A behavior-analytic account of motivational interviewing

Several published reports have now documented the clinical effectiveness of motivational interviewing (MI). Despite its effectiveness, there are no generally accepted or empirically supported theoretical accounts of its effects. The theoretical accounts that do exist are mentalistic, descriptive, and not based on empirically derived behavioral principles. Empirical research is being generated regarding the role of client and therapist verbal behavior in MI. Client and therapist speech in MI sessions has been correlated with subsequent client behavior change (Amrhein, Miller, Yahne, & Fulcher, 2003; Gaume, Gmel, & Daeppen, 2008; Moyers et al., 2007). Although provocative, these findings are correlational and no theory has yet been provided to explain them. The purposes of the present paper are (a) to bring MI to the attention of clinical behavior analysts; (b) to provide a conceptual account of MI that relies on recent developments in the behavior analysis of motivation and verbal behavior, especially stimulus equivalence and transformation of functions; (c) to provide a possible answer to two critical questions: "How does MI evoke client in-session talk abut behavior change?" and "Why is this change talk related to outcomes?"; and (d) to use this account to identify important research questions and perhaps enhance MI's effectiveness.

Stratified random sampling for estimating billing accuracy in health care systems

This paper presents a stratified random sampling plan for estimating accuracy of bill processing performance for the health care bills submitted to third party payers in health care systems. Bill processing accuracy is estimated with two measures: percent accuracy and total dollar accuracy. Difficulties in constructing a sampling plan arise when the population strata structure is unknown, and when the two measures require different sampling schemes. To efficiently utilize sample resource, the sampling plan is designed to effectively estimate both measures from the same sample. The sampling plan features a simple but efficient strata construction method, called rectangular method, and two accuracy estimation methods, one for each measure. The sampling plan is tested on actual populations from an insurance company. Accuracy estimates obtained are then used to compare the rectangular method to other potential clustering methods for strata construction, and compare the accuracy estimation methods to other eligible methods. Computational study results show effectiveness of the proposed sampling plan.