While patient-controlled health records (PCHRs) promise easy and unprecedented access to medical information, user access policies will need to be carefully defined to preserve privacy and confidentiality. There are particular challenges in pediatrics, where both the minor's and the parent's rights to privacy and confidentiality need to be upheld. We propose a framework to define access control policies for a pediatric PCHR.

BACKGROUND: Consumer-centered health information systems that address problems related to fragmented health records and disengaged and disempowered patients are needed, as are information systems that support public health monitoring and research. Personally controlled health records (PCHRs) represent one response to these needs. PCHRs are a special class of personal health records (PHRs) distinguished by the extent to which users control record access and contents. Recently launched PCHR platforms include Google Health, Microsoft's HealthVault, and the Dossia platform, based on Indivo. OBJECTIVE: To understand the acceptability, early impacts, policy, and design requirements of PCHRs in a community-based setting. METHODS: Observational and narrative data relating to acceptability, adoption, and use of a personally controlled health record were collected and analyzed within a formative evaluation of a PCHR demonstration. Subjects were affiliates of a managed care organization run by an urban university in the northeastern United States. Data were collected using focus groups, semi-structured individual interviews, and content review of email communications. Subjects included: n = 20 administrators, clinicians, and institutional stakeholders who participated in pre-deployment group or individual interviews; n = 52 community members who participated in usability testing and/or pre-deployment piloting; and n = 250 subjects who participated in the full demonstration of which n = 81 initiated email communications to troubleshoot problems or provide feedback. All data were formatted as narrative text and coded thematically by two independent analysts using a shared rubric of a priori defined major codes. Sub-themes were identified by analysts using an iterative inductive process. Themes were reviewed within and across research activities (ie, focus group, usability testing, email content review) and triangulated to identify patterns. RESULTS: Low levels of familiarity with PCHRs were found as were high expectations for capabilities of nascent systems. Perceived value for PCHRs was highest around abilities to co-locate, view, update, and share health information with providers. Expectations were lowest for opportunities to participate in research. Early adopters perceived that PCHR benefits outweighed perceived risks, including those related to inadvertent or intentional information disclosure. Barriers and facilitators at institutional, interpersonal, and individual levels were identified. Endorsement of a dynamic platform model PCHR was evidenced by preferences for embedded searching, linking, and messaging capabilities in PCHRs; by high expectations for within-system tailored communications; and by expectation of linkages between self-report and clinical data. CONCLUSIONS: Low levels of awareness/preparedness and high expectations for PCHRs exist as a potentially problematic pairing. Educational and technical assistance for lay users and providers are critical to meet challenges related to: access to PCHRs, especially among older cohorts; workflow demands and resistance to change among providers; inadequate health and technology literacy; clarification of boundaries and responsibility for ensuring accuracy and integrity of health information across distributed data systems; and understanding confidentiality and privacy risks. Continued demonstration and evaluation of PCHRs is essential to advancing their use.

BACKGROUND/PURPOSE: In 2009, the Childhood Arthritis and Rheumatology Research Alliance (CARRA) established a longitudinal multi-center, multiple disease U.S. national registry (CARRA Registry) for pediatric rheumatology with the intent of providing a new framework to drive observational clinical research and best practices, evidence-based care. Simultaneously, recognizing that widely variable therapeutic approaches hinder the ability to conduct meaningful comparative effectiveness studies and pragmatic trials in pediatric rheumatic diseases, CARRA investigators convened expert groups to formulate new consensus-based treatment plans (CTPs) in 5 major pediatric rheumatic disease areas. As the CTP approaches are adopted, it is important to establish baseline treatment variability across pediatric rheumatic diseases and clinical sites in the CARRA network. Using longitudinal data from the CARRA Registry, we provide a first description of variability of care across the network. METHODS: We examine variations of medication usage across 55 clinical sites in the treatment of 8 rheumatic conditions, including juvenile idiopathic arthritis (JIA), SLE and mixed connective tissue disease (MCTD), juvenile dermatomyositis (JDM), localized scleroderma, systemic sclerosis, juvenile primary fibromyalgia syndrome (JPFS), sarcoidosis, and vasculitis. Management of uveitis in JIA patients was also assessed. Study participants include all CARRA registry subjects enrolled in May 2010 through December 2013. Medications were categorized into 4 major classes: biologics, DMARDs, steroids and NSAIDs. We compare the percentage of patients exposed to each medication class at each; care variations were quantified using dispersion measures of standard deviation and range. A subgroup analysis was conducted to assess care variations among the largest group of subjects with similar characteristics of and low disease activity (JIA subjects with an average active joint count of 0 to 1 averaged over the enrolment period), where treatment were hypothesized to be most similar. RESULTS: 8,869 subjects were included in data analysis. Therapeutic approaches were highly variable for all 8 rheumatic diseases (Table 1, Fig 1). Subgroup analysis for JIA showed persistence of variability (Fig 2). CONCLUSION: We quantify a substantial degree of therapeutic practice variability across sites, persisting across disease-severity-matched cohorts. Although enrollment bias is a significant limitation, the magnitude of the variability for the largest cohort (JIA) and persistence across multiple diseases and subtypes supports a widespread effect. This baseline quantification and methods developed for assessing variability will support ongoing efforts to monitor new consensus treatment protocol-based standardization efforts across the CARRA network.