NURS FPX 6016 Assessment 3 Data Analysis and Quality Improvement Initative Proposal

Name

Capella university

NURS-FPX 6016 Quality Improvement of Interprofessional Care

Prof. Name

Date

Data Analysis and Quality Improvement Initiative Proposal

Hello, everyone. I am ________. Today, I am excited to share a detailed strategy to improve patient safety and streamline care provision within healthcare settings.

 Near-miss events in healthcare settings underscore the constant need for vigilance and improvement in patient safety protocols (Griffey et al., 2023). One such incident at Stanford Health Care, involving a near-miss medication administration error, is a distressing reminder of the potential risks and consequences inherent in healthcare delivery. This discussion focuses on the critical importance of data analysis and quality improvement initiatives to address such incidents effectively.

Through a comprehensive examination of benchmark data, identification of healthcare issues, and integration of interprofessional perspectives, this analysis aims to propose a robust quality improvement initiative tailored to the unique needs of Stanford Health Care. By leveraging collaboration strategies and technology, the proposed initiative seeks to improve patient care and work-life excellence, ultimately elevating the standard of care delivery.

Analysis of Dashboard Data Related to Healthcare Issues

National-level and State-level Benchmarks

Healthcare institutions must measure their performance against established benchmarks to ensure quality care and patient safety. These benchmarks are provided by national organizations such as The Joint Commission (TJC), the Centers for Medicare & Medicaid Services (CMS), and the National Committee for Quality Assurance (NCQA). TJC emphasizes the importance of using health information technology systems, such as Electronic Health Records (EHRs), to increase patient care and decrease medication mistakes (NAMSS, 2023; TJC, 2023).

They require institutions to measure near miss events that can lead to Adverse Drug Events (ADEs) and adherence to drug administration protocols. CMS’s Hospital Quality Initiative provides benchmarks focusing on reducing Hospital-Acquired Conditions (HACs) and Patient Safety Indicators (PSIs), including metrics for complications and adverse events (CMS, 2023). NCQA’s Healthcare Effectiveness Data and Information Set (HEDIS) includes measures relevant to medication management, such as the proper use of high-risk medications and medication reconciliation post-discharge (NCQA, 2023).

Identified Healthcare Issues

Following the critical adverse dialysis event involving Rachel, a healthcare issue identified at Stanford Health Care is the high incidence of near-miss events leading to medication errors and ADEs, particularly with medications like human albumin used in dialysis. The data reveals that the institution’s performance on these metrics is below national benchmarks, indicating a need for significant improvement.

Table: Metrics Comparison

Metrics	Benchmark Data	Stanford Health Care’s Data
Near miss events that can lead to Adverse Drug Events (ADEs)	TJC: Less than 5% incidence rate (TJC, 2023)	7.5% incidence rate (Stanford, n.d.)
Medication Errors	CMS: Less than 1.5 errors per 1,000 medication doses (CMS, 2023)	3.2 errors per 1,000 medication doses (Stanford, n.d.)
Medication Reconciliation	NCQA: 90% compliance with medication reconciliation (NCQA, 2023)	75% compliance
Compliance with Medication Protocols	TJC: 95% adherence to drug administration protocols (TJC, 2023)	85% adherence
Patient Safety Indicators (PSIs)	CMS: Less than 2 PSIs per 1,000 patient days (CMS, 2023)	3.8 PSIs per 1,000 patient days (Stanford, n.d.)

Quality of the Data Evaluation

Stanford Health Care collects various data points related to medication administration, patient safety, and compliance with treatment protocols. This data includes incident reports, patient wristband checks, medication reconciliation records, and compliance with pre-administration checklists. The quality of this data is critical for understanding the current state of patient safety and identifying areas for improvement. The data indicates several trends and issues (Caspi et al., 2023).

For instance, there is a high incidence of near miss events that can lead to ADEs and medication errors, which points to lapses in the medication administration process. The data also shows inconsistent medication reconciliation, particularly post-discharge, which can lead to patient safety issues. Compliance with medication protocols is below national benchmarks, indicating a need for enhanced training and stricter adherence to procedures (Caspi et al., 2023).

Analyzing the trends, it is evident that the occurrence of near miss events and medication errors is not random but rather indicative of systemic issues in the medication management process. The outcome measures include the rate of near miss events, the frequency of medication errors, and the adherence to pre-administration checklists. To calculate specific rates, detailed data on the number of ADEs per patient, the frequency of medication checks, and the compliance rate with medication protocols must be collected (Lahti et al., 2023).

Quality Improvement Initiative and Proposed Strategies 

In response to the critical adverse dialysis event involving Rachel and the identified deficiencies in medication administration at Stanford Health Care, a comprehensive Quality Improvement (QI) initiative is proposed. This initiative focuses on enhancing patient safety and ensuring stringent adherence to medication protocols, particularly for medications frequently used in dialysis, such as human albumin (Fair et al., 2023). The primary objective of this QI start is to lessen the occurrence of near miss events that can lead to ADEs and medication errors by implementing a more rigorous pre-administration checklist and integrating advanced Electronic Health Record (EHR) functionalities. This includes incorporating Barcode Medication Administration (BCMA) technology to ensure accurate patient identification and medication administration (Fair et al., 2023).

Data analysis reveals that Stanford Health Care’s current performance metrics for ADEs and medication errors significantly exceed national benchmarks. Specifically, the incidence of ADEs at 7.5% surpasses the TJC’s benchmark of less than 5%, and medication errors occur at a rate of 3.2 per 1,000 medication doses, compared to the CMS benchmark of less than 1.5.

Additionally, compliance with medication reconciliation stands at 75%, well below the NCQA’s benchmark of 90% (Stanford, n.d.). These figures underscore the need for targeted interventions to enhance medication safety and protocol adherence. The proposed interventions are founded on the PDSA Quality Improvement model, emphasizing iterative planning, implementation, observation, and adjustment cycles. This model ensures a systematic approach to implementing and evaluating changes, fostering continuous improvement in patient care processes (Griffeth et al., 2023).

Strategies for Improvement

• Enhanced EHR Integration: Implement an advanced EHR system with BCMA technology to ensure precise patient identification and medication administration. This technology will minimize errors by requiring healthcare providers to scan medication labels and patient wristbands, thereby verifying correct matches in real time (Palojoki et al., 2021).
• Comprehensive Training Programs: Conduct extensive training for healthcare staff on the new EHR functionalities and the importance of adherence to updated medication protocols. This training will emphasize the five rights of medicine: the right patient, drug, dose, route, and time (Palojoki et al., 2021).
• Standardized Communication Protocols: Develop and implement standardized communication practices to improve coordination among interprofessional teams. Clear written and verbal communication guidelines will ensure accurate information transfer and understanding (Farcas et al., 2020).
• Continuous Monitoring and Feedback: Create a system for continuing checking and feedback to measure the efficiency of the strategies. Regular audits and data reviews will help identify areas of improvement and ensure continuous adherence to protocols (Farcas et al., 2020).

Expected Outcomes

The expected outcomes of this QI initiative include a significant reduction in the occurrence of near miss events that can lead to ADEs and medication mistakes, improved compliance with medication protocols, and enhanced patient safety. By aligning with national benchmarks and leveraging advanced health information technology, Stanford Health Care aims to foster a safer and more reliable medication administration process (Farcas et al., 2020). This ultimately leads to better patient outcomes and increased trust in the healthcare system.

Knowledge Gaps and Uncertainties

Despite the proposed QI initiative, uncertainties about the long-term sustainability of these improvements and staff adherence to new protocols over time still need to be addressed. Additionally, more detailed patient outcome data and a thorough cost-benefit analysis are needed to assess the initiative’s financial impact. Further evaluation is required to understand staff engagement techniques to ensure consistent protocol adherence and effective use of the advanced EHR system (Lahti et al., 2023).

Integrating Interprofessional Perspectives

Incorporating interprofessional viewpoints is essential for the success of the QI initiative aimed at increasing patient care and work-life excellence at Stanford Health Care. Nurses, physicians, pharmacists, and IT specialists are vital in this collaborative effort. Nurses who are on the frontline of medication administration provide valuable insights into the practical challenges and needs associated with the new EHR system. Their feedback is essential for designing user-friendly interfaces and protocols that support safe and efficient medication administration practices. Additionally, nurses’ experiences with patient interactions can help identify areas where the EHR system can improve patient safety and care quality (Yan et al., 2021).

Physicians contribute by assessing how the EHR system supports clinical decision-making and treatment protocols. Their input ensures that the system facilitates accurate and timely patient management, aligning with the five rights of medicine: the right patient, drug, dose, route, and time. By involving physicians in the design and implementation process, the initiative can address potential clinical workflow disruptions and ensure the system enhances, rather than hinders, patient care (Yan et al., 2021).

NURS FPX 6016 Assessment 3 Data Analysis and Quality Improvement Initative Proposal

Pharmacists bring expertise in medication safety and pharmaceutical care, which is crucial for evaluating the EHR system’s impact on drug acquisition, storage, preparation, and administration processes. Their role includes assessing how well the system supports medication reconciliation and prevents near miss events. Their perspective helps ensure that the EHR system effectively tracks and manages medications, reducing the likelihood of errors and enhancing overall patient safety (Brady et al., 2022).

IT specialists are essential for the technical implementation and maintenance of the EHR system. Their expertise ensures that the system is robust, reliable, and user-friendly. They work closely with healthcare professionals to tailor the EHR interface to meet specific safety and medication administration requirements (Foster et al., 2022). Ongoing support and training from IT specialists are vital for maintaining system functionality and addressing issues post-implementation. By incorporating these interprofessional perspectives, the QI initiative can significantly improve patient care and work-life excellence. The collaborative approach ensures that the EHR system is well-integrated into clinical workflows, reducing errors, enhancing patient care, and improving the overall efficiency of healthcare delivery (Foster et al., 2022).

Assumptions

Assumptions underlying the integration of interprofessional perspectives include the belief that each healthcare role brings unique insights critical for optimizing the QI initiative. It assumes that nurses, physicians, pharmacists, and IT specialists are willing to engage in the collaborative process and share their expertise actively. Furthermore, it presupposes effective communication and mutual respect among team members, facilitating productive discussions and problem-solving. Additionally, it assumes that the EHR system implementation aligns with the organization’s goals and priorities, garnering support from all stakeholders (Brady et al., 2022).

Effective Collaboration and Communication Strategies

Efficient teamwork tactics play a vital role in advancing quality enhancement in interprofessional healthcare at Stanford Health Care. One approach entails creating transparent communication pathways and nurturing an environment of candid discussions among members of the healthcare team. This allows for the exchange of ideas, concerns, and feedback, facilitating collaboration and problem-solving. Regular interdisciplinary meetings and forums provide opportunities for nurses, physicians, pharmacists, and IT specialists to come together to discuss patient care strategies, share best practices, and address challenges related to the implementation of the EHR system (Kosteniuk et al., 2023).

Another crucial strategy is promoting mutual respect and understanding among team members. Each healthcare professional brings unique expertise and perspectives, and recognizing and valuing these contributions is essential for effective collaboration. By fostering an environment of mutual respect, where all team members feel heard and valued, healthcare organizations can harness their workforce’s collective knowledge and skills to drive quality improvement initiatives forward (Beckmann et al., 2021).

NURS FPX 6016 Assessment 3 Data Analysis and Quality Improvement Initative Proposal

Promoting shared accountability and responsibility for patient outcomes can also enhance collaboration and teamwork. When all team members actively engage in the QI initiative and feel accountable for its success, they are more likely to collaborate effectively and work towards common goals. This can involve establishing interdisciplinary QI teams tasked with specific objectives related to patient care and work-life excellence (Beckmann et al., 2021).Moreover, utilizing technology to facilitate collaboration can improve communication and coordination among healthcare team members.

For example, implementing secure messaging platforms or EHRs allows real-time access to patient information and facilitates communication regarding medication orders, treatment plans, and patient status updates. It is assumed that by leveraging technology effectively, healthcare organizations can streamline workflows, reduce errors, and enhance interprofessional collaboration (Kosteniuk et al., 2023). Moreover, it is assumed that applying effective collaboration strategies such as clear communication, mutual respect, shared accountability, and technology utilization, Stanford Health Care can promote quality improvement in interprofessional care and achieve better patient outcomes.

Conclusion

In conclusion, the analysis of data and proposal for a quality improvement initiative at Stanford Health Care focuses the acute role of data-driven executive in increasing patient safety and care quality. Through a thorough examination of benchmark data and identification of healthcare issues, opportunities for improvement have been identified. Integrating interprofessional perspectives and collaboration strategies is pivotal in driving the proposed initiative forward, ensuring comprehensive and practical solutions. 

References

Beckmann, M., Dittmer, K., Jaschke, J., Karbach, U., Köberlein-Neu, J., Nocon, M., Rusniok, C., Wurster, F., & Pfaff, H. (2021). Electronic patient record and its effects on social aspects of interprofessional collaboration and clinical workflows in hospitals (eCoCo): A mixed methods study protocol. BMC Health Services Research, 21(1). https://doi.org/10.1186/s12913-021-06377-5 

Brady, J. E., Simon, S. R., Yeksigian, K., Zillich, A. J., Moyer, J., & Linsky, A. (2022). Can nonclinicians classify medication discrepancies as accurately as clinical pharmacists? A validation study. Health Science Reports, 5(5). https://doi.org/10.1002/hsr2.824 

NURS FPX 6016 Assessment 3 Data Analysis and Quality Improvement Initative Proposal

Caspi, H., Perlman, Y., & Westreich, S. (2023). Managing near-miss reporting in hospitals: The dynamics between staff members’ willingness to report and management’s handling of near-miss events. Safety Science, 164. https://doi.org/10.1016/j.ssci.2023.106147 

CMS. (2023, September 6). Quality measures. Www.cms.gov. https://www.cms.gov/medicare/quality/measures 

Fair, L., Burns, C., & Lindsley, J. (2023). Improving medication safety in an ICU. American Journal of Nursing, 123(7), 39–45. https://doi.org/10.1097/01.naj.0000944924.15137.c8 

Farcas, A., Ko, J., Chan, J., Malik, S., Nono, L., & Chiampas, G. (2020). Use of incident command system for disaster preparedness: A model for an emergency department COVID-19 response. Disaster Medicine and Public Health Preparedness, 15(3), 1–6. https://doi.org/10.1017/dmp.2020.210 

NURS FPX 6016 Assessment 3 Data Analysis and Quality Improvement Initative Proposal

Foster, L., Choxi, S., Rosenberg, R. E., Tracy, J., Toscano, D., Betancur Paez, J., & Glick, A. F. (2022). Meds to beds: A quality improvement approach to optimizing the discharge medication process for pediatric patients. The Joint Commission Journal on Quality and Patient Safety, 48(2), 92–100. https://doi.org/10.1016/j.jcjq.2021.09.014 

Griffeth, E. M., Gajic, O., Schueler, N., Todd, A., & Ramar, K. (2023). Multifaceted intervention to improve patient safety incident reporting in intensive care units. Journal of Patient Safety, 19(7), 422–428. https://doi.org/10.1097/PTS.0000000000001151 

Griffey, R. T., Schneider, R. M., & Todorov, A. A. (2023). Near-miss events detected using the emergency department trigger tool. Journal of Patient Safety, 19(2), 59–66. https://doi.org/10.1097/pts.0000000000001092 

Kosteniuk, J., Morgan, D., Elliot, V., Bayly, M., Boden, C., & O’Connell, M. E. (2023). Factors identified as barriers or facilitators to EMR/EHR based interprofessional primary care: A scoping review. Journal of Interprofessional Care, 38(2), 1–12. https://doi.org/10.1080/13561820.2023.2204890 

Lahti, C., Takala, A., Holmström, A.-R., & Airaksinen, M. (2023). Applicability of drug-related problem (DRP) classification system for classifying severe medication errors. BMC Health Services Research, 23(1). https://doi.org/10.1186/s12913-023-09763-3 

NAMSS. (2023). NAMSS: 2023 Annual conference recording: Verify and comply: CMS, TJC, NCQA, ACHC, and DNV credentialing standards compared and contrasted. Learn.namss.org. https://learn.namss.org/products/2023-annual-conference-recording-verify-and-comply-cms-tjc-ncqa-achc-and-dnv-credentialing-standards-compared-and-contrasted 

NCQA. (2023). HEDIS and Performance Measurement. NCQA. https://www.ncqa.org/hedis/ 

Palojoki, S., Saranto, K., Reponen, E., Skants, N., Vakkuri, A., & Vuokko, R. (2021). Classification of electronic health record–related patient safety incidents: Development and validation study. JMIR Medical Informatics, 9(8). https://doi.org/10.2196/30470 

NURS FPX 6016 Assessment 3 Data Analysis and Quality Improvement Initative Proposal

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Yan, Q., Jiang, Z., Harbin, Z., Tolbert, P. H., & Davies, M. G. (2021). Exploring the relationship between electronic health records and provider burnout: A systematic review. Journal of the American Medical Informatics Association, 28(5), 1009–1021. https://doi.org/10.1093/jamia/ocab009