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Chapter One provided an overview of the various types of health care data and information that are generated and used by health care organizations. We established the importance of understanding health care data and information in order to reach the goal of having effective health care information systems. There is another fundamental aspect of health care data and information that is central to developing effective health care information systems—data quality. Consider for a moment an organization with sophisticated health care information systems that affect every type of health care information, from patient specific to knowledge based. What if the quality of the documentation going into the systems is poor? What if there is no assurance that the reports generated from the systems are accurate or timely? How would the users of the systems react? Are those information systems beneficial or detrimental to the organization in achieving its goals?
In this chapter we will examine several aspects of data quality. We begin by distinguishing between health care data and health care information. We then look at some problems associated with poor-quality health care data, both at an organizational level and across organizations. The discussion continues with a presentation of two sets of guidelines that can be used in evaluating data quality and ends with an examination of the major types of health care data errors.
Within the broad category of data and information created internally by the health care organization, we will focus on clinical and administrative information directly related to the activities surrounding the patient encounter, both the individual encounter and the collective encounter. We break information related to the patient encounter into the subcategories of patient specific, aggregate, and comparative. Our focus is on the clinical and administrative individual and aggregate health care information that is associated with a