The use of telehealth for diabetes management: a qualitative study of telehealth provider perceptions

BACKGROUND: Monitoring and Messaging Devices (MMDs) are telehealth systems used by patients in their homes, and are designed to promote patient self-management, patient education, and clinical monitoring and follow-up activities. Although these systems have been widely promoted by health care systems, including the Veterans Health Administration, very little information is available on factors that facilitate use of the MMD system, or on barriers to use. METHODS: We conducted in-depth qualitative interviews with clinicians using MMD-based telehealth programs at two Veterans Affairs Medical Centers in the Midwestern United States. RESULTS: Findings suggest that MMD program enrollment is limited by both clinical and non-clinical factors, and that patients have varying levels of program participation and system use. Telehealth providers see MMDs as a useful tool for monitoring patients who are interested in working on management of their disease, but are concerned with technical challenges and the time commitment required to use MMDs. CONCLUSION: Telehealth includes a rapidly evolving and potentially promising range of technologies for meeting the growing number of patients and clinicians who face the challenges of diabetes care, and future research should explore the most effective means of ensuring successful program implementation

Assessing batch effects of genotype calling algorithm BRLMM for the Affymetrix GeneChip Human Mapping 500 K array set using 270 HapMap samples

<p>Abstract</p> <p>Background</p> <p>Genome-wide association studies (GWAS) aim to identify genetic variants (usually single nucleotide polymorphisms [SNPs]) across the entire human genome that are associated with phenotypic traits such as disease status and drug response. Highly accurate and reproducible genotype calling are paramount since errors introduced by calling algorithms can lead to inflation of false associations between genotype and phenotype. Most genotype calling algorithms currently used for GWAS are based on multiple arrays. Because hundreds of gigabytes (GB) of raw data are generated from a GWAS, the samples are typically partitioned into batches containing subsets of the entire dataset for genotype calling. High call rates and accuracies have been achieved. However, the effects of batch size (i.e., number of chips analyzed together) and of batch composition (i.e., the choice of chips in a batch) on call rate and accuracy as well as the propagation of the effects into significantly associated SNPs identified have not been investigated. In this paper, we analyzed both the batch size and batch composition for effects on the genotype calling algorithm BRLMM using raw data of 270 HapMap samples analyzed with the Affymetrix Human Mapping 500 K array set.</p> <p>Results</p> <p>Using data from 270 HapMap samples interrogated with the Affymetrix Human Mapping 500 K array set, three different batch sizes and three different batch compositions were used for genotyping using the BRLMM algorithm. Comparative analysis of the calling results and the corresponding lists of significant SNPs identified through association analysis revealed that both batch size and composition affected genotype calling results and significantly associated SNPs. Batch size and batch composition effects were more severe on samples and SNPs with lower call rates than ones with higher call rates, and on heterozygous genotype calls compared to homozygous genotype calls.</p> <p>Conclusion</p> <p>Batch size and composition affect the genotype calling results in GWAS using BRLMM. The larger the differences in batch sizes, the larger the effect. The more homogenous the samples in the batches, the more consistent the genotype calls. The inconsistency propagates to the lists of significantly associated SNPs identified in downstream association analysis. Thus, uniform and large batch sizes should be used to make genotype calls for GWAS. In addition, samples of high homogeneity should be placed into the same batch.</p

The importance of organizational characteristics for improving outcomes in patients with chronic disease: a systematic review of congestive heart failure

Luci K. Leykum, Jacqueline Pugh, Valerie Lawrence, and Polly H. Noel are with the South Texas Veterans Health Care System and Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio TX, 78229, USA -- Michael Parchman is with the South Texas Veterans Health Care System and Department of Family and Community Medicine, University of Texas Health Science Center at San Antonio, San Antonio TX, 78229, USA -- Reuben R. McDaniel Jr. is with the McComb's School of Business, University of Texas at Austin, Austin TX, USABackground: Despite applications of models of care and organizational or system-level interventions to improve patient outcomes for chronic disease, consistent improvements have not been achieved. This may reflect a mismatch between the interventions and the nature of the settings in which they are attempted. The application of complex adaptive systems (CAS) framework to understand clinical systems and inform efforts to improve them may lead to more successful interventions. We performed a systematic review of interventions to improve outcomes of patients with congestive heart failure (CHF) to examine whether interventions consistent with CAS are more likely to be effective. We then examine differences between interventions that are most effective for improving outcomes for patients with CHF versus previously published data for type 2 diabetes to explore the potential impact of the nature of the disease on the types of interventions that are more likely to be effective. Methods: We conducted a systematic review of the literature between 1998 and 2008 of organizational interventions to improve care of patients with CHF. Two independent reviewers independently assessed studies that met inclusion criteria to determine whether each reported intervention reflected one or more CAS characteristics. The effectiveness of interventions was rated as either 0 (no effect), 0.5 (mixed effect), or 1.0 (effective) based on the type, number, and significance of reported outcomes. Fisher's exact test was used to examine the association between CAS characteristics and intervention effectiveness. Specific CAS characteristics associated with intervention effectiveness for CHF were contrasted with previously published data for type 2 diabetes. Results and discussion: Forty-four studies describing 46 interventions met eligibility criteria. All interventions utilized at least one CAS characteristic, and 85% were either 'mixed effect' or 'effective' in terms of outcomes. The number of CAS characteristics present in each intervention was associated with effectiveness (p < 0.001), supporting the idea that interventions consistent with CAS are more likely to be effective. The individual CAS characteristics associated with CHF intervention effectiveness were learning, self-organization, and co-evolution, a finding different from our previously published analysis of interventions for diabetes. We suggest this difference may be related to the degree of uncertainty involved in caring for patients with diabetes versus CHF. Conclusion: These results suggest that for interventions to be effective, they must be consistent with the CAS nature of clinical systems. The difference in specific CAS characteristics associated with intervention effectiveness for CHF and diabetes suggests that interventions must also take into account attributes of the disease.McCombs School of [email protected]

Home Telehealth Uptake and Continued Use Among Heart Failure and Chronic Obstructive Pulmonary Disease Patients: a Systematic Review

Background Home telehealth has the potential to benefit heart failure (HF) and chronic obstructive pulmonary disease (COPD) patients, however large-scale deployment is yet to be achieved. Purpose The aim of this review was to assess levels of uptake of home telehealth by patients with HF and COPD and the factors that determine whether patients do or do not accept and continue to use telehealth. Methods This research performs a narrative synthesis of the results from included studies. Results Thirty-seven studies met the inclusion criteria. Studies that reported rates of refusal and/or withdrawal found that almost one third of patients who were offered telehealth refused and one fifth of participants who did accept later abandoned telehealth. Seven barriers to, and nine facilitators of, home telehealth use were identified. Conclusions Research reports need to provide more details regarding telehealth refusal and abandonment, in order to understand the reasons why patients decide not to use telehealth

Network-Guided Analysis of Genes with Altered Somatic Copy Number and Gene Expression Reveals Pathways Commonly Perturbed in Metastatic Melanoma

Cancer genomes frequently contain somatic copy number alterations (SCNA) that can significantly perturb the expression level of affected genes and thus disrupt pathways controlling normal growth. In melanoma, many studies have focussed on the copy number and gene expression levels of the BRAF, PTEN and MITF genes, but little has been done to identify new genes using these parameters at the genome-wide scale. Using karyotyping, SNP and CGH arrays, and RNA-seq, we have identified SCNA affecting gene expression (‘SCNA-genes’) in seven human metastatic melanoma cell lines. We showed that the combination of these techniques is useful to identify candidate genes potentially involved in tumorigenesis. Since few of these alterations were recurrent across our samples, we used a protein network-guided approach to determine whether any pathways were enriched in SCNA-genes in one or more samples. From this unbiased genome-wide analysis, we identified 28 significantly enriched pathway modules. Comparison with two large, independent melanoma SCNA datasets showed less than 10% overlap at the individual gene level, but network-guided analysis revealed 66% shared pathways, including all but three of the pathways identified in our data. Frequently altered pathways included WNT, cadherin signalling, angiogenesis and melanogenesis. Additionally, our results emphasize the potential of the EPHA3 and FRS2 gene products, involved in angiogenesis and migration, as possible therapeutic targets in melanoma. Our study demonstrates the utility of network-guided approaches, for both large and small datasets, to identify pathways recurrently perturbed in cancer

Omics-based molecular techniques in oral pathology centred cancer: Prospect and challenges in Africa

: The completion of the human genome project and the accomplished milestones in the human proteome project; as well as the progress made so far in computational bioinformatics and “big data” processing have contributed immensely to individualized/personalized medicine in the developed world.At the dawn of precision medicine, various omics-based therapies and bioengineering can now be applied accurately for the diagnosis, prognosis, treatment, and risk stratifcation of cancer in a manner that was hitherto not thought possible. The widespread introduction of genomics and other omics-based approaches into the postgraduate training curriculum of diverse medical and dental specialties, including pathology has improved the profciency of practitioners in the use of novel molecular signatures in patient management. In addition, intricate details about disease disparity among diferent human populations are beginning to emerge. This would facilitate the use of tailor-made novel theranostic methods based on emerging molecular evidences