Are physicians' perceptions of healthcare quality and practice satisfaction affected by errors associated with electronic health record use?

Background

Electronic health record (EHR) adoption is a national priority in the USA, and well-designed EHRs have the potential to improve quality and safety. However, physicians are reluctant to implement EHRs due to financial constraints, usability concerns, and apprehension about unintended consequences, including the introduction of medical errors related to EHR use. The goal of this study was to characterize and describe physicians'' attitudes towards three consequences of EHR implementation: (1) the potential for EHRs to introduce new errors; (2) improvements in healthcare quality; and (3) changes in overall physician satisfaction.

Methods

Using data from a 2007 statewide survey of Massachusetts physicians, we conducted multivariate regression analysis to examine relationships between practice characteristics, perceptions of EHR-related errors, perceptions of healthcare quality, and overall physician satisfaction.

Results

30% of physicians agreed that EHRs create new opportunities for error, but only 2% believed their EHR has created more errors than it prevented. With respect to perceptions of quality, there was no significant association between perceptions of EHR-associated errors and perceptions of EHR-associated changes in healthcare quality. Finally, physicians who believed that EHRs created new opportunities for error were less likely be satisfied with their practice situation (adjusted OR 0.49, p=0.001).

Conclusions

Almost one third of physicians perceived that EHRs create new opportunities for error. This perception was associated with lower levels of physician satisfaction.     

Organizational complements to electronic health records in ambulatory physician performance: the role of support staff

In industries outside healthcare, highly skilled employees enable substantial gains in productivity after adoption of information technologies. The authors explore whether the presence of highly skilled, autonomous clinical support staff is associated with higher performance among physicians with electronic health records (EHRs). Using data from a survey of general internists, the authors assessed whether physicians with EHRs were more likely to be top performers on cost and quality if they worked with nurse practitioners or physician assistants. It was found that, among physicians with EHRs, those with highly skilled, autonomous staff were far more likely to be top performing than those without such staff (OR 7.0, 95% CI 1.7 to 34.8, p=0.02). This relationship did not hold among physicians without EHRs (OR 1.0). As we begin a national push towards greater EHR adoption, it is critical to understand why some physicians gain from EHR use and others do not.     

Correlates of Electronic Health Record Adoption in Office Practices: A Statewide Survey

Objective

Despite emerging evidence that electronic health records (EHRs) can improve the efficiency and quality of medical care, most physicians in office practice in the United States do not currently use an EHR. We sought to measure the correlates of EHR adoption.

Design

Mailed survey to a stratified random sample of all medical practices in Massachusetts in 2005, with one physician per practice randomly selected for survey.

Measurements

EHR adoption rates.

Results

The response rate was 71% (1345/1884). Overall, while 45% of physicians were using an EHR, EHRs were present in only 23% of practices. In multivariate analysis, practice size was strongly correlated with EHR adoption; 52% of practices with 7 or more physicians had an EHR, as compared with 14% of solo practices (adjusted odds ratio, 3.66; 95% confidence interval, 2.28–5.87). Hospital-based practices (adjusted odds ratio, 2.44; 95% confidence interval, 1.53–3.91) and practices that teach medical students or residents (adjusted odds ratio, 2.30; 95% confidence interval, 1.60–3.31) were more likely to have an EHR. The most frequently cited barriers to adoption were start-up financial costs (84%), ongoing financial costs (82%), and loss of productivity (81%).

Conclusions

While almost half of physicians in Massachusetts are using an EHR, fewer than one in four practices in Massachusetts have adopted EHRs. Adoption rates are lower in smaller practices, those not affiliated with hospitals, and those that do not teach medical students or residents. Interventions to expand EHR use must address both financial and non-financial barriers, especially among smaller practices.     

Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis

ObjectiveTo derive 7 proposed core electronic health record (EHR) use metrics across 2 healthcare systems with different EHR vendor product installations and examine factors associated with EHR time.Materials and MethodsA cross-sectional analysis of ambulatory physicians EHR use across the Yale-New Haven and MedStar Health systems was performed for August 2019 using 7 proposed core EHR use metrics normalized to 8 hours of patient scheduled time.ResultsFive out of 7 proposed metrics could be measured in a population of nonteaching, exclusively ambulatory physicians. Among 573 physicians (Yale-New Haven N = 290, MedStar N = 283) in the analysis, median EHR-Time₈ was 5.23 hours. Gender, additional clinical hours scheduled, and certain medical specialties were associated with EHR-Time₈ after adjusting for age and health system on multivariable analysis. For every 8 hours of scheduled patient time, the model predicted these differences in EHR time (P < .001, unless otherwise indicated): female physicians +0.58 hours; each additional clinical hour scheduled per month −0.01 hours; practicing cardiology −1.30 hours; medical subspecialties −0.89 hours (except gastroenterology, P = .002); neurology/psychiatry −2.60 hours; obstetrics/gynecology −1.88 hours; pediatrics −1.05 hours (P = .001); sports/physical medicine and rehabilitation −3.25 hours; and surgical specialties −3.65 hours.ConclusionsFor every 8 hours of scheduled patient time, ambulatory physicians spend more than 5 hours on the EHR. Physician gender, specialty, and number of clinical hours practicing are associated with differences in EHR time. While audit logs remain a powerful tool for understanding physician EHR use, additional transparency, granularity, and standardization of vendor-derived EHR use data definitions are still necessary to standardize EHR use measurement.     

The Relationship between Electronic Health Record Use and Quality of Care over Time

Objective

Electronic health records (EHRs) have the potential to advance the quality of care, but studies have shown mixed results. The authors sought to examine the extent of EHR usage and how the quality of care delivered in ambulatory care practices varied according to duration of EHR availability.

Methods

The study linked two data sources: a statewide survey of physicians' adoption and use of EHR and claims data reflecting quality of care as indicated by physicians' performance on widely used quality measures. Using four years of measurement, we combined 18 quality measures into 6 clinical condition categories. While the survey of physicians was cross-sectional, respondents indicated the year in which they adopted EHR. In an analysis accounting for duration of EHR use, we examined the relationship between EHR adoption and quality of care.

Results

The percent of physicians reporting adoption of EHR and availability of EHR core functions more than doubled between 2000 and 2005. Among EHR users in 2005, the average duration of EHR use was 4.8 years. For all 6 clinical conditions, there was no difference in performance between EHR users and non-users. In addition, for these 6 clinical conditions, there was no consistent pattern between length of time using an EHR and physicians performance on quality measures in both bivariate and multivariate analyses.

Conclusions

In this cross-sectional study, we found no association between duration of using an EHR and performance with respect to quality of care, although power was limited. Intensifying the use of key EHR features, such as clinical decision support, may be needed to realize quality improvement from EHRs. Future studies should examine the relationship between the extent to which physicians use key EHR functions and their performance on quality measures over time.     

Physicians' Use of Key Functions in Electronic Health Records from 2005 to 2007: A Statewide Survey

Objective

Electronic health records (EHRs) have potential to improve quality and safety, but many physicians do not use these systems to full capacity. The objective of this study was to determine whether this usage gap is narrowing over time.

Design

Follow-up mail survey of 1,144 physicians in Massachusetts who completed a 2005 survey.

Measurements

Adoption of EHRs and availability and use of 10 EHR functions.

Results

The response rate was 79.4%. In 2007, 35% of practices had EHRs, up from 23% in 2005. Among practices with EHRs, there was little change between 2005 and 2007 in the availability of nine of ten EHR features; the notable exception was electronic prescribing, reported as available in 44.7% of practices with EHRs in 2005 and 70.8% in 2007. Use of EHR functions changed inconsequentially, with more than one out of five physicians not using each available function regularly in both 2005 and 2007. Only electronic prescribing increased substantially: in 2005, 19.9% of physicians with this function available used it most or all the time, compared with 42.6% in 2007 (p < 0.001).

Conclusions

By 2007, more than one third of practices in Massachusetts reported having EHRs; the availability and use of electronic prescribing within these systems has increased. In contrast, physicians reported little change in the availability and use of other EHR functions. System refinements, certification efforts, and health policies, including standards development, should address the gaps in both EHR adoption and the use of key functions.     

A systematic review of contributing factors of and solutions to electronic health record–related impacts on physician well-being

ObjectivePhysicians often describe the electronic health record (EHR) as a cumbersome impediment to meaningful work, which has important implications for physician well-being. This systematic review (1) assesses organizational, physician, and information technology factors associated with EHR-related impacts on physician well-being; and (2) highlights potential improvements to EHR form and function, as recommended by frontline physicians.Materials and methodsThe MEDLINE, Embase, CINAHL, PsycINFO, ProQuest, and Web of Science databases were searched for literature describing EHR use by physicians and markers of well-being.ResultsAfter reviewing 7388 article, 35 ultimately met the inclusion criteria. Multiple factors across all levels were associated with EHR-related well-being among physicians. Notable predictors amenable to interventions include (1) total EHR time, (2) after-hours EHR time, (3) on-site EHR support, (4) perceived EHR usability, (5) in-basket burden, and (6) documentation burden. Physician recommendations also echoed these themes.ConclusionsThere are multiple complex factors involved in EHR-related well-being among physicians. Our review shows physicians have recommendations that span from federal regulations to organizational policies to EHR modifications. Future research should assess multipronged interventions that address these factors. As primary stakeholders, physicians should be included in the planning and implementation of such modifications to ensure compatibility with physician needs and clinical workflows.     

A novel application of SMART on FHIR architecture for interoperable and scalable integration of patient-reported outcome data with electronic health records

ObjectiveDespite a proliferation of applications (apps) to conveniently collect patient-reported outcomes (PROs) from patients, PRO data are yet to be seamlessly integrated with electronic health records (EHRs) in a way that improves interoperability and scalability. We applied the newly created PRO standards from the Office of the National Coordinator for Health Information Technology to facilitate the collection and integration of standardized PRO data. A novel multitiered architecture was created to enable seamless integration of PRO data via Substitutable Medical Apps and Reusable Technologies on Fast Healthcare Interoperability Resources apps and scaled to different EHR platforms in multiple ambulatory settings.Materials and MethodsWe used a standards-based approach to deploy 2 apps that source and surface PRO data in real-time for provider use within the EHR and which rely on PRO assessments from an external center to streamline app and EHR integration.ResultsThe apps were developed to enable patients to answer validated assessments (eg, a Patient-Reported Outcomes Measurement Information System including using a Computer Adaptive Test format). Both apps were developed to populate the EHR in real time using the Health Level Seven FHIR standard allowing providers to view patients’ data during the clinical encounter. The process of implementing this architecture with 2 different apps across 18 ambulatory care sites and 3 different EHR platforms is described.ConclusionOur approach and solution proved feasible, secure, and time- and resource-efficient. We offer actionable guidance for this technology to be scaled and adapted to promote adoption in diverse ambulatory care settings and across different EHRs.     

Optimizing the electronic health record: An inpatient sprint addresses provider burnout and improves electronic health record satisfaction

ObjectiveWe sought reduce electronic health record (EHR) burden on inpatient clinicians with a 2-week EHR optimization sprint.Materials and MethodsA team led by physician informaticists worked with 19 advanced practice providers (APPs) in 1 specialty unit. Over 2 weeks, the team delivered 21 EHR changes, and provided 39 one-on-one training sessions to APPs, with an average of 2.8 hours per provider. We measured Net Promoter Score, thriving metrics, and time spent in the EHR based on user log data.ResultsOf the 19 APPs, 18 completed 2 or more sessions. The EHR Net Promoter Score increased from 6 to 60 postsprint (1.0; 95% confidence interval, 0.3-1.8; P = .01). The NPS for the Sprint itself was 93, a very high rating. The 3-axis emotional thriving, emotional recovery, and emotional exhaustion metrics did not show a significant change. By user log data, time spent in the EHR did not show a significant decrease; however, 40% of the APPs responded that they spent less time in the EHR.ConclusionsThis inpatient sprint improved satisfaction with the EHR.     

Evaluating a scalable model for implementing electronic health records in resource-limited settings

Current models for implementing electronic health records (EHRs) in resource-limited settings may not be scalable because they fail to address human-resource and cost constraints. This paper describes an implementation model which relies on shared responsibility between local sites and an external three-pronged support infrastructure consisting of: (1) a national technical expertise center, (2) an implementer''s community, and (3) a developer''s community. This model was used to implement an open-source EHR in three Ugandan HIV-clinics. Pre–post time–motion study at one site revealed that Primary Care Providers spent a third less time in direct and indirect care of patients (p<0.001) and 40% more time on personal activities (p=0.09) after EHRs implementation. Time spent by previously enrolled patients with non-clinician staff fell by half (p=0.004) and with pharmacy by 63% (p<0.001). Surveyed providers were highly satisfied with the EHRs and its support infrastructure. This model offers a viable approach for broadly implementing EHRs in resource-limited settings.     

Electronic health records and clinician burnout: A story of three eras

ObjectiveThe study sought to provide physicians, informaticians, and institutional policymakers with an introductory tutorial about the history of medical documentation, sources of clinician burnout, and opportunities to improve electronic health records (EHRs). We now have unprecedented opportunities in health care, with the promise of new cures, improved equity, greater sensitivity to social and behavioral determinants of health, and data-driven precision medicine all on the horizon. EHRs have succeeded in making many aspects of care safer and more reliable. Unfortunately, current limitations in EHR usability and problems with clinician burnout distract from these successes. A complex interplay of technology, policy, and healthcare delivery has contributed to our current frustrations with EHRs. Fortunately, there are opportunities to improve the EHR and health system. A stronger emphasis on improving the clinician’s experience through close collaboration by informaticians, clinicians, and vendors can combine with specific policy changes to address the causes of burnout.Target audienceThis tutorial is intended for clinicians, informaticians, policymakers, and regulators, who are essential participants in discussions focused on improving clinician burnout. Learners in biomedicine, regardless of clinical discipline, also may benefit from this primer and review.ScopeWe include (1) an overview of medical documentation from a historical perspective; (2) a summary of the forces converging over the past 20 years to develop and disseminate the modern EHR; and (3) future opportunities to improve EHR structure, function, user base, and time required to collect and extract information.     

Measuring time clinicians spend using EHRs in the inpatient setting: a national,mixed-methods study

ObjectiveTo understand hospitals’ use of EHR audit-log-based measures to address burden associated with inpatient EHR use.Materials and MethodsUsing mixed methods, we analyzed 2018 American Hospital Association Information Technology Supplement Survey data (n = 2864 hospitals; 64% response rate) to characterize measures used and provided by EHR vendors to track clinician time spent documenting. We interviewed staff from the top 3 EHR vendors that provided these measures. Multivariable analyses identified variation in use of the measures among hospitals with these 3 vendors.Results53% of hospitals reported using EHR data to track clinician time documenting, compared to 68% of the hospitals using the EHR from the top 3 vendors. Among hospitals with EHRs from these vendors, usage was significantly lower among rural hospitals and independent hospitals (P < .05). Two of these vendors provided measures of time spent doing specific tasks while the third measured an aggregate of auditable activities. Vendors varied in the underlying data used to create measures, measure specification, and data displays.DiscussionTools to track clinicians’ documentation time are becoming more available. The measures provided differ across vendors and disparities in use exist across hospitals. Increasing the specificity of standards underlying the data would support a common set of core measures making these measures more widely available.ConclusionAlthough half of US hospitals use measures of time spent in the EHR derived from EHR generated data, work remains to make such measures and analyses more broadly available to all hospitals and to increase its utility for national burden measurement.     

Investigating Response Bias in an Information Technology Survey of Physicians

Monitoring the diffusion of electronic health records (EHR) into ambulatory clinical practice has important policy implications. However, estimates of EHR use are typically derived from survey data and may be subject to significant response bias. The current study is a retrospective analysis testing for response bias in a large information technology survey of physicians (n=14,921). To detect bias, respondents were compared to nonrespondents on known characteristics. Moreover, early respondents were compared to late respondents with respect to key variables in the survey that are likely to influence participation. The 4203 respondents (28.2% participation rate) did not differ demographically from nonrespondents. Response rates, by specialty, differed slightly. When comparing early and late survey respondents, no differences were detected in EHR use, length of time since EHR installation, practice size, physician age, years since medical school graduation, and years of practice in their current community. Overall, response bias was not detected using established methodologies in this mailed survey of physician EHR use. Similar surveys of physicians, even with a lower than expected response rate, may still be valid.     

A decade post-HITECH: Critical access hospitals have electronic health records but struggle to keep up with other advanced functions

ObjectiveDespite broad electronic health record (EHR) adoption in U.S. hospitals, there is concern that an “advanced use” digital divide exists between critical access hospitals (CAHs) and non-CAHs. We measured EHR adoption and advanced use over time to analyzed changes in the divide.Materials and MethodsWe used 2008 to 2018 American Hospital Association Information Technology survey data to update national EHR adoption statistics. We stratified EHR adoption by CAH status and measured advanced use for both patient engagement (PE) and clinical data analytics (CDA) domains. We used a linear probability regression for each domain with year-CAH interactions to measure temporal changes in the relationship between CAH status and advanced use.ResultsIn 2018, 98.3% of hospitals had adopted EHRs; there were no differences by CAH status. A total of 58.7% and 55.6% of hospitals adopted advanced PE and CDA functions, respectively. In both domains, CAHs were less likely to be advanced users: 46.6% demonstrated advanced use for PE and 32.0% for CDA. Since 2015, the advanced use divide has persisted for PE and widened for CDA.DiscussionEHR adoption among hospitals is essentially ubiquitous; however, CAHs still lag behind in advanced use functions critical to improving care quality. This may be rooted in different advanced use needs among CAH patients and lack of access to technical expertise.ConclusionsThe advanced use divide prevents CAH patients from benefitting from a fully digitized healthcare system. To close the widening gap in CDA, policymakers should consider partnering with vendors to develop implementation guides and standards for functions like dashboards and high-risk patient identification algorithms to better support CAH adoption.     

Predicting the Adoption of Electronic Health Records by Physicians: When Will Health Care be Paperless?

ObjectivesThe purpose of this study was threefold. First, we gathered and synthesized the historic literature regarding electronic health record (EHR) adoption rates among physicians in small practices (ten or fewer members). Next, we constructed models to project estimated future EHR adoption trends and timelines. We then determined the likelihood of achieving universal EHR adoption in the near future and articulate how barriers can be overcome in the small and solo practice medical environment.DesignThis study used EHR adoption data from six previous surveys of small practices to estimate historic market penetration rates. Applying technology diffusion theory, three future adoption scenarios, optimistic, best estimate, and conservative, are empirically derived.MeasurementEHR adoption parameters, external and internal coefficients of influence, are estimated using Bass diffusion models.ResultsAll three EHR scenarios display the characteristic diffusion S curve that is indicative that the technology is likely to achieve significant market penetration, given enough time. Under current conditions, EHR adoption will reach its maximum market share in 2024 in the small practice setting.ConclusionThe promise of improved care quality and cost control has prompted a call for universal EHR adoption by 2014. The EHR products now available are unlikely to achieve full diffusion in a critical market segment within the time frame being targeted by policy makers.     

Brief communication: Facility characteristics associated with the use of electronic health records in residential care facilities

The integration of electronic health records (EHRs) across care settings including residential care facilities (RCFs) promises to reduce medical errors and improve coordination of services. Using data from the 2010 National Survey of Residential Care Facilities (n=2302), this study examines the association between facility structural characteristics and the use of EHRs in RCFs. Findings indicate that in 2010, only 3% of RCFs nationwide were using an EHR. However, 55% of RCFs reported using a computerized system for one or more (but not all) of the functionalities defined by a basic EHR. Ownership, chain membership, staffing levels, and facility size were significantly associated with the use of one or more core EHR functionalities. These findings suggest that facility characteristics may play an important role in the adoption of EHRs in RCFs.     

Impact of the 2015 Health Information Technology Certification Edition on Interoperability among Hospitals

ObjectiveMost nonfederal acute care hospitals use electronic health records (EHRs) certified by the Office of the National Coordinator for Health Information Technology. In 2015, the Office of the National Coordinator for Health Information Technology finalized the 2015 Health IT Certification Edition and adoption by hospitals began in 2016. We examine the impact of the 2015 Edition on rates of interoperable exchange among nonfederal acute hospitals.Materials and MethodsThe study applies a standard difference-in-differences design and a recently developed fixed effects estimator that relaxes the assumption of treatment effects being constant across groups and time. In the analysis, we identify separate effects of the 2015 Edition for hospitals that switched EHR developers and forecast hospitals’ interoperability over 2015 Edition adoption rates.ResultsThe adoption of the 2015 Edition increased hospitals’ rates of interoperable exchange and especially benefited hospitals that switched EHR developers in the post-implementation period. Forecasting results indicate that if all hospitals adopted the 2015 Edition, 53% to 61% of hospitals would engage in interoperable health information exchange compared with the current rate of 46%.DiscussionHospitals’ levels of interoperability have been rising over the last few years. Adoption of newer technology improved hospitals’ interoperability and accounts for up to 12% of the rise in interoperability.ConclusionsCertified technology is one mechanism to ensure providers use recent and safe technologies for interoperable exchange. Adoption of certified EHRs improves the nation’s interoperable exchange; however, it has a clear limited effect. Other mechanisms are necessary for achieving comprehensive interoperable exchange.     

High-throughput phenotyping with temporal sequences

ObjectiveHigh-throughput electronic phenotyping algorithms can accelerate translational research using data from electronic health record (EHR) systems. The temporal information buried in EHRs is often underutilized in developing computational phenotypic definitions. This study aims to develop a high-throughput phenotyping method, leveraging temporal sequential patterns from EHRs.Materials and MethodsWe develop a representation mining algorithm to extract 5 classes of representations from EHR diagnosis and medication records: the aggregated vector of the records (aggregated vector representation), the standard sequential patterns (sequential pattern mining), the transitive sequential patterns (transitive sequential pattern mining), and 2 hybrid classes. Using EHR data on 10 phenotypes from the Mass General Brigham Biobank, we train and validate phenotyping algorithms.ResultsPhenotyping with temporal sequences resulted in a superior classification performance across all 10 phenotypes compared with the standard representations in electronic phenotyping. The high-throughput algorithm’s classification performance was superior or similar to the performance of previously published electronic phenotyping algorithms. We characterize and evaluate the top transitive sequences of diagnosis records paired with the records of risk factors, symptoms, complications, medications, or vaccinations.DiscussionThe proposed high-throughput phenotyping approach enables seamless discovery of sequential record combinations that may be difficult to assume from raw EHR data. Transitive sequences offer more accurate characterization of the phenotype, compared with its individual components, and reflect the actual lived experiences of the patients with that particular disease.ConclusionSequential data representations provide a precise mechanism for incorporating raw EHR records into downstream machine learning. Our approach starts with user interpretability and works backward to the technology.     

EHR Safety: The Way Forward to Safe and Effective Systems

Diverse stakeholders—clinicians, researchers, business leaders, policy makers, and the public—have good reason to believe that the effective use of electronic health care records (EHRs) is essential to meaningful advances in health care quality and patient safety. However, several reports have documented the potential of EHRs to contribute to health care system flaws and patient harm. As organizations (including small hospitals and physician practices) with limited resources for care-process transformation, human-factors engineering, software safety, and project management begin to use EHRs, the chance of EHR-associated harm may increase. The authors propose a coordinated set of steps to advance the practice and theory of safe EHR design, implementation, and continuous improvement. These include setting EHR implementation in the context of health care process improvement, building safety into the specification and design of EHRs, safety testing and reporting, and rapid communication of EHR-related safety flaws and incidents.     

Social networks and physician adoption of electronic health records: insights from an empirical study

Objective

To study how social interactions influence physician adoption of an electronic health records (EHR) system.

Design

A social network survey was used to delineate the structure of social interactions among 40 residents and 15 attending physicians in an ambulatory primary care practice. Social network analysis was then applied to relate the interaction structures to individual physicians'' utilization rates of an EHR system.

Measurements

The social network survey assessed three distinct types of interaction structures: professional network based on consultation on patient care-related matters; friendship network based on personal intimacy; and perceived influence network based on a person''s perception of how other people have affected her intention to adopt the EHR system. EHR utilization rates were measured as the proportion of patient visits in which sentinel use events consisting of patient data documentation or retrieval activities were recorded. The usage data were collected over a time period of 14 months from computer-recorded audit trail logs.

Results

Neither the professional nor the perceived influence network is correlated with EHR usage. The structure of the friendship network significantly influenced individual physicians'' adoption of the EHR system. Residents who occupied similar social positions in the friendship network shared similar EHR utilization rates (p<0.05). In other words, residents who had personal friends in common tended to develop comparable levels of EHR adoption. This effect is particularly prominent when the mutual personal friends of these ‘socially similar’ residents were attending physicians (p<0.001).

Conclusions

Social influence affecting physician adoption of EHR seems to be predominantly conveyed through interactions with personal friends rather than interactions in professional settings.Social influence pervades our lives. Watching a movie recommended by friends, reading a news article referred by colleagues, dressing up for a formal social event (assuming everybody else will do the same), and so on, are all examples of how other people''s opinions or behavior affect our everyday choices. Social influence theories therefore postulate that people are neither born with beliefs or behavior nor are beliefs or behavior developed in isolation. Their formation and evolution occur primarily through social interactions as people compare their own beliefs or behavior with those of others, in particular, similar others.¹Social influence plays the same role in the process of innovation diffusion. This is especially true when an innovation is complex entailing unknown costs or unknown consequences. For example, it has been shown that physicians who are ‘socially proximate’ in a social environment often use one another as information sources or behavior referents to manage the uncertainty of adopting new antibiotic drugs.² Does social influence exert a similar effect on physician adoption of complex technological innovations such as electronic health records (EHR)?Answering this question is very important in a healthcare policy climate in which strong emphasis has been placed on increased and improved use of health information technology, and EHR in particular. Furthermore, EHR is much more complex than other types of medical innovations. The adoption of EHR not only requires significant financial investments and learning effort, but also introduces radical change to every single aspect of clinical work. Understanding the social mechanisms underlying physician adoption of EHR is therefore critical to identifying effective strategies to accelerate EHR diffusion and to promote its meaningful use. Unfortunately, such an understanding has been largely missing,^{3 4} resulting in failed implementations⁵ and suboptimal or even adverse outcomes.^{6 7} Given this context, we designed and conducted a study to examine physician adoption of EHR through the lens of social influence.Social influence, often crystallized as opinion exchange and behavior ‘imitating’, is conveyed in physicians'' interpersonal social interactions. Social network analysis (SNA), which views the structure of social interactions as networks composed of nodes (physicians) interconnected by edges (social relations), is an ideal approach for delineating interaction patterns to study how social influence is transmitted among physicians and how it affects their contingent behavior such as EHR adoption. In particular, we designed and conducted a SNA study to assess the social structures among physicians in an ambulatory primary care practice and then relate these structures to individual physicians'' utilization rates of an EHR system.