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There are several reasons why it is important to measure the quality of healthcare in a healthcare organization.  These reasons include giving the strengths and weaknesses of the current system so that areas that need further improvement are identified. However, the chief reason for measurement of quality is to ensure that increased patient and physician satisfaction and ensuring that patients receive the best possible care. Three measures which include structure, process and outcome are mainly used (Rubin, Pronovost, & Diette, 2001). In this paper, advantages and disadvantages of process and outcome measures are addressed.

Outcome measures


One of the main advantages of outcome measure is that it can only be used to deduce the outcomes only if it assumed to have a link with process. Additionally, it gives a reflection of all aspects of the process and not only those that are measurable or measured (Mant, 2001). This suggests that determinants such as technical expertise and operator skills can as well be measured by using outcome measures but cannot be measured by use of process measures.

Process measures can direct clinicians to focus on ritualistic approach in giving healthcare to patients. This is contrary to outcome measures which require that physicians become innovative in delivering good health status for the patient. This means that in achieving positive healthcare outcomes, clinicians can employ technology and collaboration of different systems. In addition, since outcomes are usually taken for a long period of time, it helps the administration of a healthcare organization to come up with long term plans for the facility that ensures good outcome which can be in form of technology (Goddard, et.al 2002).

It is important to note that most of the measures of outcome are cheap since once implemented, they can only be reviewed and not re-implemented. This means that the clinicians cannot manipulate the results of outcome measurements in their favor. Besides, most outcome measurements such as mortality or quality of life are beyond the influence of the providers (Goddard, et .al 2002).


Unlike process measures, outcome measures are not direct determinants on the quality of health care. As this is the case, it means that sometimes, depending on the condition of the patient, false conclusions can be derived from the speculated or expected outcome thus leading to a difference in care of the patient if the case is otherwise. As a result, medical practitioners are at a loss in deciding which particular case should be subject to outcome measurement and which should not (Mant, 2001).

Outcome measures that are recorded for outcomes are usually not validated and therefore make it difficult to capture outcome features with relevance to the patient. Additionally, the interpretation of outcome depends on the study design. This suggests that a particular measure in one healthcare organization cannot be used to make improvement in another setup unless the same study design is applied. By doing this, time and costs increases (Barlow, Lamping, Davey, & Nathwani, 2003).

Process measures


Process has an influence on the outcome of the patient and therefore measuring the quality of a process makes it possible for physicians to determine what step they did or did not take that had an effect on the outcome of the patient. This means that the results of the process measurements are actionable. Meaning that it indicates what is done well and what needs improvement. Additionally, when the measurements are accurate, they make the clinician or the physician feel responsible for the outcome of the patient (Rubin, Pronovost, & Diette, 2001).

The process measurement data is usually collected electronically thus making data collection easier and reliable. Furthermore, process data does not need any risk adjustment as in the case of outcome measurements. It is worth noting that adjustments of the raw data reduce the accuracy and thus the validity of the results. Moreover, collection of data for adjustment requires a larger population than what is normally demanded by other process measurements.

As is suggested by the data collection methods, process is quicker because a smaller sample size is required whereas outcome would require that more time, including years, for the evaluation. This may mostly be seen in cases of the quality of life of the patient. Additionally, the small sample size is seen because most patients will be subjected to the same procedures unlike in outcome measurement where only a few patients will experience a certain outcome.


It is unfortunate that for the process measurement to be valid, it must have a strong relationship with outcome. This can be done by using the outcomes of previous records which can be non-existent or incorrect. Furthermore there is a propensity for coming to paradoxical conclusions. Patients who are sicker always receive better care and usually have worse outcomes. This can be paradoxically concluded that better care results to worse outcomes which in reality are not the case (Rubin, Pronovost, & Diette, 2001).

It should be understood that a healthcare organization may require doing some marketing. Unfortunately, they may not use information based on process measurement since it means very little to patients and non-clinicians. What this group of people are interested in is outcome and not process. Additionally, process measurement is specific for a certain element of care and not a comprehensive measure of how care is provided thus making the measure unsuitable for complex and sensitive healthcare programs (Rubin, Pronovost, & Diette, 2001).

Process measurements are dependent on technology which can become obsolete and thus require that sometimes after the devises are installed, an overhaul is done so that measurement is kept up to date. This increases the cost of the particular health organization. Besides, there is a propensity of clinicians or physicians tampering with the recordings so that they read in their favor. Furthermore, process measurements rely on self reporting which makes it vulnerable to misrepresentation as well as misinterpretation (Goddard, et.al 2002).


The two will always go together. None is superior to the other although there are differences depending on the aspect of healthcare being evaluated. However, the link between the two will always be there. It is important to note that the need for measuring the variables is not to determine whether the clinicians follow protocol but for the sole reason of improving the delivery of health care to the people. It should always be kept in mind that all processes in health care are patient minded.

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