DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require
Grand Canyon University DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require-Step-By-Step Guide
This guide will demonstrate how to complete the DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require assignment based on general principles of academic writing. Here, we will show you the A, B, Cs of completing an academic paper, irrespective of the instructions. After guiding you through what to do, the guide will leave one or two sample essays at the end to highlight the various sections discussed below.
How to Research and Prepare for DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require
Whether one passes or fails an academic assignment such as the Grand Canyon University DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require depends on the preparation done beforehand. The first thing to do once you receive an assignment is to quickly skim through the requirements. Once that is done, start going through the instructions one by one to clearly understand what the instructor wants. The most important thing here is to understand the required format—whether it is APA, MLA, Chicago, etc.
After understanding the requirements of the paper, the next phase is to gather relevant materials. The first place to start the research process is the weekly resources. Go through the resources provided in the instructions to determine which ones fit the assignment. After reviewing the provided resources, use the university library to search for additional resources. After gathering sufficient and necessary resources, you are now ready to start drafting your paper.
How to Write the Introduction for DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require
The introduction for the Grand Canyon University DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require is where you tell the instructor what your paper will encompass. In three to four statements, highlight the important points that will form the basis of your paper. Here, you can include statistics to show the importance of the topic you will be discussing. At the end of the introduction, write a clear purpose statement outlining what exactly will be contained in the paper. This statement will start with “The purpose of this paper…” and then proceed to outline the various sections of the instructions.
How to Write the Body for DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require
After the introduction, move into the main part of the DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require assignment, which is the body. Given that the paper you will be writing is not experimental, the way you organize the headings and subheadings of your paper is critically important. In some cases, you might have to use more subheadings to properly organize the assignment. The organization will depend on the rubric provided. Carefully examine the rubric, as it will contain all the detailed requirements of the assignment. Sometimes, the rubric will have information that the normal instructions lack.
Another important factor to consider at this point is how to do citations. In-text citations are fundamental as they support the arguments and points you make in the paper. At this point, the resources gathered at the beginning will come in handy. Integrating the ideas of the authors with your own will ensure that you produce a comprehensive paper. Also, follow the given citation format. In most cases, APA 7 is the preferred format for nursing assignments.
How to Write the Conclusion for DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require
After completing the main sections, write the conclusion of your paper. The conclusion is a summary of the main points you made in your paper. However, you need to rewrite the points and not simply copy and paste them. By restating the points from each subheading, you will provide a nuanced overview of the assignment to the reader.
How to Format the References List for DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require
The very last part of your paper involves listing the sources used in your paper. These sources should be listed in alphabetical order and double-spaced. Additionally, use a hanging indent for each source that appears in this list. Lastly, only the sources cited within the body of the paper should appear here.
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DNP 805 Topic 4 DQ 2
Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require. How could the EHR database facilitate this type of integration between clinical and administration systems
Sample Answer for DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require
Electronic Health Record (EHR) are used in our healthcare organization and widely used to research as well. The validity of the results is dependent upon the assumptions of the healthcare system. EHR based data have challenges and some threats to validity and includes target population, availability and interpretability of clinical and non-clinical data. EHR includes socioeconomic status, race, and ethnicity that can be compared. Availability of data for fundamental markers of health are important for identifying inequities. The data has the ability to capture individuals clinical trials , data sets and measures the outcome that has potential risk factors. The EHR can be robust, informative and important to the understanding of health and disease in the population.
The Veterans Health Administration is a one-of-a-kind healthcare organization that can illuminate how to implement a community health strategy to increase vaccine acceptance. I work at the VA, and I can tell you that we serve a distinct community population. The COVID-19 pandemic, combined with vaccine reluctance, has posed a public health risk. The use of EHR-based tools in a population health approach to vaccine uptake can have a significant impact on healthcare system immunization rates. In the years preceding the COVID-19 pandemic, vaccine hesitancy, defined as “the unwillingness or refusal to vaccinate despite the availability of vaccines,” was listed as a “top 10” global health issue. Large-scale vaccine skepticism focuses on authoritative voices, involving health care workers, scientists, and techniques. The scale and scope of the Veterans Health Administration, the characteristics of EHR primary focuses in health population, a track record of high quality preventive care, and the development of an evidence-based vaccine hesitancy strategy The ultimate goal is to boost vaccine uptake in clinical and operational settings. Identifying educational opportunities for clinicians and veterans is one step toward increasing vaccine acceptability. The development of vaccination acceptance tools, as well as the implementation of a population health approach, will be easily accessible.
References:
Centers for Disease Control and Prevention. COVID Data tracker. Available at: https://covid.cdc.gov/covid-datatracker/#vaccinations_vacc-total-admin-rate-total. Accessed September 1, 2021.
Ni K, Chu H, Zeng L, et al. Barriers and facilitators to data quality of electronic health records used for clinical research in China: a qualitative study. BMJ Open. 2019;9(7):e029314. doi: 10.1136/bmjopen-2019-029314. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
Verheij RA, Curcin V, Delaney BC, et al. Possible sources of bias in primary care electronic health record data use and reuse. J Med Internet Res. 2018;20(5):e185. doi: 10.2196/jmir.9134. [PMC free article] [PubMed] [CrossRef] [Google Scholar]
World Health Organization. Ten threats to global health in 2019. Available at: https://www.who.int/news-room/spotlight/ten-threats-to-global-health-in-2019. Accessed September 1, 2021.
Sample Answer 2 for DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require
Great topic Beverly—The Covid pandemic came on quickly like a rush of a whirlwind or tornado and caused so much havoc and left in its wake a lot of devastation and then dissipated or slowly dissipating. In the wake of the Pandemic, the administration and the clinical systems had to work together to follow the center for disease rules and regulations concerning this pandemic by creating policies for their decisions and the informaticists created the electronic health records (EHR) that would be used to obtain some form of minimal history and physical before the vaccine could be given and also used to record the type of vaccine that was given so that CDC can monitor the effectiveness of the medication to determine the need for further treatment or not. Like you pointed out Beverly, the EHR was used to keep track of those who had not taken the vaccine since there was no record of them taking it. Which led to increased process of re-education. So, with the EHR, it shows the need for educating people to the need for vaccinations. In my hospital facility, there were those who also refused to take it until it was mandated and then some took it and others presented exemptions.
Reference:
Centers for Disease Control and Prevention (CDC). (2021, April 2). Monitoring COVID-19 Vaccine Effectiveness How and Why CDC Tracks How Well the Vaccines Are Working. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/vaccines/effectiveness/how-they-work.html
Sample Answer 3 for DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require
Thank you for providing an insightful post. The COVID-19 pandemic has tremendously impacted all healthcare systems. According to Balut et al. (2021), sufficient uptake of the vaccination is imperative to slow the spread of COVID-19, especially among the most vulnerable such as homelessness. Of the 83,523 Veterans who experience homelessness, about 45.8% were vaccinated based on the database collected by the U.S. Department of Veteran Affairs (VA). In addition, there is a strong correlation between COVID-19 vaccinations and Veterans who utilize VA healthcare and service (Balut et al., 2021). With this, I agree with you that a vaccine acceptance tool should be readily available, ly to those who are more vulnerable such as Veterans experiencing homelessness.
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Reference
Balut, M. D., Chu, K., Gin, J. L., Dobalian, A., & Der-Martirosian, C. (2021). Predictors of COVID-19 vaccination among veterans experiencing homelessness. VACCINES, 9(11). https://doi-org.lopes.idm.oclc.org/10.3390/vaccines9111268
Sample Answer 4 for DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require
The electronic medical record One of the most important data sources for data analysis is the electronic medical record (EMR). It can now be used to drive public health decision-making, identify risk factors for infectious diseases and treat them, and provide continuity of care among various medical institutions while improving healthcare quality and pushing forward medical and scientific research (Wang, 2019). Data integration is the process of collecting a cluster of raw data from various sources and combining them into one source, which is then stored and distributed to various applications as new data from the storage location. As a result, data mining would yield a wealth of information needed to provide useful insights for research, allowing the EMR to be compatible with various hospitals. It is the process of combining two different companies’ systems into a single centralized data set. As a result, the integration and interoperability of healthcare data from various sources of information and communication technology (ICT) in a region or country is critical for hospital care and treatments (Sreemathy, Naveen Durai, Lakshmi Priya, Deebika, Suganthi, & Aisshwarya, 2021). (Wang, 2019).
Integration is frequently misunderstood as simply entering data into a system, but it goes far beyond that. Because the two systems are not built the same and may have different levels and vendor policies, there is a need to include the social factors as well as the broader context in the integration process (Bjrnstad, & Ellingsen, 2019).
Chronic heart failure (CHF) patients are the patient population for whom I would like to integrate their data information. It is a chronic debilitating disease with a high mortality rate and a severe symptom burden that lasts for a long time. Shortness of breath (SOB), Dyspnea, pain, fatigue, decreased physical activity, anxiety, and depression are physical symptoms of CHF (Siouta, Heylen, Aertgeerts, Clement, Janssens, Van Cleemput, & Menten, 2021). The patient demographic, which includes age, gender, allergies, weight, admitting symptoms, prior diagnosis, history, and physical with any chronic symptoms such as dyspnea, lower extremity edema, any use of oxygen, medications, laboratories, diagnostics, procedures, treatment care plans, and any tolerable physical activity, would be the integration data from this population. For there to be integration between clinical and administrative systems, the integration process must adhere to the facilities’ and regulators’ ethical and legal standards. Integrative systems such as enterprise resource planning systems, enterprise application integration, component ware, and middleware are in place to allow all clinical and administrative systems to integrate. System standardization is also required for integration and other purposes. The most recent is the open EHR standard 17, as well as an international initiative to structure and standardize clinical knowledge through global consensus (Bjrnstad, & Ellingsen, 2019).
IT systems in hospitals support cooperative work. Schmidt and Simone28 argue that cooperative work interleaves distributed tasks; articulation work manages the consequences of the distributed nature of the work. Hence, information technology (IT) systems in hospitals need coordination and articulation work to function (Bjørnstad, & Ellingsen, 2019).
Improving the processes for patients and providers with the policy approaches must be evaluated to make sure that they remove unnecessary steps and complications for patients, while decreasing administrative burdens for providers. Standards and approaches must reflect how information flows through the health care system, the technical systems that are needed, and the crucial role of health information professionals play in translating across clinical and administrative domains. Also, the sharing of health information across payers and providers requires consideration of privacy policies, to ensure that only the minimum necessary information is shared, and they are not used beyond the specific transaction limited (American Health Information Management Association (AHIMA), 2020).
The data for trauma care is a requirement for the designation of a trauma center. It is actually required for a year prior to having your first visit for designation. Most of this data is raw data that should be able to be pulled directly from predefined fields within the Electronic Medical Record (EHR). This allow for not only streamline entry, but it also takes out the human factor of manual entry errors. This data can be looked at more globally for tracking and trending data. This data collection can truly help say patients lives. Thru the collection of data and comparing it to patient outcomes to determine gold standards in practice. An example of this is the discovery of the trauma triad of death and the importance of increasing trauma room temperature to prevent hypothermia that will lead to coagulopathy and metabolic acidosis. This continual collection of data allows for ongoing process improvement centered on improving patient outcomes. This is the foundation of the performance improvement plan. There are many different ways that you can take various interventions and compare them by the patient outcome to identify interventions to improve outcomes. This is not only beneficial for hospital interventions, but it is vital for prehospital (Hossenizadeh et al., 2022). This allows the hospitals to close to loop on patients with traumatic injuries to let them know if they went to the right facility for the patient, but also feedback based on the findings. For example, a stable patient with a pelvic fracture and sternal fracture was taken to a facility that was not a trauma facility. This allows for follow up for them that there was a better facility to take them too.
References
Hosseinzadeh, A., Karimpour, A., Kluger, R., & Orthober, R. (2022). Data linkage for crash outcome assessment: Linking police-reported crashes, emergency response data, and trauma registry records. Journal of Safety Research. https://doi-org.lopes.idm.oclc.org/10.1016/j.jsr.2022.01.003
Sample Answer 5 for DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require
Schizophrenia is a severe psychiatric disorder, characterized by delusions, hallucinations and disorganized thinking which affects about 1% of the world’s population. Schizophrenia is a severe psychiatric disorder associated with both structural and functional brain abnormalities. In the past few years, there has been growing interest in the application of machine learning techniques to neuroimaging data for the diagnostic and prognostic assessment of this disorder. Patients with serious mental illness are more likely to die early from general medical illness, suicide, or medication risk, compared with patients without mental illness. Even persons with mild to moderate mental illness can be mentally and physically incapacitated because of a behavioral health disorder. Behavioral health is an underinsured area; many persons with mental illness lack proper access to care and medication, a problem that can be addressed, in part, by improving HIT systems (Hu et al., 2016).
Comprehensive strategies will be needed to design EHR systems that address concerns about policy, practice, costs, and stigma and that protect patients’ privacy and confidentiality. However, these goals must not detract from continuing to challenge the notion that behavioral health and general medical health should be treated as separate and distinct. Utilization of EHRs among behavioral health care providers will improve the coordination of services and overall patient care, which is essential to reducing mental health disparities. Behavioral health care professionals recognize opportunities to strengthen Health Information Technology (HIT) systems in ways that support improved mental health care, including promoting policy agendas that facilitate improvements.
EHRs contain different types of patient-level variables, such as demographics, diagnoses, problem lists, medications, vital signs, and laboratory data. According to the National Academies of Medicine, an EHR has multiple core functionalities, including the capture of health information, orders and results management, clinical decision support, health information exchange, electronic communication, patient support, administrative processes, and population health reporting (Howes, O. D., & Murray, R. M, 2014).
References
Howes, O. D., & Murray, R. M. (2014). Schizophrenia: An integrated sociodevelopmental-cognitive model. Lancet, 383(9929), 1677– 1687. https://doi.org/10.1016/S0140-6736(13)62036-X
Hu, M. L., Zong, X. F., Mann, J. J., Zheng, J. J., Liao, Y. H., Li, Z. C., … Tang, J. S. (2016). A review of the functional and anatomical default mode network in schizophrenia. Neuroscience Bulletin, 33, 73– 84. https://doi.org/10.1007/s12264-016-0090-1
Sample Answer 6 for DNP 805 Topic 4 DQ 2 Discuss the type of integration data from your defined patient population in Topic 4 DQ 1 would require
Healthcare data integration services entail integrating technology, concepts, and teams when creating the infrastructure capable of big housing data and using it in a meaningful way while addressing data accessibility, ownership, and privacy (Austin et al., 2020). This framework is essential because it provides a way to use existing data to create a comprehensive health record that closely examines a multitude of sourcing informational summaries, enabling proper attention to be paid to the needs of clinicians, as well as providing opportunities for patient lifetime development (Austin et al., 2020). Coinciding with healthcare data integration, clinicians can now benefit from seamlessly searching among a wide array of healthcare systems to grasp a detailed understanding of an individual patient is HER (Austin et al., 2020). Integrating different data types within both exchange of health information as well as EHR systems can assist healthcare organizations in getting more out of their EHR systems. In contrast, firm health data governance policies can improve EHR data integrity (Austin et al., 2020). The strengths of data integration in healthcare combine real-time and historical data analysis to predict trends, improve care, and drive long-term growth (Austin et al., 2020). Most systems currently grant providers demographic informational accessibility, results from lab examinations, and lists of medicinal and allergic aspects, accompanied by various other patient EHR information (Austin et al., 2020). Despite this, social determinants of health data are still largely absent from clinical data (Austin et al., 2020).
EHRs can be comprehensive systems that manage clinical and administrative data; for example, an EHR may collect medical histories, diagnostic data, laboratory data, and physician notes, consults, and assist with billing, inter-practice referrals, appointments, scheduling, and prescription refills (Colquhoun et al., 2020). Clinical data derives from reputable sources such as laboratory records, reports from radiology, and HER (Colquhoun et al., 2020). Administrative information entailing billing employed information data (e.g., hospital as well as professional billing documentation) alongside the involvement of oversight pertaining towards health systems (i.e., system documentation from either transfer, admission, or event registration, accompanied by even discharge) (Colquhoun et al., 2020). Sourcing from clinical-based information may provide additional comprehension compared to administrative information but does provide the downside of additional processing when ensuring secondary usage (Colquhoun et al., 2020). For example, a CHF diagnosis with origins deriving from clinical data possibly needs to acknowledge laboratory values from serum blood sugar, consider medication treatments, and text search unstructured clinical notes (Colquhoun et al., 2020; Park et al., 2009). Data from administration provide a powerful framework but can also provide scope restrictions. For example, a CHF diagnosis may be readily identified in administrative data as a single structured data element (e.g., International Classification of Diseases, Tenth Revision [ICD-10], code I50. 20). Registries can potentially blend these by including both clinical and administrative data to leverage the strength of each at the cost of additional data validation or adjudication (Colquhoun et al., 2020; Park et al., 2009).
References
Austin, R. C., Schoonhoven, L., Richardson, A., Kalra, P. R., & May, C. R. (2020). How do SYMPtoms and management tasks in chronic heart failure imPACT a person’s life (SYMPACT)? Protocol for a mixed‐methods study. ESC heart failure, 7(6), 4472-4477.
Colquhoun, D. A., Shanks, A. M., Kapeles, S. R., Shah, N., Saager, L., Vaughn, M. T., … & Mathis, M. R. (2020). Considerations for integration of perioperative electronic health records across institutions for research and quality improvement: the approach taken by the Multicenter Perioperative Outcomes Group. Anesthesia and analgesia, 130(5), 1133.
Park, H. Y., Kim, K., & Park, E. J. (2009). Study on the Feasibility of CHF Data Integration.