Assessment tools such as the MDS meet predefined needs for data and information. Additionally, these data sets reflect the limitations of the technology that was available when the assessment form was first developed; data storage was far more expensive than it is today, databases were largely limited to "flat files" and the internet did not exist. Typically, forms with specific questions and phrases that reflect the end-users' need for data provide the structure by which persons record values that populate specific fields within the data set. In this approach to data entry, standardized terms, phrases, and sentences are presented in a highly structured format in order to encode concepts related to functioning and disability, thereby enabling consistent and comparable data. The recording of data is accomplished by people who complete the forms on paper and then enter the data into an electronic format, or by completing an electronic version of the form. Often the form provides a structure for organizing clinical data elements into categories that are later aggregated even further in order to meet the goals of various statistical classification and reporting requirements. The important point is that the person completing the form is presented with a limited set of terms and values and must understand the underlying purposes for which the data set was constructed in order to correctly complete the form. The amount and nature of information available for sharing and re-use for purposes such as automated alerts, decision support, quality monitoring, outcomes research and policy development is constrained by the limited scope of the data set.
In addition to the MDS, the Centers for Medicare and Medicaid Services (CMS) provides oversight of two other data sets that focus on the provision of post acute care services: the Outcome and Assessment Information Set (OASIS) for home care agencies, and the Inpatient Rehabilitation Facility Patient Assessment Instrument (IRF PAI) for rehabilitation units and hospitals. Each of these data sets was developed independently of the other. Consequently, different terms are used to describe similar clinical characteristics of beneficiaries, different rating scales are used, and the time periods in which assessments are completed differs, all limiting the comparability of the data. For example, the MDS requires that a value of 0-3 be entered into each of five data fields indicating over the course of seven days the frequency with which a resident exhibits a variety of behaviors classified as "behavioral symptoms". One item concerns each of the following: wandering, verbally abusive behavior symptoms, physically abusive behavioral symptoms, socially inappropriate/disruptive behaviors, and resists care. Behavioral symptoms are further classified as "Mood and behavior patterns." The OASIS-B1 home care data set requires that a single item be checked indicating, over the course of one month, the "Frequency of behavior problems (e.g. wandering episodes, self abuse, verbal disruption, physical aggression, etc.)." These behavioral problems are further classified as "Neuro/emotional/behavioral status." The developers of both data sets were likely interested in the same clinical data. If specific and detailed clinical descriptions were recorded and indexed within the patient's medical record using standardized and uniform data standards, clinically relevant data could be and retrieved and aggregated for reporting requirements. The present situation seriously limits an analysis of the variation in patients and patient outcomes across post acute cares settings, and resulting in insufficient information on which to base policy decisions.14
This situation is not specific to post-acute care. The data sets on which most public health statistical reporting systems are based were similarly developed independent of each other, and are described as "a patchwork of data collection systems."15 Among the goals of the NHII is that reporting requirements could be derived from patient medical record information, and given well-coordinated systems consistent and comparable expressions of clinical data would be enabled.