Evidence-Based Practice and Research
Instructions
Describe and evaluate the differences between evidence-based practice and research.
Describe the importance and application of health care information, data mining, and importance to application in patient care outcomes
Discuss how data mining and interpretation influences case management and utilization
Describe participation in managed care and the importance of quality care initiatives and performance indicators (remember to use AHRQ as a resource)
Parameters:
1000-1500 words not including the cover page and references (total, not for each topic)
Follow the APA 7th edition for references and citations
Include a minimum of 6 scholarly references (does not include text or websites)
Demonstrate analysis, evaluation, and synthesis of information
Sample Paper
Evidence-Based Practice and Research
Describe and Evaluate the Differences between Evidence-based Practice and Research
Research is a scientific process that involves answering research questions and testing hypotheses while using rigorous scientific methods. The aim of the research is to generate new knowledge or validate the existing knowledge based on specific theories. While it focuses on generating, discovering, and validating new and existing knowledge, it requires a comprehensive understanding of the scientific principles and methods for the results of the inquiry to be reliable, valid, and acceptable by others. Research involves collecting data, analyzing it to generate results, and interpreting the generated results to draw logical conclusions and make recommendations. Research can be either be qualitative or quantitative. Qualitative research focuses on people’s experiences or observations without manipulating the variables, while quantitative research involves the manipulation of variables under study to determine the impact on specific aspects (Nieswiadomy & Bailey, 2018).
Evidence-based practice, unlike research, does not focus on developing new knowledge or making discoveries; rather, it involves utilizing the best existing evidence to inform patient care decisions for improved outcomes. EBP mainly focuses on translating results generated in research to clinical practice. It also puts into consideration the experience of the care provider, patient preference, and values to determine the most appropriate intervention. The aim of evidence-based practice is to bridge the gap between nursing research and practice by implementing relevant findings from research to improve the quality of healthcare services. EBP has three main pillars: nursing research, clinical expertise, and patient preferences/values. EBP helps to develop care interventions that meet the patient’s unique needs and values, leading to improved healthcare experience and better patient outcomes (Albarqouni et al., 2018).
Describe the importance and application of health care information, data mining, and importance to application in patient care outcomes
Healthcare information refers to patients’ personal information concerning their health status and any other information related to their wellbeing. It includes information such as the symptoms and diagnosis, medical history of the patient, including diagnosis, treatment, surgeries, and other complications, patient’s genetic information, current prescriptions, and other information related to one’s health. Healthcare information is important in informing care providers’ decisions, such as determining diagnosis and the appropriate treatment for the patient. For example, when a patient presents to a healthcare facility, care providers rely on healthcare information such as symptoms, previous diagnosis, medications, and surgeries to make a diagnosis and initiate the right treatment for the patient. Health information is also important in preventive medicine since it helps determine individuals at risk of developing specific preventable conditions such as diabetes. By using a patient’s genetic information, care providers can be able to identify specific markers that increase the risk of a person developing certain conditions and therefore put in place relevant preventive strategies to protect the patient leading to better patient outcomes.
Data mining is a process that involves analyzing large sets of data to discover anomalies, patterns, and correlations with the aim of predicting future trends and occurrences. Data mining has two models, including descriptive and predictive models. Descriptive models are used to find patterns in data, which are then interpreted to make a conclusion about the topic of study. Predictive models are used to make predictions about possible future occurrences based on the evidence provided by the existing data. Data mining has several potential applications in healthcare, such as informing healthcare decisions to improve the quality of services (Sohail et al., 2019). Data mining can be used to determine symptoms patterns or occurrences of genetic markers or specific behaviors that contribute to the development of a condition, and such data can be used to develop prevention strategies for the identified conditions. Data mining can be used to measure the effectiveness of a treatment, a large set of data for patients receiving a specific drug can be analyzed to determine its effectiveness and associated side effects. It can also be used to detect a case of fraud and resource abuse in healthcare; this would involve analyzing data to identify unusual medical claims, prescriptions referrals, and other insurance claims. It can also assist in managing healthcare facilities by identifying the most effective management practices (Wu et al., 2021).
Discuss how Data Mining and Interpretation Influences Case Management and Utilization
Case management is a process that involves linking the patients with the appropriate care providers and facilities to achieve maximum benefits. The process involves assessment, care coordination, planning, advocacy, and evaluation of the care services that meet the needs of the patient and their families. Case managers assist patients in identifying the best care providers throughout the continuum of care while ensuring that available resources are allocated appropriately to ensure maximum value for the client (Thoma & Waite, 2018). Data mining can be used in case management to select the most appropriate healthcare providers. Case managers can analyze data/records to determine the previous performance of the existing care providers and facilities to predict the likelihood of their client receiving the most appropriate care to meet the needs. They can then make the appropriate recommendation to their clients based on such knowledge. Data mining can also be used to determine or predict the likely outcomes of a case, and therefore such knowledge can be used to select the most appropriate services while avoiding unnecessary treatments that may not improve the patient’s condition (Sohail et al., 2019).
Describe participation in managed care and the importance of quality care initiatives and performance indicators
Managed care is a system of healthcare delivery that allows health insurers to contract specific healthcare facilities or professionals to provide care to their customers at a lower price while still maintaining the high quality of the care services. Managed care ensures that patients receive quality healthcare services at a relatively lower cost. To determine the best available care providers, managed care organizations use quality indicators to assess the performance of a facility (Kaufman et al., 2019). Quality indicators are measures used to assess the quality of services based on the facility’s inpatient administrative data. They include inpatient quality indicators such as mortality rates which assess the efficiency of care services inside the hospitals. The prevention quality indicators focus on issues that relate to outpatient care, such as follow-ups after discharge, and also identify cases and complications that could have been avoided. Patient safety indicators identify all the hospital safety events and concerns, such as surgical complications and adverse events following medical procedures such as childbirth. These indicators represent opportunities for improvement in the delivery of healthcare services. Pediatric quality indicators assess preventable complications related to treatment among pediatric patients. Quality care initiatives are efforts that involve setting specific and measurable targets with an aim to improve the quality-of-care services provided. Quality care initiatives are built on the quality indicators, and they focus on the interventions, such as the preventive strategies that can be employed to avoid preventable conditions. Managed care organizations are nowadays involved in promoting quality care initiatives that ensure that their clients practice healthy lifestyle behaviors, which reduces the need for treatments, reducing the cost incurred in reimbursements to health facilities and providers (Agency for Healthcare Research and Quality, 2021).
References
Agency for Healthcare Research and Quality, (2021) Quality Improvement and monitoring at your fingertips Retrieved from: https://qualityindicators.ahrq.gov/
Albarqouni, L., Hoffmann, T., Straus, S., Olsen, N. R., Young, T., Ilic, D., … & Glasziou, P. (2018). Core competencies in evidence-based practice for health professionals: consensus statement based on a systematic review and Delphi survey. JAMA network open, 1(2), e180281-e180281. https://jamanetwork.com/journals/jamanetworkopen/article-abstract/2685621
Kaufman, B. G., Spivack, B. S., Stearns, S. C., Song, P. H., & O’Brien, E. C. (2019). Impact of accountable care organizations on utilization, care, and outcomes: a systematic review. Medical Care Research and Review, 76(3), 255-290. https://journals.sagepub.com/doi/abs/10.1177/1077558717745916
Nieswiadomy, R. M., & Bailey, C. (2018). Foundations of nursing research. https://mtshohoe.edu.gh/library/index.php?p=show_detail&id=804&keywords=ebook
Seehusen, C., Britton, R., & Duys, D. (2021). Managed care organizations in counseling practice, research, and education.
Sohail, M. N., Jiadong, R., Uba, M. M., & Irshad, M. (2019). A comprehensive looks at data mining techniques contributing to medical data growth: a survey of researcher reviews. In Recent developments in intelligent computing, communication and devices (pp. 21-26). Springer, Singapore. https://link.springer.com/chapter/10.1007/978-981-10-8944-2_3
Thoma, J. E., & Waite, M. A. (2018). Experiences of nurse case managers within a central discharge planning role of collaboration between physicians, patients and other healthcare professionals: A sociocultural qualitative study. Journal of clinical nursing, 27(5-6), 1198-1208. https://onlinelibrary.wiley.com/doi/full/10.1111/jocn.14166?casa_token
Wu, W. T., Li, Y. J., Feng, A. Z., Li, L., Huang, T., Xu, A. D., & Lyu, J. (2021). Data mining in clinical big data: the frequently used databases, steps, and methodological models. Military Medical Research, 8(1), 1-12. https://mmrjournal.biomedcentral.com/articles/10.1186/s40779-021-00338-z
