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Original Investigation |

The Practice Impact of Electronic Health Record System Implementation Within a Large Multispecialty Ophthalmic Practice FREE

Rishi P. Singh, MD1,2; Rumneek Bedi, BS1; Ang Li, BS1; Sharmila Kulkarni, BS1; Tiffany Rodstrom, COT, RN1; Gene Altus, BA, MBA1; Daniel F. Martin, MD1
[+] Author Affiliations
1Cole Eye Institute, Cleveland Clinic, Cleveland, Ohio
2Clinical Systems Office, Cleveland Clinic, Cleveland, Ohio
JAMA Ophthalmol. 2015;133(6):668-674. doi:10.1001/jamaophthalmol.2015.0457.
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Published online

Importance  Given the lack of previous reports examining the impact of electronic health record (EHR) system migration in ophthalmology, a study evaluating the practice and economic effect of implementing an EHR into an ophthalmic practice is warranted.

Objective  To examine the clinical and economic impact of EHR system implementation into a large multispecialty ophthalmic practice.

Design, Setting, and Participants  A retrospective case-control study was conducted comparing the pre-EHR and post-EHR time periods at the Cole Eye Institute, Cleveland, Ohio. Eight months were spent prior to implementation personalizing and customizing the system to enable advanced charting functions (July 1, 2011, to March 1, 2012). The periods were compared regarding total revenue, total visit volume, revenue per visit, coding volumes, and the number of diagnostic tests and procedures performed. In addition, the total costs of the EHR implementation and the expected return in EHR incentive payments were evaluated. Data analysis was performed from April 1, 2011, through April 5, 2013.

Main Outcomes and Measures  Net revenue, patient volume, revenue to volume ratio, diagnostic and procedure volume, capital and implementation costs, EHR incentive payments received, and coding volumes (including eye and evaluation and management [E/M] codes).

Results  A total of 28 161 patient encounters were identified (13 969 in the pre-EHR period and 14 191 in the post-EHR period). No significant change was identified with total net fiscal revenue between the periods (median, −$44 372 per month; 25th to 75th interquartile range [IQR], −$103 850 to $83 126; P = .42). No significant change in patient volume (median, +217.0; IQR, −511.5 to 812.0; P = .57) or revenue per visit volume (median, −$7; IQR, −$9 to −$1; P = .20) was identified. The volume of diagnostic tests and procedures billed was unchanged after conversion (median, +93; IQR, −20 to 235; P = .13). Overall use of eye codes declined (−15.7%) and use of E/M codes increased (14.7%) following EHR implementation (P < .001). The composition of eye codes showed a 2% change toward comprehensive codes over intermediate codes after implementation, but only the composition of new E/M codes increased (42.6%) (P < .001 for both values). Total capital costs amounted to $1 571 864, and personnel costs amounted to $1 514 334. A cumulative amount of $983 103 from meaningful use attestation is expected by 2016.

Conclusions and Relevance  The analyses conducted in this study did not identify significant differences in revenue or productivity following EHR conversion in this clinical setting. The EHR incentive payments did not offset costs of implementation.

The implementation of electronic health record (EHR) systems into the medical setting has been a topic of debate as it pertains to efficiency and quality of care and its economic impact. The transition to EHRs from paper records can theoretically reduce long-term costs and improve efficiency.1 Items such as prepopulated fields, one-click ordering of diagnostic tests and procedures, and a shared medical record among practitioners can potentially increase physician productivity.

The reality is that studies2,3 have instead demonstrated higher costs associated with the transition to EHR systems. In these cases, hospital monetary savings that were expected with EHR implementation were offset by the expense of purchasing, and maintaining the new medical record system and training staff.3 The EHR start-up costs have been estimated at $10 329 per physician, and few studies have evaluated the costs of implementation in the outpatient setting.4 These start-up costs are often a reason for reluctance in adopting EHRs. In addition, some ophthalmology practices have experienced a sustained loss in productivity, which has led in some cases to abandonment and return to paper records.

Traditionally, EHR systems have not been accommodating to ophthalmologists. The American Academy of Ophthalmology5 published guidelines of the necessary features for EHR systems to accommodate an ophthalmology practice workflow. Adolescent technologies of the past were not able to store the visual descriptions of the eye, such as drawings and photographs that a practitioner would make to describe the patient’s condition.6 Advances in computer software and hardware have allowed for better and more thorough recording of the patient visit, which may accurately justify higher coding levels.7 At the same time, the ease of autofilling default fields in EHR may falsely enable up-coding.8 Given the multiple advances within the field of EHR software, EHR incentive payments available, and the few reports of EHR impact within ophthalmology practices, the purpose of this study was to evaluate the practice and economic impact of implementing EHRs systems into a large, multispecialty ophthalmic practice.

Before implementation of an EHR system, the Cole Eye Institute, Cleveland, Ohio, used paper records for the documentation of visits, diagnostic testing, orders, and procedure notes. Visit charges and procedural charges were entered on paper tickets that were passed to the billing department for manual entry into the system. If proper documentation could not be obtained or was lost, no bill was submitted for reimbursement.

A highly customized version of an EHR system (Kaleidoscope Ophthalmology Module; Epic Systems) was implemented among all subspecialties of ophthalmology at the main office of the Cole Eye Institute. Only physicians with pre-EHR and post-EHR data were included for this analysis to adequately draw comparisons. A total of 23 physicians participated in the EHR implementation: 2 comprehensive ophthalmologists, 5 cornea specialists, 2 glaucoma specialists, 2 neuroophthalmology specialists, 1 oncology specialist, 1 optometrist, 2 pediatric ophthalmologists, 1 oculoplastic specialist, 6 retina specialists, and 1 uveitis specialist. Thin-client personal computers running Windows XP (Microsoft Corp) with 24-inch monitors were used by all clinicians. Zeiss Forum image management system, version 2.6 (Carl Zeiss Meditech) was installed as the imaging picture archiving and communication system, and Health Level 7 (HL-7) links between the Zeiss Forum software and the Epic system were created to integrate the diagnostic instruments. The institutional review board of Cleveland Clinic approved the study with waiver of informed consent.

The customization process began July 1, 2011, and was completed March 31, 2012. During this time, 7 full-time employees worked exclusively on adding content and features within the system. The EHR enabled medication and allergy reconciliation, ordering and reporting of results of diagnostics tests and procedures, electronic prescribing of medications, and advanced charting functions to allow for annotated drawings and automated electronic billing. No scribes were used during the implementation process, and technician allocation was not adjusted significantly for the conversion to EHR. A total of 41 ophthalmic technicians were employed in 2011, 42 in 2012, and 43 in 2013. Prior to the time of implementation, 5 physicians piloted an earlier version of the system (Epic EMR Ambulatory model). Technicians were trained before this time with the participating physicians. These physicians were eliminated from the analyses that are presented to fairly evaluate the preimplementation and postimplementation changes. The number of full-time equivalent employees evaluated before and after the transition did not change.

The EHR system was implemented on April 2, 2012. To facilitate the successful adoption of EHR, clinical schedules were reduced by 25% during the first 2 weeks of the process. Subsequently, all clinical schedules were returned to their pre-EHR levels.

The pre-EHR period (defined as April 4, 2011, to March 30, 2012) and post-EHR period (defined as April 2, 2012, to April 5, 2013) were compared. The primary end points evaluated were total revenue, total visit volume, revenue per visit, and the frequency of diagnostic tests and procedures performed with year-to-date comparisons. In addition, costs of the implementation and reimbursement from meaningful use reporting for the EHR implementation were included in the evaluation.

End points to characterize specific coding behavior changes following EHR implementation were also collected. Changes in the coding levels and volume differences for eye (intermediate and comprehensive) examinations, new and established office (level 1-5) visits, and office consultations were tabulated before and after EHR implementation.9

The Cole Eye Institute’s operations division provided all numbers reported; all data were deidentified. Descriptive summaries of all measures were created using means (SDs), medians, and 25th to 75th percentile interquartile ranges (IQRs) to describe levels for each year and the differences between years across months. Wilcoxon signed rank tests were used to compare levels between years by month. Analysis was performed from April 1, 2011, through April 5, 2013, using SAS, version 9.3 (SAS Institute Inc).

Table 1 demonstrates the total and subspecialty changes in monthly net revenue before and after EHR implementation obtained from the enterprise practice management system. There was a mean net revenue decline of $44 732 per month noted after implementation (IQR, −$103 850 to $83 126), but no significant differences were identified (P = .42). Oncology and plastic surgery demonstrated increases following EHR implementation ($17 627 [P = .02] and $9954 [P = .009], respectively, per month). Comprehensive, neuroophthalmology, and pediatric services showed declines (−$26 513 [P = .01], −$27 972 [P = .02], and −$12 442 [P = .02], respectively, per month).

Table Graphic Jump LocationTable 1.  Total and Subspecialty Changes in Net Revenue and Volume per Month

Table 1 reports the summaries of total and subspecialty changes in patient volume. Overall, the total volume increased by a mean of 217.0 visits per month from 2011 to 2013, but no significant differences were identified before EHR implementation (P = .57). Only the glaucoma specialists showed a significant increase in visit volumes from 2011 to 2013 (198.5 visits per month [P = .01]).

Table 2 reports the total and subspecialty revenue to volume ratios before and after EHR implementation. The analysis of revenue to volume ratio can determine whether practitioners were receiving greater revenue per visit from improved electronic charge capture or new coding features within the system. Overall, there was a decrease in the revenue to volume (−$7 per visit [P = .20]). The revenue for glaucoma and comprehensive services declined in the ratio from 2011 to 2013 (−$15 per visit [P = .03] and −$20 per visit [P = .02], respectively), but the oncology service showed an increase ($38 per visit [P = .009]).

Table Graphic Jump LocationTable 2.  Total and Individual Changes in Revenue to Volume Ratio by Ophthalmology Subspecialty

Table 3 indicates changes in diagnostics and procedures before and after EHR implementation (shown by code volume between periods). Laser for secondary cataract (Current Procedural Terminology [CPT] code 66821) and optical coherence tomographic scans (CPT code 92134) showed increases between years (+10, P = .03; and +48, P = .04, respectively). Overall, there was an observed increase in code volume (+93; P = .13).

Table Graphic Jump LocationTable 3.  Summaries of Diagnostic and Procedural Volume by Transaction Master Identification Code per Month
Meaningful Use

The Health Information and Technology for Economic and Clinical Health Act (http://www.cbo.gov/publication/20452) allows hospitals and physicians an opportunity to receive authorized incentive payments through Medicare and Medicaid, provided they adopt EHR in a way that improves care delivery, also known as the meaningful use of EHR. These incentives are tied to the achievements in patient care with EHR adoption.10

The EHR incentive payments (stage 1 and stage 2) toward eligible physicians with implementation of EHR are presented in eTable 1 in the Supplement. Estimation of payments based on the total number of clinicians and participation was performed for future years. In 2011, there were 1 participating physician and 24 nonparticipating physicians, which yielded a reported total of $18 000 of stage 1 EHR incentive payment. From 2012 to 2016, it is projected that there will be continuous participation of 23 of the 25 physicians within the Cole Eye Institute, who will receive a combination of stage 1 and 2 meaningful use incentives. The practice forecasts receiving $983 103 of meaningful use incentives by 2016.

Implementation Costs

The budget for EHR implementation during the project period was made up of capital purchases and personnel-based costs. Capital costs included an image management system, legacy medical device upgrades, and license fees for the EHR system. The actual amount spent was $424 880 in 2011 and $1 146 984 in 2012 for a total of $1 571 864 (eTable 2 in the Supplement). The total personnel and ongoing costs of the EHR system in 2011 were $1 160 694, and the total operating costs were $1 514 334 (eTable 3 in the Supplement). These costs consisted of full-time employee salaries plus fringe benefits.

Coding Changes After EHR Implementation

The composition of eye codes and evaluation and management (E/M) codes during the pre-EHR coding of office visits were compared with post-EHR coding. The pre-EHR period was measured from April 4, 2011, to March 30, 2012, and the post-EHR period was measured from April 2, 2012, to April 4, 2013. An increase in E/M codes after EHR transition was complemented by a decrease in eye codes (+14.7% and −15.7% respectively [P < .001]) (Table 4). Among eye examination codes, there was an increase in the volume percentage of comprehensive eye codes and a statistically significant decline in intermediate eye codes (+2% in favor of comprehensive over intermediate [P < .001]). Regarding E/M codes, only new patient E/M codes displayed significant differences in distribution of coding levels before and after the EHR change (+42.6% [P < .001]).

Table Graphic Jump LocationTable 4.  Comparison of Coding Patterns Before and After EHR Implementation

Few studies11,12 have evaluated the economic impact of implementing an EHR into a large, multispecialty ophthalmic practice. The results of those studies demonstrated minimal productivity or revenue changes after implementation. There were no identified differences in total visit volume or overall revenue, and there were no identified changes in the total volume of diagnostic tests and procedures year to date. Many physicians were able to qualify for meaningful use; however, this reimbursement failed to offset the initial costs of implementation.

The stability of volume and revenue from the implementation of an EHR system may be attributable to the method by which the EHR implementation was strategically conducted. A pilot group of 5 physicians used an earlier version of the system while the customization process continued. These physicians were eliminated from the present analysis to best understand the economic impact of the transition. The pilot group allowed for troubleshooting and the identification of problems with the system during the early stages of its implementation, thus alleviating major system issues during the time of implementation. Technicians were experienced by the date of implementation since they received training earlier and were exposed to the pilot physicians prior to the implementation date. This process also made it more manageable for practitioners to access assistance when problems with EHR occurred during clinical workflow. This “piecemeal” roll-out alleviated the common consequence of disrupting the clinical workflow of the entire group.

The roll-out was strategically placed in the first quarter of 2012 because this period during the year historically represented the lowest seasonal visit volumes. In addition, the clinic appointments were decreased only by 25% for 2 weeks. This is in contrast to the vendor-recommended 50% reduction for 2 weeks and then a 25% reduction for an additional 2 weeks. This temporary reduction in volume allowed clinicians to focus on learning and optimizing their use of the new system during a period when maximal “at the elbow” support was available.

It was expected that there would be a proportional increase in the volume of diagnostics and procedures captured because the migration to electronic ordering eased both the ordering and completion of diagnostic and procedural items and allowed for greater visibility for billing. This pattern was not observed, which might be the result of the stringent billing review process that was in place before implementation. Indeed, the revenue per visit ratio was also unchanged following EHR implementation.

A change in coding behavior was observed in our study. This change is of particular interest given the warning letter that Health and Human Services Secretary Kathleen Sebelius and US Attorney General Eric Holder signed in September 2013 (http://www.modernhealthcare.com/Assets/pdf/CH82990924.pdf) citing that the Centers for Medicare and Medicaid Services was paying particular attention to physicians who “up-code” the care provided as a way to make a profit. However, the changes in coding observed in the present study did not demonstrate up-coding following implementation. A couple of factors may be responsible for the observed movement from eye codes to E/M codes. The EHR system allowed for quicker assessment of physical examination findings, which would lend itself to E/M coding vs eye codes, since eye codes require additional history element items, which are more difficult to enter within the system.

The unchanged revenue cannot be attributed solely to EHR implementation since physician availability and changes in medical indications for drugs and procedures within the observed year may also be a significant factor. Although additional ND:YAG capsulotomy and optical coherence tomography volume were observed, this change in volume cannot solely be attributed to increased capture from EHR. These increases may instead represent the widely reported increased usage of optical coherence tomography for its diagnostic capabilities. There might have been changes in the reimbursement for services received from one year to the next; however, this effect is likely small. In addition, no scribes were used for documentation within the EHR. Scribes have been shown13 to improve productivity and efficiency in some practices. It might be possible that the introduction of scribes increases volume and revenue.

Attesting to meaningful use encourages physicians to participate in EHR implementation by supporting the costs of EHR use with incentive payments.9 The payments received for successfully attesting to meaningful use did not offset the costs incurred within our practice since the EHR incentive payments received and projected were below the initial costs of implementation. Other studies14 indicated that the average nonophthalmic practice paid for its EHR costs in 2.5 years, with a significant increase in profits after that period. Especially within ophthalmology, projections indicate that cost savings are observed from 5 to 10 years after EHR implementation.6 The lack an increased revenue observed with the present EHR migration might also represent a learning curve by which changes in the clinical workflow were made. The present study documents financial and patient volume measures but is short in recognizing the physician’s view or changes to productivity after EHR implementation. After the implementation period, physicians are forced to examine, diagnose, and prescribe treatment for patients alongside learning the pace of a new EHR system and documenting patient visits. Therefore, this 1-year study is not fully representative of all the potential benefits of EHR implementation. By 2016, the EHR incentive payments received are projected to total $983 103, which will likely not offset the overall amortized implementation costs, as other studies11,12 have indicated.

There are drawbacks to the analysis performed within this study. Practitioners were allowed to make individualized customizations within their module to provide for more detailed documentation during a patient visit. Physicians spent a mean of 2 hours specifically customizing their templates before EHR implementation. This study was also performed at an outpatient facility within a large hospital practice and may not be extrapolated to smaller multispecialty practices. At the time of implementation of the EHR to Cole Eye Institute, all other medical specialties at the Cleveland Clinic were using the EHR, and lessons learned from their implementation were applied. This implementation also had access to numerous resources, such as an in-house information technology support staff, large capital budget, and access to software licenses and upgrades that facilitated the process. In addition, although net revenue was unchanged, the study did not explore whether the actual measure of health care value or relative value units change after EHR implementation. Because a strong correlation typically exists between revenue and relative value units, a significant difference is unlikely.

Furthermore, none of these measurements (eg, revenue, volume, or revenue/volume ratios) performed necessarily indicate a change in the quality of patient care or allow us to comment on physician productivity with implementation of the EHR system. The stability of patient volume observed in this study does not accurately document physician efficiency, nor does it provide a valued observation of improvement in quality of care with implementation of the EHR system. Since physician time is a resource from which most, if not all, revenues are derived in some way, extra time spent by physicians on EHR documentation could itself be considered an opportunity loss.

The present analysis also does not include the opportunity costs associated with reallocating physicians, technicians, and other support staff to temporarily work on the implementation process. Future studies are warranted to investigate the root causes of up-coding to detect inaccuracies in coding as well as to target promotion of rightful coding practices and prevention of behaviors that inappropriately benefit from the electronic system.

The progress of EHRs should be further monitored for additional evaluation of cost efficiency to ensure long-term stability in operating revenue and volume. If such stability is identified, then long-term EHR implementation benefits within the hospital will continue.

Submitted for Publication: September 2, 2014; final revision received January 30, 2015; accepted February 4, 2015.

Corresponding Author: Rishi P. Singh, MD, Cole Eye Institute, Cleveland Clinic, 9500 Euclid Ave, Room i32, Cleveland, OH 44195 (drrishisingh@gmail.com).

Published Online: April 16, 2015. doi:10.1001/jamaophthalmol.2015.0457.

Author Contributions: Dr Singh had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Singh, Bedi, Rodstrom, Altus.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Singh, Bedi, Li, Rodstrom, Altus, Martin.

Critical revision of the manuscript for important intellectual content: Singh, Bedi, Kulkarni, Altus.

Statistical analysis: Singh, Bedi, Li.

Administrative, technical, or material support: Singh, Rodstrom, Martin.

Study supervision: Singh, Rodstrom, Altus.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.

Funding/Support: Cleveland Clinic receives licensing and consulting fees from organizations outside of Cleveland Clinic for EHR implementation projects. All participants are employees of Cleveland Clinic.

Role of the Funder/Sponsor: The Cleveland Clinic had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Hillestad  R, Bigelow  J, Bower  A,  et al.  Can electronic medical record systems transform health care? potential health benefits, savings, and costs. Health Aff (Millwood). 2005;24(5):1103-1117.
PubMed   |  Link to Article
Menachemi  N, Burkhardt  J, Shewchuk  R, Burke  D, Brooks  RG.  Hospital information technology and positive financial performance: a different approach to finding an ROI. J Healthc Manag. 2006;51(1):40-58.
PubMed
Himmelstein  DU, Wright  A, Woolhandler  S.  Hospital computing and the costs and quality of care: a national study. Am J Med. 2010;123(1):40-46.
PubMed   |  Link to Article
Patil  M, Puri  L, Gonzalez  CM.  Productivity and cost implications of implementing electronic medical records into an ambulatory surgical subspecialty clinic. Urology. 2008;71(2):173-177.
PubMed   |  Link to Article
Chiang  MF, Boland  MV, Brewer  A,  et al; American Academy of Ophthalmology Medical Information Technology Committee.  Special requirements for electronic health record systems in ophthalmology. Ophthalmology. 2011;118(8):1681-1687.
PubMed   |  Link to Article
DeBry  PW.  Considerations for choosing an electronic medical record for an ophthalmology practice. Arch Ophthalmol. 2001;119(4):590-596.
PubMed   |  Link to Article
Lowes  R. Hospitals to feds: EHRs mean more accurate coding. Medscape website. http://www.medscape.com/viewarticle/772025. Published 2012. Accessed September 1, 2014.
Miller  RH, Sim  I.  Physicians’ use of electronic medical records: barriers and solutions. Health Aff (Millwood). 2004;23(2):116-126.
PubMed   |  Link to Article
American Medical Association. CPT 2012 Professional Edition. Chicago, IL: AMA Press; 2012.
Blumenthal  D, Tavenner  M.  The “meaningful use” regulation for electronic health records. N Engl J Med. 2010;363(6):501-504.
PubMed   |  Link to Article
Chiang  MF, Read-Brown  S, Tu  DC,  et al.  Evaluation of electronic health record implementation in ophthalmology at an academic medical center (an American Ophthalmological Society thesis). Trans Am Ophthalmol Soc. 2013;111:70-92.
PubMed
Barlow  S, Johnson  J, Steck  J.  The economic effect of implementing an EMR in an outpatient clinical setting. J Healthc Inf Manag. 2004;18(1):46-51.
PubMed
Arya  R, Salovich  DM, Ohman-Strickland  P, Merlin  MA.  Impact of scribes on performance indicators in the emergency department. Acad Emerg Med. 2010;17(5):490-494.
PubMed   |  Link to Article
Miller  RH, West  C, Brown  TM, Sim  I, Ganchoff  C.  The value of electronic health records in solo or small group practices. Health Aff (Millwood). 2005;24(5):1127-1137.
PubMed   |  Link to Article

Figures

Tables

Table Graphic Jump LocationTable 1.  Total and Subspecialty Changes in Net Revenue and Volume per Month
Table Graphic Jump LocationTable 2.  Total and Individual Changes in Revenue to Volume Ratio by Ophthalmology Subspecialty
Table Graphic Jump LocationTable 3.  Summaries of Diagnostic and Procedural Volume by Transaction Master Identification Code per Month
Table Graphic Jump LocationTable 4.  Comparison of Coding Patterns Before and After EHR Implementation

References

Hillestad  R, Bigelow  J, Bower  A,  et al.  Can electronic medical record systems transform health care? potential health benefits, savings, and costs. Health Aff (Millwood). 2005;24(5):1103-1117.
PubMed   |  Link to Article
Menachemi  N, Burkhardt  J, Shewchuk  R, Burke  D, Brooks  RG.  Hospital information technology and positive financial performance: a different approach to finding an ROI. J Healthc Manag. 2006;51(1):40-58.
PubMed
Himmelstein  DU, Wright  A, Woolhandler  S.  Hospital computing and the costs and quality of care: a national study. Am J Med. 2010;123(1):40-46.
PubMed   |  Link to Article
Patil  M, Puri  L, Gonzalez  CM.  Productivity and cost implications of implementing electronic medical records into an ambulatory surgical subspecialty clinic. Urology. 2008;71(2):173-177.
PubMed   |  Link to Article
Chiang  MF, Boland  MV, Brewer  A,  et al; American Academy of Ophthalmology Medical Information Technology Committee.  Special requirements for electronic health record systems in ophthalmology. Ophthalmology. 2011;118(8):1681-1687.
PubMed   |  Link to Article
DeBry  PW.  Considerations for choosing an electronic medical record for an ophthalmology practice. Arch Ophthalmol. 2001;119(4):590-596.
PubMed   |  Link to Article
Lowes  R. Hospitals to feds: EHRs mean more accurate coding. Medscape website. http://www.medscape.com/viewarticle/772025. Published 2012. Accessed September 1, 2014.
Miller  RH, Sim  I.  Physicians’ use of electronic medical records: barriers and solutions. Health Aff (Millwood). 2004;23(2):116-126.
PubMed   |  Link to Article
American Medical Association. CPT 2012 Professional Edition. Chicago, IL: AMA Press; 2012.
Blumenthal  D, Tavenner  M.  The “meaningful use” regulation for electronic health records. N Engl J Med. 2010;363(6):501-504.
PubMed   |  Link to Article
Chiang  MF, Read-Brown  S, Tu  DC,  et al.  Evaluation of electronic health record implementation in ophthalmology at an academic medical center (an American Ophthalmological Society thesis). Trans Am Ophthalmol Soc. 2013;111:70-92.
PubMed
Barlow  S, Johnson  J, Steck  J.  The economic effect of implementing an EMR in an outpatient clinical setting. J Healthc Inf Manag. 2004;18(1):46-51.
PubMed
Arya  R, Salovich  DM, Ohman-Strickland  P, Merlin  MA.  Impact of scribes on performance indicators in the emergency department. Acad Emerg Med. 2010;17(5):490-494.
PubMed   |  Link to Article
Miller  RH, West  C, Brown  TM, Sim  I, Ganchoff  C.  The value of electronic health records in solo or small group practices. Health Aff (Millwood). 2005;24(5):1127-1137.
PubMed   |  Link to Article

Correspondence

CME


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Supplement.

eTable 1. EHR Incentive Payments (US Dollars) Received and Projected From EHR Implementation for Physicians Qualifying for Stage 1 and 2

eTable 2. Total Capital Implementation Costs

eTable 3. Cumulative Personnel Implementation Costs

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