The value of data collection is a concept that is generally understood and valued by electronic health record (EHR) developers. What the EHR developer and the healthcare provider are able to do with that data, however, is the true key to delivering quality care to patients and succeeding in an independent practice. Making data actionable is a critical step in the information-gathering process.
There is a lot of data available today. In fact, the amount of data in the world grew by 5,000% between 2010 and 2020. The question is, what can the EHR developer and the independent healthcare provider do with that data to make a difference? The answer is to make that data actionable.
Converting raw healthcare data into actionable intelligence can impact many areas of healthcare, including:
- Research and prediction of disease
- Early detection of disease
- Prevention of unnecessary doctor’s visits
- More accurate calculation of health insurance rates
- More effective sharing of patient data
- Personalization of patient care
Treating patients safely and effectively can be achieved with data that is collected, analyzed, and put into action in real time. As a clearer understanding of the complex healthcare environment is developed, a systematic approach can also be developed to improve patient outcomes and to continuously develop and implement enhancements to healthcare processes.
The provider who takes advantage of available technology to analyze patient data can realize a reduction in duplication and errors as well as better identify at-risk populations. As patient data is used in these types of analyses and turned into actionable data, the result can impact the factors that influence quality care:
- The health outcomes that patients expect and that matter most to them
- How the processes that healthcare providers use impact patients’ desired outcomes
- How the resources, equipment, regulations, and other aspects of healthcare infrastructure affect the quality of care that patients receive.
When considering patient-reported outcome measures, it is important to understand that these differ from process measures of improvement as they focus on what matters most to the patient, typically:
- Recovery from acute illness
- Living well while managing a chronic condition
- Maintaining dignity at the end of life.
Actionable patient data can include how they feel about their overall health, their mood and energy level, and their pain level. Collecting this data does require time and effort but the data can be maintained and managed in the patient’s EHR. The provider must also take into consideration the social and demographic factors that influence patient outcomes.
Tools for analyzing and making data actionable generally fall into three categories:
- Software that acquires the data from sources that include patient surveys, case files, and machine-to-machine data transfers
- Programs that clean, validate, and analyze the data in response to a specific research question
- Software that builds on the results of the analysis to suggest various actions to achieve specific healthcare goals.
Healthcare data analysis can be applied to every aspect of patient care as well as practice management. The EHR developer must secure the data and the analysis results while also ensuring that the healthcare professional can easily access the information that they need to provide quality care for their patients.