Organizational Safety Vredenburgh

Organizational safety:

Which management practices are most effective

in reducing employee injury rates?

Alison G. Vredenburgh*

Vredenburgh and Associates, Inc., PMB 353, 2588 El Camino Real, Suite F, Carlsbad, CA 92008, USA

Received 6 December 2000; received in revised form 5 August 2001; accepted 19 November 2001

Abstract

Problem: While several management practices have been cited as important components of safety

programs, how much does each incrementally contribute to injury reduction? This study examined

the degree to which six management practices frequently included in safety programs (management

commitment, rewards, communication and feedback, selection, training, and participation)

contributed to a safe work environment for hospital employees. Method: Participants were solicited

via telephone to participate in a research study concerning hospital risk management. Sixty-two

hospitals provided data concerning management practices and employee injuries. Results: Overall,

the management practices reliably predicted injury rates. A factor analysis performed on the

management practices scale resulted in the development of six factor scales. A multiple regression

performed on these factor scales found that proactive practices reliably predicted injury rates.

Remedial measures acted as a suppressor variable. Discussion: While most of the participating

hospitals implemented reactive practices (fixing problems once they have occurred), what

differentiated the hospitals with low injury rates was that they also employed proactive measures

to prevent accidents. Impact on Industry: The most effective step that hospitals can take is in the

front-end hiring and training of new personnel. They should also ensure that the risk management

position has a management-level classification. This study also demonstrated that training in itself is

not adequate. D 2002 National Safety Council and Elsevier Science Ltd. All rights reserved.

Keywords: Safety culture; Risk management; Injury reduction; Accidents; Hazards

0022-4375/02/$ - see front matter D 2002 National Safety Council and Elsevier Science Ltd. All rights reserved.

PII: S0022 -4375 (02 )00016 -6

* Tel.: +1-760-434-4741; fax: +1-760-434-6029.

E-mail address: [email protected] (A.G. Vredenburgh).

www.elsevier.com/locate/jsr

Journal of Safety Research

33 (2002) 259–276

1. Introduction

On an average day, 17 US workers are killed and 16,000 are injured in work-related

accidents, resulting in a cost to industry of more than US$110 billion annually (Barr,

1998). This injury rate is increasing. Traditional safety efforts have focused on the

engineering aspects of safety; however, relatively few accidents (10%) are a consequence

of unsafe mechanical or physical conditions. While most on-the-job accidents and injuries

appear to result from employees’ unsafe acts, incidents typically are not caused by single

operator errors, but are end-events in a chain of interacting factors on several systems

levels (Wilpert, 1994). While many unsafe acts are committed, very few will penetrate an

organization’s defenses to result in accident or injury (Reason, 1994).

It is becoming increasingly apparent that it is restrictive to discuss failures of large-scale

technological systems solely in terms of the technological aspects. Individuals, their

organizations, groups, and cultures are all-important factors in the design, construction,

operation, and monitoring of technological systems. Until recently, this issue has been

described in the related literature in terms of ‘‘human error.’’ While human error does

contribute to accidents, the behavioral causes of failure are often found to be far more

subtle when incidents are analyzed as part of a technological system (Pidgeon, 1991).

Many expectations are built into the current US health and safety legislation that

specifies the responsibilities of managers and employees with regard to safe working

practices. These suppositions are more likely to be fulfilled if a positive cultural attitude

toward safety exists. The costs of failure to comply with these expectations are increasing.

As workers become more educated, they are more likely to expect safer working

conditions; a more safety and environmentally conscious public is increasingly willing

to express its disapproval of companies that are perceived to behave carelessly. This public

reproach was evident during the American consumer boycott of Exxon gasoline following

the Valdez oil spill (Turner, 1991).

Researchers have found that safety performance is affected by an organization’s

socially transmitted beliefs and attitudes toward safety (Ostrom, Wilhelmsen, & Kaplan,

1993). The concept of safety culture (Pidgeon, 1991) was developed as a result of the 1986

Chernobyl accident, which focused attention on the human and organizational elements

contributing to the unsafe operation of technological systems. Safety culture is an

organization’s norms, beliefs, roles, attitudes, and practices concerned with minimizing

exposure of employees to workplace hazards (Turner, 1991). The goal of a safety culture is

to develop a norm in which employees are aware of the risks in their workplace and are

continually on the lookout for hazards (Ostrom et al., 1993). A safety culture motivates

and recognizes safe behavior by focusing on the attitudes and behaviors of the employees.

It is a process—not a program; it takes time to develop and requires a collective effort to

implement its many features (Barr, 1998).

Changing a company’s culture is more difficult than issuing a new policy statement.

Traditional customs and practices constrain new thinking (Kletz, 1985). While many

authors on safety management attach great importance to a formal statement of a company’s

safety policy, Kletz (1993) does not believe such a statement will impact a company’s

accident record. He believes that the culture or ‘‘common law’’ of a company is more

influential, conveyed by such actions as a phone call from the head office immediately after

A.G. Vredenburgh / Journal of Safety Research 33 (2002) 259–276260

an incident, asking not if anyone was hurt, but when the plant would be back on line. In this

case, the cultural ‘‘message’’ is that production, not people or safety, is the priority.

Researchers have found a direct organizational culture–performance link. According to

Siehl and Martin (1990), a ‘‘strong’’ organizational culture is one where espoused values

are consistent with behavior and where employees share the same view of the firm.

Conversely, a weak culture results when people at all levels of the hierarchy fail to share

the values espoused by management. The challenge facing organizations is to discover

how to displace existing cultural patterns where they lack an appropriate concern with

safety, and to replace them with new, self-perpetuating elements, which show a greater

degree of care. While there are many potential external influences that make it difficult to

define a ‘‘strong’’ safety culture across settings, there are many features that safety cultures

from successful organizations have in common. In order to cultivate a strong safety

culture, several measures can be taken.

Zohar’s (1980) study of safety climate used a factor analysis to identify climate

dimensions that could discriminate among factories based on their safety climate levels. A

few practitioners and experts (Cohen & Cleveland, 1983; Pidgeon, 1991; Turner, 1991)

described factors they believe to be prevalent in the safety culture of organizations that

have low injury rates. The variables described below are a compilation of the factors found

across several of these reports.

Six management practices have been consistently discussed in reports concerning

safety culture: (a) rewards, (b) training, (c) hiring, (d) communication/feedback, (e)

participation, and (f) management support. The objective of the current study was to

determine the extent to which these six variables predict employee injury rates.

2. Six management practices studied

2.1. Worker participation

Worker participation (or employee involvement) is a behavioral-oriented technique that

involves individuals or groups in the upward communication flow and decision-making

process within the organization. The amount of participation can range from no

participation, where the supervisor makes all decisions, to full participation, where

everyone connected with, or affected by, the decision is involved.

Employees close to the work are recognized as often being the best qualified to make

suggestions about improvements. Participative managers will solicit opinions from other

individuals or groups before making final decisions, especially for those that affect the

employees. The empowerment of employees is both a management style and attitude.

Empowering workers provides them with authority, responsibility, and accountability for

required decisions and ensures that both employees and management are involved in setting

goals and objectives. It induces employees to do their best work as individuals and as a team,

while relieving the manager to plan, monitor, lead, and mentor (Cohen & Cleveland, 1983).

In the United States, employee involvement has tended to focus on greater personal

influence on the shop floor and on a greater role in the decision-making involving the

employees’ daily work experience (Cohen & Cleveland, 1983).

A.G. Vredenburgh / Journal of Safety Research 33 (2002) 259–276 261

Safety committees have become a standard feature of workplace safety programs;

however, committees themselves do not necessarily mean effective employee involve-

ment. Committees must be given real power to implement change. The members must be

in positions where they can have a positive impact on the committee’s work (such as

production and engineering supervisors), and must be well trained.

Participation has been found to be a key component in successful hospital injury

prevention programs. In a 1992 study done by the Department of Veterans Affairs Medical

Center (VAMC) in New Jersey, a program was implemented to reduce lost-time injury

cases. The intervention included the involvement of all levels of employees in every phase

of the safety program. This program dramatically reduced the lost-time injury cases within

1 year of implementation (Garrett & Perry, 1996).

2.2. Safety training

In order for employees to be active participants in a safety program, they must receive

occupational safety training. A well-designed and administered training program should

emphasize safe work practices and be derived from a true assessment of need. Training

should be followed with a program based on goal-setting and performance feedback

(Cohen & Jensen, 1984). Training program assessment should verify that the safe work

practices could be demonstrated to be effective and to endure beyond cessation of

performance feedback. According to Cohen and Jensen, there should be a redefinition

of group norms sustained through informal influences such as peer modeling of desired

behaviors, continued management support of the program, and a behavior sampling

procedure specifying performance-based criteria.

Safety training provides the means for making accidents more predictable. The basic

difference between safe employees and those who frequently get hurt is that safe employees

can recognize hazards and hazardous actions and understand the consequences. To improve

the quality of safety and health for all employees, organizations should institute a

systematic, comprehensive safety and health training program for new employees, provide

a mentor for these employees, and use a buddy system to help orient new employees in the

safety and health and quality systems. They should also institute a system of continual re-

education and retraining of employees in current safety and health issues (Roughton, 1993).

Several issues affect the perception of risk levels and should be understood when

training employees in occupational safety. People tend not to use the likelihood of injury in

their judgments of product safety; rather, the severity of injury plays the foremost role in

decisions to read warnings and act cautiously (Young, Brelsford, & Wogalter, 1990).

Vredenburgh and Cohen (1995) found that the level of perceived danger increased

compliance to warnings and instructions; therefore, it is critical that all employees are

trained to identify the hazards associated with their workplace.

2.3. Hiring practices

The development of a safety culture can be facilitated if recruitment criteria for new

personnel include the selection of people who are predisposed to displaying a safety-

conscious attitude in their work. If an organization fosters a safety-conscious image, the


recruitment task will be influenced because those with compatible attitudes and expect-

ations would be more likely to seek out this company, presumably in part due to a desire

for a safe work environment (Turner, 1991).

Eckhardt (1996) states that while interviewers cannot influence whether someone is an

inherent risk-taker, they can place such applicants in jobs with a corresponding level of

high-risk tasks. Recruiters can also select candidates with a lower propensity to take risks.

While it has been a long held belief, by different authorities, that many personal

characteristics such as gender, age, stature, and body weight are possible risk factors for

work-related injuries, none of these traits have been reasonably correlated with the

occurrence of injury-producing incidents or their severity. One’s medical history, medical

examination, or spine X-rays are sometimes able to reveal some clues of potential health

risks. However, medical advice or warning regarding a career choice might be disregarded

by an applicant who needs a job (Lin & Cohen, 1984b).

2.4. Reward system

People are motivated to behave in ways that lead to desired consequences; they will

modify their behavior to conform to a cultural norm if it is perceived that compliance will

lead to a desirable outcome. Culture is learned through a connection that is made between

behaviors and consequences. Thompson and Luthans (1990) state that since organizational

culture occurs in an environment where there are multiple reinforcements and reinforcing

agents, changing an organization involves identifying the various reinforcing agents in

order to determine their effects on the change process.

A correctly designed safety-incentive program reinforces the reporting of a hazard or an

unsafe act that leads to an injury while giving bonuses for fewer lost-time accidents. A

safety incentive program must be part of a campaign that runs parallel to safety education

and training. It must be directed at the prevention of accidents, not punishment after an

accident occurs (Peavey, 1995). Informational (feedback, self-recording), social (praise,

recognition), and tangible reinforcers (trading stamps, cash bonuses) have been used as

well as nonmonetary privileges (Komaki, Barwick, & Scott, 1978).

As with any policy, the effort to develop a strong safety culture is unlikely to be

effective if the organization is not reinforcing the desired behaviors (or is rewarding

inconsistent behaviors such as speed or production rates). A well-designed incentive

program offers recognition, which can help modify behavior. A key characteristic of a

successful incentive program is that it receives a high level of visibility within the

organization. Participants must be able to comprehend what the incentive program is

designed to accomplish and how their performance will be measured (Halloran, 1996).

Simply distributing prizes and money without pairing them with a clear, consistent set of

contingencies reduces the potential to achieve the desired outcome. It may even increase

the undesired behavior, more accidents (Swearington, 1996).

2.5. Management commitment

In one of the first investigations of safety climate, Zohar (1980) found that

management’s commitment to safety is a major factor affecting the success of an


organization’s safety programs. This commitment can manifest itself through job training

programs, management participation in safety committees, consideration of safety in job

design, and review of the pace of work. For example, people working for a supervisor

that never mentions safety perceive that safety is unimportant; as a result, they will not

place a strong emphasis on safety (Hofmann & Stetzer, 1996). The degree to which

management values safety is expressed in its style and level of assumable risk. These

two factors are the most influential components of culture; however, safety professionals

have very little influence over these variables. When discussions of safety are conducted

in a false or insincere rhetoric, the phony statements are readily seen for what they are

(Turner, 1991).

In five plants recognized by the National Safety Council for no lost workdays, all of the

plants required advance approval by safety personnel for any changes in the design of the

work facilities. In four of the plants, the plant safety director had direct contact with the

plant manager on a daily basis (Cohen & Cleveland, 1983). The motivation to perform a

job in a safe manner is a function of both the individual’s own concern with safety as well

as management’s expressed concern for safety. Safety concerns must result in an

observable activity on the part of management; they must be demonstrated in their

behavior as well as their words (Hofmann, Jacobs, & Landy, 1995).

In the 1992 Veteran’s Hospital (VAMC) study, the guiding force behind the initiative to

reduce the number of injury cases was management’s commitment, which began at the

very top management level, with the Medical Center Director. Without sincere support

from top hospital administrators, this project would not have achieved its level of success

(Garrett & Perry, 1996).

2.6. Communication and feedback

The role of feedback concerning employees’ performance is critical because behaviors

resulting in industrial accidents are not typically new occurrences. Their causes are deeply

rooted in past minor incidents, where damage was insignificant and workers and

bystanders were not injured (Kletz, 1993). Regular feedback on performance can be

communicated to employees through posted charts and a review of behavioral data in

safety meetings (Roughton, 1993).

The incubation model of disasters suggests that near-miss events will often differ from

actual incidents by the absence of the final trigger event and the intervention of chance.

Pidgeon (1991) states that organizations can interpret near-miss incidents as warning

signals. In some contexts, such as the aviation industry (Hall & Hecht, 1979), a high

premium is placed on the analysis and dissemination of incident data obtained on a ‘‘no-

fault’’ reporting basis. In the five National Safety Council award-winning plants, the

organizations had some form of employee hazard identification system in which they were

encouraged to report hazards to management (Cohen & Cleveland, 1983). In order to

encourage communication, it is important not to blame employees when accidents occur.

As managers have gained experience with the techniques used to improve quality, they

have learned the importance of improving the process of production. Many managers now

work to solve production problems upstream rather than inspecting for defects down-

stream (Roughton, 1993).


Consistent and forthright communication is an essential characteristic of any strong

organization. Good communication leads to trust, which is a fundamental element of

strength. In order for organizations to foster a climate where employees are alert to

hazards, they must have an appreciation of the employees’ and organizations’ tendency to

conceal and distort significant available information (Pidgeon, 1991). In order to influence

safety practices, feedback must be provided to the employees who are capable of using it.

It needs to be given to those working at the point in the process where their behavior can

effectively influence outcomes. People cannot behave in a safety-conscious manner unless

they have the authority to change their own actions to improve their work conditions. It is

illogical to ask employees to be careful if they do not have the power or discretion to avoid

hazards (Turner, 1991). Laws (1996, p. 26) writes, ‘‘motivation is no big deal, you can

motivate a baboon. But if you don’t back that motivation with tools, skills, training,

counseling, and leadership, then all you have is a highly frustrated, motivated ape that

cannot get the job done.’’

3. The hospital environment

In a study conducted by the National Institute for Occupational Safety and Health

(NIOSH), only 8% of the 3686 hospitals surveyed met all of NIOSH’s basic components

of an effective occupational safety and health program for hospital employees (Lin &

Cohen, 1984a). Healthcare workers are at great risk for injury; nationally, the total lost

workday injury and illness incidence rates for hospitals (4.1) are greater than those for

private industry (3.6). Furthermore, workers in home health care (5.0) and nursing care

(8.8) are at greater risk than construction workers (4.9; Cal/OSHA, 1997).

Healthcare employees have to cope with psychological stress resulting from shift

rotations and the frequent need to work overtime. Of the 27 occupations ranked as the

highest stress, 15 were occupations found in hospitals (Lin & Cohen, 1984a). Since

hospitals never shut down, and rarely slow down, numerous hazards develop due to

fatigue from long hours, stress, rotating shift work, and changes in policy. One shift may

create a hazard (such as leaving a cart blocking an emergency exit) that is overlooked by

subsequent shifts (Johnson, 1997).

Hospital employees must face the daily traumas of life and death as well as the constant

interaction with a diverse patient population. Many people may expect that the occupa-

tional safety and health services would be conveniently accessible to hospital personnel;

however, there tends to be a lack of focus in this area shown by hospital administration,

which has received many complaints and criticisms from the affected healthcare workers

(Werdegar, 1980). A possible explanation of this deficiency is that since medical facilities

are to provide treatment and improve health, special facilities for employee care may

appear redundant (Lin & Cohen, 1984a).

The proper focus of attention to improve a hospital’s quality of service, and employee

and patient safety is not on the personnel who participate in a flawed process, but the

processes that create the flaws. Hospitals that employ quality improvement methods have

been found to achieve new levels of efficiency, patient satisfaction, safety, clinical

effectiveness, and profitability (Berwick, Godfrey, & Roessner, 1990). However, due to


the health services’ traditional orientation toward sick care rather than health maintenance

and hazard prevention and because of the concern for the cost of safety and health

management, the implementation of an employee safety and health program has rarely

been considered a top priority by hospital administration. Hospital employees typically do

not participate in hazard management; thus, a great deal of resources are often required to

train employees in communication and problem-solving skills and in quality/measurement

techniques (NIOSH, 1983). Quality assessment often lacks the necessary evaluation tools.

It also is missing a general theory regarding the source of hazards in the complex processes

of health care. To the extent that quality measurement tools have been developed, they

tend to unveil the symptoms, not their underlying causes (Berwick et al., 1990).

Several common types of injuries to hospital employees have been recognized and

identified: strains and sprains, needle punctures, communicable diseases, toxic and

hazardous substances, dermatitis (caused by handling cleansers, medicines, antiseptics,

and solvents), and thermal burns (primarily in food service, laundry, and sterilizing areas).

Back sprains and strains are the most common injuries to hospital workers; 46% of nurses,

aides, orderlies, and attendants report back injuries, as opposed to 26% in private industry

occupations (Cal/OSHA, 1997). These injury data must be collected and reported to the

Joint Commission on Accreditation of Healthcare Organizations (JCAHO) and the

Occupational Safety and Health Administration (OSHA).

The hospital environment was selected for the current study because injury data were

thought to be readily available to use as a criterion measure and because it represents a

growing and dynamic influence within the US service industries. It was also selected

because incidence rates among various sectors of health services are at least one-third

above the average service industry rates (NIOSH, 1983).

While few people would dispute the importance of workplace safety, a review of the

literature reveals a paucity of well-controlled studies demonstrating the efficacy of

workplace safety programs. While well-controlled studies are reported in simulated work

settings, in-house safety programs are notable for their lack of systematic assessment. The

accounts reported in trade journals are primarily anecdotal.

4. Method

4.1. Participants

Participants were risk managers from 62 hospitals located in several states in the United

States. They were recruited from professional organizations for hospital risk managers as

well as direct mail and phone solicitation to hospitals. Participation was voluntary. Public,

private, and investor-owned hospitals were solicited. All participating hospitals were

medical/surgical; none were neuropsychiatric or nursing homes. Most respondents were

managers (55 or 89%); seven (11%) were not in management.

Rousseau (1990) states that research concerning culture frequently focuses upon key

informants who are identified as those possessing special or more complete knowledge

than others in the organization. Hospital risk managers were presumed to have more

complete information about their institutions’ risk management programs, and thus, were


solicited as participants. While the 62 participants performed the risk management

function, 26 had the title of risk manager, 3 were in human resources, 10 were in

administration, 8 were called safety officers, 5 were nurses, and 8 did not fit into the above

categories. Seventy-four percent of the respondents had worked at their participating

hospital for 5 or more years.

Respondents were asked if their facility had undergone a change in ownership during

the 3-year period of study. Of the 62 respondents, 57 (92%) reported no change, 3 (5%)

reported a change in owner with no impact on the responses to survey items and 2 (3%)

reported a change that may have impacted survey items.

Participating hospitals ranged in size from 55 to 6000 employees (full-time equivalent),

with a median size of 390 employees. Most of the hospitals, 40 (65%) were public, 21

were private (34%), and one provided no information.

4.2. Level of analysis

Climate researchers have often debated issues concerning the level of analysis and

aggregation procedures. Climate surveys, which collect data at the individual level,

provide limited information about the actual activities of an organization. Culture research

calls for in-depth case studies that may require multiple organizations as the units of

analysis to compare performance. In order to change an organization, data concerning an

organization, as well as how that organization compares to others are required (Reichers &

Schneider, 1990). The goal of the present study is to determine what factors, across

organizations, predict injury rates; thus, the unit of study is at the organizational level.

When studying organizational culture, the focal unit (whole organization, department, or

work group) must be specified. When the level of analysis is not identified, there is a risk

of ambiguity that Rousseau (1990) feels plagued much of the early climate research. In the

current study, participating risk managers were informed, ‘‘Please keep your responses

general, to your hospital as a whole.’’

4.3. Instruments

4.3.1. Organizational factors data

Perception surveys have been used to effectively identify improvements in and

deterioration of safety system elements (Ostrom et al., 1993). Participating hospitals were

evaluated for the six predictor variables via an instrument designed for this study. Items

were adapted from Ostrom and his colleagues’ study and pilot-tested with risk managers

from three hospitals. Items that were unclear to these risk managers were reworded until

there was agreement in the interpretation of the questions.

Participants were given the instructions, ‘‘Considering only the hospital where you

work, please respond to the following questions by circling the appropriate number

following each question.’’ Extent scales 1 = no extent to 5 = a great extent followed each

item. Three items were developed to assess each of the six management practices. A

sample item used to assess training was ‘‘To what extent do you believe that the safety

training provided to personnel is adequate to enable them to assess hazards in their

work areas?’’ A sample item to evaluate level of participation was ‘‘To what extent do


safety committees or teams have the power to implement change?’’ See Table 1 for all

items.

Additional items solicited the frequency of the safety meetings, the frequency that top

administrators met with safety committee members, and the type of rewards used. There

was also an item to determine whether the hospital had changed ownership (such as

Table 1

Management practices survey items

Management practice Survey item

Rewards To what extent do you think that work-related injuries are due to a

lack of rewards for reporting hazards?

To what extent are employees rewarded for reporting a safety hazard

(e.g., thanked, have employee recognized in hospital newsletter,

receive cash or other awards)?

To what extent are employees punished for reporting a safety hazard

(e.g., they are ignored or told to keep it quiet)?*

Training To what extent do you believe that the safety training provided to personnel

is adequate to enable them to assess hazards in their work areas?

To what extent does the training program perform assessments following

instruction to verify that the safe work practices are being carried out in

the work areas?

To what extent do you think that work-related injuries are due to a lack

of training?*

Management commitment To what extent do you think that work-related injuries are due to a

lack of management support in correcting employee safety hazards?

To what extent do supervisors in your hospital enforce safe

working procedures?

To what extent do the administrators of your hospital demonstrate

that safety is important to them (e.g., take immediate action to

eliminate safety hazards, list safety issues high on the agenda of

management meetings)?

Communication

and feedback

To what extent does your hospital use a hazard reporting system

where employees can communicate hazard information before

incidents occur?

To what extent are near-miss incidents analyzed as warning signals

that must be studied and corrected?


of feedback to employees about their unsafe behavior?*

Selection To what extent are employees hired based on a good safety record in

their previous positions?

To what extent does management seek information about job candidates’

prior safety performance in selecting or transferring employees?


of hiring people who are safety conscious?*

Participation To what extent do employees participate in identifying safety problems?

To what extent does management solicit opinions from employees before

making final decisions?

To what extent do safety committees or teams have the power to

implement change?

* Reverse-scored.


from public to private). If they responded yes, they were then asked if their responses

would be different if they pertained to the hospital under previous ownership. There was

little demographic data requested to protect anonymity of the hospitals. Internal

consistency reliability of the overall management practices scale was calculated at .86

(coefficient a).

4.3.2. Hospital injury data

Participating hospitals provided data for the criterion variable via an instrument

designed specifically for this study. This form provided respondents with a space to

document the number of injuries for 15 injury categories. Injury categories were

generated based on injury data (OSHA 200 forms) provided as examples from two

facilities. Participants were asked to ‘‘Please fill in the number of injuries of each type

that occurred to hospital employees during the 3 previous years, in the shaded area

below.’’ These categories included ‘‘sprains, strains, and fractures,’’ ‘‘communicable or

infectious diseases,’’ ‘‘needle punctures,’’ and ‘‘fractured/crushed fingers or hands.’’

Participants were asked to indicate the number of injuries (frequency) of each type that

occurred to hospital employees during the 3-year period (1994–1996). There was also a

statement in the instructions, ‘‘If you cannot easily provide the information in the format

as it is requested on this form, you may send copies of your hospital’s OSHA 200 forms

covering this 3-year period. Remember to remove your hospital’s name from the top of

the forms to insure confidentiality.’’ If the data was sent on the OSHA 200 forms, the

researcher tallied and converted the data onto the survey form and destroyed the OSHA

forms.

In order to maintain confidentiality, few demographic questions were included. The

three demographic items requested the type of facility (public, private, investor-owned),

the hospital’s full-time equivalent (FTE) employment (to control for facility size differ-

ences), and whether this included per diem and contractor employees.

4.3.3. Severity data

In order to assign weights to calculate the composite criterion, severity data were

collected. Since severity is very difficult to measure from existing data due to a variety of

regulatory and organizational constraints, perceived severity ratings by an ‘‘expert’’ panel

were used. The instrument (with the same 15 injury categories) was pilot-tested with two

physicians. Some changes were then made to the instructions to increase clarity. The 14

experts who completed this questionnaire were all physicians who work in hospitals as

part of their job. Because physicians are used as experts to testify in court as to the extent

of damages resulting from an injury, they were selected to rank the injuries concerning

their severity.

Participants were instructed, ‘‘For my doctoral dissertation, I need to have rankings

assigned to each of the risk factors listed below in order that I may assign weights for the

statistical analysis. Considering your work in the hospital(s) where you practice, and based

on your experience, please rank the hazards from 1 (not severe) to 15 (extremely severe).

Please take into consideration such factors as days off work, permanent or long-term

inability to perform current job duties, medical expenses, and whether the hazard is life-

threatening (not probability of occurrence).’’


4.4. Procedure

Participants were solicited via telephone to participate in a research study concerning

hospital risk management. During this discussion, the experimenter explained the system

to protect anonymity. Research materials, a confidentiality agreement, and a pre-addressed

return envelope were mailed to volunteers. Responses were assigned random numbers;

thus, it was impossible to link data to its hospital.

Participants received follow-up calls or faxes to remind them to return the surveys.

Since the researcher did not know who responded, all original contacts were recontacted.

There was a statement on the written reminder that thanked them if they had already

returned the survey.

4.4.1. Response rate

Out of the 194 phone calls (only calls that reached the risk manager were counted), 125

agreed to participate (64%) and were mailed surveys. Of these 125 surveys, 74 were

returned (59%); however, only 62 had criteria information and were usable for the

regression analyses (50%).

5. Results

The central question addressed in this study concerned the degree to which six

management practices predicted hospital employee injury rates. To evaluate this issue,

several steps were required.

5.1. Expert rankings

In order to compare hospitals’ employee injury rates, it was necessary to determine both

the frequency and severity of the injuries. Severity data were collected as expert rankings,

which were converted into an interval scale and used to weight the frequency data. An

estimate of reliability of the responses by the 14 expert raters was .82. Two of the raters

were found to have contributed the most to the variance in the ratings. By removing both,

reliability increased to .87. The rankings of the remaining 12 raters were then converted

into an interval scale using Thurstone’s discriminate model.

5.2. Computing the criterion

There was a large range in the frequencies of the different injury types. Table 2 presents

the mean (adjusted for number of employees to control for hospital size) and relative

frequencies of the 15 injury types. The mean frequency is the annual average for each

injury type based on 3-year’s injury data. The first step in computing the criterion measure

was to weight the frequencies of each injury type with the severity factor developed from

the physicians’ expert rankings. The total number of (weighted) injuries per hospital

ranged from 19 to 1780 injuries, with an average of 262 injuries and a standard deviation

of 327. The total number of (weighted) injuries was divided by the number of full-time


employees for each hospital, resulting in the number of (weighted) injuries per employee

for each participating hospital. These values ranged from 0.03 to 1.12, with a mean of 0.43

(weighted) injuries per employee and a standard deviation of 0.22.

Several of the responding risk managers included a note with their injury data

indicating that their hospitals did not record illness data. Some respondents noted that

their hospitals recorded exposure to illnesses, while others reported that they recorded only

actual infections. As a result of the variability in the recording and reporting of exposure to

diseases/illnesses, the incident types, ‘‘communicable or infectious diseases’’ and ‘‘needle

punctures, blood exposure’’ were not used in the calculation of the criterion variable; thus,

only the 13 injury types were used (see Table 2 for the 15 injury categories). The final

criterion variable (one observation per hospital) ranged from 0.02 to 0.90 injuries per

employee, with a mean of 0.30 injuries and a standard deviation of 0.17.

5.3. Predicting injuries

The principal analysis was a linear multiple regression that assessed the predictive

capacity of management practices (subscales) Participation, Management support, Train-

ing, Hiring practices, Communication/feedback, and Rewards of hospital employee injury

rates. The multiple correlation was .41, R2=.165, and adjusted R2=.137. A significant F

statistic [F(2,59) = 5.84, P < .01] indicated a reliable linear relationship between the

management practice subscales and the criterion. The only management practice that

individually predicted injury rates was Hiring practices; the multiple correlation was .268,

R2=.07, and adjusted R2=.06. A reliable linear relationship [F(1,60) = 4.66, P < .05] was

established.

Table 2

Averages and relative frequencies of the injury types (across all hospitals)

Injury type Mean

frequency/year

Percent

of total

Mean frequency/year

(per 100 employees)

Sprains, strains, and fractures 40.25 34 6.00

Needle punctures, blood exposure 14.94 13 2.70

Contusions 14.87 13 2.10

Lacerations/cuts 10.35 9 1.90

Cumulative trauma disorder (CTD) 7.51 6 1.40

Other (allergic reactions,

unknown causes)

6.53 5 0.87

Disease exposure 5.35 5 0.69

Burns 3.23 3 0.61

Abrasions 3.78 3 0.60

Eye injuries 3.08 3 0.59

Skin disease 2.86 2 0.36

Finger injuries 2.20 2 0.34

Toxic exposure 2.01 1 0.34

Mental stress 0.86 1 0.19

Human or animal bites 0.50 0 0.13

Total 118.11 100 18.82


Another variable that was found to account for the differences in injury rates was

whether the person who performed the risk management function was classified as a

manager. The multiple correlation was .274, R2=.075, and the adjusted R2=.06. A

significant linear relationship [F(1,60) = 4.87, P < .05] was found.

The size of the hospital (number of employees) also predicted injury rates, with smaller

hospitals averaging more injuries per employee than the larger ones. The multiple

correlation was .380, R2=.145, and the adjusted R2=.130.

An exploratory factor analysis was conducted to verify that the management practices

items (predictors) loaded onto the expected subscales (the six management practices). Six

factors, with eigenvalues > 1, emerged in 10 iterations and were rotated using the Varimax

method. In total, the solutions accounted for 69% of the variance in the data: Factor 1

accounted for 29.7% of the variance; Factor 2 accounted for 10.8%; Factor 3 accounted for

8.0%; Factor 4 accounted for 7.2%; Factor 5 accounted for 6.6%; and Factor 6 accounted

for 6.1%. The items comprising the six factor scales did not correspond to the categories

derived from the practitioners’ reports (the management practices subscales). As a result of

the factor analysis, six factor scales were developed. Items were accepted for a factor scale

if they had a correlation with the factor (factor loading coefficient) greater than .70.

A multiple regression analysis was performed using the six factor scales identified in

the factor analysis to determine whether the factor scales predicted injury rates. The six

factor scales were entered (items equally weighted within the factor scales). Factors 1 and

2 made a significant contribution to the prediction of the variance in hospital employee

injury rates; the multiple correlation was .385, R2=.15, and adjusted R2=.12. A relationship

between Factors 1 and 2 and injury rates [F(2,59) = 5.14, P < .01] was found.

Table 3 provides the items comprising Factors 1 and 2; the items comprising Factor 1

(near-miss incidents are analyzed as warning signals, and supervisors enforce safe work

practices) were reactive. There was a safety violation that needed correction. Factor 2

contained proactive practices concerning the initial selection and training of employees.

Because Factor 1 was positively related to injury rates (i.e., the more hospitals performed

these desirable actions, the higher their employee injury rates), Factor 1 was acting as a

suppressor variable. Factor 1 controlled for a portion of the error variance of Factor 2,

Table 3

Best predictors of employee injury rates items comprising factors 1 and 2

Factor Correlations

with criterion

Critical questions

2 � .227 Predict injury rates

To what extent are employees hired based on a good safety record in their

previous positions?

To what extent does management seek information about job candidates’ prior

safety performance in selecting or transferring employees?

To what extent does the training program perform assessments following instruction

to verify that the safe work practices are being carried out in the work areas?

1 .192 Suppressor

To what extent are near-miss incidents analyzed as warning signals that must be

studied and corrected?

To what extent do supervisors in your hospital enforce safe working procedures?


which was negatively related to criterion (see Table 4 for the model summary). Thus,

while all of the participating hospitals, to some extent employed the reactive measures

comprising Factor 1, the primary difference in performance was that the participants with

lower injury rates also performed the proactive measures (Factor 2), while the hospitals

with high injury rates relied solely on ‘‘putting out fires’’ or ‘‘fixing’’ hazards after

problems had occurred.

Post-hoc tests were performed to determine whether there were possible alternate

explanations for the results. Since the type of hospital was categorical (public, private,

investor-owned), a nonparametric (independent sample Mann–Whitney) test was per-

formed; the type of hospital made no difference in the employee injury rates. A Mann–

Whitney test was also performed to determine if the job title of the person (risk manager,

safety officer, nurse, etc.) who performed the risk-management function had any impact on

injury rates. No difference was found.

6. Discussion

The most important finding of this study is that when organizations take proactive

measures to protect their employees, the company derives a financial benefit in reduced

lost time and workers compensation expenses. While previous research has typically

discussed management practices as general goals, the current study systematically

examined the specific elements of these practices that predict employee injury rates.

Consistent with Eckhardt (1996) and Turner (1991), the current study found that the

consideration of safety performance in the selection of employees was found to be a

significant predictor of injury rates. The results from this study may help establish a bona

fide occupational requirement for requesting these data (to avoid discrimination claims).

Furthermore, since safety behavior is often tied to quality of performance, it is probable

that an added benefit of this approach may be an improvement in productivity.

When reviewing the results of this study, one may be inclined to believe that the items

comprising Factor 1 actually caused the poor injury performance. However, with further

analysis, it becomes apparent that Factor 1 is acting as a suppressor variable. It would be

incorrect to infer that analyzing near miss incidents and enforcing safety practices

increased injury rates; in fact, these measures were employed by both high and low

performing hospitals. Therefore, it is not recommended that hospitals discontinue the

practices of Factor 1, if they are in effect; however, resources and focus should be

channeled toward the proactive measures of Factor 2.

The most effective step that hospitals can take is in the front-end hiring and training of

new personnel. They should also ensure that the risk management position has a

Table 4

Model summary

Factor R R2 Adjusted R2 S.E. R2 change b F

2 .227 .051 .036 0.165 .051 � .366 3.253

1 .385 .148 .120 0.158 .097 .341 5.143**

** P < .01.


management-level classification. This study also demonstrated that training in itself is not

adequate. Organizations must verify that the safe practices taught in the classes are being

implemented in the work areas. The results of this study can be used to determine which

factors to emphasize when performing an organizational development change in safety

culture. While it is not recommended that hospitals discontinue the reactive practices that

are in effect, resources and focus should be channeled toward more proactive measures.

Due to the high turnover of hospital personnel, selection of new employees is an ongoing

process; therefore, there is ample opportunity to consider safety records when selecting

new employees (Cal/OSHA, 1997).

A few hospital risk managers wrote that they were unable to obtain information about

job candidates’ prior injury records from other facilities. One reliable and valid approach

to solicit this type of information is through the behavioral based interview (Thornton &

Byham, 1982). To use this approach, the interviewer must be trained in the concepts and

techniques of behavioral interviews. An example of a question that may be used to assess

an employee’s safety record is ‘‘Please describe the types of accidents or near misses you

have had in your current or previous jobs.’’ Another example is ‘‘Please provide an

example of when you had to call a co-worker’s attention to a possible violation of a safety

regulation.’’ The applicant should describe the situation, the action he/she took, and the

result (Huck, personal communication, July 1998).

The injury rates at smaller hospitals were found to be higher than the larger ones. These

findings may result from these institutions having a less comprehensive safety program,

causing them to take a more reactive approach to injury prevention.

The data collected in this study to measure management practices reflected the

perceptions (and potential biases) of the risk managers. It is not possible to determine a

‘‘true’’ level of these characteristics. The number of responses used in the factor analysis

poses another limitation; the 12 responses that had missing criterion data were included in

this factor analysis to raise the sample size to 74. This number is somewhat lower than the

‘‘rule of thumb’’ of five per item (which would require 90 responses), due to the difficulty

in recruiting hospitals. However, according to Tabachnick and Fidell (1989, p. 603), ‘‘If

there are strong, reliable correlations and a few, distinct factors, a sample size of 50 may

even be adequate, as long as there are notably more cases than factors.’’ Distinct, strong

correlations were found in this study. This issue was further mitigated by using a high

factor-loading cutoff score (.70).

Since this was the first study of this type, a replication and extension of this work is

recommended. A recommended follow-up study is to select two comparable hospitals,

preferably within the same system, with the same (or similar) scores on the four

management practices comprising Factors 1 and 2. A preliminary assessment could be

conducted to establish a baseline measure of the performance of these practices. An

intervention can then be developed to maximize performance on the three proactive items

identified in this study as the best predictors of low injury rates (Factor 2). This

intervention would emphasize a front-end approach where new personnel are screened

and selected based on their past safety records. The approach could include behavior-based

assessment. In addition, after these new (and existing) personnel are trained in appropriate

safe work practices, an assessment will be performed to verify that the safe behaviors have

been implemented in the work areas.


While the level of reactive practices (Factor 1) should be measured, the practices should

not be changed. This intervention would be implemented in one of the facilities, with the

second acting as a comparison site. A program evaluation could be performed with 3-

year’s archival data as the baseline measure. Data could then be collected at 6-month

intervals following the intervention for a period of 3 years. Any preliminary differences

between the two facilities would serve as covariates. This proposed study would determine

whether taking a proactive approach positively influences safety culture to reduce

employee injury rates.

Acknowledgements

Many thanks to my dissertation chair, Richard Sorenson, who provided guidance

throughout this research. This study was funded in part by Error Analysis.

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Alison Vredenburgh holds a PhD in Industrial–Organizational Psychology and a MS in Systems Management.

She is currently a postdoctoral research fellow at the School of Medicine (Department of Anesthesiology) at the

University of California, San Diego, where she is researching medical error. She is President of Vredenburgh and

Associates Inc., a consulting firm specializing in human factors and safety. Her principle publications are in the

areas of human factors, ergonomics, and workplace management practices. She is active in the Human Factors

and Ergonomics Society, where she has held several leadership roles.


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