Person:

Weitzman, Elissa

Background: Data stored in personally controlled health records (PCHRs) may hold value for clinicians and public health entities, if patients and their families will share them. We sought to characterize consumer willingness and unwillingness (reticence) to share PCHR data across health topics, and with different stakeholders, to advance understanding of this issue. Methods: Cross-sectional 2009 Web survey of repeat PCHR users who were patients over 18 years old or parents of patients, to assess willingness to share their PCHR data with an-out-of-hospital provider to support care, and the state/local public health authority to support monitoring; the odds of reticence to share PCHR information about ten exemplary health topics were estimated using a repeated measures approach. Results: Of 261 respondents (56% response rate), more reported they would share all information with the state/local public health authority (63.3%) than with an out-of-hospital provider (54.1%) (OR 1.5, 95% CI 1.1, 1.9; p = .005); few would not share any information with these parties (respectively, 7.9% and 5.2%). For public health sharing, reticence was higher for most topics compared to contagious illness (ORs 4.9 to 1.4, all p-values < .05), and reflected concern about anonymity (47.2%), government insensitivity (41.5%), discrimination (24%). For provider sharing, reticence was higher for all topics compared to contagious illness (ORs 6.3 to 1.5, all p-values < .05), and reflected concern for relevance (52%), disclosure to insurance (47.6%) and/or family (20.5%). Conclusions: Pediatric patients and their families are often willing to share electronic health information to support health improvement, but remain cautious. Robust trust models for PCHR sharing are needed.

Objective: Test a novel health monitoring approach by engaging an international online diabetes social network (SN) in consented health surveillance. Methods: Collection of structured self-reports about preventive and self-care practices and health status using a software application (“app”) that supports SN-mediated health research. Comparison of SN measures by diabetes type; and, SN with Behavioral Risk Factor Surveillance System (BRFSS) data, for US-residing insulin dependent respondents, using logistic regression. Results: Of 2,414 SN app users, 82% (n=1979) provided an A1c and 41% (n=996) completed a care survey of which 931 have diabetes. Of these: 65% and 41% were immunized against influenza and pneumonia respectively, 90% had their cholesterol checked, 82% and 66%, had their eyes and feet checked, respectively. Type 1/LADA respondents were more likely than Type 2/pre-diabetic respondents to report all five recommended practices (Adjusted OR (95% CI) 2.2 (1.5, 3.2)). Past year self-care measures were: 58% self-monitored their blood glucose (SMBG) ≥ 5 times daily, 37% saw their diabetes nutritionist, 56% saw a diabetes nurse educator, 53% saw a doctor for their diabetes ≥ 4 times. Reports of health status did not differ by diabetes type in the SN sample. The SN group was more likely than the BRFSS comparator group to use all five preventive care practices (Adjusted OR (95% CI) 1.8 (1.4, 2.1) and SMBG ≥ 5 times daily (Adjusted OR (95% CI) 10.1 (6.8, 14.9). Conclusions: Rapid assessment of diabetes care practices using a novel, SN-mediated approach can extend the capability of standard health surveillance systems.

Background: Surveillance and response to diabetes may be accelerated through engaging online diabetes social networks (SNs) in consented research. We tested the willingness of an online diabetes community to share data for public health research by providing members with a privacy-preserving social networking software application for rapid temporalgeographic surveillance of glycemic control. Methods and Findings: SN-mediated collection of cross-sectional, member-reported data from an international online diabetes SN entered into a software applicaction we made available in a ‘‘Facebook-like’’ environment to enable reporting, charting and optional sharing of recent hemoglobin A1c values through a geographic display. Self-enrollment by 17% (n = 1,136) of n = 6,500 active members representing 32 countries and 50 US states. Data were current with 83.1% of most recent A1c values reported obtained within the past 90 days. Sharing was high with 81.4% of users permitting data donation to the community display. 34.1% of users also displayed their A1cs on their SN profile page. Users selecting the most permissive sharing options had a lower average A1c (6.8%) than users not sharing with the community (7.1%, p = .038). 95% of users permitted re-contact. Unadjusted aggregate A1c reported by US users closely resembled aggregate 2007–2008 NHANES estimates (respectively, 6.9% and 6.9%, p = 0.85). Conclusions: Success within an early adopter community demonstrates that online SNs may comprise efficient platforms for bidirectional communication with and data acquisition from disease populations. Advancing this model for cohort and translational science and for use as a complementary surveillance approach will require understanding of inherent selection and publication (sharing) biases in the data and a technology model that supports autonomy, anonymity and privacy.

Purpose Family health history is often collected through single-item queries that ask patients whether or not their family members are affected by certain conditions. The specific wording of these queries may affect what individuals report. Methods: Parents of Boston Children’s Hospital patients were invited to participate in a web-based survey about the return of individual genomic research results about their children. Participants reported whether 11 types of medical conditions affected them or their family. Randomization determined whether or not participants were specifically instructed to consider their extended family. Results: 2,901 participants reported family health history. Those asked to consider their extended family were more likely to report a positive family history for 8 of 11 medical conditions. The largest differences were observed for cancer (65.1% vs 45.7%, p<0.001), cardiovascular conditions (72.5% vs 56.0%, p<0.001), and endocrine/hormonal conditions (50.9% vs 36.7%, p<0.001). Conclusions: Small alterations to the way family health history queries are worded can substantially change patient responses. Clinicians and researchers need to be sensitive about patients’ tendencies to omit extended family from health history reporting unless specifically asked to consider them.

Background: In an effort to reduce barriers to screening for alcohol use in pediatric primary care, the National Institute on Alcoholism and Alcohol Abuse (NIAAA) developed a two-question Youth Alcohol Screening Tool derived from population-based survey data. It is unknown whether this screening tool, designed for use with general populations, accurately identifies risk among youth with chronic medical conditions (YCMC). This growing population, which comprises nearly one in four youth in the US, faces a unique constellation of drinking-related risks. Method To validate the NIAAA Youth Alcohol Screening Tool in a population of YCMC, we performed a cross-sectional validation study with a sample of 388 youth ages 9–18 years presenting for routine subspecialty care at a large children’s hospital for type 1 diabetes, persistent asthma, cystic fibrosis, inflammatory bowel disease, or juvenile idiopathic arthritis. Participants self-administered the NIAAA Youth Alcohol Screening Tool and the Diagnostic Interview Schedule for Children as a criterion standard measure of alcohol use disorders (AUD). Receiver operating curve analysis was used to determine cut points for identifying youth at moderate and highest risk for an AUD. Results: Nearly one third of participants (n = 118; 30.4%) reported alcohol use in the past year; 86.4% (106) of past year drinkers did not endorse any AUD criteria, 6.8% (n = 8) of drinkers endorsed a single criterion, and 6.8% of drinkers met criteria for an AUD. Using the NIAAA tool, optimal cut points found to identify youth at moderate and highest risk for an AUD were ≥ 6 and ≥12 drinking days in the past year, respectively. Conclusions: The NIAAA Youth Alcohol Screening Tool is highly efficient for detecting alcohol use and discriminating disordered use among YCMC. This brief screen appears feasible for use in specialty care to ascertain alcohol-related risk that may impact adversely on health status and disease management.

We reviewed research regarding system- and visit-level strategies to enhance clinical preventive service delivery and quality for adolescents and young adults. Despite professional consensus on recommended services for adolescents, a strong evidence base for services for young adults, and improved financial access to services with the Affordable Care Act’s provisions, receipt of preventive services remains suboptimal. Further research that builds off successful models of linking traditional and community clinics is needed to improve access to care for all youth. To optimize the clinical encounter, promising clinician-focused strategies to improve delivery of preventive services include screening and decision support tools, particularly when integrated into electronic medical record systems and supported by training and feedback. Although results have been mixed, interventions have moved beyond increasing service delivery to demonstrating behavior change. Research on emerging technology—such as gaming platforms, mobile phone applications, and wearable devices—suggests opportunities to expand clinicians’ reach; however, existing research is based on limited clinical settings and populations. Improved monitoring systems and further research are needed to examine preventive services facilitators and ensure that interventions are effective across the range of clinical settings where youth receive preventive care, across multiple populations, including young adults, and for more vulnerable populations with less access to quality care.

Background: Children with Juvenile Idiopathic Arthritis (JIA) often have poor health-related quality of life (HRQOL) despite advances in treatment. Patient-centered research may shed light on how patient experiences of treatment and disease contribute to HRQOL, pinpointing directions for improving care and enhancing outcomes. Methods: Parent proxies of youth enrolled in the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry shared patient-reported outcomes about their child’s HRQOL and experiences of disease and treatment burden (pain interference, morning stiffness, history of medication side effects and methotrexate intolerance). Contributions of these measures to HRQOL were estimated using generalized estimating equations accounting for site and patient demographics. Results: Patients (N = 180) were 81.1% white non-Hispanic and 76.7% female. Mean age was 11.8 (SD = 3.6) years, mean disease duration was 7.7 years (SD = 3.5). Mean Total Pediatric Quality of Life was 76.7 (SD = 18.2). Mean pain interference score was 50.1 (SD = 11.1). Nearly one-in-five (17.8%) youth experienced >15 min of morning stiffness on a typical day, more than one quarter (26.7%) reported ≥1 serious medication side effect and among 90 methotrexate users, 42.2% met criteria for methotrexate intolerance. Measures of disease and treatment burden were independently negatively associated with HRQOL (all p-values <0.01). Negative associations among measures of treatment burden and HRQOL were attenuated after controlling for disease burden and clinical characteristics but remained significant. Conclusions: For youth with JIA, HRQOL is multidimensional, reflecting disease as well as treatment factors. Adverse treatment experiences undermine HRQOL even after accounting for disease symptoms and disease activity and should be assessed routinely to improve wellbeing. Electronic supplementary material The online version of this article (10.1186/s41687-017-0025-2) contains supplementary material, which is available to authorized users.

Objective: To characterize current and future approaches to surveillance of chronic and non-communicable diseases and establish the agenda for both methodological and condition-specific progress. Introduction: Major global stakeholder groups including the United Nations, World Health Organization and Institute of Medicine seek to raise awareness of the threat to global health and security of chronic and non-communicable diseases. These conditions comprise 50–85% of the global annual morbidity burden and constitute a major drain on national economies. To move from awareness of this problem to action and amelioration of issues, we need effective means for monitoring and intervening with populations using approaches that span primary, secondary and tertiary prevention. Methods: This session will begin with a discussion of key concepts and terms and their implications for defining target problems, populations and surveillance strategies. We will also begin by reviewing the epidemiologic and economic arguments for advancing surveillance in this area. The discussion will center on a critical assessment of issues related to surveillance of chronic and non-communicable diseases: how do approaches differ from established and evolving approaches to surveillance of infectious disease? Are there opportunities for synergy with current surveillance efforts and assets? Where are new methods needed? How might surveillance approaches be advanced in different regions (e.g., developing and industrialized settings)? Might new approaches predicated on “citizen science” and engaged patient and public health cohorts provide platforms for advancing surveillance of chronic and non-communicable diseases and what is required to ensure their success? Results: Points of discussion: Participants are encouraged to come prepared to share their experiences engaging patient and public health cohorts in this area, including sharing experiences engaging cohorts using online social networks, participatory research and surveys.Brainstorm ideas for development of a workshop in non-communicable disease surveillance. Sample questions: What are the issues related to surveillance in the context of resource rich and poor contexts?What are the special needs for establishing cost-effective and sustainable methods for longitudinal tracking?How can technological advances and engaged patient and public health cohorts be used in the advancement of surveillance? What are methods to maximize engagement in both the developed and developing world? Conclusions: Non-communicable diseases are a major and growing morbidity and mortality burden globally. This round table discussion will focus on the importance of non-communicable disease surveillance, attempt to elicit participant’s experiences in the surveillance of these conditions, and outline special needs for establishing cost-effective and sustainable methods for longitudinal tracking of non-communicable diseases.