Using Routine Data Sources to Feed an Immunization Information System for High-Risk Patients—A Pilot Study
BackgroundVaccine-preventable diseases among high-risk patients are a public health priority in high-income countries. Most national immunization programs have included vaccination recommendations for these population groups but they remain hard-to-reach and coverage data are poorly available. In a...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2018-02-01
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| Series: | Frontiers in Public Health |
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| Online Access: | http://journal.frontiersin.org/article/10.3389/fpubh.2018.00037/full |
| _version_ | 1798044569196036096 |
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| author | Domenico Martinelli Francesca Fortunato Stefania Iannazzo Maria Giovanna Cappelli Rosa Prato |
| author_facet | Domenico Martinelli Francesca Fortunato Stefania Iannazzo Maria Giovanna Cappelli Rosa Prato |
| author_sort | Domenico Martinelli |
| collection | DOAJ |
| description | BackgroundVaccine-preventable diseases among high-risk patients are a public health priority in high-income countries. Most national immunization programs have included vaccination recommendations for these population groups but they remain hard-to-reach and coverage data are poorly available. In a pilot study, we developed and tested an automated approach for identifying individuals with underlying medical conditions to feed an immunization information system (IIS).MethodsWe reviewed published recommendations on medical conditions that indicate vaccination against influenza, pneumococcal disease, meningococcal disease, hepatitis A, and hepatitis B. For each medical condition, we identified the International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis and procedure codes, the user fee exempt codes and the Anatomical Therapeutic Chemical Classification System codes and we reported these data in correspondence tables. Using these tables, we extracted three lists of patients recorded in three current data sources between 2001 and 2010 in the Apulia region of Italy: the hospital discharge registry, the user fee exempt registry, and the drug prescription registry. Using a unique personal identification number, we linked these three lists of patients with the regional IIS (2012 database), obtaining a list of patients with chronic diseases eligible for vaccination. We tested completeness, sensitivity, and positive predictive value (PPV) of this approach by asking a sample of 28 general practitioners (GPs) to evaluate the matching between a sublist of patients with clinical recommendations for influenza vaccination and the GPs individual subjects medical records.ResultsWe included a total of 1,204,496 subjects with underlying medical conditions eligible to receive any of the aforementioned vaccinations. Of these, 9% were identified in all three data sources, 18% in two sources, and 73% in one source. The completeness of this automated process in identifying GPs high-risk patients eligible for influenza vaccination was 88.9% [95% confidence intervals (95% CI): 88.1–89.8%], with a sensitivity of 69.2% (95% CI: 67.7–70.6%) and a PPV of 85.7% (95% CI: 84.4–86.8%).ConclusionThe high completeness of the methodology used for identifying high-risk patients in current data sources encouraged us to apply this approach for feeding the regional IIS. |
| first_indexed | 2024-04-11T23:06:10Z |
| format | Article |
| id | doaj.art-621575a3850a413fbf1162967308eca6 |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-04-11T23:06:10Z |
| publishDate | 2018-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj.art-621575a3850a413fbf1162967308eca62022-12-22T03:58:00ZengFrontiers Media S.A.Frontiers in Public Health2296-25652018-02-01610.3389/fpubh.2018.00037297543Using Routine Data Sources to Feed an Immunization Information System for High-Risk Patients—A Pilot StudyDomenico Martinelli0Francesca Fortunato1Stefania Iannazzo2Maria Giovanna Cappelli3Rosa Prato4Department of Medical and Surgical Sciences, University of Foggia, Foggia, ItalyDepartment of Medical and Surgical Sciences, University of Foggia, Foggia, ItalyDirectorate-General of Health Prevention, Ministry of Health, Rome, ItalyDepartment of Medical and Surgical Sciences, University of Foggia, Foggia, ItalyDepartment of Medical and Surgical Sciences, University of Foggia, Foggia, ItalyBackgroundVaccine-preventable diseases among high-risk patients are a public health priority in high-income countries. Most national immunization programs have included vaccination recommendations for these population groups but they remain hard-to-reach and coverage data are poorly available. In a pilot study, we developed and tested an automated approach for identifying individuals with underlying medical conditions to feed an immunization information system (IIS).MethodsWe reviewed published recommendations on medical conditions that indicate vaccination against influenza, pneumococcal disease, meningococcal disease, hepatitis A, and hepatitis B. For each medical condition, we identified the International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis and procedure codes, the user fee exempt codes and the Anatomical Therapeutic Chemical Classification System codes and we reported these data in correspondence tables. Using these tables, we extracted three lists of patients recorded in three current data sources between 2001 and 2010 in the Apulia region of Italy: the hospital discharge registry, the user fee exempt registry, and the drug prescription registry. Using a unique personal identification number, we linked these three lists of patients with the regional IIS (2012 database), obtaining a list of patients with chronic diseases eligible for vaccination. We tested completeness, sensitivity, and positive predictive value (PPV) of this approach by asking a sample of 28 general practitioners (GPs) to evaluate the matching between a sublist of patients with clinical recommendations for influenza vaccination and the GPs individual subjects medical records.ResultsWe included a total of 1,204,496 subjects with underlying medical conditions eligible to receive any of the aforementioned vaccinations. Of these, 9% were identified in all three data sources, 18% in two sources, and 73% in one source. The completeness of this automated process in identifying GPs high-risk patients eligible for influenza vaccination was 88.9% [95% confidence intervals (95% CI): 88.1–89.8%], with a sensitivity of 69.2% (95% CI: 67.7–70.6%) and a PPV of 85.7% (95% CI: 84.4–86.8%).ConclusionThe high completeness of the methodology used for identifying high-risk patients in current data sources encouraged us to apply this approach for feeding the regional IIS.http://journal.frontiersin.org/article/10.3389/fpubh.2018.00037/fullchronic illnesshigh-risk patientsunderlying medical conditionscomorbid disordersvaccinationimmunization information system |
| spellingShingle | Domenico Martinelli Francesca Fortunato Stefania Iannazzo Maria Giovanna Cappelli Rosa Prato Using Routine Data Sources to Feed an Immunization Information System for High-Risk Patients—A Pilot Study Frontiers in Public Health chronic illness high-risk patients underlying medical conditions comorbid disorders vaccination immunization information system |
| title | Using Routine Data Sources to Feed an Immunization Information System for High-Risk Patients—A Pilot Study |
| title_full | Using Routine Data Sources to Feed an Immunization Information System for High-Risk Patients—A Pilot Study |
| title_fullStr | Using Routine Data Sources to Feed an Immunization Information System for High-Risk Patients—A Pilot Study |
| title_full_unstemmed | Using Routine Data Sources to Feed an Immunization Information System for High-Risk Patients—A Pilot Study |
| title_short | Using Routine Data Sources to Feed an Immunization Information System for High-Risk Patients—A Pilot Study |
| title_sort | using routine data sources to feed an immunization information system for high risk patients a pilot study |
| topic | chronic illness high-risk patients underlying medical conditions comorbid disorders vaccination immunization information system |
| url | http://journal.frontiersin.org/article/10.3389/fpubh.2018.00037/full |
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