Prioritizing the Risk Factors Influencing the Success of Clinical Information System Projects

2008 ◽  
Vol 47 (03) ◽  
pp. 251-259 ◽  
Author(s):  
C. Sicotte ◽  
M. Jaana ◽  
D. Girouard ◽  
G. Paré
Keyword(s):  
Risk Factors ◽  
Information System ◽  
Information Systems ◽  
Information Technologies ◽  
Clinical Information System ◽  
Clinical Information ◽  
Clinical Work ◽  
Perceived Usefulness ◽  
Clinical Information Systems ◽  
Factors Influencing

Summary Objective: The aim of this study is to gain a better understanding of the risk factors influencing the success of clinical information system projects. Methods: This study addresses this issue by first reviewing the extant literature on information technology project risks, and second conducting a Delphi survey among 21 experts highly involved in clinical information system projects in Québec, Canada, a region where government have invested heavily in health information technologies in recent years. Results: Twenty-three risk factors were identified. The absence of a project champion was the factor that experts felt most deserves their attention. Lack of commitment from upper management was ranked second. Our panel of experts also confirmed the importance of a variable that has been extensively studied in information systems, namely, perceived usefulness that ranked third. Respondents ranked project ambiguity fourth. The fifth-ranked risk was associated with poor alignment between the clinical information systems’ characteristics and the organization of clinical work. The large majority of risk factors associated with the technology itself were considered less important. This finding supports the idea that technology-associated factors rarely figure among the main reasons for a project failure. Conclusions: In addition to providing a comprehensive list of risk factors and their relative importance, the study presents a major contribution by unifying the literature on information systems and medical infor - matics. Our checklist provides a basis for further research that may help practitioners identify the effective countermeasures for mitigating risks associated with the implementation of clinical information systems.

Model-based Design of Clinical Information Systems

2008 ◽  
Vol 47 (05) ◽  
pp. 399-408 ◽  
Author(s):  
J. Werner ◽  
Y. Lee ◽  
B. Malin ◽  
A. Ledeczi ◽  
J. Mathe
Keyword(s):  
Information System ◽  
Information Systems ◽  
Service Oriented Architecture ◽  
Clinical Information System ◽  
Clinical Information ◽  
Security And Privacy ◽  
Clinical Information Systems ◽  
Great Promise ◽  
Model Based ◽  
Business Process Execution

Summary Objective: The goal of this research is to provide a framework to enable the model-based development, simulation, and deployment of clinical information system prototypes with mechanisms that enforce security and privacy policies. Methods: We developed the Model-Integrated Clinical Information System (MICIS), a software toolkit that is based on model-based design techniques and highlevel modeling abstractions to represent complex clinical workflows in a service-oriented architecture paradigm. MICIS translates models into executable constructs, such as web service descriptions, business process execution language procedures, and deployment instructions. MICIS models are enriched with formal security and privacy specifications, which are enforced within the execution environment. Results: We successfully validated our design platform by modeling multiple clinical workflows and deploying them onto the execution platform. Conclusions: The model-based approach shows great promise for developing, simulating, and evolving clinical information systems with formal properties and policy restrictions.

Effectivness of Health Information System Applications: Clinical Information and Diagnosis-Treatment Systems in Turkey

2017 ◽  
Vol 5 (1) ◽  
pp. 122
Author(s):  
Assist. Prof. Dr. Demokaan DEMİREL
Keyword(s):  
Decision Making ◽  
Information System ◽  
Information Systems ◽  
Management Information System ◽  
Health Sector ◽  
Health Information System ◽  
Clinical Information ◽  
Clinical Decision ◽  
Clinical Information Systems ◽  
Management Information

The distinctive quality of the new social structure is that information becomes the only factor of production. In today's organizations, public administrators are directly responsible for applying information to administrative processes. In addition to his managerial responsibilities, a knowledge based organization requires every employee to take responsibility for achieving efficiency. This has increased the importance of information systems in the decision-making process. Information systems consist of computer and communication technology, data base management and model management and include activity processing system, management information system, decision support systems, senior management information system, expert systems and office automation systems. Information systems in the health sector aim at the management and provision of preventive and curative health services. The use of information systems in healthcare has the benefits of increasing service quality, shortening treatment processes, maximizing efficiency of the time, labour and medical devices. The use of information systems for clinical decision making and reducing medical errors in the healthcare industry dates back to the 1960s. Clinical information systems involve processing, storing and re-accessing information that supports patient care in a hospital. Clinical information systems are systems that are directly or indirectly related to patient care. These systems include electronic health/patient records, clinical decision support systems, nurse information systems, patient tracking systems, tele-medicine, case mix and smart card applications. Diagnosis-treatment systems are information-based systems used in the diagnosis and treatment of diseases. It consists of laboratory information systems, picture archiving and communication system, pharmacy information system, radiology information system, nuclear medicine information system. This study aims to evaluate the effectiveness of health information system applications in Turkey. The first part of the study focuses on the concept of information systems and the types of information systems in organization structures. In the second part, clinical information systems and applications for diagnosis-treatment systems in Turkey are examined. Finally, the study evaluates applications in the health sector qualitatively from the new organizational structure, which is formed by information systems.

scholarly journals Current Challenges and Opportunities for Better Integration of Human Factors Research with Development of Clinical Information Systems

2009 ◽  
Vol 18 (01) ◽  
pp. 48-58 ◽  
Author(s):  
J. J. Saleem ◽  
A. L. Russ ◽  
P. Sanderson ◽  
T. R. Johnson ◽  
J. Zhang ◽  
...  
Keyword(s):  
Information Systems ◽  
Human Factors ◽  
User Satisfaction ◽  
Clinical Decision Making ◽  
Clinical Information System ◽  
Healthcare Delivery ◽  
Clinical Information ◽  
Lessons Learned ◽  
Clinical Information Systems ◽  
Human Factors Research

Summary Objectives Clinical information system (CIS) developers and implementers have begun to look to other scientific disciplines for new methods, tools, and techniques to help them better understand clinicians and their organizational structures, clinical work environments, capabilities of clinical information and communications technology, and the way these structures and processes interact. The goal of this article is to help CIS researchers, developers, implementers, and evaluators better understand the methods, tools, techniques, and literature of the field of human factors. Methods We developed a framework that explains how six key human factors topics relate to the design, implementation, and evaluation of CISs. Results Using this framework we discuss the following six topics: 1) informatics and patient safety; 2) user interface design and evaluation; 3) workflow and task analysis; 4) clinical decision making and decision support; 5) distributed cognition; and 6) mental workload and situation awareness. Conclusions Integrating the methods, tools, and lessons learned from each of these six areas of human factors research early in CIS design and incorporating them iteratively during development can improve user performance, user satisfaction, and integration into clinical workflow. Ultimately, this approach will improve clinical information systems and healthcare delivery.

Building a Comprehensive Clinical Information System from Components

2003 ◽  
Vol 42 (01) ◽  
pp. 01-07 ◽  
Author(s):  
S.P. Narus ◽  
S.M. Huff ◽  
T.A. Pryor ◽  
P.J. Haug ◽  
T. Larkin ◽  
...  
Keyword(s):  
Information System ◽  
Information Systems ◽  
Clinical Information System ◽  
Clinical Information ◽  
Data Repository ◽  
Attractive Alternative ◽  
Systems Architecture ◽  
Advantages And Disadvantages ◽  
Information Systems Architecture ◽  
Almost All

Summary Objectives: To discuss the advantages and disadvantages of an interfaced approach to clinical information systems architecture. Methods: After many years of internally building almost all components of a hospital clinical information system (HELP) at Intermountain Health Care, we changed our architectural approach as we chose to encompass ambulatory as well as acute care. We now seek to interface applications from a variety of sources (including some that we build ourselves) to a clinical data repository that contains a longitudinal electronic patient record. Results: We have a total of 820 instances of interfaces to 51 different applications. We process nearly 2 million transactions per day via our interface engine and feel that the reliability of the approach is acceptable. Interface costs constitute about four percent of our total information systems budget. The clinical database currently contains records for 1.45 m patients and the response time for a query is 0.19sec. Discussion: Based upon our experience with both integrated (monolithic) and interfaced approaches, we conclude that for those with the expertise and resources to do so, the interfaced approach offers an attractive alternative to systems provided by a single vendor. We expect the advantages of this approach to increase as the costs of interfaces are reduced in the future as standards for vocabulary and messaging become increasingly mature and functional.

scholarly journals Factors Influencing User Satisfaction with Information Systems: A Systematic Review

2020 ◽  
Vol 9 ◽  
pp. 1686
Author(s):  
Leila R Kalankesh ◽  
Zahra Nasiry ◽  
Rebecca Fein ◽  
Shahla Damanabi
Keyword(s):  
Information System ◽  
Information Systems ◽  
User Satisfaction ◽  
Information Quality ◽  
Measurement Instrument ◽  
Quality System ◽  
Management Style ◽  
Perceived Usefulness ◽  
System Quality ◽  
Factors Influencing

User satisfaction has been considered as the measure of information system effectiveness success. User satisfaction is difficult to define but is considered an evaluation construct. Globally health organizations, particularly hospitals, invest a huge amount of money on information system projects. If hospital information systems (HISs) are to be successful, factors influencing or related to user satisfaction should be taken into account at the time of designing, developing or adopting such systems. The current study aimed to provide a comprehensive review of factors related to user satisfaction with information systems. The researchers systematically searched PubMed, Science Direct, and IEEE electronic databases for articles published from January 1990 to June 2016. A search strategy was developed using a combination of the following keywords:  “model,” “user satisfaction,” “information system,” “measurement,” “instrument,” and “ tool.” Reported dimensions, factors, and their possible influence on user satisfaction with information systems were extracted from the studies wherever was possible. Overall factors influencing user satisfaction with information systems can be categorized in seven dimensions: Information quality, system quality, vendor support quality, system use, perceived usefulness, user characteristics, and organizational structure& management style. If all these factors are considered properly in the process of developing, designing, implementing, or purchasing information systems, the higher user satisfaction with the system will be likely. Otherwise, it would end up with unsatisfied users that will finally contribute to the system failure. [GMJ.2020;9:e1686]

scholarly journals Barriers to the secondary use of data in critical care

2017 ◽  
Vol 19 (2) ◽  
pp. 127-131
Author(s):  
Karl Prince ◽  
Matthew Jones ◽  
Alan Blackwell ◽  
Alexander Simpson ◽  
Sallyanne Meakins ◽  
...  
Keyword(s):  
Critical Care ◽  
Information Systems ◽  
Online Survey ◽  
Clinical Information System ◽  
Clinical Information ◽  
Clinical Information Systems ◽  
Critical Care Units ◽  
Secondary Use ◽  
Use Of Data ◽  
Using Data

Purpose We explore the challenges of the secondary use of data in clinical information systems which critical care units in the National Health Service (England) are facing. Methods We conducted an online survey of critical care units in England regarding their practices in collecting and using clinical information systems and data. Results Critical care units use clinical information systems typically independently of hospital information systems and focus mainly on using data for auditing, management reporting and research. Respondents reported that extracting data from their clinical information system was difficult and that they would use stored data more if it were easier to access. Data extraction takes time and who extracts data, the training they receive and the tools they use affect the extraction and use of data. Conclusion A number of key challenges affect the secondary use of data in critical care: a lack of integration of information systems within critical care and across departments; barriers to accessing data; mismatched data tools and user requests. Data are predominantly used for reporting and research with less emphasis on using data to inform clinical practice.

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