Integrating lab results into analytic databases can yield valuable information

June 1, 2005

In the evolving process of electronically linking all aspects of the healthcare industry so that important data can be shared quickly, efficiently and effectively, another step is being taken, one that holds promise for those who take the time to understand the potential value as well as how to overcome some inherent challenges.

In the evolving process of electronically linking all aspects of the healthcare industry so that important data can be shared quickly, efficiently and effectively, another step is being taken-one that holds promise for those who take the time to understand the potential value as well as how to overcome some inherent challenges.

In the evolving process of electronically linking all aspects of the healthcare industry so that important data can be shared quickly, efficiently and effectively, another step is being taken-one that holds promise for those who take the time to understand the potential value as well as how to overcome some inherent challenges.

This important step is the integration of laboratory results data in analytical databases containing claims and eligibility information. The value of this substantially richer information, say experts, is significant: The melding of lab data with claims, encounter and eligibility information increases the usefulness of these data sources. In the short term, the integrated data can be used to improve provider efficiency and effectiveness, and further reduce medical errors-thus resulting in higher quality patient care. Moreover, thoughtful analysis and application of such integrated data has the long-term potential of helping rein in the ever-escalating cost of healthcare.

Practically speaking, the ease of lab results data integration differs depending on the type of results. For example, results can come in numeric, categorical or descriptive formats. Numerical results, such as those for blood sugar, cholesterol and serum potassium, can be a logical starting point because analysis can be applied broadly for averaging, trending, etc. Categorical results may be more challenging to manipulate since arithmetic operations can not be directly applied. Finally, descriptive formats lack the needed structure for data integration with other analytic information.

LAB RESULTS MEET ANALYTICS For healthcare payers that are considering going down this path, Medstat recommends beginning with numeric lab results because they naturally lend themselves to analytic purposes, and also because there is a standard coding system that provides the needed specificity that CPT codes do not provide for categorization-that system is Logical Observation Identifiers Names and Codes (LOINC), a publicly available coding system developed by the Regenstrief Institute.