In increasingly connected healthcare systems, data grows with exponential volume, value, and velocity. To make sense of this data and derive meaningful insights, hospitals, research centres, and pharmaceutical and biotech companies must adopt Health Data Management (HDM).
HDM is crucial for improving healthcare data quality and service delivery while reducing costs. The healthcare big data must make sense for analysts and business leaders while meeting the requirements of the Health Insurance Portability and Accountability Act (HIPAA).
This article explains health data management, types of healthcare data and its benefits and challenges.
What is health data management?
HDM or Health Information Management (HIM) comprises patient’s health data from doctor visits in digital form. This includes Electronic Medical Records (EMRs) and Electronic Health Records (EHRs), from test reports to printed reports and handwritten prescriptions. Research shows that most healthcare organisations collect data about claims, EMR, enrolment, and medical programs. A lesser number of organisations currently collect EMR feeds, disease management program data, patient lifestyle information, data from wearable devices, and surveys.
Types of healthcare data
- Electronic health records – EHRs include patient’s health, clinical, and demographic information that was digitised under the Affordable Care Act (ACA).
- Electronic medical records – EMR is a subset of EHR and contains only the status of current treatment and medical care, not the entire history of the patient.
- Public health data – This data gives a bird´s eye view of the overall health status in a region or a community.
- Imaging data – This includes information from patient´s reports such as X-rays, ultrasounds, MRIs, CT scans, etc.
- Administrative and demographic data – This comprises data from patient’s insurance claims, billing, reimbursement, and payment. Since it contains a patient’s credit card numbers and social security numbers, it is sensitive.
- Data from wearables – From Fitbits to implants that monitor a heart’s performance, data from wearables tracks information about a user’s activity.
- Research and clinical trials – Data from research and clinical trials is anonymous and should not be traceable to the participant.
- Dashboards – Software systems within the healthcare system contain financial, patient, and services dashboards that produce data for better decision-making.
