NURS FPX 6612 Assessment 2 Quality Improvement Proposal

Quality Improvement Proposal

The Medicare and Medicaid Services define ACOs as associations that deliver high-quality care treatments freely to Medicare cases through effective care collaboration (Millwee, 2020). The Sacred Heart Hospital (SHH) under Vila Health seeks to acquire the status of an Accountable Care Organization (ACO). Assuming the duty of a case director at SHH, a quality enhancement offer will be recommended to include more quality criteria by expanding the sanitarium’s megahit with a broad focus on Electronic Health Records (EHRs).

Ways to Expand Hospital’s HIT to Include Quality Metrics

The EHR system of SHH is outdated and requires applicable updates to give a better range of quality criteria on mammograms and colonoscopies. There are several ways by which the EHR system of SHH can be bettered by adding redundant features similar to social work tabs, which will integrate patient health data and keep track of visits with cases. Also, the quality criteria applicable to patient care pretensions will be integrated within EHR (Aerts et al., 2021). These quality criteria will be rates of preventative wireworks similar to mammograms and colonoscopies, drug crimes, patient satisfaction, and quality of care. The SHH will unite with public health departments and other conventions to gather data on cases not entering recommended individual tests, including mammograms and colonoscopies (Dawson et al., 2021).

By exercising population health data, it’ll be easier for SHH to identify trends and walls to watch that people encounter during routine individual tests. This data will be anatomized to point to specific case populations, similar to women seeing gynecologists demanding targeted interventions (Eckelman et al., 2020). These problems can be answered by enforcing care collaboration strategies similar to using the EHR to identify at-risk cases, rehearsing monuments and cautions for providers to engage with at-risk cases, and promoting care collaboration to achieve advanced rates of cases witnessing preventative wireworks. This approach will also help track the health information from the community to make necessary advancements grounded on the gathered data (Watterson et al., 2020).

NURS FPX 6612 Assessment 2 Quality Improvement Proposal

Several issues can arise during expanding megahit within the association.

• The association requires acceptable finances to apply practical ways to enhance EHR features and ameliorate interoperability, including quality criteria. Due to a limited budget, the association must meet fiscal conditions similar to seller selection and elevation of EHR systems (Gill et al., 2020).
• The healthcare association is vulnerable to inconsistent standardized data, which hinders assessing the delicacy of gathered data on quality criteria.
• The association is also prone to face resistance to changes that are allowed to be enforced within EHR and exercised clinically. This resistance to change from staff can impact the effectiveness of including quality criteria without making them adequately used (Cho et al., 2021).

These issues can be rationally answered by following strategies.

• Uniting with other healthcare associations for finances can ameliorate SHH’s fiscal capacity.
• Introduce the standardized data protocols to maximize delicacy in assessing added-up data on quality criteria.
• Educate the healthcare staff on the benefits of using recently upgraded EHR in patient care quality and how it can grease timely care treatments (Cho et al., 2021).

NURS FPX 6612 Assessment 2 Quality Improvement Proposal

Expanding the megahit in the environment of upgrading EHRs at SHH integrates the vital places of informatics in nursing care in the form of nanny informaticists. The nanny informaticist specializes in care collaboration through the effective use of megahit, facilitates care planning, and streamlines communication among healthcare staff. Also, the nanny informaticist conducts training and educational programs on promoting care collaboration by using informatics tools (Gill et al., 2020). The training sessions are acclimatized to address specific workflows and use cases applicable to nursing care collaboration. Also, informatics enterprises similar to upgraded EHR use in hospitals foster a culture of nonstop enhancement as the nurses continue to solicit EHR feedback and apply it in the enterprise (Eckelman et al., 2020). Using megahit and informatics tools within healthcare systems, including SHH, quality criteria can be better incorporated and employed to ameliorate patient care.

Information Gathering in Healthcare

Healthcare systems use patient health information to assess quality criteria and trends in delivering high-quality care and dissect the dragging areas. The primary focus of information gathering in healthcare settings like SHH is to gain comprehensive data about cases, processes, issues, and organizational performance. This information is the foundation for substantiation-grounded decision-making and the development of directorial practices to enhance patient care and functional effectiveness (Hathaliya & Tanwar, 2020).

• EHRs can be practical tools to gather information about cases’ clinical health data and estimate treatment performed and achieved issues. For illustration, the information displayed on EHR, including patient demographics, medical history, lab results, drug lists, and treatment plans, can be. Used by clinicians to make well-informed and aware opinions about case care (Eckelman et al., 2020).
• The association can also gather data on quality criteria and performance pointers to assess the effectiveness of healthcare installations. For illustration, drug crimes display the need to include interventions that promote safe drug administration (Lv & Qiao, 2020).
• Information gathering in the association also encompasses functional data similar to staffing situations and resource application. These data help healthcare associations identify openings to ameliorate the quality of care and overall organizational performance (Lv & Qiao, 2020).

NURS FPX 6612 Assessment 2 Quality Improvement Proposal

At SHH, healthcare associations can gather information on these aspects and interrogate about patient health data through EHR and particular interviews. One similar illustration from SHH includes communicating with a case named Caroline McGlade, combating bone cancer, and describing her lack of knowledge in conducting mammograms and preventative care. The information handed out shows a dragging factor behind preventative care at SHH due to fiscal constraints and the need for further education about precautionary care (Ye, 2021). Using this information, acclimatized strategies can be developed and enforced to promote preventative care, essential for SHH to qualify as an ACO.

Potential Problems with Data Gathering Systems and Outputs

Healthcare information plays a vital part in perfecting organizational performance. This is possible by gathering ample data from healthcare systems and determining logical labors. The data collection can be from patient doors, EHRs, functional data, fiscal data, dashboard metric evaluation, and case-reported feedback. Data-gathering procedures can stem colorful problems that lead to poor data affairs (Aerts et al., 2021). These problems include

Privacy and Security Concerns

Healthcare data-gathering systems must cleave to strict sequestration and security regulations to cover patient confidentiality and prevent unauthorized access or breaches. Failure to adequately guard sensitive case health information can affect legal and ethical consequences similar to actions, suits, eroded patient trust, and damaged organizational character. These enterprises can be addressed by enforcing robust data encryption and stronger authentication mechanisms to help prevent data breaches and cyberattacks (Hathaliya & Tanwar, 2020).

Data Overload and Information Overload

Inordinate data collection and reporting can overwhelm healthcare providers, leading to information overload and cognitive fatigue. This results in disabled clinical decision-making and workflow effectiveness as clinicians must sift through large data volumes to prize crucial findings. This can be overcome by prioritizing data collection efforts to capture practicable information that directly informs the decision-making process and quality enhancement action. Also, dashboards can be erected to present data in a terse or stoner-friendly format that facilitates quick interpretation and decision-making (Ye, 2021).

The misgivings in dealing with these challenges also persist. There’s a query in anticipating all safety pitfalls and cyberattacks due to evolving technologies, which may question the effectiveness of security measures integrated within the system. The point of query lies in the delicacy of large volumes of data uprooted by healthcare professionals. This requires effective tools to show the delicacy and absoluteness of data gathered (Ihnaini et al., 2021). The healthcare professionals at SHH must be apprehensive of these problems when performing data collection processes. Thus, the suggestions handed out must be considered to help prevent the issues from arising during the data collection process.

Conclusion

To conclude, SHH under Vila Health can be good as an ACO by prioritizing technology expansion by upgrading EHR. The system excrescences must be linked and addressed to ensure care collaboration with minimal use of informatics tools. Information gathering is essential to dissect the dragging areas that bear advancements. Still, the problems that can potentially arise during the data collection process must be addressed beforehand to avoid posterior complications.Discover key insights and a polished structure in our NURS FPX 6612 Assessment 2 Quality Improvement Proposal for ACO Development sample paper.

NURS FPX 6612 Assessment 2 Quality Improvement Proposal

Hathaliya, J. J., & Tanwar, S. (2020). An exhaustive survey on security and privacy issues in healthcare 4.0. Computer Communications, 153(1), 311–335. https://doi.org/10.1016/j.comcom.2020.02.018

Ihnaini, B., Khan, M. A., Khan, T. A., Abbas, S., Daoud, M. Sh., Ahmad, M., & Khan, M. A. (2021). A smart healthcare recommendation system for multidisciplinary diabetes patients with data fusion based on deep ensemble learning. Computational Intelligence and Neuroscience, 2021, 1–11. https://doi.org/10.1155/2021/4243700

Lv, Z., & Qiao, L. (2020). Analysis of healthcare big data. Future Generation Computer Systems, 109, 103–110. https://doi.org/10.1016/j.future.2020.03.039 

Millwee, B. (2020). Accountable care organizations in Medicaid. Journal of Ambulatory Care Management, 43(1), 11–14. https://doi.org/10.1097/jac.0000000000000318 

Watterson, J. L., Rodriguez, H. P., Aguilera, A., & Shortell, S. M. (2020). Ease of use of electronic health records and relational coordination among primary care team members. Health Care Management Review, 45(3), 1. https://doi.org/10.1097/hmr.0000000000000222 

Ye, J. (2021). The impact of electronic health record–integrated patient-generated health data on clinician burnout. Journal of the American Medical Informatics Association, 28(5). https://doi.org/10.1093/jamia/ocab017