Overview of Quality in Health Care Health, Medicine, Nursing Essay

Overview of Quality in Health Care
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Overview of Quality in Health Care
Introduction
Quality in healthcare is dependant on how information is shared, stored, and interpreted. In this regard, healthcare institutions must be able to measure, record, and communicate information accurately to avoid errors or negative care outcomes. The need for evidence-based practices and accurate implementation of healthcare information management systems is essential in warranting positive care outcomes as well as enhanced patient safety. When data management is ignored, there are higher risks for medical malpractices, clinical errors, and overall poor health outcomes. The paper focuses on healthcare data management and its impact on quality of care.
Healthcare Data Management
Healthcare data management entails the process of recording, storing, and analysing of healthcare information in order to create a comprehensive perspective of the processes, patients, and care standards so as to improve the quality of care. Evidence-based interventions in the process of care provision are direct outcome of effective management of health information (Adane, Gizachew, & Kendie, 2019). Many institutions have poor data management incentives, which leads to numerous medical malpractices, errors, and poor care outcomes. The main challenges resulting from poor data management incentives include higher costs of clinical care, inefficient operations and care processes, increased medical errors, diagnosis errors, and wrong drug administration. With proper incentives for managing healthcare information, these issues can be addressed and accurate decisions made regarding the processes of care (Nahatakyan, n.d.).
Evidence-Based Practice, Research, and Performance Improvement
Healthcare relies on evidence-based practices to ensure that there is continuous improvement of care quality. Notably, research allows organizations to have a “systematic evidence” concerning a certain approach that ensures it can assist in enhancing results (Luciano, Aloia, & Brett, 2019). Research can be used to address the challenge of data management by formulating context-appropriate measures for a particular environment. This considers the existing infrastructure, the improvements that must be made, and training required to warrant effectiveness. In this regard, research is the primary step towards evidence-based practice because the benefits of the adopted data management model outweigh the potential risks (Luciano, Aloia, & Brett, 2019). Improving the performance of a healthcare team or organization requires appropriate utilization of existing information. Therefore, data management is an essential aspect that warrants effectiveness of the clinical processes (HRSA, 2011).
The performance improvement requires measurement of the inputs, processes, and outcomes in order to acquire a holistic outlook to healthcare decisions. Practitioners must be at the frontline of advocating for proper data management systems. This will allow easy communication across departments, leading to enhanced quality of care. With a focus on efficient utilization of healthcare records, there will be an overall, reduction on waste, both of time and resources (HRSA, 2011). Performance improvement incentives applied in data management allow team leaders to highlight the gaps and create incentives for sealing these gaps. In order to improve the performance through data management, there is a need for continuous measuring and evaluation of the existing processes. This will allow the team to understand how quality care outcomes can be achieved. Moreover, because personnel are part of the care provision process, there is need to consult and lobby for their input. This will eliminate any potential risks and ensure that all stakeholders are part of the proposed improvements (HRSA, 2011).
Quality Improvement Process
Effective management of healthcare information and data is an effective way of enhancing care quality. Moreover, it is a means through which medical errors are eliminated and patient satisfaction enhanced. In order to ensure that there is an effective approach for managing healthcare data, the Continuous Quality Improvement (CQI) process will be utilized (Hughes, 2008). This is informed by the continuous change in technology, which is a means for improving data storage, manipulation, and communication. The central idea of CQI is that there is an opportunity for improvement at every stage. This ensures that the organization’s data management system is optimized for the current challenges. Moreover, it inculcates multidisciplinary perspectives in quality improvement, ensuring that decisions at each level of care are evidence-based (Hughes, 2008).
Another advantage of using the CQI framework comes from the focus on microsystems. With sufficient information, organization will be able to assess each care aspect independently. The small functional units within the hierarchy of the organization’s...