The Importance of Data Analysis in Healthcare Administration – Part 1

Are you a current or aspiring healthcare administrator and also a data nerd? This multi-part article is for you, as it describes the importance of data analysis in healthcare administration positions. 

Many people may think data analysis is reserved for administrators working in a hospital setting, as they typically have access to greater amounts of raw data and higher-powered analysis and computing tools. However, the principles and techniques described here are applicable throughout the healthcare industry. The presentation may be less refined if you use more basic tools, but the insights can be similarly valuable.

Administrators throughout the industry must do their best to apply these principles to their practice setting. Effective data management can help the practice, the hospital, or the healthcare industry run more smoothly and, most importantly, help ensure patients get the best care possible.

Making Smart Decisions

Clinical providers typically get the “glory” within various healthcare settings. Clinical auxiliary staff have engaging opportunities to support those providers and connect with patients before and after exams or procedures.

Entry-level healthcare administrators may still have opportunities for some of these rewarding interactions, but as their careers advance, they are typically more removed from these scenarios and instead focus on important decisions related to business operations. 

Just like healthcare providers rely on clinical trials or other evidenced-based data sources to drive their clinical decision-making, healthcare administrators rely on data analysis to drive their administrative decision-making. The major difference is that they often must rely upon internal data sources instead of external data sources.

Understanding Patient Needs

Patient data comes in various forms, and it is up to healthcare administrators and business operations support staff to package the data effectively. This is easier said than done. However, when done properly, administrators can assess data related to chief complaints, diagnoses, and procedures to identify trends related to the service needs of their patient population. 

Examples of how this can be used to ensure the facility is proactively preparing to help their patients include ordering extra supplies due to an anticipated or actual trend in the patient population (e.g., buying more tests during the flu season) or providing training to staff (e.g., assessing outcomes related to ER transfer rates from urgent care and training team members to properly identify the scenarios which can be addressed through lower-cost approaches that do not require a hospital transfer).

Budgeting Wisely

The same data used to identify trends related to the tests or procedures that the patient population needs can tell a story to healthcare administrators about how to spend budgeted resources (i.e., money) in the most effective way possible. 

This helps drive efficiency in the system, ensuring there are enough medical supplies and staff without wasting resources. Some sources suggest that hospitals using data analysis for decision-making reduce patient care costs by up to 20%, although this can be difficult to quantify for the industry overall as there is too much variability between facilities.

Other data sources that can be assessed, if tracked, include details on waste. This may include unused/wasted medications or other supplies that expire and must be disposed of via landfill or biohazard containers. By reviewing the data prospectively and retrospectively, administrators can forecast proactively and refine their forecasting methods for future use.

Improving Hospital Services

Over the past twenty years, an emerging trend has involved the persistent drive to collect more patient satisfaction data and incorporate it into healthcare administrators’ decision-making process. 

Data analysis helps administrators identify trends in patient feedback and can help hospitals or other medical facilities identify what they are doing great with and what areas of their operation they need to fix. This seems very valuable on its face and such data has been tied to insurance reimbursement rates for federal health benefits like Medicare.

However, it is essential to note that this has remained a controversial topic. While designed to assess the quality of the patient experience, such metrics can sometimes be distorted. When patients come into healthcare settings wanting a specific treatment or medication to be recommended and a provider denies that request because it is not indicated, this can trigger patients to score the provider poorly.

This system, along with the general litigiousness of the American healthcare system, has resulted in many providers employing “defensive medicine” tactics, where they perform unnecessary tests and prescribe unnecessary treatment to ward off complaints or lawsuits about their failing to do enough. This increases overall healthcare costs and is a significant contributor to healthcare inflation, so it is a double-edged sword.

Conclusion

Data analysis offers numerous benefits to healthcare administrators. We spoke about a few of them in this article, and we will expand upon these concepts and more in Part 2 of this multi-part article. Stay tuned for more details next month!