Data Quality Measures are tools used to measure and track the quality of healthcare services provided by eligible professionals, eligible hospitals, and critical access hospitals within the healthcare system. In recent times, healthcare reporting has been shifting more and more to the use of electronic clinical quality measures mostly referred to as e-measures. These measures use data that shows health care provider’s ability to meet long-term quality goals. William Edwards Deming (October 14, 1900 – December 20, 1993) was an American engineer, statistician, professor, lecturer, and management consultant. His renowned book The New Economics of Industry, Government, and Education is critically acclaimed and its principles have been used widely across industries. He developed the sampling technique and had a great impact on the practice and science of quality management. His principles have what has been translated and adapted into the healthcare industries quality improvement strategies.

One of the defining principles of healthcare improvement is that Managed Care means managing the process and not the health practitioners. This principle emphasizes that managed care should focus on managing the process and not be managing the health practitioners such as the doctors, nurses, or clinicians. Understanding this principle is very crucial for quality improvement to be effective. In the past, managed care has been misunderstood as managing and sometimes micro-managing the people instead of the process. This could lead to drastic negative effects. Health practitioners should be included in the process of quality improvement as they understand the system better and are usually the direct recipients of complaints (for feedback purposes) and uses the system every day. They understand it best and should be included in the decision-making process. If the quality improvement approach attempts to manage health practitioners it could lead to a drop in working morale and even worse a worsening of the process and subsequently, quality of healthcare.

A proper management of the process leads health organizations to avoid a common problem of quality measures which is shaky data integrity. Data Integrity

One of the causes of e-measure inaccuracies is the integrity of the data. This accuracy is often caused by documentation, workflow variation or human error. Take, for example, a scenario in which the hospital EHR is set up to automatically capture a patient’s arrival time as they are being registered with the emergency department. This may seem like an efficient way to collect patient information from the registration workflow but what if the patient is triaged first and then registered? In this case, a change in the workflow produces an inaccurate ED arrival time, which affects the accuracy of any e-measures using this data. This goes exactly as it sounds. Health organizations need the right data at the right time and in the right hand. It’s a trifecta that must always go together for efficient quality improvement. For example, if you have the right data but at the wrong time, it might be useless. And if the right data is available at the right time but to the wrong person (or department) that data becomes either useless or misused. Having data flow efficiently through the organization is very important for quality improvement to take place.

There are some principles that apply in every situation without the need for a variation such as respect for people. In the healthcare industry respecting health, practitioners are essential as their work involves a lot of patient interaction and most importantly life and death situations. If employees are happy it affects the quality of service. In healthcare, a drop in quality of service could lead to life-threatening situations. The usefulness of electronic clinical quality measures outweighs the negatives. Its advantages will accelerate as EHR technologies and standards continue to mature. A robust data governance program will help healthcare practitioners and health organizations prepare for – and take advantage of – this transition in quality reporting.

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