Case study

Purpose – In recent years, many development projects of the medical systems encounter difficulties and eventually fail. Failure is often due to very complicated and changeable medical procedures and the inconsistent understanding between system stakeholders, especially the healthcare providers, and information technology staff. Many research results also indicate that poor communication easily results in negative consequences during the implementation of the medical information system. To effectively overcome this obstacle, the purpose of this paper is to propose an enhanced Delphi method to assist in reaching consensus during the software development with some additional steps. Design/methodology/approach – As an alternative to the traditional way to elicit pertinent feedback from respondents, the enhanced Delphi method stresses the systematic, flexible, and cyclic stages to construct a questionnaire with viewpoints from different types of panelists and a self-assessment procedure as a validating step to measure the improvements in the system implementation. Findings – The better communication between the members of project team does increase the comprehensive assessment of a project. Originality/value – Based on a practical case, the enhanced Delphi method really demonstrates good performance and effectiveness.

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KCEBSA

Journal of Enterprise Information Management ◽

10.1108/jeim-12-2015-0123 ◽

2017 ◽

Vol 30 (4) ◽

pp. 625-643 ◽

Cited By ~ 1

Author(s):

Shu-Chen Kao ◽

ChienHsing Wu ◽

Chieh-Lin Huang

Keyword(s):

Balanced Scorecard ◽

Delphi Method ◽

Evaluation Model ◽

Practical Case ◽

Analytic Hierarchy ◽

Qualitative Variable ◽

Content Type ◽

Knowledge Community ◽

Internal Process ◽

Community Evaluation

Purpose From the academic perspective, there are challenges to develop an appropriate evaluation model that is linked to both theoretical and professional viewpoints for online knowledge community evaluation (KCE). These challenges are mainly the evaluation principles, the method used to derive the evaluation items, and the techniques used to determine the importance of evaluation items to formulate the evaluation model. The purpose of this paper is to propose and develop an online KCE model by considering the Delphi method, analytic hierarchy process (AHP) technique, and balanced scorecard (BSC) approach that contains facets of member, strategy, learning and growth, and internal process. Design/methodology/approach The qualitative study was used to develop the KCE model. The BSC approach was used to construct the facets of evaluation model. The Delphi method and AHP technique were utilized to derive structural measure items and to determine item weight in the development process, respectively. An illustrated practical case was used to demonstrate the proposed KCE model. Findings The member facet is perceived the most important facet while the internal process the least, implying that the invited participants perceive that community members, as represented by member satisfaction and loyalty, are the most important factors. In the knowledge management process sub-facet, knowledge creation obtains the highest weight compared with knowledge acquisition, dissemination, and utilization. Data analysis results based on 822 survey samples for the demonstrated Yahoo!Kimo Knowledge+ case are obtained. Findings and implications are also addressed. Originality/value Unlike the exclusively quantitative approach, the proposed KCE model balances both qualitative and quantitative approaches. First, it performed a face-to-face collaboration based on the Delphi method to deal with the unstructured cognition, opinions, and comments of the invited participants. Second, it developed an evaluation model based on the consensus of the invited participants by using the AHP technique in which the perceived importance of measure item to their immediate super item (qualitative variable) is transformed into number (quantitative variable).

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Differentially Private Medical Texts Generation Using Generative Neural Networks

ACM Transactions on Computing for Healthcare ◽

10.1145/3469035 ◽

2022 ◽

Vol 3 (1) ◽

pp. 1-27

Author(s):

Md Momin Al Aziz ◽

Tanbir Ahmed ◽

Tasnia Faequa ◽

Xiaoqian Jiang ◽

Yiyu Yao ◽

...

Keyword(s):

Data Science ◽

Medical Information ◽

Healthcare Providers ◽

Well Being ◽

Original Text ◽

Sensitive Information ◽

Classification Problems ◽

Medical Texts ◽

Health Records ◽

Content Type

Technological advancements in data science have offered us affordable storage and efficient algorithms to query a large volume of data. Our health records are a significant part of this data, which is pivotal for healthcare providers and can be utilized in our well-being. The clinical note in electronic health records is one such category that collects a patient’s complete medical information during different timesteps of patient care available in the form of free-texts. Thus, these unstructured textual notes contain events from a patient’s admission to discharge, which can prove to be significant for future medical decisions. However, since these texts also contain sensitive information about the patient and the attending medical professionals, such notes cannot be shared publicly. This privacy issue has thwarted timely discoveries on this plethora of untapped information. Therefore, in this work, we intend to generate synthetic medical texts from a private or sanitized (de-identified) clinical text corpus and analyze their utility rigorously in different metrics and levels. Experimental results promote the applicability of our generated data as it achieves more than 80\% accuracy in different pragmatic classification problems and matches (or outperforms) the original text data.

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Cost-sensitive learning in random forest for dialysis monthly program adequacy estimation: practical case

Informatization and communication ◽

10.34219/2078-8320-2020-11-4-113-119 ◽

2020 ◽

Vol 4 ◽

pp. 113-119

Author(s):

Irina Lakman ◽

◽

Ruslan Akhmetvaleev ◽

Anastasiya Padukova ◽

Viktor Timoshin ◽

...

Keyword(s):

Random Forest ◽

Medical Information ◽

Estimation Algorithm ◽

Medical Information System ◽

Gradient Boosting ◽

Practical Case ◽

Learning Technology ◽

Type I ◽

Cost Sensitive Learning ◽

Boosting Method

The research presented in this article is aimed to solve the case of imbalanced dataset, which appears to be a problem in the process of constructing a mathematical model for estimation of the adequacy of a monthly dialysis program for patients with a diagnosis of chronic renal failure treatment. The research is based on a dataset collected using the medical information system «Lexema-Medicine» deployed in the network of hemodialysis clinics «Hemodialysis Laboratory» and consists of 27,829 datapoints representing a monthly dialysis in the form feature vectors. The solution demonstrated in the work is based on the application of the random forest algorithm, improved by the gradient boosting method and the costsensitive learning technology. This solution allows you to significantly reduce the value of the miss rate, while not changing the monthly dialysis program adequacy estimation algorithm accuracy by statistically significant value. As a result of machine learning procedures and techniques implement, such as gradient boosting and cost-sensitive learning, an optimal ratio was obtained between the smallest type I error and the accuracy of the dialysis program adequacy classification algorithm.

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Algorithm of ensuring confidential data security of the cloud medical information system

E3S Web of Conferences ◽

10.1051/e3sconf/202022403023 ◽

2020 ◽

Vol 224 ◽

pp. 03023

Author(s):

L Babenko ◽

A Shumilin ◽

D Alekseev

Keyword(s):

Information System ◽

Data Streams ◽

Medical Information ◽

Medical Information System ◽

Cloud Platform ◽

Medical Systems ◽

Protection Method ◽

Confidential Data ◽

System Data ◽

Increase Productivity

The objectives of the study are to develop and assess the effectiveness of the structure of a cloud platform for storing, processing and organizing medical data, determining a method of protection, in particular, ensuring confidentiality when transferring and storing examination results. The proposed method for protecting a medical information system involves the use of an original DICOM file and subsequently a converted PNG image, which is subjected to a pixel encryption algorithm. An algorithm based on chaos theory is used to encrypt the image. The capabilities of chaos systems can significantly increase productivity. Hierarchical division of data streams into levels and standardization of data transmission protocols, as well as their storage formats, allow to form a universal, flexible and reliable medical information system. The proposed architecture has the ability to integrate into existing medical systems. In the course of the work, it was found that the considered protection method is an effective way to ensure the confidentiality of medical system data.

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A decision-support approach under uncertainty for evaluating reverse logistics capabilities of healthcare providers in Iran

Journal of Enterprise Information Management ◽

10.1108/jeim-09-2019-0299 ◽

2020 ◽

Vol 33 (5) ◽

pp. 991-1022

Author(s):

Amir Karbassi Yazdi ◽

Peter Fernandes Wanke ◽

Thomas Hanne ◽

Eleonora Bottani

Keyword(s):

Delphi Method ◽

Reverse Logistics ◽

Success Factors ◽

Healthcare Providers ◽

Manufacturing Companies ◽

Content Type ◽

Critical Success ◽

Three Phase ◽

Logistics Capabilities ◽

Best Worst Method

PurposeThis paper aims to assess and prioritize manufacturing companies in the healthcare industry based on critical success factors (CSFs) of their reverse logistics (RL). The research involves seven medical device companies located in the Tehran Province, Iran.Design/methodology/approachTo identify and prioritize companies based on CSFs of RL, the study proposes a three-phase decision-making framework that integrates the Delphi method, the best-worst method (BWM) and the Additive Ratio Assessment (ARAS) method with Z-numbers. The weights required for this method are obtained by a variant of the BWM based on Z-numbers, denoted as Z-numbers Best-Worst Method, or ZBWM. Since decision-makers face an uncertain environment, Z-numbers, which are a kind of fuzzy numbers, are applied.FindingsFirst, after customizing CSFs by the Delphi method and obtaining 15 CSFs of RL, these are ranked by the hybrid BWM-ARAS method with Z-numbers. Results reveal which company appears to perform best with respect to their RL implementations. Based on this result, healthcare device companies should choose the highest priority company based on the selected RL CSFs and results from using the BWM-ARAS method with Z-numbers.Originality/valueThe contribution of this paper is using a hybrid ARAS-BWM method based on Z-numbers. Each of these methods has some merits compared to other similar methods. The combination of these methods contributes a new approach for prioritizing companies based on RL CSFs with high accuracy and reliability.

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Current Status of a Medical Information System

Methods of Information in Medicine ◽

10.1055/s-0038-1636005 ◽

1970 ◽

Vol 09 (03) ◽

pp. 149-160 ◽

Cited By ~ 1

Author(s):

E. Van Brunt ◽

L. S. Davis ◽

J. F. Terdiman ◽

S. Singer ◽

E. Besag ◽

...

Keyword(s):

Information System ◽

Medical Records ◽

Medical Information ◽

Clinical Laboratory ◽

Development Program ◽

Medical Data ◽

Direct Access ◽

Medical Information System ◽

Current Status ◽

Central System

A pilot medical information system is being implemented and currently is providing services for limited categories of patient data. In one year, physicians’ diagnoses for 500,000 office visits, 300,000 drug prescriptions for outpatients, one million clinical laboratory tests, and 60,000 multiphasic screening examinations are being stored in and retrieved from integrated, direct access, patient computer medical records.This medical information system is a part of a long-term research and development program. Its major objective is the development of a multifacility computer-based system which will support eventually the medical data requirements of a population of one million persons and one thousand physicians. The strategy employed provides for modular development. The central system, the computer-stored medical records which are therein maintained, and a satellite pilot medical data system in one medical facility are described.

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Coordinating Medical Literature with Patient Care

Methods of Information in Medicine ◽

10.1055/s-0038-1636598 ◽

1977 ◽

Vol 16 (04) ◽

pp. 234-240 ◽

Cited By ~ 1

Author(s):

Joann Gustafson ◽

J. Nelson ◽

Ann Buller

Keyword(s):

Health Care ◽

Medical Staff ◽

Medical Information ◽

Medical Literature ◽

Medical Information System ◽

Staff Members ◽

Information Displays ◽

Medical Displays ◽

Computerized Medical Information ◽

The Given

The contribution of a special library project to a computerized problem-oriented medical information system (PROMIS) is discussed. Medical information displays developed by the PROMIS medical staff are accessible to the health care provider via touch screen cathode terminals. Under PROMIS, members of the library project developed two information services, one concerned with the initial building of the medical displays and the other with the updating of this information. Information from 88 medical journals is disseminated to physicians involved in the building of the medical displays. Articles meeting predetermined selection criteria are abstracted and the abstracts are made available by direct selective dissemination or via a problem-oriented abstract file. The updating service involves comparing the information contained in the selected articles with the computerized medical displays on the given topic. Discrepancies are brought to the attention of PROMIS medical staff members who evaluate the information and make appropriate changes in the displays. Thus a feedback loop is maintained which assures the completeness, accuracy, and currency of the computerized medical information. The development of this library project and its interface with the computerized health care system thus attempts to deal with the problems in the generation, validation, dissemination, and application of medical literature.

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