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Contrasting continuous qualityimprovement, Six Sigma, and lean

management for enhancedoutcomes in US hospitals

Charles R. Gowen IIIDepartment of Management, Northern Illinois University, DeKalb,

Illinois, USA, and

Kathleen L. McFadden and Sriranjita SettaluriDepartment of Operations Management & Information Systems,

Northern Illinois University, DeKalb, Illinois, USA

Abstract

Purpose Rapidly rising healthcare costs, partially due to preventable medical errors, have ledhospitals to redouble their process improvement (PI) efforts. The purpose of this paper is to examinehow PI initiatives mediate the effect of medical error sources to enhance three hospital outcomes(patient safety, operational effectiveness, and competitiveness).

Design/methodology/approach Drawing from Dynamic Capabilities Theory, the authorsdevelop a framework to explore three PI initiatives: Continuous Quality Improvement (CQI), SixSigma Initiatives (SSI), and Lean Management Initiatives (LMI). Hierarchical regression analysis isemployed to test the proposed model, using data from a nationwide survey of 210 US hospitals.

Findings For enhancing patient safety outcomes, it was found that CQI and LMI were significant inmediating hospital error sources; however, SSI was not significant after accounting for the other twoPI types. For improving organizational effectiveness, CQI and SSI were significant; whereas LMI wasnot significant over and above the other two PI types. Finally, only SSI was significant for superiorsustainable competitive advantage.

Research limitations/implications The paper provides insight into which PI initiatives weremost effective for various hospital outcomes. The findings can benefit healthcare practitioners as theyselect among different PI programs for enhancing healthcare results. Limitations of the study includethe use of perceptual measures, relatively small sample size, and potential alternate relationshipsrelevant to the outcome variables.

Originality/value This is the first study to explore the mediating effects of three PI programs forthe impact of medical errors on each of three hospital outcomes.

KeywordsUnited States of America, Hospitals, Quality improvement, Six Sigma,Continuous Quality Improvement, Lean, Healthcare operations, Patient safety

Paper typeResearch paper

IntroductionMedical errors and soaring healthcare expenditures continue to be the focus of acceleratednational attention. Slow progress has occurred since the Institute of Medicine report(Kohnet al., 2000), which estimated that about 58 percent of US medical errors may bepreventable (Leape and Berwick, 2005). Hospital errors cause longer stays and cost about$17 billion annually (Van den Boset al., 2011). Medical errors and other sources of costscause a greater proportion of annual personal income and national economic resources

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Contrasting CQI,Six Sigma

and lean

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American Journal of BusinessVol. 27 No. 2, 2012

pp. 133-153q Emerald Group Publishing Limited

1935-5181DOI 10.1108/19355181211274442


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to shift toward healthcare (Chernew et al., 2009). About $2.6 trillion is spent onhealthcare, which is 17.9 percent of US gross domestic product (GDP) and accounts for54 percent of total federal revenue (Martinet al., 2011). Due to the trend of medical costsincreasing at a rate exceeding that for GDP growth in all developed countries, the

worldwide concern about medical expenditureshas promotedan awareness of the needforgreater effectiveness in healthcare systems (Kumar et al., 2011).

Process improvement (PI) initiatives are designed to helpreduce or eliminate sourcesoferrors. In hospitals, frequent sources of errors relate to communication, system and culturefailures (Garbutt et al., 2008). Error sources, such as poorly designed tasks/jobs, equipmentfailure/malfunction, lack of employee expertise/knowledge, willful employee misconduct,infrastructure issues (public/internal backup services), unplanned circumstances/events,and computer issues, cause healthcare process inefficiencies (Spath, 2011). The mostcommon sources are poorly designed tasks that contribute to human error (Leape, 2009).Hospital errors can also arise from other systemic factors such as infrastructurebreakdown, and system malfunction due to internal or external demand surge (Barryet al.,2002). Infrastructure breakdowns include power outages, shortages of water supply, anddisruptions in communication systems. Internal demand relates to things like unplannedshortage of capacity, errors in scheduling, fatigued staff, and unexpected demand forpersonnel in one specific area of the hospital (Pham et al., 2012). In contrast, externaldemand is beyond the control of the hospital and can result from natural disasters, such asearthquakes, chemical spills or forest fires, where many people require immediate medicalattention. While sources of errors can cause frustration, impede employees, and decreaseoverall hospital performance, they nonetheless provide improvement opportunities,potentially resulting in organizational learning and increased performance (Tucker, 2004).Despite the possible benefits, most organizations find it challenging to learn from errors(Carroll et al., 2002). Traditional means of addressing sources of hospital errors alone seemto fall short of their potential to improve organizational performance (Tucker, 2004).

The purpose of this study is to examine hospital error sources (HES) and how PIinitiatives enhance hospital outcomes such as patient safety results (PSR), organizationaleffectiveness results (OER), and sustainable competitive advantage (SCA). We expect thatthe implementation of PI initiatives, such as continuous quality improvement (CQI), SixSigma initiatives (SSI), and lean management initiatives (LMI) may mediate therelationship between HES and outcomes. Moreover, we propose that improved hospitalperformance can be achieved by an integrated PI approach, including CQI, SSI and LMI.Figure 1 graphically shows our conceptual model that guides this study.Figure 1.

Framework for the impactof hospital error sources(HES) on patient safetyresults (PSR),organizational

effectiveness results(OER), and sustainablecompetitive advantage(SCA), mediated bycontinuous qualityimprovement (CQI), SixSigma initiatives (SSI),and lean managementinitiatives (LMI)

CQI

SSI

LMI

OERHES

SCA

PSR

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PI initiatives have been applied in manufacturing for many years, resulting in numerousbenefits for successful PI adoption. More recently, service organizations have learnedthe value and importance of PI techniques in increasing quality, reducing costs andimproving customer service. An empirical study by Gowen and Tallon (1999) found that

manufacturing firms reported a significantly greater perceived use of PI techniques, andexperienced greater success in achieving competitive advantage than service firms.However, PI initiatives have evolved over time and today are more adaptive to theunique challenges of the service sector (Hiltonet al., 2008).

The application of PI techniques has increased in popularity especially for healthcare(DelliFraineet al., 2010). To resolve medical errors, hospital personnel have recentlyrated PI initiatives as more important than previously reported and experienced morefrequent improvements in patient safety, quality, employee satisfaction, andcompetitiveness (Lighter, 2011). In hospitals, PI programs include quality teams thatdeploy PI tools to improve process outcomes such as decreased emergency room visittime (Arthur, 2009), lower clinical tray contamination (Lacey, 2009), and reducedradiology waiting time (Lodge and Bamford, 2008). During the past few years,healthcare organizations have increasingly embraced PI as an effective technique forimproving productivity, profitability, quality, and competitiveness (Arthur, 2011b).CQI, SSI and LMI are the leading types of PI techniques (Inozu et al., 2011). Over the last20 years, CQI has been deployed by nearly all hospitals (Kazandjian, 1997). According toa survey by the American Society for Quality, 42 percent of US hospitals use some formof SSI and 53 percent of US hospitals use some type of LMI (Henke, 2009).

CQI is an incremental approach toward process improvement and takes anorganization-wide systems perspective, which is tied to the strategic goals and alignedwith a culture of quality (Sollecito and Johnson, 2011). CQI initiatives used inhealthcare include the plan, do, check/study, and act (PDCA/PDSA) method, the use ofquality improvement employee teams, employee recognition and rewards, promotion

opportunity, patient satisfaction measures, and competitive benchmarking (Evans andLindsay, 2011; Ryan and Thompson, 1998). Employee teams implement the PDCA/PDSAcycle in order to take advantage of the diversity in team member skills, experience, andknowledge. Employeerecognition, rewardsand promotional opportunities are linked to PIprogram success to promote individual, team and organizational performance. Patientsatisfaction assessment consists of utilizing measures, identifying causes ofdissatisfaction, and implementing process improvements to enhance patientsatisfaction and retention. Finally, competitive benchmarking involves evaluating ahospitals processes against those that are best-in-class at other facilities.

In contrast, Six Sigma is a radical breakthrough approach that is heavily focused onbottom lineresults, specifically for process improvementprojects (George,2003; Nair etal.,2011; Van der Meulenet al., 2011). Critical Six Sigma concepts for healthcare include the

define, measure, analyze, improve, and control (DMAIC) process, green belt and/or blackbelt employee training, statistical process/quality control, and project review and closure(Furterer, 2011). Six Sigma problem-solving projects utilize the DMAIC methodology thatincorporates a wide variety of statistical tools and process improvement techniques(Georgeet al., 2005). The success of a Six Sigma team depends on employee Black Beltand Green Belt training in statistical techniques, team building, leadership, andproject-selection skills (Stamatis, 2010). Six Sigma teams apply statistical process controlto measure and monitor variation in a process over time. Finally, Six Sigma requires


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project reviews and project closure to determine the success of each project andto communicate the resulting best practices throughout the organization.

The implementation of lean management is motivated by the relentless pursuit ofefficiency, reduced costs, and increased delivery speed of products and services (Arthur,

2011a). Healthcare non-value added is estimated at 95 percent of healthcare operations,leaving room for substantial efficiency improvement (Hagan, 2011). Common leanmanagement tools in healthcare include process mapping, value stream mapping,Kaizen improvement events, just-in-time process management, and 5S principles(Cottington and Forst, 2010; Graban, 2009; Protzman et al., 2010). The 5S principlesreduce waste by deploying five steps:

(1) sort for necessity;

(2) simplify the workplace;

(3) shine for cleanliness;

(4) standardize processes; and

(5) sustain standard processes.

Process mapping requires the analysis of individual steps and leads to potentialefficiencies by redesigning the process to eliminate unessential elements. Value streammapping visually displays the process flow, distinguishes between value-added andnon-value-addedactivities, assists in pointingout root causes of waste, identifies problemsand opportunities for improving workflow, and shows how the future workflow wouldlook. A Kaizen improvement event consistsof defining the problem, analyzing workflows,cycle times, and value stream maps, testing improvement alternatives, deploying theselected solution, and reporting out to top management. Finally, just-in-time ( JIT) processmanagement eliminates waste and streamlines operations through reduction in waitingtime delays, inventories, employee motion, and transportation.

CQI, LMI and SSI often provide synergistic benefits. For instance, organizations tendto couple lean with Six Sigma for greater overall outcomes (Bisgaard, 2009). Both focuson customer requirements, reducing cost, and making a significant financial impact(Arthur, 2009). However, a clear difference is that they attack different types ofproblems. Lean focuses on speed and the more visible problems in processes such asinventory, material flow and safety (Arthur, 2011a), while Six Sigma focuses onprecision and accuracy, which are less visible problems of variation in performance(Antony, 2011). Similarly, SSI complements CQI as both seek to improve quality andcustomer satisfaction for long-term results (Revereet al., 2004).

Conceptual developmentAs a theoretical basis for research of healthcare PI initiatives, the dynamic capabilities

model (DCM) emphasizes designing sources of competitive advantage. The DCMrequires dynamic alignment of organizational resources in a changing businessenvironment. A recent review identifies four dimensions of dynamic capability as the:

(1) propensity to make market-based decisions for changing customer needs;

(2) assessment and taking advantage of opportunities and threats;

(3) ability to make timely decisions; and

(4) realignment of the firms resource base (Barreto, 2010).

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of 177 studies of Six Sigma programs in healthcare suggests that the actual degree ofquality improvement results is only moderate (DelliFraine et al., 2010). Likewise,a review of 47 healthcare studies concluded that many Six Sigma and lean initiativeswere successful, but up to 62 percent failed due to lack of stakeholder acceptance

(Glasgowet al., 2010).Research also supports effective reconfiguration of dynamic capabilities from LMI

implementation. LMI can be effectively applied to healthcare by the achievement ofcritical success factors and key performance indicators for numerous lean techniques(Kollberget al., 2007). The application of lean thinking can transform an organizationtoward a patient safety culture (Wellman et al., 2011). For the Seattle Childrens Hospitalprogram that began in 2007 with first-hand observation of lean programs in Japan, theirlean management initiative resulted in dramatically reducing surgical-site infectionrates, patient length of stay, supply costs, and new facility expenses (Hagan, 2011).A review of lean studies reveals that a program requires training of appropriateemployees, initiating pilot projects, and deploying cross-functional teams (Poksinska,

2010). Hospital case studies have demonstrated that lean initiatives are successful inimplementing the 5S principles (Esain et al., 2008), decreasing rounding time perpatient (Vatset al., 2011), reducing waiting times (Lodge and Bamford, 2008), cuttingcosts for regulated medical waste (Stonemetz et al., 2011), and comprehensivelyredesigning a hospital for patient-centered care (Kenney, 2010). Finally, a longitudinalfield study of outpatient clinics revealed dramatic efficiency gains for a lean PI project,as well as improvements in service capacity, workflow, resource alignment,appointment scheduling, and no-show rates (LaGanga, 2011).

Simultaneous implementation of different types of PI initiatives provides enhancedoutcomes for healthcare organizations. Several studies have reported improvements inpatient safety by implementing CQI (Kennedy and Fiss, 2009; Shortell et al., 1995),Six Sigma (Jing, 2009; Gowenet al., 2008), and lean management tools (Proudlove et al.,

2008). However, an integrated PI program can consist of a combination of CQI, Six Sigmaand lean, which mutually reinforce each other when used simultaneously for superiorresults (Gowen and Johnson, 2009). Using a sample of 226 US manufacturing plants,Zuet al. (2008) found that SSI complemented traditional CQI practices. A healthcarestudy by Revereet al.(2004) proposed a framework for integrating Six Sigma with CQIfor improving patient care. Similarly, lean tools can enhance the effectiveness ofSix Sigma programs in hospitals, as demonstrated by several studies (Arthur, 2011b;Buell, 2010; Furterer, 2011; Pocha, 2010; Shah et al., 2008).

Based on the DCM, it is expected that implementing PI initiatives will mediate theeffect of error sources on patient safety results. Past literature has defined patient safetyresults in terms of heightened awareness and understanding of errors, as well as the

reduction in the frequency and impact of errors (Gowen et al., 2006b; Katz-Navonet al.,2005; McFadden et al., 2004). Furthermore, studies have reported improved patientsafety outcomes through the implementation of PI initiatives (McFaddenet al., 2006b;Shortellet al., 1995; Stocket al., 2007). Therefore, the literature leads to the followingresearch hypothesis:

H1. The effect of hospital error sources on patient safety results will be mediatedby: (a) continuous quality improvement (b) Six Sigma initiatives, and (c) leanmanagement initiatives.

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The DCM also suggests that organizational effectiveness can be enhanced by PIinitiatives (Reedet al., 2000) such as CQI, Six Sigma, and lean management programs.PI practices are proprietary processes that convert organizational resources intocustomer value, especially for patient relationship management in healthcare (Liu and

Lin, 2007). Dynamic capabilities evolve from learning mechanisms, such as experienceaccumulation, knowledge articulation, and knowledge codification. Halbesleben andRathert (2008) reported that enhanced experience and knowledge from CQI programsresulted in improved work effectiveness in hospitals. Environmental changeand heterogeneity enhances the impact of dynamic capabilities on organizationalperformance (Drnevich and Kriauciunas, 2011). A multi-industry study includinghealthcare found that PI initiatives served as dynamic capabilities throughenhancement of organizational purpose, processes, and people (Anand et al., 2009).

Empirical research also suggests that PI implementation is associated with improvedorganizational effectiveness, in terms of service quality, customer satisfaction, net costsavings, and patient satisfaction (Marley et al., 2004). Widespread adoption of PIprograms has expanded dramatically for healthcare organizations (Carrigan andKujawa, 2006). As a means of resolving quality issues, many healthcare organizationshave undertaken PI initiatives targeted towards improving organizational performance(Hiltonet al., 2008; Lloyd and Holsenback, 2006). Empirical studies have found the levelof CQI practices adopted by hospitals was positively and significantly related toorganizational performance (Shortellet al., 1995; Douglas and Judge, 2001). Similarly,case studies of SSI programs have resulted in diverse pragmatic improvements, such asclinical, operational, and service benefits (Bisgaard, 2009; Cravenet al., 2006; Neriet al.,2008). Therefore, the literature leads to the following research hypothesis:

H2. The effect of hospital error sources on organizational effectiveness results willbe mediated by: (a) continuous quality improvement (b) Six Sigma initiatives,and (c) lean management initiatives.

According to the dynamic capabilities theory, sustainable competitive advantage canalso result for hospitals that successfully implement PI initiatives (Barney et al., 2011;Thompson et al., 2008). Competitive advantage can be achieved through dynamiccapabilities that are characterized by four factors: valuable, rare, in-imitable, andnon-substitutable (Hitt et al., 2010). Valuable refers to the degree to which the firmsresources enable the organization to respond to external threats and opportunities. Rareconcerns the degree to which competing firms do not possess the organizationsparticular valuable resources. In-imitable focuses on the cost disadvantage faced byother firms that do not possess a certain resource. Non-substitutable captures the degreeto which a resource has no strategic equivalent. Practically, an organization has onlysome measure of each factor. Certain PI factors, such as DMAIC and value stream

mapping, can lead to value and rareness through enhanced effectiveness and efficiency(De Mast, 2006). Also, adaptation of PI factors to unique hospital conditions and patientneeds could increase the level of in-imitability and non-substitutability.

The literature has also reported PI initiatives as a potential source of competitiveadvantage. Reed et al. (2000) provided preliminary evidence that firms which implementCQI principles achieve a competitive advantage over those firms that do not adopt suchprinciples. Douglas and Judge (2001) found strong empirical support for the relationshipbetween the degree of adoption of CQI practices and the degree of sustainable


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previously (McFadden et al., 2004, 2006a, b, 2009; Stock et al., 2007). The four-itemorganizational effectiveness results scale consists of four items that were reported in paststudies (Gowen et al., 2006a, b). Sustainable competitive advantage is measured byBarneys (1991, 2002) scale which contains four items. In addition to the variables

presented above, we also examined three control variables that could have impacted thestudy variables hospital size (number of beds), quality staff (number of FTE employeesdedicated to process improvement and study of hospital errors), and PI programexperience (number of years that a hospital had a PI system in place).

The construct descriptive statistics, correlations and reliabilities (Cronbachs acoefficients) are presented in Table I. The Cronbachs ascale reliability values for theseven constructs consisted of a range of 0.68-0.87, which is beyond the minimumacceptable level of 0.60 for exploratory research (Flynn et al., 1990). Confirmatory factoranalysis using Varimax rotation with Kaiser normalization is utilized for all of theconstructs of this study, as advocated by Hinkin (1995). The results in Table II indicatediscriminant validity among the three mediators, by the observation that the five CQI

items loaded on component 3, the four SSI items loaded on component 2, and the five LMIitems loaded on component 1. Additionally, we used Harmans one-factor test to checkwhether common method bias was present (Podsakoff et al., 2003). This test

Mean SD HES CQI SSI LMI PSR OER SCA

HES 1.93 0.67 (0.76)CQI 3.97 0.62 0.142 * (0.68)SSI 3.29 1.04 0.234 * * * 0.415 * * * (0.89)LMI 1.10 1.37 0.077 0.186 * * 0.121 (0.87)PSR 3.37 0.64 0.190 * * 0.252 * * * 0.176 * 0.197 * * * (0.76)OER 3.18 0.70 0.242 * * * 0.314 * * * 0.282 * * * 0.191 * * 0.636 * * * (0.69)

SCA 2.40 0.85 0.151*

0.242* * *

0.296* * *

0.042 0.347* * *

0.491* * *

(0.75)Note:Significant at: *p , 0.05, * *p , 0.01 and * * *p , 0.005

Table I.Descriptive statistics,

correlations andreliabilities (Cronbachs a

coefficients inparentheses) for hospital

error sources (HES),continuous quality

improvement (CQI), SixSigma initiatives (SSI),

lean managementinitiatives (LMI), patient

safety results (PSR),organizational

effectiveness results(OER), and sustainable

competitiveadvantage (SCA)

Component1 2 3

PDCA/PDSA method 20.041 0.044 0.729Employee PI teams 0.146 0.131 0.724Employee recognition 0.089 0.247 0.587Satisfaction measures 20.055 0.008 0.568Competitive benchmarking 0.188 0.359 0.574

SPC/SQC tools 0.077 0.838 0.224DMAIC method 0.018 0.854 0.096PI tools training 0.009 0.845 0.120Project review and closure 0.081 0.847 0.1395S organization method 0.839 0.090 20.021Process mapping 0.759 0.044 20.006Value stream mapping 0.883 0.026 0.126Kaizen methods 0.830 20.023 0.008Just-in-time method 0.742 0.087 0.144

Table II.Confirmatory factor

analysis for continuousquality improvement, Six

Sigma initiatives, andlean management

initiatives indicators


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resulted in nine factors accounting for 64.1 percent of the variance, with the firstfactor at 19.1 percent. Because no factor accounted for most of the variance, thesingle method of data collection appears to be an acceptable risk. Finally, the items foreach scale were averaged to create the variables used in the subsequent regression

analysis.

ResultsTo test our hypotheses, we applied hierarchical regression analysis using theoreticallygrouped sets of variables (Cohen et al., 2002). In this approach, the independentvariable, hospital error sources, was first entered into multiple regression analysis.Then, each potential mediator was entered into the regression model, and an Fstatisticwas calculated to determine whether the change in variance explained (R2) by theadditional variable was statistically significant. Tables III-V show the cumulativeresult for each dependent variable by entering the independent variable, then CQI, SSI,and LMI individually, and finally all three potential mediators into the overallregression model. The findings from the statistical analysis indicate that the impact ofhospital error sources is significantly mediated by PI programs.

For each of the regression models reported in the following tables, the three controlvariables (hospital size, quality staff, and PI program experience) were entered beforeany of the independent and moderator variables. For all regressions, the coefficients forthe control indicators were not statistically significant. Therefore, the control variableswere not included in the subsequent analysis.

Variable Model 1 Model 2 Model 3 Model 4 Model 5

HES 0.242 * * * 0.201 * * * 0.268 * * * 0.228 * * * 0.175 * *

CQI 0.286 * * * 0.229 * * *SSI 0.312 * * * 0.147 *

LMI 0.174 * * 0.122R2 0.058 0.138 0.112 0.088 0.156Change R2 0.080 * * * 0.054 * * * 0.030 * * 0.097 * *

F 12.91 * * * 16.63 * * * 13.11 * * * 10.04 * * * 12.65 * * *

Notes: Significant at: *p , 0.05, * *p , 0.01 and * * *p , 0.005; table entries show standardizedregression coefficients

Table IV.Regression results for

hospital error sources(HES), continuous qualityimprovement (CQI), SixSigma initiatives (SSI),and lean managementinitiatives (LMI), withorganizationaleffectiveness results asthe dependent variable


HES 0.190 * * 0.158 * 0.158 * 0.176 * * 0.150 *

CQI 0.230 * * * 0.203 * * *

SSI 0.139 * 0.049LMI 0.184 * * 0.148 *

R2 0.036 0.088 0.055 0.070 0.109Change R2 0.052 * * * 0.018 * 0.034 * * 0.073 * *

F 7.82 * * 9.97 * * * 5.98 * * * 7.78 * * * 8.40 * * *


Table III.Regression results for

hospital error sources(HES), continuous qualityimprovement (CQI), SixSigma initiatives (SSI),and lean managementinitiatives (LMI), withpatient safety results asthe dependent variable

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The results in Table III supportH1a (p , 0.005),H1b (p , 0.05) andH1c (p , 0.01),when CQI, SSI or LMI is independently entered into a separate regression model. Thisdemonstrates that CQI, SSI and LMI act as a mediator for patient safety results if each PIvariable is considered alone. However, when entering CQI, SSI and LMI simultaneously

into another model, we find that only CQI and LMI are significant in mediating hospitalerror sources for patient safety results.

Similarly, Table IV supportsH2a(p , 0.005),H2b(p , 0.005) andH2c(p , 0.01),when CQI, SSI or LMI is independently entered into a separate regression model. Itsignifies that CQI, SSI and LMI act as a mediator for organizational effectivenessresults if each PI variable is considered alone. But, when entering CQI, SSI and LMIsimultaneously into another model, we find that only CQI and SSI are significant inmediating hospital error sources for organizational effectiveness results.

Table V supports hypotheses H3a (p , 0.005) and H4b (p , 0.005), but not H4c,when CQI, SSI or LMI is independently entered into a separate regression model. Thisexplains that CQI and SSI act as a mediator for sustainable competitive advantage ifeach PI variable is considered alone, whereas LMI does not independently mediate the

impact of error sources for sustainable competitive advantage. However, whenentering CQI, SSI and LMI simultaneously into another model, we find that only SSI issignificant in mediating hospital error sources for sustainable competitive advantage.

Conclusions and pragmatic implicationsAs hospitals set priorities for desired areas of improvement and strive to meet shrinkingbudgets, administrators must be more selective about PI program implementation.Hospitals face increased pressure to enhance patient safety, operational effectiveness,and competitiveness. This is the first study to explore the mediating effects of CQI, SSI,and LMI on medical error sources for enhancing these three types of hospital outcomes.Although there may be some overlap of PI items in actual practice, our confirmatory

factor analysis in Table II indicates that CQI, SSI, and LMI consist of three distinctconstructs. Also, the regression analysis results demonstrate that each of the three typesof PI programs mediates hospital error sources differently for each type of outcomes.Therefore, our findings can benefit healthcare practitioners as they select among PItechniques for desired hospital outcomes.

For hospital administrators trying to enhance patient safety results, our findingsindicate that CQI is the most effective PI approach and that LMI offers some added benefitsover and above CQI. It makes intuitive sense that CQI would enhance patient safety results


HES 0.151 * 0.119 0.086 0.148 * 0.086

CQI 0.226 * * * 0.140SSI 0.276 * * * 0.276 * * *

LMI 0.031 0.002R2 0.023 0.073 0.095 0.024 0.095Change R2 0.050 * * * 0.072 * * * 0.001 0.072 * * *

F 4.83 * 8.10 * * * 10.80 * * * 2.51 10.80 * * *


Table V.Regression results for

hospital error sources(HES), continuous qualityimprovement (CQI), SixSigma initiatives (SSI),and lean managementinitiatives (LMI), with

sustainable competitiveadvantage as the

dependent variable


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given that it emphasizes incremental improvement in quality of care with a focus ongradual long-termresults. Ourfindings indicate that CQIis the most often used PI initiative(with an average use of 3.97 on a 0-5 scale). These results are consistent with previousresearch forCQI in resolving medical errorsand providing a widerange of patient-centered

benefits (Evans and Lindsay, 2011; Ryan, 2007; Ryan and Thompson, 1998).It is a surprising finding that Six Sigmadid not enhance patient safety beyond thegains

for CQI and LMI, given that SSI focuses on accuracy. SSI tools such as statistical processcontrol, fishbone diagrams, and the disciplined statistical approach to problem-solving ofthe DMAIC process, emphasize achieving 3.4 or fewer defects per million opportunitieswhich equates to 99.99966 percent accuracy (Evans and Lindsay, 2011). It may be thatthe potential emphasis on bottom line results for Six Sigma can compete with patientsafety goals. As stated previously, comprehensive literature reviews suggest thatSSI implementation provides only a modest level of improvement for hospitals(DelliFraineet al., 2010; Glasgow et al., 2010). Our findings from Table I demonstratesimilar mid-level gains for our measures of hospital outcomes (PSR, OER and SCA).

A second issue for enhanced patient safety from PI programs is the level ofdeployment of SSI. Some case studies report success only for those hospitals with highSSI implementation (Buell, 2010; Hilton et al., 2008). It seems that considerable patientsafety results depend on the extensive use of SSI. For our study, hospitals report only amoderate level of SSI implementation (with an average use of 3.29 on a 0-5 scale) for oursample of hospitals. An extensive initial investment in resources is required for SSI, sofew hospitals may have been able to implement it comprehensively in recent economicconditions.

A third novel contribution of this study for patient safety is the finding that LMI iseffective for improving patient safety results, despite being the least commonly used PIinitiatives among the hospitals we surveyed (with an average use of 1.10 on a 0-5 scale),The limited application and results in healthcare is consistent with previous research

(Glasgowet al., 2010). We expect LMI is significant for patient safety results becauselean tools are quickly learned, implemented, and produce immediate results (Graban,2009; Protzmanet al., 2010). The 5S, process and value stream mapping, kaizen, and

JIT tools measured for LMI seem to be exceptionally suited for improving patientsafety. However, the internal and project-driven emphasis of LMI may reduce itsimpact on long-range organizational effectiveness and competitiveness.

Forhospital practitioners seeking improvement in organizational effectiveness, we findthat CQI and SSI are significant in mediating hospital error sources, but LMI is notsignificant over and above CQI and SSI.Organizational effectivenessrefers to the ability toachieve quality improvements, enhance patient satisfaction, produce net cost savings, andreduce the severity of errors. It seems logical that CQI would be associated with improvedorganizational effectiveness. It has been deployed in most hospitals for the past two

decades (Kazandjian, 1997), and has been reported to be successful in improving qualityand customer satisfaction from the organizational perspective (Sollecito and Johnson,2011). SSI may accordingly be linked to organizational effectiveness because it is designedto contain variation, so hospitals that use it tend to have more effective and consistentprocesses. Similarly, SSI hasbeen demonstrated to be useful in containing costs, improvingquality and enhancing patient satisfaction (Bisgaard, 2009; Kennedy and Fiss, 2009).

Finally, for hospital administrators desiring to gain a sustainable competitiveadvantage, SSI is significant in mediating hospital error sources; however, CQI and

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LMI are not significant over and above SSI. Our findings suggest that SSI can be adistinctive strategic resource that contributes to hospital competitiveness. This resultaugments previous healthcare literature that emphasized CQI for achieving acompetitive advantage in theory (Reedet al., 2000) and in practice (Douglas and Judge,

2001). The recent widespread use of CQI suggests that it may no longer provide adistinctive competence in terms of rareness and non-substitutability among hospitals.In contrast, LMI does not yield greater competitiveness possibly due to its limiteddeployment so far. Our study provides insight on greater competitiveness from SSI andpotentially for LMI in the future, through more prevalent application in healthcare.

Limitations and future researchA major limitation of our findings is the dependence on perceptual indicators. However,dependent variables in healthcare management research are most frequentlycharacterized by perceptual measures (Alexander et al., 2007; Caldwell et al., 2008;Goldstein and Iossifova, 2011; Halbesleben and Rathert, 2008; Khatri et al., 2007), with

some exceptions in using third-party objective measures (Menachemi et al., 2008;Thouinet al., 2008). Potential sources of objective outcome data were considered forthe current study, but they were not publicly available for all US hospitals at the time ofthis study. Common method bias was examined with Harmans one-factor test(Podsakoff et al., 2003) above, suggesting that the single method of data collectionappears to be an acceptable risk. Other limitations of this study include the use of arelatively small sample size, compared to the overall US hospital population, soexpanding the survey to greater number of hospitals could be beneficial. Furthermore,including other potential alternate mediating or moderating constructs can enhance thesophistication of the relationships relevant to the outcome variables. Future studies withobjective measures, such as patient satisfaction and quality of care data, could produce abroader view of the research findings.

As our study is exploratory, future research could enhance theoretical and practicalimplications of the study results shown here. Our findings can serve as an initial point ofdeparture for a more sophisticated research model. This could include examining the PIinitiatives in terms of their impact on outcomes other than patient safety, organizationaleffectiveness and sustainable competitive advantage. The different findings for each ofthe three PI initiatives suggest that additional mediating constructs, such as hospitalexecutive leadership, could also prove fruitful for an expanded framework. Overall,examining an expanded framework with additional mediators and dependentmeasures might accentuate the significance of their interrelatedness and provideadditional direction for healthcare practitioners designing superior PI interventions.

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Appendix. Questionnaire construct itemsRespondents provided a score for each item below on a scale of 0-5, where 0 was none, 1 wasvery low, 2 was low, 3 was moderate, 4 was high and 5 was very high.

Hospital error sources (HES)To what extent does each of the following has contributed to errors at your hospital?. Equipment failure/malfunction.. Demand surge caused by factors internal to the hospital.. Demand surge caused by factors external to the hospital.. Infrastructure: public services and internal backup services.. Unplanned circumstances and events.. Computer issues.. Employee willful misconduct.

Continuous quality improvement (CQI)To what extent has your hospital implemented each of the following tools?

. Plan, do, check/study, and act (PDCA/PDSA) quality improvement method.

. Teams of employees for quality/process improvement.

. Employee recognition, rewards, and promotion opportunity for quality program success.

. Patient satisfaction measures (e.g. voice of the customer) by surveys, focus groups, etc.

. Competitive benchmarking of best-in-class processes.

Six Sigma initiatives (SSI)To what extent has your hospital implemented each of the following tools?

. PI tools. Statistical process control chart, check sheet, histogram, Pareto chart, Fishbonediagram, etc.

. PI method, e.g. define, measure, analyze, improve, and control (DMAIC).

.

Training in PI tools for employees, such as change agents, Green Belts, Black Belts,Champions, etc.. PI projects, review, and closure.

Lean management initiatives (LMI)To what extent has your hospital implemented each of the following tools?

. 5S workplace organization: sort, set in order (straighten), shine, standardize, andsustain.

. Process mapping (flow chart, process map, etc.).

. Value stream mapping (VSM).

. Kaizen or Kaizen Blitzes (continuous improvement events).

. Just-in-time ( JIT) process management or inventory management.

Patient safety results (PSR)To what extent have results been realized?. Reduction in the frequency of errors.. Increased understanding of errors.. Heightened awareness of errors.. Reduction in the impact of errors.

Organizational effectiveness results (OER)To what extent have results been realized?

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. Quality improvement.

. Patient satisfaction increase.

. Net cost savings.

.

Reduction in the severity of errors.Sustainable competitive advantage (SCA)To what extent does your quality program achieve sustainable competitive advantage interms of:

. Value added. How well do your firms resources and capabilities enable your firm torespond to external threats and opportunities?

. Rareness. How much are your firms resources and capabilities not possessed bycompetitors?

. Costly-to-imitate.How much do firms without your resources and capabilities face a costdisadvantage to duplicate your program?

. Non-substitutability.How much is there no strategic equivalent for your program?

About the authorsCharles R. Gowen III, PhD, is a Professor of Management in the College of Business at NorthernIllinois University. His current research interests are in quality, healthcare, and strategicmanagement. He has published in several leading journals, such as the Journal of Operations

Management, Quality Manag ement Journal, Journal of Equip ment Lease Financing,International Journal of Production Research, Health Care Management Reviewand Journal ofHigh Technology Management Research and presented papers at numerous national andinternational conferences. He has worked in operations management at Eastman KodakCompany, in commercial credit at Bank One (now JPMorgan Chase), and in consulting for

Fortune100 companies. Charles R. Gowen III is the corresponding author and can be contactedat: [email protected]

Kathleen L. McFadden, PhD, is a Professor of Operations Management in the College ofBusiness at Northern Illinois University. Her current research interests are in the area of

healthcare operations, aviation safety, quality management, and process improvement. Herresearch has been published in a number of academic journals including the Journal ofOperations Management, International Journal of Operations and Production Management,

International Journal of Production Research, International Journal of Production Economics,Quality Management Journal, Health Care Management ReviewandDecision Sciences Journal of

Innovative Education. She has worked as a consultant and contract researcher for the FederalAviation Administration, and has served as an expert witness.

Sriranjita Settaluri is pursuing a Masters in Management Information Systems in the Collegeof Business at Northern Illinois University. She is also a Graduate Research Assistant within thecollege, and has more than four years of IT professional experience. She has worked as A SeniorSoftware Engineer for Infosys Technologies Limited and as a Software Trainee Engineer forMicrosoft India Limited.


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