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Figure.  Mean Monthly Work Relative Value Units (wRVUs) and Clinic Visit Volume of All 5 Practitioners
Mean Monthly Work Relative Value Units (wRVUs) and Clinic Visit Volume of All 5 Practitioners

Shown is a decreasing trend after electronic medical record (EMR) transition in wRVUs and clinic visit volume.

Table 1.  Monthly Work Relative Value Units (wRVUs) Before and After Transition to the Electronic Medical Record (EMR)
Monthly Work Relative Value Units (wRVUs) Before and After Transition to the Electronic Medical Record (EMR)
Table 2.  Monthly Clinic Visit Volume Before and After Transition to the Electronic Medical Record (EMR)
Monthly Clinic Visit Volume Before and After Transition to the Electronic Medical Record (EMR)
Table 3.  Work Relative Value Units (wRVUs) Comparing 6-Month Intervals Before vs After Transition to the Electronic Medical Record (EMR)
Work Relative Value Units (wRVUs) Comparing 6-Month Intervals Before vs After Transition to the Electronic Medical Record (EMR)
1.
Furukawa  MF.  Electronic medical records and efficiency and productivity during office visits.  Am J Manag Care. 2011;17(4):296-303.PubMedGoogle Scholar
2.
Wang  SJ, Middleton  B, Prosser  LA,  et al.  A cost-benefit analysis of electronic medical records in primary care.  Am J Med. 2003;114(5):397-403.PubMedGoogle ScholarCrossref
3.
Jackson  HA, Cashy  J, Frieder  O, Schaeffer  AJ.  Data mining derived treatment algorithms from the electronic medical record improve theoretical empirical therapy for outpatient urinary tract infections.  J Urol. 2011;186(6):2257-2262.PubMedGoogle ScholarCrossref
4.
Chaudhry  B, Wang  J, Wu  S,  et al.  Systematic review: impact of health information technology on quality, efficiency, and costs of medical care.  Ann Intern Med. 2006;144(10):742-752.PubMedGoogle ScholarCrossref
5.
Steinbrook  R.  Health care and the American Recovery and Reinvestment Act.  N Engl J Med. 2009;360(11):1057-1060.PubMedGoogle ScholarCrossref
6.
Blumenthal  D.  Stimulating the adoption of health information technology.  N Engl J Med. 2009;360(15):1477-1479.PubMedGoogle ScholarCrossref
7.
Patel  V, Jamoom  E, Hsiao  CJ, Furukawa  MF, Buntin  M.  Variation in electronic health record adoption and readiness for meaningful use: 2008-2011.  J Gen Intern Med. 2013;28(7):957-964.PubMedGoogle ScholarCrossref
8.
Samaan  ZM, Klein  MD, Mansour  ME, DeWitt  TG.  The impact of the electronic health record on an academic pediatric primary care center.  J Ambul Care Manage. 2009;32(3):180-187.PubMedGoogle ScholarCrossref
9.
Mahboubi  H, Salibian  AA, Wu  EC, Patel  MS, Armstrong  WB.  The role and utilization of electronic medical records in ambulatory otolaryngology.  Laryngoscope. 2013;123(10):2418-2422.PubMedGoogle Scholar
10.
Hing  E, Hall  MJ, Ashman  JJ.  Use of electronic medical records by ambulatory care providers: United States, 2006.  Natl Health Stat Report. 2010;(22):1-21.PubMedGoogle Scholar
11.
DesRoches  CM, Campbell  EG, Rao  SR,  et al.  Electronic health records in ambulatory care: a national survey of physicians.  N Engl J Med. 2008;359(1):50-60.PubMedGoogle ScholarCrossref
12.
Romano  MJ, Stafford  RS.  Electronic health records and clinical decision support systems: impact on national ambulatory care quality.  Arch Intern Med. 2011;171(10):897-903.PubMedGoogle Scholar
13.
Simon  SR, McCarthy  ML, Kaushal  R,  et al.  Electronic health records: which practices have them and how are clinicians using them?  AMIA Annu Symp Proc. 2006:1097.PubMedGoogle Scholar
14.
Burt  CW, Sisk  JE.  Which physicians and practices are using electronic medical records?  Health Aff (Millwood). 2005;24(5):1334-1343.PubMedGoogle ScholarCrossref
15.
Gans  D, Kralewski  J, Hammons  T, Dowd  B.  Medical groups’ adoption of electronic health records and information systems.  Health Aff (Millwood). 2005;24(5):1323-1333.PubMedGoogle ScholarCrossref
16.
Mahboubi  H, Salibian  AA, Wu  EC, Patel  MS, Armstrong  WB.  Contributing factors to adoption of electronic medical records in otolaryngology offices.  Laryngoscope. 2013;123(11):2658-2663.PubMedGoogle ScholarCrossref
17.
Bhattacharyya  N.  Characteristics and trends in ambulatory otolaryngology visits and practices.  Otolaryngol Head Neck Surg. 2012;147(6):1060-1064. PubMedGoogle ScholarCrossref
18.
Sun  GH, Eisenberg  LD, Ermini  EB,  et al.  2012 Update on meaningful use of electronic health records: recommendations from the AAO-HNS Medical Informatics Committee.  Otolaryngol Head Neck Surg. 2012;146(4):544-546.PubMedGoogle ScholarCrossref
19.
Shekelle  PG, Morton  SC, Keeler  EB.  Costs and benefits of health information technology.  Evid Rep Technol Assess (Full Rep). 2006;(132):1-71.PubMedGoogle Scholar
20.
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.PubMedGoogle ScholarCrossref
21.
Soper  WD.  Why I love my EMR.  Fam Pract Manag. 2002;9(9):35-38.PubMedGoogle Scholar
22.
Tundia  NL, Kelton  CM, Cavanaugh  TM, Guo  JJ, Hanseman  DJ, Heaton  PC.  The effect of electronic medical record system sophistication on preventive healthcare for women.  J Am Med Inform Assoc. 2013;20(2):268-276.PubMedGoogle ScholarCrossref
23.
Wagenblast  J, Adunka  O, Gstöttner  W,  et al.  AdOnco database: six years’ experience with the documentation of clinical and scientific data on patients with head and neck cancer.  In Vivo. 2010;24(4):603-606.PubMedGoogle Scholar
24.
Linder  JA, Ma  J, Bates  DW, Middleton  B, Stafford  RS.  Electronic health record use and the quality of ambulatory care in the United States.  Arch Intern Med. 2007;167(13):1400-1405.PubMedGoogle ScholarCrossref
25.
Crosson  JC, Ohman-Strickland  PA, Hahn  KA,  et al.  Electronic medical records and diabetes quality of care: results from a sample of family medicine practices.  Ann Fam Med. 2007;5(3):209-215.PubMedGoogle ScholarCrossref
26.
Victores  AJ, Coggins  K, Takashima  M.  Electronic health records and resident workflow: a time-motion study of otolaryngology residents.  Laryngoscope. 2015;125(3):594-598.PubMedGoogle ScholarCrossref
27.
duPont  NC, Koeninger  D, Guyer  JD, Travers  D.  Selecting an electronic medical record system for small physician practices.  N C Med J. 2009;70(5):399-403.PubMedGoogle Scholar
28.
Yasnoff  WA, Sweeney  L, Shortliffe  EH.  Putting health IT on the path to success.  JAMA. 2013;309(10):989-990.PubMedGoogle ScholarCrossref
29.
Miller  RH, Sim  I.  Physicians’ use of electronic medical records: barriers and solutions.  Health Aff (Millwood). 2004;23(2):116-126.PubMedGoogle ScholarCrossref
30.
Castillo  VH, Martínez-García  AI, Pulido  JR.  A knowledge-based taxonomy of critical factors for adopting electronic health record systems by physicians: a systematic literature review.  BMC Med Inform Decis Mak. 2010;10:60.PubMedGoogle ScholarCrossref
31.
Gadd  CS, Penrod  LE.  Assessing physician attitudes regarding use of an outpatient EMR: a longitudinal, multi-practice study.  Proc AMIA Symp. 2001:194-198.PubMedGoogle Scholar
Original Investigation
January 2017

Association Between Electronic Medical Record Implementation and Otolaryngologist Productivity in the Ambulatory Setting

Author Affiliations
  • 1Department of Otolaryngology–Head and Neck Surgery, University of California–Irvine Medical Center
JAMA Otolaryngol Head Neck Surg. 2017;143(1):20-24. doi:10.1001/jamaoto.2016.2528
Key Points

Question  Does transitioning to an electronic medical record system affect physician productivity as measured by work relative value units or clinic visit volume?

Findings  In this observational study, we examined 5 otolaryngologists in an academic ambulatory practice for 24 months. Monthly work relative value units before and after electronic medical record transition demonstrated a statistically significant decrease from 334 to 284, and monthly clinic visit volume showed a nonsignificant decrease from 132 to 121.

Meaning  Transitioning to an electronic medical record system in an ambulatory otolaryngology tertiary care setting may slightly decrease physician productivity in the 12-month period after implementation.

Abstract

Importance  In the current health care era, many medical practices are transitioning to a new electronic health record system. Until now, there has been little information published on the association between electronic medical record (EMR) use and otolaryngologist productivity in the ambulatory setting.

Objective  To examine the association between transitioning to an EMR system and physician productivity in otolaryngology.

Design, Setting, and Participants  Observational study at a tertiary care academic ambulatory center. Participants were 5 full-time otolaryngologists in practice, among whom a retrospective analysis of physician productivity was performed from May 5, 2013, through April 30, 2015.

Main Outcomes and Measures  We examined 5 practicing otolaryngologists for 24 months (12 months before and 12 months after transitioning to a new EMR system). Physician productivity was measured using the mean work relative value units (wRVUs) and the mean number of clinic visits. Each practitioner, with his wRVUs and clinic visit volume, was compared before and after implementation of the EMR system. The overall change in wRVUs and clinic visit volume was measured. The mean time spent after a full clinic day editing documentation before and after implementation of the EMR system for each practitioner was also recorded.

Results  Among all 5 practitioners (age range, 38-51 years), the monthly wRVUs decreased from a mean of 334 before EMR implementation to a mean of 284 after EMR implementation, with an absolute difference of 50 (95% CI, 6-85). The monthly clinic visit volume decreased from a mean of 132 to 121, with an absolute difference of 11 (95% CI, 0-18). When examined individually, only 1 physician had a significant decrease in wRVUs. The remainder of the physicians did not demonstrate a significant change in wRVUs or clinic visit volume. On average, the physicians spent 2.1 hours after clinic reviewing and editing documentation before the transition to the EMR system and 1.9 hours after the transition.

Conclusions and Relevance  Transitioning to an EMR system in an ambulatory otolaryngology tertiary care setting slightly decreased physician productivity as measured by wRVUs and clinic visit volume in the 12-month period after implementation in an incentivized compensation system.

Introduction

In the current health care era, many medical practices are transitioning to a new electronic health record system. Electronic medical records (EMRs) have been implemented in the ambulatory and hospital settings, with the goal of enhancing the quality and efficiency of health care.1 The use of EMRs has been shown to have many potential advantages, which include decreasing major health care cost,2 facilitating data collection and retrieval,3 reducing medical errors,4 and improving availability of the records to both patients and physicians.

Although there is no federal requirement for EMR use by physicians, the US government has incentivized the use of EMRs by subsidizing the adoption of “meaningful use” of certified EMRs in their practice.5 Under the American Recovery and Reinstatement Act of 2009, the federal government has allocated $17 billion in incentives for purchase and adoption of EMRs.6 Furthermore, physicians who do not demonstrate meaningful use of certified electronic health records will receive deductions from their reimbursement for services provided to Medicare and Medicaid patients effective from 2015 onward. The deductions began at 1% in 2015, increased to 2% in 2016, and will become 3% in 2017.6

Despite these federal incentives, many facilities remain reluctant to make a transition to an EMR system for many reasons. One possible explanation for this hesitation is that the use of EMRs may result in a decrease in physician productivity as previously shown in primary care facilities.7,8 Until now, there has been little information published, to our knowledge, on the association between EMR use and otolaryngologist productivity in the ambulatory setting. The objective of our study was to examine the association between transitioning to an EMR system and physician productivity in an ambulatory tertiary care otolaryngology clinic.

Methods

Institutional review board approval for the study was obtained from the University of California–Irvine Medical Center. Oral informed consent was obtained from participants. We examined 10 full-time otolaryngologists in the ambulatory setting at the tertiary care University of California–Irvine Medical Center from May 5, 2013, through April 30, 2015. On May 5, 2014, the otolaryngology ambulatory clinic made a transition to EMR use (Allscripts, Chicago, Illinois) for visit notes. The time frame examined represented a 24-month period, including 12 months before implementing the EMR switch and 12 months after transitioning to the new EMR system. Physician productivity was measured using the mean outpatient clinic work relative value units (wRVUs) and the mean number of ambulatory visits for each practitioner.

Five practitioners who either worked part-time at some point during the examined period or did not have at least 12 months of preimplementation and postimplementation wRVUs and clinic visit volume were excluded, resulting in 5 practitioners who were included in the study. Two other practitioners were not included because their practices were less than 2 years old and were continually increasing in volume. Physicians with less than 5 years of practice who continued to have growth in their practice were excluded because it would have confounded the data. The 5 physicians studied had been in practice for at least 5 years and were all subspecialists. They ranged in age from 38 to 51 years and had overall similar experience with the EMR system. All clinicians were comfortable with and trained in the EMR system before implementation.

A Wilcoxon rank sum test (nonparametric version of a paired t test) was used to compare each practitioner’s change in monthly wRVUs and clinic visit volume before and after EMR implementation. The overall mean of all practitioners’ monthly wRVUs and clinic visit volume was also compared before and after EMR implementation with a Wilcoxon rank sum test. Statistical analysis was performed using software programs (PASW Statistics 18; SPSS Inc and Minitab 17; Minitab Inc). The absolute difference and 95% CI for each analysis are reported. After implementation of the EMR system, each physician was retrospectively asked about the mean amount of time he spent editing documentation before and after EMR implementation, represented as hours spent after clinic per full clinic day.

Results

The overall wRVUs for each practitioner were compared in the 12 months before and 12 months after the transition to an EMR system and are listed in Table 1. Each of the 5 physicians demonstrated a decrease in wRVUs, only 1 of which was statistically significant. Among the 5 practitioners, the monthly wRVUs decreased from a mean of 334 before EMR implementation to a mean of 284 after EMR implementation, with an absolute difference of 50 (95% CI, 6-85).

The overall monthly clinic visit volume for each practitioner was compared in the 12 months before the transition and 12 months after the transition to an EMR system (Table 2). Each practitioner demonstrated a decrease in clinic visit volume after transitioning to the EMR system, which did not reach statistical significance. Among all 5 practitioners, the monthly clinic visit volume decreased from a mean of 132 to 121, with an absolute difference of 11 (95% CI, 0-18). The monthly wRVUs and clinic visit volume for all practitioners are shown in the Figure.

At the University of California–Irvine Medical Center, physicians were asked to reduce their clinic visit volume for the first week after implementation of the EMR system. The mean wRVUs and clinic visit volume further stratified into 6-month periods are listed in Table 3. Specifically, the wRVUs and clinic visit volume for the first 6 months before implementation were compared with the first 6 months after implementation. This comparison demonstrated no significant decrease in either variable, suggesting that the decrease in wRVUs and clinic visit volume demonstrated in the 12-month period after the transition was not an effect of an initial drop in productivity.

On average, the physicians spent 2.1 hours after clinic reviewing and editing documentation before the transition to the EMR system. After the transition to the EMR system, the mean time spent was 1.9 hours.

Discussion

Despite the federal incentives and presumed benefits of EMRs, the rate of EMR adoption by ambulatory clinics has been slow as noted by several studies.7,9-11 Other studies12-15 of ambulatory clinics showed that practices with 11 or more physicians were more likely to use an EMR system compared with smaller ones. Surgical specialty offices, such as otolaryngology, affiliated with institutions (eg, health maintenance organizations or academic centers) are more likely to use EMRs.16 On average, EMR use in otolaryngology during recent years has progressed almost in parallel to other medical fields, with the percentage of otolaryngology practices at least partly using an EMR system increasing from 27% to 48.5%.9,16 In 2012, Bhattacharyya17 found that approximately 40.2% of otolaryngology outpatient practices were using EMRs. A survey performed in 2011 by the American Academy of Otolaryngology–Head and Neck Surgery indicated that 67% of the respondents were using EMRs in their practices.18

Electronic medical records have been discussed as a way to decrease medical errors, reduce costs, and increase coordination and quality of patient care.2,19-21 However, studies on the effect of EMRs on practices have shown conflicting results. Two studies1,22 found that the use of EMRs improves health care quality and practitioner productivity. Wagenblast et al23 showed that EMR use could result in reliable, time-efficient, and accurate patient care. Furukawa1 reported that the use of EMRs was associated with higher probabilities of ordering or performing examinations, laboratory tests, health education, and diagnostic services, whereas the visit duration remained unchanged. Multiple studies12,24,25 have not demonstrated an association between quality of care and EMR use.

Decreased productivity could also have potential consequences on resident physician education. In our study, residents had a uniform role in documentation in all clinics with all the physicians. Resident physicians assist in a proportion of clinic encounters and document the visit in its entirety, after which a short addendum and electronic signature by the attending is added. This workflow was similar both before and after implementation of EMRs. A recent study26 examining residents showed no difference in the time spent on didactic education after implementation of the EMR system; however, informal education in the clinic occurring between the residents and attendings was not examined. Therefore, the association between EMR use and education in the clinic remains unclear at this time. Further studies are required to better assess this issue.

Electronic medical record implementation in an ambulatory setting is hindered by multiple obstacles, including high costs, lack of a standardized platform, complexity of the EMR system, and absence of skilled staff.20,27,28 Another commonly cited barrier to transitioning to an EMR system in the ambulatory setting is the potential for future loss of productivity and efficiency.29,30 Electronic medical record use has been shown to result in decreased physician productivity in primary care facilities.7,8 Similarly, Gadd and Penrod31 demonstrated physician dissatisfaction and significant time concerns after 6 months’ use of EMRs. Until now, there has been little published, to our knowledge, on the association between EMR use and otolaryngologist productivity in the ambulatory setting.

Our study examined physician productivity in an ambulatory tertiary care center. The study examined 2 periods during 24 months that represent a similar time of year, eliminating seasonal or census variation. Overall, among all the practitioners, there was a significant decrease in wRVUs and a nonsignificant decrease in clinic visit volume in the 12-month period after transitioning to EMRs compared with the 12-month period before transitioning to EMRs, even in an incentivized compensation model. There was a decreasing overall trend in both wRVUs and clinic visit volume in the months after the switch to EMRs. Comparing the individual 6-month periods before and after EMR implementation, we demonstrated no significant change in the initial 6-month period in physician productivity, suggesting that the overall change in productivity after EMR implementation may not be a product of an initial drop and, in fact, persists for 12 months after implementation.

Based on a survey of the physicians included in our study, the mean amount of time spent after clinic reviewing documentation demonstrated no significant change after EMR implementation. Overall, we showed that transitioning to an EMR system in an otolaryngology tertiary care clinic may result in a decrease in productivity when measured by wRVUs and clinic visit volume, without changing the hours spent by the clinician on documentation after clinic. This finding may be due to an increase in the amount of time spent documenting during clinic with an EMR system, which results in a decrease in productivity.

Furthermore, before EMR implementation, the physicians would generally take handwritten notes during the clinic visit and dictate between visits or at the end of the day. These dictations then were later reviewed and finalized. The EMR system has allowed the physicians to eliminate the extra step of reviewing dictations but has increased the time spent typing documents during the clinic day. None of the physicians used a scribe during the 24-month period. To improve productivity and reduce the amount of time spent on documentation, clinicians at our clinic have turned to scribes as a possible solution. Three of the physicians are either currently using a scribe or considering obtaining one. While speech-to-text software is another alternative available in our EMR system, it has not been found to be reliable, and none of the physicians use it. In a subspecialty practice where almost all patients are referred, a letter is sent to all referring physicians for every visit. In this context, the EMR system has made it more convenient and has automated the process of sending the clinic note to physicians involved in patient care because the system contains a database of physicians with their contact information, allowing for ease of communication.

There are certain limitations that should be considered when evaluating the findings from this study. First, we evaluated only 5 physicians. While the sample size for the study was adequately powered to detect a difference in our primary outcome, a larger sample size would further reduce the risk of falsely accepting the null hypothesis. A second potential limitation is the short length of time examined. Although we thought that 1 year would eliminate seasonal and holiday variation, there may be potential changes in each physician’s clinical practice and volume that might have affected the results over 24 months. In addition, the assessment of the length of time spent reviewing documentation by each clinician is subject to recall bias. Instead, clinician responses may characterize the perceived rather than the actual length of time they spent on documentation. Despite these limitations, we believe that this observational study contributes to the literature by examining the association between EMR use and physician productivity.

Conclusions

Electronic medical record use is projected to continue to increase among otolaryngology ambulatory care practices. The association between EMR use and physician productivity continues to hinder the transition within some facilities. Transitioning to an EMR system in an ambulatory otolaryngology tertiary care setting was shown to decrease overall physician productivity as measured by wRVUs and clinic visit volume.

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Article Information

Corresponding Author: Hamid R. Djalilian, MD, Department of Otolaryngology–Head and Neck Surgery, University of California–Irvine Medical Center, 19182 Jamboree Rd, Irvine, CA 92697 (hdjalili@uci.edu).

Accepted for Publication: July 8, 2016.

Published Online: September 1, 2016. doi:10.1001/jamaoto.2016.2528

Author Contributions: Dr Haidar 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: Haidar, Moshtaghi, Mahboubi, Djalilian.

Acquisition, analysis, or interpretation of data: Haidar, Moshtaghi, Ghavami, Ziai, Hojjat, Armstrong.

Drafting of the manuscript: Haidar, Moshtaghi, Ghavami, Hojjat.

Critical revision of the manuscript for important intellectual content: Haidar, Moshtaghi, Mahboubi, Ziai, Armstrong, Djalilian.

Statistical analysis: Haidar, Moshtaghi, Mahboubi, Ghavami, Hojjat.

Administrative, technical, or material support: Ghavami, Ziai.

Study supervision: Mahboubi, Djalilian.

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

References
1.
Furukawa  MF.  Electronic medical records and efficiency and productivity during office visits.  Am J Manag Care. 2011;17(4):296-303.PubMedGoogle Scholar
2.
Wang  SJ, Middleton  B, Prosser  LA,  et al.  A cost-benefit analysis of electronic medical records in primary care.  Am J Med. 2003;114(5):397-403.PubMedGoogle ScholarCrossref
3.
Jackson  HA, Cashy  J, Frieder  O, Schaeffer  AJ.  Data mining derived treatment algorithms from the electronic medical record improve theoretical empirical therapy for outpatient urinary tract infections.  J Urol. 2011;186(6):2257-2262.PubMedGoogle ScholarCrossref
4.
Chaudhry  B, Wang  J, Wu  S,  et al.  Systematic review: impact of health information technology on quality, efficiency, and costs of medical care.  Ann Intern Med. 2006;144(10):742-752.PubMedGoogle ScholarCrossref
5.
Steinbrook  R.  Health care and the American Recovery and Reinvestment Act.  N Engl J Med. 2009;360(11):1057-1060.PubMedGoogle ScholarCrossref
6.
Blumenthal  D.  Stimulating the adoption of health information technology.  N Engl J Med. 2009;360(15):1477-1479.PubMedGoogle ScholarCrossref
7.
Patel  V, Jamoom  E, Hsiao  CJ, Furukawa  MF, Buntin  M.  Variation in electronic health record adoption and readiness for meaningful use: 2008-2011.  J Gen Intern Med. 2013;28(7):957-964.PubMedGoogle ScholarCrossref
8.
Samaan  ZM, Klein  MD, Mansour  ME, DeWitt  TG.  The impact of the electronic health record on an academic pediatric primary care center.  J Ambul Care Manage. 2009;32(3):180-187.PubMedGoogle ScholarCrossref
9.
Mahboubi  H, Salibian  AA, Wu  EC, Patel  MS, Armstrong  WB.  The role and utilization of electronic medical records in ambulatory otolaryngology.  Laryngoscope. 2013;123(10):2418-2422.PubMedGoogle Scholar
10.
Hing  E, Hall  MJ, Ashman  JJ.  Use of electronic medical records by ambulatory care providers: United States, 2006.  Natl Health Stat Report. 2010;(22):1-21.PubMedGoogle Scholar
11.
DesRoches  CM, Campbell  EG, Rao  SR,  et al.  Electronic health records in ambulatory care: a national survey of physicians.  N Engl J Med. 2008;359(1):50-60.PubMedGoogle ScholarCrossref
12.
Romano  MJ, Stafford  RS.  Electronic health records and clinical decision support systems: impact on national ambulatory care quality.  Arch Intern Med. 2011;171(10):897-903.PubMedGoogle Scholar
13.
Simon  SR, McCarthy  ML, Kaushal  R,  et al.  Electronic health records: which practices have them and how are clinicians using them?  AMIA Annu Symp Proc. 2006:1097.PubMedGoogle Scholar
14.
Burt  CW, Sisk  JE.  Which physicians and practices are using electronic medical records?  Health Aff (Millwood). 2005;24(5):1334-1343.PubMedGoogle ScholarCrossref
15.
Gans  D, Kralewski  J, Hammons  T, Dowd  B.  Medical groups’ adoption of electronic health records and information systems.  Health Aff (Millwood). 2005;24(5):1323-1333.PubMedGoogle ScholarCrossref
16.
Mahboubi  H, Salibian  AA, Wu  EC, Patel  MS, Armstrong  WB.  Contributing factors to adoption of electronic medical records in otolaryngology offices.  Laryngoscope. 2013;123(11):2658-2663.PubMedGoogle ScholarCrossref
17.
Bhattacharyya  N.  Characteristics and trends in ambulatory otolaryngology visits and practices.  Otolaryngol Head Neck Surg. 2012;147(6):1060-1064. PubMedGoogle ScholarCrossref
18.
Sun  GH, Eisenberg  LD, Ermini  EB,  et al.  2012 Update on meaningful use of electronic health records: recommendations from the AAO-HNS Medical Informatics Committee.  Otolaryngol Head Neck Surg. 2012;146(4):544-546.PubMedGoogle ScholarCrossref
19.
Shekelle  PG, Morton  SC, Keeler  EB.  Costs and benefits of health information technology.  Evid Rep Technol Assess (Full Rep). 2006;(132):1-71.PubMedGoogle Scholar
20.
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.PubMedGoogle ScholarCrossref
21.
Soper  WD.  Why I love my EMR.  Fam Pract Manag. 2002;9(9):35-38.PubMedGoogle Scholar
22.
Tundia  NL, Kelton  CM, Cavanaugh  TM, Guo  JJ, Hanseman  DJ, Heaton  PC.  The effect of electronic medical record system sophistication on preventive healthcare for women.  J Am Med Inform Assoc. 2013;20(2):268-276.PubMedGoogle ScholarCrossref
23.
Wagenblast  J, Adunka  O, Gstöttner  W,  et al.  AdOnco database: six years’ experience with the documentation of clinical and scientific data on patients with head and neck cancer.  In Vivo. 2010;24(4):603-606.PubMedGoogle Scholar
24.
Linder  JA, Ma  J, Bates  DW, Middleton  B, Stafford  RS.  Electronic health record use and the quality of ambulatory care in the United States.  Arch Intern Med. 2007;167(13):1400-1405.PubMedGoogle ScholarCrossref
25.
Crosson  JC, Ohman-Strickland  PA, Hahn  KA,  et al.  Electronic medical records and diabetes quality of care: results from a sample of family medicine practices.  Ann Fam Med. 2007;5(3):209-215.PubMedGoogle ScholarCrossref
26.
Victores  AJ, Coggins  K, Takashima  M.  Electronic health records and resident workflow: a time-motion study of otolaryngology residents.  Laryngoscope. 2015;125(3):594-598.PubMedGoogle ScholarCrossref
27.
duPont  NC, Koeninger  D, Guyer  JD, Travers  D.  Selecting an electronic medical record system for small physician practices.  N C Med J. 2009;70(5):399-403.PubMedGoogle Scholar
28.
Yasnoff  WA, Sweeney  L, Shortliffe  EH.  Putting health IT on the path to success.  JAMA. 2013;309(10):989-990.PubMedGoogle ScholarCrossref
29.
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