NUR-550: Translational research and population health management course learners examine the process of scientific inquiry, knowledge generation, utilization, and dissemination of evidence into advanced nursing practice in order to propose quality-improvement initiatives that advance the delivery of safe, high-quality care for patient populations. Additionally, learners also critically evaluate evidence, including scientific findings from the biopsychosocial fields, epidemiology, biostatistics, genetics, and genomics. They then apply levels of evidence and theoretical frameworks to design culturally appropriate clinical prevention interventions and population-based care that reduces risks, prevents disease, and promotes health and well-being.
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With our assignment help, students learn how to consider strategies to evaluate health policy and advocacy issues, the state of health care delivery, patient-centered care, and ethical principles related to health beliefs, health promotion, and risk reduction for diverse populations. Moreover, students apply these strategies to work towards recognizing gaps in nursing and health care knowledge, identifying potential solutions or innovations for those gaps, planning and implementing practice changes, and evaluating the outcomes in order to improve practice.
What is translational research?
Translational research works as a connection between science and practice. That is, it links laboratory science with patients and findings with the needs of the community. In other words, translational research is the link between different areas of research, connecting their findings to each other, and to the community at large.
Translational research involves the following:
- Inspires and promotes multidisciplinary teamwork among laboratory and clinical researchers.
- Integrates the desires of the general public, with communities being engaged to determine their needs for health innovation.
- Recognizes and supports the adoption of best medical and health practices.
Difference between translational research and clinical research?
While translational research is the connection between different areas of research, connecting their findings to each other, and to the community at large, clinical research involves the studying of human subjects through surveys, health services research, or clinical trials.
Summarized stages of translational research.
T1 research involves testing finding from basic research for clinical effect and applicability. It generates knowledge about human physiology and the potential for invention.
Some examples of the approaches in this step are preclinical and animal studies, human physiology, proof of concept, and phase 1 clinical trials.
This step involves testing new inventions in controlled environments to form the basis for clinical application and evidence-based instructions. During this stage, there is the generation of knowledge about the efficacy of the interventions in optimal settings.
This step involves approaches such as phase 2 clinical trials and phase 3 clinical trials.
T3 research involves the study of ways of applying recommendations or guidelines in general practice. Thus, during this stage, there is the generation of T3 knowledge about how interventions work in real-world settings.
Some of the approaches in this step include:
- Phase IV Clinical Trials.
- Health Services Research
- Clinical Outcomes Research
T4 research explores the factors and interventions that have an effect on the health of populations. Therefore, this stage T4 results in improved global health.
Approaches used in this stage include:
- Population-level Outcome Studies
- Social Determinants of Health.
What is population health management?
Population health management is an approach to primary health care (PHC) delivery that incorporates active outreach and engagement with the community in care delivery. This approach usually shifts primary care service delivery from reactive to proactive management of a part of a population.
The four components of population health management.
- Emphasis on primary care.
- Cautious data-driven environment.
- Physician leadership.
- Off-the-radar disease management.