Computed Radiography and Increased Productivity of the Images - Essay Example

As can be seen in figure 3, the total years of experience in their profession of respondents were 0-5 years (14%), 6-10 years (70%), and 10 above (16%).

This report will analyze the association between an increase in productivity and a decrease in cost, a decrease in lost images, an increase in the quality of images, a decrease in repeated examination/rejected films, and examination time.

Figure 1: Gender percentage

Figure 2: Highest qualification of respondents

Figure 3: Total years of experience of respondents

            Table 1 shows the questions that were asked of respondents. Likert 3-point scale was used for the survey.

1. Agree Unsure                     3. Disagree

Table 1

Variables and Their Descriptions

Variable

Description

Productivity

Do you agree that after the installation of Computed radiography, the productivity of images has increased?

Cost

Do you agree that the overall operating and maintenance expenses have decreased after the installation of the computed radiography system?

Lost Images

Do you agree that the computed radiography system reduces the number of lost images in comparison to filmed radiography?

Quality of Images

Do you agree that the Computed radiography system improves the quality of images in comparison to filmed radiography?

Repeated Examination

Do you agree that the computed radiography system reduces repeated examination /rejected films in comparison to filmed radiography?

Examination Time

Do you agree that the computed radiography system decreases examination time in comparison to filmed radiography?

Figure 4: Scatterplot of increase in productivity versus decrease in cost

Figure 5: Scatterplot of increase in productivity versus decrease in lost images

Figure 6: Scatterplot of increase in productivity versus increase in quality of images

Figure 7: Scatterplot of increase in productivity versus decrease in repeated examination

Figure 8: Scatterplot of increase in productivity versus decrease in examination time

As can be seen from Figures 4 to 7, it appears that there was a strong or very strong association between an increase in productivity and variables decrease in cost, decrease in lost images, increase in quality of images, decrease in repeated examination/rejected films, and examination time.

Table 2 shows the correlation matrix for an increase in productivity and other variables. The correlation results are given below.

An increase in productivity and a decrease in cost were very strongly correlated, r(48) = .89, p < .01.

An increase in productivity and a decrease in lost images were strongly correlated, r(48) = .76, p < .01.

Increase in productivity and a decrease in repeated examination/rejected films were strongly correlated, r(48) = .76, p < .01.

An increase in productivity and a decrease in examination time were very strongly correlated, r(48) = .90, p < .01.

An increase in productivity and an increase in the quality of images were very strongly correlated, r(48) = .84, p < .01.

Table 2

Correlations Matrix

Productivity

Cost

Lost Images

Repeated Examination

Examination Time

Quality of Images

Productivity

Pearson Correlation

1

.892(**)

.754(**)

.754(**)

.897(**)

.843(**)

Sig. (2-tailed)

.000

.000

.000

.000

.000

N

50

50

50

50

50

50

Cost

Pearson Correlation

.892(**)

1

.804(**)

.804(**)

.895(**)

.866(**)

Sig. (2-tailed)

.000

.000

.000

.000

.000

N

50

50

50

50

50

50

Lost Images

Pearson Correlation

.754(**)

.804(**)

1

1.000(**)

.885(**)

.538(**)

Sig. (2-tailed)

.000

.000

.000

.000

.000

N

50

50

50

50

50

50

Repeated Examination

Pearson Correlation

.754(**)

.804(**)

1.000(**)

1

.885(**)

.538(**)

Sig. (2-tailed)

.000

.000

.000

.000

.000

N

50

50

50

50

50

50

Examination Time

Pearson Correlation

.897(**)

.895(**)

.885(**)

.885(**)

1

.756(**)

Sig. (2-tailed)

.000

.000

.000

.000

.000

N

50

50

50

50

50

50

Quality of Images

Pearson Correlation

.843(**)

.866(**)

.538(**)

.538(**)

.756(**)

1

Sig. (2-tailed)

.000

.000

.000

.000

.000

N

50

50

50

50

50

50

**  Correlation is significant at the 0.01 level (2-tailed).

The strongest correlation was between the increase in productivity and a decrease in examination time, therefore, taking the variable decrease in examination time as the independent variable for predicting an increase in productivity (dependent variable).

A decrease in examination time significantly predicted an increase in productivity, β = .90, t(48) = 14.07, p < .01. Decrease in examination time also explained a significant proportion of variance in an increase in productivity, R2 = .81, F(1, 48) = 198.00, p < .01.

Table 3

Model Summary

Model

R

R Square

Adjusted R Square

Std. The error in the Estimate

1

.897(a)

.805

.801

.25898

a  Predictors: (Constant), Examination Time

Table 4

ANOVA(b)

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

13.280

1

13.280

198.000

.000(a)

3.220

48

.067

16.500

49

a  Predictors: (Constant), Examination Time

b  Dependent Variable: Productivity

Table 5

Coefficients(a)

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

Std. Error

Beta

.805

.057

.897

14.071

.010 above dent Variable: Productivity