The accuracy of weight reported in a web-based obesity treatment program

OBJECTIVE

The overall goal of the study was to understand the accuracy of self-reported weight over a 6-month Web-based obesity program.

MATERIALS AND METHODS

As part of a larger study, subjects (n=323; 93% female; 28% African American) were randomized to a 6-month Internet-based behavioral weight loss program with weekly group meetings delivered either: (1) entirely by online synchronous chats or (2) by a combination of online chats plus monthly in-person group sessions. Observed weights were obtained at 0 and 6 months for all participants. Self-reported weights were submitted weekly to the study Web site. Differences in Observed and Reported weights were examined by gender, race, and condition.

RESULTS

Observed and Reported weight were significantly correlated at 0 and 6 months (r=0.996 and 0.996, ps <0.001 respectively). However, Reported weight underestimated Observed weight by 0.86 kg (p<0.001) at 6 months. Further, there was a significant weight loss effect (p<0.001) with those losing more weight more accurately estimating their Reported weight at 6 months. Additionally, 6-month Reported weight change differed from Observed weight change (difference=0.72 kg, p<0.001), with weight change using Reported weights estimating a slightly larger weight loss than Observed weights.

CONCLUSIONS

In general, the accuracy of self-reported weight is high for individuals participating in an Internet-based weight loss treatment program. Accuracy differed slightly by amount of weight lost and was not improved with periodic in-person assessment. Importantly, weight change by self-report was comparable to observed, suggesting that it is suitable for Web-based obesity treatment.

Comparative effectiveness study to assess two examination modalities used to detect dental caries in preschool urban children

BACKGROUND

Dental caries affecting the primary dentition of U.S. children continues to be the most prevalent chronic childhood disease. Preventive screening for dental caries in toddlers by dental professionals is labor-intensive and costly. Studies are warranted to examine innovative screening modalities that reduce cost, are less labor-intensive, and have the potential to identify caries in high-risk children.

SUBJECTS AND METHODS

Two hundred ninety-one children were randomized into two groups: Group 1 received a traditional, visual tactile examination initially and follow up-examinations at 6 and 12 months, and Group 2 received a teledentistry examination initially and follow-up examinations at 6 and 12 months. The mean primary tooth decayed and filled surfaces (dfs) scores were calculated for all children at baseline and 6 and 12 months.

RESULTS

At baseline, the mean dfs score for children examined by means of teledentistry was 2.19, and for the children examined by means of the traditional method, the mean was 1.27; the means were not significantly different. At the 12-month examination, the mean dfs score for the children examined by means of teledentistry was 3.02, and for the children examined by means of the clinical method, the mean dfs was 1.70; the means were not significantly different. At 12 months the mean fillings score for the children examined by means of teledentistry was 1.43 and for the children examined by means of the clinical method was 0.51; the means were statistically significantly different (p<0.001).

CONCLUSIONS

These results suggest that the teledentistry examinations were comparable to clinical examinations when screening for early childhood caries in preschool children. The data further showed that color printouts of teeth with cavities provided to parents of children who received teledentistry screenings promoted oral healthcare utilization, as children from the teledentistry study group received more dental care than children from the clinical study group.

Personalized-detailed clinical model for data interoperability among clinical standards

OBJECTIVE

Data interoperability among health information exchange (HIE) systems is a major concern for healthcare practitioners to enable provisioning of telemedicine-related services. Heterogeneity exists in these systems not only at the data level but also among different heterogeneous healthcare standards with which these are compliant. The relationship between healthcare organization data and different heterogeneous standards is necessary to achieve the goal of data level interoperability. We propose a personalized-detailed clinical model (P-DCM) approach for the generation of customized mappings that creates the necessary linkage between organization-conformed healthcare standards concepts and clinical model concepts to ensure data interoperability among HIE systems.

MATERIALS AND METHODS

We consider electronic health record (EHR) standards, openEHR, and HL7 CDA instances transformation using P-DCM. P-DCM concepts associated with openEHR and HL7 CDA help in transformation of instances among these standards. We investigated two datasets: (1) data of 100 diabetic patients, including 50 each of type 1 and type 2, from a local hospital in Korea and (2) data of a single Alzheimer's disease patient. P-DCMs were created for both scenarios, which provided the basis for deriving instances for HL7 CDA and openEHR standards.

RESULTS

For proof of concept, we present case studies of encounter information for type 2 diabetes mellitus patients and monitoring of daily routine activities of an Alzheimer's disease patient. These reflect P-DCM-based customized mappings generation with openEHR and HL7 CDA standards. Customized mappings are generated based on the relationship of P-DCM concepts with CDA and openEHR concepts.

CONCLUSIONS

The objective of this work is to achieve semantic data interoperability among heterogeneous standards. This would lead to effective utilization of resources and allow timely information exchange among healthcare systems.

Innovation networks for improving access and quality across the healthcare ecosystem

Partnerships between patient communities, healthcare providers, and academic researchers are key to stepping up the pace and public health impact of clinical and translational research supported by the National Institutes of Health. With emphasis shifting toward community engagement and faster translation of research advances into clinical practice, academic researchers have a vital stake in widening the use of health information technology systems and telehealth networks to support collaboration and innovation. However, limited interaction between academic institutions and healthcare providers hinders the ability to form and sustain the integrated networks that are needed to conduct meaningful community-engaged research that improves public health outcomes. Healthcare providers, especially those affiliated with smaller practices, will need sustainable infrastructure and real incentives to utilize such networks, as well as training and additional resources for ongoing technical assistance.