Quality assurance plan for a vaccine preventable diseases surveillance program

Public health surveillance programs for vaccine preventable diseases (VPD) need functional quality assurance (QA) in order to operate with high quality activities to prevent preventable communicable diseases from spreading in the community. Having a functional QA plan can assure the performance and quality of a program without putting excessive stress on the resources. A functional QA plan acts as a check on the quality of day-to-day activities performed by the VPD surveillance program while also providing data that would be useful for evaluating the program. This study developed a QA plan that involves collection, collation, analysis and reporting of information based on standardized (predetermined) formats and indicators as an integral part of routine work for the vaccine preventable disease surveillance program at the City of Houston Department of Health and Human Services. The QA plan also provides sampling and analysis plans for assessing various QA indicators, as well as recommendations to the Houston Department of Health and Humans Services for implementation of the QA plan. The QA plan developed for VPD surveillance in the City of Houston is intended to be a low cost system that could serve as a template for QA plans as part of other public health programs not only in the city or the nation, but could be adapted for use anywhere across the globe. Having a QA plan for VPD surveillance in the City of Houston would serve well for the funding agencies like the CDC by assuring that the resources are being expended efficiently, while achieving the real goal of positively impacting the health and lives of the recipient/target population. ^

Is depression associated with insulin resistance? A systematic review

Studies suggest that depression affects glucose metabolism, and therefore is a risk factor for insulin resistance. The association between depression and insulin resistance has been investigated in a number of studies, but there is no agreement on the results. The objective of this study is to survey the epidemiological studies, identify the ones that measured the association of depression (as exposure) with insulin resistance (as outcome), and perform a systematic review to assess the reliability and strength of the association. For high quality reporting, and assessment, this systematic review used the outlined procedures, guidelines and recommendations for reviews in health care, suggested by the Centre for Reviews and Dissemination, along with recommendations from the STROBE group (Strengthening the Reporting of Observational Studies in Epidemiology). Ovid MEDLINE 1996 to April Week 1 2010, was used to identify the relevant epidemiological studies. To identify the most relevant set of articles for this systematic review, a set of inclusion and exclusion criteria were applied. Six studies that met the specific criteria were selected. Key information from identified studies was tabulated, and the methodological quality, internal and external validity, and the strength of the evidence of the selected studies were assessed. The result from the tabulated data of the reviewed studies indicates that the studies either did not apply a case definition for insulin resistance in their investigation, or did not state a specific value for the index used to define insulin resistance. The quality assessment of the reviewed studies indicates that to assess the association between insulin resistance and depression, specifying a case definition for insulin resistance is important. The case definition for insulin resistance is defined by the World Health Organization and the European Group for the Study of Insulin Resistance as the insulin sensitivity index of the lowest quartile or lowest decile of a general population, respectively. Three studies defined the percentile cut-off point for insulin resistance, but did not give the insulin sensitivity index value. In these cases, it is not possible to compare the results. Three other studies did not define the cut-off point for insulin resistance. In these cases, it is hard to confirm the existence of insulin resistance. In conclusion, to convincingly answer our question, future studies need to adopt a clear case definition, define a percentile cut-off point and reference population, and give value of the insulin resistance measure at the specified percentile.^