Signature Assignment: Proposal for a Study on Performance and Job Satisfaction Impacts of Employee Monitoring for Hand Hygiene Compliance

By Fahmeena Odetta Moore

Northcentral University

September 1, 2016

BTM7303-1

Dr. Lawrence Ness

Abstract

The proposed mixed methods study tests the habit-forming theory for explaining the effect of a hand hygiene compliance (electronic monitoring) solution on performance and employee satisfaction. It is reasonable to assume that electronic monitoring leads to habit formation. Based on the habit-forming theory, performance will steadily increase and peak at a certain level – performance follows an asymptotic curve – and there will be a sustained high-level of performance in the long-term. In addition, the theory suggests that job satisfaction and employee retention will not decrease after implementation of the monitoring system since employees are likely to view the monitoring as a way to remind them to practice hand hygiene, which is an important part of their job. The study will investigate the actual effect on performance and employee satisfaction, determine the actual reasons managers provided for implementation of the solution, and determine whether the reason is the most important predictor of employee satisfaction. The proposed study is primarily quantitative, but will use qualitative research methods to obtain different perspectives and more fully understand the phenomenon. Analysis techniques for testing hypotheses include: tests to compare means and proportions between two groups, ANOVA analyses, and regression analyses (quantitative) and constant comparative analysis (qualitative). Four companies that provide hand hygiene monitoring solutions will be used as sources of data on (for the population of) healthcare institutions that implemented a hand hygiene monitoring solution. Data will also be collected from each healthcare institution in the sample and employees from each institution surveyed for their perspective on the effects of the compliance monitoring.

            Keywords: performance, employee, information technology, employee engagement, employee satisfaction, job satisfaction, electronic monitoring, compliance with policies and procedures, infection control, hand hygiene compliance, healthcare, hospitals, infection rate, hand hygiene compliance rate, nurses, doctors, employee performance improvement, habits, short-term impact of monitoring, long-term impact of monitoring, negative impacts of monitoring

Signature Assignment: Proposal for a Study on Performance and Job Satisfaction Impacts of Employee Monitoring for Hand Hygiene Compliance

            This paper is a proposal for a mixed methods study to more fully understand the impacts of using information technology for increased employee monitoring to achieve improvements in infection control performance in the healthcare industry. First, I discuss employee engagement issues that surround the research problem, then I present the research problem, purpose statement, and research questions. Next, I discuss the research design and methodology, describing options considered and decisions made on sampling, data collection, and analysis of data to answer research questions etc. Then, I conclude with limitations and ethical considerations.

Introduction to Employee Engagement Issues that Surround the Research Problem

Employees (labor) are an important resource for the achievement of organizational goals, among other resources such as equipment and materials. Organizations aim to allocate and utilize employees effectively on projects, in departments, and across the organization as a whole to achieve goals and objectives. They are finding that this is difficult – for example, a seemingly appropriate number of employees may be allocated to a project, but the employees may not perform well or achieve goals. A seemingly qualified employee may be placed on a project, but that employee may be careless in their duties and, as a result, cause a major security event and losses for the organization.[1] Employee engagement, defined in Bedarkar and Pandita (2014)[2] as “a positive, fulfilling, work-related state of mind that is characterized by vigor, dedication and absorption,” is an issue that affects the employee’s willingness to work, willingness to go the extra mile, compliance with policies and procedures, and their alignment with organizational goals. There is now a lot of attention and focus on employee engagement, especially since a 2013 Gallup poll found that an alarming 63% of employees worldwide are not engaged at work and are therefore not motivated to be the productive, high-performing employees organizations desire.

Organizations use technology in a variety of ways to improve employee productivity and performance, i.e. improve performance indirectly through labor/employees. One example: an organization acquires hardware as well as software (VPN etc.) to allow employees to work from home hoping to improve not only productivity but employee engagement and retention. Another way technology is used to improve employee productivity and performance is to monitor employees. In a 2001 report, American Management Association reported that more than 80% of major U.S. firms use electronic performance monitoring (Bartels & Nordstrom, 2012).

Research Problem

Many believe there are more issues associated with electronic employee monitoring than benefits.

Some benefits of electronic employee monitoring include: (1) employees perform better because of the electronic presence (in line with social facilitation theory), and (2) employee satisfaction and morale increase because of more objective performance appraisals and improved feedback. However, as stated in Becker and Marique (2014), monitoring may lead to a “climate of distrust and negative emotions.” Becker and Marique (2014) explain that monitoring could increase stress and health complaints, decrease job satisfaction, and increase turnover propensity. Monitoring may also lead managers to place more emphasis on quantitative aspects of work over the quality of work (Bhave, 2014). Organizations that utilize technology for monitoring employees have to deal with these problems – they would obviously prefer a win-win solution. Research on the negative impacts of electronic monitoring could help to achieve the win-win. Research on the reasons for negative impacts, for example, could help the major U.S. firms that use electronic monitoring (over 80% of all major U.S. firms) develop solutions to lessen or eliminate negative effects. The negative impacts/effects of electronic monitoring is the problem to be addressed in this study.

This research will focus on the area of infection control, an area that is important to the operations of healthcare institutions. In the area of infection control, information technology was used to bring about desired performance changes that were difficult to achieve using other strategies such as compensation and hand hygiene enhancement policies (Simmonds, 2011). Some technology solutions increased the hand hygiene monitoring of nurses and other healthcare workers, which resulted in increased compliance with hand hygiene policies and procedures and, as a result, increased infection control performance. One company that provides a technology solution that monitors employee compliance using badges, Hill-Rom, reported that compliance increased 250% after 10 months at three hospitals that implemented their hand hygiene compliance monitoring solution (Hill-Rom, 2014). It is uncertain what the negative impact/effects associated with such high levels of performance improvement are in the short-term and in the long-term. Would employees gradually pay less attention to monitoring (and be less affected by monitoring) so that their productivity and performance decrease over time? It is uncertain whether such systems to increase monitoring of employees will have the same effect as systems to improve processes. Process improvements are designed to make permanent changes. Due to employee monitoring, productivity may decrease over time because employees become less engaged.

Related studies on electronic monitoring for hand hygiene compliance. There are a significant number of research studies on the electronic monitoring of employees to increase hand hygiene compliance. Some reviewed the impact of the monitoring such as a study by Edmunds et al. (2013) that sought to determine the impact of hand hygiene electronic monitoring on compliance rates, and a study by Simmonds and Granado-Villar (2011) to determine the utility of an electronic hand hygiene monitoring and reminder system for improving hand hygiene compliance in a hospital unit. There is little research on the long-term effects of electronic hand hygiene monitoring. A study by Arise et al. (2016) found that direct observation techniques at a Japanese hospital over 5 years resulted in an increase in hand hygiene compliance from 50.8% to 61.0% after one year and sustained compliance of 60% through the remaining years.[3] Another related study found that a short series of hand hygiene campaigns (educational programs) in India initially resulted in improved compliance, but compliance dropped after two years.

Purpose of Study

This mixed methods study will address the effects of electronic hand hygiene compliance monitoring on performance, employee satisfaction, and employee retention in the short and long term. A convergent parallel mixed methods design will be used, and it is a type of design in which qualitative and quantitative data are collected in parallel, analyzed separately, and then merged. In this study, quantitative performance data will be used to test the habit-formation theory that predicts a steady increase in employee performance and then a sustained high level of performance in the long-term. In addition, statistical data on employee complaints, satisfaction and retention as well as qualitative data on employee satisfaction from surveys developed for the study will be used to explore the effect on job satisfaction and employee engagement for those employees directly affected by the monitoring solution, and determine whether healthcare institutions that utilized the technology solutions provided by four companies – Hill-Rom Inc., HyGreen Inc., Stanley Healthcare, and GOJO Industries achieved sustained performance increases with little or no negative effects on job satisfaction.[4] With increased monitoring for hand hygiene compliance, employees are expected to develop the habit of cleaning/washing their hands when appropriate or when needed. It logically follows that once employees develop the new habit that is in line with policies, their performance will increase significantly and permanently. The habit-formation theory suggests that job satisfaction and employee retention will not decrease after implementation of the monitoring system since employees are likely to view the monitoring as a way to remind them to practice hand hygiene, which is an important part of their job. This study will include a quantitative analysis of performance data before and after implementation of a hand hygiene compliance monitoring solution, and will determine whether performance follows an asymptotic curve, which is associated with habit formation (Lally et al., 2010). There will be a quantitative analysis of numeric data on employee satisfaction such as complaints. There will also be an analysis of qualitative data on employee attitudes about monitoring and employee perspectives on the reasons for performance changes. The mix of quantitative and qualitative is needed to fully understand the phenomenon. Adding subjective views on the effect on monitoring on job satisfaction and performance (qualitative research) would provide additional information and maybe a different perspective. The research will include information from and on these types/categories of employees directly affected by the implementation of a technology solution that monitors hand hygiene compliance: nurses and doctors. Performance of the employees is measured by a hand hygiene compliance rate. Since hand hygiene helps to reduce patient infections, performance is also measured by a hospital-acquired infection rate, which measures the incidence of infections acquired during treatment at healthcare institutions.

Research Questions

The following questions are to determine whether the use of IT to improve hand hygiene performance through increased monitoring of employees results in lasting improvements without much reduction in employee satisfaction. The research questions are:

RQ1. Do technology solutions that monitor hand hygiene compliance result in improved employee performance in the short-term because employees develop the habit of cleaning/washing their hands (i.e. is there a steady increase in performance that peaks at a certain level – performance follows an asymptotic curve)?

RQ2. What is the longer-term performance impact of implementing a technology solution that monitors hand hygiene compliance, i.e. the performance impact after 1 year and beyond (after 3, 4, 5 years etc.)?

RQ3. Would employee job satisfaction and retention increase, decrease or remain unchanged following the implementation of the technology solution that monitors hand hygiene compliance?

Focusing on employees:

RQ4. Is the short-term and longer-term effect on performance and job satisfaction of employees that had related performance issues, fresh-out-of-school employees, and nurses the same as the effect on other employees?

RQ5. Does the reason managers provide for implementing the technology solution that monitors employee hand hygiene compliance primarily determine the effect on employee satisfaction?

Both doctors and nurses are responsible for practicing hand hygiene, but the technology solution that monitors hand hygiene compliance may affect their job performance as well as their job satisfaction differently. Studies indicate that the motivation of nurses is complicated (Platis, Reklitis, & Zimeras, 2015; Hsu et al., 2015; Terara & Ngirande, 2014). For example, compensation alone will not lead to high job satisfaction among nurses. Based on this, I hypothesize below that nurses will be more affected by the technology solution.

Hypotheses include:

H10: The technology solution that monitors hand hygiene compliance did not result in any short-term performance improvements.

H2A. The technology solution that monitors hand hygiene compliance resulted in a steady increase in employee performance that peaked at a certain level during the first year.

H30: Infection control performance showed no improvement one year after the implementation of the technology solution that monitors hand hygiene compliance and also in later years (after 3, 4, 5 years etc.).

H4A: The technology solution that monitors hand hygiene compliance resulted in lasting performance improvements evidenced by continued increases in employee performance one year after its implementation as well as in later years (after 3, 4, 5 years etc.).

H50: Employee job satisfaction and retention remained unchanged after implementation of the technology solution that monitors hand hygiene compliance.

H6A: Employee job satisfaction and retention decreased/increased after implementation of the technology solution that monitors hand hygiene compliance.

H70: The technology solution that monitors hand hygiene compliance improved the performance of all types/categories of employees in the same manner.

H80: The technology solution that monitors hand hygiene compliance improved the performance of nurses more than doctors.

H9A: The technology solution that monitors hand hygiene compliance improved the performance of fresh-out-of-school employees more than the performance of other employees in the short-term.

H10A: The technology solution that monitors hand hygiene compliance improved the performance of employees that had related performance problems (such as reprimands for failing to clean hands) more than the performance of other employees in the short-term.

H11A: The technology solution that monitors hand hygiene compliance resulted in a temporary change in the performance of employees that had related performance problems (performance increased in the short-term only; performance gains did not last).

H120: There is no relationship between the reason managers provide for implementing the technology solution that monitors employee hand hygiene compliance and the effect on employee satisfaction.

H13A: The reason managers provide for implementing the technology solution that monitors employee hand hygiene compliance affects employee satisfaction because there is no decrease in employee satisfaction if managers tell employees the solution is needed to develop their habit of cleaning/washing hands.

H140: The reason managers provide for implementing the technology solution that monitors employee hand hygiene compliance is the most important predictor of the effect on employee satisfaction.

H15A: The reason managers provide for implementing the technology solution that monitors employee hand hygiene compliance has a small and statistically significant relationship with employee satisfaction (it is not the most important predictor).

Research Design and Methodology

Proposed Research Method

            I considered the following design options for the quantitative part of this study: (1) an experimental design similar to designs used in studies by Arbogast et al. (2016), Becker and Marique (2014), Bartels and Nordstrom (2012), and Alder, Noel, & Ambrose (2006), (2) a survey method design similar to the study by Boardman, Vining, & Weimer (2016) that used data for organizations that fell into specific groups so that the groups could be compared, and (3) a survey method design similar to the study by Mckenzie and Keneley (2011), which used the case of four firms for their research.

             Experimental research involves controlling or manipulating the independent variable to determine whether the independent variable causes an effect on the dependent variable. True experimental designs assign conditions to participants at random. In their research to examine how the purpose and perception of electronic performance monitoring affects performance, Bartels and Nordstrom (2012) created five experimental conditions and assigned participants to each condition randomly. In one control group, participants were not monitored. In another group, participants were monitored with no reason for the monitoring provided. In the other three groups, participants were monitored with the following reasons provided: research, development, and administrative decision-making. Another example: Alder, Noel, & Ambrose (2006) assigned employees of a heavy equipment sales and service center in similar groups in their longitudinal field experiment design. Similar to the research by Bartels and Nordstrom (2012) and Alder, Noel, & Ambrose (2006), this research could utilize experimental methods. For an experimental study on how IT investment/expenditures for increased monitoring of employees affects performance and job satisfaction, the researcher would need to “manipulate” monitoring of employees/participants to see how changing the monitoring would affect their performance and job satisfaction. There could be three control groups: one group that is not monitored, another group that is monitored by video (i.e. actions are video recorded), and a final group that uses a new information system such as the system in the journal article by Salman et al. (2015). Employees that perform similar duties and receive similar pay could be used as participants so that participants are equivalent at the outset. Employees/participants would be assigned to a control group at random and their performance under the conditions recorded and analyzed. The advantage of this design is that the effect of increased employee monitoring is isolated and studied. However, when several variables or factors are at play, it could be difficult to remove the effects of other variables. Based on results, the researcher would accept or fail to accept hypotheses on the impact of monitoring and relationship between employee monitoring, performance, and job satisfaction. Using the experimental design to determine long-term effects would be more difficult. There is an issue with the length of time the experiment would need to run to determine long-term effects.

Boardman, Vining, & Weimer (2016) used external data on three panels of firms for their investigation of the long-term effects of privatization. The first panel consisted of 11 state-owned enterprises (SOE) that were privatized through share-issue privatizations. The second panel consisted of 9 comparable Always-SOE (firms that were never privatized). The third panel consisted of 9 comparable Always-Private firms. The researchers used data from Computstat and corporate annual reports. The research compared the performance of Privatized-SOEs before and after privatization as well as the performance of Privatized-SOEs to Always-SOE and Always-Private firms.  

            In their research, Mckenzie and Keneley (2011) used a sample of two privatizing banks and two privatized insurance companies to compare the performance of institutions before and after privatization. The four institutions used were representative of a small number of government-owned institutions in the population (five government-owned banks and six government-owned insurance institutions). The researchers measured performance using CAMEL indicators – indicators that measure Capital Adequacy, Asset Quality, Management Quality, Earnings, and Liquidity of banks. Data came from financial statements.

            The last two studies above used publicly available data (information on the privatization of institutions is publicly available as well as data on financial and other performance). The availability of the data probably drove the design. There is publicly available data that could be used for this study. The infection rates and hand hygiene compliance rates of hospitals and other healthcare institutions are publicly available in the U.S. For example, one state – State of Washington – provides infection data for hospitals in the state at a cost. The methods used by hospitals to improve infection rates, especially technology solutions used, are not as public. For the first two research questions RQ1 and RQ2, I need to know when an institution implemented a technology solution that involved increased monitoring of employees in addition to performance data before and after the solution was implemented. One source of data on the implementation of a technology solution is companies such as Hill-Rom, Inc. that provide technology solutions for healthcare institutions. Data on technology solutions used, infection rates, and hand hygiene compliance rates – all secondary data – would be sufficient data for a basic, objective analysis of the short- and long-term changes to performance due to the employee monitoring solution (excludes the research question on changes in employee job satisfaction and retention and other questions that focus on employees). There is data available on the job satisfaction of healthcare professionals, but not the satisfaction of specific employees impacted by an electronic employee monitoring solution.

            To answer the research question on changes in employee job satisfaction and retention as well as other research questions that involve employees, I would need data from the healthcare institutions themselves. One set of data would be (statistical) data on employee complaints, number of employees etc. In addition, I could obtain responses to questions on the impact of increased employee monitoring using technology, similar to research by Ham, Kim, & Jeong (2005) and Samaranayake and Gamage (2012). The questions would be closed questions as well as open-ended questions. The responses would be the thoughts and opinions of the employees on the effectiveness of employee monitoring and would therefore be subjective. This subjective data would provide insight into the actual performance indicated by statistical/performance data and could be used for quantitative analysis such as regression analysis.

            For this research, the survey method (rather than an experimental design) will be used. A sample of hospitals that implemented hand hygiene compliance solutions provided by four companies – Hill-Rom Inc., HyGreen Inc., Stanley Healthcare, and GOJO Industries will be used. Data on their performance will be collected separately and compared before and after the implementation of the solution. Data will also be collected on the performance of employees as well as employee satisfaction. Employee performance and satisfaction data will include statistics from healthcare institutions as well as responses provided by employees on the monitoring solution, their performance, and job satisfaction. The study will include both quantitative and qualitative research methods.

Population, Sampling, and Data Collection

Based on the research questions, the ideal population consists of U.S. healthcare institutions that have implemented a hand hygiene monitoring (technology) solution to improve hand hygiene compliance and infection rates more than 5 years ago and have not implemented other solutions or strategies since then. The size of this population is unknown. The population of U.S. healthcare institutions that implemented technology solutions from four companies – Hill-Rom Inc., HyGreen Inc., Stanley Healthcare, and GOJO Industries more than 5 years ago (2011 or earlier) is expected to be about 200. Some companies did not offer a hand hygiene compliance solution five years ago. Hill-Rom, for example, launched their hand hygiene compliance solution in 2013 – three years ago (Hill-Rom, 2013). An additional 300 healthcare institutions may have implemented solutions from the companies between 2011 and 2014. Data from institutions that implemented solutions in later years would be useful for analysis of shorter-term performance rather than long-term performance. All U.S. healthcare institutions that implemented technology solutions from the four companies – Hill-Rom Inc., HyGreen Inc., Stanley Healthcare, and GOJO Industries in 2014 or earlier are considered to be in the population.

Other strategies the healthcare institutions may have implemented to improve infection rates after implementation of the technology solution is a concern, but it is highly likely that the institutions did not implement other solutions or strategies after such a substantial investment. Further, the institutions likely implemented the technology solution as part of a program, i.e. with other activities such as training. Data from the institutions will be analyzed to determine whether only those institutions that did not implement other solutions/strategies should be included for an analysis of performance impacts in the longer-term. The adjusted population size is expected to be the same.

For the study, the sample will include: U.S. healthcare institutions that implemented hand hygiene compliance solutions from the four companies during the period 2009 (7 years ago) to 2015. The sample will therefore include “groups” of healthcare institutions based on the implementation date. The ideal range for data on performance is: 3 years prior to implementation of the solution to 5 years after the implementation of the solution. However, if the solution was implemented in 2015, for example, performance data will be available for just 1 year after implementation.

For the healthcare institutions in the sample, the data for this research will include:

1. Date the technology solution to increase employee monitoring was implemented, cost and design of the solution, and all activities performed with the implementation of the hand hygiene compliance solution such as training.
2. Monthly infection rates as well as hand hygiene compliance rates for each hospital. Main data source expected to be the Centers for Disease Control and Prevention and State offices. Data will be collected from hospitals if needed. [5] Data will also be collected from the institutions themselves for comparison. Rates are needed before and after the implementation of the solution as explained above.
3. Details of employees affected by (or was expected to be impacted by) the hand hygiene compliance solution implemented to include employee category, department, hire date, years of experience, education, and compensation (including any performance-driven compensation). Data source: healthcare institutions.
4. The performance of affected employees before and after implementation of the hand hygiene compliance solution. Data source: healthcare institutions. If the institution(s) tracked compliance performance by employee, then that data will be collected and utilized. Other data will include data such as employees who received reprimands for failing to wash hands, the number of reprimands for failing to wash hands, complaints submitted, and employees who were discharged because of related performance issues.
5. Other strategies used to improve infection control performance after implementation of the hand hygiene compliance solution with the reasons for and details of the strategies. Data source: healthcare institutions.
6. Total number of employees in the organization during the period(s) under review.
7. Total patient revenue, a measure of the size of a hospital. Data source: secondary source such as ahd.com. Data will also be collected from the institutions themselves for comparison.
8. Whether the hospital is for-profit or non-profit. Data source: secondary source such as ahd.com. Data will also be collected from the institutions themselves for comparison.

There may be issues with the data. In addition to data quality issues, i.e. errors in data collection and/or analysis, there may be standardization issues as well as changes in the calculation/determination of rates. A report by Joint Commission (2009) reported that organizations measure hand hygiene compliance in different ways so there may be more of an issue with hand hygiene compliance rates rather than infection rates.  

Survey. Options considered to collect data from employees on their attitudes about monitoring, reasons for performance changes as a result of monitoring etc. include: interviewing individual employees face-to-face, paper questionnaires (researcher will be present during completion), and online/electronic questionnaire. The use of online questionnaires is best for collecting information from employees especially since responses from employees from several institutions are needed. The institutions may be located all over the country. It is easier to request and obtain responses from a large number of people using online questionnaires. Other advantages of using online questionnaires: (1) employees may be more willing to provide personal and/or sensitive information (such as whether they had related performance problems, reasons for performance problems etc.) when they are not face-to-face with the interviewer, and (2) it is easier to conduct an anonymous survey. One disadvantage of online surveys is the inability of the employee to ask clarifying questions while taking the survey. However, clear and simple questions with explanations would mitigate this.

The same questionnaire will be used at each institution in the sample without too much involvement of the institutions (so that employers view the request as a request by an outsider)[6]. Some of the questions will be open-ended questions so that participants can provide explanations/details. Closed questions with “standard” options could be a problem – since the survey will be anonymous, I will not know the participant to contact or include in a subset if I have additional questions about a response(s). For questions on employee satisfaction and attitudes, examples and/or scales from previous research could be used. For example, in their research, Jeske, and Santuzzi (2015) used a short scale by Brayfield and Rothe (1951) for questions on job satisfaction and an affective commitment scale from Meyer et al. (1993) for other questions. To reduce inaccuracies or other issues that a researcher may encounter with questionnaires, there will be pretests and/or pilot tests to validate the instrument similar to the tests used by Huang et al. (2016) and Ham, Kim, & Jeong (2005). In Huang et al. (2016), the pretest was carried out with academic researchers to improve the content and appearance of the questionnaire.

The number of employees that were/are directly affected by the monitoring solution at each healthcare institution is expected to average 300.  All affected employees at each institution will be included in the sample. The response rate expected to be below 100%.

Analysis

Quantitative Analysis. The study will use “objective” statistical analysis to reach conclusions about performance impacts of IT investment that involves increased monitoring of employees. There will be initial analyses such as comparisons of data from sources such as the companies that provide technology solutions for hand hygiene compliance and the institutions themselves. These initial analyses will help with reliability and validity. To test hypotheses that need to or should be tested quantitatively, three different types of statistical tests/analyses will be used – tests to compare means & proportions, Analysis of Variance (ANOVA) tests, and regression analysis. The use of different methods for analysis helps with reliability of results.

The first set of statistical tests will be tests to compare means and proportions between two groups to test whether there was an increase in performance after implementation of the hand hygiene compliance solution. For example, the mean/average performance in the three years prior to the implementation (both the general rate as well as per-employee rate) would be compared to the mean/average performance in the first month, then the first three months, then the first six months, then first year, then three years after the implementation etc. The proportion of employees with related performance problems in the three years prior to the implementation would be compared with the proportion of employees with related performance problems in the first month, then the first three months, then the first six months, then first year, then three years after the implementation etc., and so on. This analysis will provide information on whether the IT investment resulted in statistically significant performance improvements, how long it took, and whether it differed significantly from institution to institution. The tests will test hypotheses such as H10 (from one perspective/way), H2A (from one perspective/way), H30, and H4A.

The second set of statistical tests could be ANOVA tests to compare performance and satisfaction of employees (mean performance and satisfaction of employees in each category) before and after implementation of the solution, similar to the analysis in Bartels and Nordstrom (2012) and Becker and Marique (2014). Both of these studies used the experimental research design, but used ANOVA for analysis. The ANOVA tests will test hypotheses H10 (from one perspective/way), H2A (from one perspective/way), H30, H4A, H50, H6A, H70, H80, H9A, H10A, and H11A.

Similar to Samaranayake and Gamage (2012), regression analysis could be used to determine the relationship between employee satisfaction (the dependent variable) and the main reason managers provided for implementing the hand hygiene compliance solution – to test hypotheses H120, H13A, H140, and H15A. The tentative model: employee satisfaction (the dependent variable) and independent variables: main reason management provided for the monitoring, whether employee believes the monitoring system violates privacy, organizational culture/climate, whether affected employees were involved in development of the solution, and views on compensation. Similar to Ham, Kim, & Jeong (2005), a factor analysis will be performed to determine which variables should be included in the multiple regression analysis as dependent variables. Reliability tests (Cronbach’s Alpha) will be used to test the consistency of each factor. Studies by Alder, Noel, & Ambrose (2006) and Alder (2001) indicate that employee reactions to monitoring may be influenced by organizational climate and culture so there may be a need to correct for multicollinearity.

To determine whether performance follows an asymptotic curve (hypothesis H2A), scatterplots will be generated similar to analysis by Lally et al. (2010). And similar to the analysis in Lally et al. (2010), both linear and non-linear regressions will be run for comparison. The basic regression models will use infection/hand hygiene compliance rates as the dependent variable and time as the independent variable to measure the effects over time (i.e. will be longitudinal regression models).

A 5% significance level will be used for tests. Since almost all data from the selected population is used, how well the sample represents this selected population is not much of an issue. There is more of an issue with how well the selected population represents the ideal population. 

Qualitative Analysis. There will be some questions on the questionnaire that request qualitative (free-form) responses. The constant comparative analysis developed for use in grounded theory research will be utilized. This means that the statements of the participants will be compared. Coding could be used to assist with the analysis. The qualitative analysis would provide answers such as the most common reason provided for implementing the technology monitoring solution, the most common explanation provided (experience) for a behavior/performance change, and what participants believe would have made a difference in their current attitude about the monitoring system. The analysis will therefore contribute to answering the research questions.

Limitations and Ethical Considerations

            The topic deals with “sensitive” ethical issues – the right to monitor employees, the right to privacy, and the inappropriate decisions and behaviors by employees. Employees who participate could be adversely affected if their responses are divulged, i.e. there is the potential for harm to employees. It is clear that I should not collect personal and other identifying information in questionnaires.

            Including a minimum number of employees who had related performance problems in the sample would be preferred, but these employees should not be singled out because of ethical considerations. Singling out these employees could cause harm. It would be difficult to ensure that these employees are included in the survey.

            In fact, healthcare institutions may not want to provide performance data for individual employees. There may be strict policies on providing performance data on individual employees. If collection of employee performance data from healthcare institutions becomes an important issue, responses by employees in the questionnaire would have to suffice (response would be optional). As a last resort, the research questions that deal with the performance of specific employees could be dropped.

            A limitation of the study is the sample of institutions based on the use of technology solutions offered by 4 companies. There may be biases associated with the sample. A broader, random sample would be better. However, the institutions that utilized the solutions are likely to be institutions that had significant performance problems.

Conclusion

The proposed study is the first to test the habit-forming theory for explaining the effect of a hand hygiene compliance (electronic monitoring) solution on performance and employee satisfaction. For the design and methodology, it pulls ideas from past studies, some in different disciplines. It is different from a lot of past studies on electronic monitoring in that it uses a survey design rather than an experimental research design. It is a mixed methods study that is primarily quantitative, but will use qualitative research methods to obtain different perspectives and more fully understand the phenomenon.

The study has 5 research questions and 15 hypotheses on how implementation of a hand hygiene compliance solution affects performance and employee satisfaction, which will provide information on whether the reported high performance gains persist to the long-term and whether there is a tradeoff associated with the high performance gains. The population for the study is not ideal, but convenient. Four companies will be used as sources of data on (for the population of) healthcare institutions that implemented a hand hygiene monitoring solution – Hill-Rom Inc., HyGreen Inc., Stanley Healthcare, and GOJO Industries. This convenience sampling is not a major issue. Data will also be collected from each healthcare institution in the sample and employees from each institution surveyed for their perspective on the effects of the compliance monitoring. Analysis techniques for testing hypotheses include: tests to compare means and proportions between two groups, ANOVA analyses, and regression analyses (quantitative) and constant comparative analysis (qualitative). Reliability and validity are considered throughout the paper.

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