Case Analysis: Patient complaints at the Massachusetts General Hospital’s Pre-Admission Testing Area
Case analysis: Patient complaints at the Massachusetts General Hospital’s Pre-Admission Testing Area – Read the case study and become familiar with the key points of the situation without…
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Instructions
To get started with your case analysis:
- Read the case study and become familiar with the key points of the situation without
adopting a position on the case. Read as carefully and objectively as you can. - After becoming familiar with the case, note the main issues as you see them. Prompts or
questions will be provided to help you focus on these. - Identify the key problems and their root causes.
- Develop solutions to the identified problems. Wherever possible, specify objective or
quantitative criteria to assess the solutions (qualitative indicators of success may be too
subjective).
How to organize your presentation/written analysis: - Abstract/Executive Summary: a paragraph or 2 summary including recommendations
- Problem Statement: Overview of key issues arising from case analysis
- Case Analysis: Theory-driven analysis of case(s) identifying factors underlying key issues
- Alternative Solutions: Pros and cons of possible solutions to problems
- Recommendations: Detailed description of optimal solution with rationale
Lastly, prepare several case-specific and topic-specific questions to pose to your peers (2 or 3 Questions pertaining to the case that I could pose to the class for them to answer)
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Solution
Executive Summary
Understanding how healthcare settings can achieve effective care provision is essential as it directly influences healthcare delivery quality and efficiency. This paper offers recommendations to effective hospital management by synthesizing a case scenario of patient complaints at the Massachusetts General Hospital’s Pre-Admission Testing Area (PATA). It provides an overview of significant issues experienced at the Massachusetts General Hospital (MGH) and the inherent causal factors and recommendations for improvement.
The recommended cause for action includes adopting selective technologies, relational care coordination, and patient-centered staffing policies. The recommendations offer effective mechanisms of achieving positive patient feedback and eliminating burnout of care providers.
Keywords: patient complaints, waiting time, quality care
Problem Statement
The case analysis of the Massachusetts General Hospital highlights significant issues that limit the adequate provision of care at the facility. This is highlighted by a complaint letter from a former patient who explains the nature longer waiting time at the facility. Essentially, the growing demand for hospital services and the constrained supply of services form the contest of this case analysis.
Studies have related healthcare quality concerns to low number staffing levels and limited resources (Hughes 2008). The management policies and resource allocation plans and policies have also directly affected the staffing levels, coordination, and quality of care. The impetus for this analysis is to discuss the common issues affecting quality care provision in the health care setting and to provide recommendations for improvement.
Case Analysis
Care Coordination
Poor coordination is highlighted as a significant issue affecting the quality of care provision at MGH. For instance, there exist variabilities in surgeon assessments of patients and incomplete or missing workups, which leads to delayed commencement of surgeries (McCarty et al., 2012). One of the underlying causes is the long waiting time that forces some patients to leave in the middle of assessment and surgeons failing to submit patients’ records. The case scenario at MGH is that of frustrations from physicians who feel surgeons lack control overs the healthcare process.
Poor coordination among care providers leads to paltry care, including inadequate solution to important healthcare, as well as negative patient feedback (Hughes 2008). The delay caused by discontinued workflow causes reduced productivity of the department. So as to achieve positive patient outcomes, relational coordination between practitioners and with patients is foundational in contributing to both care providers’ wellbeing, and patients’ experiences. Havens et al. (2018) argue that hospital settings are a complex environment in which practitioners are segregated by specialization, tasks, and time constraints; thus, efficient coordination is vital.
Staffing and Resources
At the MGH, there is limited operational capacity. For instance, the facility lacks enough personnel to care for the high admission capacity (McCarty et al., 2012). As a result, few surgeries are carried out while others re canceled, which translates to a loss of revenue. The scenario portrays PATA management as unable to implement upgrade proposals due to financial limitations and unsurmountable political and cultural hurdles. Therefore, the existing staff is often overwhelmed by being forced into overtime work and canceling surgeries.
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Studies correlate lover staffing levels with heightened risks of poor patient outcomes, especially with those that require face time (Hughes, 2008). Moreover, Yankovic & Green (2011) argue that resources should be allocated appropriately due to inadequacy despite the lack of scientific findings outlining the efficient methodology for allocating hospital resources. Such findings correlate with the situation present at the MGH.
Redundant Documentation
The case scenario identifies the consequences of fragmentation of workflow and redundant work as delayed admission of patients and consequent negative feedback. For instance, the patient intake, nursing, and assessment forms all contain a significant amount of similar patient information filled by different providers.
Despite the beneficial aspect of redundancy such as providing opportunities to reveal and amend errors (MacMillan et al., 2016), it causes significant delay in providing important clinical procedures, thus crippling the entire system. Redundancy is unproductive and is a major irritation to patients being asked to provide the same information over and over again. Besides, data integrity is called into concern when the same information is collected more than once.
Alternative Solutions
The first possible solution would be to increase working time by estimating direct productive hours of care per patent (HPPO) methodology (Yankovic & Green, 2011). The move will increase the number of patients attended to. However, the method seems impossible since the admission rates of patients are high and sometimes unpredictable. This is exemplified by the charge nurse’s inability to have control of the lunch hour assessments due to an unpredictable number of incoming patients. Besides, the providers are likely to be upset and overworked.
The second solution would be to increase infrastructure and personnel to enable the facility to attend more patients. However, it is impractical to get more personnel and build more rooms due to MGH’s financial incapability (McCarty et al., 2012). This means MGH will have to operate way above their overheads. Therefore, larger projects cannot improve the entire preoperative process due to insurmountable financial and political limitations.
The last alternative solution would be to reduce patient volume. While the move will increase face time for selected patients, the hospital might lose its reputation as the leading innovative research center in anesthesiology and dent its mandate in providing equal care to all that needs (McCarty et al., 2012). Besides, patients who require healthcare services can be limited by conditions set to limit the number of accepted patients.
Recommendations
The first recommendation relates to the American Nurses Association’s advisory on flexible staffing policies centered on patient needs rather than on practitioners’. Such policies are founded on variable factors such as patient needs, fluctuation in healthcare needs, and setting characteristics (Yankovic & Green, 2011). In this context, a queuing approach is a plausible recommendation for PATA. The model constitutes fixing staffing intervals to track patient requests and movements (Yankovic & Green, 2011).
The model is flexible and can be readily used to provide evidence-based guide on staffing decisions (including the number of nurses assigned on a daily basis) considering the random nature of patient requirements and the flexibility needed to achieve a high level of responsiveness. Another approach is through the creation of protocols to help consolidate documentation. The hospital could adopt analytic and subsequent reporting processes to consolidate data from patients, which is essential in determining the efficacy of adopted policies. According to MacMillan et al. (2016), quantifying work in a hospital setting improves efficiency.
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The second recommendation is to adopt quality communication and relationships as a tenet for relational coordination (RC). RC emphasizes functional relationships typified by mutual goals, respect and knowledge (Borkowski, 2015). In this context, providers, along the clinical process, understand their roles and those of their colleagues. According to the contemporary organization theory, coordination can be brought into practice while noting the current status of coordination rather than simply applying a given set of coordination mechanisms (Borkowski, 2015).
For instance, cross-professional intervention, also known as dialogic coordination, is plausible when clinical procedures are insufficient to coordinate workflow. Therefore, in the contest of conflicting guidelines on surgeon assessment as with MGH, relational coordination enhances the visibility between tasks and related assessments.
The last recommendation to the issues affecting MGH is the adoption of selective technology. The adoption of selective technology is founded on the significance of maintenance, growth, and optimization of the existing system to keep up with patient care (Smalley & Keskinocak, 2016).
Digitized management can help providers work smarter rather than harder by adopting selective technologies such as predictive analytic tools, staff scheduling software, and automated vital signs monitor. Therefore, nurses will be able to review schedules and adjust appropriately. The recorder user experience can be used to review the significance of technology in enhancing patients’ experience. Besides, the technologies can prioritize patients’ visits in real-time, allowing staff to focus on patients with immediate attention.
Moreover, the transitioning to a digitized system based on clinical workflow would be plausible for MGH for other reasons. A digitized system would reduce waiting time and avoid redundancy of work, thus reducing patient complaints. The staff scheduling system monitors and prevents overtime work that results in burnout and expensive turnover (Smalley & Keskinocak, 2016).
These technologies are significant in automating repetitive administration tasks such as filling patients’ personal information currently conducted at every care level. Thus, the technologies present a cost-effective opportunity to improve the patients’ experience, care, and efficiency.
Case Questions
- How can hospital departments handle patient-reported complaints?
- What is the significance of effective care coordination and management in a hospital setting?
- How can caregivers overcome burnout?
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References
- Borkowski, N. (2015). Organizational behavior, theory, and design in health care. Jones & Bartlett Publishers.
- Havens, D. S., Gittell, J. H., & Vasey, J. (2018). Impact of relational coordination on nurse job satisfaction, work engagement, and burnout: Achieving the quadruple aim. JONA: The Journal of Nursing Administration, 48(3), 132-140. https://doi.10.1097/NNA.0000000000000587
- Hughes, R. (Ed.). (2008). Patient safety and quality: An evidence-based handbook for nurses (Vol. 3). Rockville, MD: Agency for Healthcare Research and Quality. https://www.ncbi.nlm.nih.gov/books/NBK2676/#ch25.rl1
- MacMillan, T. E., Slessarev, M., & Etchells, E. (2016). eWasted time: Redundant work during hospital admission and discharge. Health informatics journal, 22(1), 60-66. https://doi.org/10.1177/1460458214534091
- McCarty, K., Gallien, J., & Levi, R. (2012). Massachusetts General Hospital’s Pre-Admission Testing Area (PATA). http://hdl.handle.net/123456789/2753
- Smalley, H. K., & Keskinocak, P. (2016). Automated medical resident rotation and shift scheduling to ensure quality resident education and patient care. Health care management science, 19(1), 66-88. https://doi.org/10.1007/s10729-014-9289-8
- Yankovic, N., & Green, L. V. (2011). Identifying good nursing levels: A queuing approach. Operations research, 59(4), 942-955. https://doi.org/10.1287/opre.1110.0943
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