title: Accelerating the development of an information ecosystem in health care, by stimulating the growth of safe intermediate processing of health information (IPHI).
abstract: Health care, in common with many other industries, is generating large amounts of routine data, data that are challenging to process, analyse or curate, so-called 'big data'. A challenge for health informatics is to make sense of these data. Part of the answer will come from the development of ontologies that support the use of heterogeneous data sources and the development of intermediate processors of health information (IPHI). IPHI will sit between the generators of health data and information, often the providers of health care, and the managers, commissioners, policy makers, researchers, and the pharmaceutical and other healthcare industries. They will create a health ecosystem by processing data in a way that stimulates improved data quality and potentially healthcare delivery by providers of health care, and by providing greater insights to legitimate users of data. Exemplars are provided of how a health ecosystem might be encouraged and developed to promote patient safety and more efficient health care. These are in the areas of how to integrate data around the unsafe use of alcohol and to explore vaccine safety. A challenge for IPHI is how to ensure that their processing of data is valid, safe and maintains privacy. Development of the healthcare ecosystem and IPHI should be actively encouraged internationally. Governments, regulators and providers of health care should facilitate access to health data and the use of national and international comparisons to monitor standards. However, most importantly, they should pilot new methods of improving quality and safety through the intermediate processing of health data.
authors.affiliation: Department of Computing, University of Surrey, Guildford, UK.
authors.forename: Harshana
authors.initials: H
authors.lastname: Liyanage
authors.forename: Siaw-Teng
authors.initials: ST
authors.lastname: Liaw
authors.forename: Simon
authors.initials: S
authors.lastname: de Lusignan
mesh_terms: D000428:Alcohol Drinking / Q000009:adverse effects / Q000453:epidemiology; D003362:Cost-Benefit Analysis; D003627:Data Interpretation, Statistical; D057225:Data Mining / Q000379:methods / Q000639:trends; D006801:Humans; D007252:Influenza Vaccines / Q000600:supply & distribution / Q000627:therapeutic use; D007251:Influenza, Human / Q000453:epidemiology / Q000517:prevention & control; D033181:Information Dissemination / Q000379:methods*; D020407:Internet / Q000639:trends; D058873:Pandemics; D011159:Population Surveillance / Q000379:methods*; D011635:Public Health Administration / Q000379:methods / Q000592:standards* / Q000639:trends; D040442:Public Health Informatics / Q000592:standards* / Q000639:trends
chemical_list: D007252:Influenza Vaccines