The power of health informatics in improving patient outcomes

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Nurse checking in on a patientIn the healthcare industry, one of the major ways that success is measured is through patient outcomes. Often defined as the fulfillment of care goals – from both a provider and patient perspective – this metric is important for ensuring that existing practices and procedures are effective and identifying those which are not and should be altered accordingly.

Measuring patient outcomes results in large data sets which in turn can be used to improve these results in a number of ways. Health informatics can have a significant part in this process. By properly collecting, analyzing and leveraging these numbers, professionals can use data to improve processes, identify at-risk patients, enhance efficiency and advance research, all in the pursuit of improved patient outcomes.

Improving processes

Countless standardized processes go into ensuring the proper daily operations of a healthcare organization. There are clinical procedures, scheduling protocols, purchasing decisions, staffing choices and much more. With so many variables to consider, sometimes it can take some time and research to determine if existing processes are effective and find ways to improve them as needed.

Large amounts of data, when analyzed have the potential to improve the effectiveness of any process, from medication recommendations to post-op care. Practices can be compared, numbers crunched and data extrapolated all with the click of a button.

This is particularly important in the current age of value-based care, in which healthcare organizations are increasingly rewarded for eliminating unnecessary procedures, readmissions and other costly practices without impacting the quality of care provided to patients. Using health informatics, providers can more effectively monitor if Drug A is as effective as the more expensive Drug B, or if more hospital readmissions occur when patients are discharged after X period of time or Y period of time following surgery.

Identifying at-risk patients

To improve outcomes, identifying problems sooner rather than later is key. However, this can be difficult for a number of reasons. Sometimes diseases or injuries do not present clear symptoms until the condition is already advanced. Other times, patients may not seek medical attention in a timely manner, perhaps because of fear, scheduling conflicts or financial difficulties. Big data can help to improve this process, giving physicians a head start in addressing conditions that can be deadly when left untreated too long.

For instance, at Adventist Health Portland, a 300-bed system, teams use a disease registry to identify at-risk patients. This system is comprised of biometric information, claims data and pharmacy information, which helps providers to determine populations that could be at risk for certain conditions, as well as those whose clinical needs are not currently being met. Teams are additionally able to use the system to ensure that steps have not been skipped in the care process, flagging signs such as unfilled prescriptions.

This method has the potential to enhance outcomes for patients and healthcare organizations alike in a number of ways. A 2014 study published in Health Affairs suggested that predictive systems could help identify patients and consequently improve outcomes in six categories: high-cost patients, readmission rates, triage, decompensation, adverse events and diseases affecting multiple organ systems. These areas alone have far-reaching benefits on both health and financial levels.

Enhancing efficiency

One of the most common uses of big data in any field is to enhance efficiency in the workplace. In healthcare and beyond, often even small changes can have significant impacts on the use of resources such as staff time and organizational finances.
One way that efficiency can be improved in the healthcare setting is by reducing variation in practices and procedures. According to members of Kaufman, Hall & Associates, LLC, in an article for Leadership+, unnecessary variation in patient care plays a significant role in suboptimal outcomes, as well as unnecessary expenses. Causes of this lack of uniformity can include:

  • Underuse of care that is already proven effective.
  • Clinical processes or practices that are suboptimal.
  • Excessive use of care that is supply-sensitive.
  • Unnecessary use of higher-cost options when the lower-cost choice would be as effective.
  • Provision of procedures or services that are not clinically necessary.

By reducing variation, providers and other hospital staff are able to ensure that the most optimal procedures are being used, creating the best chance for positive outcomes while lowering costs for both the patient and organization.

Ultimately, while the priority is providing quality care, the fact that data can positively impact an organization’s bottom line should not be underestimated. In sorting through processes, professionals who work with big data can identify processes that are inefficient, as well as those that are purposefully wrong – identifying fraud and other forms of financial abuse. According to MapR ( a data company), the Centers for Medicare and Medicaid Services in the course of a single year was able to prevent more than $210.7 million in healthcare fraud using predictive analytics.

Advancing research

Though big data can be used to have an immediate impact on patient outcomes today, it also plays an important role in the healthcare of tomorrow by furthering important research being done across the country. The mass quantities of data available through health informatics give scientists more information to work with, providing clearer pictures of diseases such as cancer and diabetes, as well as determining the efficacy of drugs, imaging scans, nursing practices and other tools and procedures used in patient care.

Some researchers are even using data from wearable devices, such as Fitbits and mobile apps to gain access to larger quantities of information than ever before. One of these scientists is Dr. Spyros Kitsiou, assistant professor in the Department of Biomedical and Health Information Sciences at the University of Illinois at Chicago.

“I have over ten years of research and professional experience in health informatics (HI). My research focused on the design, development, implementation, evaluation of mobile health informatics, mobile health technologies for chronic disease management,” Kitsiou said. “Information and communication technologies, mobile health devices, wearable technologies are all becoming very, very important for supporting remote patient monitoring and home care.”

These tools give researchers intimate data, such as patient exercise habits, heart rate and blood pressure, that may otherwise be difficult to collect reliably on a daily basis if members of the study are not admitted to the hospital or at another care facility 24/7.

To study health informatics under professors like Kitsiou who have firsthand knowledge of the ways that HI is transforming patient care and outcomes, consider enrolling in the online Master of Science in Health Informatics or Post-Master’s Certificate in Health Informatics. Through these programs, you will be able to advance your informatics knowledge and skills from the time and place of your choosing thanks to the completely online platform.

Contact admissions today for more information on why UIC may be the right choice for your career.

Recommended reading:

How health informatics tools can reduce infant mortality

5 skills needed to succeed in health informatics

Careers ideal for transitioning into health informatics 


How data can save lives: Informatics for Health 2017