Background:
There are many clinical situations in which evidence-based guidelines cannot definitively determine the appropriateness of diagnostic catheterization. One specialty benefits management company has taken a two-step approach towards handling this ambiguity: first evaluating the appropriateness of orders using a rule-based decision support system, and then having reviewers provide additional input through the review process of a nondenial prior authorization program. When reviewers did not find a clear case for appropriateness, ordering physicians were engaged in a discussion with a peer physician. This program evaluation reports on the outcomes of diagnostic catheterization orders analyzed through this two-step process.
Methods:
Data from 2015 elective diagnostic catheterization orders submitted by one health insurer’s Medicare Advantage plans were used for this program evaluation. The rates at which the rule-based system suggested orders were inadequately justified, potentially nonindicated, and potentially appropriate are presented. Rates of approval after review and information gathering by the review process are presented for the three groups of orders. Chi-squared tests were conducted to examine whether the classification of the orders by the rule-based system and the review system were independent of the plan type (HMO or PPO), the specialty of the ordering physician (cardiologist or noncardiologist), or state of residence of the patient (FL, KY, LA, OH, TX, or other).
Results:
There were 3,808 orders for elective diagnostic catheterization, and inadequate initial justification was provided for 699 (18.4%) of the orders. After inquiry through the review process, 509 (72.8%) of these orders were approved. Among the 344 (9.0%) orders deemed potentially nonindicated by the rule-based system, the review process approved 298 (86.7%). Of the 2,765 (72.6%) orders deemed potentially appropriate by the rule-based system, the review process approved 99.1% (2,740/2,765). Chi-squared tests did not show a significant association between plan type (p=0.18) or physician specialty (p=0.89) and the classification of the order by the rule-based system. However, there was a significant association between the classification of the order by the rule-based system and state of residence of the patient (p<0.001). There was not a significant association between the outcome of the review process and the health plan type (p=0.10), the provider’s specialty (p=0.57), or the state of residence of the patient (p=0.73).
Conclusions:
Rule-based decision support can be combined with a review process featuring peer discussion to determine whether care is appropriate when guidelines are ambiguous. Orders which are poorly justified are often supportable after gathering information on the patient’s presentation. There may be state-based variation in the appropriateness of orders.
Application of Fuzzy Rule based System for Highway Research Board Classification of Soils