Case series: Use of Glyceryl Trinitrate patches to improve peripheral circulation in children with severe neurodisability.

AIM: Evaluation of topical Glyceryl trinitrate as a therapeutic option to improve peripheral circulation in 16 children with severe complex neurodisability, poor capillary return and signs of vascular insufficiency, including discomfort. METHODS: If insufficient improvement in capillary return was obtained using conservative measures, a 5 mg GTN patch was placed each day on the front of the tibia of each leg. Children were reviewed clinically for up to 12 months of treatment. Distal limb comfort was measured using a Likert scale, either patient or carer reported. Standardised capillary refill time was assessed at each clinical review. RESULTS: Use of the patches led to improved capillary refill time and parent/patient reported comfort in all children. Healing of skin ulcers in lower limbs after application of the patch was also noted. There was universal parent/patient satisfaction with use of the patch. One child with Aicardi Goutieres syndrome had a skin reaction with prolonged use and minor adverse effects were reported in 4 others but this did not result in discontinuation of treatment. SUMMARY: GTN patches were relatively well tolerated in this group of children. We suggest that use of GTN patches be considered for children with severe neurodisability and poor peripheral circulation causing discomfort. GTN patches may also have a role in healing of persistent skin ulcers for these children.

Impact of integrating public health clinical decision support alerts into electronic health records on testing for gastrointestinal illness.

Laboratory testing by clinicians is essential to outbreak investigations. Electronic health records may increase testing through clinical decision support that alerts providers about existing outbreaks and facilitates laboratory ordering. The impact on laboratory testing was evaluated for foodborne disease outbreaks between 2006 and 2009. After controlling for standard public health messaging and season, decision support resulted in a significant increase in laboratory testing and may be useful in enhancing public health messaging and provider action.

Developing an online and in-person HIT workforce training program using a team-based learning approach.

Workforce training in health information technology (HIT) is in demand as electronic health record adoption becomes a nationwide priority. Columbia University and Weill Cornell Medical College worked together to develop a 6-month ONC-supported certificate course. To identify relevant skills and knowledge, we conducted a needs assessment that included: interviews and focus groups with potential employers and current HIT employees; an analysis of both published literature on competencies and actual job listings; and the development of a diverse operations-oriented curriculum advisory committee, which help to synthesize the findings into 6 core curriculum modules. We selected a team-based learning approach, allowing us to train a diverse student body and providing opportunities to build collaboration skills. Our novel hybrid adaptation of team-based learning combines online and in-person activities. Lessons learned from the development of this program are likely to have widespread applicability as training programs in the field become more prevalent.

Using electronic health record alerts to provide public health situational awareness to clinicians.

Alerting providers to public health situations requires timeliness and context-relevance, both lacking in current systems. Incorporating decision support tools into electronic health records may provide a way to deploy public health alerts to clinicians at the point of care. A timely process for responding to Health Alert Network messages sent by the New York City Department of Health and Mental Hygiene was developed by a network of community health centers. Alerts with order sets and recommended actions were created to notify primary care providers of local disease outbreaks. The process, effect, and lessons learned from alerts for Legionella, toxogenic E coli, and measles outbreaks are described. Electronic alerts have the potential to improve management of diseases during an outbreak, including appropriate laboratory testing, management guidance, and diagnostic assistance as well as to enhance bi-directional data exchange between clinical and public health organizations.

Syndromic surveillance using ambulatory electronic health records.

OBJECTIVE: To assess the performance of electronic health record data for syndromic surveillance and to assess the feasibility of broadly distributed surveillance. DESIGN: Two systems were developed to identify influenza-like illness and gastrointestinal infectious disease in ambulatory electronic health record data from a network of community health centers. The first system used queries on structured data and was designed for this specific electronic health record. The second used natural language processing of narrative data, but its queries were developed independently from this health record. Both were compared to influenza isolates and to a verified emergency department chief complaint surveillance system. MEASUREMENTS: Lagged cross-correlation and graphs of the three time series. RESULTS: For influenza-like illness, both the structured and narrative data correlated well with the influenza isolates and with the emergency department data, achieving cross-correlations of 0.89 (structured) and 0.84 (narrative) for isolates and 0.93 and 0.89 for emergency department data, and having similar peaks during influenza season. For gastrointestinal infectious disease, the structured data correlated fairly well with the emergency department data (0.81) with a similar peak, but the narrative data correlated less well (0.47). CONCLUSIONS: It is feasible to use electronic health records for syndromic surveillance. The structured data performed best but required knowledge engineering to match the health record data to the queries. The narrative data illustrated the potential performance of a broadly disseminated system and achieved mixed results.

Repurposing the clinical record: can an existing natural language processing system de-identify clinical notes?

Electronic clinical documentation can be useful for activities such as public health surveillance, quality improvement, and research, but existing methods of de-identification may not provide sufficient protection of patient data. The general-purpose natural language processor MedLEE retains medical concepts while excluding the remaining text so, in addition to processing text into structured data, it may be able provide a secondary benefit of de-identification. Without modifying the system, the authors tested the ability of MedLEE to remove protected health information (PHI) by comparing 100 outpatient clinical notes with the corresponding XML-tagged output. Of 809 instances of PHI, 26 (3.2%) were detected in output as a result of processing and identification errors. However, PHI in the output was highly transformed, much appearing as normalized terms for medical concepts, potentially making re-identification more difficult. The MedLEE processor may be a good enhancement to other de-identification systems, both removing PHI and providing coded data from clinical text.

Using empiric semantic correlation to interpret temporal assertions in clinical texts.

OBJECTIVE: To measure the uncertainty of temporal assertions like "3 weeks ago" in clinical texts. DESIGN: Temporal assertions extracted from narrative clinical reports were compared to facts extracted from a structured clinical database for the same patients. MEASUREMENTS: The authors correlated the assertions and the facts to determine the dependence of the uncertainty of the assertions on the semantic and lexical properties of the assertions. RESULTS: The observed deviation between the stated duration and actual duration averaged about 20% of the stated deviation. Linear regression revealed that assertions about events further in the past tend to be more uncertain, smaller numeric values tend to be more uncertain (1 mo v. 30 d), and round numbers tend to be more uncertain (10 versus 11 yrs). CONCLUSIONS: The authors empirically derived semantics behind statements of duration using "ago," and verified intuitions about how numbers are used.

Using a pipeline to improve de-identification performance.

Effective de-identification methods are needed to support reuse of electronic health record data for research and other purposes. We investigated using two different text-processing systems in tandem as a strategy for de-identification of clinical notes. We ran 100 outpatient notes through deid.pl, from MIT's PhysioToolkit, followed by MedLEE, and we manually compared the output with original notes to determine the amount of protected health information (PHI) retained. Pipelining resulted in an overall error rate of 2%, with 2 personal names retained in output: one initial and a commonly used English term used in medicine. All retained PHI was transformed into standardized medical concepts, making re-identification less likely. Pipelining using deid.pl improved performance of MedLEE in excluding PHI from output and may be a useful strategy for de-identifying clinical data while providing computer-readable output.

Preliminary development of the physician documentation quality instrument.

OBJECTIVES: This study sought to design and validate a reliable instrument to assess the quality of physician documentation. DESIGN: Adjectives describing clinician attitudes about high-quality clinical documentation were gathered through literature review, assessed by clinical experts, and transformed into a semantic differential scale. Using the scale, physicians and nurse practitioners scored the importance of the adjectives for describing quality in three note types: admission, progress, and discharge notes. Psychometric methods including exploratory factor analysis were applied to provide preliminary evidence for the construct validity and internal consistency reliability. RESULTS: A 22-item Physician Documentation Quality Instrument (PDQI) was developed. Exploratory factor analysis (n = 67 clinician respondents) on three note types resulted in solutions ranging from four (discharge) to six (admission and progress) factors, and explained 65.8% (discharge) to 73% (admission and progress) of the variance. Each factor solution was unique. However, four sets of items consistently factored together across all note types: (1) up-to-date and current; (2) brief, concise, succinct; (3) organized and structured; and (4) correct, comprehensible, consistent. Internal consistency reliabilities were: admission note (factor scales = 0.52-88, overall = 0.86), progress note (factor scales = 0.59-0.84, overall = 0.87), and discharge summary (factor scales = 0.76-0.85, overall = 0.88). CONCLUSION: The exploratory factor analyses and reliability analyses provide preliminary evidence for the construct validity and internal consistency reliability of the PDQI. Two novel dimensions of the construct for document quality were developed related to form (Well-formed, Compact). Additional work is needed to assess intrarater and interrater reliability of applying of the proposed instrument and to examine the reproducibility of the factors in other samples.

An electronic health record based on structured narrative.

OBJECTIVE: To develop an electronic health record that facilitates rapid capture of detailed narrative observations from clinicians, with partial structuring of narrative information for integration and reuse. DESIGN: We propose a design in which unstructured text and coded data are fused into a single model called structured narrative. Each major clinical event (e.g., encounter or procedure) is represented as a document that is marked up to identify gross structure (sections, fields, paragraphs, lists) as well as fine structure within sentences (concepts, modifiers, relationships). Marked up items are associated with standardized codes that enable linkage to other events, as well as efficient reuse of information, which can speed up data entry by clinicians. Natural language processing is used to identify fine structure, which can reduce the need for form-based entry. VALIDATION: The model is validated through an example of use by a clinician, with discussion of relevant aspects of the user interface, data structures and processing rules. DISCUSSION: The proposed model represents all patient information as documents with standardized gross structure (templates). Clinicians enter their data as free text, which is coded by natural language processing in real time making it immediately usable for other computation, such as alerts or critiques. In addition, the narrative data annotates and augments structured data with temporal relations, severity and degree modifiers, causal connections, clinical explanations and rationale. CONCLUSION: Structured narrative has potential to facilitate capture of data directly from clinicians by allowing freedom of expression, giving immediate feedback, supporting reuse of clinical information and structuring data for subsequent processing, such as quality assurance and clinical research.

Inter-patient distance metrics using SNOMED CT defining relationships.

BACKGROUND: Patient-based similarity metrics are important case-based reasoning tools which may assist with research and patient care applications. Ontology and information content principles may be potentially helpful tools for similarity metric development. METHODS: Patient cases from 1989 through 2003 from the Columbia University Medical Center data repository were converted to SNOMED CT concepts. Five metrics were implemented: (1) percent disagreement with data as an unstructured "bag of findings," (2) average links between concepts, (3) links weighted by information content with descendants, (4) links weighted by information content with term prevalence, and (5) path distance using descendants weighted by information content with descendants. Three physicians served as gold standard for 30 cases. RESULTS: Expert inter-rater reliability was 0.91, with rank correlations between 0.61 and 0.81, representing upper-bound performance. Expert performance compared to metrics resulted in correlations of 0.27, 0.29, 0.30, 0.30, and 0.30, respectively. Using SNOMED axis Clinical Findings alone increased correlation to 0.37. CONCLUSION: Ontology principles and information content provide useful information for similarity metrics but currently fall short of expert performance.

Communication and health protection issues arising from a flooding emergency.

OBJECTIVE: To identify and describe the key communication and health protection issues surrounding a flooding emergency. METHODS: A telephone questionnaire was used to assess health and safety information sources, information recalled, and behavioral responses among residents of the town of Feilding, New Zealand following a major flood in February 2004. This was supplemented by key informant interviews and a newspaper content analysis. RESULTS: A total of 154 adult residents were surveyed (76% of those successfully contacted and eligible). Of the respondents, 79% recalled being provided with health and safety information from authorities. The major sources were: radio (41%), pamphlets (23%), and newspapers (20%). The regional newspaper had extensive coverage of this flooding emergency but "health" only was mentioned in 46 (7%) of the 664 flood-related articles. Of those who recalled receiving information from authorities, most (89%) perceived that it was adequate. Nevertheless, 18% actively sought out information (mainly about water safety and availability). In the post-flood period, 73% of all respondents boiled water; however, only 4% maintained boiling water or bottled water use for the necessary nine-week period. Some forms of emergency preparations did not change substantially from before the flood, compared to four months afterwards (e.g., having a radio with batteries increased from 62% to 68%). Perceived health concerns around the flooding were low, though 59% were concerned about the risk of water contamination. Actual self-reported, health consequences from the flood were rare, as only two (1%) people out of 154 reported flood-related health problems. CONCLUSIONS: Health and safety information generally was communicated successfully and was regarded as appropriate by the population of this flood-affected town. Nevertheless, there are further improvements needed in the emergency response by both residents and authorities.

Analyzing the structure and content of public health messages.

BACKGROUND: Health messages are crucial to the field of public health in effecting behavior change, but little research is available to assist writers in composing the overall structure of a message. In order to develop software to assist non-expert message writers in constructing effective messages, the structure of existing health messages must be understood, and an appropriate method for analyzing health message structure developed. METHODS: 72 messages from expert sources were used for development of the method, which was then tested for reproducibility using ten randomly selected health messages. Four raters analyzed the messages and inter-coder agreement was calculated. RESULTS: A method for analyzing the structure of the messages was developed using sublanguage analysis and discourse analysis. Overall kappa between four coders was 0.69, demonstrating "substantial agreement." CONCLUSION: A novel framework for characterizing health message structure and a method for analyzing messages appears to be reproducible.

Development of competency-based on-line public health informatics tutorials: accessing and using on-line public health data and information.

In response to training and information needs of the public health workforce, the New York City Department of Health and Mental Hygiene, in collaboration with the Department of Biomedical Informatics, Columbia University and the New York Academy of Medicine, is developing a series of on-line, interactive tutorials in public health informatics. The goal is to teach public health practitioners how to locate, use, and disseminate data and information on the Internet, while imparting basic informatics principles. Course content is based on Public Health Informatics Competencies, and evaluation will be performed by measuring changes in self-efficacy and knowledge as well as determining user satisfaction.