BACKGROUND: Personally controlled health records (PCHRs), a subset of personal health records (PHRs), enable a patient to assemble, maintain and manage a secure copy of his or her medical data. Indivo (formerly PING) is an open source, open standards PCHR with an open application programming interface (API). RESULTS: We describe how the PCHR platform can provide standard building blocks for networked PHR applications. Indivo allows the ready integration of diverse sources of medical data under a patient's control through the use of standards-based communication protocols and APIs for connecting PCHRs to existing and future health information systems. CONCLUSION: The strict and transparent personal control model is designed to encourage widespread participation by patients, healthcare providers and institutions, thus creating the ecosystem for development of innovative, consumer-focused healthcare applications.

To support a rich ecosystem of third-party applications around a personally controlled health record (PCHR), we have redesigned Indivo, the original PCHR, as a web-based platform with feature-level substitutability. Core to this new release is the Indivo X Application Programming Interface (API), the contract between the PCHR platform and the end-user apps. Using rapid iterative development to build a minimal feature set from real-world requirements, the resulting Indivo X API, now in public stable beta, is enabling developers, including third-party contributors, to quickly create and integrate novel features into patients' online records, ultimately building a fully customizable experience for diverse patient needs.

OBJECTIVE: Development of national biosurveillance systems to advance regional and national data exchange among sites of clinical care and public health authorities is a top federal priority, creating the opportunity to develop a unified national network for tracking and responding to cases of vaccine-preventable diseases. The purpose of this study was to assess the current practice and feasibility of developing a nationwide network of children's hospitals to conduct surveillance for vaccine preventable diseases. METHODS: In 2004-2005, Web-based surveys were sent to 506 key hospital personnel from 119 pediatric hospitals, identified by the National Association of Children's Hospitals and Related Institutions. Surveys measured attitudes toward public health initiatives, willingness to join a surveillance network of children's hospitals, knowledge of mandated reporting requirements, methods of disease detection and reporting, and data sources available for surveillance. RESULTS: A total of 395 (78%) respondents from 119 hospitals completed the survey. Surveillance at pediatric hospitals is largely passive and driven by unreimbursed efforts of infection control staff. It is vulnerable to missing cases that occur in the outpatient setting and are diagnosed clinically without laboratory confirmation or are never diagnosed by clinicians. Nearly 90% of hospital leaders are interested in participating in public health programs, and most are interested in a national network to conduct active surveillance for vaccine-preventable diseases, dependent on the provision of sufficient funding. Pediatric hospitals store records relevant to surveillance in an electronic fashion accessible to query, but 20% of these hospitals use automated methods to report cases of disease. CONCLUSIONS: There is both the will and capability to create a robust active pediatric hospital-based reporting system for vaccine preventable diseases. This effort would dovetail well with the national priority to bolster surveillance, as well as with the goal of reducing morbidity and mortality from vaccine-preventable diseases.

OBJECTIVE: We determined the incidence of serious invasive bacteremia caused by Neisseria meningitidis and other organisms in febrile infants and children with a petechial rash. Further, we studied the diagnostic value of laboratory and clinical finding in these patients. STUDY DESIGN: We conducted this prospective cohort study in the emergency department of an urban pediatric teaching hospital, during an 18-month period, and enrolled consecutive patients with temperature of 38 degrees C or higher and petechiae. Our measures included (1) laboratory tests (leukocyte count, coagulation profile, blood culture, and cerebrospinal fluid bacterial culture); (2) a questionnaire requesting clinical data including general appearance, number and location of petechiae, and presence or absence of purpura; and (3) a follow-up telephone survey documenting health status. RESULTS: A total of 411 patients were enrolled, with 57.7% between 3 and 36 months of age. Eight patients (1.9%) had bacteremia or clinical sepsis. Six had serious invasive bacteremia: N. meningitidis (two patients), group A streptococcus (one), or sepsis with negative culture results (three). Two had occult bacteremia caused by Streptococcus pneumoniae and no evidence of sepsis. No patient had a positive cerebrospinal fluid culture result. None of the 357 well-appearing patients (95% confidence interval: 0.0%, 1.0%) had serious invasive bacteremia. Fifty-three patients appeared ill, including all six with serious invasive bacteremia. Ill appearance of the child had a sensitivity of 1.00 (95% confidence interval: 0.60, 1.00), and a leukocyte count of 15,000 or greater, or of less than 5000, had a sensitivity of 1.0 (95% confidence interval: 0.53, 1.00) for detecting serious invasive bacteremia. All children with meningococcemia had purpura. CONCLUSIONS: Invasive bacteremia occurred less frequently in our study than in previous series and was identified by clinical criteria. Our data support the treatment of selected well-appearing children with fever and petechiae as outpatients.

BACKGROUND: Clinical prediction rules do not incorporate real-time incidence data to adjust estimates of disease risk in symptomatic patients. OBJECTIVE: To measure the value of integrating local incidence data into a clinical decision rule for diagnosing group A streptococcal (GAS) pharyngitis in patients aged 15 years or older. DESIGN: Retrospective analysis of clinical and biosurveillance predictors of GAS pharyngitis. SETTING: Large U.S.-based retail health chain. PATIENTS: 82 062 patient visits for pharyngitis. MEASUREMENTS: Accuracy of the Centor score was compared with that of a biosurveillance-responsive score, which was essentially an adjusted Centor score based on real-time GAS pharyngitis information from the 14 days before a patient's visit: the recent local proportion positive (RLPP). RESULTS: Increased RLPP correlated with the likelihood of GAS pharyngitis (r(2) = 0.79; P 0.001). Local incidence data enhanced diagnostic models. For example, when the RLPP was greater than 0.30, managing patients with Centor scores of 1 as if the scores were 2 would identify 62, 537 previously missed patients annually while misclassifying 18, 446 patients without GAS pharyngitis. Decreasing the score of patients with Centor values of 3 by 1 point for an RLPP less than 0.20 would spare unnecessary antibiotics for 166, 616 patients while missing 18, 812 true-positive cases. LIMITATIONS: Analyses were conducted retrospectively. Real-time regional data on GAS pharyngitis are generally not yet available to clinicians. CONCLUSION: Incorporating live biosurveillance data into clinical guidelines for GAS pharyngitis and other communicable diseases should be considered for reducing missed cases when the contemporaneous incidence is elevated and for sparing unnecessary antibiotics when the contemporaneous incidence is low. Delivering epidemiologic data to the point of care will enable the use of real-time pretest probabilities in medical decision making.

Syndromic surveillance refers to methods relying on detection of individual and population health indicators that are discernible before confirmed diagnoses are made. In particular, prior to the laboratory confirmation of an infectious disease, ill persons may exhibit behavioral patterns, symptoms, signs, or laboratory findings that can be tracked through a variety of data sources. Syndromic surveillance systems are being developed locally, regionally, and nationally. The efforts have been largely directed at facilitating the early detection of a covert bioterrorist attack, but the technology may also be useful for general public health, clinical medicine, quality improvement, patient safety, and research. This report, authored by developers and methodologists involved in the design and deployment of the first wave of syndromic surveillance systems, is intended to serve as a guide for informaticians, public health managers, and practitioners who are currently planning deployment of such systems in their regions.

INTRODUCTION: Laboratory test orders constitute an early outbreak data source. CDC receives laboratory order data in HL7 format from the Laboratory Corporation of America (LabCorp) and plans to use the data in the BioSense Early Event Detection and Situation Awareness System. METHODS: These LabCorp data contain information on tests ordered and include the type of test ordered and the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)-coded reasons for the order. A consensus panel was formed to group test orders on the basis of expert opinion into eight standard syndrome categories to provide an additional data source for early outbreak detection. A laboratory order taxonomy was developed and used in the mapping consolidation phase. The five main classes of this taxonomy are miscellaneous functional tests, fluid screening tests, system-specific tests, tests for specific infections (by primary manifestation), and tests for specific noninfectious diseases. RESULTS: Summary of numbers of laboratory order codes in each syndrome category are fever (53), respiratory (53), gastrointestinal (27), neurological (35), rash (37), lymphadenitis (20), localized cutaneous lesion (11), and specific infection (63). CONCLUSION: With the daily use of laboratory order data in BioSense, the actual distribution of laboratory order codes in syndrome groups can be evaluated, allowing modification of the mapping.

Evidence is accumulating that universal vaccination of schoolchildren would reduce the transmission of influenza. The authors sought to identify target age groups within the pediatric population that develop influenza the earliest and are most strongly linked with mortality in the population. Patient visits for respiratory illness were monitored, using real-time syndromic surveillance systems, in six Massachusetts health-care settings, including ambulatory care sites and emergency departments at tertiary-care and community hospitals. Visits from January 1, 2000, to September 30, 2004, were segmented into age group subpopulations. Timeliness and prediction of each subpopulation were measured against pneumonia and influenza mortality in New England with time-series analyses and regression models. Study results show that patient age significantly influences timeliness (p = 0.026), with pediatric age groups arriving first (p 0.001); children aged 3-4 years are consistently the earliest (p = 0.0058). Age also influences the degree of prediction of mortality (p = 0.036), with illness among children under age 5 years, compared with all other patients, most strongly associated with mortality (p 0.001). Study findings add to a growing body of support for a strategy to vaccinate children older than the currently targeted age of 6-23 months and specifically suggest that there may be value in vaccinating preschool-age children.

OBJECTIVE: Registries are a well-established mechanism for obtaining high quality, disease-specific data, but are often highly project-specific in their design, implementation, and policies for data use. In contrast to the conventional model of centralized data contribution, warehousing, and control, we design a self-scaling registry technology for collaborative data sharing, based upon the widely adopted Integrating Biology & the Bedside (i2b2) data warehousing framework and the Shared Health Research Information Network (SHRINE) peer-to-peer networking software. MATERIALS AND METHODS: Focusing our design around creation of a scalable solution for collaboration within multi-site disease registries, we leverage the i2b2 and SHRINE open source software to create a modular, ontology-based, federated infrastructure that provides research investigators full ownership and access to their contributed data while supporting permissioned yet robust data sharing. We accomplish these objectives via web services supporting peer-group overlays, group-aware data aggregation, and administrative functions. RESULTS: The 56-site Childhood Arthritis & Rheumatology Research Alliance (CARRA) Registry and 3-site Harvard Inflammatory Bowel Diseases Longitudinal Data Repository now utilize i2b2 self-scaling registry technology (i2b2-SSR). This platform, extensible to federation of multiple projects within and between research networks, encompasses >6000 subjects at sites throughout the USA. DISCUSSION: We utilize the i2b2-SSR platform to minimize technical barriers to collaboration while enabling fine-grained control over data sharing. CONCLUSIONS: The implementation of i2b2-SSR for the multi-site, multi-stakeholder CARRA Registry has established a digital infrastructure for community-driven research data sharing in pediatric rheumatology in the USA. We envision i2b2-SSR as a scalable, reusable solution facilitating interdisciplinary research across diseases.