Is data the bedrock of an evidence bad health and disability system?
Written by Tom Varghese
Is Data the bedrock of an evidence based health system Diagram
The mission of health care institutions demands effective and efficient medical data for evidence-based intervention. Installing an appropriate health care data management system with valid case definition enables efficient data extraction, improves communication for clinical decision making in medical practice, and clinical research, eventually upgrades the quality of health care services downstream.
Data is the golden thread that runs right through the hospital, from patients up to the board level, and we can enable people to make data-driven decisions in all care settings. The challenge is to deliver this within healthcare budgets. New opportunities are arising for treatment through genetics, and better decision making is possible using algorithms and artificial intelligence. Learning more from health data can support these changes and help achieve better care in a cost-efficient manner.
In addition, the delivery of population health relies on the accessibility of good data across the system enabling health and care professionals to make informed decisions. Making sure that this data can be shared, embedded in local pathways and interpreted by the workforce is key to planning effective population health strategies and to improve patient care.
The healthcare sector has never been as focused on data as it is today. From the control of expenses to the detection of fraud and the coordination of consultations, the use of data analysis has been considered essential for solving various types of problems in the sector. In practice, however, the volume of data can end up being a big challenge. Considering the different medical record systems, information provided by medical devices, employee spreadsheets, patient satisfaction surveys, and monitoring medical equipment, a hospital generates an exorbitant amount of data.
Some question the problems that arise in relation to the security of data collection in healthcare and these issues shouldn’t be dismissed. However, as an overarching theme, big data analytics leverage the gap within structured and unstructured data sources. The shift to an integrated data environment is a well-known hurdle to overcome. Therefore, it is essential for technologists and professionals to understand this evolving situation. In the coming years it can be projected that big data analytics will march towards a predictive system.
Taken together, big data will facilitate healthcare by providing early warnings of disease conditions, and helping in the discovery of novel biomarkers and intelligent therapeutic intervention strategies for an improved quality of life.
Quantifying this value is a complex endeavour dependent on multiple variables. There are significant costs that need to be taken into account associated with curating, processing and analysing electronic patient records. Lastly, challenges around interoperability and diverse data contents need to be addressed.
