Pub Date : 2020-07-01DOI: 10.4018/ijhisi.2020070103
T. Guimaraes, M. C. Caccia-Bava, Melissa J. Geist
This study empirically tests the relationship between hospital competition intensity and its quality, and the moderating impact of hospital culture on this relationship. An emailed questionnaire collected data from 239 American hospital CEO's to validate the measures and test the hypothesized relationships. The results corroborated the importance of competition intensity as determinant of hospital quality and the positive moderating impact of hospital organization culture as measured here. Future research should expand this model to include other potential determinants of hospital quality such as economic conditions and hospital size. Also, future research should explore other potential moderators and mediators for inclusion in a more elaborate model. While hospitals administrators cannot control the intensity of their competition, and are forced to do everything they can to improve hospital quality (including establishing a helpful organization culture), understanding how to measure these constructs and manage their relationships should be very useful.
{"title":"The Moderating Effect of Organization Culture on Competition Intensity and Hospital Quality","authors":"T. Guimaraes, M. C. Caccia-Bava, Melissa J. Geist","doi":"10.4018/ijhisi.2020070103","DOIUrl":"https://doi.org/10.4018/ijhisi.2020070103","url":null,"abstract":"This study empirically tests the relationship between hospital competition intensity and its quality, and the moderating impact of hospital culture on this relationship. An emailed questionnaire collected data from 239 American hospital CEO's to validate the measures and test the hypothesized relationships. The results corroborated the importance of competition intensity as determinant of hospital quality and the positive moderating impact of hospital organization culture as measured here. Future research should expand this model to include other potential determinants of hospital quality such as economic conditions and hospital size. Also, future research should explore other potential moderators and mediators for inclusion in a more elaborate model. While hospitals administrators cannot control the intensity of their competition, and are forced to do everything they can to improve hospital quality (including establishing a helpful organization culture), understanding how to measure these constructs and manage their relationships should be very useful.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127014187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.4018/ijhisi.2020070105
C. C. Agbo, Q. Mahmoud
Blockchain, an immutable ledger or database shared by peers in a network, is comprised of records of events or transactions that are appended chronologically. Introduced via Bitcoin to the world, blockchain is increasingly being accepted and adopted in different industries and for diverse use cases. Among key industries, health care offers several significant opportunities for applying blockchain conceptualization. Chief areas for health care blockchain applications include electronic medical records management, pharmaceutical supply chain management, biomedical research and education, remote patient monitoring, health insurance claim processing, and health data analytics. Even so, applying blockchain concepts in health care is not without challenges, including interoperability, security-privacy, scalability-speed, and stakeholders' engagement issues. While these challenges may militate against blockchain applications in health care, there are possible countermeasures and implementation techniques, which if adhered to, can reasonably contain many aspects of such challenges.
{"title":"Blockchain in Healthcare: Opportunities, Challenges, and Possible Solutions","authors":"C. C. Agbo, Q. Mahmoud","doi":"10.4018/ijhisi.2020070105","DOIUrl":"https://doi.org/10.4018/ijhisi.2020070105","url":null,"abstract":"Blockchain, an immutable ledger or database shared by peers in a network, is comprised of records of events or transactions that are appended chronologically. Introduced via Bitcoin to the world, blockchain is increasingly being accepted and adopted in different industries and for diverse use cases. Among key industries, health care offers several significant opportunities for applying blockchain conceptualization. Chief areas for health care blockchain applications include electronic medical records management, pharmaceutical supply chain management, biomedical research and education, remote patient monitoring, health insurance claim processing, and health data analytics. Even so, applying blockchain concepts in health care is not without challenges, including interoperability, security-privacy, scalability-speed, and stakeholders' engagement issues. While these challenges may militate against blockchain applications in health care, there are possible countermeasures and implementation techniques, which if adhered to, can reasonably contain many aspects of such challenges.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128034404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.4018/ijhisi.2020070101
N. Faruk, N. Surajudeen-Bakinde, A. Abdulkarim, A. Oloyede, L. Olawoyin, O. Bello, S. Popoola, Thierry Oscar Edoh
Access to quality healthcare is a major problem in Sub-Saharan Africa with a doctor-to-patient ratio as high as 1:50,000, which is far above the recommended ratio by the World Health Organization (WHO) which is 1:600. This has been aggravated by the lack of access to critical infrastructures such as the health care facilities, roads, electricity, and many other factors. Even if these infrastructures are provided, the number of medical practitioners to cater for the growing population of these countries is not sufficient. In this article, how information and communication technology (ICT) can be used to drive a sustainable health care delivery system through the introduction and promotion of Virtual Clinics and various health information systems such as mobile health and electronic health record systems into the healthcare industry in Sub-Saharan Africa is presented. Furthermore, the article suggests ways of attaining successful implementation of telemedicine applications /services and remote health care facilities in Africa.
{"title":"Rural Healthcare Delivery in Sub-Saharan Africa: An ICT-Driven Approach","authors":"N. Faruk, N. Surajudeen-Bakinde, A. Abdulkarim, A. Oloyede, L. Olawoyin, O. Bello, S. Popoola, Thierry Oscar Edoh","doi":"10.4018/ijhisi.2020070101","DOIUrl":"https://doi.org/10.4018/ijhisi.2020070101","url":null,"abstract":"Access to quality healthcare is a major problem in Sub-Saharan Africa with a doctor-to-patient ratio as high as 1:50,000, which is far above the recommended ratio by the World Health Organization (WHO) which is 1:600. This has been aggravated by the lack of access to critical infrastructures such as the health care facilities, roads, electricity, and many other factors. Even if these infrastructures are provided, the number of medical practitioners to cater for the growing population of these countries is not sufficient. In this article, how information and communication technology (ICT) can be used to drive a sustainable health care delivery system through the introduction and promotion of Virtual Clinics and various health information systems such as mobile health and electronic health record systems into the healthcare industry in Sub-Saharan Africa is presented. Furthermore, the article suggests ways of attaining successful implementation of telemedicine applications /services and remote health care facilities in Africa.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127869814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.4018/ijhisi.2020070102
Jessica Elaine Helwig, Katherine E. Bishop-Williams, L. Berrang‐Ford, S. Lwasa, D. Namanya
Health information systems (HIS) are used to manage information related to population health. The goal of this research was to conduct an evaluation of a HIS used at a hospital in south-western Uganda using participatory approaches. The evaluation structure was based on guidelines generated by the Center for Disease Control and Prevention and a series of theoretical and methodological concepts regarding participatory engagement that encouraged stakeholder participation throughout the evaluation. The primary objectives were to describe the areas of strength and limitations of the HIS, and develop potential system enhancements. Ultimately, engagement of local staff members throughout each stage of the evaluation resulted in the development of a series of recommendations considered relevant and feasible by local stakeholders. We build on these results by highlighting the value of stakeholder engagement and opportunities to apply participatory and community-based research methods and an Ecohealth framework to an HIS evaluation.
{"title":"Doing More Than Asking for Opinions: A Framework for Participation and Ecohealth in Health Information System Evaluations","authors":"Jessica Elaine Helwig, Katherine E. Bishop-Williams, L. Berrang‐Ford, S. Lwasa, D. Namanya","doi":"10.4018/ijhisi.2020070102","DOIUrl":"https://doi.org/10.4018/ijhisi.2020070102","url":null,"abstract":"Health information systems (HIS) are used to manage information related to population health. The goal of this research was to conduct an evaluation of a HIS used at a hospital in south-western Uganda using participatory approaches. The evaluation structure was based on guidelines generated by the Center for Disease Control and Prevention and a series of theoretical and methodological concepts regarding participatory engagement that encouraged stakeholder participation throughout the evaluation. The primary objectives were to describe the areas of strength and limitations of the HIS, and develop potential system enhancements. Ultimately, engagement of local staff members throughout each stage of the evaluation resulted in the development of a series of recommendations considered relevant and feasible by local stakeholders. We build on these results by highlighting the value of stakeholder engagement and opportunities to apply participatory and community-based research methods and an Ecohealth framework to an HIS evaluation.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130305808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-07-01DOI: 10.4018/ijhisi.2020070104
Urvashi Sharma, M. Sood, Emjee Puthooran, Y. Kumar
The digitization of human body, especially for treatment of diseases can generate a large volume of data. This generated medical data has a large resolution and bit depth. In the field of medical diagnosis, lossless compression techniques are widely adopted for the efficient archiving and transmission of medical images. This article presents an efficient coding solution based on a predictive coding technique. The proposed technique consists of Resolution Independent Gradient Edge Predictor16 (RIGED16) and Block Based Arithmetic Encoding (BAAE). The objective of this technique is to find universal threshold values for prediction and provide an optimum block size for encoding. The validity of the proposed technique is tested on some real images as well as standard images. The simulation results of the proposed technique are compared with some well-known and existing compression techniques. It is revealed that proposed technique gives a higher coding efficiency rate compared to other techniques.
{"title":"A Block-Based Arithmetic Entropy Encoding Scheme for Medical Images","authors":"Urvashi Sharma, M. Sood, Emjee Puthooran, Y. Kumar","doi":"10.4018/ijhisi.2020070104","DOIUrl":"https://doi.org/10.4018/ijhisi.2020070104","url":null,"abstract":"The digitization of human body, especially for treatment of diseases can generate a large volume of data. This generated medical data has a large resolution and bit depth. In the field of medical diagnosis, lossless compression techniques are widely adopted for the efficient archiving and transmission of medical images. This article presents an efficient coding solution based on a predictive coding technique. The proposed technique consists of Resolution Independent Gradient Edge Predictor16 (RIGED16) and Block Based Arithmetic Encoding (BAAE). The objective of this technique is to find universal threshold values for prediction and provide an optimum block size for encoding. The validity of the proposed technique is tested on some real images as well as standard images. The simulation results of the proposed technique are compared with some well-known and existing compression techniques. It is revealed that proposed technique gives a higher coding efficiency rate compared to other techniques.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121217132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-01DOI: 10.4018/ijhisi.2020040103
Gagandeep Kaur, Abhinav Hans, Anshu Vashisth
The proposed research work is for the early diagnosis of the inflammatory disease named Osgood-Schlatter disease of the knee joint. As the system deals with fuzzy values, a MATLAB (R2013a) fuzzy logic controller is used for the implementation. The knowledge engineering phase is done with the help of an orthopedic expert. Four symptoms are used for diagnosing the severity of disease. Also, this diagnosis provides the treatment for the respective level of disease. Data collection is completed by the survey method and various defuzzification methods are used to check the accuracy. The proposed system was tested on 25 patients.
{"title":"A Fuzzy Rule Based Expert System for Early Diagnosis of Osgood Schlatter Disease of Knee Joint","authors":"Gagandeep Kaur, Abhinav Hans, Anshu Vashisth","doi":"10.4018/ijhisi.2020040103","DOIUrl":"https://doi.org/10.4018/ijhisi.2020040103","url":null,"abstract":"The proposed research work is for the early diagnosis of the inflammatory disease named Osgood-Schlatter disease of the knee joint. As the system deals with fuzzy values, a MATLAB (R2013a) fuzzy logic controller is used for the implementation. The knowledge engineering phase is done with the help of an orthopedic expert. Four symptoms are used for diagnosing the severity of disease. Also, this diagnosis provides the treatment for the respective level of disease. Data collection is completed by the survey method and various defuzzification methods are used to check the accuracy. The proposed system was tested on 25 patients.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121205729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-01DOI: 10.4018/ijhisi.2020040101
S. Singh, Anjali Goyal
Cervical cancer is second most prevailing cancer in women all over the world and the Pap smear is one of the most popular techniques used to diagnosis cervical cancer at an early stage. Developing countries like India has to face the challenges in order to handle more cases day by day. In this article, various online and offline machine learning algorithms has been applied on benchmarked data sets to detect cervical cancer. This article also addresses the problem of segmentation with hybrid techniques and optimizes the number of features using extra tree classifiers. Accuracy, precision score, recall score, and F1 score are increasing in the proportion of data for training and attained up to 100% by some algorithms. Algorithm like logistic regression with L1 regularization has an accuracy of 100%, but it is too much costly in terms of CPU time in comparison to some of the algorithms which obtain 99% accuracy with less CPU time. The key finding in this article is the selection of the best machine learning algorithm with the highest accuracy. Cost effectiveness in terms of CPU time is also analysed.
{"title":"Performance Analysis of Machine Learning Algorithms for Cervical Cancer Detection","authors":"S. Singh, Anjali Goyal","doi":"10.4018/ijhisi.2020040101","DOIUrl":"https://doi.org/10.4018/ijhisi.2020040101","url":null,"abstract":"Cervical cancer is second most prevailing cancer in women all over the world and the Pap smear is one of the most popular techniques used to diagnosis cervical cancer at an early stage. Developing countries like India has to face the challenges in order to handle more cases day by day. In this article, various online and offline machine learning algorithms has been applied on benchmarked data sets to detect cervical cancer. This article also addresses the problem of segmentation with hybrid techniques and optimizes the number of features using extra tree classifiers. Accuracy, precision score, recall score, and F1 score are increasing in the proportion of data for training and attained up to 100% by some algorithms. Algorithm like logistic regression with L1 regularization has an accuracy of 100%, but it is too much costly in terms of CPU time in comparison to some of the algorithms which obtain 99% accuracy with less CPU time. The key finding in this article is the selection of the best machine learning algorithm with the highest accuracy. Cost effectiveness in terms of CPU time is also analysed.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128016836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-01DOI: 10.4018/ijhisi.2020040102
R. Kaur, Kamaldeep Kaur, A. Khamparia, Divya Anand
Artificial intelligence is emerging as a persuasive tool in the field of medical science. This research work also primarily focuses on the development of a tool to automate the diagnosis of inflammatory diseases of the knee joint. The tool will also assist the physicians and medical practitioners for diagnosis. The diseases considered for this research under inflammatory category are osteoarthritis, rheumatoid arthritis and osteonecrosis. A five-layer adaptive neuro-fuzzy (ANFIS) architecture was used to model the system. The ANFIS system works by mapping input parameters to the input membership functions, input membership functions are mapped to the rules generated by the ANFIS model which are further mapped to the output membership function. A comparative performance analysis of fuzzy system and ANFIS system is also done and results generated shows that the ANFIS system outperformed fuzzy system in terms of testing accuracy, sensitivity and specificity.
{"title":"An Improved and Adaptive Approach in ANFIS to Predict Knee Diseases","authors":"R. Kaur, Kamaldeep Kaur, A. Khamparia, Divya Anand","doi":"10.4018/ijhisi.2020040102","DOIUrl":"https://doi.org/10.4018/ijhisi.2020040102","url":null,"abstract":"Artificial intelligence is emerging as a persuasive tool in the field of medical science. This research work also primarily focuses on the development of a tool to automate the diagnosis of inflammatory diseases of the knee joint. The tool will also assist the physicians and medical practitioners for diagnosis. The diseases considered for this research under inflammatory category are osteoarthritis, rheumatoid arthritis and osteonecrosis. A five-layer adaptive neuro-fuzzy (ANFIS) architecture was used to model the system. The ANFIS system works by mapping input parameters to the input membership functions, input membership functions are mapped to the rules generated by the ANFIS model which are further mapped to the output membership function. A comparative performance analysis of fuzzy system and ANFIS system is also done and results generated shows that the ANFIS system outperformed fuzzy system in terms of testing accuracy, sensitivity and specificity.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"373 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116624722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-04-01DOI: 10.4018/ijhisi.2020040104
B. Ram, M. Rashid, Kamlesh Lakhwani, Shibi S. Kumar
Agriculture plays a vital role in India's economy. 44% of the employment in India is engaged in agriculture and allied activities and it also contributes 17% of the gross value added. As most of the country's people are in the agricultural sector and out of them only a few are literate about how to protect their cultivation ultimately gives rise to severe problems like a low economy in the sector and starvation for the nation. The job of this research is to help the farmers to save crops from disease. The authors came with the thought of combining a pattern recognition method and an image processing technique. The system allows a farmer to follow a particular pattern of growing crops so that threats will be analyzed earlier. Combining this with the power of Internet of Things, the authors can automate the process without the need for human resources. This research can ultimately make the agriculture process faster and farmers can cultivate more in a less amount of time.
{"title":"Health Detection of Wheat Crop Using Pattern Recognition and Image Processing","authors":"B. Ram, M. Rashid, Kamlesh Lakhwani, Shibi S. Kumar","doi":"10.4018/ijhisi.2020040104","DOIUrl":"https://doi.org/10.4018/ijhisi.2020040104","url":null,"abstract":"Agriculture plays a vital role in India's economy. 44% of the employment in India is engaged in agriculture and allied activities and it also contributes 17% of the gross value added. As most of the country's people are in the agricultural sector and out of them only a few are literate about how to protect their cultivation ultimately gives rise to severe problems like a low economy in the sector and starvation for the nation. The job of this research is to help the farmers to save crops from disease. The authors came with the thought of combining a pattern recognition method and an image processing technique. The system allows a farmer to follow a particular pattern of growing crops so that threats will be analyzed earlier. Combining this with the power of Internet of Things, the authors can automate the process without the need for human resources. This research can ultimately make the agriculture process faster and farmers can cultivate more in a less amount of time.","PeriodicalId":101861,"journal":{"name":"Int. J. Heal. Inf. Syst. Informatics","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133954061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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