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.<\/p>\n
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.<\/p>\n
Limitations- This study is limited to only hospitals and the results. The results may not be applicable to other business organizations.<\/p>\n
Information Technology, Nursing, Hospital<\/p>\n
INTRODUCTION<\/p>\n
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.<\/p>\n
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<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
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.<\/p>\n
The present study is undertaken to find out the following.<\/p>\n
To identify the extent to which nurse have access to and use information technology and information management systems.<\/p>\n
To identify the purposes for which nurses use information techonolgy and information mangement systems.<\/p>\n
To find the association between the demographic profile and the work related activities with using computer<\/p>\n
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.<\/p>\n
To understand the barriers that prevents nurses from benefitng from information technology and information management system.<\/p>\n
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.<\/p>\n
1<\/p>\n
Female<\/p>\n
70<\/p>\n
100<\/p>\n
2<\/p>\n
Below 30<\/p>\n
55<\/p>\n
79<\/p>\n
30-40<\/p>\n
15<\/p>\n
21<\/p>\n
3<\/p>\n
Staff Nurse<\/p>\n
42<\/p>\n
60<\/p>\n
ANM<\/p>\n
25<\/p>\n
36<\/p>\n
Surgical technician<\/p>\n
2<\/p>\n
3<\/p>\n
Anesthesia technician<\/p>\n
1<\/p>\n
1<\/p>\n
4<\/p>\n
Continuous shift worker<\/p>\n
54<\/p>\n
77<\/p>\n
Day shift worker<\/p>\n
7<\/p>\n
10<\/p>\n
Evening shift worker<\/p>\n
4<\/p>\n
6<\/p>\n
Night shift worker<\/p>\n
1<\/p>\n
1<\/p>\n
Morning and Evening shift worker<\/p>\n
3<\/p>\n
4<\/p>\n
Evening and night shift worker<\/p>\n
1<\/p>\n
1<\/p>\n
5<\/p>\n
Diploma<\/p>\n
46<\/p>\n
66<\/p>\n
UG<\/p>\n
12<\/p>\n
17<\/p>\n
PG<\/p>\n
2<\/p>\n
3<\/p>\n
Other<\/p>\n
10<\/p>\n
14<\/p>\n
6<\/p>\n
General ward<\/p>\n
43<\/p>\n
61<\/p>\n
Annexe ward<\/p>\n
7<\/p>\n
10<\/p>\n
Operation Theatre<\/p>\n
7<\/p>\n
10<\/p>\n
Dialysis Unit<\/p>\n
4<\/p>\n
6<\/p>\n
ICU<\/p>\n
9<\/p>\n
13<\/p>\n
The data was collected from the nurses of the selected hospital through a questionaire which has 11 parts, namely;<\/p>\n
Demographic characteristics and background of IT<\/p>\n
Access and Use of computers<\/p>\n
Use of Information Technology<\/p>\n
Access to Internet and Intranet<\/p>\n
Knowledge of current Health I.T initiatives<\/p>\n
Job requirement for I.T<\/p>\n
Training and Education about Information technology<\/p>\n
Barriers to use of computers<\/p>\n
Technical support<\/p>\n
Management attitudes and support<\/p>\n
Security<\/p>\n
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.<\/p>\n
H0: There is no significant relation between age and Work related activities at Home computer.<\/p>\n
H1: There is significant relation between age and Work related activities at Home computer.<\/p>\n
H0: There is no significant relation between designation and Work related activities at Home computer.<\/p>\n
H1: There is significant relation between designation and Work related activities at Home computer.<\/p>\n
H0: There is no significant relation between shift timings and Work related activities at Home computer.<\/p>\n
H1: There is significant relation between shift timings and Work related activities at Home computer.<\/p>\n
H0: There is no significant relation between qualifications and Work related activities at Home computer.<\/p>\n
H1: There is significant relation between qualifications and Work related activities at Home computer.<\/p>\n
H0: There is no significant relation between department and Work related activities at Home computer.<\/p>\n
H1: There is significant relation between department and Work related activities at Home computer.<\/p>\n
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.<\/p>\n
1<\/p>\n
Age and Work related activities at Home computer.<\/p>\n
12.853 < 14.07 ( Not Significant)<\/p>\n
2<\/p>\n
Designation and Work related activities at Home computer.<\/p>\n
25.408 < 32.67 ( Not Significant)<\/p>\n
3<\/p>\n
Shift timings and Work related activities at Home computer.<\/p>\n
36.97 < 49.80 ( Not Significant)<\/p>\n
4<\/p>\n
Qualifications and Work related activities at Home computer.<\/p>\n
26.34 < 32.67( Not Significant)<\/p>\n
5<\/p>\n
Department and Work related activities at Home computer.<\/p>\n
34.14 < 41.33 ( Not Significant)<\/p>\n
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.<\/p>\n
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.<\/p>\n
.859<\/p>\n
Bartlett’sTestof Sphericity<\/p>\n
Approx. Chi-Square<\/p>\n
1144.756<\/p>\n
Df<\/p>\n
153.000<\/p>\n
Sig.<\/p>\n
.000<\/p>\n
Component<\/p>\n
Initial Eigen values<\/p>\n
Extraction Sums of Squared Loadings<\/p>\n
Total<\/p>\n
% of Variance<\/p>\n
Cumulative %<\/p>\n
Total<\/p>\n
% of Variance<\/p>\n
Cumulative %<\/p>\n
1<\/p>\n
9.288<\/p>\n
51.599<\/p>\n
51.599<\/p>\n
9.288<\/p>\n
51.599<\/p>\n
51.599<\/p>\n
2<\/p>\n
1.926<\/p>\n
10.698<\/p>\n
62.298<\/p>\n
1.926<\/p>\n
10.698<\/p>\n
62.298<\/p>\n
3<\/p>\n
1.468<\/p>\n
8.154<\/p>\n
70.452<\/p>\n
1.468<\/p>\n
8.154<\/p>\n
70.452<\/p>\n
4<\/p>\n
1.254<\/p>\n
6.965<\/p>\n
77.416<\/p>\n
1.254<\/p>\n
6.965<\/p>\n
77.416<\/p>\n
5<\/p>\n
.869<\/p>\n
4.830<\/p>\n
82.246<\/p>\n
6<\/p>\n
.728<\/p>\n
4.044<\/p>\n
86.290<\/p>\n
7<\/p>\n
.476<\/p>\n
2.642<\/p>\n
88.933<\/p>\n
8<\/p>\n
.353<\/p>\n
1.960<\/p>\n
90.893<\/p>\n
9<\/p>\n
.334<\/p>\n
1.853<\/p>\n
92.746<\/p>\n
10<\/p>\n
.264<\/p>\n
1.465<\/p>\n
94.211<\/p>\n
11<\/p>\n
.237<\/p>\n
1.319<\/p>\n
95.530<\/p>\n
12<\/p>\n
.225<\/p>\n
1.250<\/p>\n
96.780<\/p>\n
13<\/p>\n
.148<\/p>\n
.820<\/p>\n
97.600<\/p>\n
14<\/p>\n
.140<\/p>\n
.778<\/p>\n
98.379<\/p>\n
15<\/p>\n
.107<\/p>\n
.596<\/p>\n
98.975<\/p>\n
16<\/p>\n
.087<\/p>\n
.481<\/p>\n
99.455<\/p>\n
17<\/p>\n
.055<\/p>\n
.308<\/p>\n
99.763<\/p>\n
18<\/p>\n
.043<\/p>\n
.237<\/p>\n
100.000<\/p>\n
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.<\/p>\n
Total<\/p>\n
% of Variance<\/p>\n
Cumulative %<\/p>\n
6.626<\/p>\n
36.812<\/p>\n
36.812<\/p>\n
2.707<\/p>\n
15.038<\/p>\n
51.850<\/p>\n
2.660<\/p>\n
14.777<\/p>\n
66.627<\/p>\n
1.942<\/p>\n
10.790<\/p>\n
77.416<\/p>\n
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%.<\/p>\n
Apple Mac OS<\/p>\n
.125<\/p>\n
.204<\/p>\n
.106<\/p>\n
SPSS<\/p>\n
.212<\/p>\n
.245<\/p>\n
-.014<\/p>\n
Reference tools<\/p>\n
.199<\/p>\n
.291<\/p>\n
-.072<\/p>\n
Spreadsheet<\/p>\n
.219<\/p>\n
.152<\/p>\n
.065<\/p>\n