Semantic Medical Prescriptions – Towards Intelligent and Interoperable Medical Prescriptions. Khalili, A. & Sedaghati, B. In IEEE Seventh International Conference on Semantic Computing (ICSC 2013), pages 347-354, Sept, 2013.
doi  abstract   bibtex   
Medication errors are the most common type of medical errors in health-care domain. The use of electronic prescribing systems (e-prescribing) have resulted in significant reductions in such errors. However, dealing with the heterogeneity of available information sources is still one of the main challenges of e-prescription systems. There already exists different sources of information addressing different aspects of pharmaceutical research (e.g. chemical, pharmacological and pharmaceutical drug data, clinical trials, approved prescription drugs, drugs activity against drug targets. etc.). Handling these dynamic pieces of information within current e-prescription systems without bridging the existing pharmaceutical information islands is a cumbersome task. In this paper we present semantic medical prescriptions which are intelligent e-prescription documents enriched by dynamic drug-related meta-data thereby know about their content and the possible interactions. Semantic prescriptions provide an interoperable interface which helps patients, physicians, pharmacists, researchers, pharmaceutical and insurance companies to collaboratively improve the quality of pharmaceutical services by facilitating the process of shared decision making. In order to showcase the applicability of semantic prescriptions we present an application called Pharmer. Pharmer employs datasets such as DBpedia, Drug Bank, Daily Med and RxNorm to automatically detect the drugs in the prescriptions and to collect multidimensional data on them. We evaluate the feasibility of the Pharmer by conducting a usability evaluation and report on the quantitative and qualitative results of our survey.
@INPROCEEDINGS{Pharmer-Khalili-2013,
  author = {Khalili, Ali and Sedaghati, Bita},
  title = {Semantic Medical Prescriptions -- Towards Intelligent and Interoperable
	Medical Prescriptions},
  booktitle = {IEEE Seventh International Conference on Semantic Computing (ICSC
	2013)},
  year = {2013},
  pages = {347-354},
  month = {Sept},
  abstract = {Medication errors are the most common type of medical errors in health-care
	domain. The use of electronic prescribing systems (e-prescribing)
	have resulted in significant reductions in such errors. However,
	dealing with the heterogeneity of available information sources is
	still one of the main challenges of e-prescription systems. There
	already exists different sources of information addressing different
	aspects of pharmaceutical research (e.g. chemical, pharmacological
	and pharmaceutical drug data, clinical trials, approved prescription
	drugs, drugs activity against drug targets. etc.). Handling these
	dynamic pieces of information within current e-prescription systems
	without bridging the existing pharmaceutical information islands
	is a cumbersome task. In this paper we present semantic medical prescriptions
	which are intelligent e-prescription documents enriched by dynamic
	drug-related meta-data thereby know about their content and the possible
	interactions. Semantic prescriptions provide an interoperable interface
	which helps patients, physicians, pharmacists, researchers, pharmaceutical
	and insurance companies to collaboratively improve the quality of
	pharmaceutical services by facilitating the process of shared decision
	making. In order to showcase the applicability of semantic prescriptions
	we present an application called Pharmer. Pharmer employs datasets
	such as DBpedia, Drug Bank, Daily Med and RxNorm to automatically
	detect the drugs in the prescriptions and to collect multidimensional
	data on them. We evaluate the feasibility of the Pharmer by conducting
	a usability evaluation and report on the quantitative and qualitative
	results of our survey.},
  doi = {10.1109/ICSC.2013.66},
  keywords = {document handling;drugs;medical information systems;DBpedia dataset;Daily
	Med dataset;Drug Bank dataset;Pharmer application;RxNorm dataset;drug
	detection;dynamic drug-related meta data;e-prescription systems;electronic
	prescription systems;health care domain;intelligent e-prescription
	documents;interoperable interface;medication errors;pharmaceutical
	information islands;pharmaceutical research;semantic medical prescriptions;usability
	evaluation;Companies;Drugs;Ontologies;Resource description framework;Semantics;Semantic
	prescription;e-health;e-prescription;semantic annotation}
}
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