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Data analytics platforms: The key to quality of care improvements

By Lisa Carter, Writer at Arcadia
Unlocking Big Data Healthcare Analytics Quality Improvement

Data is critical for revolutionizing patient care, enhancing operational efficiency, and identifying cost-saving opportunities. The series Unlocking Big Data, presented by HIMSS and moderated by Dr. Indu Subaiya, explores the importance of delivering trusted data to healthcare decision-makers.

This article covers insights from Episode 1 of the series, which features industry leaders Michael Meucci, CEO of Arcadia, and Albert Marinez, Chief Analytics Officer at Cleveland Clinic. They provide a clearer picture of the tangible benefits that data analytics platforms can bring to healthcare organizations, especially for quality of care.

From challenges to opportunities: A call to action for quality of care improvements

A December 2023 study by HIMSS Market Insights surveyed more than 100 healthcare leaders, and the results unveiled this statistic: 56% of healthcare leaders prioritized quality of care as the foremost goal enabled by data analytics. This insight shows a universal aspiration within the healthcare industry: to improve patient outcomes through data-driven strategies.

Despite this shared goal, improving patient outcomes with data can have many obstacles. These include conflicts over strategy, hurdles integrating technology, scarce resources, and financial constraints. These challenges show how hard it can be to leverage data analytics in healthcare. This is especially true when compared against the backdrop of diverse organizational scales and infrastructures.

For example, healthcare leaders at larger organizations were more likely to face change management resistance when implementing a data analytics platform compared to smaller organizations that cited insufficient IT infrastructure as their biggest barrier. The journey toward an integrated data analytics platform is not without its challenges.


Many of the barriers listed [in the report] are real. So how do we reconcile that?

Albert Marinez
Chief Analytics Officer at Cleveland Clinic

4 strategies to improve quality of care with a data analytics platform

1. Align analytics initiatives with organizational priorities

When it comes to implementing a data analytics platform to improve quality of care, it is necessary for analytics initiatives to be in harmony with organizational priorities. By aligning analytics tools with strategic priorities, healthcare organizations can ensure that these powerful capabilities directly contribute to their core objectives.

For example, Cleveland Clinic has leveraged data to enhance patient access and operational efficiency. They have applied machine learning for scheduling optimization, illustrating the tangible benefits of data-driven strategies.

Even small improvements can create meaningful change within healthcare organizations, especially when it comes to data analytics platforms. These platforms, combined with new technology, are ushering in a new era of healthcare.

2. Embrace AI and data analytics

AI and data analytics herald a new era of possibilities in healthcare. Generative AI and large language models (LLMs) represent a seismic shift, democratizing access to analytical insights and transforming the speed and efficiency of decision-making processes. This evolution departs from conventional analytics methodologies, facilitating a more intuitive and personalized approach to healthcare management and patient care.

Headshot of Michael Meucci

We now live in this world where LLM and Generative AI allow business users to have conversations with robots that can get you much closer to the answer much faster, and it has a multiplying effect on the value of the platform.

Michael Meucci
President and Chief Executive Officer at Arcadia

AI, combined with the power of data analytics platforms, has not only democratized access to information but also enabled healthcare leaders to tackle broader societal challenges, such as improving health outcomes and expanding access to care.

3. Rethink health longevity versus health quality

Even though technology continues to grow and impact the healthcare industry, have we made society better? People in Western civilization live longer. However, the same number live in poor to moderate health today.

This calls for a critical examination of our achievements in healthcare, urging a refocus on not only extending life but enhancing the quality of life through better health outcomes. We must challenge the healthcare community to leverage analytics in pursuit of "happier, healthier days on the planet," prioritizing quality of health over mere longevity.

Healthcare leaders should then point their analytics teams at those questions and democratize access to information.

4. Democratize the data

The democratization of data in healthcare is not only about making data available through an analytics platform. It's about ensuring that healthcare professionals, regardless of their technical expertise, can leverage data analytics to enhance patient care, improve operational efficiencies, and drive strategic decision-making.

Here are three ways that democratized data can prepare the workforce for a data-driven era and leverage a data analytics platform for optimal results:

  1. Gain strategic alignment and governance. The necessity of balancing innovation with oversight requires consistent platforms with consistent rules of engagement. These guardrails are essential to ensure that the democratization of data does not lead to fragmented approaches to data analytics but instead supports a unified strategy that aligns with the organization's goals and patient care objectives.
  2. Upskill healthcare workers. Asking the right questions and interpreting answers from AI is a crucial skill for healthcare professionals. This requires the need for educational and training programs to upskill the workforce, ensuring healthcare professionals can leverage new tools effectively.
  3. Ensure high-quality data and analytics. A data strategy must prioritize accuracy, reliability, and ethical considerations. This focus on quality is crucial to building trust in AI-driven insights and ensuring that these tools enhance decision-making and patient outcomes.

The future of healthcare analytics

The evolution of data analytics platforms and AI in healthcare is not only a technological revolution but a catalyst for a broader transformation of the healthcare industry. Navigating this transition demands the following:

  • Strategic foresight
  • Collaborative innovation
  • Commitment to aligning technological advancements with the fundamental mission of healthcare: Deliver superior patient care and improve health outcomes for communities worldwide.

Through this lens, the journey of unlocking big data becomes not only a technical endeavor but a moral imperative to harness the power of data for better quality of care.