness, validates the well-known and details their industry-specific nuances. The methods used in this research yield a well-rounded HA readiness-assessment (HARA) approach and offer practical insights to hospitals. - PublicationHealth-Analytics Readiness Assessment: Elaborated Action Design Research and Nascent Theoretical Implications(01-01-2022)
;Venkatraman, SathyanarayananHealth analytics (HA) technology enables and enhances fact-based decision-making capabilities of hospitals in the clinical, operational, and administrative domains. It is, however, the case that HA success presupposes a hospital's readiness to adopt, absorb, and put the technology to effective use. Currently, there is a paucity of research that focuses on how hospital executives can assess their organization's readiness for HA. The principal objective of our study is to fill this gap. We design HA readiness-assessment artifacts guided by cross-sectional case studies to inform the design and the elaborated action design research approach that extends past artifacts through iterative collaboration with practitioners and industry experts. This article details the design process and artifacts and highlights implications for nascent theory and generalizable knowledge. - PublicationExploring health-analytics adoption in indian private healthcare organizations: An institutional-theoretic perspective(01-09-2022)
;Venkatraman, Sathyanarayanan; Seethamraju, RaviIn India, private hospitals are at the cusp of adopting health-analytics (HA) technology to manage their organizational performance through data-driven decision-making. Past studies have analyzed the applications and benefits of HA. Our study builds on this descriptive base to investigate the patterns of HA adoption and the institutional factors which impact adoption. We conducted a cross-sectional field study that involved ten Indian private healthcare organizations and four health-ecosystem partners and analyzed the case study data using an institutional theory lens. Our cases reveal that the breadth and depth of HA adoption varies and falls into three distinct patterns: far-sighted, conservative, and niche. We assess how these patterns are influenced by the two key dimensions of institutional environments (material-resource environment and institutional environment). We highlight distinctive factors (management support for building organizational trust on data-driven decisions and IT-Medical practitioner collaboration) that exert important contextual influences on HA adoption. Our study identifies areas of commonalty for HA adoption across national healthcare settings as well as contextual aspects representative of the burgeoning Indian healthcare field. - PublicationPrototype design of a healthcare-analytics pre-adoption readiness assessment (HAPRA) instrument(01-01-2016)
;Venkatraman, Sathyanarayanan; Mukherjee, AnikHealthcare organizations (HCO) adopt emerging technology solutions such as Healthcare Analytics (HA) to improve the quality and efficiency of their operations, patient care, and clinical decisions. While their intent is to adopt HA, many of them are unsure of their organizational readiness for that adoption. There is a paucity of research on HA pre-adoption readiness assessment techniques and tools, which can be leveraged by hospitals, to make well-informed decisions. In this paper, we fill this gap, by proposing a prototype design of an instrument based on the design science approach. We base the constructs used in our artifact on our findings from the multi-case study analysis of three hospitals, which we also discuss briefly. The key contribution of this research is the process that we followed in integrating the case study approach with DSRM in the area of HA adoption. - PublicationAssessing strategic readiness for healthcare analytics: System and design theory implications(01-01-2018)
;Venkatraman, Sathyanarayanan; Seethamraju, RaviThe adoption of analytics solutions in hospitals is a recent trend aimed at fact-based decision making and data-driven performance management. However, the adoption of analytics involves diverse stakeholder perspectives. Currently, there is a paucity of studies that focus on how the practitioners assess their organizational readiness for health analytics (HA) and make informed decisions on technology adoption given a set of alternatives. We fill this gap with our study by designing a strategic assessment framework guided by a DSRM approach that iteratively extends our past artifact. Our approach first entails the use of many in-depth case-studies, as well as embedded experts from the industry to inform the objective setting and design process. These inputs are then supported by two multi-criteria decision-making methods. We also evaluate our framework with healthcare practitioners for both design validity and future iterations of this project. Implications of our work for theory of design and action are also highlighted.