Claims data are more difficult to work with to extract the necessary information about patient conditions in relationship to costs. There can be multiple claims for the same patient episode from different sources. A physician visit after an inpatient claim can be followed up for the inpatient stay rather than to consider the inpatient stay as the start of a new patient episode or a new patient problem. Therefore, in addition to analyzing patient conditions as represented by ICD9 codes, we must also attempt to define an episode and to distinguish between new problems and follow up of old problems.
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Claims data are used to identify general trends concerning patient treatment. (Smith-Bindman, Quale, Chu, Rosenberg, & Kerlikowske, 2006; Wilkinson, Askew, & Dixon, 2006) Claims data are also used to make cross-references to different treatments. In Ceratti, Roger France, and Beguin, claims information was compared to the hospital clinical database to determine if treatment and diagnosis were related, or whether treatment was absent given a diagnosis. (Ceratti, France, & Beguin, 2008) Such observational studies relating billing data to clinical outcomes are fairly common.(Kaushal, Bates, Franz, Soukup, & Rothschild, 2007) Billing charges for prophylactic medication can also be compared to average costs of disease treatment.(Collinet-Adler et al., 2007)
Another study cross-referenced billing data from general practice to that of hospital emergency departments to see if patient visits for infection in the general practice could predict near term increases in emergency room utilization for similar infections.(Sloane et al., 2006) Another use of claims data has been to determine whether appropriate testing is conducted for patients with chronic illnesses. For example, claims are used to determine if patients with diabetes are administered regular A1C tests or to determine if patients with heart conditions are prescribed an ace inhibitor. (Philipneri et al., 2008)
Since multiple providers treat the same patients, the development of a patient severity index will not be as useful to rank the quality of providers since it will become difficult to separate the contribution of each provider. Instead, it can be used to find patterns of treatment and to find those treatment patterns that lead to the best patient outcomes. It can be used to find the relationship between different treatments and different outcomes for the same patient conditions.