ABSTRACT
Introduction: Biomedical waste (BMW) generated is a matter of great concern as it consists of high levels of hazardous waste. The lack of segregation and disposal policy in India leads to use of such infectious waste in day-to-day life [1]. Lack of awareness about segregation of Biomedical Waste (BMW) at source is a major cause for Hospital Acquired Infection (HAI) and increased risk of contamination of hospital and external environment. Materials & Methods: To address the problem, we decided to train interns and health care workers to increase their awareness about BMW segregation and thereby reduce HAI. The program was run in 3 phases. In the 1st phase need assessment was done as to how important and effective this program would be in controlling HAI. The 2nd phase comprised of identifying the stake holders in the program who will play the key role in implementing the program effectively. The 3rd phase of Biomedical Segregation Program BMWSP focused on the outcomes as enumerated in the Kirkpatrick model [2], viz., participants’ reaction, learning, change in behavior and results. Measuring the impact of the program on the learners at these four levels revealed the effectiveness of the program. Results: To overcome the shortfalls in the Kirkpatrick model we used Logic model which took care of the instructional design. Logic model is better suitable for evaluating BMWSP as it considers inter-relation between constituents in a sequence and their effect on the process as well as product providing the necessary roadmap from the planned work (inputs and activities) to the intended results (outputs, outcomes and impact). It is a sequence of events connecting each other starting with Resources / Inputs, Activities, Outputs, Outcomes and Impact. The model helped medical interns and dental students to understand the importance for BMWSP and also made a significant difference in its implementation. Conclusion: The program helped in making the health care staff more aware about BMWSP. It also increased their knowledge, and helped in implementation of the program. This will significantly reduce HAI and overall benefit the society.
ABSTRACT
Introduction: Type 2 diabetes is the third largest cause of mortality in the United Kingdom, with about 50% of patients’ having developed complications at time of diagnosis. We consider that the evidence which explores the actual hazard ratios of mortality has not been consistent. n this paper we discuss methodology and review the most recent accurate data on mortality in type 2 diabetes. Methods: A systematic review will be undertaken aimed at synthesis of evidence of relative risk of mortality in type 2 diabetes, using the Centre for Reviews and Dissemination guidelines. We will explore conflicting and unanswered questions in relation to mortality. The primary outcome is all-cause, overall-cause or total mortality expressed as hazard ratios. Sub-groups will also be explored; age, gender, socio-economic factors and causes of death. We will review abstracts published after 1990 in the English language. Our data source will include electronic databases; the Cochrane library, the Centre for Reviews and Dissemination, Medline/PubMed, and other grey literature. The study populations are type 2 diabetes patients whose mortality outcome, expressed as hazard ratio, has been evaluated. Data extraction will be undertaken by one reviewer and triangulated by the second and third reviewer. The quality of the included studies will be evaluated in accordance with the inclusion/exclusion criteria; methodological quality that meets the critical appraisal framework and the relevance to the research questions. Evidence from data will be synthesised through a descriptive epidemiological review from included studies; meta-analysis will be used if appropriate. Result & Conclusion: We expect to pool homogenous studies of large population cohorts which explore the hazard ratio of mortality, and to summarise the evidence of the actual mortality risk in type 2 diabetes, with limited bias. This will help direct future research in areas of unanswered questions and may influence healthcare policy decisions.