Introduction
Many health facilities are continuously undertaking process improvement primarily aimed at reducing cases of medical errors and bring consistency in the standard of care received by patients. Hughes (2008) posits that majority of medical errors in a healthcare setting results from faulty and inefficient processes, changing case mix of patients and variations in provider education and experience, among other factors. This paper discusses the parameters and methodologies that could be employed in ensuring that medical errors and lack of consistency in the standard of care are successfully dealt with.
Methodologies for Integrating QI Strategies into Performance Measurements
It is imperative to have a working definition of performance measurements before dealing with the methodologies that could be used to integrate QI strategies into the measurements. According to Davis (2007), “…performance measures are defined as whether or how often a process of care or outcome of care occurs” (para. 4). The ultimate twin objectives of most performance measures in a health facility context is to improve patient care in a cost-effective manner and encourage best clinical practices by allowing clinicians to collect data aimed at identifying gaps in performance and guiding improvement. Davis (2007) acknowledges that the measures fall into three broad categories of data that are comparatively easy to measure in a clinical context: process assessments, outcome assessments, and descriptive assessments.
There exist a number of methodologies which can be used to integrate QI strategies into performance measurements. This section will discuss three such methodologies, namely: Six Sigma, Plan-Do-Study-Act (PDSA), and Root Cause Analysis (RCA). Originally designed as a business approach, Six Sigma “…involves improving, designing, and monitoring process to minimize or eliminate waste while optimizing satisfaction and increasing financial stability” (Hughes, 2008, para. 16). In the context of the performance improvement area (medical errors and lack of consistency), this methodology can be used to measure or assess improvement by comparing the baseline process capability or competence with the process competence after piloting probable solutions for quality improvement. The health facility can use the Six-Sigma methodology to inspect process outcome and count the medical errors or instances of inconsistency in standard of care, calculate a defect rate of the stated variables per million, and then use a statistical table provided in the model to convert the defect rate per million to a σ (sigma) to know the direction taken by the planned improvement efforts. This should be done to pre-analytic processes as well as to post-analytic processes so as to note and quantify the change and inform the improvement strategies (Hughes, 2008).
The PDSA quality improvement initiatives are focused on the establishment of a functional or causal relationship between shifts in the health facility’s processes (particularly behaviors and capacities) and outcomes (Hughes, 2008). This author notes that this application relies on the cyclic nature of impacting and evaluating change, most effectively achieved through small and repeated PDSAs rather that full-size and time-consuming ones, before changes are made to the whole system. In the case scenario, the PDSA cycle may start with determining the nature and scope of medical errors and lack of consistency as observed or recorded in the health facility. The application will then embark in evaluating the changes that should be made and afterwards develop a plan for undertaking the changes proposed. This plan should include all the people involved, the measurement indicators to understand the impact of change, and the critical area(s) where the strategy will be targeted (Hughes, 2008). When changes are implemented and data collected, the results from the implementation of the things needed to check medical errors and inconsistencies will then be evaluated and interpreted by reviewing a number of key measurements that may indicate success or failure.
Originally used in the engineering field, RCA “…is a formalized investigation and problem-solving approach focused on identifying and understanding the underlying causes of an event as well as potential events that were intercepted” (Hughes, 2008, para. 22). In the case scenario, the RCA can be used to identify trends and evaluate risks involving human error with the understanding that the health facility system, rather than individual aspects, is likely the root cause of most problems related to medical errors and lack of consistency in the standard of care. The data collected must focus on these two variables (medical errors and inconsistencies) and casual factors that may have led to the occurrence of the variables. This assists to identify the root causes and develop improvement strategies to reduce future risks in a reactive manner. The application also allows for constant monitoring of the effectiveness of the improvement strategies undertaken (Hughes, 2008). It is imperative to note that the application uses a qualitative process to uncover all underlying causes of the medical errors and inconsistencies in the standard of care by specifically looking at the enabling factors, latent conditions, and situational factors that contributed to or enabled the events under consideration. Afterwards, the RCA develops recommendations for system and process improvements in clinical practices and elimination of inconsistencies based on the outcomes of the analysis.
Information Technology Applications
Information and communication technology (ICT) is fundamental to realizing considerable quality improvement in healthcare practice, not mentioning that ICT can be used to improve access to information in addition to supporting evidence-based decision making in clinical settings (Ortiz & Clancy, 2003). This section will discuss three such applications, namely: Practice-Based Research Networks (PBRNs), Translating Research into Practice (TRIP) and Computer-based Physician Order Entry (CPOE).
Developed by the Agency for Healthcare Research and Quality (AHRQ), “…the PBRNs are made up of community-based, primary care clinicians working together with experienced health services researchers to address clinically relevant healthcare issues and translate research findings into practice to improve quality of care” (Ortiz & Clancy, 2003, para. 12). According to these authors, the PBRNs encourage a “user-driven” paradigm, where clinical and research ideas originate straightforwardly from the “front-line” clinicians who are interacting with patients in their daily practice, hence able to provide the health facility with an exclusive occasion to undertake “real-world” effectiveness research as they go about their duties. For example, clinicians in the health facility can be encouraged to use hand-held devices with programmable decision support materials to reduce instances of medical errors.
Translating Research into Practice (TRIP) is yet another initiative by AHRQ intended to align clinical practices to good scientific evidence regarding a particular medical intervention’s impact on important healthcare outcomes (Ortiz & Clancy, 2003). The authors further acknowledge that this application can help to surmount the gap in clinical knowledge management and application by improving the transformation, implementation, and dissemination of noteworthy research outcomes in the healthcare context. In the case scenario, IT applications such as a multi-media computer program can be used to narrow the gap between knowledge and practice by facilitating the use of meticulously derived evidence to improve disease-related knowledge and attitudes.
Another IT-based clinical decision support system that can be used in QI management initiatives is the computer-based physician order entry (CPOE). According to Sittig & Stead (1994), “…the rational for physician order entry includes process improvement, support of cost-conscious decision making, clinical decision support, and optimization of physician’s time” (p. 108). CPOE is critical as a component of QI management particularly in reducing medical errors and inconsistencies in the standard of care since the user interface of the application will behave consistently in all situations.
Benchmarks & Milestones in Managing Quality Improvement
According to Hughes (2008), “…benchmarking in healthcare is defined as the continual and collaborative discipline of measuring and comparing the results of key work processes with those of the best performers in evaluating organizational performance (para. 6). Benchmarks and milestones are involved in the management of quality indicators to facilitate the measurements intended to improve quality and, more importantly, reveal whether the improvement efforts are leading to change in the principal end point (area of concern) in the desired direction. In the case scenario, the level of patient satisfaction, level of technology adoption, and clinicians’ willingness to use the clinical decision support tools can be used as benchmarks aimed at assessing the direction of efforts taken to reduce medical errors as well as inconsistencies in the standard of care.
Alignment of Performance and Quality Measures to Mission Statement
Health facilities worldwide are mostly driven by the need to offer effective treatment strategies that will improve patient outcomes. This broad goal is underlined in the mission statements, visions, and strategic plans of these organizations. Performance and quality measures are therefore aligned to the mission statements and strategic plans of health facilities by virtue of the fact that they seek to improve processes and procedures that will ensure effective treatment strategies and promote positive patient outcomes. Positive performance and quality measures therefore imply that the health facility is succeeding in providing good-quality healthcare (Hughes, 2008), thus succeeding in meeting their mission statements. The vision of Pine Breeze hospital is to provide efficient cost-effective clinical services to all people. As such, the measures discussed in this paper are aligned with this vision statement since they are interested in shaping the processes that will enable the health facility to provide efficient cost-effective services.
Reference List
Davies, N.L. (2007). Integrating performance improvement and continuing medical education. Almanac, 29(6).
Hughes, R.G. (2008). Tools and strategies for quality improvement and patient safety. In R.G. Hughes (Eds) Patient safety and quality: An evidence-based handbook for nurses. AHRQ. Web.
Ortiz, E., & Clancy, C.M. (2003). Use of information technology to improve the quality of healthcare in the United States. Health Services Research, 38(2), 11-22. Web.
Sittig, D.F., & Stead, W.W. (1994). Computer-based physician order entry: The state of the art. Journal of the American Medical Informatics Association, 1(2), 108-123.