Khatri MGMT Culture 07

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Relationship between managementphilosophy and clinical outcomes

Naresh Khatri

Jonathon R.B. Halbesleben

Gregory F. Petroski

Wilbert Meyer

Background:Medical research continues to focus overwhelmingly on biomedical

interventions, such as drugs, devices, and procedures. The dysfunctional health care

cultures and systems need more attention for quality of care to improve further.

Purpose:The existing health services management research has not used a

systematic theoretical framework to predict the effects of organizational variables

on clinical outcomes. This study tests the theoretical model proposed by N. Khatri, A.

Baveja, S. Boren, and A. Mammo (2006).

Methodology:This study surveyed employees from hospitals in Missouri.

The sample consisted of 77 respondents from 16 hospitals.

Findings:The control-based management approach (Management Control and

Silos) was found to be positively associated with Culture of Blame and negatively

with Learning From Mistakes. In contrast, the commitment-based approach

(Fair Management Practices and Employee Participation) was negatively associated

with Culture of Blame and positively with Learning From Mistakes, Camaraderie,

and Motivation. Mediating variables of Learning From Mistakes and Camaraderie

showed a significant negative relationship with Medical Errors. Learning

From Mistakes, Camaraderie, and Motivation all showed a significant positive

relationship with Quality of Patient Care. The mediating variables had much

stronger relationships with Medical Errors and Quality of Patient Care than did

the independent variables, lending support to the proposed mediation.

Implications for Practice: Health care organizations can improve the quality of

care and reduce medical errors significantly by enhancing learning from mistakes

and boosting camaraderie and morale of their employees. They can do so by

breaking down silos in their structures, implementing just and fair management

practices, and involving employees in decision making.

AprilJune 2007128

Health Care Manage Rev, 2007, 32(2), 128-139Copyright A 2007 Wolters Kluwer Health | Lippincott Williams & Wilkins

Naresh Khatri, PhD, is Assistant Professor, Health Management and Informatics, University of Missouri, Columbia. E-mail:[email protected].

Jonathon R.B. Halbesleben, PhD, is Assistant Professor, Health Management and Informatics, University of Missouri, Columbia. E-mail:[email protected] F. Petroski, PhD, is Research Assistant Professor of Biostatistics, Health Management and Informatics, University of Missouri,Columbia. E-mail: [email protected].

Wilbert Meyer, MA, FACHE, is Associate Director of HMI Group, Health Management and Informatics, University of Missouri,Columbia. E-mail: [email protected].

Key words: commitment-based management, medical errors, quality of patient care, silos

Copyr ight Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.


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The reports of the Institute of Medicine (1999,2001) generated much interest and a flurry ofactivity in the health care community aimed at

improving clinical outcomes. Consistent with the tra-

dition in health care of investing in technology to findsolutions to clinical problems, health care organizationsfurther intensified investments in technological solu-tions, and health care research continued its focus over-whelmingly on biomedical interventions such as drugs,devices, and procedures (Leape, 2004).

Although technology is critical in improving healthcare delivery, it cannot overcome adverse events arisingfrom poor organization and management of the healthcare delivery process (Pearl, 2003). For example, re-search evidence suggests that two commonly toutedtechnological solutionscomputerized physician order

entry systems and electronic medical recordsare notable to prevent the majority of patient safety incidentsthat significantly contribute to preventable deaths andexcess costs each year (Health Grades, Inc., 2004;Leape, 2004).

The current bias toward innovative technologicalsolutions over those that require the transformation ofcurrent dysfunctional culture, management systems, andwork processes in health care must be corrected ifmedical errors and quality of patient care are to betaken seriously (Tucker & Edmondson, 2003). Onlyapproximately one third of adverse events are currently

unpreventable in the sense that reducing them wouldrequire advances in medical sciences (Leape, Berwick, &Bates, 2002). The other two thirds have nothing to dowith technical advances and can be addressed onlyby improving health care cultures and systems. Thus,further investments in technology alone, without con-sidering organizational and management factors, mayhave limited impact on medical errors and quality ofcare (Khatri, Baveja, Boren, & Mammo, 2006).

Theoretical Background

Based on a comprehensive review of 42 articles onclinical and health services management literature re-garding the linkages between organizational factors, med-ical errors, and patient safety, Hoff, Jameson, Hannan,and Flank (2004) lamented that almost all used nosystematic theoretical framework for predicting orexplaining the effects of their organizational variableson clinical outcomes. Addressing the problem of pa-tient safety requires a comprehensive framework thatdirects the entire organization to understand the ra-tionale for a focus on patient safety (Koehoorn, Lowe,Rondeau, Scellenberg, & Wagar, 2002). To overcomethe lack of such a framework, Khatri et al. (2006)developed a comprehensive model linking the overall

management approach to clinical outcomes. This studyexamines the relationship between overall manage-ment approach and clinical outcomes using theirtheoretical model.

The model of Khatri et al. (2006) is an extensionof McGregors (1985) notion of Theory X and Theory Yto health care organizations and is based on two alter-native management theories on human motivation:(a) control based and (b) commitment based. Thecontrol-based view assumes (implicitly or explicitly)that people are incapable of self-regulating their be-haviors and cannot be trusted. Consistent with thisassumption, the natural emphasis of control-based man-agement is on monitoring employee behavior closely viaa variety of control mechanisms.

The alternative view based on commitment has two

underlying assumptions: (a) people are capable of self-discipline, and given the opportunity and develop-mental experiences, they will seek responsibility andexercise initiative; and (b) people work best when theyare fully committed to the organization. The commit-ment-based management approach emphasizes creatingan environment that encourages commitment to orga-nizational objectives and provides opportunities for theexercise of initiative, ingenuity, and self-direction inachieving them.

Control-based management practices are best suited toprevent undesirable actions and behaviors from a small

fraction of employees (McGregor, 1985). The closecontrolling and monitoring of behavior in control-basedmanagement is seen by employees to be constraining anddemoralizing. An unintended but important consequenceis the restriction it imposes on the initiative, creativity,and morale of the majority of the employees who wouldperform better in the absence of control. Control-basedmanagement undermines learning from mistakes andfoments a culture of blame (Khatri et al., 2006).

On the other hand, openness, cooperation, coordi-nation, and teamwork are natural organizational pro-cesses in a commitment-based management approach.

These processes enhance clinical outcomes via im-proved communication, information sharing, and orga-nizational learning, both formally and informally. Thecommitment-based management approach also providesthe environment to achieve improved clinical outcomesby boosting employee morale and camaraderie.

Hypotheses

The model proposed by Khatri et al. (2006) includesnumerous independent, mediating, and dependent vari-ables. It is mediated at two levels. The number of vari-ables and two-level mediation processes make empiricaltesting of the entire model in a single study quite difficult.

Relationship Between Management Philosophy and Clinical Outcomes 129



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As a result, we have adapted the most critical parts of themodel for this study. The adapted model and hypothe-sized relationships are presented in Figure 1.

The adapted model in Figure 1 suggests that the cur-rent culture and systems in health care organizations arecontrol based. The control-based model was developed

F i g u r e 1

The link between management approach and clinical outcomes. From Medical errors andquality of care: From control to commitment by N. Khatri, A. Baveja, S. Boren,

and A. Mammo, 2006,California Management Review, 48(3), pp. 115141. Copyright 2006by Haas School of Business. Adapted with permission.

AprilJune 2007130 Health Care Management REVIEW



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(McGregor, 1985). In a control-based work environ-ment, employees develop feelings of helplessness, frus-tration, and insecurity. The emphasis on complianceand obedience rather than on commitment does not

permit the full utilization of the knowledge and emo-tional energy of the workforce. In short, control-basedmanagement unleashes negative emotional energy inemployees (Khatri et al., 2006).

Employees who work in a commitment-based orga-nization are actively engaged in their work. They takepride in the organization and its mission and areempowered and fully energized. In a commitment-basedorganization, employee turnover is usually low and theutilization of human capacity is high. High employeemorale generates a positive emotional energy. Hence,the following hypotheses:

H2a: The control-based management approach isnegatively associated with camaraderie and moti-vation of employees.

H2b: The commitment-based management ap-proach is positively associated with camaraderieand motivation of employees.

Employee Behaviors andClinical Outcomes

The safe thing to do for health care professionalsoperating in a culture of blame is to hide a mistake whenit occurs. If, however, the mistake surfaces despite thebest efforts to hide it, the natural tendency for anemployee is to blame it on others. In such a scenario,mistakes are underreported, and, if reported, they arenot resolved properly.

Edmondson (1996) found that willingness to reporterrors influences the ability to detect errors in a unit.Specifically, interceptions of mistakes were more preva-lent in units in which members were less concerned

about being caught making a mistake. The nurse leader-ship behaviorsespecially related to how mistakes arehandledwere found to create an ongoing, continuallyreinforced climate of openness or of fear of discussingdrug errors.

In an open and trusting culture, employees are notafraid to report and discuss a mistake thoroughly untilthe root cause of the mistake is identified and propercorrection mechanism is adopted and applied. Thecommitment-based approach provides for a work envi-ronment with a focus on improving the process andensuring that such a mistake does not occur in thefuture. In such a culture, an individual employee is notblamed for the event due to his or her negligence ordeliberate intent.

H3a: The culture of blame is positively associatedwith medical errors. Alternatively, an open andtrusting culture is negatively associated with medi-cal errors.

H3b: Learning from mistakes is negatively associ-ated with medical errors.

Empirical studies examining the relationship betweenmanagement practices and service quality are prolifer-ating (Gelade & Ivery, 2003; Manring & Brailsford,2001) For example, Manring and Brailsford (2001)found that encounters of patients with hospital em-ployees are an important driver of perceived servicequality and patient satisfaction. Gelade and Ivery(2003) reported that human resource management

practices impacted the performance of a bank branchboth directly and indirectly. In its direct effect, un-derstaffing and working overtime elevated job demand,causing stress and depressed individual performance.Indirectly, management practices influenced bankbranch performance by affecting positively the workclimate. The authors noted that satisfied employeesradiate positive affect, producing an emotionally satis-fying experience for the customer.

Prolonged exposure to jobs high in demands and lowin controllability typical in health care organizationsleads to stress-related mental and physical problems

(Fox, Dwyer, & Ganster, 1993). Health care organiza-tions should meet their employees needs to participateand make a contribution, provide psychological andeconomic security, offer opportunities for skill develop-ment, and have the right balance of job demands andresources to raise employee morale essential for deliveringhigh-quality patient care (Koehoorn et al., 2002).

Evidence in support of the commitment-basedphilosophy is slowly emerging in health care organiza-tions. For example, a study of Veterans Health Admin-istration hospitals found that teamwork culture waspositively associated with inpatient satisfaction and

that rule-based, bureaucratic culture was negatively as-sociated with it (Meterko, Mohr, & Young, 2004). Thepositive relationship between teamwork and inpatientsatisfaction was mediated by more effective coordinationand greater cohesion among employees working towardthe same goal. Similarly, a study of 283 Canadian nursinghomes found that homes that had implemented moreprogressive management practices and reported aworkplace climate that strongly valued employee partici-pation produced better clinical outcomes (Rondeau &Wagar, 2001).

Quality of work life among health care workers hasdeteriorated to the point where it is impeding thecapacity of the system to recruit and retain staff neededto provide effective care. It is unrealistic to expect a




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tough fight from demoralized, hapless, and exhaustedtroops. Health care organizations must develop and im-plement cultures and management systems that em-power employees to use their talents and skills fully in

providing safe and high-quality patient care. Hence, thefollowing hypotheses:

H4a: Camaraderie in health care workers ispositively associated with the quality of patientcare they provide.

H4b: The motivation level of health care workersis positively associated with the quality of patientcare they provide.

Method

Participants and Procedure

This study surveyed employees of hospitals in Missouri.The human resource directors were contacted viatelephone and e-mail, and those who showed interest inthe study were mailed five questionnaires to be distrib-uted to five employees such that each employeerepresented a different department. The decision to limitthe survey to five employees from each hospital wasestablished in order not to overload and become a

deterrent to hospital participation in the study yet pro-vide a sufficient number of responses for data analysis.Employees were chosen as respondents instead of

senior managers because it is the employees who areimpacted by the overall management approach. Researchsuggests that views of senior management can divergefrom that of employees; senior managers may think theyuse a certain management approach that employees donot experience (Gabris & Giles, 1983).

In all, 200 questionnaires were mailed to the humanresource directors at 33 hospitals for distribution to theiremployees. The questionnaires were coded, but the

respondents were assured of the confidentiality of theirresponses. The respondents were provided with self-addressed prepaid business reply envelopes for returningthe completed questionnaires directly to the researchteam. Seventy-seven completed questionnaires from em-ployees of 16 hospitals were received, for a response rateof 38.5%. The distribution of the number of respondentsper hospital was as follows: one hospital had one re-spondent, four hospitals had two respondents each, fourhospitals had three respondents each, and five hospitalshad four respondents each. In addition, one hospitalvolunteered to complete more than five questionnaires.We received 36 questionnaires from this hospital. Thesize of the hospitals in the sample varied from a hospitalwith 41 licensed beds to a hospital with 1,277 licensed

beds. There were seven respondents from four largehospitals having 250, 274, 375, and 1,277 licensed beds.The remaining 70 respondents were from 12 hospitalswith size ranging from 41 to 84 licensed beds. Thus, the

study sample largely represents county hospitals with lessthan 100 licensed beds spread all over Missouri.

The largest number of respondents was from thesurgery department, with 28 respondents. Eleven re-spondents were from the nursing department, 8 from theobstetrics/gynecology department, 6 from the intensivecare unit, 5 from the laboratory, 4 from the emergencyroom, and the rest from other departments. The dis-tribution of the titles of the respondents was as follows:6 departmental heads, 7 nurse managers, 7 technicians,30 registered nurses, 15 certified nursing assistants,6 licensed practical nurses, 5 ward clerks, and 1 physical

therapist. The average work experience of the respon-dents in the work unit was 5.8 years. Fifty-six respon-dents worked in the day shift, 12 in the night shift, and9 in more than one shift.

Measures

Items in the scales are a combination of new itemsdeveloped for this study, as well as items adapted fromprevious research (see Appendix A). All items used afive-point Likert scale format (1 = strongly disagree to5 = strongly agree). The scales used to measure the four

independent variables of Management Control (fouritems), Silos in Organization (three items), Just andFair Practices (three items), and Employee Participa-tion (five items) are all new. This study used four scalesto measure mediating variablesCulture of Blame(two items), Learning From Mistakes (three items),Camaraderie (seven items), and Motivation (six items).

Medical Errors and Quality of Patient Care are the twodependent variables in the study. Research suggests thatmeasurement of medical errors is quite complex.Hospitals can vary significantly in their definition andreporting of medical errors. To overcome this problem,

we focused only on drug-related errors in this study. Drug-related errors are specific and cut across specialties.The respondents were asked to indicate their responseon a scale of 1 (strongly disagree) to 5 (strongly agree) tothe item Drug-related errors occur frequently in thisdepartment. The scale used to measure Quality of Pa-tient Care had three items.

The hypothesized relationships in Figure 1 were testedusing path modeling. Two standard assumptions under-lying conventional methods of path analysis are that theobserved data represent a random sample from a multi-variate normal distribution and that the sample size issufficiently large to justify the asymptotic normality ofthe parameter estimates (Bollen, 1989). Similarly thechi-square goodness of fit also requires a large sample




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size to be strictly valid. In this study, the normality as-sumption cannot be satisfied due to the ordinal nature ofthe response variables, and the sample size may not besufficient to rely on asymptotic standard errors for testing

the path coefficients. To address both issues, bootstrapmethods (Efron & Tibshirani, 1993) as implemented inthe software package Mplus v3.13 (Muthen & Muthen,2004) were used to provide tests of the path coefficients.The bootstrap is a resampling-based method that does notrequire specific distributional assumptions for validinference. It allows the structural equation modelinganalyses to be performed even on sample sizes rangingbetween 50 and 60 (Schneider, Ehrhart, Mayer, Saltz, &Niles-Jolly, 2005).

Results

The descriptive statistics and zero-order correlations arepresented in Table 1. Reliability and factor analyses wereperformed for checking the reliability and validity ofscales. The Cronbachs a for scales measuring the fourindependent variables of Management Control, Silos inOrganization, Just and Fair Practices, and EmployeeParticipation was .71, .58, .90, and .77, respectively. Re-liabilities of scales, with the exception of Silos inOrganization, are all good. The low reliability of thescale on Silos may be attributed partly to fewer items inthe scale (three items), diverse content of the items, and

reverse coding of items. Factor analysis showed that itemsin the four scales loaded unambiguously on the fourcorresponding factors, thus providing evidence forconvergent and divergent validities of the scales(Finkelstein, 1992; results of the factor analysis can beobtained from the authors).

Factor analysis of the four mediating variables ofCulture of Blame, Learning From Mistakes, Camaraderie,and Motivation revealed four factors with items loadingclearly on the corresponding factors. The Cronbachs a

for both Camaraderie and Motivation scales was .86.The reliability coefficient for the Culture of Blame wasnot computed because it had only two items. TheCronbachs a for Learning From Mistakes was .53. Webelieve that the afor the scale is satisfactory in view ofthe diverse content of the items, fewer items (only threeitems), and one of the three items being reversecoded. The scale to measure the dependent variable ofQuality of Patient Care showed satisfactory reliability(Cronbachs a= .68).

For path analysis, we started with the original model inwhich each of Culture of Blame, Learning From Mistakes,

Camaraderie, and Motivation was regressed on Man-agement Control, Silos in Organization, Just and FairPractices, and Employee Participation, and Medical Er-rors and Quality of Patient Care were regressed on eachof the independent and mediating variables, giving usa model of both direct and indirect effects of manage-ment approach on Quality of Patient Care and MedicalErrors. Because there is no generally agreed upon bestmeasure of fit for structural models, it has becomecustomary to quote several measures of fit. For thisstudy, we present the chi-square goodness of fit test alongwith the TuckerLewis Index (TLI; Tucker & Lewis,

1973) and the root-mean-square error of approximation(RMSEA; Browne & Cudeck, 1993). For the full model,the values of three goodness-of-fit indices were as follows:2 = 12.26 withdf= 6, TLI = .75, and RMSEA = .12.

To achieve a better fitting and more parsimoniousmodel, we removed the paths that were not statistically

T ab l e 1

Descriptive statistics and correlations

Variables Mean SD 1 2 3 4 5 6 7 8 9 10

1. Management Control 3.19 0.80 .71 .26* .23* .46** .56** .17 .26* .33** .16 .052. Silos in Organization 2.48 0.74 .58 .22* .30** .42** .33** .51** .28* .22* .36**

3. Just and Fair Practices 3.86 0.81 .90 .37** .41** .31** .24* .28* .11 .32**

4. Employee Participation 3.70 0.60 .77 .34** .20 .41** .46** .11 .40**

5. Culture of Blame 2.76 0.87 .14 .36** .23* .23* .176. Learning 3.59 0.71 .53 .30** .19 .30** .38**

7. Camaraderie 3.66 0.72 .86 .46** .30** .53**

8. Motivation 4.14 0.64 .86 .07 .52**

9. Medical Errors 2.37 1.16 .32**

10. Quality of Care 4.08 0.66 .68

Note. Reliabilities (Cronbachs a) are reported in italics in the diagonal.

*Significant at p < .05.

**Significant at p < .01.




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significant (p < .05). The resulting model with significantpaths is presented in Figure 2. For this model, the fitindices were as follows: 2 = 22.8 withdf= 23 (p= .51),TLI = 1.0, and RMSEA = .00, with the significance level

for the test of close fit based on RMSEA being .73.Collectively, the fit measures suggest an excellent fit forthe model displayed in Figure 2. Although the numberof cases is small (N = 77), the fit indices and boot-strapping analyses dispel any major concern that usuallyarises when the sample is small.

Management Control and Silos in Organizationindicated the extent of the control-based management,whereas Employee Participation and Just and FairPractices indicated the extent of the commitment-basedapproach. Management Control and Silos in Organiza-tion showed a significant positive relationship with

Culture of Blame. Silos also had a highly significant butnegative relationship with Learning From Mistakes.

Together, these findings support Hypothesis 1a (Thecontrol-based management approach is positively associ-ated with the culture of blame and negatively associatedwith learning from mistakes). Just and Fair Practices

showed a negative relationship with Culture of Blameand a positive relationship with Learning From Mistakes.Employee Participation was, however, not significantlyrelated to either Culture of Blame or Learning FromMistakes. These findings thus provide partial support toHypothesis 1b (The commitment-based approach isnegatively associated with the culture of blame andpositively associated with learning from mistakes).

Hypothesis 2a, which states that the control-basedmanagement approach is negatively associated withcamaraderie and motivation of employees, receivedpartial support in that only Silos showed a significant

negative relationship with Camaraderie. ManagementControl had no significant relationship with either

F i g u r e 2

The best-fitting path model linking management approach to clinical outcomes




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Camaraderie or Motivation. Similarly, Hypothesis 2b waspartially supported. Whereas Employee Participation hada significant positive relationship with both Camaraderieand Motivation, Just and Fair Practices showed no sig-

nificant relationship with either.Surprisingly, Hypothesis 3a, stating that Culture of

Blame is positively associated with Medical Errors, wasnot supported; the relationship was statistically insignif-icant. Hypothesis 3b (Learning from mistakes isnegatively associated with medical errors) was fullysupported. The data analyses lent strong support toHypotheses 4a (Camaraderie in workforce is positivelyassociated with quality of patient care) and 4b (Themotivation level of health care workers is positivelyassociated with quality of patient care). In summary,control-based management practices enhance Culture of

Blame and undermine Learning From Mistakes andCamaraderie in the workforce. The commitment-basedmanagement practices, on the other hand, weaken Cul-ture of Blame and strengthen Learning From Mistakes,Camaraderie, and Motivation in the workforce.

The mediating variables of Learning From Mistakesand Camaraderie showed a significant and negativerelationship with Drug-Related Errors. Learning FromMistakes, Camaraderie, and Motivation all showed asignificant and positive relationship with Quality ofPatient Care. The mediating variables showed strongerrelationships with Drug-Related Errors and Quality of

Patient Care than did the independent variables, thusproviding support to the proposed mediation. In otherwords, the management approach influences clinicaloutcomes not directly but indirectly via impactingemployee behaviors.

In addition, we found two significant paths that we hadnot hypothesized. Management Control had a directpositive relationship with Quality of Patient Care, andDrug-Related Errors had a significant negative relation-ship with Quality of Patient Care. Whereas the latter isconsistent with the broader theoretical logic underlyingthe study (as one would expect that errors would lead to a

reduced perception of quality of care), the former iscontradictory.

Discussion

Unsurprisingly, silos in organizational structure, arisingfrom a confluence of factors (control-based managementphilosophy and many specialties and professional culturesin health care), turned out to be one of the mostsignificant variables in the study. Silos result in a strongerculture of blame and finger pointing. Even more im-portant, they diminish learning and camaraderie in theworkplace, the two mediating variables that have a largeimpact on medical errors and quality of patient care. Silosare symptomatic of a dysfunctional organization and have

a negative effect on organizations, leading to turf wars,power struggles, and personality conflicts, all of whichresult in poor teamwork and cooperation. Silos create anenvironment in which the personal and departmental

interests of managers take precedence over the well-beingof the organization. The reasons for the formation of silosin hospitals include an organizational structure rigidlydesigned around functional areas, corporate culture,and traditions that do not encourage collaboration;lack of cooperation/participation in cross-functionalteams; poor departmental leadership; inadequate inter-personal skills; poorly designed reward systems; andpolicies that make cooperation difficult (Stone, 2004).A classic example of the adverse consequences of silos isthe intelligence failures that occurred allowing forterrorist attacks now known as the 9/11 disaster. The

familiar phrase of failing to connect the dots is nothingbut intelligence remaining stuck in silos created byboundaries of various departments and agencies involvedin intelligence gathering.

The study findings indicate that camaraderie andlearning from mistakes are two important mediating(or process) variables. Both had a highly significantnegative relationship with drug-related errors and apositive relationship with quality of patient care. Thus,reduction of medical errors and enhancement of qualityof patient care require an open trusting culture and a spiritof cooperation and teamwork in the workforce. The

current control-based management approach leads to aculture of blame and suppresses both camaraderie andopenness. Hospitals need to employ a commitment-basedapproach by fostering employee participation in decisionmaking and establishing just, fair, and egalitarianmanagement practices. Both camaraderie and learningfrom mistakes are relatively unexplored constructs.However, given their pivotal role in affecting clinicaloutcomes, they need much more attention from healthcare management scholars.

Employee participation in decision making was sig-nificantly and positively related to camaraderie and

motivation of employees. It is the only independentvariable having a significant positive impact on themotivation (and satisfaction) of employees. This findingis perhaps not surprising given the consistent linksbetween participation in decision making and jobsatisfaction in the health services management literature(Cavanaugh, 1992). Thus, employee participation is ofchief importance in improving the morale and camara-derie of the workforce.

Unexpectedly, we found a significant positive rela-tionship between management control and quality ofpatient care. Although this finding seems contrary towhat is expected in a highly professionalized environ-ment such as health care, several studies have foundrelationships between control and quality to the extent




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that control leads to standardized processes that ensureconsistent quality in some settings (Bijisma-Frankema &Koopman, 2004). As such, this finding may have been theresult of perceived consistency in patient care from a

management system that strictly enforces procedures forcare. This consistency may have been interpreted interms of a higher quality patient care.

In addition, we did not find the expected relationshipbetween a culture of blame and medical errors. Aninteresting finding was that these two variables werecorrelated (r = .23,p < .05), but their relationship was notsignificant when the other variables in the model wereconsidered simultaneously. This suggests the possibilitythat methodological limitations (e.g., sample size andrelatively high correlations between variables in themodel) suppressed the relationship between culture of

blame and errors.This study has several limitations. First, although fit

indices and bootstrapping analyses indicate that the smallsample was not a major weakness of the study, the datacollection was limited to hospitals in Missouri. Thus, totest and increase the generalizability of the findings,data from a national sample of hospitals need to begathered and analyzed. Second, responses of individualsin hospitals may not be necessarily different from oneanother. Statistically, this becomes an issue becauseresponses from multiple individuals within the sameinstitution may not be independent. Assuming indepen-

dence when, in fact, responses are correlated can producea downward bias in standard errors, thereby producingfalse significance levels. Finally, the data collected werecross-sectional in nature. Future research that confirmsthese findings using longitudinal methods may be bettersuited for making causal claims regarding the relation-ships among the variables.

Implications for Practice

The study findings have important implications for

practitioners. Currently, the efforts of most health careorganizations are limited to measuring and fosteringsatisfaction of their employees using quantitative mea-surement tools such as the Press Ganey Survey. Thisresearch suggests that although the role of employeesatisfaction in affecting clinical outcomes may besignificant, other variables such as learning from mistakesand camaraderie also play a critical role in determiningmedical errors and quality of patient care. Employeesatisfaction is a component of motivation in this study,and motivation had a significant positive relationshipwith quality of care but no direct relationship withmedical errors. Thus, if health care organizations wantto improve their clinical outcomes, they should notonly be focused on employee satisfaction but also pay

attention to learning from mistakes, camaraderie, andmotivation of their workforce.

Health care organizations are making concerted ef-forts in improving the quality of care. Unfortunately,

most quality improvement initiatives are implemented ina highly control-based context. Consistent with thecontrol-based management approach, management hascreated a separate quality assurance department or unitto address the issue. By creating yet another departmentby management sends an inadvertent signal to otherdepartments that actually deliver health care that theyare not directly accountable for medical errors and qualityof care. Quality of care cannot be managed by creating aseparate quality assurance department; it must be integralto the health care delivery process. A commitment-basedmanagement approach by emphasizing employee partic-

ipation, cooperation, information sharing, and teamworkfocuses on quality of care quite naturally without aseparate department or mandate.

The theory and practice underlying the control-basedapproach is relatively simple, and conventional humanresource practices perpetuate control-based managementin health care organizations (Khatri et al., 2006). Thecommitment-based management approach is more com-plex to implement than control-based management andrequires emotionally intelligent managers to be placed atall levels in the organization. Health care organizationsmust build internal human resource capability to

implement a commitment-based management approach(Khatri, 2006).

Conclusion

The predominant thinking in health care organizationsis that technology can solve all its problems. Timeis growing shorter as to how long medical costs can con-tinue to rise. We argued and provided evidence thatthe answer to further improvements in clinical outcomesdoes not lie in further investments in technology alone

but also in improvements in the organization andmanagement of health care delivery process. The man-agement culture and systems in health care remainentrenched in the control-based model, which isconsistent with the old industrial model of manage-ment. However, health care organizations are notfactories. They are highly knowledge-intensive andservice-oriented entities and thus require managementculture and systems premised on the commitment ofemployees to achieving the highest level of quality ofpatient care. Health care organizations need to moveaway from controlling employees to involving them indecision making and providing them a just and fairwork environment. Health care organizations need tobreak down silos that exist in their structures and embrace




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a management approach that encourages learning andcamaraderie in the workforce.

Acknowledgments

We would like to thank Peter Oppelt and Hetal Rupanifor their assistance in data collection and entry forthis research.

References

Bijisma-Frankema, K., & Koopman, P. (2004). The oxymoronof control in an era of globalization: Vulnerabilities of amega myth.Journal of Managerial Psychology,18, 204217.

Bollen, K. A. (1989). Structural equations with latent variables.New York: Wiley.

Browne, M. W., Cudeck, R. (1993). Alternative ways ofassessing model fit. In K. A. Bollen, J. S. Long (Eds.),Testing structural equation models. (pp.136142). New-bury Park, CA: Sage.

Cannon, M. D., & Edmondson, A. C. (2001). Confrontingfailure: Antecedents and consequences of shared beliefsabout failure in organizational work groups. Journal ofOrganizational Behavior, 22, 161177.

Cavanagh, S. (1992). Job satisfaction of nursing staff workingin hospitals. Journal of Advanced Nursing, 17, 704711.

Edmondson, A. C. (1996). Learning from mistakes is easiersaid than done: Group and organizational influences onthe detection and correction of human behavior. Journalof Applied Behavioral Science, 32(1), 528.

Efron, B., & Tibshirani, R. J. (1993). An introduction to thebootstrap. New York: Chapman & Hall.

Finkelstein, S. (1992). Power in top management teams:Dimensions, measurement, and validation. Academy ofManagement Journal, 35(3), 505538.

Fox, M. L., Dwyer, D. L., & Ganster, D. C. (1993). Effects ofstressful job demands and control on physiological andattitudinal outcomes in a hospital setting. Academy ofManagement Journal, 36(2), 289318.

Gabris, G. T., & Giles, W. A. (1983). Perceptions of man-agement style and employee performance: Resurrectinga diminishing debate. Public Personnel Management, 12,167180.

Gelade, G. A., & Ivery, M. (2003). The impact of humanresource management and work climate on organizationalperformance. Personnel Psychology, 56(2), 383404.

Gittell, J. H. (2000). Paradox of coordination and control.California Management Review, 42(3), 117134.

Health Grades, Inc. (2004).Patient safety in American hospitals.Health Grades Quality Study. Retrieved August 10, 2005,from www.healthgrades.com/media/english/pdf/HG_Patient_Safety_Study_Final_pdf.

Hoff, T., Jameson, L., Hannan, E., & Flink, E. (2004). Areview of the literature examining linkages betweenorganizational factors, medical errors, and patient safety.Medical Care Research and Review, 61(1), 337.

Institute of Medicine. (1999). To err is human: Building asafer health system. Washington, DC: The National Acade-mies Press.

Institute of Medicine. (2001). Crossing the quality chasm: Anew health system for the 21st century. Washington, DC:The National Academies Press.

Khatri, N. (2006). Building HR capability in health careorganizations. Health Care Management Review, 31(1),4554.

Khatri, N., Baveja, A., Boren, S., & Mammo, A. (2006). Med-ical errors and quality of care: From control to commit-ment.California Management Review,48(3), 115141.

Koehoorn, M., Lowe, G. S., Rondeau, K. V., Schellenberg, G.,& Wagar, T. H. (2002). Creating high-quality health care

workplaces [Work Network Discussion Paper W/14]. Ottawa,Canada: Canadian Policy Research Networks Inc.

Leape, L. L. (2004). Making health care safe: Are we up to it?Journal of Pediatric Surgery, 39(3), 258266.

Leape, L. L., Berwick, D. M., & Bates, D. W. (2002). Whatpractices will most improve safety? Evidence-basedmedicine meets patient safety. JAMA, 288(4), 501507.

Manring, S. L., & Brailsford, A. (2001). Collaboration towardservice excellence: A unionmanagement and empoweredemployee partnership. Hospital Topics, 79(3), 2531.

McGregor, D. (1985).The human side of enterprise. New York:McGraw-Hill.

Meterko, M., Mohr, D. C., & Young, G. J. (2004). Teamworkculture and patient satisfaction in hospitals. Medical Care,

42(5), 492498.Muthen, L., & Muthen, B. (2004). M Plus users guide.

(3rd ed.). Los Angeles: Muthen & Muthen.

Pearl, R. A. (2003).System in crisis: Finding a solution for healthcare in America. Stanford Executive Briefings. Palo Alto,CA: Stanford University.

Rondeau, K. V., & Wagar, T. H. (2001). Impact of humanresource management practices on nursing home perfor-mance.Health Services Management Research,14,192202.

Schneider, B., Ehrhart, M. G., Mayer, D. M., Saltz, J. L., &Niles-Jolly, K. (2005). Understanding organizationalcustomer links in service settings. Academy of Management

Journal, 48,10171032.

Stone, F. (2004, Spring). Deconstructing silos and supportingcollaboration. Employment Relations Today, 31, 1118.

Tucker, A. L., & Edmondson, A. C. (2003). Why hospitalsdont learn from failures: Organizational and psychologicaldynamics that inhibit system change. California Manage-ment Review, 45(2), 5571.

Tucker, L. R., & Lewis, C. (1973). A reliability coefficientfor maximum likelihood factor analysis. Psychometrika,38,110.




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The scales used in the study

Independent variablesManagement Control (a= .71): (1) It is generally safer to say that you agree with management even when youdont really agree. (2) In my department, it is difficult to make decisions without an approval from higherauthority. (3) In my department, bureaucratic procedures generally govern what people do. (4) Variousprofessional groups (e.g., nurses, physicians, administrators, and technicians) perceive significant statusdifferences between them.Silos in Organization (a = .58): (1) I would characterize the communication between various employee groups orunits in my department as good (reverse coded). (2) I think that communication between physicians, nurses,

managers, and other health care professionals in my department is good (reverse coded). (3) Various employeegroups or units in my department pursue goals and priorities that are inconsistent with overall departmentalgoals and priorities.Just and Fair Practices (a= .90): Recall the most recent evaluation of your job performance and circle the responsethat most accurately describes your view about the following statements: (1) I received the evaluation that Ideserved, (2) the evaluation reflected the quality of my performance, and (3) an independent observer fromoutside the organization would have made a similar judgment about my performance.Employee Participation (a = .77): (1) Employees are given opportunity to suggest improvements in the wayclinical services are provided. (2) Employees have a feeling of personal empowerment and ownership of workprocesses. (3) Employees have the authority to make decisions required by their day-to-day work problems.(4) I am able to contribute to decision making that affects my job. (5) Employees are kept informed aboutdepartmental goals and priorities and involved in achieving those goals and priorities.

Mediating (or process) variables

Culture of Blame: (1) There is a culture of blame in my department. (2) The response to medical errors in mydepartment focuses primarily on the individuals at fault.Learning from Mistakes (a = .53): (1) In my department, we often spend time in analyzing and discussing medicalerrors with a view to preventing them from happening again. (2) The same sort of medical errors keephappening again and again because the system within which they occur doesnt change (reverse coded).(3) Most of the medical errors in department get reported.Camaraderie (a= .86): (1) The employee morale is high in my department. (2) The members in my departmenttrust each other. (3) People in my department enjoy working together. (4) A spirit of cooperation and teamworkexists in my department. (5) There is a lot of unpleasantness in members of this department (reverse coded).(6) Employees in my department are very productive. (7) I can say with confidence that employees in mydepartment try to do their best.Motivation (a = .86): (1) There are things about working in this department that encourage me to work hard.(2) This department inspires the very best in me. (3) I am satisfied with the kind of work I do. (4) Overall, I amsatisfied with my job. (5) I talk up this department to my friends as a great department to work for. (6) I am

proud to tell others that I am part of this department.

Dependent variablesMedical Errors: (1) Drug-related errors occur frequently in this department.Quality of Patient Care (a= .68): (1) I would rate the technical (or clinical) quality of patient care in mydepartment as outstanding. (2) I would rate the service quality of patient care in my department as outstanding.(3) Patients often complain about how this department functions (reverse coded).

All the scales used a five-point Likert scale format (1 = strongly disagree to 5 = strongly agree).


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Khatri MGMT Culture 07