Victoria Navarro-Compán1, Josef S Smolen2, Tom W J Huizinga3, Robert Landewé4, Gianfranco Ferraccioli5, José A P da Silva6, Robert J Moots7, Jonathan Kay8, Désirée van der Heijde3. 1. Department of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands, mvictoria.navarroc@gmail.com. 2. Department of Internal Medicine III, Medical University of Vienna 2nd Department of Medicine, Center for Rheumatic Diseases, Hietzing Hospital, Vienna, Austria. 3. Department of Rheumatology, Leiden University Medical Center, Leiden, The Netherlands. 4. Amsterdam Rheumatology Center, Amsterdam, Department of Rheumatology, Atrium Medical Center Heerlen, Heerlen, The Netherlands. 5. Division of Rheumatology, Institute of Rheumatology and Affine Sciences, School of Medicine, Catholic University of the Sacred Heart, Rome, Italy. 6. Department of Rheumatology, Hospitals and Faculty of Medicine, University of Coimbra, Portugal. 7. Institute for Chronic Diseases and Ageing, University of Liverpool, Liverpool, UK and. 8. Division of Rheumatology, Department of Medicine, UMass Memorial Medical Center and University of Massachusetts Medical School, Worcester, MA, USA.
Abstract
OBJECTIVE: To test the feasibility of collecting, storing, retrieving and analysing necessary information to fulfil a preliminary set of quality indicators (QIs) that have been proposed by an international task force in a large multinational clinical practice database of patients with RA. METHODS: Data from all 12 487 patients with 46 005 visits in the Measurement of Efficacy of Treatment in the Era of Outcome in Rheumatology database from January 2008 until January 2012 were analysed to test the feasibility of collecting information on 10 QIs: time to diagnosis; frequency of visits; assessment of autoantibodies and radiographs, disease activity and function; disease remission, low disease activity, normal function; time to first DMARD and type of first DMARD. For each QI, two aspects were assessed: information availability and target achievement. RESULTS: Information was available for <50% of patients regarding the following QIs: time to diagnosis, assessment of ACPAs or radiographs, time to first DMARD and type of first DMARD. Information was available for function assessment in 49% of visits and 67% of patients and for disease activity assessment in 85% of visits and 86% of patients. Information relevant to the QI frequency of visits was available for all patients. Relevant information to calculate the proportion of patients who achieved a defined target could be obtained for all QIs. CONCLUSION: Collecting storing, retrieving and analysing the core data necessary to meaningfully assess quality of care is feasible in a multinational, practice-based electronic database.
OBJECTIVE: To test the feasibility of collecting, storing, retrieving and analysing necessary information to fulfil a preliminary set of quality indicators (QIs) that have been proposed by an international task force in a large multinational clinical practice database of patients with RA. METHODS: Data from all 12 487 patients with 46 005 visits in the Measurement of Efficacy of Treatment in the Era of Outcome in Rheumatology database from January 2008 until January 2012 were analysed to test the feasibility of collecting information on 10 QIs: time to diagnosis; frequency of visits; assessment of autoantibodies and radiographs, disease activity and function; disease remission, low disease activity, normal function; time to first DMARD and type of first DMARD. For each QI, two aspects were assessed: information availability and target achievement. RESULTS: Information was available for <50% of patients regarding the following QIs: time to diagnosis, assessment of ACPAs or radiographs, time to first DMARD and type of first DMARD. Information was available for function assessment in 49% of visits and 67% of patients and for disease activity assessment in 85% of visits and 86% of patients. Information relevant to the QI frequency of visits was available for all patients. Relevant information to calculate the proportion of patients who achieved a defined target could be obtained for all QIs. CONCLUSION: Collecting storing, retrieving and analysing the core data necessary to meaningfully assess quality of care is feasible in a multinational, practice-based electronic database.
Authors: Edward C Keystone; Peter C Taylor; Yoshiya Tanaka; Carol Gaich; Amy M DeLozier; Anna Dudek; Jorge Velasco Zamora; Jose Arturo Covarrubias Cobos; Terence Rooney; Stephanie de Bono; Vipin Arora; Bruno Linetzky; Michael E Weinblatt Journal: Ann Rheum Dis Date: 2017-08-10 Impact factor: 19.103
Authors: Josef S Smolen; Joel M Kremer; Carol L Gaich; Amy M DeLozier; Douglas E Schlichting; Li Xie; Ivaylo Stoykov; Terence Rooney; Paul Bird; Juan Miguel Sánchez Bursón; Mark C Genovese; Bernard Combe Journal: Ann Rheum Dis Date: 2016-10-31 Impact factor: 19.103
Authors: Uta Kiltz; Robert B M Landewé; Désirée van der Heijde; Martin Rudwaleit; Michael H Weisman; Nurullah Akkoc; Annelies Boonen; Jan Brandt; Philippe Carron; Maxime Dougados; Laure Gossec; Merryn Jongkees; Pedro M Machado; Helena Marzo-Ortega; Anna Molto; Victoria Navarro-Compán; Karin Niederman; Percival Degrava Sampaio-Barros; Gleb Slobodin; Filip E Van den Bosch; Astrid van Tubergen; Salima van Weely; Dieter Wiek; Juergen Braun Journal: Ann Rheum Dis Date: 2019-10-11 Impact factor: 19.103
Authors: Eun-Jung Park; Hyungjin Kim; Seung Min Jung; Yoon-Kyoung Sung; Han Joo Baek; Jisoo Lee Journal: Korean J Intern Med Date: 2020-01-02 Impact factor: 2.884
Authors: Pedro Santos-Moreno; Paola Castillo; Laura Villareal; Carlos Pineda; Hugo Sandoval; Omaira Valencia Journal: Open Access Rheumatol Date: 2020-11-06
Authors: Harald J Hamre; Van N Pham; Christian Kern; Rolf Rau; Jörn Klasen; Ute Schendel; Lars Gerlach; Attyla Drabik; Ludger Simon Journal: Patient Prefer Adherence Date: 2018-03-16 Impact factor: 2.711