Browsing by Subject "quality measurement"

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    Comparison of Assertive Community Treatment Fidelity Assessment Methods: Reliability and Validity
    (Springer, 2016-03) Rollins, Angela L.; McGrew, John H.; Kukla, Marina; McGuire, Alan B.; Flanagan, Mindy E.; Hunt, Marcia G.; Leslie, Doug L.; Collins, Linda A.; Wright-Berryman, Jennifer L.; Hicks, Lia J.; Salyers, Michelle P.; Department of Psychology, School of Science
    Assertive community treatment is known for improving consumer outcomes, but is difficult to implement. On-site fidelity measurement can help ensure model adherence, but is costly in large systems. This study compared reliability and validity of three methods of fidelity assessment (on-site, phone-administered, and expert-scored self-report) using a stratified random sample of 32 mental health intensive case management teams from the Department of Veterans Affairs. Overall, phone, and to a lesser extent, expert-scored self-report fidelity assessments compared favorably to on-site methods in inter-rater reliability and concurrent validity. If used appropriately, these alternative protocols hold promise in monitoring large-scale program fidelity with limited resources.
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    Provider-specific quality measurement for ERCP using natural language processing
    (Elsevier, 2017) Imler, Timothy D.; Sherman, Stuart; Imperiale, Thomas F.; Xu, Huiping; Ouyang, Fangqian; Beesley, Christopher; Hilton, Charity; Coté, Gregory A.; Department of Medicine, IU School of Medicine
    Background and Aims Natural language processing (NLP) is an information retrieval technique that has been shown to accurately identify quality measures for colonoscopy. There are no systematic methods by which to track adherence to quality measures for ERCP, the highest risk endoscopic procedure widely used in practice. Our aim was to demonstrate the feasibility of using NLP to measure adherence to ERCP quality indicators across individual providers. Methods ERCPs performed by 6 providers at a single institution from 2006 to 2014 were identified. Quality measures were defined using society guidelines and from expert opinion, and then extracted using a combination of NLP and data mining (eg, ICD9-CM codes). Validation for each quality measure was performed by manual record review. Quality measures were grouped into preprocedure (5), intraprocedure (6), and postprocedure (2). NLP was evaluated using measures of precision and accuracy. Results A total of 23,674 ERCPs were analyzed (average patient age, 52.9 ± 17.8 years, 14,113 were women [59.6%]). Among 13 quality measures, precision of NLP ranged from 84% to 100% with intraprocedure measures having lower precision (84% for precut sphincterotomy). Accuracy of NLP ranged from 90% to 100% with intraprocedure measures having lower accuracy (90% for pancreatic stent placement). Conclusions NLP in conjunction with data mining facilitates individualized tracking of ERCP providers for quality metrics without the need for manual medical record review. Incorporation of these tools across multiple centers may permit tracking of ERCP quality measures through national registries.