Impact of technology-based care and management systems on aged care outcomes in Australia

Research Article

Impact of technology-based care and management systemson aged care outcomes in Australianhs_668 87..94

Tracey McDonald, rn, phd and Frances Russell, bapsc., mphSchool of Nursing, Australian Catholic University and RSL LifeCare, Sydney, New South Wales, Australia

Abstract This study determined the impact of a computerized care documentation system on client outcomes, regula-tory compliance, and staff workloads after 3 years of use. The survey was conducted at an 800-bed aged carefacility, and staff using the computerized care system were invited to participate (n = 112). The survey was anadapted version of the Nurses Computer Attitudes to Technology Inventory, which was refined to make itrelevant to the aged care workplace. Four multiple regression models were produced, assessing the impact ofthe computerized care management system on staff and workload; time; accuracy, and regulatory data; andresident care.The analysis showed that the perceived benefits of the computerized system were influenced bypersonal attitudes towards computer use and feelings of empowerment related to the computer system. Eventhose with poor computer skills and feelings of insecurity about using computers believed that there weresignificant benefits to be gained by using the system. This result has implications with regards to the trainingand recruitment of staff in the aged care sector, as facilities introduce computerized care systems.

Key words aged care, care outcome, information technology, quality of care, time management, work design.

INTRODUCTION

The expansion of computer usage in all businesses and healthservices has increased exponentially over recent decades, andnurses in all care contexts in all countries now rely on com-puters for a range of management, communication, andcare documentation purposes. Without computerization, thesustainability of most organizations and services would be indoubt (Ibrahim et al., 2006; Poulos et al., 2007), and theirability to meet mandatory reporting to funding authoritiesjeopardized (Munyisia et al., 2011).In early 2010, 3 years after the full introduction of the

Lee Total Care (LTC) computerized records system, staff atRSL LifeCare in Sydney,Australia, were surveyed to find outhow they were coping with the change in work design, andwhether they thought benefits had been gained for residentcare and management outcomes.The LTC electronic data capture system was adapted to

existing documentation, and reporting mechanisms so as toreduce transition issues and retain regulatory complianceunder the Australian Commonwealth Aged Care Act 1997and Quality Principles (as amended). Internationally, LTChas been adapted to the legislative requirements applying toparticular countries or provinces. Since that time, other resi-dential aged care sites within the RSL LifeCare organizationhave incorporated the LTC system. In all, the system now

provides computerized care records, quality reporting, onlinetraining, and evidence searches to over 800 RSL LifeCareemployees who provide nursing care and treatment servicesto 882 clients. To date, no research had been undertaken toassess the staff-perceived impact of computerized care docu-mentation systems on outcomes, such as resident care, staffworkloads, and time management.

Literature review

With information and communication technologies (ICT)now ubiquitous in all enterprises, it is not surprising thathealth and aged care services in all developed countries havegrasped the opportunity to introduce information technology(IT) to all aspects of management and the delivery of careand treatment services to their clientele most of whom arevulnerable.The magnitude of this change also affects employ-ees, many of whom entered aged care employment expectingtheir work to remain low tech and very much hands on.Options for non-technological approaches to their work arediminishing, as ICT permeates their work role responsi-bilities, while increasingly, the use of ICT is mandated byregulatory authorities and employers.To date, little research has focused on the impact that aged

care workers feel that these technologies have had on theresidents in their care, or on their own work practices.Simpson (2004) found that technology makes nurses nervousand afraid that they might be replaced by computers,whereasin a national survey of Australias nurses, Eley et al. (2009a)found that the vast majority of nurses have positive attitudes

Correspondence address: Tracey McDonald, PO Box 968, North Sydney, NSW 2059,Australia. Email: [email protected] 14 June 2011; accepted 16 November 2011.

Nursing and Health Sciences (2012), 14, 8794

2012 Blackwell Publishing Asia Pty Ltd. doi: 10.1111/j.1442-2018.2011.00668.x

towards computers and the benefits of ICT to clinical care.This finding builds on earlier work by Yu (2005), who foundthat aged care workers were mostly supportive of the intro-duction of ICT to their workplaces.Mandatory change lies outside an individual employees

volitional control, and therefore, introduction of technologi-cal change has the potential to alter nursing practice andredefine the point of care for nursing work (Courtney et al.,2005). As such, the introduction of ICT poses inherent risksof losing valuable employees who find the technology chal-lenges too great, and/or of diminishing work quality becauseof user errors.A review of the literature using CINAHL, Journals@Ovid,

Medline, and Nursing Resource Centre, with the keywordsaged care and technology was performed. This revealeda number of papers looking at impacts of ICT across thehealthcare sector. Most published research focused on theimpact of telehealth, especially with regard to keeping olderpeople in their own homes for longer; however, far fewerwere found focusing specifically on long-term or residentialaged care (Saligari et al., 2002; Soar & Seo 2007).A common issue across the Australian literature was the

aging of the population and the commensurate increasein demand for aged care services (Vimarlund & Olve, 2005;Ibrahim et al., 2006; Soar & Seo, 2007). This increase indemand is coupled with an aging of the aged care workforceitself (Yu et al.,2006),andfinancial pressures for organizationsto maintain competiveness in the aged care sector (Chaudhryet al., 2006; Ibrahim et al., 2006).National government regula-tory authorities are increasingly mandating the use of elec-tronic communication and aged care data reporting, causingemployers to make the introduction of ICT a priority. Theimperative is thereby transferred to the employee to adapt tothe changing work environment and incorporate ICT into theway they provide care to the residents.Theoretical frameworks pertaining to volitional uptake of

technologies and information systems include the theoryof reasoned action (Madden et al., 1992) and the theory ofplanned behavior (Ajzen, 1985); however, the question ofwhether rapid and deep changes occurring within the agedcare and health industries offer employees choices abouttechnology uptake need to be considered and incorporatedinto change-management strategies. The theory of reasonedaction has been used to inform the market in relation togenerational changes (Belleau et al., 2007), but in an employ-ment situation, technology skill requirements are determinedby the employer. Successful implementation of technologyand the changes to work activity that this inevitably bringsare more closely associated with the theory of plannedbehavior (Blue, 1995), which promotes personal involvementin the decision to alter ones approach to a situation.Acknowledgment of the psychological aspects of computerusage (Yaghmaie et al., 2002) was also taken into account inthe study design.The initial introduction of the LTC system in this 800-bed

facility was accompanied by considerable staff training andindividual coaching, as well as an investment in state-of-the-art IT systems throughout the organization (McDonald et al.,2008).

Success in change management depends on the skills andattitudes of employees, and the support they receive in incor-porating the change into their work processes. Ibrahim et al.(2006) found that it was vital to both educate care staff andinvolve them in the design of ICT systems if they were to besuccessfully adopted by the workforce. Courtney et al. (2005)reported that nurses are not intrinsically opposed to IT intheir practices. They reported that nurses have acceptedtechnological innovations when they can be shown toimprove the care they can provide.Eley et al. (2009b) reported that nurses who responded to

their survey did not feel that IT had made their jobs easier.They felt there was duplication in data entry and that errorscontinued to occur.The researchers also found that age was a small but sig-

nificant factor in attitude to IT by nurses (p. 17). This is animportant issue to consider in the aged care sector, as theworkforce is aging. Eley et al. (2009a) found that respondentsdid not feel their age was a barrier; however, their age wasfound to have positive correlations with both knowledge andconfidence in the use of computers.A number of researchers have found that aged care

workers and nurses are concerned that IT will take more timeand reduce their time for hands-on care of residents, whichis what they see as their primary task (Eley et al., 2009b).However, paper-based documentation has become a time-consuming burden, and so IT is seen as a possible remedy tothis issue (Pelletier et al., 2005; Yu et al., 2006).On the basis of the review, the variables deemed important

to the study were identified and then validated through con-sultation with experts in aged care, management, and ICT.The survey tool was then modified to emphasize these vari-ables (demographic information, personal usage of comput-ers, personal decision-making, attitudes towards computers,computer experience at work, personal stress attributed tousing computers and the computer system, perceived per-sonal control related to computer use at work, pressure usingcomputers at work, and evaluating the use of computers andthe computer system), and then further refined to set up thedata for regression modeling.

Study aim

The research was designed to determine the attitudes andperceptions of aged care staff towards computer usage atwork, and whether their use supports management and careoutcomes.

Objectives

The objectives of this study were to: (i) identify managementand employee hurdles in implementing computerized infor-mation systems in the aged care context; (ii) identify staffaptitude and proficiency factors that enhance or impede tech-nology uptake; and (iii) examine the effect of a computerizedcare records system on employee attitudes towards potentialimpacts on resident clinical outcomes.

88 T. McDonald and F. Russell

2012 Blackwell Publishing Asia Pty Ltd.

METHODS

Design

A questionnaire formed the basis for this exploratory study,and all data were analyzed using regression modeling.

Participants

Information and invitations to employees to be involved inthe study were placed on notice boards in the workplace, andannouncements made at various staff meetings. Participantswere drawn from employees at the aged care facility, wherethe computerized system had been in place for 3 years.Booklet surveys were circulated to the 250 employeesexpected to be using the LTC computerized system as part oftheir work. These employees included registered nurses,enrolled and assistant nurses, and allied health staff. Partici-pants indicated their consent to contribute to the study bycompleting and returning the survey. Anonymity and confi-dentially were ensured by participants, using a formula toestablish a code for themselves that only they would know.Surveys were deposited anonymously in a box at each work-place, and these were emptied each day and returned to theresearchers for analysis.Managers were asked to remind staffthrough general announcements that they could volunteer tobe part of the study if they completed their surveys andplaced them in the boxes.

Data collection

The survey was adapted initially by Jayasuriya & Caputi(1996) from the NCATT (Nurses Computer Attitudes toTechnology Inventory) to produce a practical instrumentfor both students and practitioners. The refined tool wasreported to have evidence of concurrent validity and somemeasures of construct validity (Jayasuriya et al., 1998). Then,with permission from the authors, and using variables rel-evant for this study,we further adapted it to be relevant to theaged care workplace.Questions were pilot tested with a smallgroup of aged care workers, who were not based in Sydney, tocheck for clarity and meaning.The survey consisted of 125 questions, including three

questions on demographics (age, sex, role), seven questionson personal use of computers to assess a baseline level ofcomputer usage, 16 questions to determine the respondentspersonal decision-making style, 21 questions to determineattitudes towards computers, 21 questions to determinerespondents feelings and experiences on using computers atwork, five questions on personal stress attributed to usingcomputers at work, six questions relating to perceived per-sonal control related to computer use at work, 15 questions todetermine the level of pressure felt regarding using comput-ers at work, and 31 questions about the way the respondentsfelt and thought about using the LTC system.

Ethical considerations

Approval to conduct this research was granted by themanager of the aged care facility. Ethics approval was

granted by the Australian Catholic University HumanResearch Ethics Committee. The risk to employees was con-sidered quite low, and steps were taken to ensure that no oneother than the person volunteering to participate could iden-tify their survey booklet. At no time did the employer ormanagers have access to completed surveys, which remainedin a sealed box until delivered to the researchers for analysis.

Data analysis

We produced four multiple linear regression models assess-ing the impact of the introduction of the computerized caremanagement system on: (i) staff and workload; (ii) time; (iii)accuracy and regulatory/accreditation data; and (iv) residentcare. Modeling was conducted in two stages. First, relevantpredictor variables were analyzed in a univariate linearregression model, that is, the impact of each individual pre-dictive variable was assessed on the outcome of interest.Those covariates that had a P-value of less than 0.10 in theunivariate analysis were retained for use in the multivariatemodel.Once the univariate modeling was completed, the retained

predictive variables were entered into a multiple linearregression procedure. Variables were removed in abackwards-stepwise procedure, starting with those with thehighest P-value in the multivariate model, until the partialP-value for all covariates were significant at the P < 0.05level. However, the effect of removal of individual covariateson the overall model was assessed using the F-test, such thatif P > 0.10, the covariate was retained.Variables with a high intercorrelation (>0.60) were com-

bined, and rescaled as either eight- or 15-item scales. Thesecombined predictors were named: Attitude to computers, combining uncomfortable

and fear (8-item scale, intercorrelation: 0.70) Computer experience at work combining unsure/

doubtful and fear (8-item scale, intercorrelation: 0.73) Stress, combining personal stress using computers

and pressure using computers, which included frequencyand amount (15-item scale, intercorrelation range: 0.720.94).Modeling was conducted using SPSS version 9 (IBM SPSS,Armonk, NY, USA).

Interpretation

In the univariate linear regression, a single unit increase inthe covariate leads to a b-unit increase in the end-point ofinterest. In the multivariate analysis, when all other covari-ates are held fixed, a single unit rise in the covariate of inter-est leads to a b-unit increase in the end-point of interest.

RESULTS

Of the 250 surveys distributed, we received 112 responses(16% males, 84% females). The overall response rate was45%. Respondents included 23 registered nurses (21%), 57enrolled and assistant nurses (52%), and others, includingallied health staff.

Impact of technology on aged care outcomes 89


Perceived impact on staff and workload

Following the univariate analysis (Table 1), 14 covariateswere retained for use in the multivariate model. Refinementof the multivariate model led to the inclusion of computerexperience at work (secure), personal control (empower-ment), and stress (not stressful, frequency, and amount) beingretained in the model (Table 2). The covariates included inthe final multivariate model accounted for 53.7% of the vari-ability in the impact on staff and workload.Respondents were greatly influenced by their own feelings

of control over the computer-use situation and the pressureor comfort they experienced in using computer software.Those who felt empowered in terms of personal controlrelated to computer use at work believed that the computer-ized system impacted favorably on staff and workloads.However, respondents who felt high levels of personal stress,and stress about the frequency and amount of use of thecomputerized system at work, believed that it had impactednegatively on staff and workloads.

Perceived time saving

Following univariate analysis (Table 3), refinement of themultivariate model led to the inclusion of job role,age, thoughtful personal decision-making, secure computerexperience at work, powerlessness, and stress (not stressful,frequency, and amount) (Table 4). The covariates includedin the final multivariate model accounted for 52.3% of the

Table 1. Impact on staff and workload: univariate analysis

Covariate Coefficient (b) P-value N

Job role 102Registered nurse Reference Enrolled nurse 1.88 0.216Other 2.72 0.142

Sex 101Male Reference Female -0.20 0.909

Age -0.02 0.611 95Personal usage of computers 0.18 0.057 102Personal decision-making 102Thoughtful 0.81 0.000Intuitive -0.13 0.394Avoidance -0.19 0.247

Attitude to computers 102Comfortable 0.36 0.000Uncomfortable -0.16 0.097Fearful -0.25 0.137Uncomfortable & fearful -0.16 0.097

Computer experience at work 102Secure 0.74 0.000Unsure/doubtful -0.42 0.002Fearful -0.19 0.319Unsure/doubtful and fearful -0.30 0.032

Personal stress computersNot stressful -0.88 0.000 81Stressful 1.06 0.000 79

Personal controlEmpowerment 1.03 0.000 100Powerlessness -0.08 0.710 99

Pressure using computers 102Frequency -0.23 0.000Amount -0.21 0.000

Stress: not stressful, frequency, &amount

-0.23 0.000 102

Combined covariate, due to intercorrelation.

Table 2. Impact on staff and workload: multivariate analysis

Covariate Coefficient (b) P-value t

Computer experience at work:secure

0.51 0.000 4.43

Personal control: empowerment 0.49 0.015 2.50Stress: not stressful, frequency,& amount

-0.11 0.013 -2.55


Table 3. Impact on time saving: univariate analysis


Job role 102Registered nurse ReferenceEnrolled nurse 3.98 0.005Other 2.52 0.138

Sex 101Male ReferenceFemale -1.19 0.468

Age -0.11 0.048 95Personal usage of computers 0.05 0.552 102Personal decision-making 102Thoughtful 0.62 0.001Intuitive 0.00 0.975Avoidance 0.22 0.515

Attitude to computers 102Comfortable 0.20 0.012Uncomfortable -0.03 0.740Fearful 0.03 0.858Uncomfortable & fearful -0.01 0.948






-0.18 0.000 102

Combined covariate due to intercorrelation.



variability in the impact on time. Enrolled nurses who used athoughtful, personal decision-making style, and who feltsecure in their computer experience at work, felt the com-puterized system had the greatest impact on time saving.Those who had a high level of personal stress and pressureusing computers, who felt powerless, and had a high level ofpersonal usage of computers, felt that the computerizedsystem had a negative impact on time savings.

Perceived accuracy and regulatory accreditation

Following univariate analysis (Table 5), refinement of themultivariate model led to the inclusion of four covariates(Table 6). The covariates included in the final multivariatemodel accounted for 56.6% of the variability in the impact onaccuracy and regulatory accreditation.Those respondents who used a thoughtful decision-making

approach, who were secure with their computer experienceat work, and who felt empowered, felt that the computerizedsystem had the biggest impact on accuracy and regulatoryaccreditation. Once again, those who had a high level ofpersonal stress and pressure using computers, who felt pow-erless, and felt high levels of personal stress and stress aboutthe frequency and amount of use of the computerized systemat work, felt it had a negative impact on accuracy and regu-latory accreditation.

Perceived impact on client care

Following univariate analysis (Table 7), refinement of themultivariate model led to the inclusion of six covariates(Table 8). The covariates included in the final multivariatemodel accounted for 63.7% of the variability in the impact onclient care. Those respondents with thoughtful decision-making, secure computer experience at work, and who feltempowered, felt that the computerized system improvedclient care. However, those who used avoidance in their per-sonal decision-making, and who felt high levels of personalstress and stress about the frequency and amount of use ofthe computerized system at work, felt it had a negativeimpact on client care.

Summary

The results indicate that perceived negative impact of com-puterized care system is felt by staff who: (i) have high levels

of personal stress; (ii) are stressed about the frequency andamount of use of the computerized system; (iii) feel power-less; and (iv) use avoidance in personal decision-making.Although negative perceptions were present, these were

Table 4. Impact on time saving: multivariate analysis


Job role: enrolled nurse 2.41 0.041 2.09Personal usage of computers -0.12 0.009 2.69Personal decision-making:thoughtful

0.44 0.020 2.38


0.33 0.009 2.69

Personal control: powerlessness -0.53 0.020 -2.40Stress: not stressful, frequency, &amount

-0.12 0.020 -2.39


Table 5. Impact on accuracy and regulatory accreditation: univari-ate analysis


Job role 102Registered nurse ReferenceEnrolled nurse 2.40 0.122Other 3.62 0.054

Sex 101Male ReferenceFemale 1.93 0.282

Age 0.02 0.686 95Personal usage of computers 0.08 0.429 102Personal decision-making 102Thoughtful 0.82 0.000Intuitive -0.13 0.395Avoidance -0.11 0.524







-0.25 0.000 102


Table 6. Impact on accuracy and regulatory accreditation: multi-variate analysis


Personal decision-making:thoughtful

0.52 0.005 2.90


0.38 0.003 3.06

Personal control: empowerment 0.47 0.021 2.37Stress: not stressful, frequency, &amount

-0.16 0.001 -3.62




much less intense than the positive perceptions reported bymore confident system users. The implications of the findingfor existing staff lie in the way in which the computer systemwas introduced, and the support they received from their

employer and the system support team in learning to use itwell.Alternatively, the results show that perceived positive

impact of computerized care system is felt by staff who: (i)feel empowered in terms of computer use at work; (ii) havethoughtful decision-making style; and (iii) are secure in theircomputer experience, was overwhelmingly positive. Thisresponse is likely to be due to the user interface and func-tionality of the system, as well as the relevance and appro-priateness of the system to the technical and professionalwork needed to be achieved.

DISCUSSION

Key to the delivery of care and the development of profi-ciency in the use of computers and associated software in anyservice environment is the belief of staff and managers thatthe systems and equipment are useful in reducing repetitivework, and also that the time saved by using the system can beallocated to improving the direct care of residents or clients.The introduction of ICT involves a mutual transformationprocess that actively engages people, organizations, andtechnology. Successful implementation requires adequatefunding, strong leadership and project management, integra-tion of information technology with work practices, manag-ing change and end-user expectations, as well as end-usertraining and support (Yu et al., 2010). Investment in IT inaged care contexts is increasing,with twice as many aged carefacilities in New South Wales, Australia, using computers forresident information in 2004, as had been the case 4 yearspreviously (Albert Research, 2004). With this in mind, it isessential that care services embrace and implement ICT ifhoped-for benefits to care recipients are to be achieved.If we had measured clinical indicators of care (or the lack

of), such as skin breakdown or falls, any claim that a causallink exists between these outcomes and the introduction ofan intervention, such as the LTC computer system, would bespurious at best. By surveying employees about their atti-tudes towards computers at work and their beliefs about theeffects of computer use on care outcomes, we have been ableto tap into the deep drivers of behavior that have conse-quences for the quality of care delivered by staff.Their beliefthat an intervention does save time, that accuracy isenhanced, or that clinical care is improved, can make all thedifference to the actual performance of care and manage-ment tasks.The resident outcome section is of particular importance

when considering the introduction of new technologies thatcould distract attention from clinical and other care matters.Respondents were asked whether the new system hasaffected their confidence in meeting their professional andmoral duty of care to clients, and overwhelmingly, theybelieved it had helped.Other aspects of care include linkagesbetween care plans and outcomes evaluations; coordinationof hospital transfers; increased awareness of risks, allowingpreventative action to be taken; incorporating the residentsinterests within care and lifestyle plans; incorporating acutecare needs within care and lifestyle goals; ensuring comple-mentary therapy plans are compatible with care and lifestyle

Table 7. Impact on residential care: univariate analysis


Job role 102Registered nurse ReferenceEnrolled nurse -0.33 0.896Other 0.82 0.790

Sex 101Male ReferenceFemale 0.70 0.808

Age 0.02 0.844 95Personal usage of computers 0.22 0.155 102Personal decision-making 102Thoughtful 1.39 0.000Intuitive -0.14 0.568Avoidance -0.49 0.064







-0.39 0.000 102


Table 8. Impact on residential care: multivariate analysis


Personal decision-makingThoughtful 0.79 0.006 2.86Avoidance -0.69 0.004 -2.98

Attitude to computers:uncomfortable & fearful

0.37 0.018 2.43


0.84 0.000 4.12

Personal control: empowerment 0.81 0.008 2.75Stress: not stressful, frequency, &amount

-0.91 0.005 -2.93




goals; incorporating palliative care planning, podiatry, andtherapy plans within their holistic care goals; and for resi-dents with acute and complex care needs, making sure thatthese are met in ways that are compatible with contemporarycare and client lifestyle choices.Within all of these parameters on care outcomes, the

respondents believed that overall, the impact of computer-ized care systems had been very positive. Even respondentswho found computer usage stressful and disempowering stillfound that the LTC had a positive impact, albeit less positivethan those who felt secure in their computer use. The stron-gest advocates for the impact of the LTC were those whoused a thoughtful, personal decision-making style, who feltsecure in their computer use at work, and who felt empow-ered. Detractors were those who felt high levels of personalstress and stress about the frequency and amount of use ofthe LTC at work. As Timmons (2003) reported, successfuladoption of IT by nurses is affected by their attitudes andwillingness to comply with use. This is supported by ourresults. Eley et al. (2009a) found that the vast majority ofnurses demonstrate positive attitudes towards computer use,and acknowledge the benefits of ICT to clinical care. Pastexperience with computers in the workplace and at homemake a major contribution to this positive attitude. Ourresults also support these findings,with the majority of nursesfeeling that the LTC system had a positive effect in all areasconsidered, especially for those who were secure in theircomputer use.It is noteworthy that some of the respondent descriptors

appeared to have little impact on their view of LTC. Forexample, respondent age was only important in determiningthe impact of the LTC on time savings, with older respon-dents less likely to believe that the LTC was useful. Similarly,work classification impacted only on the time-saving model,with enrolled nurses more likely to believe that the LTC isuseful in this context. The sex of participants was not linkedto any perceived difference in impact of LTC across all areastested. These results concur with those of other researchers,including Eley et al. (2009b), who reported that 87% of theirrespondents felt that their age was never or rarely a barrier totheir use of technology.Our models explain the variability in impacts in the four

models reasonably well, with R2 ranging between 52% and64%.That is, our covariates are able to explain the variabilityin the impacts of staff and workloads, time savings, accuracyand regulatory accreditation, and client care with reasonableaccuracy.

Limitations

The survey tool was a slightly modified version of one thathad been validated in an earlier study of nurses and technol-ogy uptake, a practice that has been endorsed as appropriatefor such studies by Munyisia et al. (2011). The return rate forsurveys was acceptable at 45%, considering that it had beendistributed to people assumed to be using computers in thecare areas, and in many instances, this assumption was notcorrect. Survey booklets were distributed with the instructionthat all those using the computerized care documentation

system could participate. As a result, many self-selected outof the study. It also became apparent during the course of ourresearch that not all staff who were authorized to use theLTC system were actually using the system.We attempted toincrease participation rates by encouraging the nurse man-agers to prompt their staff to complete the survey. Furtherresearch into the task allocation that occurs at the care arealevel is needed to determine if some staff are prevented fromusing the computerized system because of role, languageskills, or job design.

Conclusions

After 3 years of using the LTC system, computerized carerecords and online information access have become ubiqui-tous for managers and clinicians alike throughout the agedcare facility.With this revised survey tool, we were able to identify

barriers and facilitators to staff use of the LTC system, as wellas staff attitudes towards potential impacts of system use onclient clinical outcomes.The change reported here was implemented within a care

context with traditional reliance on non-technology solu-tions. Three years on, the success of the transition to ICTsystems underwrites the commitment of managers and clini-cians to: (i) adequate IT resourcing; (ii) organizationalculture of support; (iii) acknowledgment of staff input andinnovation; and (iv) evaluation of outcomes for staff, manag-ers, and clients.Implications for nurses inAustralia and elsewhere,who are

provided with opportunities to use computerized care docu-mentation systems, are that there are benefits to themselves,their employers, and their patients of developing proficiencyin using the technology. Colleagues, whose access to comput-ers at work is hampered by poor language and literacy, needto be assisted and coached so that they too can feel empow-ered and valued. Where data entry is performed by nurseassistants, nurses need to take care to oversee the accuracyand appropriateness of information, and provide leadershipand guidance as needed.Disadvantages for employees who have little or no per-

sonal computing experience in moving to a technology-basedreporting system go beyond their own discomfort. Staffattitudes towards and proficiency in using computers on careoutcomes, and the organizations ability to meet regulatoryand accreditation compliance requirements, could also becompromised if these aspects are not well managed.Our findings also have implications for the recruitment of

future staff to the aged care sector, where non-technologicalapproaches to management and care are rapidly becomingredundant.

ACKNOWLEDGMENTS

The authors wish to thank Dr Dave Grayson for conductingthe statistical analysis, and Dr Belinda Butcher,WriteSourceMedical Pty Ltd for statistical advice and medical writingassistance.



Access to project documentation was provided by LeeConsulting Australia Pty Ltd,Victoria,Australia, who designand distribute the Lee Total Care system internationally.

CONTRIBUTIONS

Study Design: TM, FRData Collection and Analysis: TM, FRManuscript Writing: TM, FR

REFERENCES

Ajzen I. From intentions to actions: a theory of planned behaviour.In: Kuhl J, Beckmann J (eds). Action Control: From Cognition toBehaviour. Berlin and New York: Springer-Verlag, 1985; 1139.Pub ID 103-371-616.

Albert Research. Results of Research into the Residential Aged CareIndustrys Use of Computers and the Internet. Canberra:AustralianGovernment Department of Health and Ageing, 2004.

Belleau B, Summers T, Xu Y, Pinel R. Theory of reasoned action:purchase intention of young consumers.Cloth.Textiles Res. J. 2007;25: 244257. doi: 10.1177/0887302X07302768.

Blue C. The predictive capacity of the theory of reasoned action andthe theory of planned behaviour in exercise research: an integratedliterature review. Res. Nurs. Health 1995; 18: 105121.

Chaudhry B,Wang J,Wu S et al. Systematic review: impact of healthinformation technology on quality, efficiency, and costs of medicalcare. Ann. Intern. Med. 2006; 144: E-12W-16.

Courtney K, Demiris G, Alexander G. Information technology:changing nursing processes at the point-of-care.Nursing Adminis-tration Quarterly Will Technology Change Our Practice? 2005;October/December, 29: 315322.

Eley R, Fallon T, Soar J, Buikstra E, Hegney D. Barriers to use ofinformation and computer technology by Australias nurses: anational survey. J. Clin. Nurs. 2009a; 18: 11511158.

Eley R, Soar J, Buikstra E, Fallon T, Hegney D. Attitudes of Austra-lian nurses to information technology in the workplace: a nationalsurvey. Comput. Inform. Nurs. 2009b; 27: 114121.

Ibrahim R, Barnett KR, Buys LR. Introduction of an electronicdocumentation system: impact of IT integration on residential staffin an aged care organisation.Geriaction 2006; 24: 1119.

Jayasuriya R, Caputi P. Computer attitude and computer anxiety innursing: validation of an instrument using an Australian sample.Comput. Nurs. 1996; 14: 340345.

Jayasuriya R, Rawstorne P, Caputi P, Mortimer-Fox M, Potts M. ITadoption and diffusion: study of implementing an electronicpatient record [online]. In: Thelander N, Bennett J,Ward M (eds).

HIC 98: Proceedings. Brunswick East, Vic.: Health InformaticsSociety of Australia, 1998; 198204.

Madden T, Ellen PS,Ajzen I.A comparison of the theory of plannedbehaviour and the theory of reasoned action. Pers. Soc. Psychol.Bull. 1992; 18: 39. DOI: 10.1177/0146167292181001.

McDonald T, Lee C, Hardy J, Kwok C. Implementing technology-based care and management systems for effective aged care out-comes: issues and recommendations.HIC 2008 Health InformaticsSociety of Australia, The person in the centre. Melbourne, Aug31 to Sept 2 2008. Melbourne: Health Informatics Society of Aus-tralia Ltd (HISA) Publishers. 2008: 178183.

Munyisia EN, Yu P, Hailey D. The change in caregivers perceptionsabout the quality of information and benefits of nursing documen-tation associated with the introduction of an electronic documen-tation system in a nursing home. Int. J. Med. Inform. 2011; 80:116126.

Pelletier D,Duffield C,Donoghue J.Documentation and the transferof clinical information in two aged care settings.Aust. J.Adv. Nurs.2005; 22: 4045.

Poulos CJ, Gazibarich BM, Egar K. Supporting work practices,improving patient flow and monitoring performance using a clini-cal information management system. Aust. Health Rev. 2007; 31(Suppl. 1):S79S85.

Saligari J, Flicker L, Loh PK,Maker S, Ramesh P, Goldswain P. Theclinical achievements of a geriatric telehealth project its first year.J. Telemed. Telecare 2002; 8 (Suppl. 3): 5355.

Simpson RL. The softer side of technology: how IT helps nursingcare. Nurs. Adm. Q. 2004; 28: 302305.

Soar J, Seo Y. Health and aged care enabled by information tech-nology. Ann. N. Y. Acad. Sci. 2007; 1114: 154161.

Timmons S.Nurses resisting information technology.Nurs. Inq. 2003;10: 257269.

Vimarlund V, Olve N. Economic analyses for ICT in elderlyhealthcare: questions and challenges. Health Inform. J. 2005; 11:309322.

Yaghmaie F, Jayasuriya R, Caputi P. The effect of individualpsychological characteristics in the use of computerised informa-tion systems. In: Ribbons R, Dall V, Webb R (eds). HIC 2002Handbook of Abstracts: Improving Quality by Lowering Barriers.Melbourne: Health Informatics Society of Australia, 2001; 5556.

Yu P. Research summary: capacity and willingness of residentialaged care workers to use IT to manage care information. Geri-action 2005; 23: 2223.

Yu P, Qiu Y, Crook P. Computer-based nursing documentation innursing homes: a feasibility study. Stud. Health Technol. Inform.2006; 122: 570574.

Yu P, Yu H, McDonald T. Critical factors for the successfulintroduction of information and communication technologies intohealth care organisations. J. Med. Inform. 2010; 31: 17.



Documents

Impact of technology-based care and management systems on aged care outcomes in Australia