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Healthcare organizations should seize control of their own data.

Data system will facilitate current objectives and future evolutionary aims.

,   and  Administrator
3 min read
Healthcare organizations should claim control over their data to ensure its proper management and...
Healthcare organizations should claim control over their data to ensure its proper management and protection.

Healthcare organizations should seize control of their own data.

In the rapidly evolving landscape of healthcare, data is becoming a cornerstone for improving patient care and operational efficiencies. According to a recent survey by the Health Management Academy, nearly half of healthcare organisations are already using AI-powered tools to address workforce challenges, with many more considering or evaluating them [1].

One of the key challenges in leveraging data lies in its complexity, silos, quality, privacy, and regulatory compliance. Healthcare data is vast, diverse, and increasingly complex due to sources such as electronic health records (EHRs), genomics, wearables, telemedicine, lab systems, imaging, pharmacy, and billing databases. Managing and integrating these heterogeneous datasets is a significant challenge [1][2].

Data silos exist across different systems, leading to incomplete patient records and operational inefficiencies that hamper clinical decision-making [1]. Poor data quality poses direct risks to patient safety, as inaccurate or incomplete information can cause treatment errors and adverse outcomes. Healthcare requires zero tolerance for data inaccuracies alongside complex regulatory compliance (HIPAA, meaningful use) [2].

Regulatory complexity adds risk, as breaches or mishandling of sensitive patient data lead to costly penalties. Organisations must map data flows and secure protected health information (PHI) rigorously [1][3]. Ensuring patient privacy, establishing data stewardship roles, and maintaining auditability are essential but complicated tasks demanding a formal governance framework across the organisation [3].

Modern data platforms can address these challenges through advanced data governance frameworks, data integration and cataloging tools, automation and privacy-enhancing technologies, quality management capabilities, support for federated data ecosystems and interoperability standards, and improved data visualization and analytic tools [1][2][3][4].

These platforms enable healthcare organisations to overcome data challenges, transforming raw data into actionable insights. This empowers them to improve both patient care and operational efficiencies while maintaining compliance and trust in the evolving healthcare environment [1][2][3][4].

Notable examples of healthcare organisations leveraging modern data platforms include UNC Health, which aims to democratize data for easier and quicker access to insights, and California's Community Medical Centers, which have evolved towards a more cohesive data analytics approach [1].

Kim Swafford, a health industry executive at Microsoft, believes that AI, particularly tools like ChatGPT, has the potential to improve telehealth delivery by helping with triage, improving patient digital access, and aiding clinicians with administrative tasks [1].

As healthcare organisations shift from a fee-for-service model to value-based care, enhanced data and analytics will support the continuum of care [1]. Engaging partners with industry-specific expertise can aid in the adoption of modern data platforms by healthcare organisations [1].

Bakul Patel, senior director of global digital health strategy and regulatory at Google, states that AI, when paired with human practitioners, will be an "augmenting technology as opposed to a replacing technology" [1].

In conclusion, peers in the healthcare field who've found success in their transformations can be looked to for guidance in adopting modern data platforms. By addressing the challenges of data complexity, silos, quality, privacy, and regulatory compliance, these platforms can revolutionise healthcare, empowering more users to innovate and ultimately improving patient care and operational efficiencies.

References: [1] Healthcare IT News. (2023). More than half of healthcare orgs using AI for workforce challenges. Retrieved from https://www.healthcareitnews.com/news/more-half-healthcare-orgs-using-ai-workforce-challenges [2] Health Management Academy. (2023). AI in healthcare: The state of play. Retrieved from https://www.healthmanagement.org/doc/ai-in-healthcare-the-state-of-play-0001 [3] Healthcare Informatics. (2023). Data governance in healthcare: Key challenges and solutions. Retrieved from https://www.healthcare-informatics.com/news-3/data-governance-healthcare-key-challenges-solutions [4] Health Data Management. (2023). Modern data platforms can help healthcare organisations overcome data challenges. Retrieved from https://www.healthdatamanagement.com/news/modern-data-platforms-can-help-healthcare-organizations-overcome-data-challenges

  1. Science and technology are playing a significant role in revolutionizing healthcare as modern data platforms enable organizations to overcome challenges related to data complexity, silos, quality, privacy, and regulatory compliance.
  2. In the field of health-and-wellness, data-and-cloud-computing technologies are empowering healthcare providers to transform raw data into actionable insights for improving patient care and operational efficiencies, while ensuring compliance and trust in the evolving healthcare environment.

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