NURS FPX 6424 Assessment 2 Conference Poster Presentation

Part 1: Abstract

• Title

Increasing Quality Outcomes in Chronic Disease Care Coordination with the Help of the Health Information Systems (HIS) Model and Health Informatics Tools.

• Overview

The chronic diseases, including heart failure and diabetes, are managed according to the American Nurses Association (ANA) standards that facilitate collaboration, use information systems, and enhance the quality of care delivery (American Nurses Association, 2024). This presentation explains how the HIS Model can be combined with the health informatics tools (Electronic Health Records-EHRs and Clinical Decision Support Systems-CDSS) to use the evidence to inform the intervention for chronic conditions.

As an illustration, in the case of chronic illnesses such as diabetes or CHF, a CDSS is able to identify abnormal lab data, instigate evidence-based treatment, and lower medication mistakes. It also improves the coordination of care since the real-time access of each team member is to consistent and validated information. Nurses can monitor patient progress, reduce readmissions, and improve the coordination of care using effective data management and trending. The data management and trending allow nurses to track patient improvement, decrease readmission, and enhance coordination of care.

• Literature Review

Informatics is an area that ANA focuses on, and it highlights the importance of health technology in enhancing continuity of care. The presence of research papers in the ANA Online Journal of Issues in Nursing demonstrates that technological interventions, or in other words, EHRs, CDS tools, and predictive analytics, can be utilized to support the process of care coordination, enhance the rates of communication between healthcare professionals, and ultimately deliver superior outcomes in patients with chronic diseases (Huter et al., 2020).

Whereas Electronic Medical Records (EMRs) are commonly applied in the healthcare setting of a single healthcare institution to record patient data, EHRs are applied to verify the sharing of patient data among various healthcare providers, which guarantees a continuum of care across care settings. The literature supports the idea that effective data-driven decision making, which is delivered by standardized terminologies and high-quality data management processes, is the key to care gap identification, patient progress monitoring, and intervention guidance (Huter et al., 2020). The data management and trending would provide an actionable insight that would go a long way in the mitigation of the load of chronic diseases like cardiac ailments, diabetes, and other chronic diseases.

Encourage People to be Agents of Change: Health Information Systems (HIS) Model

Health Information Systems (HIS) Model focuses on the combination of data, information, knowledge, and wisdom to enhance healthcare provision and decision-making. The model provides the tools of care coordination improvement and care of chronic diseases, in particular, through the assistance of health informatics tooling, including EHRs, CDS, and predictive analytics (Barbosa et al., 2021). The setting was a mid-sized city hospital where an intervention was being undertaken on heart failure, whereby the HIS model was actively utilized by nurses so that they could make their decisions on the model and achieve better patient outcomes.

Nurses might become quite proactive regarding their chronic disease management strategy by getting a chance to incorporate the real-time data on EHRs into their workflow. The trends of data, e.g., the data on weight changes, taking medications, and adhering to visits, were also observed closely, and the interventions could be conducted in due time. This was evident in the case of predictive analytics, whereby patients who were more likely to be readmitted were identified, and some of the interventions were put in place.

ANA is also focused on quality and safety; thus, such a solution also fits into this area of concern because, upon using informatics tools, it can be possible to make evidence-based decisions, coordinate care, and, finally, reduce complications of chronic diseases, such as heart failure (Titler, 2024). Following the HIS Model, the nurses were substituted by data-driven nurses who make real-time decisions as a substitute for data recording nurses. That enabled the nursing teams to be agents of change since they can make personal amendments to the care plans, enhancing patient engagement and satisfaction.

Data Conclusions

The information that was gathered in the EHR system demonstrated important indicators that led to the timely interventions. Weight increase of the patients, lost medications, and missed visits at the appointed visits were identified as some of the risk factors, for example. The real-time data allowed the results to be measured since they were used to initiate the interventions. Including but not limited to, readmissions decreased by 18 percent, patient satisfaction increased by 25 percent, and the overall perception of the care coordination was improved (Cyrus et al., 2022).

These findings justify the importance of structured data use in the treatment of chronic disorders. With standardized terminologies like ICD-10 (International Classification of Diseases) and SNOMED CT (Systematized Nomenclature of Medicine–Clinical Terms), healthcare providers have a greater opportunity to classify and also analyze patient data, leading to more personalized care plans.

These terminologies enable a uniform record of patient diagnosis, laboratory findings, and medical discovery, which can be analyzed using valid data and forecast modeling. The data management processes encompass real- time data validation, secure data storage, routine audits, and data visualization dashboards, which allow clinicians and nurse leaders to track the progress as well as make better decisions due to having the correct, timely, and standardized health information.

Conclusion

The adoption of health informatics tools and models, including the Health Information Systems (HIS) Model, is very helpful in improving coordination of chronic disease care. EHRs, CDS, predictive analytics, timely interventions, and personalized care will be used to provide data-driven decision-making. Evidence-based practices and application of informatics could make nurses stay ahead of chronic diseases by reducing hospital readmission, enhancing patient satisfaction, and improving population health. This, however, is not merely the way out following the vision of ANA of sophisticated and information-driven care, but also aligned with the welfare of the whole healthcare enhancement through appropriate data management, trending, and collaboration.

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