2023 POST 1 Lodian Mixed method research assists in answering a research question from several perspectives
Nursing 2023 Reply with a comment to each post with 2 reference below each post.
POST 1 Lodian Mixed method research assists in answering a research question from several perspectives 2023 Assignment
POST 1
Lodian
Mixed method research assists in answering a research question from several perspectives and ensure there are limited gaps in the information collected (Kaur, 2016). Mixed method research offers a richer explanation than a single use of either qualitative or quantitative methods as it can draw on the strength of each approach and overcome their weaknesses. Mixed methods research is a well‐established research approach that integrates qualitative and quantitative method to understand the phenomenon of interest (Irvine et al., 2020). Mixed method research is known to enhance qualitative and quantitative research strengths and compensate for any limitations of the individual approaches, thereby offering multiple ways of evaluating a phenomenon (Irvine et al., 2020). In the article, The Role of Simulation in Mixed-Methods Research: A Framework and Application to Patient Safety, reviewed patient safety as a national priority (Guise et al., 2017). A mixed-method research approach was utilized to simulate a multi-dimensional approach to patient safety across all age groups. The mixed-method research approach is beneficial as it helps to capture missing details that would be missing or lacking from a qualitative or quantitative approach (McKenna et al., 2021).
A challenge that may present when using a mixed-method in the study selected is the age groups may offer different forms of understanding and interaction that may not be easily measured quantitatively (Guise et al., 2017). Also, the simulation may provide hypotheses generated from other formative research approaches and quantitative tests that may not validate specific measures. Other challenges and limitations may occur from constraints of the focus groups, or lack of representativeness due to small sample sizes or limited geographic area (Guise et al., 2017).
References
Guise, J. M., Hansen, M., Lambert, W., & O’Brien, K. (2017). The role of simulation in mixed-methods research: a framework & application to patient safety. BMC Health Services Research, 17, 1-7. https://doi.org/10.1186/s12913-017-2255-7
Irvine, F. E., Clark, M. T., Efstathiou, N., Herber, O. R., Howroyd, F., Gratrix, L., Sammut, D., Trumm, A., Hanssen, T. A., Taylor, J., & Bradbury, J. C. (2020). The state of mixed methods research in nursing: A focused mapping review and synthesis. Journal of Advanced Nursing, 76, 2798-2809. https://doi.org/10.1111/jan.14479
Kaur, M. (2016). Application of mixed method approach in public health research. Indian Journal of Community Medicine, 41(2), 93-97. https://doi.org/10.4103/0970-0218.173495
McKenna, L., Copnell, B., & Smith, G. (2021). Getting the methods right: Challenges and appropriateness of mixed methods research in health‐related doctoral studies. Journal of Clinical Nursing, 30, 581-587. https://doi.org/10.1111/jocn.15534
POST 2
Jacqueline
A mixed-methods review is a research approach whereby researchers collect and analyze quantitative and qualitative data within the same study ( Bowers et al., 2013). Selecting the correct research method starts with identifying the research question and study aims.
The mixed-methods design is appropriate for answering research questions that neither quantitative nor qualitative methods could answer alone. ( Ivankova, 2006). The practice situation for the discussion board this week is to Identify stress levels among new graduate registered nurses working in the Intensive Care Unit. With this research question, qualitative and quantitative data would strengthen the study; therefore, the mixed method is used.
Quantitative data could measure levels of workplace stress using surveys, while qualitative data can complete personal interviews with the new nurses and obtain personal experiences with the stressful work environment. The combination of data will make for a great study giving the researcher the ability to combine personal experiences with national data.
There are challenges with every study, so it is expected in this study as well. Some of the challenges expected include the concern that more resources and time will be required. Additionally, mixed-method studies usually incur a large volume of data, so there may be some challenges with synthesizing the data and making it useful for practice.
The benefits of using a mixed-method will, however, outweigh any challenges the researcher will incur. Mixed methods can be used to gain a better understanding of connections or contradictions between qualitative and quantitative data; it can provide opportunities for participants to have a strong voice and share their experiences across the research process, and they can facilitate different avenues of exploration that enrich the evidence and enable questions to be answered more deeply. (Wisdom et al., 2013 ). Furthermore, mixed methods can facilitate more significant scholarly interaction and enrich the experiences of researchers as different perspectives help clarify the issues being studied.
Mixed method research is very beneficial to health care and adds new insight and information to strengthen evidence-based practice. As providers, health care administrators, and policymakers strive to ensure quality and safety for patients and families, researchers can use mixed methods to explore contemporary health care trends and practices across increasingly diverse practice settings and patient populations.
Reference:
Bowers B, Cohen LW, Elliot AE, (2013). Creating and supporting a mixed methods health services research team. Health Serv Res (48) pp.2157–80.
Ivanova NV. Using mixed-methods sequential explanatory design: from theory to practice. Field methods 2006;18:3–20.
Wisdom J, Creswell JW. Mixed methods: integrating quantitative and qualitative data collection
and analysis while studying patient-centered medical home models. Rockville, MD: Agency for Healthcare Research and Quality, 2013.
POST 3
Lolade
Differentiate the process of evaluating health information technology systems from other types of evaluation in health care. What specific strategies might you employ for an information system evaluation? What factors might you examine to judge the system’s effectiveness?
Evaluation of health information technology is an important practice in health organizations. The evaluation provides insights into the effectiveness of the technology in facilitating the desired success in the organization. The evaluation of health information technologies however, differ from other types of evaluation in healthcare. Accordingly, the evaluation in health information technology is multifaceted in nature with a focus placed on human, social, technology and timing factors. The evaluation based on technology factors focuses on the structural qualities of the hardware, software, and functionality of the system. The evaluation based on human factors examines whether the system addresses the needs of the users. The data from the evaluation of human factors is used for optimizing technology function and ensuring that users benefit from the technology. The evaluation based on social factors examines the influence of the technology on human behaviors. Lastly, evaluation based on timing factors determines whether the technology provides the needed information for making efficient and effective organizational decisions (Comite, 2017). The above approaches to evaluation differ from the other evaluations that aim at process and outcome measures alone.
Assess the main challenges of designing a successful information system evaluation
One of the strategies that I will employ in the evaluation of health information systems is incorporating inter-professional teams in the process. The mix of the professional backgrounds will strengthen the quality of evaluation data. The other strategy is evaluating the system against the pre-developed metrics of assessment. This will ensure objectivity in the evaluation process. Some of the factors that I will judge to determine the effectiveness of the system include user experiences, protection of data integrity, interoperability, efficiency, timeliness of data, and cost of maintenance and use. The main challenges in designing a successful information system evaluation include the lack of a defined approach to system evaluation. The other challenges include inadequate planning, voluminous data, bad data, and the use of ineffective approaches to system evaluation (Kawachi et al., 2020). Therefore, proven interventions in the industry should be applied in the system evaluation process.
References
Saba, V. K., & McCormick, K. A. (2021). Essentials of Nursing Informatics, 7th Edition. McGraw-Hill Education
Singh, R., & Ramdeo, S. (2020). Leading Organizational Development and Change: Principles and Contextual Perspectives. Springer Nature.
POST 4
Shelby
Implementations require thorough appraisal, especially when differentiating health information technology systems to evaluate the advantages, disadvantages, and implications it has for clinical practice. Doctorally prepared nurses become increasingly more engaged in decision making and consequently, capability to evaluate and facilitate the election of health information technology is critical. Being equipped with skills relative to the various domains of nursing practice is imperative.
Differentiating Evaluation Processes, Strategizing, and Judging Efficacy
Processes for evaluating health information technology systems is different than other types of evaluation in health care. Historically speaking, the majority of evaluations focused on system efficacy, quality care, user and patient satisfaction, and usability through subjective methodology and the quantification of cost and advantages (Rahio &Vimarlund, 2007, p. 429). Evaluation of health information systems requires the application of theoretical models that guide appraisal of advantages and disadvantages (Harkness, Hawcutt, Neame, Roberts, Sefton, & Sinha, 2020, p. 2). The application of theoretical frameworks for the evaluation of health information systems and health care in general is a similarity. HIT system evaluation includes, but is not limited to, attention to health resources, patient and user satisfaction, quality and process outcomes, adverse events, data quality and reliability, social engagement amongst all entities engaged in care, usability, diagnostic reliability, alterations in accessibility, referral rates, configurability, applicable use training, user technology competency levels, and infrastructure (Harkness, Hawcutt, Neame, Roberts, Sefton, & Sinha, 2020, p. 5). These are some of the factors that are examined to critique a system’s efficacy. Ultimately evaluation in health care is typically relative to patient condition status and patient outcomes or satisfaction. In regard to HIT system evaluations, delineating cause and effect as it impacts usability, interoperability, workflow, continuity of care, patient outcomes, and organizational functioning requires additional skills and knowledge, as opposed to the evaluation of patients and care processes which is a fundamental component of one’s professional-specific education and training.
Specific strategies that are applicable to optimally evaluating health information technology systems includes competencies. According to the American Nurses Association (2008), evaluation competencies include the ability to conduct systematic, ongoing, and criterion-based evaluations of structures, processes, and project, the ability to collaborate with key stakeholders, the ability to identify and strategize toward goal attainment, the ability to evaluate evidence-based approaches and outcomes, the ability to evaluate strategy efficacy, the ability to document outcomes, and the ability to disseminate results in accordance with legislation and policy (p. 78). The competencies are critical to the evaluation of HIT systems. Strategic approaches focus on collaboration with the interest of all stakeholders and entities being considered. Additionally, time-oriented goals with anticipated outcomes should be mutually understood and prioritized. Outcome measures including economic outcomes, patient outcomes, user implications, workflow, satisfaction, safety, and quantifying adverse outcomes is one way of judging the system’s efficacy.
Challenges of Designing Successful Information System Evaluations
As with all processes or interventions, barriers are anticipated and require diligent efforts to both diminish and resolve. Challenges to designing a successful information system evaluation is related resources, both financial and personnel. Additionally, other barriers include the inability to correlate information technology investments to objective outcomes due to a lack of case-control designs (Rahio & Vimarlund, 2007, p. 430). The challenges associated with generalizing a solitary study that is applicable to clinical practice on a larger scale is another hinderance (Rahio & Vimarlund, 2007, p. 430. With this being said, limitations of designing successful information system evaluations are relative to a deficit in strong scholarly recommendations and empirical evidence that indicates a superior approach. A lack of resources coupled with insufficient guidelines and frameworks is contributory to the challenges of designing a successful and operation information system evaluation.
References
American Nurses Association. (2008). Nursing Informatics: Scope and standards of practice. Silver Spring, MD: Author.
Rahio, B., & Vimarlund, V. (2007). Methods to evaluate health information systems in healthcare settings: A literature review. Journal of Medical Systems, 31(5), 397-432. doi:10.1007/s10916-007-9082-z. Retrieved from https://www-proquest-com.ezp.waldenulibrary.org/docview/757015619/fulltextPDF
Harkness, D., Hawcutt, D. B., Neame, M. T., Roberts, M., Sefton, G., & Sinha, I. P. (2020). Evaluating health information technologies: A systematic review of framework recommendations. International Journal of Medical Informatics, 142, 1-9. doi:10.1016/j.ijmedinf.2020.104247. Retrieved from https://ezp.waldenulibrary.org/login?url=https://search.ebscohost.com/login.aspx?direct=true&db=edselp&AN=S1386505620308261&site=eds-live&scope=site
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