Managed Care Penetration and Other Factors Affecting Computerized Physician Order Entry in the Ambulatory Setting

December 1, 2006
Nir Menachemi, PhD, MPH
Nir Menachemi, PhD, MPH

,
Eric W. Ford, PhD, MPH
Eric W. Ford, PhD, MPH

,
Askar Chukmaitov, MD, PhD
Askar Chukmaitov, MD, PhD

,
Robert G. Brooks, MD, MBA
Robert G. Brooks, MD, MBA

Volume 12, Issue 12

Objectives: To estimate the current uses level of ambulatorycomputerized physician order entry (A-CPOE) among physiciansand to examine the relationship of managed care penetration aswell as other market and practice characteristics to use of A-CPOEby physicians.

Data Sources: This study uses both primary and secondary datasources. The primary data source was a large-scale survey of physicians' use of information technologies in Florida. Secondary dataon managed care penetration were obtained from the FloridaAgency for Health Care Administration, and other market-leveldata were extracted from the area resource file.

Methods: A hierarchical logistic regression model was used toexamine the correlation of county-level and practice-level characteristicswith physicians' self-reported use of A-CPOE systems.

P

Results: Overall, 1360 physicians (32.4%) indicated use of anA-CPOE system. Findings suggest that 1% more managed care penetrationwas associated with 2.1% lower use of A-CPOE (= .003).Additionally, practice size, multispecialty affiliation, and primarycare practice were significantly and positively correlated withthe use of A-CPOE. Physician age was negatively associatedwith A-CPOE use.

Conclusion: Managed care organizations may experience significantfinancial savings from A-CPOE use by physicians; however,managed care penetration in a community negatively affectsA-CPOE use among physicians in their practices. Further studyregarding the causal nature of this association is warranted.

(Am J Manag Care. 2006;12:738-744)

Prescribing of medications for patients occurs frequentlyin ambulatory facilities. An estimated66.8% of clinical encounters in this setting resultin a physician prescribing or continuing a medicationfor a patient.1 Furthermore, 82.2% of prescription writingin the ambulatory setting takes place in a physician'sprivate office.2 Given the frequency with whichmedications are prescribed, it is important to note thatpreventable adverse drug events are common in theambulatory clinical setting.3

Ambulatory computerized physician order entry(A-CPOE), a health information technology (HIT) notedfor its potential ability to reduce medication errors andimprove quality,4-6 is a software application that supportsthe ordering of medications, diagnostic tests,interventions, and referrals by outpatient providers.7Similar to inpatient systems, A-CPOE systems includelab test ordering functions. However, electronic drugprescribing is by far the most common use of A-CPOEsystems.4

Analysis has shown that use of A-CPOE can bringsubstantial financial savings to consumers, physicians,and payers. Potential savings have been estimated to beas much as $44.2 billion annually in the United States ifsuch systems were universally adopted.7 Additionally,stories in the lay press have highlighted the benefits ofA-CPOE systems to patients and health payers.8 As aresult, the national strategic plan for the adoption of HIThas included A-CPOE, and the Medicare ModernizationAct of 2003 has sought to promote the use of A-CPOEsystems.9

Compared with the growing literature on hospital-basedCPOE systems,10-18 empirical research on the useof A-CPOE systems is relatively rare and often consistsof case studies. Among the available studies, Schectmanet al found that the use of an A-CPOE system in one academicambulatory clinic was strongly associated withphysicians' attitudes toward the potential benefits of thesystem.19 Overhage et al found that after a brief learningperiod, little or no ongoing training was required forphysicians using a well-designed A-CPOE system.20 Pizziet al found that early adopters of A-CPOE systems weremore likely to be generalists, have fewer years in practice,and work in technology-equipped offices.21However, this later study's generalizability was limitedfor a variety of reasons, including a narrow sample ofonline users, a very low response rate (3.7%), and the useof descriptive statistical methods that did not control forother important factors (eg, practice characteristics,market variables). To our knowledge, no study has documentedthe organizational factors (eg, practice size,type, specialty) that relate to the use of A-CPOE in privatephysicians' offices. Nor has any study examined therelationship of market-level factors (eg, managed carepenetration, competition) with A-CPOE adoption decisionsin the office setting.

The purpose of this paper is to fill those gaps in theliterature. First, we sought to estimate the currentA-CPOE utilization level among physicians in privatepractices. In particular, we were interested in the functionof electronic prescription order entry. Second, weexamined the correlation of managed care penetration,as well as other market, organizational, and individualfactors, with the use of A-CPOE among physicians. Assuch, this study makes 2 new contributions to the studyof health information technology (IT). First, it establishesa benchmark for A-CPOE adoption that can be usedto measure progress in the diffusion of this technology.Second, it comprehensibly evaluates physicians' A-CPOE utilization levels in the practice context andcompetitive market environments. Such informationwill allow policymakers and physicians to more effectivelytarget their A-CPOE promotion efforts.

METHODS

The analyses presented herein used both primaryand secondary data sources. The primary data sourcewas a comprehensive large-scale survey (n = 14 921) ofphysicians' use of HITs in Florida. Secondary data onmanaged care penetration were obtained from theFlorida Agency for Health Care Administration, andother market data were extracted from the area resourcefile (ARF). The following sections describe each of thesedata sources, as well as the variables and analyticalapproach used in the study. A list of variables and theirsources is in Table 1.

Primary Data

In the spring of 2005, a large-scale survey of physicianspracticing in Florida was conducted. The survey,which was approved by the Florida State Universityinstitutional review board, targeted all primary carephysicians (family doctors, general internists, generalpediatricians, and obstetrician-gynecologists) in thestate. In addition, 25% of the other physicians practicingin the ambulatory setting (eg, medical and surgical specialists,general surgeons, dermatologists, psychiatrists)were randomly selected from the Florida Department ofHealth's list of physicians with clear and active licenses.The survey included questions regarding types of IT (eg,e-mail, personal digital assistants [PDAs], electronichealth records) used by physicians in the office setting.A complete description of the survey methodology,22,23including an analysis of potential response bias (nonedetected),24 was previously published. Briefly, the surveywas developed based on a comprehensive literaturereview and refined with the aid of experts' advice toestablish content and face validity. Before deployment,the survey instrument was cognitively tested with apanel of physicians for clarity and readability. Thisprocess resulted in several iterations before the finalversion of the questionnaire.Numerous vendors and system variants exist forA-CPOE. For example, electronic order entry can occurvia a stand-alone software application on a personalcomputer (PC), a handheld device (eg, a PDA), or anexisting electronic health record (EHR) system.4,21,25,26As mentioned above, the survey asked respondents toindicate whether or not they used a PC, PDA, and/orEHR system in the scope of their practice. Whenresponding in the affirmative to any of these questions,each respondent was further asked to select from a listthe functions that they used on each of these platforms.For example, those using a PDA were asked toindicate by a check mark whether they used their PDAfor things such as drug references, medication interactions,electronic order entry (eg, labs, x-rays), electronicprescriptions, and various other clinical andadministrative functions. In the current study, wewere interested in the A-CPOE functionality regardlessof system variant (eg, PC, PDA, EHR). In addition,given the nature of the data, it was feasible for a givenphysician to have A-CPOE capabilities via more than 1such platform. Therefore, the selected outcome variablefor the current study was physicians' self-reporteduse of at least 1 of these forms of A-CPOE in theiroffice practice.

Physician-level independent variables from the surveywere measured as follows. Practice size was categorizedinto 4 levels representing the number of physicians at agiven practice location (solo, 2-9, 10-49, or 50+). Themedical-training variable was dichotomized to facilitatecomparison between primary care physicians versusother specialists. Last, physicians practicing in rural communitieswere identified by 1 of the following criteria:1) their office was located in one of Florida's 33 statutorilydesignated rural counties, 2) their office waslocated in a rural part of a nonrural county as designatedby the Rural Urban Commuting Area codes,27 or3) their address was in the current Health Resourcesand Services Administration list of defined Florida ruralzip codes. Collectively, along with physician demographicinformation, these practice characteristicsallowed for the examination of the factors that may berelated to the use of A-CPOE.

Secondary Data

Using the latest available version (2004) of the ARF,various market-level indicators were matched, by county,to the primary data collected via the physician ITsurvey described above. The ARF dataset is compiled bythe Health Resources and Services Administration andcontains county-level information aggregated fromnumerous national sources.28 In particular, we wereinterested in managed care penetration rates. However,the current version of the ARF data contained outdated(1999) information for this variable. Assuch, managed care penetration rates forthe first quarter of 2005, for each Floridacounty, were obtained from the FloridaAgency for Health Care Administration.This agency licenses all health insurers andmanaged care organizations in the stateand collects this information for statutorilyrequired reporting purposes. The countylevelmanaged care penetration rate wascalculated by taking the number of residentsenrolled in an HMO and dividing it bythe total number of residents in that county.Higher managed care penetration rateshave been shown to slow the diffusion ofsome medical technologies.29,30 However,less is known about the relationshipbetween managed care penetration and useof HIT among physicians. Theoretically,use of HIT is consistent with the goals ofmanaged care; that is, to improve informationgathering, increase administrative andclinical efficiencies, and promote clinicaleffectiveness. Therefore, a continuouslymeasured market-level (county) managedcare penetration rate was included in theanalysis. Additionally, a number of the documentedbenefits4,6,7 associated with ACPOEmay make it an attractiveinvestment for physicians, particularlywhen practicing in more competitive environments.To control for competition, wecomputed the county number of physiciansper (1000) capita using the ARF data.Last, we included several other county-levelmeasures to control for environmentalfactors that may be related to A-CPOEuse. These measures included poverty andunemployment rates, percentage of thepopulation that is white/non-Hispanic, percentage of thepopulation age 65 years or older, and newborns as a percentageof the population.

Statistical Analyses

P

To analyze the data, standard descriptive statisticswere calculated to examine the data for anomalies andto ensure that the assumptions of all analyses were met.To examine the independent relationship of the market-leveland practice-level characteristics to the outcomevariable, a hierarchical logistic regression model wasused. The model utilized the "enter" method for variableinclusion and a 2-block nested approach. The firstblock represented county-level characteristics such aspercent managed care penetration, poverty rate, physiciansper capita, geographic location (rural vs urban),and other county-level demographic information (seeTable 1). The second block represented practice-levelcharacteristics including physician age and sex as wellas practice scope (primary care or specialty practice),size, and type (single specialty vs multispecialty). Thismethod was selected because physician-level and practice-level characteristics are likely influenced by localmarket forces. As such, controlling for these factors in anested model was warranted. It should be noted that thecurrent statistical approach had a cross-sectional designthat cannot assess causality. Therefore, the resultsshould be interpreted as associations. All analyses wereconducted with SPSS version 13.0 (SPSS Inc, Chicago,Ill), and significance was assessed at the < .05 level.

RESULTS

Overall, 4203 physicians completed the survey andcould be matched to the ARF data, representing a 28.2%response rate. Demographic and practice characteristics,along with descriptive information on the ARF variablesused, appear in Table 1. Respondents' demographicswere consistent with known physician demographicpatterns in Florida.31 Briefly, the average age of physicianswas 50.6 years with a range of 30 to 86 years. Themajority of respondents were Caucasian (68.4%) andmale (75.9%), and worked in a single-specialty practice(85.6%).

P

P

P

P

In descriptive analysis, the presence of an academicmedical center did not correlate with being in a high orlow HMO penetration area (&#967;2 = .622, = .430). However,those in rural areas (&#967;2 = 158.4, < .001) andthose in central Florida (&#967;2 = 903.7, < .001) weremore likely to be in low HMO penetration areas.Alternatively, those in the southern part of the statewere more likely to be in high HMO penetration areas(&#967;2 = 903.7, < .001).

P

P

P

P

P

P

A total of 1360 physicians (32.4%) indicated theyused an A-CPOE function in their office practice. Whenall variables in the hierarchical model were controlledfor, 4 factors had a significant independent relationshipwith the use of an A-CPOE system among physicians (seeTable 2). Among the county-level variables examined,only the managed care penetration variable was significantlyand negatively correlated with A-CPOE availability.Specifically, 1% more managed care penetration wasassociated with 2.1% less use of A-CPOE (= .003).Four practice-level characteristics were related toA-CPOE adoption as well. For example, compared withphysicians in solo practice, those in groups of 10 to 49physicians (odds ratio [OR] = 2.78, < .001) or 50+physicians (OR = 7.36, < .001) were significantly morelikely to indicate using A-CPOE. Moreover, those physicianspracticing in primary care (OR = 1.43, = .001)or in a multispecialty practice (OR = 1.43, = .013)were more likely to use an A-CPOE system. Physiciansex did not seem to have an effect; however, age wasnegatively related to A-CPOE use. Specifically, a 1-yearincrease in age was associated with a 2.5% decreasein the frequency of physicians reporting A-CPOE use(< .001).

DISCUSSION

The literature about CPOE usage in hospitals isextensive10-18 and growing rapidly. However, less isknown about the use of CPOE in ambulatory settings.Taking into consideration the unique nature of ambulatorymedical practice and the importance of A-CPOE inensuring medication safety, the present study examinedthe overall utilization rate of A-CPOE and the factorsthat are related to the adoption of this technology in theoutpatient setting.

Overall, in mid-2005, about one third of physiciansresponding to the Florida survey indicated using anA-CPOE function in their office practice. This level ismarkedly higher than the estimated 2% of all prescriptionswritten in 1999 that were done electronically32 andthe reported 19% of physicians that used an A-CPOEsystem in 2003.21 The rate for A-CPOE usage amongrespondents is also higher than recent data on CPOEusage (approximately 10%) in the inpatient setting.33Given the more visible pressures from hospital stakeholders(eg, the Leapfrog group) to adopt CPOE, themotivation for A-CPOE may not be as strong. However,the difference in adoption rates between the inpatientand outpatient settings may reflect the less complex, andless costly, installations associated with the ambulatorysetting.34,35 Also, at this point, it is unclear what rolethe e-prescribing adoption incentives from the MedicareModernization Act of 2003 have on A-CPOE systems.With respect to adoption factors, our findings suggestthat managed care penetration in a community appearsto be negatively related to the use of A-CPOE amongphysicians. This trend is consistent with previousresearch that identified a negative relationship betweenmanaged care penetration rates and the use of magneticresonance imaging and other "high tech" services.29,30With respect to A-CPOE, there may be several explanationsfor this finding. First, managed care penetrationmay be associated with decreased financial flexibilityamong physicians.36-39 The lower level of resource availabilitymay arise from systematically lower reimbursements,more time pressures, and/or potentially higheroverhead that is needed to contract with managedcare organizations. As a result, less capital may beavailable to physicians and their practices to invest inA-CPOE systems and other HITs.Several administrative practices commonly promotedby HMOs are more easily executed with the use of IT.For example, IT enables data gathering and managementfor activities such as physician profiling, identifyingpatients with chronic diseases, engagingin quality improvement, establishingbenchmarks of excellence, and estimatingboth case mix and expected resourceutilization. Ironically, if the negative relationshipwe identify is causal, managedcare organizations may be inadvertentlyslowing the adoption of A-CPOE, whosebenefits (eg, preventing duplicate ordersand medication errors) primarily accrueto the payer.4-7 Traditionally, HMOs arecost conscious and do not spendresources on initiatives that do not havea demonstrated return on investmentthat is superior to other alternatives.Perhaps more evidence of a direct returnon investment will be necessary beforemanaged care organizations activelyincentivize the adoption of A-CPOEamong independent physicians workingin their networks.

Previous research suggests that medicalpractices owned by HMOs were 3times more likely to use EHR systemsthan self-owned or group-owned practices.40 Moreover, HMO clinics in areaswith higher HMO penetration were morelikely to use various ITs.41 These trendssuggest that HMOs recognize severalbenefits from the use of IT in their ownin-house, clinical operations. If all physiciansadopted A-CPOE, 1 apparent benefitto managed care organizations wouldinclude an improved ability to manageand enforce compliance with their formularies.Future research should examinehow the adoption of A-CPOE andother IT by physicians can specificallybenefit managed care organizations.It should be noted, however, thatmanaged care organizations may have afinancial interest to negatively influencethe adoption of HIT among physicianswith whom they contract. As physicians increasinglyuse HIT to manage their administrative and clinicalduties, electronic access to practice-level data maymake them better equipped to negotiate contractualarrangements with HMOs and other third-party payers.Medical practice managers also may be more effectiveat managing their claims, thus reducing their accountsreceivable and denied charges. Presumably, thesefeatures would cost the insurer more money. Last,managed care arrangements of differing types (eg,capitation, discount fee for service) may have differing financial incentives regarding physician useof HIT.

Other factors in the current study that were found tobe linked to A-CPOE availability among physicians werepractice size, practice type, primary care practice, andphysician age. Specifically, larger practices or those withmultiple specialties were significantly more likely toindicate the use of A-CPOE. These findings echo theconclusions of similar work that examined EHR systems,22,42,43 and are likely related to the additional financialand human resources available in larger grouppractices. The greater use of A-CPOE among primarycare physicians also seems to confirm previous work.21Primary care physicians prescribe more drugs perpatient and see more patients per day than specialists.As a result, they may have a greater need for, and canbenefit more from, A-CPOE systems to increase practicethroughput and charge capture.

Notwithstanding the contribution of the currentstudy, several limitations are worth mentioning. Forexample, our dependent variable did not inherentlymeasure the frequency of use or the cost of A-CPOEsystems among respondents. Instead, it capturedinformation about whether or not a physician hadreportedly adopted an A-CPOE system. Moreover, wemeasured managed care market penetration at thecounty level, not as a percentage of a given physician'spatient base that is covered by an HMO. Althoughboth approaches provided important information, thelatter approach is more suited for clinician-level conclusions.Furthermore, given the limitation of county-levelinformation, it is possible that dense urbancounties have poorer granularity than less dense ruralareas. Granularity, in this case, refers to the level ofdetail necessary to distinguish differences if they exist.If so, this may influence the results we present.Additionally, given the nature of the survey methodused, response bias is always possible, although nonewas detected in a formal assessment24 using establishedmethodologies.44-46 Last, our cross-sectional correlationstudy utilized data from 1 state, at a single point intime, and may have been limited by missing variablesnot included in our models. As such, generalizability toother locations and causality should be inferred withcaution.

In conclusion, market-level managed care penetrationand other physician factors seem to be correlatedwith the diffusion of an important HIT that can improvethe safety and quality of care. Knowing the factors thatinfluence A-CPOE utilization by physicians and theirpractices will allow policymakers, researchers, payers,and other stakeholders to understand the barriers andfacilitators that influence the adoption of A-CPOEtechnology.

From the Department of Family Medicine and Rural Health (NM, AC, RGB), the Centeron Patient Safety (NM, AC, RGB), and the Division of Health Affairs (NM, AL, RGB), FloridaState University College of Medicine, Tallahassee, Fla; and the Area of Management, RawlsCollege of Business, Texas Tech University, Lubbock, Tex (EWF).

This project was funded by the US Center for Medicare and Medicaid Services,Department of Health and Human Services, under contract 500-02 FL02.

Address correspondence to: Nir Menachemi, PhD, MPH, FSU College of Medicine,1115 West Call St, Tallahassee, FL 32306. E-mail: nir.menachemi@med.fsu.edu.

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