The Benefit of using Big Data as Part of a Clinical System

The Benefit of using Big Data as Part of a Clinical System

     According to (Milstead & Short, 2019) electronic health records (EHRs) represent one of the best sources of big data in healthcare today. Integration with monitoring devices and point-of-care devices, such as glucometers, provides additional data streams for EHRs while eliminating the need to enter measurements manually, thereby simultaneously streaming work flow and improving data quality (Milstead & Short, 2019). Utilizing the EHRs allows for faster and more accurate diagnoses and preventive measures, which are some of the benefits of using big data as part of the clinical system. For example, suppose a patient’s blood sugar is elevated, the EHR system will send an alert in real-time to the clinical team. The clinical team will then further assess the patient and implement a treatment protocol based on the blood sugar results.

The Challenge of Big Data as part of a Clinical System

     One of the challenges of using big data as part of the clinical system is outdated hospital technology. For example, using paper charting for documentation can increase the potential for data entry errors. Whereas point-of-care devices, such as glucometers, automatically transmit blood sugar results into the EHR system.

Strategy to Mitigate the Challenge of Big Data as part of the Clinical System

     Milstead & Short (2019) states “a knowledge strategy and infrastructure, expertise, and tools are required to discover new learning and knowledge in big data.”  A strategy I have utilized is reviewing the patient’s past results and comparing them to the current results. For example, knowing a patient’s baseline blood sugar is essential, especially when you have a blood sugar that is out of the normal range for the patient. Also, tracking blood sugar trends can be beneficial for future treatment plans. 

     The data generated in each medical act should not only be used to the benefit of that individual patient but also to generate knowledge potentially useful for future patients. All the knowledge generated through big data analyses should be applied to improve clinical decision making and to produce benefits for individual patients (Sacristan & Dilla, 2015). 

                                                                                                                                                                 References

Milstead, J., A. & Short, N., M. (2019). Health policy and politics: A nurse’s guide (6th ed.). Burlington MA: Jones & Bartlett Learning.

Sacristan, J., A. & Dilla, T. (2015). No big data without small data: learning health care systems begin and end with the individual patient. Journal of Evaluation in Clinical practice. https://onlinelibrary.wiley.com/doi/epdf/10.1111/jep.12350