p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 2 7 1 e2 7 5
Available online at www.sciencedirect.com
Public Health journal homepage: www.elsevier.com/puhe
Short Communication
Identifying data sources for a national populationbased registry: the experience of the Spanish Rare Diseases Registry n a, E. Barcelo a, M.D. Esteban Vasallo a, A.C. Zoni a,*, M.F. Domı´nguez Berjo I. Abaitua b, J. Jimenez Villa c, M. Margolles Martins d, C. Navarro e,f, zquez Santos f, M. Posada b, J.M. Ramos Aceitero g, C. Va O. Zurriaga Llorens h,i, J. Astray Mochales a, Spain-RDR Group a
Area of Epidemiology, Sub-directorate of Health Promotion and Prevention, General Directorate of Primary Care, Health Department of the Autonomous Government of Madrid, Spain b Research Institute for Rare Disease, Institute of Health Carlos III, Madrid, Spain c Operative Planning and Evaluation Division, Health Area, Catalan Health Service (CatSalut) Autonomous ~ a, Spain Government of Catalun d Epidemiology & Surveillance Service, General Directorate of Public Health, Health Department of the Autonomous Government of Asturias, Spain e Dep. of Pathology & Neuropathology, University Hospital of Vigo (CHUVI-SERGAS), Spain f Neurosciences Research Group ‘NC-CHUVI’, Instituto de Investigacion Biomedica de Vigo (IBIV), Xerencia de Xesti on Integrada de Vigo e SERGAS, Spain g Sub-Directorate of Epidemiology, General Directorate of Public Health, Health Department of the Autonomous Government of Extremadura, Spain h Epidemiological Surveys & Health Statistics Service, General Directorate of Public Health, Autonomous Government of Valencia, Spain i Centre for Public Health Research (CSISP), Autonomous Government of Valencia, Spain
article info Article history: Received 28 November 2013 Received in revised form 9 December 2014 Accepted 12 December 2014 Available online 16 February 2015
Background Rare Diseases (RD) are a diverse group of diseases with low prevalence (5 cases per 10,000 population),
most of them chronic, with disability and premature mortality.1 RD are considered a priority for action in the Public Health Programme of the European Union (EU). The European Commission Communication (November 11, 2008) and the recommendations of the Council of Europe and the European Parliament about RD (June 8, 2009), stressed the need for information on RD and the creation of registries and a database. Based on these recommendations, several technical projects on RD are being carried out, such as EPIRARE (European Platform for Rare Disease Registries), RD-CONNECT (an integrated platform connecting databases, registries, biobanks and clinical bioinformatics for RD research), IRDiRC (International Rare Diseases Research Consortium), etc.2
* Corresponding author. C/ San Martin de Porres N 6, 1ª planta, 28035 Madrid, Spain. Tel.: þ34 91 370 08 11; fax: þ34 91 426 56 25. E-mail address: [email protected] (A.C. Zoni). http://dx.doi.org/10.1016/j.puhe.2014.12.013 0033-3506/© 2015 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
272
p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 2 7 1 e2 7 5
Population-based disease registries are key instruments for RD research due to the scarcity of cases and lack of knowledge about them.3e5 They have become one of the main objectives of the IRDiRC strategy. The Spain-RDR is a Spanish IRDiRC project aimed at creating a national population-based RD registry (RDR) and may provide useful, high quality information for multiple purposes, beneficial for different stakeholders, not only for the patient and their families, but also for clinical professionals, researchers and decision-makers. The Spain-RDR will contribute to improving the planning and management of these diseases, creating clinical reference centers and reaching statistical power for conclusive research. The objective of the study was to identify the RD data sources available in Spain in order to develop a national RDR.
assigning one point for each: availability in the AC (if the source was available in at least 12 AC), ability to identify the cases, comparability between AC (if it was a coded database), and the population covered (if it was a population-based database). Databases with three or four points were classified as essential and the rest as complementary. This score helps to identify those data sources considered as essential and prioritize them in order to ensure a homogenous starting point on national level. According to the Personal Data Protection Law,6 personal data subject to processing may be communicated to a third person only with the prior consent of the subject, except for when the transfer is authorized by law, when the transfer of personal health data is necessary for resolving an emergency, or for conducting epidemiological studies as established by national or regional health legislation.
First steps Spain is organized administratively and politically into 17 autonomous communities (AC) and two autonomous cities (Ceuta and Melilla). The Spain-RDR project is coordinated by the Institute of Rare Disease Research (IIER-ISCIII). It involves all autonomous health departments, the main Spanish Rare Disease Patient Alliance (FEDER), industry, medical societies and the Ministry of Health. Each AC has a RDR coordinator. This is a descriptive study. An electronic ad hoc questionnaire was elaborated by a working group formed by experts in health information systems to gather the RD data sources available in each AC before December 31, 2012. The questionnaire was administered to the AC RDR coordinators, together with instructions on how to fill it out. For each information source the following characteristics and the availability of specific data were assessed: type of RD recorded, type of diagnosis coding (International Classification of Diseases ‘ICD-9-CM and ICD-10’, International Classification of Primary Care ‘ICPC-2’, Systematized Nomenclature of Medicine ‘SNOMED’, ORPHANET, codification of nursing diagnoses ‘NANDA’, none, and others), clinical data (onset of symptoms, diagnosis and death dates), personal information (name, surname, personal identification number and health insurance number) and if the data transfer from each AC-RDR to the Spain-RDR was scheduled and how (anonymized or not; because under current legislation, some AC cannot transfer information with personal data to Spain-RDR). Previously, all data sources were grouped into 17 generic headings: health insurance card database, electronic hospital clinical records, electronic primary care clinical records, cancer registry, newborn screening registry (metabolic diseases), notifiable disease registry, mortality registry, chronic renal diseases registry, orphan drugs registry, birth defect registry, birth registry, compassionate drugs registry, specific information from RD projects, RD patient associations, social services sources (social work registries, assessment of disability and dependency records, social services for people with disabilities, early care teams…), educational sources (students with special needs) and other registries (oral health, biobank, asbestos workers, transplant, abortion…). Finally, each data source was classified as essential or complementary for the Spain-RDR. This classification was based on a score which took into account the following items,
Results The questionnaires were completed by each AC-RDR coordinator between April 30 and July 30, 2012. The response rate was 100% (17 AC) and variables used to distinguish essential or complementary sources were completed at 100%. A total of 280 data sources were identified. The median was 14 RD data sources per AC (range: 4e40). Essential sources represented 43.3% and included the hospital discharge Minimum Basic Data Set (MBDS), cancer registries, newborn screening records, health insurance card database, notifiable disease records, mortality registry, chronic renal disease registry and orphan drug registry. Complementary data sources included electronic primary care clinical records, birth defect registry, birth registry, compassionate drugs registry, information from specific RD projects, RD patients associations, social and educational sources. The list of data sources by groups and by AC is given in Table 1. The MBDS was the only source available in all AC, followed by the cancer registry, newborn screening registry and health insurance card database (88.2% of the AC each). Most of the AC can access personal data in these sources, which allows controlling for duplicates and cross-matching different data sources. The greatest differences in accessibility were found in the chronic renal disease registries and orphan drug registries. To date, linking the essential data sources resulted in a minimum data set consisting of: unique patient number, names, surnames, personal identification number, health insurance number, sex, date of birth, address, date of death, cause of death, RD name, ICD9-CM (code and name), ICD10 (code and name). Regarding compatibility, all clinical data sources are coded in ICD9-CM at least. The estimated number of RD that may be linked to the Spain-RDR is around 1200. The transference of non-anonymized data to IIER-ISCIII, with proper legal regulations, was allowed in 10 of the 17 AC. This report provides a comprehensive description of RD data sources available in Spain and their best possible use for the construction of the Spain-RDR. As the MBDS will be the source which will identify the largest number of cases, those RD which, given their natural history, do not require hospitalization for diagnosis or treatment will be underrepresented.7 However, this is mitigated in
Table 1 e Most common data sources available for RD registry in each autonomous community before December 31, 2012. Data sourcesa
Autonomous communities ~ a Extremadura Galicia La Madrid Murcia Navarra C.Valenciana Pais Andalucı´a Aragon Asturias Baleares Canarias Cantabria Castilla Castilla- Catalun -L LM Rioja Vasco x x x
x x
x x x
x x x
x x x
x x x
x x x
x x
x x
x x
x x
x x
x x
x x
x
x
x
x
x
x
x
x
x x x x
x
x
x
x
x
x
x
x x
x
x
x
x x
x
x x x
x x x
x x
x x
x
x
x
x
x
x
x
x
x
x
x x x
x
x x x
x
x x
x x
x
x
x
x
x x x
x x x
x x x
x
x x
x x
x
x
x
x
x
x
x
x
x x x
x
x x x
x
x x
x
p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 2 7 1 e2 7 5
Essential MBDS Cancer registry Metabolic diseases registry HICD Notifiable diseases registry Mortality registry Chronic renal diseases registry Orphan drugs registry Complementary EPCCR Birth defects registry Birth registry Compassionate drugs registry
x
x
x
Abbreviations: MBDS, Hospital Discharge Minimum Basic Data Set. HICD, Health Insurance Card Database. EPCCR, Electronic Primary Care Clinical Records. a Sorted by the score which took into account the following items, assigning one point for each: availability in the AC (if the source was available in at least 12 AC), ability to identify the cases, comparability between AC (if it was a coded database), and the population covered (if it was a population-based database).
273
274
p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 2 7 1 e2 7 5
part by the inclusion of cases from the cancer registry, chronic renal disease, newborn screening and orphan drug registries, which are available in many AC. One limitation of the study is that the feasibility of working with the linked data sources in terms of data quality will have to be verified in the future. The awareness of the limitations of using the ICD9-CM to identify RD are also known.1,2,8 But the project is still in its beginnings, and one of its strong points is the linking of existing databases from 17 AC, which have been widely used for specific research individually, but are rarely combined. The complexity of the RD imposes a large geographical coverage of the data collection, which implies cooperation in order to share the clinical and epidemiological experience.2,3
Future Related to the standardization of the databases, every variable with personal information will have a normalization process in order to validate the format. For example, the health insurance number must be alphanumeric with 16 characters. Also, all databases will be coded in ICD9-CM. The data will be linked using the health insurance number or name plus the last name and the date of birth. The variables of personal identification plus the ICD9-CM codes will be used to control cases duplicates. The next steps planned are auditing electronic clinical records and integrating specific health information systems and public health sources with information from other non-health related agencies.9 Many people with RD require specialized services and resources for disability. This information is complementary and it will help provide a complete picture of the burden of RD. Through the linkage of these databases and the creation of Spain-RDR, the authors hope to improve patients' access to expert care and provide useful, high quality information to decision-makers; thus contributing to improvements in the prevention, diagnosis, treatment and quality of life for the patients and their families.10
Ethical approval None required.
Funding Spanish Rare Diseases Registries Research Network (SpainRDR), Grant number IR11-RDR. Financial agency: Instituto de Salud Carlos III (ISCIII) e International Rare Diseases Research Consortium (IRDiRC).
Competing interests None declared.
Authors' information Following persons are the members of the Spain-RDR group: Josefa Marı´a Aldana Espinal, Marı´a del Amor Bueno Delgado, ndez, Antonio Gonza lez-Meneses Lo pez, Aurora Megı´as Ferna Laura Lahera Robles, Celia Salamanca Rivera, Reyes Sanz Amores (Andalucı´a). Federico Arribas, Clara Laguna Berna n). Laura Pruneda Gonza lez (Asturias). Mercedes Caf(Arago ~ o Riera, Anto nia Galme s Truyols faro Rovira, Eusebi Castan (Illes Baleares). Ione Aguiar, Patricia Carrillo, Milagrosa San s Alvarado Garcı´a, Miguel Garcı´a Ribes, tana (Canarias). Andre rrez, Luis Miguel Ruiz Ceballos (Cantabria). Gonzalo Gutie Ricardo Ortega (Castilla La Mancha). Rufino Alamo Sanz, Jesu´s nchez, Toma s Vega Alonso (Castilla Leo n). Roser Dı´az Sa , Gemma Rovira (Catalun ~ a). Carmen Francisco, Pilar Magrinya Barona Vilar, Clara Cavero Carbonell, Rosana Guaita Cala nez trava, Miguel Angel Martı´nez Beneito, Carmen Martos Jime (Comunitat Valenciana). Marı´a del Carmen Antonaya Rojas, n, M.de los Angeles Garcı´a Bazaga (Extremadura). Enrique Gala nica Alonso, Teresa Garcı´a (INGESA). Angela Almansa, Vero Carroquino, Patricia Garcı´a Primo, Manuel HensMarı´a Jose rez, Antonio Morales-Piga, Ana Villaverde (IIER). Ana Bele n Pe pez, Joaquı´n Palomar Rodrı´guez, Marta Segura Moreno Lo Aroca (Murcia). Eva Ardanaz, Esther Vicente Cemborain (Navarra). Luis Martı´nez, Ruth Martı´nez (Paı´s Vasco). Enrique mara (La Rioja). Ramalle Go
Author statements All authors participated in the design, analysis and data interpretation. All authors designed the survey, E. Barcelo developed the database and A.C. Zoni wrote the first draft of the manuscript. All authors contributed to successive drafts and approved the final version.
Acknowledgments The authors would like to thank all the people who helped make available the data, including the families affected, social workers and information technology technicians. The authors would also like to thank Dr. Vendula Blaya kova (Department of Preventive Medicine and Quality Nova ~o n, Management, General University Hospital Gregorio Maran Madrid) for providing valuable comments and helping with the translation of the article.
references
1. Kodra Y, Fantini B, Taruscio D. Classification and codification of rare diseases. J Clin Epidemiol 2012;65(9):1026e7. ra J. The European Union policy 2. Montserrat Moliner A, Waligo in the field of rare diseases. Public Health Genomics 2013;16(6):268e77. http://dx.doi.org/10.1159/000355930 [Epub 2014 Feb 3]. 3. Schieppati A, Henter JI, Daina E, Aperia A. Why rare diseases are an important medical and social issue. Lancet 2008;371(9629):2039e41. 4. Forrest CB, Bartek RJ, Rubinstein Y, Groft SC. The case for a global rare-diseases registry. Lancet 2011;377(9771):1057e9. S, Kole A, Rodwell C. Patient registries the field of rare 5. Ayme diseases: overview of the issues surrounding the establishment, governance and financing of academic registries. Rare Disease Task Force. Available at: http://www.eucerd.eu/EUCERD/
p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 2 7 1 e2 7 5
upload/file/RDTFReportRegistriesJuly2011.pdf; 2011 [accessed 02.09.13]. 6. Organic law 15/1999 of 13 December on the protection of personal data. Spanish Off J, number 298, of 14 December, 1999. Available at: http://www.agpd.es/portalwebAGPD/ english_resources/regulations/common/pdfs/Ley_Orgaica_ 15-99_ingles.pdf. [accessed 02.09.13]. 7. Knight AW, Senior TP. The common problem of rare disease in general practice. Med J Aust 2006;185:82e3.
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8. Posada de la Paz M, Garcı´a Ribes M. Epidemiology concepts: current situation and future perspectives. Aten Primaria 2010;42:169e72. n FJ, Ferna ndez Merino JC. Contributions to the 9. Garcı´a Leo development of a public health information system. SESPAS report 2010. Gac Sanit 2010;24:96e100. 10. Gliklich RE, Dreyer NA. Registries for evaluating patient outcomes: a user's guide. 2nd ed. Rockville (MD): Agency for Healthcare Research and Quality (US); 2010.
Available online at www.sciencedirect.com
Public Health journal homepage: www.elsevier.com/puhe
Short Communication
Identifying data sources for a national populationbased registry: the experience of the Spanish Rare Diseases Registry n a, E. Barcelo a, M.D. Esteban Vasallo a, A.C. Zoni a,*, M.F. Domı´nguez Berjo I. Abaitua b, J. Jimenez Villa c, M. Margolles Martins d, C. Navarro e,f, zquez Santos f, M. Posada b, J.M. Ramos Aceitero g, C. Va O. Zurriaga Llorens h,i, J. Astray Mochales a, Spain-RDR Group a
Area of Epidemiology, Sub-directorate of Health Promotion and Prevention, General Directorate of Primary Care, Health Department of the Autonomous Government of Madrid, Spain b Research Institute for Rare Disease, Institute of Health Carlos III, Madrid, Spain c Operative Planning and Evaluation Division, Health Area, Catalan Health Service (CatSalut) Autonomous ~ a, Spain Government of Catalun d Epidemiology & Surveillance Service, General Directorate of Public Health, Health Department of the Autonomous Government of Asturias, Spain e Dep. of Pathology & Neuropathology, University Hospital of Vigo (CHUVI-SERGAS), Spain f Neurosciences Research Group ‘NC-CHUVI’, Instituto de Investigacion Biomedica de Vigo (IBIV), Xerencia de Xesti on Integrada de Vigo e SERGAS, Spain g Sub-Directorate of Epidemiology, General Directorate of Public Health, Health Department of the Autonomous Government of Extremadura, Spain h Epidemiological Surveys & Health Statistics Service, General Directorate of Public Health, Autonomous Government of Valencia, Spain i Centre for Public Health Research (CSISP), Autonomous Government of Valencia, Spain
article info Article history: Received 28 November 2013 Received in revised form 9 December 2014 Accepted 12 December 2014 Available online 16 February 2015
Background Rare Diseases (RD) are a diverse group of diseases with low prevalence (5 cases per 10,000 population),
most of them chronic, with disability and premature mortality.1 RD are considered a priority for action in the Public Health Programme of the European Union (EU). The European Commission Communication (November 11, 2008) and the recommendations of the Council of Europe and the European Parliament about RD (June 8, 2009), stressed the need for information on RD and the creation of registries and a database. Based on these recommendations, several technical projects on RD are being carried out, such as EPIRARE (European Platform for Rare Disease Registries), RD-CONNECT (an integrated platform connecting databases, registries, biobanks and clinical bioinformatics for RD research), IRDiRC (International Rare Diseases Research Consortium), etc.2
* Corresponding author. C/ San Martin de Porres N 6, 1ª planta, 28035 Madrid, Spain. Tel.: þ34 91 370 08 11; fax: þ34 91 426 56 25. E-mail address: [email protected] (A.C. Zoni). http://dx.doi.org/10.1016/j.puhe.2014.12.013 0033-3506/© 2015 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
272
p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 2 7 1 e2 7 5
Population-based disease registries are key instruments for RD research due to the scarcity of cases and lack of knowledge about them.3e5 They have become one of the main objectives of the IRDiRC strategy. The Spain-RDR is a Spanish IRDiRC project aimed at creating a national population-based RD registry (RDR) and may provide useful, high quality information for multiple purposes, beneficial for different stakeholders, not only for the patient and their families, but also for clinical professionals, researchers and decision-makers. The Spain-RDR will contribute to improving the planning and management of these diseases, creating clinical reference centers and reaching statistical power for conclusive research. The objective of the study was to identify the RD data sources available in Spain in order to develop a national RDR.
assigning one point for each: availability in the AC (if the source was available in at least 12 AC), ability to identify the cases, comparability between AC (if it was a coded database), and the population covered (if it was a population-based database). Databases with three or four points were classified as essential and the rest as complementary. This score helps to identify those data sources considered as essential and prioritize them in order to ensure a homogenous starting point on national level. According to the Personal Data Protection Law,6 personal data subject to processing may be communicated to a third person only with the prior consent of the subject, except for when the transfer is authorized by law, when the transfer of personal health data is necessary for resolving an emergency, or for conducting epidemiological studies as established by national or regional health legislation.
First steps Spain is organized administratively and politically into 17 autonomous communities (AC) and two autonomous cities (Ceuta and Melilla). The Spain-RDR project is coordinated by the Institute of Rare Disease Research (IIER-ISCIII). It involves all autonomous health departments, the main Spanish Rare Disease Patient Alliance (FEDER), industry, medical societies and the Ministry of Health. Each AC has a RDR coordinator. This is a descriptive study. An electronic ad hoc questionnaire was elaborated by a working group formed by experts in health information systems to gather the RD data sources available in each AC before December 31, 2012. The questionnaire was administered to the AC RDR coordinators, together with instructions on how to fill it out. For each information source the following characteristics and the availability of specific data were assessed: type of RD recorded, type of diagnosis coding (International Classification of Diseases ‘ICD-9-CM and ICD-10’, International Classification of Primary Care ‘ICPC-2’, Systematized Nomenclature of Medicine ‘SNOMED’, ORPHANET, codification of nursing diagnoses ‘NANDA’, none, and others), clinical data (onset of symptoms, diagnosis and death dates), personal information (name, surname, personal identification number and health insurance number) and if the data transfer from each AC-RDR to the Spain-RDR was scheduled and how (anonymized or not; because under current legislation, some AC cannot transfer information with personal data to Spain-RDR). Previously, all data sources were grouped into 17 generic headings: health insurance card database, electronic hospital clinical records, electronic primary care clinical records, cancer registry, newborn screening registry (metabolic diseases), notifiable disease registry, mortality registry, chronic renal diseases registry, orphan drugs registry, birth defect registry, birth registry, compassionate drugs registry, specific information from RD projects, RD patient associations, social services sources (social work registries, assessment of disability and dependency records, social services for people with disabilities, early care teams…), educational sources (students with special needs) and other registries (oral health, biobank, asbestos workers, transplant, abortion…). Finally, each data source was classified as essential or complementary for the Spain-RDR. This classification was based on a score which took into account the following items,
Results The questionnaires were completed by each AC-RDR coordinator between April 30 and July 30, 2012. The response rate was 100% (17 AC) and variables used to distinguish essential or complementary sources were completed at 100%. A total of 280 data sources were identified. The median was 14 RD data sources per AC (range: 4e40). Essential sources represented 43.3% and included the hospital discharge Minimum Basic Data Set (MBDS), cancer registries, newborn screening records, health insurance card database, notifiable disease records, mortality registry, chronic renal disease registry and orphan drug registry. Complementary data sources included electronic primary care clinical records, birth defect registry, birth registry, compassionate drugs registry, information from specific RD projects, RD patients associations, social and educational sources. The list of data sources by groups and by AC is given in Table 1. The MBDS was the only source available in all AC, followed by the cancer registry, newborn screening registry and health insurance card database (88.2% of the AC each). Most of the AC can access personal data in these sources, which allows controlling for duplicates and cross-matching different data sources. The greatest differences in accessibility were found in the chronic renal disease registries and orphan drug registries. To date, linking the essential data sources resulted in a minimum data set consisting of: unique patient number, names, surnames, personal identification number, health insurance number, sex, date of birth, address, date of death, cause of death, RD name, ICD9-CM (code and name), ICD10 (code and name). Regarding compatibility, all clinical data sources are coded in ICD9-CM at least. The estimated number of RD that may be linked to the Spain-RDR is around 1200. The transference of non-anonymized data to IIER-ISCIII, with proper legal regulations, was allowed in 10 of the 17 AC. This report provides a comprehensive description of RD data sources available in Spain and their best possible use for the construction of the Spain-RDR. As the MBDS will be the source which will identify the largest number of cases, those RD which, given their natural history, do not require hospitalization for diagnosis or treatment will be underrepresented.7 However, this is mitigated in
Table 1 e Most common data sources available for RD registry in each autonomous community before December 31, 2012. Data sourcesa
Autonomous communities ~ a Extremadura Galicia La Madrid Murcia Navarra C.Valenciana Pais Andalucı´a Aragon Asturias Baleares Canarias Cantabria Castilla Castilla- Catalun -L LM Rioja Vasco x x x
x x
x x x
x x x
x x x
x x x
x x x
x x
x x
x x
x x
x x
x x
x x
x
x
x
x
x
x
x
x
x x x x
x
x
x
x
x
x
x
x x
x
x
x
x x
x
x x x
x x x
x x
x x
x
x
x
x
x
x
x
x
x
x
x x x
x
x x x
x
x x
x x
x
x
x
x
x x x
x x x
x x x
x
x x
x x
x
x
x
x
x
x
x
x
x x x
x
x x x
x
x x
x
p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 2 7 1 e2 7 5
Essential MBDS Cancer registry Metabolic diseases registry HICD Notifiable diseases registry Mortality registry Chronic renal diseases registry Orphan drugs registry Complementary EPCCR Birth defects registry Birth registry Compassionate drugs registry
x
x
x
Abbreviations: MBDS, Hospital Discharge Minimum Basic Data Set. HICD, Health Insurance Card Database. EPCCR, Electronic Primary Care Clinical Records. a Sorted by the score which took into account the following items, assigning one point for each: availability in the AC (if the source was available in at least 12 AC), ability to identify the cases, comparability between AC (if it was a coded database), and the population covered (if it was a population-based database).
273
274
p u b l i c h e a l t h 1 2 9 ( 2 0 1 5 ) 2 7 1 e2 7 5
part by the inclusion of cases from the cancer registry, chronic renal disease, newborn screening and orphan drug registries, which are available in many AC. One limitation of the study is that the feasibility of working with the linked data sources in terms of data quality will have to be verified in the future. The awareness of the limitations of using the ICD9-CM to identify RD are also known.1,2,8 But the project is still in its beginnings, and one of its strong points is the linking of existing databases from 17 AC, which have been widely used for specific research individually, but are rarely combined. The complexity of the RD imposes a large geographical coverage of the data collection, which implies cooperation in order to share the clinical and epidemiological experience.2,3
Future Related to the standardization of the databases, every variable with personal information will have a normalization process in order to validate the format. For example, the health insurance number must be alphanumeric with 16 characters. Also, all databases will be coded in ICD9-CM. The data will be linked using the health insurance number or name plus the last name and the date of birth. The variables of personal identification plus the ICD9-CM codes will be used to control cases duplicates. The next steps planned are auditing electronic clinical records and integrating specific health information systems and public health sources with information from other non-health related agencies.9 Many people with RD require specialized services and resources for disability. This information is complementary and it will help provide a complete picture of the burden of RD. Through the linkage of these databases and the creation of Spain-RDR, the authors hope to improve patients' access to expert care and provide useful, high quality information to decision-makers; thus contributing to improvements in the prevention, diagnosis, treatment and quality of life for the patients and their families.10
Ethical approval None required.
Funding Spanish Rare Diseases Registries Research Network (SpainRDR), Grant number IR11-RDR. Financial agency: Instituto de Salud Carlos III (ISCIII) e International Rare Diseases Research Consortium (IRDiRC).
Competing interests None declared.
Authors' information Following persons are the members of the Spain-RDR group: Josefa Marı´a Aldana Espinal, Marı´a del Amor Bueno Delgado, ndez, Antonio Gonza lez-Meneses Lo pez, Aurora Megı´as Ferna Laura Lahera Robles, Celia Salamanca Rivera, Reyes Sanz Amores (Andalucı´a). Federico Arribas, Clara Laguna Berna n). Laura Pruneda Gonza lez (Asturias). Mercedes Caf(Arago ~ o Riera, Anto nia Galme s Truyols faro Rovira, Eusebi Castan (Illes Baleares). Ione Aguiar, Patricia Carrillo, Milagrosa San s Alvarado Garcı´a, Miguel Garcı´a Ribes, tana (Canarias). Andre rrez, Luis Miguel Ruiz Ceballos (Cantabria). Gonzalo Gutie Ricardo Ortega (Castilla La Mancha). Rufino Alamo Sanz, Jesu´s nchez, Toma s Vega Alonso (Castilla Leo n). Roser Dı´az Sa , Gemma Rovira (Catalun ~ a). Carmen Francisco, Pilar Magrinya Barona Vilar, Clara Cavero Carbonell, Rosana Guaita Cala nez trava, Miguel Angel Martı´nez Beneito, Carmen Martos Jime (Comunitat Valenciana). Marı´a del Carmen Antonaya Rojas, n, M.de los Angeles Garcı´a Bazaga (Extremadura). Enrique Gala nica Alonso, Teresa Garcı´a (INGESA). Angela Almansa, Vero Carroquino, Patricia Garcı´a Primo, Manuel HensMarı´a Jose rez, Antonio Morales-Piga, Ana Villaverde (IIER). Ana Bele n Pe pez, Joaquı´n Palomar Rodrı´guez, Marta Segura Moreno Lo Aroca (Murcia). Eva Ardanaz, Esther Vicente Cemborain (Navarra). Luis Martı´nez, Ruth Martı´nez (Paı´s Vasco). Enrique mara (La Rioja). Ramalle Go
Author statements All authors participated in the design, analysis and data interpretation. All authors designed the survey, E. Barcelo developed the database and A.C. Zoni wrote the first draft of the manuscript. All authors contributed to successive drafts and approved the final version.
Acknowledgments The authors would like to thank all the people who helped make available the data, including the families affected, social workers and information technology technicians. The authors would also like to thank Dr. Vendula Blaya kova (Department of Preventive Medicine and Quality Nova ~o n, Management, General University Hospital Gregorio Maran Madrid) for providing valuable comments and helping with the translation of the article.
references
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