The data elements suggested by the domain experts, ACOVE indicators, and MDS quality measure reflect differing perspectives related to the essential data on which to infer quality of care. There is clearly a different emphasis on the type of information needed to understand quality between the clinical experts (both the individual domain experts and the ACOVE panels) and the MDS quality measures. The clinical experts emphasized assessments that identify persons with actual or potential problems, and then link those assessments and judgments to processes of care. A repeating theme in the ACOVE panels is that it is the failure to identify persons who would benefit from specific care processes that is an indicator of quality, not merely the occurrence of the event.
The focus of the MDS quality indicators and quality measures is on the prevalence of the three conditions, reflecting in part the nature of data within the MDS but also perhaps a public demand for prevalence and outcomes data. However, as experts in the measurement of quality emphasize, such data are extremely difficult to interpret accurately, particularly in the absence of information needed to adequately risk adjust and the absence of information about the processes of care associated with those outcomes. This suggests that the MDS quality measures may not be the most relevant indicators of quality for inferring quality.
The construction of quality indicators and quality measures from MDS data elements is constrained by the availability of data within the MDS; the availability of data within the MDS is constrained by the limited clinical content within the MDS. The difference in the extent to which the MDS provided acceptable pressure ulcer data compared to chronic pain and urinary incontinence data suggests that the MDS be examined carefully for the completeness with which quality inferences can be made. A highly coordinated and structured NHII would enable reporting data for quality oversight functions to be derived from a patient medical record information system. In addition, and perhaps more important to improving quality in long-term care facilities, automated decision support systems could be built within that patient medical record information (PMRI) system thereby providing alerts and reminders at the point-of-care.