Data Analytics in Healthcare Administration
“The integration of data analytics into the domain of healthcare administration has sparked a profound transformation, positioning administrators at the forefront of evidence-based decision-making.”
Christina Gardiner, PhD, Professor in the Department of Global Health Management and Administration, University of Maryland Global Campus, School of Business
In 2018, approximately 30 percent of the world’s data volume was being generated by the healthcare industry. Electronic health records, remote patient monitoring, wearable gadgets, and other advancements have almost certainly edged up the share even further. But data is only as valuable as the insights and patterns which can be drawn from it. Data analytics is the art and science of leveraging those insights and patterns in decision-making processes.
Healthcare administrators have a unique position when it comes to data analytics, sitting at the intersection of business and healthcare. It’s a position that’s only growing in importance, too: the stream of health data isn’t slowing down, and the power of machine learning algorithms is accelerating in tandem. Healthcare administrators are tasked with directing this mass of potential toward the benefit of patients, providers, and healthcare organizations, and that goal comes with its unique challenges.
Read on to learn more about how data analytics is used in healthcare administration.
Meet the Expert: Christina Gardiner, PhD, LNHA, CSSBB
Dr. Christina Gardiner is a highly respected collegiate faculty and professor in the Department of Global Health Management and Administration at the University of Maryland Global Campus, School of Business. Renowned for her expertise in healthcare data analytics, she brings extensive executive healthcare experience spanning two decades.
As the president of Summit Healthcare Advisors, Dr. Gardiner specializes in leveraging data analytics to drive informed decision-making and improve healthcare outcomes. Her research and consulting work focus on enhancing healthcare quality, safety, and cost-efficiency through meaningful insights from healthcare information technology programming.
Dr. Gardiner actively supports public health initiatives, collaborating with nonprofit organizations and post-secondary institutions to empower evidence-based decision-making through data analysis. Her exceptional expertise in healthcare data analytics positions her as a key influencer for positive change in improving healthcare systems and outcomes.
The Power of Data Analytics in Healthcare Administration
“The integration of data analytics into the domain of healthcare administration has sparked a profound transformation, positioning administrators at the forefront of evidence-based decision-making,” Dr. Gardiner says. “As technology advances and data becomes more accessible, the healthcare administration profession is experiencing a remarkable shift towards a data-driven paradigm.”
In this data-driven paradigm, predictive analytics can help locate patterns that directly translate to improved patient outcomes and provider benefits. One such example is hospital readmission rates: the percentage of patients who return to a hospital within a short period of time after discharge. Readmission represents a failure of healthcare service and a high economic cost.
But mining health data can help recognize readmission patterns, allowing administrators to direct resources and policies that reduce them—and help implement tailored strategies for higher-risk patients.
“Healthcare administrators utilize machine learning algorithms to analyze vast amounts of patient data, enabling them to identify patterns and trends,” Dr. Gardiner says. “This data-driven approach can allow administrators to optimize healthcare delivery, improve resource allocation, and drive better patient care throughout the organization.”
Challenges for Data Analytics in Healthcare Administration
High-powered data analytics and machine learning models can go as far as mapping disease progression and aiding in developing personalized treatment plans based on individual characteristics. This type of efficiency is good for patients, providers, supply chains, and a healthcare organization’s bottom line. But there are caveats. Ensuring data quality and reliability is critical. Inaccurate and incomplete data can be as bad as incorrect data and lead to flawed conclusions.
“Depending on the situation, the data may not capture the full complexity of healthcare situations, including patient experiences and unique circumstances,” Dr. Gardiner says. “Administrators must balance quantitative insights with qualitative aspects, which may not be easily quantified.”
Basing decisions on objective data reduces personal bias, but it does not eliminate bias altogether. In fact, algorithms and data sets can, themselves, be unconsciously biased. It’s paramount for healthcare administrators to keep in mind that despite the proliferation of tech and data, healthcare is still a human field, with human factors and human stakes. Healthcare administrators need to apply collaboration and critical thinking to the data-driven mindset.
“Healthcare leaders should actively involve multidisciplinary teams, consider the populations that they serve, and seek input from a wide array of stakeholders,” Dr. Gardiner says. “The synergy between data-driven analytics and the expertise of healthcare professionals empowers organizations to make informed and well-rounded decisions.”
Tools and Frameworks for Data Analytics in Healthcare Administration
In some business circles, talk about data analytics can drift into generalities and buzzwords. But data analytics is very much a science, one undergirded by statistical concepts like hypothesis testing, regression analysis, and data modeling. Healthcare administrators will benefit from a solid statistics foundation and familiarity with a complex suite of data analytics tools.
“Aspiring healthcare administrators should familiarize themselves with data analytic tools like Tableau and Power BI,” Dr. Gardiner says. “These platforms not only offer powerful data visualization capabilities but also include features such as machine learning algorithms and reporting functionalities that enable in-depth data analysis and insights.”
Frameworks such as the Healthcare Analytics Adoption Model (HAAM) and Analytics Maturity Model for Healthcare (AMMH) provide structured roadmaps for implementing and advancing data analytics in healthcare.
But healthcare administrators should also regularly communicate with the teams and individuals who manage data directly, learning the nuances and limitations of data, and building fluency and literacy around data analytics throughout an organization.
They can also contact data-focused professional associations like the Healthcare Information and Management Systems Society (HIMSS) and the American Health Information Management Association (AHIMA) for valuable insights and guidelines.
The Future of Data Analytics in Healthcare Administration
Healthcare is always in a state of flux, but the past few years have been particularly change-filled. Dr. Gardiner points to the ripple effects of the pandemic—a swift industry-wide digitalization, the proliferation of telemedicine, and major advances in remote patient monitoring—as areas of continued growth. Tomorrow’s healthcare administrators will encounter the opportunities and challenges that rapid evolution brings, and Dr. Gardiner is helping students at UMGC prepare for that complex future.
“The landscapes of healthcare and healthcare administration stand on the brink of revolutionary change, and the next five to ten years will likely witness profound transformations,” Dr. Gardiner says. “It is expected that a fusion of advanced technologies such as artificial intelligence (AI), machine learning (ML), the Internet of Things (IoT), and robotics will redefine the very fabric of healthcare administration.”
Data-based decision-making will continue to play a pivotal role, bringing together the technological advancements in electronic health records, personalized medicine, wearable technology, and genomics.
But as the future becomes more algorithmic and tech-based, it’s more important than ever for healthcare to maintain a patient-centric orientation. Healthcare administrators can play a large part in positioning the industry for the future.
“In this era of dynamic change, healthcare administrators are not merely spectators, but active contributors, leading the charge to shape a resilient, responsive, and patient-centric healthcare environment that benefits us all,” Dr. Gardiner says.