Benchmark- Evidence-Based Practice Project Proposal Discussion

Benchmark- Evidence-Based Practice Project Proposal Discussion

The expanding healthcare sector is becoming more patient-centered and systems are being developed to enhance proper performance by care workers and better patient outcomes. With respect to this, there is a need to evaluate the organizational culture by excluding behaviors, ceremonies, observable symbols, and other values, assumptions, and beliefs in healthcare organizations. This is because by highlighting the organizational culture there is a better representation of shared feelings, behaviors, and thinking (Gabutti et al., 2023). In addition, organizational readiness is the situation whereby the members of an organization are behaviorally and psychologically willing to enhance the proposed change. Through organizational readiness, the use of tools like RACT will be applied to improving safety and workplace health (Ellis wet al., 2023). The paper evaluates the organizational culture and readiness through healthcare and towards improving outcomes, developing readiness strategies, stakeholder’s roles, and identifying appropriate technologies for evidence-based practice interventions. Benchmark- Evidence-Based Practice Project Proposal Discussion

Centre for Disease Control (CDC) Culture

CDC is the leading service organization across the nation in terms of creating data-driven and science-based evaluations of public health concerns. The organization’s mission is to work around the clock to protect the citizens by enhancing safety, health, and security threats in terms of disease breakouts. The most critical roles of the CDC are to identify and respond to emerging health issues, encounter health issues causing disabilities, and use science to advance technology in healthcare. CDC enhances the safety and health of its employees through the support of policies and workplace programs. The establishment of culture and readiness for change in the organization is consistent in safety operations where everyone is given the responsibility of reporting and implementing safety. There is also a free environment that reduces the extent of errors since workers executive their duties without fear of punishment or reprimand. For instance, the focus of any healthcare organization is its people hence the need to influence kindness, empathy, respect, trust, and honesty when patients and staff interact (Frieden, 2020).

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Risk Assessment and Categorization Tool (RACT)

The RACT instrument helps in identifying risk, data, and processes and also managing portfolios through collaboration and electronic processes the importance of this tool is to make the operations of healthcare organizations more seamless and simplified. This is because as organizations become more complex with big data, management systems bigger geographical locations, and larger teams there is a need for more sophisticated tools. The tool excellently replaces the traditional models of risk trackers in organizations by enhancing efficiency. Also, the tool helps in building compliance which reduces the possibility of critical events and routines being missed (Jaguste, 2019). The tool is also future-proof that expanding data volumes will be adequately managed. The tool is also customizable to ensure lead users are able to configure it to their firms and perfect their operations. This tool can be critical for highlighting major data and risk issues across the CDC and making critical change initiatives. It will also be paramount in identifying the content and the resources available and also the capacity to bring the most needed change to the organization (Gabutti et al., 2023). Benchmark- Evidence-Based Practice Project Proposal Discussion

Improving Quality, Safety, and Cost-effectiveness

The CDC being a data-driven organization in healthcare should enhance better and more focused clinical interventions. The organization should improve the risk assessments of dangerous diseases across the communities and also along the borders. This will help in initiating quality improvement through collaboration with healthcare facilities, government agencies, and leading researchers. Also, after collecting data and making critical analysis there is a need to bring care providers together and make radical decisions about the way to address the emerging or serious disease in a given region (Jaguste, 2019). The use of RACT will be a special tool in this aspect since it will used in swiftly making risk assessments across every area to ascertain the level of spread and the infections from disease. Such will improve planning and readiness for the organization in addressing the health issues and lobbying for necessary resources (Frieden, 2020).

Enhancing Organizational Readiness

Readiness for change in an organization is vital in ensuring the success of EBP interventions. Some of the methods that can be used in raising awareness for change include creating a culture of innovation, leadership engagement, and having the urge for change. Execution of these strategies is ideal for the integration of EBP interventions and making sure there is proper access to beneficial information (Ellis wet al., 2023).

Stakeholders and Team members

A well-formulated committee of representative members will be created to govern this change. The team will involve nurse informatics, nurse leaders, administrators, emergency staff, managers, It technologists, and external sponsors. The management and the leaders will be leading resource allocation for the project while the team of nurses and informatics will help in designing the most suitable elements of the project. The IT personnel will lean into creating and regular improvement of the reporting tool (Gabutti et al., 2023). Benchmark- Evidence-Based Practice Project Proposal Discussion

Information and Communication Technologies

Healthcare delivery systems can be adequately supported through the use of information and communication technologies. Important technologies to use in this project include electronic health records (EHR), tele-monitoring, web-based services, and alert systems (Jaguste, 2019).

 References

Ellis, L. A., Tran, Y., Pomare, C., Long, J. C., Churruca, K., Saba, M., & Braithwaite, J. (2023). Hospital organizational change: The importance of teamwork culture, communication, and change readiness. Frontiers in public health11, 1089252. https://doi.org/10.3389/fpubh.2023.1089252

Frieden T. (2020). A Strong Public Health System: Essential for Health and Economic Progress. China CDC Weekly2(8), 128–130.

Gabutti, I., Colizzi, C., & Sanna, T. (2023). Assessing Organizational Readiness to Change through a Framework Applied to Hospitals. Public Organization Review23(1), 1–22. https://doi.org/10.1007/s11115-022-00628-7

Jaguste V. S. (2019). Risk-based monitoring: Review of the current perceptions and toward effective implementation. Perspectives in clinical research10(2), 57–61. https://doi.org/10.4103/picr.PICR_18_18

Introduction

Obesity is one of the most prevalent health threats, with its prevalence linked to high mortality and morbidity rates, along with increased healthcare costs. It is linked with several non-communicable diseases such as diabetes, cardiovascular diseases, and some cancers that add to the healthcare expenses and decrease health standards. Obesity can only be solved by developing efficient and long-term treatment solutions that treat patients and help them improve their lives. This paper proposes to systematically evaluate the evidence on the efficacy of particularised, enhanced LCMs that include diet and exercise in managing obesity in adults with the condition. The guiding PICOT statement is: In persons of 18 years and older with obesity, does using an individualized, intensive lifestyle modification mobile application program with dietary changes and exercise compared with routine care result in weight loss over six months? Benchmark- Evidence-Based Practice Project Proposal Discussion

Search Methods

The rigorous method for selecting and searching for articles was used on scientific databases, including PubMed, CINAHL, PsycINFO, and Google Scholar. In the search process, the emphasis was placed on individualized LMP and the availability of articles published between 2020 and 2024 in peer-reviewed journals only. These keywords were used when searching for materials on obesity, personal change, dieting, exercise, and weight loss.

The inclusion criteria of selecting high-quality studies were applied to screen the studies. Considerations for the studies were the inclusion of adult groups, the use of individually tailored behavioral programs, and weight loss as the measure of effectiveness. Eliminated were papers related to children, articles not in English, and those that focused on surgical and pharmacologic methods of weight management to stay on the subject of lifestyle modifications. A total of six articles were retrieved from the databases and critically reviewed based on how they related to the PICOT question; however, four articles were ultimately selected based on the method used and the overall quality of the studies. Benchmark- Evidence-Based Practice Project Proposal Discussion

 

 Articles Reviewed

Article Research Question, Hypothesis, Purpose or Aim of Study Study Design Setting and Sample Methods Analysis and Data Collection Outcomes and Key Findings Recommendations
Vaz et al. (2021)

https://onlinelibrary.wiley.com/doi/abs/10.1002/osp4.503

To investigate how a smartphone app-delivered lifestyle intervention affects an obese person’s ability to lose weight. Randomized controlled trial 28 obese adults aged 21-48 years with a BMI of 25-42 kg/m2 in sedentary occupations The intervention group received a smartphone app with activity trackers, food logs, and personalized coaching; the control group received no intervention. At baseline and six months later, measurements of weight, BMI, and metabolic health indicators were taken. ANOVA and paired t-tests were among the statistical tests used. Significant weight reduction and improved metabolic health in the intervention group (p < 0.05). Support for tech-based individualized interventions in weight management. Mobile technology can significantly reduce weight within six months.
Beleigoli et al. (2020) https://www.jmir.org/2020/11/e17494/ To evaluate the impact of web-based interventions with or without personalized feedback on weight loss. Randomized controlled trial 1298 university students and staff in Brazil with BMI ≥ 25 kg/m2 The intervention group was assigned a web platform with personalized feedback from a dietitian; the control group received a general health information e-booklet. BMI and weight were assessed both at baseline and six months later. Regression analysis and ANCOVA were the two statistical tests used. Greater weight loss in the intervention group with personalized feedback (p < 0.05). Higher involvement and compliance were reported. Personalized feedback enhances the efficacy of web-based weight loss interventions.
Lugones-Sanchez et al. (2022)

https://www.jmir.org/2022/2/e30416/

To assess the long-term effects of a mobile health intervention for weight loss. Randomized controlled trial 650 Spanish adults recruited from primary care centers Intervention included a smartphone app, activity tracker, and brief sessions with a health counselor. Measurements of baseline and 12-month weight, body composition, and physical activity levels were made. ANOVA with repeated measurements and mixed-effects models were two types of statistical testing. The intervention group saw a moderate decrease in weight and an improvement in body composition and physical activity (p < 0.05). Benchmark- Evidence-Based Practice Project Proposal Discussion Sustained support is crucial for achieving and maintaining weight loss through mobile health interventions. Long-term commitment is key.
Spring et al. (2024)

https://jamanetwork.com/journals/jama/article-abstract/2818967

To evaluate the effectiveness of a coaching-free and wireless feedback system-based weight loss strategy. Noninferiority randomized trial 400 adults with BMI 27–45 kg/m2 recruited from a US academic center Intervention subjects received wireless feedback with an activity tracker and scale; some received additional coaching. We examined weight and physical activity levels at baseline and six months later. Regression analysis and t-tests were two types of statistical tests. The proportions of the teaching and non-coaching groups differed significantly (p < 0.05). Personalized coaching significantly improves weight loss interventions. Individual reinforcement is important.
Spring et al. (2024)

https://jamanetwork.com/journals/jama/article-abstract/2818967

To compare the efficacy of a weight loss intervention using a wireless feedback system with and without coaching. Noninferiority randomized trial 400 adults with BMI 27–45 kg/m2 recruited from a US academic center Intervention subjects received wireless feedback with an activity tracker and scale; some received additional coaching. Weight and physical activity levels measured at baseline and after 6 months. Statistical tests included t-tests and regression analysis. Significant weight loss in the group with coaching compared to the group without coaching (p < 0.05). Personalized coaching significantly improves weight loss interventions. Individual reinforcement is important.
Naz et al. (2023)

https://bmjopen.bmj.com/content/13/8/e070913.abstract

To explore the feasibility of a peer-supported, WhatsApp-assisted lifestyle modification intervention for weight reduction in a low-resource area. Mixed-methods, single-group, pretest–post-test, quasi-experimental study 50 adults from a slum in Karachi with BMI >23 kg/m2 Lifestyle modification guidance and peer support were delivered via WhatsApp over 5 weeks. Weight, dietary intake, and physical activity levels were measured pre- and post-intervention. Statistical tests included paired t-tests and thematic analysis for qualitative data. Benchmark- Evidence-Based Practice Project Proposal Discussion Significant weight loss, reduced calorie consumption, and high retention rate (p < 0.05). Tech-based peer intervention is feasible and effective in low-resource settings. WhatsApp can be leveraged for widespread implementation.

 

 

 

Synthesis of the Literature

All the articles reviewed in this paper affirm the PICOT statement, revealing that obese adults can benefit from individualized, technology-based lifestyle modification programs in their weight loss endeavours. As in the case of prior studies, features shared among them include mobile applications and feedback assistance to users that help them adhere strictly to recommended diets and physical activity. Evaluating the key points, it is possible to note that technology plays a significant role in weight loss and that it is crucial to ensure long-term support and coaching.

Comparison of Articles

The reviewed articles are similar in terms of the population that was focused on – the adult obesity patient and the choice of the research method, a randomized controlled trial recognized as the most reliable method to evaluate the efficiency of an intervention. All the studies reported positive outcomes of lifestyle changes in weight loss. They affirmed that individualized interventions provided better results shared features comprised of technology-based administration, individual feedback, and the need for maintenance. Benchmark- Evidence-Based Practice Project Proposal Discussion

The research studies highlighted several aspects, with a significant focus on the importance of technology in supporting dietary and physical activity interventions. For example, Vaz et al. (2021) and Lugones-Sanchez et al. (2022) showed the efficient use of mobile applications to deliver interventions for lifestyle changes. According to Beleigoli et al. (2020), it is crucial to provide individual real-time feedback through Web-based platforms; Spring et al. (2024) added the effectiveness of the wireless feedback systems with coaching into training.

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However, it should be noted that the studies concerned different populations of patients. For example, Beleigoli et al. (2020) used only the university students and staff participants, while Lugones-Sanchez et al. (2022) included participants from the primary care centers. These population differences indicate that outcomes cannot be generalized across the world. Additionally, the strategies for implementing interventions varied: Mobile apps were employed in some of the research (Naz et al., 2023; Vaz et al., 2021; Lugones-Sanchez et al., 2022), and in some other studies, feedback coaching systems were used (Spring et al., 2024).

They also varied in terms of feedback customization. Beleigoli et al. (2020) adopted a web application to give feedback through an online dietitian, while Spring et al. (2024) employed wireless training alongside personal coaching. These differences suggest that intervention should be tailored to promote weight reduction successfully.

Limitations

The following limitations were noted in the studies that were conducted. These can be seen as methodological issues such as bias in self-assessment measures, inconsistencies in the mode of intervention implementation, and disparities in the length of follow-up periods. For example, the self-reported information about weight and diet in Beleigoli et al. (2020) and Lugones-Sanchez et al. (2022) could result in reporting bias, which distorts the results. Furthermore, disparities in the length of follow-up periods are another factor that hinders the comparability of long-term health implications. Additionally, in the work of Stevens et al. (2023), the importance of providing treatment that would be adjusted to the needs of particular patients, including patients with severe mental disorders, is also mentioned. These two essential aspects show that future studies will require standardization of the frequency and duration of interventions. Benchmark- Evidence-Based Practice Project Proposal Discussion

Suggestions for Future Research

This is evidenced by the following issues, which would require further research: Knowing the frequency and the length of time for the intervention for the different targets of lifestyle modification is essential to ensure the effectiveness of the approach. Therefore, comparative analysis, especially regarding the cost-effectiveness of these programs relative to conventional treatment, should be carried out to facilitate wider adoption. Future studies should also aim to compare studies of different ages and cultural characteristics, as most reviewed studies were based on university students and primary care patients.

It may be beneficial to examine the nature of technology and feedback mechanisms, how they operate, and what makes them effective. Future studies should also explore other motivational, self-efficacy, and social predictors of weight loss endeavors due to the possibility of identifying these factors essential for designing potential intervention measures.

Conclusion

The literature review highlights the need for patients’ tailored LSM programs to lose weight for adult obesity from the literature review. Integrated personal interventions, especially those with a vital technological component and extended follow-up, lead to significant and lasting weight loss. The results of studies show that it is possible to use technology and feedback to deliver individualized treatment and lose weight. The following evidence supports the outlined evidence-based practice project and offers a base to design concrete intervention strategies to tackle obesity and enhance health. Benchmark- Evidence-Based Practice Project Proposal Discussion

 

 

References

Beleigoli, A., Andrade, A. Q., Diniz, M. D. F., & Ribeiro, A. L. (2020). Personalized web-based weight loss behavior change program with and without dietitian online coaching for adults with overweight and obesity: randomized controlled trial. Journal of medical Internet research22(11), e17494. https://www.jmir.org/2020/11/e17494/

Lugones-Sanchez, C., Recio-Rodriguez, J. I., Agudo-Conde, C., Repiso-Gento, I., G Adalia, E., Ramirez-Manent, J. I., … & EVIDENT 3 Investigators. (2022). Long-term effectiveness of a smartphone app combined with a smart band on weight loss, physical activity, and caloric intake in a population with overweight and obesity (evident 3 study): randomized controlled trial. Journal of medical Internet research24(2), e30416. https://www.jmir.org/2022/2/e30416/

Naz, S., Haider, K. A., Jaffar, A., Khan, U., Azam, I., Siddiqui, A. R., & Iqbal, R. (2023). Feasibility of a peer-supported, WhatsApp-assisted, lifestyle modification intervention for weight reduction among adults in an urban slum of Karachi, Pakistan: a mixed-methods, single-group, pretest–post-test, quasi-experimental study. BMJ open13(8), e070913. https://bmjopen.bmj.com/content/13/8/e070913.abstract

Spring, B., Pfammatter, A. F., Scanlan, L., Daly, E., Reading, J., Battalio, S., … & Nahum-Shani, I. (2024). An Adaptive Behavioral Intervention for Weight Loss Management: A Randomized Clinical Trial. JAMA. https://jamanetwork.com/journals/jama/article-abstract/2818967

Stevens, H., Smith, J., Bussey, L., Innerd, A., McGeechan, G., Fishburn, S., & Giles, E. (2023). Weight management interventions for adults living with overweight or obesity and severe mental illness: a systematic review and meta-analysis. Benchmark- Evidence-Based Practice Project Proposal Discussion