Healthcare quality and safety improvement is a commitment that governments, healthcare professionals, and the public share. In many cases, these efforts involve changing how healthcare is organized and delivered at the systems level (Hill et al., 2020). Continuous Quality Improvement (CQI) within healthcare has gained momentum to enhance care provision while reducing costs. The use of CQI in health care has evolved since the 1990s by borrowing from quality assurance techniques and management theories practiced in industries and manufacturing sectors. The essay discusses CQI by exploring two process measures and one outcome measure that can be used for CQI. In addition, it will discuss how these measures were selected, methods of data collection, and how to determine success and data-driven, cost-effective solutions to the issue.
Process Measures
Hospitals use CQI metrics, or process measures, to evaluate the efficacy of the patient discharge procedure. One process measure is ‘Length of Stay’ or LoS, the time a hospitalized person takes from admission to discharge. LoS measures seek to reduce the time that lapses between when a doctor writes a discharge summary and when the patient is released from the hospital to ensure patients experience shorter hospital stays (Daghistani et al., 2019). The other process measure is how long medication orders take after release from the pharmacy until they are delivered and used by patients upon being discharged from wards. Usually, delays in pharmacy delivery could stall patient release, providing an opportunity for improving healthcare services. Thus, these two indicators reflect the efficiency of the entire healthcare system. They help evaluate whether specific actions concerning patient care are successful and can be used to design strategies that either maintain or enhance the quality of future patients’ experiences.
Outcome Measure
The Centers for Medicare and Medicaid Services (CMS) use outcome measurements or metrics to quantify patients’ outcomes, evaluate healthcare procedures, and report the outcomes to commercial insurance providers and the government (Boney et al., 2021). An example of an outcome measure is surgical site infection cases. Healthcare organizations are keen on tracking surgical site infections because of the higher mortality rate associated with it, increased treatment costs, and the risk of non-payment. Using outcome metrics allows us to assess whether a particular process or its outcomes align with the intended objectives. It is important to remember that various factors, some of which are beyond the control of healthcare providers, affect these outcome measures. Moreover, healthcare professionals can gain insights by monitoring the progress of specific patient groups over time. When care outcomes do not meet expectations, it becomes evident through these outcome metrics, thus emphasizing their importance in healthcare evaluation.
Description of Why Each Measure Was Chosen.
I chose “Length of Stay” and the duration medication orders take after release from the pharmacy to when it is delivered and used by patients because they are essential for effective planning and management of healthcare facility resources. According to Stone et al. (2022), healthcare organizations intentionally predict patients’ LoS to improve care, manage hospital expenses, and enhance service efficiency. On the other hand, surgical site infections impact how long the patient has to stay in the hospital, their likelihood of dying, and the total cost of care, including the cost of care that insurance companies do not cover. Surgical site infections also leave a lasting impression on patients. It explains why it is essential to consider the overall patient experience when assessing quality healthcare delivery (Simunovic et al., 2021). Therefore, it is essential to implement infection prevention measures when higher infection rates are realized. These may include checking everything from surgical equipment and procedures to cleaning rooms between procedures.
How Data Would be Collected for Each Measure
In Continuous Quality Improvement (CQI), data collection for process and outcome metrics entails systematic methods. Therefore, data for process measures can be collected through direct observation, patient records, or electronic health records. For example, it would be possible to measure how long patients can be released after physicians give discharge orders if time stamps are recorded in the electronic medical records (Hjollund et al., 2019). Similarly, information about pharmacy delivery times can be found in hospital documents. Outcome measures such as surgical site infection rates or patient mortality require data from clinical records and post-discharge follow-ups. Infection surveillance can identify infections, while mortality statistics arise from patient indicators found in health system databases. Accurate data collection must be achieved to measure the efficiency of healthcare’s quality improvement efforts.
How Success Would Be Determined
Healthcare Continuous Quality Improvement (CQI) facilities can only enjoy long-term sustainability and success through accurate and reliable performance measurement and benchmarking (Boyle, 2020). Benchmarking refers to the assessment of operational procedures in a facility relative to those of its counterparts. Different sources, including facility databases, government agencies such as CMS, or national databases examining the healthcare sector, can be used to derive patient safety and quality performance standards. For example, quality performance benchmarking within health organizations includes evaluating specific processes and outcome indicators such as surgical infection rates or patient length of stay. The main objective of CQI benchmarks is to aid healthcare organizations in realizing triple-aim goals: improving patient care, improving population health, and minimizing costs for healthcare systems.
Data-Driven, Cost-Effective Solutions
Managers find value in using outcome measurements to make cost-effective decisions. In other words, successfully integrating care that reduces LoS and SSIs among surgical patients will enable a smooth transition between hospitals, surgeries and inpatient care units. According to Bradshaw et al. (2021), these transitional points in patient care help ensure consistent and timely care delivery to the right patient while striving to minimize costs. Interoperability is essential for creating a seamless system from the healthcare database. This interoperability helps in information exchange among different areas, such as hospital departments, physician offices, and hospital-affiliated clinics (Boney et al., 2021). In addition, it enables patients who can access their medical history through electronic medical records to coordinate their care with the appropriate health providers effectively. Thus, information sharing throughout the healthcare system is essential to meeting established standards and improving patient outcome metrics.
Conclusion
It is essential to continuously improve quality (CQI) to improve healthcare quality. CQI helps healthcare teams implement procedures that provide high-quality care to patients. To avoid variations and waste in healthcare processes, they must identify the root causes of issues by developing solutions that enhance quality and cost-effectiveness. There are two basic strategies for ensuring the success of quality improvement initiatives, including performance measures and benchmarking. Streamlining patient care processes using process and outcome metrics can reduce variables and related costs. Following CQI criteria for assessment will result in more satisfied patients with their healthcare services.
References
Hill, J. E., Stephani, A. M., Sapple, P., & Clegg, A. J. (2020). The effectiveness of continuous quality improvement for developing professional practice and improving health care outcomes: a systematic review. Implementation Science, 15(1), 1–14. https://doi.org/10.1186/s13012-020-0975-2
Bradshaw, A., Santarelli, M., Khamis, A. M., Sartain, K., Johnson, M., Boland, J., … & Murtagh, F. E. (2021). Implementing person-centred outcome measures (PCOMs) into routine palliative care: A protocol for a mixed-methods process evaluation of The RESOLVE PCOM Implementation Strategy. BMJ open, 11(9), e051904.
Stone, K., Zwiggelaar, R., Jones, P., & Mac Parthaláin, N. (2022). A systematic review of the prediction of hospital length of stay: Towards a unified framework. PLOS Digital Health, 1(4), e0000017. https://doi.org/10.1371/journal.pdig.0000017
Hjollund, N. H. I., Valderas, J. M., Kyte, D., & Calvert, M. J. (2019). Health data processes: a framework for analyzing and discussing efficient use and reuse of health data focusing on patient-reported outcome measures. Journal of medical Internet research, 21(5), e12412. Doi: 10.2196/12412
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