R H Dolin1. 1. Kaiser Permanente, Southern California Region, USA. Robert.Dolin@kp.org
Abstract
OBJECTIVE: Describe a high-level conceptual electronic health record (EHR) data model, explain how the model is expressive, present an algorithm for querying the model and determine the complexity of this algorithm. DESIGN: Entity-Relationship diagramming is used to represent the model, which relies on variably nested relations to enable expressiveness. The algorithm complexity is described using "big-oh" or "O()" notation. RESULTS: The data model appears to be highly expressive. A tractable recursive query processing algorithm is presented which is polynomial in time and space complexity. CONCLUSION: Several hurdles remain before the model and algorithm described can be fully tested in a live setting, including the development of techniques to populate the model. However, the study does show the ability to formally analyze an EHR model to understand its particular expressiveness and query complexity.
OBJECTIVE: Describe a high-level conceptual electronic health record (EHR) data model, explain how the model is expressive, present an algorithm for querying the model and determine the complexity of this algorithm. DESIGN: Entity-Relationship diagramming is used to represent the model, which relies on variably nested relations to enable expressiveness. The algorithm complexity is described using "big-oh" or "O()" notation. RESULTS: The data model appears to be highly expressive. A tractable recursive query processing algorithm is presented which is polynomial in time and space complexity. CONCLUSION: Several hurdles remain before the model and algorithm described can be fully tested in a live setting, including the development of techniques to populate the model. However, the study does show the ability to formally analyze an EHR model to understand its particular expressiveness and query complexity.
Authors: P W Moorman; A M van Ginneken; P D Siersema; J van der Lei; J H van Bemmel Journal: J Am Med Inform Assoc Date: 1995 Nov-Dec Impact factor: 4.497