http://www.biomedcentral.com/bmcmedinformdecismak/ The most accessed research articles published by BMC Medical Informatics and Decision Making 2009-11-06T00:00:00Z This is an RSS newsfeed from BioMed Central It is intended to be used with an RSS reader. For more information about RSS newsfeeds from BioMed Central, visit http://www.biomedcentral.com/info/about/rss/ Background: There are few studies that examine the processes that interdisciplinary teams engage in and how we can design health information systems (HIS) to support those team processes. This was an exploratory study with two purposes: (1) To develop a framework for interdisciplinary team communication based on structures, processes and outcomes that were identified as having occurred during weekly team meetings. (2) To use the framework to guide 'e-teams' HIS design to support interdisciplinary team meeting communication. Methods: An ethnographic approach was used to collect data on two interdisciplinary teams. Qualitative content analysis was used to analyze the data according to structures, processes and outcomes. Results: We present details for team meta-concepts of structures, processes and outcomes and the concepts and sub concepts within each meta-concept. We also provide an exploratory framework for interdisciplinary team communication and describe how the framework can guide HIS design to support 'e-teams'. Conclusion: The structures, processes and outcomes that describe interdisciplinary teams are complex and often occur in a non-linear fashion. Electronic data support, process facilitation and team video conferencing are three HIS tools that can enhance team function. http://www.biomedcentral.com/1472-6947/9/43 Craig Kuziemsky Elizabeth Borycki Mary Ellen Purkis Fraser Black Michael Boyle Denise Cloutier-Fisher Lee Ann Fox Patricia MacKenzie Ann Syme Coby Tschanz Wendy Wainwright Helen Wong BMC Medical Informatics and Decision Making 2009, 9:43 2009-09-15T00:00:00Z doi:10.1186/1472-6947-9-43 BMC Medical Informatics and Decision Making 1472-6947 9 43 2009-09-15T00:00:00Z XML Background: Despite the growing interest by leaders, policy makers, and others, the terminology of health information technology as well as biomedical and health informatics is poorly understood and not even agreed upon by academics and professionals in the field.DiscussionThe paper, presented as a Debate to encourage further discussion and disagreement, provides definitions of the major terminology used in biomedical and health informatics and health information technology. For informatics, it focuses on the words that modify the term as well as individuals who practice the discipline. Other categories of related terms are covered as well, from the associated disciplines of computer science, information technolog and health information management to the major application categories of applications used. The discussion closes with a classification of individuals who work in the largest segment of the field, namely clinical informatics.SummaryThe goal of presenting in Debate format is to provide a starting point for discussion to reach a documented consensus on the definition and use of these terms. http://www.biomedcentral.com/1472-6947/9/24 William Hersh BMC Medical Informatics and Decision Making 2009, 9:24 2009-05-15T00:00:00Z doi:10.1186/1472-6947-9-24 BMC Medical Informatics and Decision Making 1472-6947 9 24 2009-05-15T00:00:00Z XML Background: Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies.DiscussionApproaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures), and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine.SummaryThis perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In addition, to represent meaningful benefits to personalized decision-making, a comparison of current and future applications of clinical decision support to enable individualized medical treatment plans is presented. If clinical decision support tools are to impact outcomes in a clear and positive manner, their development and deployment must therefore consider the needs of the providers, including specific practice needs, information workflow, and practice environment. http://www.biomedcentral.com/1472-6947/9/44 Gregory Downing Scott Boyle Kristin Brinner Jerome Osheroff BMC Medical Informatics and Decision Making 2009, 9:44 2009-10-08T00:00:00Z doi:10.1186/1472-6947-9-44 BMC Medical Informatics and Decision Making 1472-6947 9 44 2009-10-08T00:00:00Z XML Background: Supporting 21st century health care and the practice of evidence-based medicine (EBM) requires ubiquitous access to clinical information and to knowledge-based resources to answer clinical questions. Many questions go unanswered, however, due to lack of skills in formulating questions, crafting effective search strategies, and accessing databases to identify best levels of evidence. Methods: This randomized trial was designed as a pilot study to measure the relevancy of search results using three different interfaces for the PubMed search system. Two of the search interfaces utilized a specific framework called PICO, which was designed to focus clinical questions and to prompt for publication type or type of question asked. The third interface was the standard PubMed interface readily available on the Web. Study subjects were recruited from interns and residents on an inpatient general medicine rotation at an academic medical center in the US. Thirty-one subjects were randomized to one of the three interfaces, given 3 clinical questions, and asked to search PubMed for a set of relevant articles that would provide an answer for each question. The success of the search results was determined by a precision score, which compared the number of relevant or gold standard articles retrieved in a result set to the total number of articles retrieved in that set. Results: Participants using the PICO templates (Protocol A or Protocol B) had higher precision scores for each question than the participants who used Protocol C, the standard PubMed Web interface. (Question 1: A = 35%, B = 28%, C = 20%; Question 2: A = 5%, B = 6%, C = 4%; Question 3: A = 1%, B = 0%, C = 0%) 95% confidence intervals were calculated for the precision for each question using a lower boundary of zero. However, the 95% confidence limits were overlapping, suggesting no statistical difference between the groups. Conclusion: Due to the small number of searches for each arm, this pilot study could not demonstrate a statistically significant difference between the search protocols. However there was a trend towards higher precision that needs to be investigated in a larger study to determine if PICO can improve the relevancy of search results. http://www.biomedcentral.com/1472-6947/7/16 Connie Schardt Martha Adams Thomas Owens Sheri Keitz Paul Fontelo BMC Medical Informatics and Decision Making 2007, 7:16 2007-06-15T00:00:00Z doi:10.1186/1472-6947-7-16 BMC Medical Informatics and Decision Making 1472-6947 7 16 2007-06-15T00:00:00Z XML Background: Combining multiple databases with disjunctive or additional information on the same person is occurring increasingly throughout research. If unique identification numbers for these individuals are not available, probabilistic record linkage is used for the identification of matching record pairs. In many applications, identifiers have to be encrypted due to privacy concerns. Methods: A new protocol for privacy-preserving record linkage with encrypted identifiers allowing for errors in identifiers has been developed. The protocol is based on Bloom filters on q-grams of identifiers. Results: Tests on simulated and actual databases yield linkage results comparable to non-encrypted identifiers and superior to results from phonetic encodings. Conclusion: We proposed a protocol for privacy-preserving record linkage with encrypted identifiers allowing for errors in identifiers. Since the protocol can be easily enhanced and has a low computational burden, the protocol might be useful for many applications requiring privacy-preserving record linkage. http://www.biomedcentral.com/1472-6947/9/41 Rainer Schnell Tobias Bachteler Joerg Reiher BMC Medical Informatics and Decision Making 2009, 9:41 2009-08-25T00:00:00Z doi:10.1186/1472-6947-9-41 BMC Medical Informatics and Decision Making 1472-6947 9 41 2009-08-25T00:00:00Z XML Background: Integrated personal health records (PHRs) offer significant potential to stimulate transformational changes in health care delivery and self-care by patients. In 2006, an invitational roundtable sponsored by Kaiser Permanente Institute, the American Medical Informatics Association, and the Agency for Healthcare Research and Quality was held to identify the transformative potential of PHRs, as well as barriers to realizing this potential and a framework for action to move them closer to the health care mainstream. This paper highlights and builds on the insights shared during the roundtable.DiscussionWhile there is a spectrum of dominant PHR models, (standalone, tethered, integrated), the authors state that only the integrated model has true transformative potential to strengthen consumers' ability to manage their own health care. Integrated PHRs improve the quality, completeness, depth, and accessibility of health information provided by patients; enable facile communication between patients and providers; provide access to health knowledge for patients; ensure portability of medical records and other personal health information; and incorporate auto-population of content. Numerous factors impede widespread adoption of integrated PHRs: obstacles in the health care system/culture; issues of consumer confidence and trust; lack of technical standards for interoperability; lack of HIT infrastructure; the digital divide; uncertain value realization/ROI; and uncertain market demand. Recent efforts have led to progress on standards for integrated PHRs, and government agencies and private companies are offering different models to consumers, but substantial obstacles remain to be addressed. Immediate steps to advance integrated PHRs should include sharing existing knowledge and expanding knowledge about them, building on existing efforts, and continuing dialogue among public and private sector stakeholders.SummaryIntegrated PHRs promote active, ongoing patient collaboration in care delivery and decision making. With some exceptions, however, the integrated PHR model is still a theoretical framework for consumer-centric health care. The authors pose questions that need to be answered so that the field can move forward to realize the potential of integrated PHRs. How can integrated PHRs be moved from concept to practical application? Would a coordinating body expedite this progress? How can existing initiatives and policy levers serve as catalysts to advance integrated PHRs? http://www.biomedcentral.com/1472-6947/8/45 Don Detmer Meryl Bloomrosen Brian Raymond Paul Tang BMC Medical Informatics and Decision Making 2008, 8:45 2008-10-06T00:00:00Z doi:10.1186/1472-6947-8-45 BMC Medical Informatics and Decision Making 1472-6947 8 45 2008-10-06T00:00:00Z XML Background: Text-based patient medical records are a vital resource in medical research. In order to preserve patient confidentiality, however, the U.S. Health Insurance Portability and Accountability Act (HIPAA) requires that protected health information (PHI) be removed from medical records before they can be disseminated. Manual de-identification of large medical record databases is prohibitively expensive, time-consuming and prone to error, necessitating automatic methods for large-scale, automated de-identification. Methods: We describe an automated Perl-based de-identification software package that is generally usable on most free-text medical records, e.g., nursing notes, discharge summaries, X-ray reports, etc. The software uses lexical look-up tables, regular expressions, and simple heuristics to locate both HIPAA PHI, and an extended PHI set that includes doctors' names and years of dates. To develop the de-identification approach, we assembled a gold standard corpus of re-identified nursing notes with real PHI replaced by realistic surrogate information. This corpus consists of 2,434 nursing notes containing 334,000 words and a total of 1,779 instances of PHI taken from 163 randomly selected patient records. This gold standard corpus was used to refine the algorithm and measure its sensitivity. To test the algorithm on data not used in its development, we constructed a second test corpus of 1,836 nursing notes containing 296,400 words. The algorithm's false negative rate was evaluated using this test corpus. Results: Performance evaluation of the de-identification software on the development corpus yielded an overall recall of 0.967, precision value of 0.749, and fallout value of approximately 0.002. On the test corpus, a total of 90 instances of false negatives were found, or 27 per 100,000 word count, with an estimated recall of 0.943. Only one full date and one age over 89 were missed. No patient names were missed in either corpus. Conclusion: We have developed a pattern-matching de-identification system based on dictionary look-ups, regular expressions, and heuristics. Evaluation based on two different sets of nursing notes collected from a U.S. hospital suggests that, in terms of recall, the software out-performs a single human de-identifier (0.81) and performs at least as well as a consensus of two human de-identifiers (0.94). The system is currently tuned to de-identify PHI in nursing notes and discharge summaries but is sufficiently generalized and can be customized to handle text files of any format. Although the accuracy of the algorithm is high, it is probably insufficient to be used to publicly disseminate medical data. The open-source de-identification software and the gold standard re-identified corpus of medical records have therefore been made available to researchers via the PhysioNet website to encourage improvements in the algorithm. http://www.biomedcentral.com/1472-6947/8/32 Ishna Neamatullah Margaret Douglass Li-wei Lehman Andrew Reisner Mauricio Villarroel William Long Peter Szolovits George Moody Roger Mark Gari Clifford BMC Medical Informatics and Decision Making 2008, 8:32 2008-07-24T00:00:00Z doi:10.1186/1472-6947-8-32 BMC Medical Informatics and Decision Making 1472-6947 8 32 2008-07-24T00:00:00Z XML Background: Adoption of EHRs by U.S. ambulatory practices has been slow despite the perceived benefits of their use. Most evaluations of EHR implementations in the literature apply to large practice settings. While there are similarities relating to EHR implementation in large and small practice settings, the authors argue that scale is an important differentiator. Focusing on small ambulatory practices, this paper outlines the benefits and barriers to EHR use in this setting, and provides a "field guide" for these practices to facilitate successful EHR implementation.DiscussionThe benefits of EHRs in ambulatory practices include improved patient care and office efficiency, and potential financial benefits. Barriers to EHRs include costs; lack of standardization of EHR products and the design of vendor systems for large practice environments; resistance to change; initial difficulty of system use leading to productivity reduction; and perceived accrual of benefits to society and payers rather than providers. The authors stress the need for developing a flexible change management strategy when introducing EHRs that is relevant to the small practice environment; the strategy should acknowledge the importance of relationship management and the role of individual staff members in helping the entire staff to manage change. Practice staff must create an actionable vision outlining realistic goals for the implementation, and all staff must buy into the project. The authors detail the process of implementing EHRs through several stages: decision, selection, pre-implementation, implementation, and post-implementation. They stress the importance of identifying a champion to serve as an advocate of the value of EHRs and provide direction and encouragement for the project. Other key activities include assessing and redesigning workflow; understanding financial issues; conducting training that is well-timed and meets the needs of practice staff; and evaluating the implementation process.SummaryThe EHR implementation experience depends on a variety of factors including the technology, training, leadership, the change management process, and the individual character of each ambulatory practice environment. Sound processes must support both technical and personnel-related organizational components. Additional research is needed to further refine recommendations for the small physician practice and the nuances of specific medical specialties. http://www.biomedcentral.com/1472-6947/9/15 Nancy Lorenzi Angelina Kouroubali Don Detmer Meryl Bloomrosen BMC Medical Informatics and Decision Making 2009, 9:15 2009-02-23T00:00:00Z doi:10.1186/1472-6947-9-15 BMC Medical Informatics and Decision Making 1472-6947 9 15 2009-02-23T00:00:00Z XML Background: The objective of this feasibility study was to gain insight into occupational physicians' (OPs) and employees' use of, and attitudes towards, 'Snelbeter' (Get Well Fast), a new web-based counselling program for employees on sick leave due to non-specific back or neck pain and their OPs. Methods: Registered user information was collected from the website to get insight in the use of the program by employees (n = 24). Qualitative information was obtained through semi-structured in-depth interviews with 19 OPs and nine employees in order to get insight in the actual use of the provided information, the attitudes towards the program and possible improvements of the program. Results: Actual use of the program among OPs was low. The majority of OPs, eight out of 11 (73%), never or only occasionally signed in. The greatest obstacle for OPs to use the program was the low number of eligible employees involved. Employees appreciated the program but their use was moderate. A small majority of the employees who used the program, 14 out of 24 (58%), opened 50% to 100% of the provided documents, a majority of the interviewed employees, seven out of nine (78%), used the provided information sometimes or regularly. The absence of personal contact was found to be a major barrier towards use of the program by employees. Conclusion: Although both OPs and employees appreciated the idea of the program and employees appreciated using it, program utilization was moderate to low. The discussion section reveals that before implementation can be started to any extent, the program will need adaptations that make it more attractive to use. The program should be considered for both return to work (RTW) and the prevention of sick leave. Adding personal contact (e.g. involving physiotherapists) to the program may also be promising. http://www.biomedcentral.com/1472-6947/9/46 Tanja de Jong Judith Heinrich Birgitte Blatter Johannes Anema Allard van der Beek BMC Medical Informatics and Decision Making 2009, 9:46 2009-11-06T00:00:00Z doi:10.1186/1472-6947-9-46 BMC Medical Informatics and Decision Making 1472-6947 9 46 2009-11-06T00:00:00Z XML Background: The medical problem list is an important part of the electronic medical record in development in our institution. To serve the functions it is designed for, the problem list has to be as accurate and timely as possible. However, the current problem list is usually incomplete and inaccurate, and is often totally unused. To alleviate this issue, we are building an environment where the problem list can be easily and effectively maintained. Methods: For this project, 80 medical problems were selected for their frequency of use in our future clinical field of evaluation (cardiovascular). We have developed an Automated Problem List system composed of two main components: a background and a foreground application. The background application uses Natural Language Processing (NLP) to harvest potential problem list entries from the list of 80 targeted problems detected in the multiple free-text electronic documents available in our electronic medical record. These proposed medical problems drive the foreground application designed for management of the problem list. Within this application, the extracted problems are proposed to the physicians for addition to the official problem list. Results: The set of 80 targeted medical problems selected for this project covered about 5% of all possible diagnoses coded in ICD-9-CM in our study population (cardiovascular adult inpatients), but about 64% of all instances of these coded diagnoses. The system contains algorithms to detect first document sections, then sentences within these sections, and finally potential problems within the sentences. The initial evaluation of the section and sentence detection algorithms demonstrated a sensitivity and positive predictive value of 100% when detecting sections, and a sensitivity of 89% and a positive predictive value of 94% when detecting sentences. Conclusion: The global aim of our project is to automate the process of creating and maintaining a problem list for hospitalized patients and thereby help to guarantee the timeliness, accuracy and completeness of this information. http://www.biomedcentral.com/1472-6947/5/30 Stephane Meystre Peter Haug BMC Medical Informatics and Decision Making 2005, 5:30 2005-08-31T00:00:00Z doi:10.1186/1472-6947-5-30 BMC Medical Informatics and Decision Making 1472-6947 5 30 2005-08-31T00:00:00Z XML