Searching for Answers on a Clinical Information System

1995 ◽  
Vol 34 (01/02) ◽  
pp. 79-84 ◽  
Author(s):  
C. Safran

Abstract:We examined observational data on the use of a clinical computing system in an effort to develop an empirical model of clinicians’ information needs. Clinicians turn to information systems most often to review the results of diagnostic studies. After that clinicians turn to information systems most often for communication. Bibliographic retrieval is the third most frequent reason for use, but is an order of magnitude less frequent than either results inquiry or electronic mail. Secondary retrieval of aggregate data from a clinical database is two orders of magnitude less common than primary retrieval. In a study at our hospital, clinicians gained access to an information resource during 16% of all general medical visits of patients with human immunodeficiency virus (HIV) infection while the patient was present. Insofar as our narrow focus on the primary care of HIV infection models the larger context of clinical medicine, clinicians are most often looking at information relating to therapeutics. Whatever knowledge structures are adopted, they must accommodate this observed need for therapeutic information.

2008 ◽  
Vol 47 (03) ◽  
pp. 251-259 ◽  
Author(s):  
C. Sicotte ◽  
M. Jaana ◽  
D. Girouard ◽  
G. Paré

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.


2009 ◽  
Vol 18 (01) ◽  
pp. 48-58 ◽  
Author(s):  
J. J. Saleem ◽  
A. L. Russ ◽  
P. Sanderson ◽  
T. R. Johnson ◽  
J. Zhang ◽  
...  

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.


2008 ◽  
Vol 47 (05) ◽  
pp. 399-408 ◽  
Author(s):  
J. Werner ◽  
Y. Lee ◽  
B. Malin ◽  
A. Ledeczi ◽  
J. Mathe

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.


1999 ◽  
Vol 38 (04/05) ◽  
pp. 298-302 ◽  
Author(s):  
M. Joubert ◽  
D. Fieschi ◽  
M. Fieschi ◽  
P. Staccini

AbstractWithin a hospital, the moving of medical information systems from retrospective data-gathering methods to prospective clinical information systems raises the question of the confidentiality of patient data. A method of improving the traditional matrix model usually used to achieve access controls is described. The event-driven model refers to the way a security system ensures that a given user has a valid »need-to« relationship to a given patient. Events are defined as the occurrence of specific data that trigger the creation or the updating of the relationship between the identity of a user and the identity of a patient (e. g., admission, discharge, transfer, prescription, and report). The creation and the deletion of the relationships between users and patients are based on numerous repositories and working lists of patients. This implementation requires an organization of the hospital activities which is able to manage, in a real-time manner, those repositories as closely as possible to the steps occurring during the patient’s care process. Although this approach seems to reasonably fit the dynamic of the care process, it adds significant organizational constraints.


2003 ◽  
Vol 42 (01) ◽  
pp. 01-07 ◽  
Author(s):  
S.P. Narus ◽  
S.M. Huff ◽  
T.A. Pryor ◽  
P.J. Haug ◽  
T. Larkin ◽  
...  

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.


2017 ◽  
Vol 19 (2) ◽  
pp. 127-131
Author(s):  
Karl Prince ◽  
Matthew Jones ◽  
Alan Blackwell ◽  
Alexander Simpson ◽  
Sallyanne Meakins ◽  
...  

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.


2010 ◽  
Vol 36 (2) ◽  
pp. 437-450 ◽  
Author(s):  
Georgios Konstantinidis ◽  
George C. Anastassopoulos ◽  
Alexandros S. Karakos ◽  
Emmanouil Anagnostou ◽  
Vasileios Danielides

Author(s):  
David Youens ◽  
Rachael Moorin ◽  
Amy Harrison ◽  
Richard Varhol ◽  
Suzanne Robinson ◽  
...  

General practice is often a patient’s first point of contact with the health system and the gateway to specialist services. In Australia different aspects of the health system are managed by the Commonwealth Government and individual state/territory governments. Although there is a long history of research using administrative data in Australia, this split in the management and funding of services has hindered whole-system research. Additionally, the administrative data typically available for research are often collected for reimbursement purposes and lack clinical information. General practices collect a range of patient information including diagnoses, medications prescribed, results of pathology tests ordered and so on. Practices are increasingly using clinical information systems and data extraction tools to make use of this information. This paper describes approaches used on several research projects to access clinical, as opposed to administrative, general practice data which to date has seen little use as a resource for research. This information was accessed in three ways. The first was by working directly with practices to access clinical and management data to support research. The second involved accessing general practice data through collaboration with Primary Health Networks, recently established in Australia to increase the efficiency and effectiveness of health services for patients. The third was via NPS MedicineWise’s MedicineInsight program, which collects data from consenting practices across Australia and makes these data available to researchers. We describe each approach including data access requirements and the advantages and challenges of each method. All approaches provide the opportunity to better understand data previously unavailable for research in Australia. The challenge of linking general practice data to other sources, currently being explored for general practice data, is discussed. Finally, we describe some general practice data collections used for research internationally and how these compare to collections available in Australia. Keywords: General practice; administrative data; big data, health information systems, medical records systems


1964 ◽  
Vol 3 (02) ◽  
pp. 45-50 ◽  
Author(s):  
D. Yoder ◽  
R. Swearingen ◽  
E. Schenthal ◽  
W. Sweeney ◽  
J. Nettleton

An automated clinical record system must have the following characteristics: as far as the physician is concerned it must operate in natural language on standard sized paper; it must be able to accept information from the physician at a time when he is oriented to clinical terminology and a clinical mode of thinking; it must have an output which is clinically useful for the care and management of a patient; each item of information must be addressable so that it may act as an index for scientific information retrieval; it must be capable of accepting quantative and natural language information.Clinical information constitutes a mathematical set, only a few members of which are applicable to any particular clinical situation, and to which new members are constantly being added. The members of this set are seldom mutually exclusive. An acceptable system which is capable of processing this type of information has been designed utilizing the concepts of self-encoding forms and variable-field, variable-length records. Applications of these principles will expedite hospital automation, the establishment of drug evaluation information systems, and of regional and nationwide medical record systems.


1987 ◽  
Vol 26 (04) ◽  
pp. 189-194
Author(s):  
S. S. El-Gamal

SummaryModern information technology offers new opportunities for the storage and manipulation of hospital information. A computer-based hospital information system, dedicated to urology and nephrology, was designed and developed in our center. It involves in principle the employment of a program that allows the analysis of non-restricted, non-codified texts for the retrieval and processing of clinical data and its operation by non-computer-specialized hospital staff.This Hospital Information System now plays a vital role in the efficient provision of a good quality service and is used in daily routine and research work in this hospital. This paper describes this specialized Hospital Information System.


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