Abstract-The healthcare system is a knowledge driven industry which consists of vast and growing volumes of narrative information obtained from discharge summaries/reports, physicians case notes, pathologists as well as radiologists reports. This information is usually stored in unstructured and non-standardized formats in electronic healthcare systems which make it difficult for the systems to understand the information contents of the narrative information. Thus, the access to valuable and meaningful healthcare information for decision making is a challenge. Nevertheless, Natural Language Processing (NLP) techniques have been used to structure narrative information in healthcare. Thus, NLP techniques have the capability to capture unstructured healthcare information, analyze its grammatical structure, determine the meaning of the information and translate the information so that it can be easily understood by the electronic healthcare systems. Consequently, NLP techniques reduce cost as well as improve the quality of healthcare. It is therefore against this background that this paper reviews the NLP techniques used in healthcare, their applications as well as their limitations.
The healthcare domain is a complex domain which lacks a unified terminological set, most especially in clinical cases. As a result of this, the messaging standards employed in the healthcare domain use different terms for the same concept which often results in clinical misinterpretation, knowledge mismanagement, misdiagnosis of the patient's illness or even death. Consequently, the healthcare system is characterized by high error rate and semantic heterogeneity. A lot of efforts have been made to resolve this problem through the use of standards, clinical terminologies, web services as well as the use of achetype. However, these solutions have proved unsuccessful in resolving semantic heterogeneity in healthcare. Ontologies have also been developed to resolve this problem by making explicit the meaning of terms used in healthcare. Ontologies provide a source of shared and precisely defined terms, resulting in interoperability by knowledge sharing and reuse. Unfortunately, the variety of ways that the healthcare domain is conceptualized results in the creation of different ontologies with contradicting or overlapping parts. Thus, the available ontologies also introduce semantic heterogeneity to this domain. An effective solution to this problem is the introduction of methods for finding matches among the various components of ontologies in healthcare in order to facilitate semantic interoperability. Therefore, this paper aims at examining the various attempts for achieving semantic interoperability in healthcare and also motivates the critical needs for ontology matching in healthcare systems.
The healthcare domain requires the seamless, secured and meaningful exchange of health related information for effective and efficient patient care. These information are highly sensitive and they are meant to be highly confidential. However, health related information are usually distributed across several heterogeneous and autonomous healthcare systems which makes the interoperability process prone to abuse, medical fraud, inappropriate disclosure of patients' information for secondary purposes by unauthorized persons and misuse. The effects of inadequate security and privacy in healthcare include monetary penalties, loss of revenue, damage to the healthcare system reputation, risk of receiving less information for optimum care, decreased quality of patients' care as well as threat to patients' lives. Consequently, effective information protection within the healthcare domain is highly significant. Hence, this paper examines the security and privacy policies that safeguard sensitive and confidential information in healthcare systems during the exchange and use of vital health information. The paper also proposes a security based framework that seeks to mitigate security risks in healthcare, and thus protect the integrity, confidentiality, and access to health related information. General TermsInteroperability, security, privacy.
Abstract-Interoperability of health related information is one of the agendas of many counties in the world, with no exception to Nigeria and other developing countries. This is because healthcare costs are rising exponentially. Ho wever, interoperability of health related informat ion seem largely unattainable in Nigeria due to reluctance to change fro m the traditional paper based healthcare system to the use of e-health systems, inadequate ICT infrastructure, poor utilization of the available ICT resources, erratic power supply, increased burden of underdevelopment, poverty, political instability, shortage of educational capacity in Nigeria rural and urban healthcare centers, low level of ICT awareness, poor maintenance culture as well as corruption. Consequently, the healthcare system in Nigeria is saddled with h igh cost, high rate of d isease outbreak driven by HIV/AIDs, malaria and other infectious diseases which results in a h igh rate of mortality. Nevertheless, the urgent need to meaningfully exchange safe and reliab le health informat ion is a key priority to the healthcare system in Nigeria as the qualities of patients' care depend majorly on the timely acquisition, processing and retrieval of data related to the patient. Thus, this paper attempts to unravel the factors hindering interoperability in the Nigeria healthcare system and suggests ways of making total interoperability a reality in Nigeria healthcare system as well as other developing countries.
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