BACKGROUND: Worldwide, population-based influenza vaccination strategies are being developed to trace, immunize and monitor high-risk persons efficiently. Computerized prevention modules may facilitate such a strategy in general practice. OBJECTIVES: We established the applicability of a computerized influenza prevention module and specifically addressed improvement of immunization coverage in high-risk patients during two consecutive influenza vaccination rounds after introduction of the module. METHODS: In this descriptive study, four computerized practices of the Utrecht General Practices Network, covering about 36000 patients, participated. In 1995, all patients with high-risk diseases were traced by relevant tags, ICPC- and ATC-codes, using the module. According to changed Dutch immunization guidelines in 1996, healthy elderly people over 65 years were also traced. Demographical and medical data included age, high-risk disease and vaccine uptake. RESULTS: In October 1995, 3871 high-risk patients were identified (11% of population); overall vaccination coverage was 68%. Over one-third of these patients had not been indicated before. In between the two vaccination rounds, 1104 previously unknown patients with high-risk disease <65 years were found by means of the module's on-line status. In October 1996, 6889 persons, including 2308 healthy elderly, were indicated (19%), and vaccination coverage was 62%. Of 3477 patients whose high-risk diseases were documented in both vaccination rounds, an overall improvement of vaccination coverage from 71 % in 1995 to 76% in 1996 was observed (P < 0.05). Main improvements were found in elderly patients. Immunization rates were highest in those with more than one risk factor, lung or cardiac disease, and lowest in healthy elderly and patients under 65 years with lung, renal or other diseases. CONCLUSION: Computerized prevention modules and CMRs may facilitate population-based prevention of influenza and the use should be further encouraged.
BACKGROUND: Worldwide, population-based influenza vaccination strategies are being developed to trace, immunize and monitor high-risk persons efficiently. Computerized prevention modules may facilitate such a strategy in general practice. OBJECTIVES: We established the applicability of a computerized influenza prevention module and specifically addressed improvement of immunization coverage in high-risk patients during two consecutive influenza vaccination rounds after introduction of the module. METHODS: In this descriptive study, four computerized practices of the Utrecht General Practices Network, covering about 36000 patients, participated. In 1995, all patients with high-risk diseases were traced by relevant tags, ICPC- and ATC-codes, using the module. According to changed Dutch immunization guidelines in 1996, healthy elderly people over 65 years were also traced. Demographical and medical data included age, high-risk disease and vaccine uptake. RESULTS: In October 1995, 3871 high-risk patients were identified (11% of population); overall vaccination coverage was 68%. Over one-third of these patients had not been indicated before. In between the two vaccination rounds, 1104 previously unknown patients with high-risk disease <65 years were found by means of the module's on-line status. In October 1996, 6889 persons, including 2308 healthy elderly, were indicated (19%), and vaccination coverage was 62%. Of 3477 patients whose high-risk diseases were documented in both vaccination rounds, an overall improvement of vaccination coverage from 71 % in 1995 to 76% in 1996 was observed (P < 0.05). Main improvements were found in elderly patients. Immunization rates were highest in those with more than one risk factor, lung or cardiac disease, and lowest in healthy elderly and patients under 65 years with lung, renal or other diseases. CONCLUSION: Computerized prevention modules and CMRs may facilitate population-based prevention of influenza and the use should be further encouraged.
Authors: Stephanie Mayne; Dean Karavite; Robert W Grundmeier; Russell Localio; Kristen Feemster; Elena DeBartolo; Cayce C Hughes; Alexander G Fiks Journal: AMIA Annu Symp Proc Date: 2012-11-03
Authors: Tom Marshall; Paul Westerby; Jenny Chen; Mary Fairfield; Jenny Harding; Ruth Westerby; Rajai Ahmad; John Middleton Journal: BMC Public Health Date: 2008-02-25 Impact factor: 3.295
Authors: E Hak; A W Hoes; D E Grobbee; J W J Lammers; G A van Essen; A M van Loon; T J M Verheij Journal: Am J Epidemiol Date: 2003-04-15 Impact factor: 4.897