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Exploring Strategies for Reducing Hospital Errors

April 4, 2006

By McFadden, Kathleen L; Stock, Gregory N; Gowen, Charles R III; Cook, Patricia

EXECUTIVE SUMMARY

The purpose of this study is to explore current strategies for reducing errors at U.S. hospitals. Reports by the Institute of Medicine highlight concerns about the staggering number of medical errors that occur in the U.S. healthcare system. These reports have exerted considerable pressure on hospitals to establish programs that reduce errors and improve patient safety.

A previous research study identifies seven critical strategies for reducing hospital errors based on a case study of four Chicago- area hospitals. These strategies include (1) partnership with stakeholders, (2) reporting errors free of blame, (3) open discussion of errors, (4) cultural shift, (5) education and training, (6) statistical analysis of data, and (7) system redesign. This article reports the results of our nationwide survey of 525 hospitals. We examined the perceptions of healthcare quality directors about the importance of these seven patient safety strategies, the factors that act as barriers, the level of adoption of these strategies, and the benefits resulting from implementation of these strategies.

Our results indicate that a considerable gap exists between current hospital practices and the perceived importance of various approaches to improving patient safety. Results of our regression analysis reveal that internal organizational barriers are associated with a larger gap between perceived importance and actual implementation. Moreover, the regression analysis also reveals that smaller gaps are associated with better error outcomes such as reduction in the frequency and severity of errors. The findings provide specific directions for enhancing patient safety programs at hospitals in the future.

Hospital administrators are currently struggling with the challenges associated with reducing medical errors and improving patient safety. Two reports by the Institute of Medicine (IOM) have served as the catalyst for the heightened awareness of and the immediate need to take action on these issues (Kohn, Corrigan, and Donaldson 2000; IOM 2001). These reports highlight the extent of the problem of errors in healthcare, explore the costs of these errors, and recommend improvements in healthcare delivery. The first report, To Err Is Human, suggests that medical errors account for more than 98,000 deaths per year in U.S. hospitals and that 58 percent of these error-related deaths may have been preventable. It acknowledges that the necessary system improvements require a “concerted effort” on the part of many individuals, from patients to policymakers. These IOM reports, along with the adoption of patient- safety goals by the Joint Commission on Accreditation of Healthcare Organizations (JCAHO), have put considerable pressure on healthcare organizations to find ways to reduce medical errors.

A medical error is defined as “the failure of a planned action to be completed as intended (i.e., an error of execution) or the use of a wrong plan to achieve an aim (i.e., an error of planning).” Some medical errors could lead to an adverse event, which is defined as “an injury caused by medical management rather than the underlying condition of the patient.” An adverse event attributable to error is a “preventable adverse event” (Kohn, Corrigan, and Donaldson 2000, 28).

Hospitals across the country are developing strategies for reducing medical errors and adverse events. They are at various stages in the development and implementation of their programs and are seeking to identify best practices. McFadden, Towell, and Stock (2004) used a case study approach (interviewing directors of quality, performance improvement, and risk managers at four hospitals in the state of Illinois) and identified seven strategies critical to the success of reducing hospital errors.

These strategies appear to reduce the likelihood of medical errors or decrease the magnitude of the effects of medical errors.

Our study extends the research by McFadden, Towell, and Stock, collecting input from a nationwide sample of professionals who work directly in the area of quality or risk management at hospitals throughout the United States. The specific objectives of our research were as follows:

1. To examine the extent to which each of the seven strategies are viewed as important in reducing hospital errors

2. To explore the level of implementation of the seven strategies in U.S. hospitals

3. To study the extent to which various factors act as barriers to implementing error-reduction strategies at U.S. hospitals

4. To determine the extent to which benefits have been realized as a result of implementing error-reduction strategies at U.S. hospitals

Prior literature has considered various error-reduction strategies. However, such research typically has examined only a relatively small subset of approaches to dealing with medical errors. This article takes a more systemsoriented perspective to explore how these potential strategies may work together as a coherent approach to reducing errors. Moreover, much of the prior research has been based on small samples or case studies. In contrast, our study is based on data collected from a broad sample of U.S. hospitals, which should yield greater confidence in the validity of its findings.

STRATEGIES FOR REDUCING ERRORS

The literature on patient safety has identified several strategies for reducing errors. In addition, the Agency for Healthcare Research and Quality published an extensive review of practices that appear to reduce the likelihood of adverse events. McFadden, Towell, and Stock (2004) reviewed the literature and derived a list of seven critical strategies, which are summarized below. The common theme that ties these strategies together is an emphasis on the process over the individual.

The first strategy critical to enhancing patient safety is to create a partnership with all stakeholders (Vanderveen 1991; Kumar and Subramanian 1998; Doolan and Bates 2002; Klein, Motwani, and Cole 1998). Stakeholders in a hospital include doctors, nurses, administrators, trustees, and patients. Working collaboratively in organizations to create ideas and test improvements tends to generate effective solutions (Kumar and Subramanian 1998). Creating a partnership with patients and families has also proven successful in improving healthcare processes (Bushell and Shelest 2002). It is important to understand the needs and perspectives of all constituents and to gain the support and commitment of top-level management in this process. Patient safety is a “team sport” that can only be achieved and sustained when all key stakeholders participate and contribute (Hudson 2004).

The second strategy is to develop an effective system for reporting errors without placing blame (Leape 1994; Uribe et al. 2002). Without a systematic method for identifying errors, patient safety is generally doomed to failure. An effective reporting system should be confidential, encourage reporting of errors, be impartial, and ensure no retribution for those reporting. A key factor to increasing the reporting of errors has been to establish trust within the organization (Firth-Cozens 2004). It is also important for error-reporting systems to go beyond the typical medical model of assigning blame when an error is reported and to offer incentives for reporting. A number of studies have examined the role of error reporting systems (see Doolan and Bates 2002; Chiang 2001; Walshe, Bennett, and Ingram 1995; Greene 1999), all of which suggest that the focus should be on the overall process rather than on the person reporting the error (Leape 1994).

The third strategy is to foster open discussions of errors (Klein, Motwani, and Cole 1998; Vanderveen 1991). For example, quality circles, a staple in manufacturing quality management, have been effective in the areas of quality improvement in a number of medical areas (Mullins and Schmele 1993). Small-group participants take part in a variety of exercises that identify risks, define goals, and measure progress. The intent is to foster an environment where individuals feel comfortable with discussing errors and where information and knowledge are shared freely. One study of 29 small rural hospitals in the western United States reports that 87 percent of the hospital staff felt comfortable or somewhat comfortable discussing the topic of medical errors (Cook et al. 2004).

The fourth strategy involves a cultural shift within an organization (Klein, Motwani, and Cole 1998; Ruchlin, Dubbs, and Callahan 2004). A culture is a set of beliefs and values shared by members of the organization. Creating a safety culture in healthcare involves making patient safety the number one priority within the hospital and having the commitment as well as the ability to address patient safety issues. Rather than apply the traditional approach of “naming, shaming, and blaming” when errors occur, a safety culture encourages and supports shared reporting of errors openly in a nonpunitive, positive environment. This means that the culture supports the idea that anyone can make mistakes. This strategy depends on shared values and nor\ms of behavior articulated by top management and translated into effective work practices (Gaba et al. 2003). The impact of culture on organizational performance is well documented in the literature (Johnson 2004).

The fifth strategy is to provide staff with education and training in error-reduction techniques (Becher and Chassin 2001; Huq and Martin 2000). Continuing medical education and training programs involve interventional risk management, which is an approach that can not only promote patient safety but also reduce malpractice lawsuits. Interdisciplinary training on patient safety has proven effective in strengthening healthcare teams and reducing errors (Cook et al. 2004).

The sixth strategy is to conduct statistical analysis on collected data on errors (Becher and Chassin 2001; Walshe, Bennett, and Ingram 1995). Simply collecting data is not sufficient. Quantitative techniques must be used to systematically analyze the data and understand the sources of medical errors (Plsek 1995; Klein, Motwani, and Cole 1998; Ruchlin, Dubbs, and Callahan 1998; Bedard and Johnson 1984). A common practice in hospitals today is training employees in the use of control chart analysis. However, as more comprehensive data are collected about errors, more sophisticated statistical modeling techniques can be employed to analyze more complex relationships and interactions that occur among variables that may be related to medical errors. This is important because research indicates that most errors stem from the interaction of several variables rather than from one underlying cause (Reason 1990; Chassin and Becher 2002).

The seventh strategy is to redesign the system of the process itself. System redesign refers to the implementation of changes in processes within a hospital and can result in improvements in overall quality of care (Leape 1994; Chiang 2001; Newman 1997; Bard 1994). The intent of this strategy is to reconstruct the system so that it is difficult or impossible to make a mistake. However, if a mistake does occur, employees are trained to correct it at the source.

BARRIERS TO ADOPTING ERROR-REDUCTION STRATEGIES

Prior research has also identified a number of factors that act as barriers to the implementation of error-reduction techniques. These barriers tend to fall into two major categories-internal and external. A partial list of internal barriers-those that originate within the hospital and are therefore under the control of individuals (administrators, medical staff, and other stakeholders) within the organization-may include a lack of support from top- level management, a lack of knowledge or understanding of errors, or a lack of resources such as staffing or money (Becher and Chassin 2001; Chiang 2001; Leape 1994; Uribe et al. 2002).

Other barriers to error-reduction strategies have origins that are external to the hospital. Probably chief among these external barriers is the threat of malpractice suits. Malpractice suits can affect both physicians and nurses, so they can represent significant deterrents to reporting of errors (Davis et al. 2002; Chiang 2001; Liang 1999; Becher and Chassin 2001; Fiesta 1998). In addition, cost pressures resulting from managed care have in some cases reduced the level of resources available for hospitals to devote to errors (Kovner and Gergen 1998). Media coverage of errors may also be considered an external barrier to implementation (Coffin 2002; Ceniceros 2002).

METHODOLOGY

This study employed a survey methodology to collect data on perceptions regarding the seven main strategies for reducing hospital errors. We used the directory of hospitals in the United States contained on the web site Hospitallink.com to obtain a list of hospitals to survey. This web site contains a fairly comprehensive list, including approximately 6,000 U. S. hospitals. From various links on the web site, we were able to obtain the addresses and telephone numbers for most of the hospitals. Items in the questionnaire were based on the relevant literature. The hospital questionnaire was pretested in a pilot survey sent to several quality directors in the Chicagoland area. Telephone interviews were also initially conducted to improve the clarity of the survey and reduce any ambiguity of the questions. Input from all these groups was incorporated into the final survey design.

We sent surveys via e-mail to a random sample of 930 hospitals. We stratified the sample based on geographic region to increase the generalizability of the findings. All 50 states were represented among the respondents; a breakdown of hospital respondents by region can be found in Figure 1. Typically, the title of those completing the survey was director of quality, director of performance improvement, director of safety, or risk manager. By contacting the hospitals by telephone first, we were able to ensure that the survey was e-mailed to the appropriate person.

FIGURE 1

Distribution of Respondent Hospitals by Region

Out of a total of 930 questionnaires e-mailed, 525 completed questionnaires were received, yielding a response rate of 56 percent. The average size of the hospitals responding was 155 beds. The number of physicians employed at these hospitals averaged 193, and on average the hospitals dedicated three full-time equivalent (FTE) employees to work on quality or risk management. In addition, 72 hospitals reported they were teaching hospitals. We asked respondents to provide information about both the perceived importance and level of implementation of the seven error-reduction strategies described earlier. Respondents also rated the levels of barriers to implementation as well as positive outcomes associated with these error-reduction strategies. The use of self-reported measures has been used and validated by previous researchers. For instance, Ward, Leong, and Boyer (1996) report that organizations are typically reluctant to share performance data because of confidentiality issues. Nonetheless, these researcher found a high correlation between objective data and perceptive performance measures. We used Harman’s one-factor test to check whether common method bias was present (Podsakoff and Organ 1986). Multiple factors were extracted, and the first factor did not account for a majority of the variance, suggesting that common method bias is not a significant influence on the results.

RESULTS

Descriptive Statistics

Table 1 provides the means and standard deviations for the perceived importance and implementation of the seven error- reduction strategies. Given that a score of 3 equates to medium importance, all strategies were viewed as highly important or important in reducing hospital errors (overall mean = 4.46). However, respondents reported only a moderate level of implementation of these strategies at their hospital (overall mean = 3.49). Respondents indicated the top three most important strategies were ( 1 ) reporting errors without blame, (2) developing a partnership with stakeholders, and (3) cultural shift. The three strategies with the highest implementation scores were ( 1 ) reporting errors without blame, (2) developing a partnership with stakeholders, and (3) education and training. The three strategies with the largest gaps between what respondents viewed as important and what strategies were actually implemented were (1) cultural shift, (2) system redesign, and (3) developing a partnership with stakeholders.

From the observed difference in the importance and the actual implementation of these strategies, we can infer that barriers to implementation may exist. Table 1 also provides descriptive statistics related to the extent to which the respondents viewed barriers to implementation of error-reduction systems. The most highly rated barrier was lack of resources (e.g., staffing, money), but it was only a “moderate” barrier to implementation (mean = 3.36).

Although the literature has identified several strategies for reducing errors, little evidence has been presented on the effectiveness of these strategies. Therefore, we wanted to determine to what extent the hospitals in the survey perceived benefits from implementing error-reduction strategies. Our findings indicate that the hospitals reported a moderate level of heightened awareness of errors, increased understanding of errors, improved quality, enhanced customer satisfaction, and reduced impact and frequency of errors. Mean and standard deviations of these outcomes are listed in Table 1.

Regression Analysis

These descriptive statistics present a summary of error- reduction strategies, barriers, and outcomes in U.S. hospitals. However, descriptive statistics do not show how these factors may be related. As we noted, the substantial gap between the perceived importance and actual implementation of errorreduction strategies suggests that barriers to implementation may be present in these hospitals. Our discussion also suggests that a smaller gap between importance and implementation may lead to better error-reduction outcomes. We now present results of additional analysis that investigates these proposed relationships.

We used principal components analysis (PCA) to reduce the large number of questionnaire items to a manageable number to be used in the regression analysis. (Details of the PCA are not reported here but are available from the authors upon request.) The results of the PCA showed that the questionnaire items actually represented a smaller set of underlying constructs. In particular, the PCA showed that the importance of the individual error-reduction strategies represented a single underlying factor; similarly, the implementation of the individual error-reduction strategies also represented a single factor. Therefore, we constructed a single overall variable representing the gap (referred to as GAP in the regression analysis) between perceived importance and actual implementation by subtracting the averageimplementation score from the average importance score for each hospital. In addition, the barriers to implementation loaded on three different factors. One of these factors represented barriers arising from sources external to the hospital (BARREXT), while the other two factors were associated with barriers arising from internal sources (BARRINT1 and BARRINT2).

TABLE 1

Questionnaire Variables

In addition, we also considered that quality managers in these hospitals likely have already been implementing more traditional quality management techniques such as benchmarking, quality teams, customer service evaluations, and statistical quality control. The PCA showed that these four techniques together represented a single quality management factor (QUAL_MGT). Finally, the PCA also showed that the set of error-reduction outcome items represented two constructs. The first factor could be interpreted as operational outcomes such as reduction in error frequency, cost savings, and reduction in error severity (OUT_OPER). The second factor may be interpreted as knowledge-related outcomes and include increased knowledge of errors and increased awareness of errors (OUT_KNOW). We also were interested in finding out whether certain hospital characteristics were related to error reduction; therefore, we also included the number of doctors (DOCS), the number of beds (BEDS), the number of full-time equivalent employees involved in error- reduction efforts (FTE), and the teaching status of the hospital (TEACH). Table 2 lists the variables used in the regression analysis and the individual questionnaire items comprising each variable.

The regression analysis results are available online at www.ache.org/pubs/jhmsub.cfm. Three regression models were estimated. In the first model, the gap between error-reduction importance and implementation (GAP) is the dependent variable. The results show that higher levels of the two internal barriers (BARRINT1 and BARRINT2) are associated with a larger gap, which is what we would expect. However, the external barrier variable is not statistically significant, which is surprising. Also, greater use of traditional quality management approaches (QUAL_MGT) is associated with a smaller gap, as is a greater number of FTEs involved in error- reduction efforts. Teaching hospitals (TEACH) are also associated with a smaller gap. What is somewhat surprising is that a higher number of doctors (DOCS) are associated with a larger gap. In the second and third regression models, error-reduction outcomes (OUT_OPER and OUT_KNOW) are the dependent variables. A larger gap between importance and implementation (GAP) is associated with lower levels of both operational and knowledge-related outcomes (OUT_OPER and OUT_KNOW). Also, greater use of traditional quality management techniques is associated with better outcomes in both models. Finally, a higher number of doctors (DOCS) are associated with better knowledge-related outcomes.

DISCUSSION

Interest and concerns in the area of patient safety and medical errors have accelerated in the last decade. Despite the challenges, our study indicates that U.S. hospitals are currently making excellent progress toward implementing strategies that enhance patient safety and reduce medical errors. On average, quality directors report at least a moderate level of implementation of all seven error-reduction strategies at their hospital. However, our results also reveal that a considerable gap exists between current hospital practices and the perceived importance of the various approaches. This indicates that there is room for improvement. Moreover, the results also show that reducing this gap will lead to better error-reduction outcomes.

TABLE 2

Regression Variable Descriptions

TABLE 3

Gap and Priority Scores of Importance Versus Implementation of Error-Reduction Strategies

While this study found the most popular technique for reducing errors is to develop reporting systems free of blame, fewer hospitals are statistically analyzing the data collected through reporting or not redesigning their systems based on the data. Our research indicates that we also have a way to go until a culture of safety is the norm in U.S. hospitals. We therefore wonder which of the seven strategies should receive the highest priority to target for healthcare reform. Consistent with the works of Meier and colleagues (1999) and Meier, Williams, and Humphreys (2000), we identified the highest priority strategies by considering both the gap scores and the importance scores, where strategies with both high importance and large gaps would receive the highest priority.

First, the raw mean scores of importance and implementation were multiplied by 20 to obtain a transformed score ranging from O to 100. Then a transformed gap score was calculated by subtracting the transformed implementation from the transformed importance. Finally, the priority score was calculated by averaging the transformed gap score and the transformed importance score. The results of this analysis are found in Table 3, which shows the order hospitals should use to prioritize the seven error-reduction strategies for future healthcare improvements. Hospitals should make creating a cultural shift toward patient safety a top priority. The second highest priority should involve developing a partnership with all stakeholders, followed by creating a reporting system free of blame.

Although developing priorities for system improvement is important, this study also highlights the need to focus on a comprehensive systems approach to safety. The systems approach to safety involves creating a safety culture with collaboration from all stakeholders of the hospital. The new culture should be one in which everyone feels comfortable and safe to discuss and learn from errors. An effective reporting system without blame should be put in place to discover sources of errors. The data obtained from both the reporting and discussing of errors should then be analyzed using appropriate statistical methodologies. Education and training should be implemented based on the findings of the data analysis. Finally, system redesign of processes is essential to effective error reduction.

Our research also shows that hospital managers should work to reduce internal barriers in their organizations, as doing so leads to a reduction in the gap between importance and implementation of error-reduction strategies. A lack of resources appears to be the primary barrier to implementation of effective strategies, followed by a lack of knowledge and understanding about errors. We suggest future research into how to bring about these sorts of organizational changes.

These findings provide insight into a very important issue of national and international importance. From a practical perspective, the results can be used as a guide to aid hospital administrators in designing more effective error-reduction systems. JCAHO has placed a strong emphasis on patient safety. Hospital accreditation has been increasingly tied to intervention and prevention of hospital errors. It is imperative that hospitals develop effective solutions to reduce medical errors to strengthen the quality of patient care nationwide.

PRACTITIONER APPLICATION

Patricia Cook, FACHE, director, Corporate Compliance and Quality, St. Anthony’s Medical Center, St. Louis, Missouri

Quality, risk, and compliance managers struggle with the question of reducing errors and even the more basic question of what constitutes an error. Much has been written since the Institute of Medicine’s publications in 2000 and 2001 about areas of highest risk, solutions to those concerns, and the bigger question of how to create a culture of safety within the hospital. The authors report a gap between recommendation and reality that is very real. The good news for healthcare is that the gap is being addressed daily in hospitals across the country through the formation of active and aggressive patient safety committees and development of performance improvement programs at the staff and unit levels.

Patient safety initiatives, such as The Leapfrog Group, the Institute for Healthcare Improvement’s 100k Lives campaign, and state and federal quality programs, have allowed facilities to focus on processes and systems that improve care and reduce both risk and errors. Many of these initiatives have also fostered partnership within facilities, putting together staff who would not have worked previously on issues and creating real and effective system redesign. As a result, we see improved education and training opportunities for staff.

The authors propose that one of the external barriers to error- reduction strategies is the threat of malpractice. That is not consistent with my experience. Rather, I find that employees are reporting errors that may result in a malpractice suit and are seeking information and assistance from risk management in how to proceed with the patient, family, and physician in resolving the issue in a timely, just, and fair manner. There is concern, however, about the initiatives that are calling for reporting of errors through a public data source. A report that aggregates errors by type of hospital may result in an increase in suits filed based on public information and may internally cause a decrease in reporting.

The use of benchmark data available from recognized external sources is helpful as well as hospitals collecting and analyzing data internally and, more importantly, sharing that data with senior leadership and board members. Such sharing will position hospitals to deal more effectively with allocation of resources in future budgets. Although there is no one-size-fits-all approach to bringing about change in an organization, this research assures hospitals that we are on the right road to transforming ourselves into quality organizations with actively functioning patient safety progra\ms that foster partnership, safe systems, and open dialog.

References

Bard, M. R. 1994. “Reinventing Health Care Delivery.” Hospital & Health Services Administration 39 (3): 397-402.

Becher, E. C., and M. R. Chassin. 2001. “Improving Quality, Minimizing Error: Making it Happen.” Health Affairs 20 (3): 68-81.

Bedard, J. C., and A. C. Johnson. 1984. “The Organizational Effectiveness Paradigm in Health Care Management.” Health Care Management Review 9 (4): 67-75.

Bushell, S., and B. Shelest. 2002. “Discovering Lean Thinking at Progressive Healthcare.” Journal for Quality & Participation 25 (2): 20-25.

Ceniceros, R. 2002. “Reporting Errors Poses Risks.” Business Insurance 36 (41): 2-27.

Chassin, M. R., and E. C. Becher. 2002. “The Wrong Patient.” Annals of Internal Medicine 136 (11): 826-33.

Chiang, M. 2001. “Promoting Patient Safety: Creating a Workable Reporting System.” Yale Journal on Regulation 18 (2): 383-408.

Coffin, B. 2002. “Seeking a Cure for Medical Errors Liability.” Risk Management 49 (10): 8-9.

Cook, A. F., H. Hos, K. Guttmannova, and J. C. Joyner. 2004. “An Error by Any Other Name.” American Journal of Nursing 104 (6): 32- 43.

Davis, P., R. Lay-Yee, J. Fitzjohn, P. Hider, R. Briant, and S. Schug. 2002. “Compensation for Medical Injury in New Zealand: Does “No Fault” Increase the Level of Claims Making and Reduce Social and Clinical Selectivity?” Journal of Health Politics, Policy, and Law 27 (5): 833-54.

Doolan, D. E, and D. W. Bates. 2002. “Computerized Physician Order Entry Systems: Mandates and Incentives.” Health Affairs 21 (4): 180-88.

Fiesta, J. 1998. “Target High-Risk Areas for Medication Errors.” Nursing Management 29 (12): 12-13.

Firth-Cozens, J. 2004. “Organizational Trust: The Keystone to Patient Safety.” Quality and Safety in Health Care (13): 56-61.

Gaba, D. M., S. J. Singer, A. D. Sinaiko, J. D. Bowen, and A. P. Ciavarelli. 2003. “Differences in Safety Climate Between Hospital Personnel and Naval Aviators.” Human Factors 45 (2): 173-85.

Greene, J. 1999. “From Whodunit to What Happened.” Hospitals and Health Networks (April): 50-54.

Hudson, M. A. 2004. Practitioner Application for “Keeping Patients Safe: An Analysis of Organizational Culture and Caregiver Training” by K. Johnson. Journal of Healthcare Management 49 (3): 179.

Huq, Z., and T. N. Martin. 2000. “Workforce Cultural Factors in TQM/CQI Implementation in Hospitals.” Health Care Management Review 25 (3): 80-93.

Institute of Medicine. 2001. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academies Press.

Johnson, K. 2004. “Keeping Patients Safe: An Analysis of Organizational Culture and Caregiver Training.” Journal of Healthcare Management 49 (3): 191-79.

Klein, D., J. Motwani, and B. Cole. 1998. “Quality Improvement Efforts at St. Mary’s Hospital: A Case Study.” Managing Service Quality 8 (4): 235-40.

Kohn, L. T., J. M. Corrigan, and M. S. Donaldson (eds.). 2000. To Err Is Human: Building a Safer Health System. Washington, DC: National Academies Press.

Kovner, C., and P. J. Gergen. 1998. “Nurse Staffing Levels and Adverse Events Following Surgery in U.S. Hospitals.” Image: Journal of Nursing Scholarship 30 (4): 315-21.

Kumar, K., and R. Subramanian. 1998. “Meeting the Expectations of Key Stakeholders: Stakeholder Management in the Health Care Industry.” SAM Advanced Management Journal 63 (2): 31-39.

Leape, L. L. 1994. “Error in Medicine.” JAMA 272: 1851-57.

Liang, B. A. 1999. “Error in Medicine: Legal Impediments to U.S. Reform.” Journal of Health Politics, Policy, and Law 24 (1): 27-58.

McFadden, K. L., E. R. Towell, and G. N. Stock. 2004. “Critical Success Factors for Controlling and Managing Hospital Errors.” Quality Management Journal 11: 61-74.

Meier, R. L., M. R. Williams, M. Humphreys, and J. Centko. 1999. “An Exploratory Study to Assess Competency Gaps in Science, Mathematics, Engineering, and Technological (SMET) Education.” Journal of Industrial Technology 15 (3): 2-8.

Meier, R. L., M. R. Williams, and M. Humphreys. 2000. “Refocusing our Efforts: Assessing Non-technical Competency Gaps.” Journal of Engineering Education (July): 377-85.

Mullins, D., and J. A. Schmele. 1993. “Reconsideration of the Quality Circle Process as a Contemporary Management Strategy.” Health Care Supervisor 12 (1): 14-22.

Newman, K. 1997. “Re-engineering for Service Quality: The Case of Leicester Royal Infirmary.” Total Quality Management 8 (5): 255-64.

Plsek, P. E. 1995. “Techniques for Managing Quality.” Hospital & Health Services Administration 40 (1): 50-79.

Podsakoff, P. M., and D. W. Organ. 1986. “Self-reports in Organizational Research: Problems and Prospects.” Journal of Management 12 (4): 531-44.

Reason, J. 1990. Human Error. Cambridge, England: Cambridge University Press.

Ruchlin, H. S., N. L. Dubbs, and M. A. Callahan. 2004. “The Role of Leadership in Instilling a Culture of Safety: Lessons from the Literature.” Journal of Healthcare Management 49 (1): 47-59.

Uribe, C. L., S. B. Schweikhart, D. S. Pathak, G. B. Marsh, and R. R. Fraley. 2002. “Perceived Barriers to Medical-Error Reporting: An Exploratory Investigation.” Journal of Healthcare Management 47 (4): 263-80.

Vanderveen, L. 1991. “CQI System Puts Process into Improving Hospital.” Health Care Strategic Management 9 (2): 16-18.

Walshe, K., J. Bennett, and D. Ingram. 1995. “Using Adverse Events in Health-care Quality Improvement: Results from a British Acute Hospital.” International Journal of Health Care Quality Assurance 8 (1): 7-14.

Ward, P. T, G. K. Leong, and K. Boyer. 1996. “Manufacturing Proactiveness and Performance.” Decision Sciences 25 (2): 99-116.

Kathleen L. McFadden, Ph.D., professor of operations management, Department of Operations Management and Information Systems, Northern Illinois University, Dekalb, Illinois; Gregory N. Stock, Ph.D., associate professor of operations management, Department of Operations Management and Information Systems, Northern Illinois University; and Charles R. Gowen III, Ph.D., professor of management, Department of Management, Northern Illinois University

For more information on the concepts in this article, please contact Dr. McFadden at kmcfadden@niu.edu.

Copyright Health Administration Press Mar/Apr 2006




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