Information Technology On Nursing Practices Health And Social Care Essay

4578 words (18 pages) Essay

1st Jan 1970 Health And Social Care Reference this

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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 < 14.07 ( Not Significant)

2

Designation and Work related activities at Home computer.

25.408 < 32.67 ( Not Significant)

3

Shift timings and Work related activities at Home computer.

36.97 < 49.80 ( Not Significant)

4

Qualifications and Work related activities at Home computer.

26.34 < 32.67( Not Significant)

5

Department and Work related activities at Home computer.

34.14 < 41.33 ( Not Significant)

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.

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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.

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.

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 < 14.07 ( Not Significant)

2

Designation and Work related activities at Home computer.

25.408 < 32.67 ( Not Significant)

3

Shift timings and Work related activities at Home computer.

36.97 < 49.80 ( Not Significant)

4

Qualifications and Work related activities at Home computer.

26.34 < 32.67( Not Significant)

5

Department and Work related activities at Home computer.

34.14 < 41.33 ( Not Significant)

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.

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