Magnetic Resonance Imaging (MRI)

Introduction 

Magnetic resonance imaging (MRI) is a well-known health procedure globally. Since its discovery, researchers and doctors have continued to advance the process to aid in medical studies and techniques. Since its invention, it has revolutionized the medical industry. Researchers, scientists, and doctors can now asses body organs using these MRI tools. MRI can create reliable, accurate pictures for diagnosis and decrease the need for repeat examinations. Improved precision saves both time and control costs, and thus reducing the number of procedures. MRI can produce accurate, reliable images for diagnosis and reduce the need for repeat exams. Such precision saves you time and control costs. Most of the studies conducted in this subject used quantitative methods, whereas a few employed qualitative techniques depending on their approach. 

In a study conducted by Barone & Lucero (2015) on how accurate CT and MRI can be used for modeling the cancer prevalence, quantitative methods were useful. The study established that MRI is more accurate in predicting the PCI preoperatively in people who are being evaluated for surgery. Medical imaging has become a daily activity in diagnosing and performing several medical problems. MRI is useful in the visualization of internal organs and tissues, with above sixty million procedures being conducted yearly. Almost two-thirds of the procedures are based on contrasted gadolinium, and MRI enhanced contrast (Wei et al. 2017). Most of the private clinic use MRI contrast as their main procedure. The study purposed to determine whether the number of MRI procedures in a hospital differ from those of a Clinic. 

Research Question 

Does the number of MRI procedures in Hospitals and Clinics differ? 

Research Method 

The study employed a quantitative methodology to achieve its aims and objectives. The methods are summarized in each of the following sub-sections. 

Description of dataset 

The dataset used in the study was titled MNHCC imaging procedure. The dataset contains 12 variables, out of which six were numerical variables, whereas the remaining were qualitative. The variables included; HCCIS ID, facility type, name, city, state, MRI procedures, SPECT procedures, CT procedures, PET procedures, PET/CT procedures, and SPECT/CT procedures. 

The primary source of data 

The study employed used secondary data obtained from the National government database. The data was collected across all medical institutions on how they carry out imaging procedures. Each hospital was assigned an HCCIS ID. The information was extracted from the entire MN dataset. 

Sample size 

The dataset was recorded in all 778 medical facilities. The medical facilities included hospitals, clinics, imaging facilities, and mobile unit locations. Thus, the study used a sample of 778 medical institutions. 

Description of variables 

Variable	Definition	Description of code	Source	Year
HCCIS ID	Medical institution identification number	Numeric	MN Data	2013
Facility type	The type of medical facility	Categorical	MN Data	2013
Name	The name of the medical facility	Categorical	MN Data	2013
City	The city of operation of the medical facility	Categorical	MN  Data	2013
State	The state of operation of the medical facility	Categorical	MN Data	2013
MRI Procedure	The number of MRI procedures	Numeric	MN  Data	2013
PET Procedure	The number of PET procedures	Numeric	MN  Data	2013
CT Procedure	The number of CT procedures	Numeric	MN  Data	2013
SPECT/CT Procedure	The number of CT and SPECT procedures	Numeric	MN  Data	2013
PET/CT Procedure	The number of CT and PET procedures	Numeric	MN Data	2013
SPECT Procedure	The number of SPECT procedures	Numeric	MN data	2013

Research method for analysis 

Since the purpose of the study was to compare several MRI procedures in hospitals and clinics, the study used both descriptive and inferential statistics. The descriptive statistics encompass mean, standard deviation, median, and variance were computed for numerical variables (Zare, 2017). Besides, the study used a two-sample T-test procedure to test the difference in the number of MRI procedures between hospitals and clinics. The test was the most suitable method since the aim of the study was to compare only two independent groups ( Lampard & Pole, 2015). 

The paper used quantitative methods to achieve their objective. Quantitative methods are techniques that use the quantifiable nature of the data to perform statistical analysis of a specific phenomenon (Palinkas et al. 2015). Quantitative research collects information regarding the subject using quantitative methods. The output of the study is presented in numerical form. The quantitative techniques usually are used for scientific studies and social science with the help of statistical purposes. Analyzing quantitative data involves several steps, including; data processing, validation, manipulation, and analysis (McCusker & Gunaydin, 2015). The well-known quantitative methods are descriptive and inferential statistics. The paper used both descriptive and inferential statistics to achieve its objectives. 

Statistical package 

The paper used Excel for analysis of the data. Data analysis tool back in excel was used to generate both descriptive statistics and the T-test procedure. Excel was used because of its more straightforward method and accessibility. 

Results 

First, we inspected the data for missing and outlying cases. We established that the data had many missing values. Thus, we remove them from the dataset. Besides, we also checked the outlying cases, which we removed from the dataset. Moreover, the normality test of the MRI procedures variable was tested by the fitting histogram. The histogram below shows that the variable met the normality test, and thus, the T-test was a suitable procedure. 

Most of the variables in the dataset had missing values. However, the MRI procedure variable had a few missing values indicated by 12 percent. 

Statistic	MRI Procedures	PET procedures	PET/CT Procedures	CT Procedures	SPECT/CT Procedures	SPECT Procedures
Mean	1775.604167	348.25	657.7551	5747.005618	2049.666667	713.8409091
Median	1763	246.5	190	2044.5	526.5	203
Standard Deviation	879.2293468	329.8771236	1666.191	9417.125835	4695.637537	1222.297873
Kurtosis	-1.0621149	0.2790234	37.5531	9.997001555	10.82388235	9.151454992
Skewness	-0.062591579	1.161896367	5.831894	2.96550964	3.250837088	2.7601543
Range	3363	700	11391	61607	16650	7174

Table 1 : Summary statistics table 

Table 2 above showed that the average number of MRI procedures in the selected medical facilities was 1775.60, with a standard deviation of 879.2229. It was also evident that the coefficient of skewness was -0.06259, which is an indication of nearly normal property. Similarly, the summary of the statistics of the other variables was represented, as shown above. 

t-Test: Two-Sample Assuming Unequal Variances
	Clinic	Hospital
Mean	1775.604167	2834.78
Variance	879.2293468	1264.337
Observations	48	100
Hypothesized Mean Difference	0
df	55
t Stat	3.147166402
P(T<=t) one-tail	0.028139367
t Critical one-tail	1.673033965
P(T<=t) two-tail	0.256278735
t Critical two-tail	2.004044783

Table 2 : T-test Statistic 

It was evident in the table above that the T-test statistic was higher than the critical value. Also, the probability value associated with the T-test statistic is less than 0.05 level of significance, and thus we rejected the null hypothesis. 

Discussion and conclusion 

The study purposed to determine whether several MRI procedures in a hospital differ from those of a Clinic. The descriptive statistics revealed that the average number of MRI procedures in US medical facilities is 1775. Since the probability value of the t statistic was established to be less than 0.05, we rejected the null hypothesis. Thus, we conclude that the number of MRI procedures in the hospital is different from that of clinics. The results of the t-test technique performed showed there is a difference between the number of MRI procedures in hospitals and clinics. The results were also supported by the output of the descriptive statistics, which show a massive deviation between the average number of MRI procedures in the hospitals with that of a clinic. The results implied that in all the states, the number of MRI procedures in hospitals differs significantly with that of clinics. It also indicates the dissimilarity of the way the MRI procedures are conducted, which could be a result of the cost associated with MRI procedures. 

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References  

Lampard, R., & Pole, C. (2015). Practical social investigation: Qualitative and quantitative methods in social research . Routledge. 

Low, R. N., Barone, R. M., & Lucero, J. (2015). Comparison of MRI and CT for predicting the Peritoneal Cancer Index (PCI) preoperatively in patients being considered for cytoreductive surgical procedures. Annals of surgical oncology , 22 (5), 1708-1715. 

McCusker, K., & Gunaydin, S. (2015). Research using qualitative, quantitative, or mixed methods and choice based on the research. Perfusion , 30 (7), 537-542. 

Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and policy in mental health and mental health services research , 42 (5), 533-544. 

Wei, H., Bruns, O. T., Kaul, M. G., Hansen, E. C., Barch, M., Wiśniowska, A., ... & Cordero, J. M. (2017). Exceedingly small iron oxide nanoparticles as positive MRI contrast agents. Proceedings of the National Academy of Sciences , 114 (9), 2325-2330 

Zare, H. (2017). HMGT 400 Research and Data Analysis in Health Care-Exercise. UMUC.EDU