JMIR Publications

ABSTRACT

Background:

Insurance companies frequently require prior authorization (PA) for medication prescriptions to ensure quality control and safety. The added layer of scrutiny can contribute to provider dissatisfaction and has been associated with adverse patient outcomes. Healthcare providers (HCP’s) have changed prescribing behaviors to avoid PA. Understanding factors contributing to this phenomenon can facilitate systemic change and better patient care.

Objective:

Identify unique subgroups of HCPs with similar PA-related behaviors using a person-centered mixture modeling approach. Characterize subgroup membership by important covariates, and examine the influence of subgroup membership on three relevant prescribing outcomes.

Methods:

Cross-sectional, online, nationwide survey of 1173 HCP’s, oversampled for psychiatry in support of developing a software-as-a-solution to facilitate PA. Latent class analysis (LCA) included 12 indicators assessing degree of PA involvement, provider-insurance communication, and methods of obtaining or avoiding PA. Covariates included age, gender, race, provider role, specialty, number of prescribers, and patient load. Three clinical decision outcomes included prescribing medication other than initially preferred due to PA delays, avoiding newer medications due to anticipated need for PA, and modifying a diagnosis to obtain PA.

Results:

1147 HCPs responded with 1144 usable surveys (median [range] age, 50.003 [25.00, 72.00] years; 569 females [49.74%], 67.13% white, 44.84% psychiatrists). Four unique classes were obtained based on 12 indicators assessing PA-related activities. Classes included a high PA denial class (291 [25.15%]), a low PA problem class (178 [15.93%]), a class denoted by problematic communications with insurers (227 [19.96%]), and a low volume PA class with problematic experiences (446 [38.97%]). Out of 7 covariates only 3 (age, specialty type, and patient load) provided additional means to characterize class membership. The largest class reporting problematic PA experiences had significantly higher mean levels for changing their prescribing and diagnostic behaviors than the remaining classes.

Conclusions:

Providers are not homogeneous regarding their experience with PA and insurance companies. It is therefore important to recognize subtle behavioral differences and find ways to accommodate the PA process to their unique needs. This will facilitate appropriate implementation of PA by insurance companies. Providers can then avoid the need to alter medications, change diagnoses, or resist prescribing newer effective medications that may require lengthy clinical documentation.