Data Collection for Healthcare Quality Improvement

Improved health care

The improvement of healthcare as a system represents a network of processes for consistent improved care. The processes within the system should be measured, improve, analyzed and controlled. The improvement of healthcare often requires being committed, with the aims to ensure process standardization for achieving predictable results, reducing process variation, as well as improve outcomes in terms of patients, healthcare systems, and organizations.

Quality improvement (qi)

In the context of quality improvement (QI), data management is a crucial aspect. It is necessary to measure a health system’s inputs, outputs, and clinical quality measures. Data management entails processes of ongoing monitoring and management, with QI teams being able to to identify and implement opportunities for improvement. When changes in quality are applied for the better, progress is being monitored. By doing so, it becomes possible to improve outcomes that include patient and staff satisfaction, organizational costs, and revenues linked to patient care.

Core measure: Patient satisfaction

The measure of patient satisfaction is an indicator of the degree to which patients are happy with their healthcare – inside and outside doctor’s office. It is a measurement that indicates care quality and provides valuable insight into different aspects of medicine, including care effectiveness and level of empathy. Patient satisfaction is a representation of patient-centered care in which the efforts of healthcare providers are focused on providing maximum support to patients and addressing all of their health concerns. In the modern healthcare context, technologies have shown to help boost patient satisfaction.

Why collect data for patient satisfaction?

Collecting various patient data can help inform progress and outcomes. Therefore, information can be seen as a catalyst of change and the development of new strategies to be implemented in the healthcare industry. In this instance, data is rather used for the purposes of learning and not judgment regarding what has gone wrong and cause dissatisfaction. With the help of data collection, healthcare professionals and researchers can help determine how changes can lead to health improvement. It becomes easier to identify which ideas are beneficial for refining intended outcomes.

Sources of Data collection

The main sources of data collection include patient and heath statistics surveys, administrative and medical records (EHRs), data on claims and vital records, as well as other sources such as registries, surveillance, peer-reviewed literature. It allows using best available data with research evidence, asking relevant clinical questions, and using preventative measures that fit certain healthcare issues. Besides, it becomes possible to look for gaps in research evidence and fill them.

Limitations and challenges

When it comes to the limitations and challenges associated with handling data collection for quality improvement, there are difficulties leveraging real-time data-driven insights. It becomes complicated to handle complex data storage and disparate data sources because staff does not have enough training to handle them. Besides, there is a challenge of the increased administrative requirements of medical health care under HIPAA. It is also important to note that data collection, especially concerning patients, comes with high costs (Jones et al., 2015).

Impact on quality measure domains

With the help of data collection, it becomes easier to improve the four quality measure domains, which include structure, process, outcome, and patient experience. The structure domain can improve with the systematic use of data collected from electronic medical health records. The process domain can improve health maintenance procedures using up-to-date data on patients. The outcome domain can improve healthcare interventions based on relevant data, while the patient experience domain can improve with the gathering of feedback from patients.

Relationship between the domains

Patient satisfaction is a core measure that can be intertwined into the four quality measure domains. Importantly, patient satisfaction can be an indicator of healthcare providers’ capacity, systems, and processes of care provision. If the processes are carried out successfully and with attention to relevant details, they can improve patient health, and, therefore, satisfaction. Therefore, there is a direct connection between structure and process domains in which patient satisfaction plays an important role. In terms of the relationship between outcome and patient experience, patient outcomes that emerge as a result of either high- or poor-quality health care will measure patient satisfaction. In turn, the degree of patient satisfaction will affect patient experience.

Data collection

To achieve an improvement in the quality of care and patient satisfaction, the process of data collection should not be complication. Teams gather together for guiding evidence and influencing changes, and such teams must be diverse enough to provide their expertise and knowledge for boosting the measurements and outcomes. Besides, it is possible to carry out time series analysis using small amounts of data that is displayed frequently. Same data can be used differently depending on what should be learned.

Leveraging data for Patient satisfaction

After each quality improvement initiative is completed, relevant healthcare data must still be collected. Any relevant improvements, if they can be made, should be be maintained and monitored. Achieving a long-term impact of quality improvement I possible through the sustained system changes and the implementation of the Plan-Do-Study-Act cycle. Overall, healthcare quality improvement is linked to the consistent post-data collection efforts aimed at studying the impact of the implemented efforts aimed at improving satisfaction.

Reference list

Abu-Baker, N. N., AbuAlrub, S., Obeidat, R. F., & Assmairan, K. (2021) ‘Evidence-based practice beliefs and implementations: a cross-sectional study among undergraduate nursing students’, BMC Nursing, 20(13).

CMS. (2021) Quality measurement and quality improvement

Jones, C., Gannon, B., Wakai, A., & O’Sullivan, R. (2015) ‘A systematic review of the cost of data collection for performance monitoring in hospitals’, Systematic Reviews, 4, p. 38.

Shah, A. (2019) ‘Using data for improvement’, BMJ, 364.

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