Widespread Adoption of Information Technology in Primary Care Physician Offices in Denmark: A Case Study

Describes the use of electronic medical records, standardized clinical communications, and patient identification numbers by Denmark's primary care physicians; a nonprofit organization's role in implementation and certification; and elements of success

Performance Measures Using Electronic Health Records: Five Case Studies

Presents the experiences of five provider organizations in developing, testing, and implementing four types of electronic quality-of-care indicators based on EHR data. Discusses challenges, and compares results with those from traditional indicators

Structured reporting: if, why, when, how—and at what expense? Results of a focus group meeting of radiology professionals from eight countries

Purpose: To determine why, despite growing evidence that radiologists and referring physicians prefer structured reporting (SR) to free text (FT) reporting, SR has not been widely adopted in most radiology departments. Methods: A focus group was formed consisting of 11 radiology professionals from eight countries. Eight topics were submitted for discussion. The meeting was videotaped, transcribed, and analyzed according to the principles of qualitative healthcare research. Results: Perceived advantages of SR were facilitation of research, easy comparison, discouragement of ambiguous reports, embedded links to images, highlighting important findings, not having to dictate text nobody will read, and automatic translation of teleradiology reports. Being compelled to report within a rigid frame was judged unacceptable. Personal convictions appeared to have high emotional value. It was felt that other healthcare stakeholders would impose SR without regard to what radiologists thought of it. If the industry were to provide ready-made templates for selected examinations, most radiologists would use them. Conclusion: If radiologists can be convinced of the advantages of SR and the risks associated with failing to participate actively in its implementation, they will take a positive stand. The industry should propose technology allowing SR without compromising accuracy, completeness, workflows, and cost-benefit balance

Automation of a problem list using natural language processing

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

Toward unsupervised outbreak detection through visual perception of new patterns

<p>Abstract</p> <p>Background</p> <p>Statistical algorithms are routinely used to detect outbreaks of well-defined syndromes, such as influenza-like illness. These methods cannot be applied to the detection of emerging diseases for which no preexisting information is available.</p> <p>This paper presents a method aimed at facilitating the detection of outbreaks, when there is no a priori knowledge of the clinical presentation of cases.</p> <p>Methods</p> <p>The method uses a visual representation of the symptoms and diseases coded during a patient consultation according to the International Classification of Primary Care 2^ndversion (ICPC-2). The surveillance data are transformed into color-coded cells, ranging from white to red, reflecting the increasing frequency of observed signs. They are placed in a graphic reference frame mimicking body anatomy. Simple visual observation of color-change patterns over time, concerning a single code or a combination of codes, enables detection in the setting of interest.</p> <p>Results</p> <p>The method is demonstrated through retrospective analyses of two data sets: description of the patients referred to the hospital by their general practitioners (GPs) participating in the French Sentinel Network and description of patients directly consulting at a hospital emergency department (HED).</p> <p>Informative image color-change alert patterns emerged in both cases: the health consequences of the August 2003 heat wave were visualized with GPs' data (but passed unnoticed with conventional surveillance systems), and the flu epidemics, which are routinely detected by standard statistical techniques, were recognized visually with HED data.</p> <p>Conclusion</p> <p>Using human visual pattern-recognition capacities to detect the onset of unexpected health events implies a convenient image representation of epidemiological surveillance and well-trained "epidemiology watchers". Once these two conditions are met, one could imagine that the epidemiology watchers could signal epidemiological alerts, based on "image walls" presenting the local, regional and/or national surveillance patterns, with specialized field epidemiologists assigned to validate the signals detected.</p

What health care for undocumented migrants in Belgium?

n/

Addendum to Informatics for Health 2017: Advancing both science and practice

This article presents presentation and poster abstracts that were mistakenly omitted from the original publication

Primary care physicians' perceptions of barriers and facilitators to management of chronic kidney disease: A mixed methods study.

BackgroundGiven the high prevalence of chronic kidney disease (CKD), primary care physicians (PCPs) frequently manage early stage CKD. Nonetheless, there are challenges in providing optimal CKD care in the primary care setting. This study sought to understand PCPs' perceptions of barriers and facilitators to the optimal management of CKD.Study designMixed methods study.Settings and participantsCommunity-based PCPs in four US cities: Baltimore, MD; St. Louis, MO; Raleigh, NC and San Francisco, CA.MethodologyWe used a self-administered questionnaire and conducted 4 focus groups of PCPs (n = 8 PCPs/focus group) in each city to identify key barriers and facilitators to management of patients with CKD in primary care.Analytic approachWe conducted descriptive analyses of the survey data. Major themes were identified from audio-recorded interviews that were transcribed and coded by the research team.ResultsOf 32 participating PCPs, 31 (97%) had been in practice for &gt;10 years, and 29 (91%) practiced in a non-academic setting. PCPs identified multiple barriers to managing CKD in primary care including at the level of the patient (e.g., low awareness of CKD, poor adherence to treatment recommendations), the provider (e.g., staying current with CKD guidelines), and the health care system (e.g., inflexible electronic medical record, limited time and resources). PCPs desired electronic prompts and lab decision support, concise guidelines, and healthcare financing reform to improve CKD care.ConclusionsPCPs face substantial but modifiable barriers in providing care to patients with CKD. Interventions that address these barriers and promote facilitative tools may improve PCPs' effectiveness and capacity to care for patients with CKD