Skip to content 
NURS FPX 6011 Assessment 1 Evidence-Based Patient Centered Needs Assessment
Evidence-Based Patient-Centered Needs Assessment
Implementing Evidence-Based Therapy for Patient-Centered Care
Evidence-based therapy is a well-liked approach to problem-solving in the clinical environment, but it’s also essential for providing patient-centered care. It combines medical expertise with the best and most recent research results alongside acknowledged patient values. To deliver the most critical treatment for patients. Collecting and examining information from various sources, such as clinical guidelines, patient interviews, and healthcare records, is necessary to assess the most applicable and practical therapies.
Evaluating Patient-Centered Care for Diabetes Management in Older Adults
This evaluation process ensures that healthcare decisions are accurate and patient-focused by considering the patient’s objectives, opinions, and preferences alongside or in addition to the medical aspects of the medical treatment. Ultimately, this will enhance patient results and treatment effectiveness (Engle et al., 2019). The primary intent of this inspection is to offer older Americans with diabetes an evaluation based on evidence.
Importance of Addressing Patient Engagement
Supporting patient engagement in managing their particular health, financial, and social requirements is crucial for addressing diabetes in the elderly community in the United States. It is difficult to overstate the critical role of patient engagement as it has an immediate influence on the effectiveness of healthcare interventions and consequences. Over a third of adult Americans with diabetes are sixty-five years of age or older, making up more than 11 million human beings with the condition (Schernthaner & Schernthaner-Reiter, 2018).
First, when clients actively participate in their care, they are more likely to follow through with therapies, dietary recommendations, and drug regimens. It’s essential to manage diabetes effectively to prevent complications, including neuropathy, cardiovascular disease, and problems with the kidneys. When patients take an active role in their treatment, they may better regulate their blood sugar, make lifestyle changes as required, and get medical care quickly (Gray & Threlkeld, 2019).
Second, since seniors may need more means, supporting their financial requirements is especially important because paying for healthcare services and prescription medication may be challenging. Considering financial situations with patients may lead to tailored solutions, such as aid programs or reasonably priced therapies (Powers et al., 2020). Lastly, to serve patients with therapy that respects their convictions and principles while being culturally competent, it is imperative to consider social norms. Diabetes approaches to treatment that are attuned to cultural differences are required to ensure that patients participate and understand, as emphasized in the NURS FPX 6011 Assessment 1 Evidence-Based Patient Centered Needs Assessment framework.
Patient Engagement Strategies
To effectively manage diabetes in elderly Americans, patient engagement—the engagement and collaboration of patients and medical professionals—is critical to enhancing their health. The first elements you should provide are custom instructional materials and self-management tools that take into consideration the unique needs and preferences of senior citizens with diabetes. (Shiyanbola et al., 2022). Provide an arrangement for the periodic evaluation and remote monitoring of geriatric diabetics.
Improving Senior Diabetes Management with Communication & Technology
This might include calling, using secure messaging services, or organizing telehealth check-ins to monitor glucose levels, medication adherence, and overall well-being. By having lines of communication open, medical professionals may quickly address any problems or concerns and adjust the medication plan when needed (Kirkland et al., 2023) Seniors with diabetes should be invited to participate in peer counseling or group support. Support from peers may help motivate older adults to remain devoted to their diabetes management regimens and improve their lifestyles (Pienaar & Reid, 2021).
Utilize technology to make it easier to take medications and adhere to them. For instance, clinicians may recommend pill organizers, computerized prescription refills, or even prescription reminder apps to help senior citizens remember to take their diabetes prescriptions. These tools encourage attendance while allowing patients to engage in their healthcare actively (Huang et al., 2019).
Use and Impact of Communication and Information Technology Tools
Enhancing Diabetes Management for Seniors with ICT Tools
ICT (information and communication technology) tools can potentially improve consumer health knowledge, particularly among older people American diabetics. This problem can be solved using a variety of tools. First, health apps for smartphones like Glucose Buddy and MyFitnessPal, which offer tailored recommendations and immediate input, may be used by seniors to track their diet, activity, and blood sugar levels. These apps assist users in better controlling their diabetes by educating them to make informed decisions concerning their lives (Scarry et al., 2022). Furthermore, older adults may now get appropriate medical advice and condition monitoring more conveniently because of telehealth providers like Zoom and Doxy. Me, which provides remote consultations with doctors and other healthcare providers (Anguilm, 2022).
NURS FPX 6011 Assessment 1 Evidence-Based Patient Centered Needs Assessment
WebMD and MedlinePlus, two online health portals with a wealth of knowledge on handling diabetes, available treatments, and preventative measures, might be helpful learning tools. They aggressively encourage learning by themselves and exhort individuals to take a leadership position in their choices regarding medical care (Gatto et al., 2022). People can start support groups to discuss their experiences, challenges, and triumphs associated with diabetes using social media platforms like Facebook and Twitter (Stellefson et al., 2019). This promotes emotional support and instruction among peers.
Enhancing Diabetes Management for Seniors with ICT Tools
These ICT tools significantly improve the consumer health literacy of older adults with diabetes. They provide peer support networks, more accessible access to information, and enhanced communication between patients and medical professionals. Consequently, older adults with diabetes become more knowledgeable about their circumstances, make wiser choices, and ultimately manage the disease more effectively, enhancing their general well-being and health (Liu et al., 2023). These medical devices may eventually result in cheaper healthcare costs and improved overall quality of life for those in this patient group.
Areas of Uncertainty
Despite earlier studies showing the potential application of ICT tools to increase knowledge about health among older adults with diabetes in the USA, there are still several unresolved inquiries and points of confusion. Investigating the specific technological preferences and accessible concerns that this patient population encounters—taking into account smartphone ownership and online literacy—would be beneficial. Additionally, considering this population’s various languages and cultures may make it less challenging to tailor ICT solutions to the unique needs of older adults in the diabetic community.
Value and Relevance of Technologies Modalities
The needs of the patient population inspection for older adults with diabetes in the US may require using various technology techniques, as highlighted in the NURS FPX 6011 Assessment 1 Evidence-Based Patient Centered Needs Assessment. These techniques include electronic medical records (EHRs), mobile health apps, smartwatches, telemedicine platforms, and patient portals. Telehealth systems provide online interactions between healthcare providers and patients, improving older adults’ access to care, notably for those with transportation issues or difficulty traveling (de Kreutzenberg, 2022).
Health applications for smartphones may assist patients in managing their diabetes by checking blood sugar levels, alerting users when to take their medications, and providing learning materials. In the opinion of Rodriguez-Leon et al. (2020), wearable technologies such as glucose monitors and fitness trackers may provide real-time data monitoring, allowing healthcare professionals and patients to alter treatment approaches quickly. By allowing information exchange and patient accessibility to medical data, EHRs and patient portals enhance healthcare collaboration and patient participation.
Exchange and Interoperability of Technology Modalities
The practical application of these technical methods depends on their interoperability and harmony. Thanks to interoperability, medical providers may get up-to-date patient data from any device, enabling data flow through several systems and technologies. This eliminates the need for redundant testing, enhances decision-making with additional information, and improves the care bar. For example, including the glucose readings from a patient’s smartwatch in their electronic health record (EHR) might give the patient and their healthcare provider an in-depth understanding of their health (Kawu et al., 2022).
Specific Ways of Communication
Apart from ensuring that people comply with data protection rules and enhancing comprehension of complex healthcare concepts and jargon, promising communication approaches are essential for developing honest and patient-focused interactions. Clear communication, visual assistance, and culturally sensitive techniques are some of these strategies.
Healthcare providers ought to reduce terminology related to medicine and use analogies to help citizens grasp medical concepts in an understanding and empathetic manner (Brooks et al., 2019). Multilingual aid and interpretation solutions can also be utilized to overcome language barriers and ensure that all patients and their families, regardless of their educational background or proficiency in the language, can engage in meaningful talks regarding how to handle their diabetes (Lloyd et al., 2018).
Innovative Strategies for Leveraging Technologies
To use technology in ways that improve the effectiveness, morality, and quality of medical treatment for older adults with diabetes in the United States, an extensive strategy is required. First, patients can handle their treatment by using applications for mobile health and telemedicine platforms that are linguistically and culturally suitable. To offer accessibility for an array of patient groups, these tools need to feature intuitive user interfaces that can switch between languages and cultural peculiarities with simplicity (Haleem et al., 2021). Enhancing interaction between patients and healthcare professionals might be possible using translation services with culturally compatible instructional materials.
Using AI, Machine Learning, and EHR for Personalized Diabetes Care
Second, machine education and artificial intelligence (AI) may be used to customize treatment plans. AI-driven predictive analytics may identify high-risk individuals in the older adult diabetic population, allowing for preemptive treatment decisions. AI-enabled surveillance devices may also monitor medication compliance, arterial blood pressure, and glucose levels. When intervention is necessary, these tools may notify medical personnel in real time (Contreras & Vehi, 2018). This approach increases the patient’s experience while efficiently using healthcare assets.
Thirdly, optimizing electronic health records (EHRs) to ensure linguistic and cultural compatibility is possible. Electronic health records can include patients’ linguistic and cultural norm choices, providing physicians with the necessary information for delivering patient-centered care (Chittalia et al., 2021). Furthermore, by enhancing patient data security and privacy, blockchain technology could improve public trust in health care.
Mitigating the Risk of Adverse Outcomes
The methods mentioned above may be successful at lowering the likelihood of adverse effects stemming from inconsistent access to client medical data and technological assets, firstly, ensuring that telemedicine systems and mobile health applications are linguistically as well as culturally acceptable guarantees that an array of patients, such as those with poor language skills or from different countries, can utilize these developments effectively. This openness promotes equal access to healthcare technology and reduces inequalities in knowledge and medical provision (Haleem et al., 2021).
Advancing Diabetes Care with AI, EHR, and Blockchain
Second, implementing artificial intelligence (AI) and machine learning algorithms enables to tailor treatments and treatment strategies for senior citizens with diabetes. These innovations ensure that susceptible patients get timely and focused care regardless of their socioeconomic standing or location by using predictive analytics to identify high-risk individuals (Chaki et al., 2020). This approach tackles gaps in healthcare access right away by giving those in dire need priority.
NURS FPX 6011 Assessment 1 Evidence-Based Patient-Centered Needs Assessment
Thirdly, incorporating electronic health records (EHRs) that respect patients’ language preferences and cultural customs ensures that all patients from any cultural background can access and fully understand medical information. By accounting for linguistic and cultural variance, customizing EHRs minimizes injustice in accessing and interpreting personal health information (Chittalia et al., 2021). Furthermore, using blockchain technology for secure data storage boosts trust and ensures patient data is maintained without regard for demographic environments.
Specific Examples
Several tactics have been used to minimize hazards and deal with improper access to patient health information and technical modalities. Patients from various cultural backgrounds can receive health services thanks to systems like AmWell, which have established multilingual assistance (Mougey et al., 2023). To reduce inequities in treatment outcomes, health institutions such as Kaiser Permanente and others have used AI-driven algorithms to proactively detect high-risk patients and then develop tailored treatment regimens (Lubell, 2023).
Managing diabetes has grown more practical and readily available to a broader spectrum of ethnic communities because applications like MySugr and Fooducate provide learning resources and graphical interfaces geared to diverse cultures (Doyle & Watson, 2022). In order to make sure that medical professionals can interact efficiently and offer culturally appropriate care, medical facilities, including Cleveland Clinic, have created customized EHRs for incorporating different cultures, as highlighted in NURS FPX 6011 Assessment 1 Evidence-Based Patient Centered Needs Assessment.
Conclusion
In a nutshell, the significant problem of Type 2 diabetes among the elderly in the US has been brought to light by the evidence-based patient-focused needs evaluation. We have painstakingly reviewed the research and patient perspectives to determine the intricacy of this problem. It is clear that successfully satisfying this group’s demands calls for a comprehensive strategy that considers psychological and physical aspects. To improve the quality of life for senior citizens with diabetes, legislators and medical providers need to prioritize patient-centered care and tailored solutions. Read more about our sample NURS FPX 6011 Assessment 2 Evidence-Based Population Health Improvement Plan for complete information about this class.
References
Anguilm, C. (2022, August 16). The power of telehealth: Revolutionizing access to medical care. Medical Advantage.
https://www.medicaladvantage.com/blog/what-is-telehealth-and-how-does-it-work/
Brooks, L. A., Manias, E., & Bloomer, M. J. (2019). Culturally sensitive communication in healthcare: A concept analysis. Collegian, 26(3), 383–391.
https://doi.org/10.1016/j.colegn.2018.09.007
Chaki, J., Thillai Ganesh, S., Cidham, S. K., & Ananda Theertan, S. (2020). Machine learning and artificial intelligence-based Diabetes Mellitus detection and self-management: A systematic review. Journal of King Saud University – Computer and Information Sciences.
https://doi.org/10.1016/j.jksuci.2020.06.013
Chittalia, A. Z., Marney, H. L., Tavares, S., Warsame, L., Breese, A. W., Fisher, D. L., Stoppie, M. E., Coen, D., Zikowski, K. A., Shapiro, A. W., & Vawdrey, D. K. (2021). Bringing cultural competency to the EHR: Lessons learned providing respectful, quality care to the LGBTQ community. AMIA Annual Symposium Proceedings, 2020, 303–310.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8075512/
Consult QD. (2019, December 6). How Cleveland Clinic’s ehr transformation ensures the delivery of world-class care everywhere. Consult QD.
Contreras, I., & Vehi, J. (2018). Artificial intelligence for diabetes management and decision support: A literature review. Journal of Medical Internet Research, 20(5), e10775.
de Kreutzenberg, S. V. (2022). Telemedicine for the clinical management of diabetes; Implications and considerations after COVID-19 experience. High Blood Pressure & Cardiovascular Prevention, 29(4), 319–326.
https://doi.org/10.1007/s40292-022-00524-7
Doyle, A., & Watson, K. (2022, August 31). The 12 best diabetes apps of 2022. Healthline.
Dragomanovich, H. M., & Shubrook, J. H. (2021). Improving cultural humility and competency in diabetes care for primary care providers. Clinical Diabetes, 39(2), cd200063.
https://doi.org/10.2337/cd20-0063
Engle, R. L., Mohr, D. C., Holmes, S. K., Seibert, M. N., Afable, M., Leyson, J., & Meterko, M. (2019). Evidence-based practice and patient-centered care: Doing both well. Health Care Management Review, 46(3), 174–184.
https://doi.org/10.1097/HMR.0000000000000254
Gatto, J., Seegmiller, P., Johnston, G., & Preum, S. M. (2022, October 6). HealthE: Classifying entities in online textual health Advice. ArXiv.org.
https://doi.org/10.48550/arXiv.2210.03246
Gray, A., & Threlkeld, R. J. (2019). Nutritional recommendations for individuals with diabetes. Nih.gov; MDText.com, Inc.
https://www.ncbi.nlm.nih.gov/books/NBK279012/
Haleem, A., Javaid, M., Singh, R. P., & Suman, R. (2021). Telemedicine for healthcare: Capabilities, features, barriers, and applications. Sensors International, 2(2).
https://doi.org/10.1016/j.sintl.2021.100117
Huang, Z., Lum, E., Jimenez, G., Semwal, M., Sloot, P., & Car, J. (2019). Medication management support in diabetes: A systematic assessment of diabetes self-management apps. BMC Medicine, 17(1).
https://doi.org/10.1186/s12916-019-1362-1
Kawu, A. A., Hederman, L., O’Sullivan, D., & Doyle, J. (2022). Patient generated health data and electronic health record integration, governance, and socio-technical issues: A narrative review. Informatics in Medicine Unlocked, 37, 101153.
https://doi.org/10.1016/j.imu.2022.101153
Kirkland, E. B., Johnson, E., Bays, C., Marsden, J., Verdin, R., Ford, D., King, K., & Sterba, K. R. (2023). Diabetes remote monitoring program implementation: A mixed methods analysis of delivery strategies, barriers, and facilitators. Telemedicine Reports, 4(1), 30–43.
https://doi.org/10.1089/tmr.2022.0038
Liu, S., Ya, L., Wang, D., He, X., Ren, W., Kong, D., & Luo, Y. (2023). Impact of digital health literacy on health-related quality of life in Chinese community-dwelling older adults: The mediating effect of health-promoting lifestyle. Frontiers in Public Health, 11.
https://doi.org/10.3389/fpubh.2023.1200722
Lloyd, C. E., Wilson, A., Holt, R. I. G., Whicher, C., & Kar, P. (2018). Language matters: A UK perspective. Diabetic Medicine, 35(12), 1635–1641.
https://doi.org/10.1111/dme.13801
Lubell, J. (2023, August 25). Kaiser Permanente’s AI approach puts patients and doctors first. American Medical Association.
Mougey, E. B., Judy, W. C., Venkatesh, R. D., Berg, E., Lee, J. A., Rosen, J. M., Li, B. U. K., Koster, A., Maiden, K., Gao, Z., & Franciosi, J. P. (2023). Equity and inclusion in pediatric gastroenterology telehealth: A study of demographic, socioeconomic, and digital disparities. Journal of Pediatric Gastroenterology and Nutrition, 77(3), 319.
https://doi.org/10.1097/MPG.0000000000003797
Pienaar, M. A., & Reid, M. (2021). A diabetes peer support intervention: Patient experiences using the Mmogo-method®. Health SA Gesondheid, 26.
https://doi.org/10.4102/hsag.v26i0.1512
Powers, M. A., Bardsley, J. K., Cypress, M., Funnell, M. M., Harms, D., Hess-Fischl, A., Hooks, B., Isaacs, D., Mandel, E. D., Maryniuk, M. D., Norton, A., Rinker, J., Siminerio, L. M., & Uelmen, S. (2020). Diabetes Self-management Education and Support in Adults With Type 2 Diabetes: A Consensus Report of the American Diabetes Association, the Association of Diabetes Care & Education Specialists, the Academy of Nutrition and Dietetics, the American Academy of Family Physicians, the American Academy of PAs, the American Association of Nurse Practitioners, and the American Pharmacists Association. Journal of the American Pharmacists Association, 60(6).
https://doi.org/10.1016/j.japh.2020.04.018
Rodriguez-Leon, C., Villalonga, C., Munoz-Torres, M., Ruiz, J. R., & Banos, O. (2020). Mobile and wearable sensing for monitoring diabetes-related Parameters: Systematic review (Preprint). JMIR MHealth and UHealth, 9(6).
Scarry, A., Rice, J., O’Connor, E. M., & Tierney, A. C. (2022). Mobile applications or mobile health technology can improve diet quality in adults. Nutrients, 14(12), 2437.
https://doi.org/10.3390/nu14122437
Schernthaner, G., & Schernthaner-Reiter, M. H. (2018). Diabetes in the older patient: Heterogeneity requires individualization of therapeutic strategies. Diabetologia, 61(7), 1503–1516.
https://doi.org/10.1007/s00125-018-4547-9
Shiyanbola, O. O., Maurer, M., Schwerer, L., Sarkarati, N., Wen, M.-J., Salihu, E. Y., Nordin, J., Xiong, P., Egbujor, U. M., & Williams, S. D. (2022). A culturally tailored diabetes self-management intervention incorporating race-congruent peer support to address beliefs, medication adherence, and diabetes control in African Americans: A pilot feasibility study. Patient Preference and Adherence, Volume 16, 2893–2912.
https://doi.org/10.2147/ppa.s384974
Stellefson, M., Paige, S., Apperson, A., & Spratt, S. (2019). Social media content analysis of public diabetes Facebook groups. Journal of Diabetes Science and Technology, 13(3), 428–438.
