Over the last decade or so, electronic health records (EHR) have been helping to streamline medical record-keeping and coordinate patient care. EHR has been instrumental in allowing hospitals to reduce errors, leverage big data for patients’ benefit, and provide a more comprehensive picture of a patient’s health.
There are so many benefits to collecting digital health data in the Information age, from patient care to research to improving efficiency within healthcare organizations, but that doesn’t mean managing this data is always easy.
Healthcare data management can run into several problems. Anyone who works with this type of data needs to be aware of the potential pitfalls so they can be reduced as much as possible. Here are the three biggest challenges facing health data management—and what can be done to overcome them.
In a perfect world, each patient would have one master health file. It would contain information from all of their prior visits with a healthcare professional and would give each provider a comprehensive view of that patient’s health history.
Unfortunately, fragmented data is a persistent problem in healthcare. Data is generated from many different sources and is stored in many different forms, such as spreadsheets with structured data and information from imaging equipment (such as MRI) which is stored in specialized formats.
Not only is this data fragmented, but it can be stored in multiple placed and copied, bloating an organization’s data storage systems. Wading through all this fragmented data isn’t easy for busy health professionals and it can cause data to be overlooked or measured more than once.
Our world is changing rapidly and healthcare data can’t always keep up. With EHR helping to aid in medical research, it’s no surprise that new treatments come on the market all the time. While that’s great for patients, it’s a problem for keeping updated health records.
Additionally, patients’ lives change over time, and those changes aren’t always reflected in their records. When a patient changes their name, healthcare professionals might not realize that the patient has existing records, essentially eliminating access to key medical information until the change is recorded.
Finally, health data faces immense regulatory challenges, due to its sensitive nature. Medical data is among the most personal information there is, and patients are understandably concerned about privacy. Privacy concerns surrounding health data are the reason we have strong regulations on patient data management.
HIPAA (the Health Insurance Portability and Accountability Act) is a law that all healthcare organizations must abide by in handling and managing sensitive data. Regulations on security, data storage, and sharing all fall under HIPAA. HIPAA violations are costly for organizations and can erode public trust. However, these regulations can make it difficult for researchers to get access to information that could potentially save lives.
Health Data Management Tools to Help Overcome Obstacles
These challenges are well-known, and fortunately, there are startups and new tools emerging to help organizations use their data more effectively. These healthcare data tools can help healthcare providers maintain ethics and patient privacy while supporting faster response times and medical treatments, streamlining operations and keeping data organized.
Some of the most promising solutions for health data management use analytics and artificial intelligence. Predictive analytics are helping healthcare organizations anticipate community health trends and adjust staffing and supplies based on anticipated local need. In many cases, no personally identifiable information is needed to provide powerful insights.
Transparency is key in big data. With new tools that use machine learning, AI, and natural language processing, health data can become even more powerful. Data visualization and innovative companies can now help organizations stay HIPAA compliant while leveraging the power of data.
Now that EHR has been implemented across the country, it’s clear that this data is extremely valuable. Organizations need to make a concerted effort to tackle the challenges of management head-on and make the most of the data they collect.
The faster we overcome these basic challenges, the faster we’ll all reap the rewards. With better access to accurate, up-to-date data, researchers can spot opportunities and develop treatments more quickly. With data, it’s easier to reduce risks and close care gaps for a healthier world.