NUR 906 Health Care Finance and Economics
Module 2: Discussion 1
Health systems face multiple barriers that hinder the collection of accurate information, ultimately compromising the quality and accuracy of healthcare data. One major challenge is the lack of standardization in data collection and documentation. Different healthcare providers may record information using inconsistent methods, making it difficult to aggregate or compare data across settings. Outdated technology is another problem because many systems are not designed to integrate with modern electronic health records or data-sharing platforms (Khalil et al., 2025). Limited financial resources often prevent investment in updated software, data infrastructure, and staff training programs. In some facilities, there is also a lack of accountability for data quality, meaning errors go unchecked. Poor communication among clinical, administrative, and technical teams can lead to incomplete or duplicated entries. Additionally, cultural factors, such as viewing documentation as secondary to direct patient care, contribute to inconsistent data practices (Lighterness et al., 2024). These barriers together create unreliable datasets that compromise clinical decisions, reporting accuracy, and organizational performance.
Poor data quality has a direct impact on nursing practice, particularly in the areas of measurement, evaluation, and improvement. Nurses rely heavily on accurate information to assess patient progress, evaluate interventions, and identify trends that signal improvement or decline in health status. When information is incomplete or inaccurate, clinical assessments may be flawed, leading to errors in care planning and evaluation of outcomes. This limits nurses’ ability to measure key indicators, such as infection rates, medication errors, and patient satisfaction (Khalil et al., 2025). Evaluation of care processes becomes less effective when the data do not reflect real clinical performance. As a result, quality improvement efforts may target the wrong issues or fail to achieve measurable progress. Inadequate data also hinders nurses from contributing effectively to evidence-based practice and system-wide initiatives aimed at improving patient safety and reducing costs. Strengthening documentation standards, promoting interprofessional collaboration, and training nurses in data management are crucial steps toward enhancing data reliability and improving patient outcomes.
References
Khalil, H., de Moel‐Mandel, C., Verma, D., Kynoch, K., Fernandez, R., Ramis, M. A., & Opie, J. E. (2025). Characteristics of quality improvement projects in health services: A systematic scoping review. Journal of Evidence‐Based Medicine, 18(1), e12670. https://doi.org/10.1111/jebm.12670
Lighterness, A., Adcock, M., Scanlon, L. A., & Price, G. (2024). Data quality–driven improvement in health care: Systematic literature review. Journal of Medical Internet Research, 26, e57615. https://doi.org/10.2196/57615
Module 2: Discussion 2
Process and outcome metrics often create challenges in healthcare because they focus on different aspects of performance. Process metrics assess the delivery of care, including staff adherence to protocols and the accuracy of documentation. Outcome metrics assess the final results, including patient recovery, mortality rates, and satisfaction levels. When too much focus is placed on processes, it can lead to paperwork overload and reduce time for direct care. On the other hand, focusing only on outcomes ignores the steps that lead to success or failure. To balance the two, nursing leaders can promote evidence-based workflows that link actions to results (Kaplan et al., 2021). For example, measuring timely pain reassessments (process) should connect to pain control scores (outcome). Leaders can also utilize data integration tools to visualize both sets of metrics, enabling teams to see how their actions impact outcomes in real-time. This approach keeps staff motivated and focused on meaningful improvement.
Nursing leaders can also balance attention to process and outcome metrics by involving staff in selecting performance indicators that reflect patient priorities and organizational goals. Transparent communication about why specific measures are tracked helps create ownership among nurses. Leaders should encourage data-driven discussions during staff meetings, where teams analyze both types of metrics together and identify practical solutions. Continuous education on quality measurement and performance improvement can enhance staff confidence in interpreting data and utilizing it for improved care planning (Van der Nat, 2022). Aligning metrics with patient-centered goals supports not only care quality but also operational sustainability, as improved outcomes lead to reduced readmissions and a more efficient use of resources. Nursing leaders who maintain this balance create a culture that values learning, accountability, and consistent improvement.
References
Kaplan, R. S., Jehi, L., Ko, C. Y., Pusic, A., & Witkowski, M. (2021). Health care measurements that improve patient outcomes. NEJM Catalyst Innovations in Care Delivery, 2(2). 10.1056/CAT.20.0527
Van der Nat, P. B. (2022). The new strategic agenda for value transformation. Health Services Management Research, 35(3), 189–193. https://doi.org/10.1177/09514848211011739
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Module 2: Discussion 1
Information is central to aligning cost, quality, and safety. What are some barriers to obtaining “good information” (e.g. quality data) in health systems? How do these barriers affect nursing practice, particularly in measurement, evaluation, and improvement?
Module 2: Discussion 2
Consider the tension that sometimes exists between process metrics and outcome metrics (or structural metrics). How can nursing leaders balance attention to both in a way that supports care quality and organizational sustainability?