Methodology -Survey based instrument was used to gather the responses from the nurses working in leading hospitals having more 300 beds in Tiruchirappalli district. 70 respondents participated in this survey.
Findings – Chi-square test revealed that demographic characteristics of nurses and usage of information technology are independent The results of factor analysis demonstrated that softwares, data bases, file tranfer and input devices are significant in explaining confidence level among nurses and factors like computer access, perception about information technology, connectivity, and shortage of computers are significant in creating barriers in usage of information technolgy. The extent to which nurses access and use information technology and the purposes for which nurses use information technolgy are also highlighted.
Limitations- This study is limited to only hospitals and the results. The results may not be applicable to other business organizations.
Keywords
Information Technology, Nursing, Hospital
INTRODUCTION
The impact of information technology on nursing has been a subject of discourse and dissertation for the latter half of the 20 (th) centuries and the early part of the 21(st). That this burgeoning technology has impacted the way nurses nurse can be without doubt. Whether this technology has and will have a negative or positive outcome on nursing practice is where the debate centres. This study was undertaken with an objective of analysing the debate that surrounds the issues of the impact of Information Technology (IT) on nursing practice. The study is also intended mainly to findout the extent and use of information technology on nursing practices.

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REVIEW OF LITERATURE
Toofany, Swaleh (2006) examined the attitude of nurses to the use of information technology (IT) in health care in Great Britain. A system is being developed by the Department of Health that will allow nurses to retrieve the health records of patients from core computer storage. A nurse does not consider themselves as having central roles in IT management. Many commentators believe that technophobia among nurses continues despite the increasing need for them to employ IT in health care
Porter-O’Grady, Tim (1999) had undertaken a study on “Technology Demands Quick-change Nursing Roles”. The study mainly focused on how nursing managers must face the emerging technological changes in health care and what is the impact of technology on nursing care and role of the manager in relation to the changes.
Simpson, Roy L (2006) in their study, focused on the significance of information technology (IT) to nursing. It is said that a new way of practicing evidence-based nursing will rely on IT. The mindset about the importance of IT is said to be the most challenging hindrance to IT ubiquity. The elements that are necessary to IT ubiquity in nursing are products, learning, access and need.
Rollins, Gina (2007) reported on the growing number of nurses in the U.S. who are leaving hospitals to enter the clinical informatics field as electronic health records proliferate. A recent survey by the Healthcare Information and Management Systems Society found the top three job responsibilities for nurse informatics include systems implementation, systems development and liaison or communicator.
Simpson, Roy L.(2002) in their study on “The virtual reality revolution: technology changes nursing education” discussed the benefits of virtual technology for the improvement of nursing education. The author also focussed on background on limited opportunities for nursing students to practice their skills; Advantages of using virtual reality technologies in improving the clinical skills of nursing students are also highlighted. Information on several nursing simulation tools were also presented in this study.
Simpson, Roy L (2007) presents an analysis of how increasing the number of informatics-trained nurses can help in the continual growth of demand for nurses in the U.S. A paradigm of the supply-side economics was provided to compare the positive effect of stimulating supply than demand. The healthcare industry has reached the world of information technology (IT) so that nurses should then learn the language that it speaks, which is informatics. The author contends that the amount of effort, time and money can be saved if informatics-trained nurses are indeed pursued as a focus of development in the industry.
Wallis, Alison (2007) in his study on “Clinical data standards and nursing” describes the benefits of information and communications technology programmes, often referred to as electronic health (e-health), to nurses in Great Britain. Among its contributions to patient care include its ability to offer ways of sharing patient information and the access it provides clinical data for benchmarking and audit. The benefits of data standards accrue to nurses at all levels, whether they work in direct patient care, in unit management or at health board level.
Brommeyer, Mark (2005) explains the concept of e-health healthcare technology. The authoer also highlighted the advantages of adopting e-health; Information and communication technologies being used in most hospitals are also studied and Implications of using the technology are clearly furnished in his study.
Hudson, Kathleen (2007), in his study “Innovations in cardiac nursing and technology” deals with several areas in which emerging technologies in cardiac nursing are most promising. The three options that exist for heart failure patients include destination therapy, bridge to transplant and bridge to recovery. A cost-effective risk predictor is the Electrocardiogram T-wave analysis using microvolt T-wave alternans. Cardiac performance can be reliably assessed by non-invasive ambulatory impedance cardiography.
RESEARCH METHODOLOGY
The present study is undertaken to find out the following.
To identify the extent to which nurse have access to and use information technology and information management systems.
To identify the purposes for which nurses use information techonolgy and information mangement systems.
To find the association between the demographic profile and the work related activities with using computer
To identify the variables and their grouping into factors that influence level of confidence in the use of the following systems like input devices, software packages, data storages, and file transfer.
To understand the barriers that prevents nurses from benefitng from information technology and information management system.
3.1 The Sampling Design
A private hospital was chosen for conducting this study. The study has taken into account the various aspects of information technology and its impact on nursing practices. A sample of 70 nurses has been chosen from the populaton of 147 nurse’s working in same hospital using simple random sampling method. The tabulated description of demographic details of sample is presented in Table 1.
Table 1. Frequency Distribution of sample demographics
S.no
Variables
Number
Frequency (%)
1
Gender
Female
70
100
2
Age
Below 30
55
79
30-40
15
21
3
Designation
Staff Nurse
42
60
ANM
25
36
Surgical technician
2
3
Anesthesia technician
1
1
4
Shift timing
Continuous shift worker
54
77
Day shift worker
7
10
Evening shift worker
4
6
Night shift worker
1
1
Morning and Evening shift worker
3
4
Evening and night shift worker
1
1
5
Qualifications
Diploma
46
66
UG
12
17
PG
2
3
Other
10
14
6
Department
General ward
43
61
Annexe ward
7
10
Operation Theatre
7
10
Dialysis Unit
4
6
ICU
9
13
3.2 Data Collection
The data was collected from the nurses of the selected hospital through a questionaire which has 11 parts, namely;
Demographic characteristics and background of IT
Access and Use of computers
Use of Information Technology
Access to Internet and Intranet
Knowledge of current Health I.T initiatives
Job requirement for I.T
Training and Education about Information technology
Barriers to use of computers
Technical support
Management attitudes and support
Security
3.3 Measurement Scale
The questionaire consisted of a series of statements, where the nurses were requested to provide answers in the form of agreement or disagreement and good or poor and rarely or frequently and confident or not confident to express their perceptions towards information technology. A Likert scale was used.
DATA ANALYSIS
4.1 Chi – Square Analysis
4.1.1 Chi- Square Test of Significance (Age and Work related activities at Home computer)
H0: There is no significant relation between age and Work related activities at Home computer.
H1: There is significant relation between age and Work related activities at Home computer.
4.1.2 Chi- Square Test of Significance (Designation and Work related activities at Home computer)
H0: There is no significant relation between designation and Work related activities at Home computer.
H1: There is significant relation between designation and Work related activities at Home computer.
4.1.3 Chi- Square Test of Significance (Shift timings and Work related activities at Home computer)
H0: There is no significant relation between shift timings and Work related activities at Home computer.
H1: There is significant relation between shift timings and Work related activities at Home computer.
4.1.4 Chi- Square Test of Significance (Qualifications and Work related activities at Home computer)
H0: There is no significant relation between qualifications and Work related activities at Home computer.
H1: There is significant relation between qualifications and Work related activities at Home computer.
4.1.5 Chi- Square Test of Significance (Department and Work related activities at Home computer)
H0: There is no significant relation between department and Work related activities at Home computer.
H1: There is significant relation between department and Work related activities at Home computer.
The values of chi-square statistics obtained from chi-squre distribution table for all 5 combinations are 14.07, 32.67, 49.80, 32.67 and 41.337 in that order and the calculated chi-square statistics values are 12.853, 25.408, 36.97, 26.34 and 34.14 in that order which lies in the acceptance region. Thus, the null hypothesis can not be rejected .So, it can be concluded that demomograhpic characteristcs of nurses are independent with regard to work related activities at home computer on the basis of statistical evidence at 5 % level of significance. Results of chi-square are presented in Table 3.
Table 3: Results of Chi-squre Analysis
S.no
Variables
Chi-square statistic
1
Age and Work related activities at Home computer.
12.853 2
Designation and Work related activities at Home computer.
25.408 3
Shift timings and Work related activities at Home computer.
36.97 4
Qualifications and Work related activities at Home computer.
26.34 5
Department and Work related activities at Home computer.
34.14 4.2 Factor Analysis
4.2.1 Key dimension: Level of confidence in using computers
Data validity for factor analysis was calculated using KMO Measure of sampling adequacy. The minimum acceptable level is 0.5. Since calculated Kaiser-Meyer-Olkin (0.859 ) is greater than 0.5, so it is appropriate to do factor analysis. Hence Bartlett’s test of sphericity value is 1144.756, it is also a kind of chi-square and it is significant. The results of Kaiser-Meyer-Olkin and Bartlett’s test of sphericity are shown in table 5.
Table 5: KMO and Bartlett’s Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
.859
Bartlett’sTestof Sphericity
Approx. Chi-Square
1144.756
Df
153.000
Sig.
.000
Table 6: Total Variance Explained
Component
Initial Eigen values
Extraction Sums of Squared Loadings
Total
% of Variance
Cumulative %
Total
% of Variance
Cumulative %
1
9.288
51.599
51.599
9.288
51.599
51.599
2
1.926
10.698
62.298
1.926
10.698
62.298
3
1.468
8.154
70.452
1.468
8.154
70.452
4
1.254
6.965
77.416
1.254
6.965
77.416
5
.869
4.830
82.246
6
.728
4.044
86.290
7
.476
2.642
88.933
8
.353
1.960
90.893
9
.334
1.853
92.746
10
.264
1.465
94.211
11
.237
1.319
95.530
12
.225
1.250
96.780
13
.148
.820
97.600
14
.140
.778
98.379
15
.107
.596
98.975
16
.087
.481
99.455
17
.055
.308
99.763
18
.043
.237
100.000
The Principal Component Analysis was used for extraction method. The Table 6 reveals that 4 factors have been extracted out of 18 variables that exceed the Eigen value of one. The variables less than the Eigen value of one are not considered during extraction method.
Table 7: Rotation Sums of Squared Loadings
Total
% of Variance
Cumulative %
6.626
36.812
36.812
2.707
15.038
51.850
2.660
14.777
66.627
1.942
10.790
77.416
The Table 7 shows that Factor 1, factor 2, factor 3 and factor 4 explain a variation of 36.812%, 15.038%, 14.777%, 10.790% respectively and together show the variance of 77.416%.
Table 8: Rotated Component Matrix
Component
1
2
3
4
Apple Mac OS
.888
.125
.204
.106
SPSS
.853
.212
.245
-.014
Reference tools
.836
.199
.291
-.072
Spreadsheet
.811
.219
.152
.065
Evidence based practice resources
.810
.116
.399
-.020
Data projector
.773
.226
.271
-.056
USB
.766
.113
.446
.030
Presentation
.684
.376
-.042
.272
Touchscreeen
.645
.282
.131
.212
Wi ndows OS
.590
.232
.150
.355
Email
.294
.868
.223
-.018
Intranet
.149
.842
.267
.030
Internet
.497
.741
.052
-.112
Data base
.195
.260
.882
.085
Cd/DVD ROM
.399
.338
.754
.079
Word processing
.352
.039
.700
.157
Keyboard
.048
.045
.067
.920
Mouse
.066
-.108
.118
.880
Table 9: Naming of Factors
Factor 1
Software Packages
Factor 2
File Transfer
Factor 3
Data Storage
Factor 4
Input devices
Apple Mac OS
Email
Data base
Keyboard
SPSS
Intranet
CD/DVD ROM
Mouse
Reference tools
Internet
Word processing
Spreadsheet
Evidence based practice resources
Data projector
USB
Presentation
Touchscreeen
Windows OS
It is infered that factor 1 consists of ten variables of which Apple Mac OS , SPSS and Reference tools are found to be significant with a variation of 36.812%. Factor 2 consists of three variables of which email and intrant are significant with a variation of 15.038%. Factor 3 consists of three a variable of which database is significant with a variation of 14.777%. Factor 4 consists of two variables of which key board is significant with a variation of 10.790 %. Based on the results of factor loading (table 8), the factors are named which is given in table 9.
4.2.2 Key Dimension: Barriers to access of computers
Data validity for factor analysis was calculated using KMO Measure of sampling adequacy. The minimum acceptable level is 0.5. Since calculated Kaiser-Meyer-Olkin (0.685) is greater than 0.5, so it is appropriate to do factor analysis. Hence Bartlett’s test of sphericity value is 592.529, it is also a kind of chi-square and it is significant. The results of Kaiser-Meyer-Olkin and Bartlett’s test of sphericity are shown in table 10.
Table 10: KMO and Bartlett’s Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
.685
Bartlett’s Test of Sphericity
Approx. Chi-Square
592.529
Df
153.000
Sig.
.000
Table 11: Total Variance Explained
Component
Initial Eigenvalues
Extraction Sums of Squared Loadings
Total
% of Variance
Cumulative %
Total
% of Variance
Cumulative %
1
6.105
33.916
33.916
6.105
33.916
33.916
2
1.759
9.774
43.689
1.759
9.774
43.689
3
1.581
8.785
52.475
1.581
8.785
52.475
4
1.517
8.430
60.905
1.517
8.430
60.905
5
1.150
6.390
67.294
1.150
6.390
67.294
6
.982
5.455
72.750
7
.828
4.599
77.348
8
.736
4.092
81.440
9
.642
3.568
85.008
10
.528
2.931
87.939
11
.458
2.544
90.482
12
.403
2.241
92.723
13
.327
1.815
94.538
14
.284
1.579
96.117
15
.246
1.365
97.482
16
.208
1.157
98.640
17
.158
.876
99.516
18
.087
.484
100.000
Table 11 reveals that 5 factors have been extracted out of 18 variables that exceed the Eigen value of one.The variables less than the Eigen value of one are not considered during extraction method.
Table 12: Rotation Sums of Squared Loadings
Total
% of Variance
Cumulative %
3.715
20.641
20.641
3.282
18.235
38.876
2.084
11.578
50.454
1.822
10.121
60.575
1.210
6.720
67.294
The table 12 shows that factor 1, factor 2, factor 3 and factor 4 explain a variation of 20.641%, 18.235%, 11.578%, 10.121% and 6.720% respectively and together show the variance of 67.274%.
Table 13: Rotated Component Matrix
Component
1
2
3
4
5
Too many work demands
.727
.023
.177
.150
.310
Confidence in use
.726
.305
-.077
.074
-.285
IT knowledge
.712
.086
-.087
.053
.063
Response time of computer
.678
.191
.359
-.014
.141
Working in computer does not fit my work demand
.675
.091
.491
.082
.137
Lack of IT support
.622
.471
.019
.086
-.053
Attitudes of IT Department
.368
.802
.051
.118
-.106
Discouragement by others
.059
.758
.065
.102
.054
Patient and others are resentful of me at the computer
-.074
.692
-.131
.030
.361
Concerns about health and safety
.274
.678
.232
.016
-.088
Lack of encouragement by mgmt
.380
.537
.267
.080
.267
Age
-.057
-.049
.852
.040
.088
Senior staff take priority
.322
.511
.600
.068
-.054
Not having Interest in using computer
.466
.248
.530
.029
-.020
Location of computer I use
.242
-.096
-.195
.813
.235
Unreliable connections
-.136
.268
.316
.787
.091
Log on is too long
.230
.212
.082
.670
-.465
Not enough computers
.182
.139
.097
.092
.687
Factor 1
Computer Access
Factor 2
Perception
Factor 3
Usage of Computer
Factor 4
Connectivity
Factor 5
Not having enough computers
Too many work demands
Attitudes of IT Department
Age
Location of computer I use
Not enough computers
Confidence in use
Discouragement by others
Senior staff take priority
Unreliable connections
IT knowledge
Patient and others are resentful of me at the computer
Not having Interest in using computer
Log on is too long
Response time of computer
Concerns about health and safety
Working in computer does not fit my work demand
Lack of encouragement by mgmt
Lack of IT support
Table 14: Naming of Factors
It is also infered that Factor 1 consists of six variables of which variables like too much demand of work and confidence in used are found to be significant with a variation of 20.641%. Factor 2 consists of five variables of which variable namely Attitudes of IT deparment is significant with a variation of 18.235 %. Factor 3 consists of three variables of which variable namely age is significant with a variation of 11.578%. Factor 4 consists of three variables of which location of computers is significant with a variation of 10.121%. Factor 5 consists of one variable of which not enough computers is significant with a variation of 6.720 %. Based on the results of factor loading (Table 13), the factors are named which is given in table 14.
CONCLUSIONS
The conclusions derived in empirical analysis are summaried below.
Most of the nurses are aware of Information Technology Practices prevailing in their workplace.
There is a common consensus that Information Technology reduces the errors in handling the Patient/client data.
Nurses use information technology for the purposes like professonal development, clinical care, patient care, administration, research and communication.
Regarding the extent of access, majority of nurses disagree that they avoid using computers at their work. They have also realized the importance of using computers in their work.
It is also found that use of information technology enables nurses in reducing errors in patient data and also helps in reducing duplication.
There is also common agreemnt on the fact that Information technolgy made their job easier.
Since the nurses are able to realize the importance of Information technolgy for their employer, they prefer that training on Information technology has to be provided to them by face-to-face.
Many nurses didn’t have their personal email id at their workplace and they are not financialy rewarded for the usage of Information technology.
There is a lack of confidence in using of systems like Patient/client monitoring ,Diagnostic result access ,Financial management,Staff Management,Delivery and On-line professional journals etc.,
The demographic characteristics of nurses have a significant impact on the work related activities at their home.
Factors like software packages, file transfer, data storage and input devices are significant in explaining the confidence level of nurses regarding the usage of computers.
Factors like computer access, perception about Information technology, usage of computers, connectively, shortages of computers are significant in explaining the barriers to access of computers.
Based on the findings, few suggestions have been made by researcher which is summarized below:
This study should be made every year to evaluate the new practices that can bring in changes in the hospital.
The hospital administrators should provide rewarding system for Using of IT in work.
The hospitals should also try to remove the barriers for improving the computer access among nurses.
The nurses may also be permitted to access the Internet and Intranet in their work place.
The management should provide them the training on the basis of the knowledge of current health initiatives
It is concluded that the latest development in the IT greatly influences the day today activities of the nurses. So the Hospital Management should take necessary steps to take initiatives for the nurses to access the technology.
LIMITATIONS AND FUTHER RESEARCH
The results obtained in this study could be subject to some limitations as mentioned below:
The study is limited to a particlar hospital in a district.
Since it is a service sector it was found to be difficult in meeting the respondents.
The findings are based on the responses of 70 moderate sample sizes of nurses.
Some avenues for further research are as follows:
A further study may be undertaken on factors that influences Information technolgy adoption among nurses and
The impact of information technolgy on patient safety
A study regarding how information management addressess the nursing issues may also be focussed.