Quality Data Collection

Data Collection and Improving the Mayo Clinic The Mayo Clinic is one of the best and most respected medical institutions in the world. However, even an organization at the forefront of the healthcare industry must remain always in a state of improvement. In order to do so, an organization must conduct meaningful and empirical research regarding its own capabilities and performance. This requires the use of the appropriate modes of data collection and implementation of instructive data presentation tools.

The discussion here below considers the need for the Mayo Clinic to help improve the scale of private investments that it helps draw to its home state and to improve the ability of other healthcare institutions to replicate its successful model. Areas of improvement: The Mayo Clinic has an inextricable relationship with its home state of Minnesota. As such, it has long been a creator of jobs in the region, a destination for national and international conferences and a highly sought after treatment facility for patients the world over.

For these reasons, the clinic is calling for the state of Minnesota to provide $600 million in subsidies for improving the Clinic and for helping it to advance its already considerable capabilities and resources. These subsidies would help Mayo to sustain the cost of the current improvement package in place. According to the article by Carlson, "Mayo pledged last year to spend $3.5 billion to improve its flagship health center in Rochester and a set of developments now known collectively as the Destination Medical Center project.

Last week, the system said it would also bring at least $2.1 billion in private investments from other sources to improve entertainment, lodging and tourism options in the city of 100,000 people." (Carlson, p. 1) This denotes a necessity to conduct informative research on the types of private investments that might be most compelling to the state. In order to make its case for subsidy from the state, the Mayo Clinic would be well-served to gather data on the best private investment opportunities to court for the state and its surrounding community.

This describes the first of two data collection challenges. As to the second, given that most public discussions on the Mayo Clinic focus on the excellence of its care quality and the consistency of its positive treatment outcomes, it is not surprising that one of the biggest complaints to be leveled against it is the seeming difficulty of replicating its successful model. This is why one big area of focus is on improving the quality of analytics and the ability to convey these analytics to other healthcare facilities.

According to the Mayo Clinic (2012), "as the director of the new Center for the Science of Health Care Delivery, Dr. Roger is helping to lead Mayo's efforts to fix the broken health care system. Researchers at the Center will use in-depth medical records studies, informatics, epidemiology health services research and systems engineering to design and validate the most efficient and effective medical practices. The results will be shared with other providers and could prove 'transformational' for U.S. health care, says Dr. Roger." (Mayo Clinic, p.

1) This objective speaks to the challenge at the center of this discussion, which is that relating to the gathering and presentation of data. For Mayo Clinic, this means finding ways to make sense of its own processes when contextualized by other health systems that might lack its resources and personnel. Data Needed: A number of data are needed in order to address the problems posed by the challenges delineated here above.

With respect to the first issue of justifying its request for subsidies from the state of Minnesota, it is incumbent upon the Mayo Clinic to gather data on the various areas where its presence justifies this subsidy. This means that data concerning the clinic's impact on the local and regional job markets is especially important. Gathering data on the job creation that could be created by further investment in the Mayo Clinic would be especially valuable in backing its request.

Additionally, there is a need to gather data to back its claims regarding the creation of private investment opportunities. This means that the Mayo Clinic should take steps to determine the kinds of investments in the region that would be most likely to appeal to lawmakers and citizens as well as the kinds that it is likely to be able to attract by way of its continued presence in Minnesota.

On the second subject of replicating its successful model in other healthcare facilities, the clinic must gather data on the various dimensions of its operations that help to produce its high quality treatment outcomes. This means combining a comprehensive investigation into the statistical performance of the Mayo Clinic with a gathering of data regarding patient experience. Under the premise that its emphasis on patient-centered strategies has helped to prefigure its success in the industry, much of this data should be accrued through direct consultation with the patient population.

Data Collection Tools: The data needed, as described here above, helps to determine the data-collection method which is best for the intended task. To this point, "a researcher will decide for one (or multiple) data collection techniques while considering its overall appropriateness to the research, along with other practical factors, such as: expected quality of the collected data, estimated costs, predicted nonresponse rates, expected level of measure errors, and length of the data collection period." (Traub, p. 1) These factors will enter into determining the most appropriate approach.

For instance, a survey might be an ideal way to enter into the discussion on replicating patient outcomes. An exit survey could be administered to patients asking for quantifiable responses regarding the quality of the patient experience. The survey, if scaled like a Likert instrument, can be used to gather quantitative data on patient experience. Its strength is its simplicity and its weakness is in its use of self-report, which is not always the most reliable data.

It is similar to the use of the interview in this way, which is also weakened by self-report. Its strength though is in its pragmatism. The interview allows the researcher to follow a natural line of questioning in pursuit of thick descriptive qualitative data. This might be useful as a way of gathering information from Mayo Clinic leaders and administrators on the informatics that are most useful for understanding hospital performance.

A final method due for consideration is the focus group, which offers its greatest strength in its discursive mode of data gathering. The flexibility.