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Health Policy and Technology (2012) 1, 28–34

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‘‘Meaningful Use’’ of ambulatory EMR: Does it improvethe quality and efficiency of health care?

Nan Xiaoa, Raj Sharmanb, Ranjit Singhc, Gurdev Singhc,Andrew Danzoc, H.R. Raob,d,n

aDepartment of Computer Information Systems & Quantitative Methods, The University of Texas-Pan American, United StatesbManagement Science and Systems, University at Buffalo, United StatescPatient Safety Research Center, University at Buffalo, United StatesdService Systems Management & Engineering, Sogang University, Republic of KoreaAvailable online 22 February 2012

ont matter & 2012012.01.009

thor. Tel.: +1 716

gmtrao@buffalo.

AbstractThe US government has initiated incentive programs to encourage the adoption of ElectronicMedical Records (EMR). To qualify for the incentive payment, healthcare providers need todemonstrate ‘‘meaningful use’’ of EMR systems, which requires the use of certified EMRs and theimplementation of a set of standard functionalities. In this paper, we examine how themeaningful use of EMRs would affect health care outcomes in outpatient settings. Our resultsshow that the use of core functionalities required by ‘‘meaningful use’’ criteria and the use ofcertified EMRs have a positive impact on the quality and efficiency of health care. In addition,we find the relationship between the meaningful use and quality of care is moderated by thelength of use. The implications of this study are also discussed.& 2012 Fellowship of Postgraduate Medicine. Published by Elsevier Ltd. All rights reserved.

Introduction

The US government is pushing for the adoption of ElectronicMedical Records (EMR) systems to transform the healthcareindustry. Significant financial incentives have been providedto encourage the ‘‘meaningful use’’ of EMR systems.Although the major motivations of implementing EMRsystems are to improve the quality of health care [1],reduce costs [2], enhance patients’ safety [3], and improveefficiency [4], findings regarding the relationship betweenEMR systems and health care outcomes are mixed. Forexample, Furukawa et al. [5] found no evidence that EMRsystems could reduce patients’ lengths of stay in hospitals.On the contrary, they found that advanced EMR systems

Fellowship of Postgraduate Medic

645 3425.

edu (H.R. Rao).

increase hospitals’ costs and increase nurse staffing level.Similarly, Romano and Stafford [6] find that there is nosignificant difference in terms of patient satisfactionbetween patients whose doctors have adopted EMRs andthose whose doctors have not. The causes of unsuccessfulEMR adoption include the long learning curve of using EMRsystems, physicians’ resistance to information systems andignoring systems alerts [7].

To understand the issues of using EMR systems, we intendto explore the factors facilitating the systems to achievedesirable outcomes, especially the efficiency and quality ofhealth care. Understanding the relationship between EMRadoption and efficiency and quality of health care willadvance our knowledge of the effectiveness of using EMRs. Itwill provide insights into how EMR systems should bedesigned and implemented. It will also inform regulatorson how to manage and coordinate the scope and pace of EMRadoption as well as healthcare providers on the decision of

ine. Published by Elsevier Ltd. All rights reserved.

‘‘Meaningful Use’’ of ambulatory EMR 29

adoption and use of EMRs. In this paper, we attempt toinvestigate the following two questions regarding EMR usageand quality and efficiency of health care delivery: (a) Does‘‘meaningful use’’ of EMR improve health care outcomes inoutpatient settings? (b) What other factors could affect theoutcome of EMR usage?

Our research makes the following contributions: First,since the publication of final rules on meaningful use ofhealth IT, our research is one of the first to empiricallyexamine the impact of using functionalities identified in thefinal rules on health care outcomes. Although the impacts ofdifferent EMR functionalities on health care outcomes havebeen examined in previous studies, few of them havefocused on meaningful use criteria. As meaningful usecriteria has become the primary regulation and will beguiding and shaping EMR adoption in the next few years,understanding its impact is needed. Second, while most ISliterature studies the impact of health IT in hospitalsettings, our research investigates the effect of EMRs onhealth care outcomes in ambulatory environments. Third,our research contributes to IT value literature by examininghow the characteristics of IT usage, including the extent ofuse, length of use and quality of systems, affect IT values.

In this paper, we used data from 222 primary carepractices to test our hypotheses. Our results show that theuse of core functionalities required by ‘‘meaningful use’’criteria has a positive impact on the quality and efficiency ofhealth care. We also find that the length of use moderatesthe relationship between meaningful use and the quality ofcare. In addition, using certified EMRs could improveefficiency and quality of health care.

Background

EMR

The costs of health care in the United States have beenrising dramatically in recent years, which have causedconcerns about its affordability and quality. Informationtechnology, especially Electronic Medical Records (EMR), isconsidered as one of the effective solutions to rein in costsand improve the quality of care. Electronic medical recordsare the electronic records of patient health information thatinclude patient demographics, progress notes, problems,medication, vital signs, past medical history, immunizations,laboratory data and radiology reports. They can be created,stored, and shared in information systems.

EMR systems could be classified into hospital EMRsystems, which are intended to facilitate the sharing andstorage of medical information across departments in ahospital, and ambulatory EMR systems, which are designedto store patients’ information in a physician practice, andexchange information with outside entities. These two typesof EMR systems differ in their functionalities, primary users,and scope of implementation. Based on the functionalities,EMR systems could be further classified in different ways:basic functionalities vs. decision support functionalities orclinical functionalities vs. administrative functionalities.

Although the implementation of EMRs is aimed to reducethe cost, improve the quality and efficiency of care, andprevent and manage diseases [8], the findings on the impact

of EMR adoption have been mixed—effects of EMRs onhealth care outcomes are not consistent and are contingenton various conditions.

The pace of EMR adoption in the US has been slow. Arecent study found only 7.6% of US hospitals adopt basicEMRs and 1.5% of US hospitals adopt comprehensive EMRs [9].In another study conducted in ambulatory settings, 13% ofphysicians have basic EMRs and only 4% used fully functionalEMRs [10]. In addition, the EMR adoption is found un-balanced in locations (e.g. urban vs. rural areas), teachingstatus (teaching hospitals vs. non-teaching hospitals), andsize (larger hospitals vs. small hospitals). The major barriersfor EMR adoption include the costs and physicians’ resis-tance to information technology.

Meaningful use

To increase the EMR adoption rate, the US governmenthas initiated financial incentives through the HITECH(The Health Information Technology for Economic andClinical Health) Act in order to encourage health careproviders to adopt EMRs. Under this Act, out of a total of $38billion ‘‘eHealth’’ investments, $19 billion have been setaside and qualified professionals may receive up to $44,000for adopting an EMR. Also, beginning in 2015, health careproviders that do not use EMRs will see a reduction in theirMedicare reimbursement as a penalty.

The essential part of this incentive program is the‘‘meaningful use’’ criteria. To qualify for the incentivepayment, health providers (including both physicians andhospitals) must demonstrate a meaningful use of EMRs.According to the Center for Medicare and Medicaid Services,‘‘meaningful use’’ refers to the need for ‘providers’ to showthat they are using EMR technology in ways that can bemeasured significantly in quality and in quantity. ‘‘Mean-ingful use’’ has two core requirements: adopting certifiedEMRs and using them to achieve a set of objectives. Thetimeline of achieving the meaningful use of objectswas broken into three stages. The final rules for stage 1(2011 and 2012) have been officially published in 2010, andas of 2011, the rules for stage 2 (to be implemented in 2013)and stage 3 (to be implemented in 2015) are still in draft.Specific ‘‘meaningful use’’ criteria are slightly different forambulatory and inpatient settings, In ambulatory settings,the first stage identifies 25 objectives and divides them intotwo groups: the core group, which consists of 15 function-alities (all of them must be implemented), and the menugroup, which consists of 10 additional functionalities fromwhich health care providers can choose any 5 to implement.The functionalities in the core group include both the basicEMR functionalities such as record patient demographics anddecision support tools (e.g., drug–drug and drug–allergyinteraction checks). The functionalities in the menu groupare more advanced, such as drug formulary checks andpatient reminders [11]. On the other hand, the Office of theNational Coordinator (ONC) for Health Information Technol-ogy has issued standards for EMR certification programs.Those standards cover a variety of EMR specificationsincluding its interoperability, functionality, utility andsecurity. Certified EMR products must meet all the standardsand pass the tests conducted by ONC Authorized Testing and

N. Xiao et al.30

Certification bodies (ATCBs). The detailed information onmeaningful use can be found at [12,13].

Despite the critical role meaningful use criteria play inthe regulation and adoption of EMRs in the United States,few empirical studies have explicitly examined their impactson health care outcomes. Therefore, in this paper, weattempt to investigate whether the adoption of certifiedEMRs and core functionalities required in the first stage ofmeaningful use will improve quality and efficiency ofhealthcare. While most IS literature studies the impact ofhealth IT in hospital settings, our research focuses onambulatory settings. Physician practices have less financialand technical support compared to hospitals, and are thusmore cautious about EMR adoption and the benefits of EMRs.

Hypothesis development

Extent of meaningful use

The ‘‘extent of meaningful use’’ refers to the degree towhich the functionalities required by meaningful use criteriahave been used. The pace of EMR adoption varies fordifferent health care providers, ranging from the adoptionof standalone single-modules to comprehensive EMRs. Themore extensive adoption indicates more functionalities andhigher integration, both of which are critical to efficiencyand quality of health care delivery. A previous study showsthat one of the major causes of low efficiency and high costis the ‘decentralized and fragmented nature of the healthcare delivery’ [14]. More extensive usage facilitates thepatients’ information flow within physicians’ practice aswell as between outside entities including hospitals, labs,pharmacies, and other health care provides. More availableinformation helps physicians to make more informeddecisions and thus reduce unnecessary tests and medicalerrors. In contrast, less extensive usage usually limits tospecific functionalities or certain groups of users, whichrestricts the ability of physicians to share information andfully utilize EMRs. This argument has been supported byAngst et al. [15], who found that hospitals that integratefundamental technologies earlier tend to have betterperformance. Therefore, we propose that

H1A. More extensive meaningful use of EMRs has apositive impact on the quality of health care in ambulatorysettings.

H1B. More extensive meaningful use of EMRs has a positiveimpact on the efficiency of health care in ambulatorysettings.

Length of EMR use

As the use of EMR systems becomes more extensive, it alsoincreases the time to realize its desired benefit. In thispaper, the length of use refers to the time since theadoption of the current EMR system and it captures thematurity of the EMR adoption. EMR implementation is acomplicated process and it takes time for users to getfamiliar with the systems. Therefore, users usually have along learning curve to climb before materializing thebenefits of EMRs, especially those used more extensively.

Longer interaction with the systems will increase theknowledge of using EMR and familiarity with the EMR, whichin turn could improve the utilization of functionalities aswell as reduce the errors associated with misunderstandingor misuse of EMR. In addition, previous studies show thatonly a small proportion of physicians received sufficienttraining on EMR, and some physicians do not know exactlywhat functionalities their EMR system has [16]. Longer use ofEMRs will make up for the lack of training and increasephysicians’ knowledge of the systems, which in turnwill improve the efficiency and effectiveness of thesystems [17]. Moreover, EMR adoption requires users toadjust their routines to adapt to new processes. A longerusage gives users sufficient time to make transitions fromold systems to EMR systems. Furthermore, there may besome errors hidden in EMR systems or some physicians do notuse the EMR systems correctly. A longer usage could exposethose errors and allow users to find solutions, which in turnwould reduce the potential risks and minimize negativeimpacts. Furthermore, longer use could affect physician’attitudes toward IT, computer skills and self-efficacy, whichcan also positively affect their EMR adoption. Previousstudies have shown that longer use of information systemshas impacts on the outcomes. For example, Setia et al. [17]found that hospitals’ experiences with business activitysystems are positively related to their financial perfor-mance. Devaraj and Kohli [18] suggested that the frequentuse of decision support systems helps to reduce mortalityrates in hospitals.

Therefore, we propose that the length of use moderatesthe relationship between the extent of meaningful use andhealth care outcomes. It may take longer for the moreextensive EMRs to reap the benefits, which lead to thefollowing hypotheses:

H2A. The extent of meaningful use of EMRs has a positiveimpact on the quality of care in practices with longer EMRusage than in those with shorter EMR usage in ambulatorysettings.

H2B. The extent of meaningful use of EMRs has a positiveimpact on the efficiency of care in practices with longer EMRusage than in those with shorter EMR usage in ambulatorysettings.

Certified EMR

Certified EMRs refers to the EMRs that receive certificationsfrom authorized organizations, such as ONC (Office of theNational Coordinator for Health Information Technology), toensure their quality. Certifications have been used in the ITindustry to signal the quality of products and indicate thatcertified products have met certain standards [19]. To becertified, an EMR system has to go through rigorous testingprocesses concerning its functionality, usability, interoper-ability, privacy and security. Certified EMRs tend to havemore features and thus are more likely to meet users’requirements to improve care and reduce costs. In addition,although the certification process focuses on softwarepackages, it is likely that the vendors of the certified EMRshave more experiences and qualification to implement thesystems successfully.

Figure 1 Research model.

‘‘Meaningful Use’’ of ambulatory EMR 31

Certification information could reduce information asym-metry for clients [19]. Health care providers use thecertification information to evaluate EMR products, whichplays an important role in their software purchase decision.Also, as we discussed earlier, certified EMR is the centralpart of meaningful use legislation and is used as a standardto determine the qualifications for the incentive programsthat control the outcomes of EMR adoption. Althoughcertified EMRs are perceived as reliable and of high quality,there is no empirical study to date investigating the effectof EMR certification on health care outcomes. Other studiessuggest that customized home-grown EMRs may servecustomers better due to their flexibility, fitness to custo-mers’ unique requirements and users’ high involvement inthe design process. In addition, compared with hospitals,most practices have a smaller number of users and a limitedscope of implementation, thus the advantage of certifiedEMR systems may not be salient in ambulatory settings. Inthis study, we investigate whether certified ambulatoryEMRs outperform non-certified ambulatory EMRs in terms ofhealth care outcomes. Therefore, we propose and test thefollowing hypotheses.

H3A. Certified EMRs have a more positive impact on thequality of care than non-certified EMRs in ambulatorysettings.

H3B. Certified EMRs have a more positive impact on theefficiency of care than non-certified EMRs in ambulatorysettings.

The research model is depicted in Figure 1.

Methods

Data

A national survey was conducted to collect the data. Sincethe focus of our research is on ambulatory EMRs, our surveyonly targeted physician practices. The contact informationof the practices was obtained from American MedicalInformation (AMI) database, which contains mail addressesof medical offices in the United States. 5200 primary carephysician offices were selected from this database using astratified sampling method to ensure that our samples werebalanced in terms of rural vs. urban. Surveys were mailed toall 5200 offices, and a reminder followed by a second mailwas sent to the non-respondent offices. 1001 completed

surveys were received during this process. The survey anddata collection are described in more detail in Singh et al.[20]. Because this current study investigates the impact ofactual EMR usage on health care outcomes, our data analysisonly includes the physician offices which had alreadyadopted EMR systems and whose data are complete for allvariables included in our model, which lead to 222observations in our final analysis.

Measurement

All measures used in the survey were either adapted fromexisting studies or developed based on extensive literaturereviews and interviews with physicians. A panel of primarycare physicians reviewed the survey to ensure its contentvalidity and clarity.

Dependent variables

Efficiency of health care was measured by three items, usinga 5-point Likert scale with anchors from ‘‘much worse’’ to‘‘much better’’, to assess how the time spent on thefollowing tasks had changed: time chasing charts, phone/faxtime dealing with and tracking labs and referrals, and timedealing with medication refills. The Cronbach’s alpha forthis measure is 0.861, which indicates the reliability issatisfactory.

Quality of health care was measured by five items, using a5-point Likert scale with anchors from ‘‘much worse’’ to‘‘much better’’, to assess how the following service levelschanged: accurate coding, level of services to patients pervisit, ability to accurately capture services provided at eachvisit, capabilities for chronic disease management prompts,and turn-around time on claims from submission topayment. The Cronbach’s alpha for this measure is 0.864.

Independent variables

Length of use was measured by a single item, which askedthe respondents how long they have used current EMR intheir offices.

Certified EMR was measured by a single item which askedthe respondents whether the EMR they are using is certified.It was coded as 1 if the EMR is certified and 0 otherwise.

Extent of meaningful use was measured by the number offunctionalities used and the corresponding use frequency.

N. Xiao et al.32

Respondents were asked to rate the use of 14 of the 15 corefunctionalities identified by meaningful use criteria (oursurvey did not ask about the functionality of ‘record smokingstatus for patients’) using a 5-point Likert scale with anchors‘‘used most of time’’, ‘‘used some time’’, and ‘‘did not use’’.A function was coded as 1 if it was used most of the time,0.5 if it was used some of the time and 0 otherwise. We thenadded all scores and used the total score of the 14functionalities to measure the extent of meaningful use.

Control variables

We controlled for a few variables that could affect thehealth care outcomes. First, we included variables relatedto the size of the practice, which has been found to have animpact on EMR adoption [21]. As the size of a physician’spractice increases, the amount of information to beprocessed and the difficulty in communication also in-creases. In addition, practices with different sizes will differin the resources they can leverage, which in turn may affecttheir health care outcomes. The size-related variablesinclude the number of patient visits, the number ofclinicians, and the number of sites. Second, followingprevious studies (e.g., [22]), we also controlled for variablesrelated to physician offices’ revenues including the percen-tage of Medicare and Medicaid billings.

Analysis and results

We used the following models to test our hypotheses.Ordinary least squares (OLS) was used to estimate theresults. Values of both variables in the moderation effectwere mean-centered to reduce the multi-collinearity. Thevariance inflation factors were all below 4 for everyregression model, indicating that multi-collinearity wasnot an issue. We then estimated the models in three steps:

Table 1 The OLS results.

Variables Quality of care

Model 1 Model 2

% of medicaid billing 0.098 0.105% of medicare billing �0.044 �0.044No. of patient visits 0.020 �0.024No. of clinicians �0.087 �0.059No. of sites �0.107 �0.110Certified EMR 0.123�

Length of use 0.215���

Extent of meaningful use 0.126�

Length of use� extent of meaningful useR square 0.035 0.127F 1.152 3.887���

DR square 0.093DF 7.544���

Number of observations 222 222

npo0.1.nnpo0.05.nnnpo0.01.

in the first step, only control variables were entered in themodel; in the second step, all independent variables wereentered in the model. In the third step, the interactionterms were entered in the model. The results of theestimation are summarized in Table 1

Quality of care ðor efficiency of careÞ¼ b1þb2ðExtentUseÞþb3ðLengthUseÞþb4ðExtentUse� LengthUseÞþb5ðCertifiedEMRÞþb6ðPatientVisitsÞþb7ðNumCliniciansÞþb8ðNumSitesÞþb9ðMedicareÞþb10ðMedicaidÞþe

Hypothesis 1A and 1B propose that a more extensive useof functionalities identified by meaningful use criteria leadsto higher quality and efficiency. The results indicate that theextent of meaningful use has a significant positive relation-ship with health care outcomes (b=0.167, po0.05;b=0.177, po0.05). Thus H1A and H1B are supported.

Hypothesis 2A and 2B propose that the relationship betweenthe extent of meaningful use and the health care outcomes ismoderated by the length of EMR use. Our results show thatwhile the length of EMR use moderates the relationshipbetween meaningful use and quality of care (b=0.121,po0.1), its effect on the relationship between meaningfuluse and efficiency of care is not significant (b=0.110, p=n.s.).Therefore, H2A is supported but H2B is not.

Hypothesis 3A and 3B propose that using certified EMRs willachieve higher quality and higher efficiency of care. Our resultsshow that the effect of certified EMRs on quality and efficiencyof care is positive and significant (b=0.117, po0.1; b=0.173,po0.01). Therefore H3A and H3B are supported.

Discussion

In this paper, we empirically tested the impacts of mean-ingful use criteria on health care outcomes. Using a survey

Efficiency of care

Model 3 Model 4 Model 5 Model 6

0.117 �0.096 �0.090 �0.080�0.043 �0.083 �0.083 �0.082�0.020 0.162� 0.117 0.121�0.065 �0.161� �0.141 �0.146�0.124 �0.130� �0.119� �0.132�

0.117� 0.179��� 0.173���

0.213� 0.129� 0.126�

0.167�� 0.139�� 0.177��

0.121� 0.1100.140 0.040 0.132 0.1423.842��� 2.245�� 4.031��� 3.903���

0.013 0.082 0.0113.160� 4.031��� 3.903���

222 222 222 222

‘‘Meaningful Use’’ of ambulatory EMR 33

data from 222 physician practices, we investigated how theuse of functionalities required by meaningful use criteriaand the use of certified EMRs could affect the quality andthe efficiency of care in outpatient settings.

First, our results reveal that a more extensive use of thefunctionalities defined in meaningful use criteria couldimprove both the quality and the efficiency of care, whichsuggests that more comprehensive and integrated EMRs maygenerate more benefits for health care providers. Second,we found that the length of EMR use moderates therelationship between the extent of use and the quality ofcare. This result indicates that the use of more functional-ities could bring more improvements to the quality of care,and using them for a longer period of time would make theimprovement even stronger. However, we did not find asignificant moderating effect of the length of use on theextent of EMR use and the efficiency of care. Third, ourfindings show that the use of certified EMRs could also have apositive impact on the quality and the efficiency of care. Ifwe consider the EMR certification as an indicator of thequality of EMR vendors and products, this research impliesthat the EMR product quality and its vendor’s qualificationmatter when it comes to the realization of the benefits ofEMR adoption. Well-designed EMRs and experienced vendorscould increase the chances of success in EMR adoption.

Implications

Implications for theory

This paper contributes to the literature on health IT. First, itsuggests that the contradicting findings in previous researchon the relationship between EMR adoption and healthcareoutcomes may be attributed to the differences in the extentand length of EMR usage. Therefore, when investigating orcomparing the outcomes of EMRs, researchers need to takeinto account factors such as the number of functionalitiesused, the length of use, and the quality of EMR products.Second, our results are consistent with previous studiesconducted in hospital settings which found that the lengthof usage plays an important role in EMR adoption [22]. Dueto the learning curve and the complexity of EMR adoption,the benefit of EMR adoption may not appear until the latestages of adoption. Third, our research contributes toliterature on IS success model [23] and IT capacity byproviding evidence that system quality (certified EMR) andsystem capacity (the extent of meaningful use) will affectthe outcome of IT usage.

Implications for practice

Our research also has implications for policy makers andhealth care providers. First, our study is one of the first totest how meaningful use criteria would affect healthcareoutcomes associated with EMR adoption. It shows thepotential of the meaningful use criteria in improving thebenefits of EMR adoption. Using certified EMRs and the corefunctionalities defined by meaningful use will not onlyqualify its users for financial incentives of EMR adoption, butmay also bring substantial benefits by improving the qualityand the efficiency of care. For healthcare providers, it is

critical to choose the scope and products when makingdecisions on EMR adoption. In addition, the health careproviders should manage their expectations regarding thelength of time it will take to see the payback of their healthIT investment, especially when using more comprehensiveEMRs.

Limitations and future research

This study has a few limitations. First, this study used cross-sectional data. Therefore, the causality may not beinferred. Future research could use longitudinal data tofurther test our model. Second, the measures for the healthcare outcomes in this paper are self-reported, so futureresearch may use objective measures to validate the model.Third, this study focuses on outpatient settings, and futureresearch might study the impacts of meaningful use criteriain hospital settings. Fourth, this study only investigated howthe total number of functionalities used in a practice affectshealth care outcomes, and future research could examinehow the impacts of different groups of functionalities (e.g.,basic functionalities vs. decision support functionalities) onhealth care outcomes vary. Fifth, our research modelincludes only one moderator—the length of EMR usage.The moderating effects of other factors including thecharacteristics of practices (e.g., specialty and rurality)and characteristics of EMR products (system usability) areworth investigation in future research.

Acknowledgment

This study was supported by a grant from the United StatesDepartment of Health and Human Services, HealthResources and Services Administration, Office of RuralHealth Policy, Grant number R04RH08597. The research ofthe last (correspondent) author has been funded in part byNSF under Grant 0916612 and by Sogang Business School’sWorld Class University Project (R31-20002) funded by KoreaResearch Foundation and Sogang University Research Foun-dation. The usual disclaimer applies. An early version of thispaper was presented as research in progress at InternationalConference on Information Systems (ICIS) 2011, Shanghai.

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