For healthcare providers to deliver the best diagnosis and treatment for their patients, the data on which they rely must be of the highest quality, completeness and trustworthiness. It must also accurately reflect how the patient’s health has changed during a period of time. One of the goals of health reform and digital medical records efforts during the past decade has been enabling the creation of unified medical records. This “ patient health timeline ” would be a complete digital chronology of the patient’s lifetime medical history (including symptoms, test results, diagnosis, provider notes and treatment activities) that providers can use when treating the patient.
An ambitious goal, the “patient health timeline” has been a difficult vision to realize due to the volume and fragmentation of patient health records – some of which have been digitized and some still reside in paper form only. Fortunately, for patients younger than 20, the majority of their health data exists in a digital form that can eventually be integrated. There are a number of technical challenges which presently exist that are currently preventing the realization of the “patient health timeline,” but data-quality management technology is rapidly helping companies to overcome some of them.
Fragmentation: Health records for a single patient are spread across the systems of a number of healthcare providers, insurance companies, pharmacies, hospitals and treatment centers. Each of these systems is unique, with no standard means of integrating patient data. Properly contextualizing data through an accurate set of relationships is key to establishing the integrity of integrated data from different sources.
Accuracy: There are portions of a patient’s health record which are relatively static throughout their lifetime (family medical history, allergies, chronic conditions and demographic data) and other portions that change with the patient’s health status and general aging (height/weight, reported symptoms, diagnosis and treatments, mental state, etc.). For the static portions (e.g., profile information), provider records often contain conflicting data, which must be reconciled and validated for accuracy. For the portions of the health timeline that change during a period of time, identifying accurate cause-and-effect relationships among data items is key to creating the actionable insights that providers need. Data validation and reconciliation technology can help companies both resolve data conflicts and identify relationships within data.
Patient Privacy: Regulations require patients to grant specific authorization for the use and sharing of personal health records. Compiling the patient health timeline would require the patient to grant authorization for the data to be integrated, for the use of the timeline data after it is compiled and to allow them to revoke authorization for specific data points or sets during the future. The patient health timeline, therefore, must be assembled in a structured and managed way that would enable disassembly in the future. Data quality management technology can help enable this transformation, so patients and providers know that the health data is both trustworthy and private.
Blazent is the leader in Data Quality, helping organizations drive downstream value by validating and transforming data into actionable intelligence. Nowhere is actionable intelligence needed more than in improving the quality of peoples’ health and wellness. How and when the patient health timeline will become a reality is still to be determined, but it is clear that data-integrity technology will be a critical component.