Academic Master

Human Resource And Management

Identifying Measurement Roadblocks


Quality measurement is crucial for ensuring high leveled performance in healthcare organizations. However, inevitable roadblocks impede the measurement process. There are five roadblocks, among which the most significant are threatening and desire for precision. All these roadblocks have grave impacts, including diminished learning, low-esteemed service passion, job insecurity on the part of the staff, and low-performance level. Various measures can reduce these impacts on performance and enhance the quality of measurement in hospitals by adopting strategic planning.

Identifying Measurement Roadblocks

The health care system in the modern world is diversified with ample aspects and dimensions. All stakeholders agree that we need a comprehensive system of practices to ensure and measure the quality of the modern health care system (Makeham et al., 2019). Measuring the goodness in this regard requires all the relevant data of a health care unit and its independent assessment. The qualitative approach in this context has been adorned with safety, trust, effectiveness, and efficiency. However, some vast distractions and disruptions vigorously impede the measurement process and are entitled as measurement roadblocks.

Measurement Roadblock Connotation:

Roadblocks are those hurdles, barricades, and barriers that limit the speed of progress, efficiency, and development in a specified system sphere. In health care measurement, it relates to all those objects and processes that impede and limit the assessment of efficiency of all stakeholders (Peimbert et al., 2019). These may range from technical to non-technical, intentional to systematic, relating to legalities, societal values, and norms, etc.

Different Measurement Roadblocks

There may be a long list of measurement roadblocks regarding the health care system. However, the most appropriate measuring roadblocks are enlisted as:

  1. Measurement is threatening
  2. The desire for Precision
  3. Using standards as Performance Objectives
  4. Limited knowledge of Statistical Process Control
  5. Numerical Illiteracy

Measurement is threatening

The most significant roadblock in healthcare measurement is referred to as threatening. It is an awful reality that data has been used to beat and punish the personals. Employees of any health organization become afraid of managers’ expectations regarding patient satisfaction. There can be more than one reason for the inefficient performance of an organization as a whole, but the most affected entity is employees. If it is right on the part of management, that efficiency number must be higher after firing out of concerned staff. But it seldom happens so. Undoubtedly, staff judge measure their performance due to threats of job snatching. Still, at the same time, their performance revolves around job security but not welfare, satisfaction, and trust-building among staffing, patients, and their families.

The ultimate impact in this regard is a blunt cut on the real efficient professionalism required for health care employees. It is a fact that when the respective data is being utilized for punishment and threatening purposes by high authorities, the learning and improvement purposes are buried. Meanwhile, the staffing definitely infers from the situation that it is useless to be part of that measurement system planted against them. So, the passion for service for good causes replaces job security because of threatening. It is so because most organizations use data to pour threat and fear among employees in the name of quality measurement.

The desire for Precision

Another very significant measurement roadblock is the desire of higher authorities and managerial executives for precision. They almost require and anxiously demand such precision in evaluating the potential of patients for any specific treatment and cure. In this regard, no attention is paid to the adopted processes and procedures by the health care staff. However, it is a fact that US Federal Government authorities categorized healthcare jobs as service jobs instead of scientific careers. For more clarity, these jobs are classified in car repair, beauty shops, and saloons in the country. Undoubtedly, scientific advancement and modern technology are necessary for health organizations, like other multiple organizations. But one thing must be clear that health care personals are not researching to achieve Nobel Prize in Physiology. But they try to understand multiple processes and variations that may occur from case to case. They all try to understand and accomplish tasks to make things efficient.

So the requirement for technological precision cannot be achieved like research readings in an experiment. Such desire by the higher authorities in health care organizations impedes the quality measurements. Further, the ultimate goal of quality measurement is not to achieve the symbolic data but to guide and support the respective organization. Contrary to such purpose, the desire for precision becomes a roadblock in the way of measurement, and overall impact arises with suspension and low quality. In addition, such desire leads an organization towards scientific and academic precision. In this context, the passion for precision resists quality measurement, and it looks like the quality measurement journey is yet to start in the near future. And something else is going on in health organizations in the name of measurement of quality. Resultantly, such a prevailed desire for precision forces the employees to think whether they make some difference in the organization or not? The service of humanity vanishes, and in such cases and figurative data remains to judge the efficiency of staffing in the name of quality measurement.

Using standards as Performance Objectives

Standards are treated as minimal levels of performance as they cease performance. So, meeting these levels reduces service passion. Meanwhile, quality insurance and measurement cannot be granted based on standards.

Limited knowledge of Statistical Process Control

Al Tehewy (2021) stated that various roadblocks that retard quality measurement relate to specific skills about multiple tools. Such roadblock is limited or defective knowledge of statistical Process Control (SPC). In this regard, staff should be trained.

Numerical Illiteracy

Numerical illiteracy is also a roadblock in quality measurement in modern healthcare units. Though such a roadblock is of minute significance compared to others, basic flaws can lead to drastic results.

Impact of these Roadblocks on Measuring Performance

Schwann et al. (2019) reported, “Between health care we have and the care we could have is not just a gap but a chasm.” It is a horrifying fact that all the roadblocks mentioned above have severe impacts on measuring performance. Undoubtedly, measurement is crucial for efficiency. The effects in this regard range from diminished learning, threats of job, misuse of data, abuse of rules and regulations, threats of unnecessary accountability, and low profiled quality. Passion for service leads to meeting standards only.

One of these Roadblocks more Impactful than another

Measurement of threatening is more impactful than other roadblocks. As it directly threatens the job of health care staffing and also fear of snatching incentives. So threatening is a more robust and impactful roadblock in this context.

Measures to Overcome these Roadblocks

Overcoming these roadblocks as a whole or on individual capacity is quite challenging. However, strategic planning and execution not only can overcome them but also create wonders in this regard. Staff should be secured with respect to the job and must be trained regarding various tools like SPC. Data and rules must not be misused, and desire for precision should be replaced with service encouragement.


Al Tehewy, Mahi. “A Roadmap for Measuring Quality in Health Care.” Egyptian Journal of Nursing and Health Sciences 2.1 (2021): 7-12.

Makeham, Meredith AB, and Angela Ryan. “Sharing information safely and securely: the foundation of a modern health care system.” The Medical Journal of Australia 210.6 (2019): S3-S4.

Peimbert-García, Rodrigo E. “Analysis and evaluation of reviews on Lean and Six Sigma in health care.” Quality Management in Healthcare 28.4 (2019): 229-236.

Schwann, Nanette M., et al. “Clinical practice improvement: Mind the gap or fall into the chasm.” Journal of cardiothoracic and vascular anesthesia 33.11 (2019): 2900-2901.



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