Development of quality indicators for the diagnosis and management of achalasia. Issue 10 (15th March 2021) - Kamal, Afrin N.; Kathpalia, Priya; Otaki, Fouad; Bredenoord, Albert J; Castell, Donald O.; Clarke, John O.; Falk, Gary W.; Fass, Ronnie; Prakash Gyawali, C.; Kahrilas, Peter J; Katz, Philip O.; Katzka, David A.; et al.
Abstract: Background: The management of achalasia has improved due to diagnostic and therapeutic innovations. However, variability in care delivery remains and no established measures defining quality of care for this population exist. We aimed to use formal methodology to establish quality indicators for achalasia patients. Methods: Quality indicator concepts were identified from the literature, consensus guidelines and clinical experts. Using RAND/University of California, Los Angeles (UCLA) Appropriateness Method, experts in achalasia independently ranked proposed concepts in a two‐round modified Delphi process based on 1) importance, 2) scientific acceptability, 3) usability, and 4) feasibility. Highly valid measures required strict agreement (≧ 80% of panelists) in the range of 7–9 for across all four categories. Key Results: There were 17 experts who rated 26 proposed quality indicator topics. In round one, 2 (8%) quality measures were rated valid. In round two, 19 measures were modified based on panel suggestions, and experts rated 10 (53%) of these measures as valid, resulting in a total of 12 quality indicators. Two measures pertained to patient education and five to diagnosis, including discussing treatment options with risk and benefits and using the most recent version of the Chicago Classification to define achalasia phenotypes, respectively. Other indicators pertained to treatment options, such as the use of botulinum toxin for those not considered surgical candidates and management of reflux following achalasia treatment. Conclusions & Inferences: Using a robust methodology, achalasia quality indicators were identified, which can form the basis for establishing quality gaps and generating fully specified quality measures. Abstract :