Health information systems (HISs) hold the promise to transform health care; however, their adoption is challenged. We have developed the Clinical Adoption Meta-Model (CAMM) to help describe processes and possible challenges with clinical adoption. The CAMM, developed through an action research study to evaluate a provincial HIS, is a temporal model with four dimensions: availability, use, behaviour changes, and outcome changes. Seven CAMM archetypes are described, illustrating classic trajectories of adoption of HISs over time. Each archetype includes an example from the literature. The CAMM and its archetypes can support HIS implementers, evaluators, learners, and researchers.
Health information systems; Adoption model
Record linkage techniques are widely used to enable health researchers to gain event based longitudinal information for entire populations. The task of record linkage is increasingly being undertaken by specialised linkage units (SLUs). In addition to the complexity of undertaking probabilistic record linkage, these units face additional technical challenges in providing record linkage ‘as a service’ for research. The extent of this functionality, and approaches to solving these issues, has had little focus in the record linkage literature. Few, if any, of the record linkage packages or systems currently used by SLUs include the full range of functions required.
This paper identifies and discusses some of the functions that are required or undertaken by SLUs in the provision of record linkage services. These include managing routine, on-going linkage; storing and handling changing data; handling different linkage scenarios; accommodating ever increasing datasets. Automated linkage processes are one way of ensuring consistency of results and scalability of service.
Alternative solutions to some of these challenges are presented. By maintaining a full history of links, and storing pairwise information, many of the challenges around handling ‘open’ records, and providing automated managed extractions are solved. A number of these solutions were implemented as part of the development of the National Linkage System (NLS) by the Centre for Data Linkage (part of the Population Health Research Network) in Australia.
The demand for, and complexity of, linkage services is growing. This presents as a challenge to SLUs as they seek to service the varying needs of dozens of research projects annually. Linkage units need to be both flexible and scalable to meet this demand. It is hoped the solutions presented here can help mitigate these difficulties.
Medical record linkage; Automatic data processing; Medical informatics computing
With the rapid development of “-omic” technologies, an increasing number of purported biomarkers have been identified for cancer and other diseases. The process of identifying those that are most promising and validating them for use at the population level for prevention and early detection is a critical next step in achieving significant health benefits.
In this paper, we propose that in order to effectively translate biomarkers for practical clinical use, it is important to distinguish and quantify the differences between the use of biomarkers and other risk factors to identify preventive interventions versus their use in disease risk prediction and early detection. We developed mathematical models for quantitatively evaluating risk and benefit in use of biomarkers for disease prevention or early detection. Simple numerical examples were used to demonstrate the potential applications of the models for various types of data.
We propose an index which takes into account potential adverse consequences of biomarker-driven interventions – the ‘naïve’ ratio of population benefit (RPB) – to facilitate evaluating the potential impact of biomarkers on cancer prevention and personalized medicine. The index RPB is developed for both binary and continuous biomarkers/risk factors. Examples with computational analyses are presented in the paper to contrast the differences in using biomarkers/risk factors for prevention and early detection.
Integrating epidemiologic knowledge into clinical decision making is a key step to translate new biomarkers/risk factors into practical use to achieve health benefits. The RPB proposed in this paper considers the absolute risk of a disease in intervention, and takes into account the risk-benefit effects simultaneously for a marker/exposure at the population level. The RPB illustrates a unique approach to quantitatively assess the risk and potential benefits of using a biomarker/risk factor for intervention in both early detection and prevention.
Ratio of population benefit; RPB; Biomarkers; Disease prevention; Disease early detection; Clinical decision making; Biomarkers for early detection; Risk/benefit analysis
This paper describes the process of developing specifically designed web-based maternity information for women with type 1 diabetes.
A participatory design was used and the information was evaluated in seven stages by researchers, professional experts and users. All steps of the development process were noted in an online logbook.
The information developed gradually and its contents were reviewed by nurse-midwives, nurses and physicians specializing in different key areas including diabetes care, paediatrics, obstetrics and breastfeeding, a clinical dietician and mothers with type 1 diabetes. The draft was reviewed in regard to its cultural suitability and the information material was adjusted to meet quality criterions. Finally, the text was adapted for a lay audience.
Using participatory design required time and resources, however; it proved a functional way of producing appropriate information for the target group.
Information; Pregnancy; Type 1 diabetes; Support; Website; Participatory design
The development of genomic tests is one of the most significant technological advances in medical testing in recent decades. As these tests become increasingly available, so does the need for a pragmatic framework to evaluate the evidence base and evidence gaps in order to facilitate informed decision-making. In this article we describe such a framework that can provide a common language and benchmarks for different stakeholders of genomic testing. Each stakeholder can use this framework to specify their respective thresholds for decision-making, depending on their perspective and particular needs. This framework is applicable across a broad range of test applications and can be helpful in the application and communication of a regulatory science for genomic testing. Our framework builds upon existing work and incorporates principles familiar to researchers involved in medical testing (both diagnostic and prognostic) generally, as well as those involved in genomic testing. This framework is organized around six phases in the development of genomic tests beginning with marker identification and ending with population impact, and highlights the important knowledge gaps that need to be filled in establishing the clinical relevance of a test. Our framework focuses on the clinical appropriateness of the four main dimensions of test research questions (population/setting, intervention/index test, comparators/reference test, and outcomes) rather than prescribing a hierarchy of study designs that should be used to address each phase.
Genetic/genomic; Test development; Diagnostic test; Prognostic test; Evaluation framework; Evidence-based decision making
Electronic health records are increasingly being used to facilitate referral communication in the outpatient setting. However, despite support by technology, referral communication between primary care providers and specialists is often unsatisfactory and is unable to eliminate care delays. This may be in part due to lack of attention to how information and communication technology fits within the social environment of health care. Making electronic referral communication effective requires a multifaceted “socio-technical” approach. Using an 8-dimensional socio-technical model for health information technology as a framework, we describe ten recommendations that represent good clinical practices to design, develop, implement, improve, and monitor electronic referral communication in the outpatient setting. These recommendations were developed on the basis of our previous work, current literature, sound clinical practice, and a systems-based approach to understanding and implementing health information technology solutions. Recommendations are relevant to system designers, practicing clinicians, and other stakeholders considering use of electronic health records to support referral communication.
Translational research typically requires data abstracted from medical records as well as data collected specifically for research. Unfortunately, many data within electronic health records are represented as text that is not amenable to aggregation for analyses. We present a scalable open source SQL Server Integration Services package, called Regextractor, for including regular expression parsers into a classic extract, transform, and load workflow. We have used Regextractor to abstract discrete data from textual reports from a number of ‘machine generated’ sources. To validate this package, we created a pulmonary function test data mart and analyzed the quality of the data mart versus manual chart review.
Eleven variables from pulmonary function tests performed closest to the initial clinical evaluation date were studied for 100 randomly selected subjects with scleroderma. One research assistant manually reviewed, abstracted, and entered relevant data into a database. Correlation with data obtained from the automated pulmonary function test data mart within the Northwestern Medical Enterprise Data Warehouse was determined.
There was a near perfect (99.5%) agreement between results generated from the Regextractor package and those obtained via manual chart abstraction. The pulmonary function test data mart has been used subsequently to monitor disease progression of patients in the Northwestern Scleroderma Registry. In addition to the pulmonary function test example presented in this manuscript, the Regextractor package has been used to create cardiac catheterization and echocardiography data marts. The Regextractor package was released as open source software in October 2009 and has been downloaded 552 times as of 6/1/2012.
Collaboration between clinical researchers and biomedical informatics experts enabled the development and validation of a tool (Regextractor) to parse, abstract and assemble structured data from text data contained in the electronic health record. Regextractor has been successfully used to create additional data marts in other medical domains and is available to the public.
Medical informatics; Information storage and retrieval; Information systems; Electronic health records; Automatic data processing
The U.S. Centers for Medicare and Medicaid Services established the Electronic Health Record (EHR) Incentive Program in 2009 to stimulate the adoption of EHRs. One component of the program requires eligible providers to implement clinical decision support (CDS) interventions that can improve performance on one or more quality measures pre-selected for each specialty. Because the unique decision-making challenges and existing HIT capabilities vary widely across specialties, the development of meaningful objectives for CDS within such programs must be supported by deliberative analysis.
We developed a conceptual framework and protocol that combines evidence review with expert opinion to elicit clinically meaningful objectives for CDS directly from specialists. The framework links objectives for CDS to specialty-specific performance gaps while ensuring that a workable set of CDS opportunities are available to providers to address each performance gap. Performance gaps may include those with well-established quality measures but also priorities identified by specialists based on their clinical experience. Moreover, objectives are not constrained to performance gaps with existing CDS technologies, but rather may include those for which CDS tools might reasonably be expected to be developed in the near term, for example, by the beginning of Stage 3 of the EHR Incentive program. The protocol uses a modified Delphi expert panel process to elicit and prioritize CDS meaningful use objectives. Experts first rate the importance of performance gaps, beginning with a candidate list generated through an environmental scan and supplemented through nominations by panelists. For the highest priority performance gaps, panelists then rate the extent to which existing or future CDS interventions, characterized jointly as “CDS opportunities,” might impact each performance gap and the extent to which each CDS opportunity is compatible with specialists’ clinical workflows. The protocol was tested by expert panels representing four clinical specialties: oncology, orthopedic surgery, interventional cardiology, and pediatrics.
Tinnitus is a prevalent and complex medical complaint often co-morbid with stress, anxiety, insomnia, depression, and cognitive or communication difficulties. Its chronicity places a major burden on primary and secondary healthcare services. In our recent national survey of General Practitioners (GPs) from across England, many reported that their awareness of tinnitus was limited and as a result were dissatisfied with the service they currently provide. GPs identified 10 online sources of information they currently use in clinical practice, but welcomed further concise and accurate information on tinnitus assessment and management. The purpose of this study was to assess the content, reliability, and quality of the information related to primary care tinnitus assessment and management on these 10 websites.
Tinnitus related content on each website was assessed using a summative content analysis approach. Reliability and quality of the information was assessed using the DISCERN questionnaire.
Quality of information was rated using the validated DISCERN questionnaire. Significant inter-rater reliability was confirmed by Kendall’s coefficient of concordance (Wt) which ranged from 0.48 to 0.92 across websites. The website Map of Medicine achieved the highest overall DISCERN score. However, for information on treatment choice, the British Tinnitus Association was rated best. Content analysis revealed that all websites lacked a number of details relating to either tinnitus assessment or management options.
No single website provides comprehensive information for GPs on tinnitus assessment and management and so GPs may need to refer to more than one if they want to maximise their coverage of the topic. From those preferred by GPs we recommend several specific websites as the current ‘best’ sources. Our findings should guide healthcare website providers to improve the quality and inclusiveness of the information they publish on tinnitus. In the case of one website, our preliminary findings are already doing so. Such developments will in turn help facilitate best practice in primary care.
World wide web; Education; Good practice guidelines; Tinnitus management
A large body of work in the clinical guidelines field has identified requirements for guideline systems, but there are formidable challenges in translating such requirements into production-quality systems that can be used in routine patient care. Detailed analysis of requirements from an implementation perspective can be useful in helping define sub-requirements to the point where they are implementable. Further, additional requirements emerge as a result of such analysis. During such an analysis, study of examples of existing, software-engineering efforts in non-biomedical fields can provide useful signposts to the implementer of a clinical guideline system.
In addition to requirements described by guideline-system authors, comparative reviews of such systems, and publications discussing information needs for guideline systems and clinical decision support systems in general, we have incorporated additional requirements related to production-system robustness and functionality from publications in the business workflow domain, in addition to drawing on our own experience in the development of the Proteus guideline system (http://proteme.org).
The sub-requirements are discussed by conveniently grouping them into the categories used by the review of Isern and Moreno 2008. We cite previous work under each category and then provide sub-requirements under each category, and provide example of similar work in software-engineering efforts that have addressed a similar problem in a non-biomedical context.
When analyzing requirements from the implementation viewpoint, knowledge of successes and failures in related software-engineering efforts can guide implementers in the choice of effective design and development strategies.
In April 2010, with an endorsement from the Ministry of Health of the People's Republic of China, the Chinese Society of Nephrology launched the first nationwide, web-based prospective renal data registration platform, the Chinese Renal Data System (CNRDS), to collect structured demographic, clinical, and laboratory data for dialysis cases, as well as to establish a kidney disease database for researchers and policy makers.
The CNRDS program uses information technology to facilitate healthcare professionals to create a blood purification registry and to deliver an evidence-based care and education protocol tailored to chronic kidney disease, as well as online forum for communication between nephrologists. The online portal https://www.cnrds.net is implemented as a Java web application using an Apache Tomcat web server and a MySQL database. All data are stored in a central databank to establish a Chinese renal database for research and publication purposes.
Currently, over 270,000 clinical cases, including general patient information, diagnostics, therapies, medications, and laboratory tests, have been registered in CNRDS by 3,669 healthcare institutions qualified for hemodialysis therapy. At the 2011 annual blood purification forum of the Chinese Society of Nephrology, the CNRDS 2010 annual report was reviewed and accepted by the society members and government representatives.
CNRDS is the first national, web-based application for collecting and managing electronic medical records of patients with dialysis in China. It provides both an easily accessible platform for nephrologists to store and organize their patient data and acts as a communication platform among participating doctors. Moreover, it is the largest database for treatment and patient care of end-stage renal disease (ESRD) patients in China, which will be beneficial for scientific research and epidemiological investigations aimed at improving the quality of life of such patients. Furthermore, it is a model nationwide disease registry, which could potentially be used for other diseases.
Clinical Prediction Rules (CPRs) are tools that quantify the contribution of symptoms, clinical signs and available diagnostic tests, and in doing so stratify patients according to the probability of having a target outcome or need for a specified treatment. Most focus on the derivation stage with only a minority progressing to validation and very few undergoing impact analysis. Impact analysis studies remain the most efficient way of assessing whether incorporating CPRs into a decision making process improves patient care. However there is a lack of clear methodology for the design of high quality impact analysis studies.
We have developed a sequential four-phased framework based on the literature and the collective experience of our international working group to help researchers identify and overcome the specific challenges in designing and conducting an impact analysis of a CPR.
There is a need to shift emphasis from deriving new CPRs to validating and implementing existing CPRs. The proposed framework provides a structured approach to this topical and complex area of research.
Decision curve analysis has been introduced as a method to evaluate prediction models in terms of their clinical consequences if used for a binary classification of subjects into a group who should and into a group who should not be treated. The key concept for this type of evaluation is the "net benefit", a concept borrowed from utility theory.
We recall the foundations of decision curve analysis and discuss some new aspects. First, we stress the formal distinction between the net benefit for the treated and for the untreated and define the concept of the "overall net benefit". Next, we revisit the important distinction between the concept of accuracy, as typically assessed using the Youden index and a receiver operating characteristic (ROC) analysis, and the concept of utility of a prediction model, as assessed using decision curve analysis. Finally, we provide an explicit implementation of decision curve analysis to be applied in the context of case-control studies.
We show that the overall net benefit, which combines the net benefit for the treated and the untreated, is a natural alternative to the benefit achieved by a model, being invariant with respect to the coding of the outcome, and conveying a more comprehensive picture of the situation. Further, within the framework of decision curve analysis, we illustrate the important difference between the accuracy and the utility of a model, demonstrating how poor an accurate model may be in terms of its net benefit. Eventually, we expose that the application of decision curve analysis to case-control studies, where an accurate estimate of the true prevalence of a disease cannot be obtained from the data, is achieved with a few modifications to the original calculation procedure.
We present several interrelated extensions to decision curve analysis that will both facilitate its interpretation and broaden its potential area of application.
In this paper, we give an overview of methadone treatment in Ireland and outline the rationale for designing an electronic health record (EHR) with extensibility, interoperability and decision support functionality. Incorporating several international standards, a conceptual model applying a problem orientated approach in a hierarchical structure has been proposed for building the EHR.
A set of archetypes has been designed in line with the current best practice and clinical guidelines which guide the information-gathering process. A web-based data entry system has been implemented, incorporating elements of the paper-based prescription form, while at the same time facilitating the decision support function.
The use of archetypes was found to capture the ever changing requirements in the healthcare domain and externalises them in constrained data structures. The solution is extensible enabling the EHR to cover medicine management in general as per the programme of the HRB Centre for Primary Care Research.
The data collected via this Irish system can be aggregated into a larger dataset, if necessary, for analysis and evidence-gathering, since we adopted the openEHR standard. It will be later extended to include the functionalities of prescribing drugs other than methadone along with the research agenda at the HRB Centre for Primary Care Research in Ireland.
General practitioners and medical specialists mainly rely on one "general medical" journal to keep their medical knowledge up to date. Nevertheless, it is not known if these journals display the same overview of the medical knowledge in different specialties. The aims of this study were to measure the relative weight of the different specialties in the major journals of general medicine, to evaluate the trends in these weights over a ten-year period and to compare the journals.
The 14,091 articles published in The Lancet, the NEJM, the JAMA and the BMJ in 1997, 2002 and 2007 were analyzed. The relative weight of the medical specialities was determined by categorization of all the articles, using a categorization algorithm which inferred the medical specialties relevant to each article MEDLINE file from the MeSH terms used by the indexers of the US National Library of Medicine to describe each article.
The 14,091 articles included in our study were indexed by 22,155 major MeSH terms, which were categorized into 81 different medical specialties. Cardiology and Neurology were in the first 3 specialties in the 4 journals. Five and 15 specialties were systematically ranked in the first 10 and first 20 in the four journals respectively. Among the first 30 specialties, 23 were common to the four journals. For each speciality, the trends over a 10-year period were different from one journal to another, with no consistency and no obvious explanatory factor.
Overall, the representation of many specialties in the four journals in general and internal medicine included in this study may differ, probably due to different editorial policies. Reading only one of these journals may provide a reliable but only partial overview.
Tinnitus, the phantom perception of sound, is a frequent disorder that causes significant morbidity and treatment is elusive. A large variety of different treatment options have been proposed and from most of them some patients benefit. However, a particular treatment that helps one patient may fail for others. This suggests that there are different forms of tinnitus which differ in their pathophysiology and their response to specific treatments. Therefore, it is a major challenge for tinnitus treatment to identify the most promising therapy for a specific patient.
However, most published clinical treatment studies have enrolled only relatively small patient samples, making it difficult to identify predictors of treatment response for specific approaches. Furthermore, inter-study comparability is limited because of varying methods of tinnitus assessment and different outcome parameters. Performing clinical trials according to standardized methodology and pooling the data in a database should facilitate both clinical subtypisation of different forms of tinnitus, and identification of promising treatments for different types of tinnitus. This would be an important step towards the goal of individualized treatment of tinnitus.
For these reasons, an international database of tinnitus patients, who undergo specific treatments, and are assessed during the course of this treatment with standardized instruments (e.g., psychoacoustic measures, questionnaires) has been established. The primary objectives of this database are (1) collecting a standardized set of data on patient characteristics, treatments, and outcomes from tinnitus patients consulting specialized tinnitus clinics all over the world (at present 13 centers in 8 countries), (2) delineating different subtypes of tinnitus based on data that has been systematically collected and (3) identifying predictors for individual treatment response based on the clinical profile. Starting in 2008, the database currently contains data from more than 400 patients. It is expected that more centers will join the project and that the patient numbers will rapidly grow, so that this international database will further facilitate future research and contribute to the development of evidence based on individualized treatment.
We propose a novel framework for management of cancer survivorship: electronic patient Self-Assessment and Management (SAM). SAM is a framework for transfer of information to and from patients in such a way as to increase both the patient's and the health care provider's understanding of the patient's progress, and to help ensure that patient care follows best practice.
Patients who participate in the SAM system are contacted by email at regular intervals and asked to complete validated questionnaires online. Patient responses on these questionnaires are then analyzed in order to provide patients with real-time, online information about their progress and to provide them with tailored and standardized medical advice. Patient-level data from the questionnaires are ported in real time to the patient's health care provider to be uploaded to clinic notes. An initial version of SAM has been developed at Memorial Sloan-Kettering Cancer Center (MSKCC) and the University of California, San Francisco (UCSF) for aiding the clinical management of patients after surgery for prostate cancer.
Pilot testing at MSKCC and UCSF suggests that implementation of SAM systems are feasible, with no major problems with compliance (> 70% response rate) or security.
SAM is a conceptually simple framework for passing information to and from patients in such a way as to increase both the patient's and the health care provider's understanding of the patient's progress, and to help ensure that patient care follows best practice.
Managing change has not only been recognized as an important topic in medical informatics, but it has become increasingly important in translational informatics. The move to share data, together with the increasing complexity and volume of the data, has precipitated a transition from locally stored worksheet and flat files to relational data bases with object oriented interfaces for data storage and retrieval. While the transition from simple to complex data structures, mirroring the transition from simple to complex experimental technologies, seems natural, the human factor often fails to be adequately addressed leading to failures in managing change.
We describe here a case study in change management applied to an application in translational informatics that touches upon changes in hardware, software, data models, procedures, and terminology standards. We use the classic paper by Riley and Lorenzi to dissect the problems that arose, the solutions that were implemented, and the lessons learned.
The entire project from requirements gathering through completion of migration of the system took three years. Double data entry into the old and new systems persisted for six months. Contributing factors hindering progress and solutions to facilitate managing the change were identified in seven of the areas identified by Riley and Lorenzi: communications, cultural changes in work practice, scope creep, leadership and organizational issues, and training.
Detailed documentation of the agreed upon requirements for the new system along with ongoing review of the sources of resistance to change as defined by Riley and Lorenzi were the most important steps taken that contributed to the success of the project. Cultural changes in tissue collection mandated by standards requirements introduced by the Cancer Bioinformatics Grid (CaBIG®) and excessive reliance on the outgoing system during a lengthy period of dual data entry were the primary sources of resistance to change.
The DREAM Project operates within the framework of the national health systems of several sub-Saharan African countries and aims to introduce the essential components of an integrated strategy for the prevention and treatment of HIV/AIDS. The project is intended to serve as a model for a wide-ranging scale-up in the response to the epidemic. This paper aims to show DREAM's challenges and the solutions adopted. One of the solutions is the efficient management of the clinical data regarding the treatment of the patients and epidemiological analyses.
Specific software for the management of the patients' EMR has been created within the DREAM programme in order to deal with the challenges deriving from the context in which DREAM operates. Setting up a computer infrastructure in health centres, providing a power supply, as well as managing the data and the project resources efficiently and reliably, are some of the questions that have been analysed in this study.
Over the years this software has proved that it is able to respond to the need for efficient management of the clinical data and organization of the health centres. Today it is used in 10 countries in sub-Saharan Africa by thousands of professionals and by now it has reached its fourth version. The medical files of over 73,000 assisted patients are managed by this software and the data collected with it have become essential for the epidemiological research that is carried out to improve the effectiveness of the therapy.
Sub-Saharan Africa is the region hardest hit by HIV and AIDS in the world. However, the resources and responses adopted so far, to confront the epidemic, have at times been rather minimalist. The DREAM project has faced the battle against the epidemic by equipping itself with qualitative standards comparable to Western ones. The experience of DREAM has revealed that it is indeed possible to guarantee levels of excellence in developing countries, also in the sphere of ICT (Information and Communication Technology), thus making the intervention even more effective and contributing to bridging the digital divide.
New legal regulations for the marketing of pharmaceutical products were introduced in 2002 in Switzerland. We investigated whether claims in drug advertisements citing published scientific studies were justified by these studies after the introduction of these new regulations.
In this cross-sectional study, two independent reviewers screened all issues of six major Swiss medical journals published in the year 2005 to identify all drug advertisements for analgesic, gastrointestinal and psychopharmacologic drugs and evaluated all drug advertisements referring to at least one publication. The pharmaceutical claim was rated as being supported, being based on a potentially biased study or not to be supported by the cited study according to pre-specified criteria. We also explored factors likely to be associated with supported advertisement claims.
Of 2068 advertisements 577 (28%) promoted analgesic, psychopharmacologic or gastrointestinal drugs. Among them were 323 (56%) advertisements citing at least one reference. After excluding multiple publications of the same drug advertisement and advertisements with non-informative references, there remained 29 unique advertisements with at least one reference to a scientific study. These 29 advertisements contained 78 distinct pairs of claims of analgesic, gastrointestinal and psychopharmacologic drugs and referenced studies. Thirty-seven (47%) claims were supported, 16 (21%) claims were not supported by the corresponding reference, and 25 (32%) claims were based on potentially biased evidence, with no relevant differences between drug groups. Studies with conflict of interest and studies stating industry funding were more likely to support the corresponding claim (RR 1.52, 95% CI 1.07–2.17 and RR 1.50, 95% CI 0.98–2.28) than studies without identified conflict of interest and studies without information on type of funding.
Following the introduction of new regulations for drug advertisement in Switzerland, 53% of all assessed pharmaceutical claims published in major medical journals are not supported by the cited referenced studies or based on potentially biased study information. In light of the discrepancy between the new legislation and the endorsement of these regulations, physicians should not trust drug advertisement claims even when they seem to refer to scientific studies.
First generation Internet technologies such as mailing lists or newsgroups afforded unprecedented levels of information exchange within a variety of interest groups, including those who seek health information. With emergence of the World Wide Web many communication applications were ported to web browsers. One of the driving factors in this phenomenon has been the exchange of experiential or anecdotal knowledge that patients share online, and there is emerging evidence that participation in these forums may be having an impact on people's health decision making. Theoretical frameworks supporting this form of information seeking and learning have yet to be proposed.
In this article, we propose an adaptation of Kolb's experiential learning theory to begin to formulate an experiential health information processing model that may contribute to our understanding of online health information seeking behaviour in this context.
An experiential health information processing model is proposed that can be used as a research framework. Future research directions include investigating the utility of this model in the online health information seeking context, studying the impact of collaborating in these online environments on patient decision making and on health outcomes are provided.
SCT is used to assess clinical reasoning in ambiguous or uncertain situations. It allows testing on real-life situations that are not adequately measured with current tests. It probes the multiple judgments that are made in the clinical reasoning process. Scoring reflects the degree of concordance of these judgments to those of a panel of reference experts.
SCT is an item format that is gaining acceptance in education in the health professions. However, there are no detailed guidelines on item writing, test scoring or test optimization.
The item format is described and the steps for preparing and administering reliable and valid SCTs are presented.
SCTs probe examinees on a specific clinical reasoning task: data interpretation, a crucial step in the clinical reasoning process. It is inferred that a high degree of concordance corresponds to optimal use of information in the context of these specific tasks and therefore provides an indication of clinical reasoning quality.