Data-Driven Decision Making: The Key to Future Health Care Business Success

ABSTRACT:In today’s rapidly evolving healthcare landscape, data-driven decision-making (DDDM) is revolutionizing the industry by enhancing operational efficiency, optimizing resource allocation, and improving patient outcomes. This research explores the role of DDDM in driving healthcare business success, emphasizing key independent variables such as technology infrastructure, organizational culture & leadership, and regulatory & policy framework. This study investigates the transformative impact of data-driven decision-making (DDDM) on business success in today's rapidly evolving landscape. By analyzing how organizations leverage data insights to optimize operations, enhance customer experiences, and drive innovation, this research highlights the critical role of DDDM in maintaining a competitive edge. The study employs a mixed-methods approach, combining quantitative analysis of performance metrics with qualitative insights from industry experts. Key findings reveal that DDDM not only improves accuracy and efficiency but also fosters a culture of innovation and enhances decision-making speed. However, the successful implementation of DDDM hinges on addressing challenges such as data quality, privacy concerns, and skill gaps. The study concludes by providing actionable strategies for building a data-driven culture, investing in advanced technologies, and ensuring data accessibility and privacy. Ultimately, this research underscores that DDDM is not just a strategic advantage but a necessity for businesses aiming to thrive in the data-centric future. The study utilizes the Resource-Based View (RBV), Triple Aim Framework, and Technology Acceptance Model (TAM) as theoretical underpinnings. By leveraging predictive analytics, real-time data processing, data integration, AI/ML utilization, and evidence-based decision-making, healthcare organizations can achieve financial stability, compliance with regulations, and innovation in service delivery. The findings highlight the significance of electronic health record (EHR) adoption, interoperability, cybersecurity, leadership support, ethical governance, and policy compliance in ensuring healthcare business success. This study provides actionable insights for policymakers, healthcare administrators, and technology developers in shaping data-driven healthcare environments.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-10
DOI
https://doi.org/10.5281/zenodo.14999516
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
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article

Data-Driven Decision Making: The Key to Future Health Care Business Success

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare
article

Data-Driven Decision Making: The Key to Future Health Care Business Success

article en

Abstract

ABSTRACT:In today’s rapidly evolving healthcare landscape, data-driven decision-making (DDDM) is revolutionizing the industry by enhancing operational efficiency, optimizing resource allocation, and improving patient outcomes. This research explores the role of DDDM in driving healthcare business success, emphasizing key independent variables such as technology infrastructure, organizational culture & leadership, and regulatory & policy framework. This study investigates the transformative impact of data-driven decision-making (DDDM) on business success in today's rapidly evolving landscape. By analyzing how organizations leverage data insights to optimize operations, enhance customer experiences, and drive innovation, this research highlights the critical role of DDDM in maintaining a competitive edge. The study employs a mixed-methods approach, combining quantitative analysis of performance metrics with qualitative insights from industry experts. Key findings reveal that DDDM not only improves accuracy and efficiency but also fosters a culture of innovation and enhances decision-making speed. However, the successful implementation of DDDM hinges on addressing challenges such as data quality, privacy concerns, and skill gaps. The study concludes by providing actionable strategies for building a data-driven culture, investing in advanced technologies, and ensuring data accessibility and privacy. Ultimately, this research underscores that DDDM is not just a strategic advantage but a necessity for businesses aiming to thrive in the data-centric future. The study utilizes the Resource-Based View (RBV), Triple Aim Framework, and Technology Acceptance Model (TAM) as theoretical underpinnings. By leveraging predictive analytics, real-time data processing, data integration, AI/ML utilization, and evidence-based decision-making, healthcare organizations can achieve financial stability, compliance with regulations, and innovation in service delivery. The findings highlight the significance of electronic health record (EHR) adoption, interoperability, cybersecurity, leadership support, ethical governance, and policy compliance in ensuring healthcare business success. This study provides actionable insights for policymakers, healthcare administrators, and technology developers in shaping data-driven healthcare environments.

Zenodo (CERN European Organization for Nuclear Research)
University of Sharjah (AE)
Industry, innovation and infrastructure
Openalex Percentile: Top 44%
Artificial Intelligence in Healthcare
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