Dewan Md Emdadul Hoque1,2, Rasa Ruseckaite1, Paula Lorgelly3, John J McNeil1, Sue M Evans1. 1. Department of Epidemiology and Preventive Medicine (DEPM), Monash University, Melbourne, Australia. 2. International Centre for Diarrhoeal Diseases Research in Bangladesh (ICDDR,B), Dhaka, Bangladesh. 3. Office of Health Economics, London, UK.
Abstract
OBJECTIVES: To investigate the attributes of Australian clinical quality registries (CQR). DESIGN AND SETTING: Survey of 40 CQRs between September 2015 and April 2016. PARTICIPANTS: CQR lead investigators/project managers. INTERVENTION: None. MAIN OUTCOME MEASURES: Registry organization, geographical coverage, data quality, management, characteristics, output and outcomes. RESULTS: Of those who responded (34/40; 85.0%), 12 (34.3%) were binational (Australia and New Zealand); 22 (64.7%) were Australian-only registries; and 13 (38.2%) had national coverage. CQRs covered critical care, infection control, cardiovascular diseases, cancer, chronic diseases, procedures and devices, and transplants. Overall, 24/34 CQRs (70.6%) were public sector funded. In total, 14 (41.2%) scored >75% on a composite score developed to assess data quality. Overall, 29/34 (85.3%) produced an annual multi-centred report; only 15/34 (44.1%) produced provider-specific reports. Mortality/survival and quality of life were collected by 82.4 and 32.4% of CQRs, respectively. Most CQRs displayed data in bar/column charts (28/34, 82.4%) and funnel plots (17/34, 50%). Most CQRs adopted an opt-out consent process (n = 17/31; 54.8%). Linear regression indicated that longer duration of CQR was associated with higher data quality (>20 vs 0-5 years coefficient = 4.76, 95% CI: 0.26, 9.26). Opt-in consent was associated with lower data quality (no active consent vs opt-in approval method, coefficient = -5.22, 95% CI: -8.71, -1.72). Six CQRs self-reported having undertaken an economic evaluation of their registry. CONCLUSION: CQRs varied in geographical coverage; stage of development, approach to recruitment; method and frequency of reporting their output; and data quality assurance. An accreditation system for CQRs would likely assist in recognizing high-quality registries.
OBJECTIVES: To investigate the attributes of Australian clinical quality registries (CQR). DESIGN AND SETTING: Survey of 40 CQRs between September 2015 and April 2016. PARTICIPANTS: CQR lead investigators/project managers. INTERVENTION: None. MAIN OUTCOME MEASURES: Registry organization, geographical coverage, data quality, management, characteristics, output and outcomes. RESULTS: Of those who responded (34/40; 85.0%), 12 (34.3%) were binational (Australia and New Zealand); 22 (64.7%) were Australian-only registries; and 13 (38.2%) had national coverage. CQRs covered critical care, infection control, cardiovascular diseases, cancer, chronic diseases, procedures and devices, and transplants. Overall, 24/34 CQRs (70.6%) were public sector funded. In total, 14 (41.2%) scored >75% on a composite score developed to assess data quality. Overall, 29/34 (85.3%) produced an annual multi-centred report; only 15/34 (44.1%) produced provider-specific reports. Mortality/survival and quality of life were collected by 82.4 and 32.4% of CQRs, respectively. Most CQRs displayed data in bar/column charts (28/34, 82.4%) and funnel plots (17/34, 50%). Most CQRs adopted an opt-out consent process (n = 17/31; 54.8%). Linear regression indicated that longer duration of CQR was associated with higher data quality (>20 vs 0-5 years coefficient = 4.76, 95% CI: 0.26, 9.26). Opt-in consent was associated with lower data quality (no active consent vs opt-in approval method, coefficient = -5.22, 95% CI: -8.71, -1.72). Six CQRs self-reported having undertaken an economic evaluation of their registry. CONCLUSION: CQRs varied in geographical coverage; stage of development, approach to recruitment; method and frequency of reporting their output; and data quality assurance. An accreditation system for CQRs would likely assist in recognizing high-quality registries.
Authors: Tim G Coulson; Michael Bailey; Chris Reid; Gil Shardey; Jenni Williams-Spence; Sue Huckson; Shaila Chavan; David Pilcher Journal: BMC Med Inform Decis Mak Date: 2021-02-02 Impact factor: 2.796
Authors: Rob A B Oostendorp; Hans Elvers; Emiel van Trijffel; Geert M Rutten; Gwendolyne G M Scholten-Peeters; Margot De Kooning; Marjan Laekeman; Jo Nijs; Nathalie Roussel; Han Samwel Journal: Front Pain Res (Lausanne) Date: 2022-08-30