Prior Authorization of Medication and Its Influence on Provider Behavior: Latent Class Analysis

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. Health care providers have changed prescribing behaviors to avoid PA. Understanding factors contributing to this phenomenon can facilitate systemic change and better patient care. Objective The objectives of this study are to identify unique unobserved subgroups of prescribers with similar PA-related behaviors using a finite mixture modeling approach; characterize subgroup membership by important covariates; and examine the influence of subgroup membership on 3 relevant prescribing outcomes. Methods A cross-sectional, web-based, nationwide survey of 1173 prescribers was oversampled for psychiatry in support of developing a software-as-a-solution to facilitate PA. Latent class analysis included 12 indicators assessing the degree of PA involvement, provider-insurance communication, and the 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 In total, 1147 prescribers responded with 1144 usable surveys (age, median 50.003 [range 25.00, 72.00] years; 569 (49.74%) females; 67.13% White; 44.84% psychiatrists). In total, 4 unique classes were obtained based on 12 indicators assessing PA-related activities. Classes included a high PA denial class (291 [25.15%]), a Low Volume PA (178 [15.93%]), a class denoted by Problematic Communication Issues with insurers (227 [19.96%]), and a Low Volume PA Class with Problematic Experiences (446 [38.97%]). Only 3 of the 7 covariates (age, specialty type, and patient load) provided additional means to characterize class membership. The observation that certain demographics (race and gender) and provider characteristics (specialty) may not be informative has policy implications and can inform means to improve provider-insurer communication. 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 the 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.

• Publication year

  2025

• Venue

  Journal of Medical Internet Research

• Publication date

  2025-04-02

• Fields of study

  Medicine

• Identifiers
  DOI 10.2196/75361PMID 40729624PMCID 12306842
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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