Rita Reyburn1, Devina Nand2, Cattram Nguyen3, Shivnay Naidu2, Arishma Bali2, Miriama Rokovutoro2, Tupou Ratu4, Simon Kumar2, Donald Lewis5, Varanisese Smith2, Fiona Russell6. 1. Murdoch Childrens Research Institute, Melbourne, Victoria, Australia. Electronic address: rita.reyburn@gmail.com. 2. Health Information, Research and Analysis Unit, Ministry of Health and Medical Services, Suva, Fiji. 3. Murdoch Childrens Research Institute, Melbourne, Victoria, Australia; Dept. of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia. 4. Murdoch Childrens Research Institute, Melbourne, Victoria, Australia. 5. Fiji Health Sector Support Program, Suva, Fiji. 6. Murdoch Childrens Research Institute, Melbourne, Victoria, Australia; Centre for International Child Health, Dept. of Paediatrics, The University of Melbourne, Melbourne, Victoria, Australia.
Abstract
OBJECTIVES: Post-licensure studies to evaluate vaccine impact are an important component of introducing new vaccines. Such studies often rely on routinely collected data but the limitations to these data must be understood. To validate administrative data for use in 10-valent pneumococcal conjugate and rotavirus vaccine impact evaluations we have audited the two electronic database capturing hospital admissions in Fiji for completeness and consistency. METHODS: Hospital admission data for one week per year between 2007-2011 and 2014-2015 was collected from ward registers for selected hospitals. Ward registers were defined as the reference standard and compared to data captured in electronic databases. Data quality was assessed for completeness of admissions data (percentage of admissions in the electronic database, expressed as sensitivity), consistency of complete reporting (determined by identifying variables associated to complete reporting), and completeness of coding (percentage of admissions in the electronic database with an assigned ICD-10-AM code). RESULTS: Over all hospitals and years, the sensitivity for completeness of admission data was 83% (95% CI: 81.3, 84.6). Consistency of complete reporting varied and was highest at tertiary hospitals using the electronic database (sensitivity: 89.1%, 95% CI: 87.4, 90.7). The overall completeness of coding at tertiary hospitals was 90.8% (95% CI: 90.5, 91.1) with annual and hospital variation. CONCLUSION: The administrative data in the electronic databases in Fiji are of reasonable quality for the vaccine impact evaluation. This quantification of the missing data can be used to adjust the vaccine impact estimates.
OBJECTIVES: Post-licensure studies to evaluate vaccine impact are an important component of introducing new vaccines. Such studies often rely on routinely collected data but the limitations to these data must be understood. To validate administrative data for use in 10-valent pneumococcal conjugate and rotavirus vaccine impact evaluations we have audited the two electronic database capturing hospital admissions in Fiji for completeness and consistency. METHODS: Hospital admission data for one week per year between 2007-2011 and 2014-2015 was collected from ward registers for selected hospitals. Ward registers were defined as the reference standard and compared to data captured in electronic databases. Data quality was assessed for completeness of admissions data (percentage of admissions in the electronic database, expressed as sensitivity), consistency of complete reporting (determined by identifying variables associated to complete reporting), and completeness of coding (percentage of admissions in the electronic database with an assigned ICD-10-AM code). RESULTS: Over all hospitals and years, the sensitivity for completeness of admission data was 83% (95% CI: 81.3, 84.6). Consistency of complete reporting varied and was highest at tertiary hospitals using the electronic database (sensitivity: 89.1%, 95% CI: 87.4, 90.7). The overall completeness of coding at tertiary hospitals was 90.8% (95% CI: 90.5, 91.1) with annual and hospital variation. CONCLUSION: The administrative data in the electronic databases in Fiji are of reasonable quality for the vaccine impact evaluation. This quantification of the missing data can be used to adjust the vaccine impact estimates.
Authors: R Reyburn; E J Tuivaga; F T Ratu; E M Dunne; D Nand; J Kado; K Jenkins; L Tikoduadua; A Jenney; B P Howden; S A Ballard; K Fox; R Devi; C Satzke; E Rafai; M Kama; S Flasche; E K Mulholland; F M Russell Journal: Lancet Reg Health West Pac Date: 2022-01-05
Authors: Li Jun Thean; Lucia Romani; Daniel Engelman; Handan Wand; Adam Jenney; Jyotishna Mani; Jessica Paka; Tuliana Cua; Sera Taole; Maciu Silai; Komal Ashwini; Aalisha Sahukhan; Mike Kama; Meciusela Tuicakau; Joseph Kado; Matthew Parnaby; Natalie Carvalho; Margot Whitfeld; John Kaldor; Andrew C Steer Journal: Lancet Reg Health West Pac Date: 2022-03-22
Authors: Adam W J Jenney; Rita Reyburn; Felisita T Ratu; Evelyn Tuivaga; Cattram Nguyen; Sokoveti Covea; Sarah Thomas; Eric Rafai; Rachel Devi; Kathryn Bright; Kylie Jenkins; Beth Temple; Lisi Tikoduadua; Joe Kado; E Kim Mulholland; Carl D Kirkwood; Kimberley K Fox; Julie E Bines; Varja Grabovac; Aalisha Sahu Khan; Mike Kama; Fiona M Russell Journal: Lancet Reg Health West Pac Date: 2020-11-25