Original Research
22 February 2022

Early Changes in Billing and Notes After Evaluation and Management Guideline Change

Publication: Annals of Internal Medicine
Volume 175, Number 4
Visual Abstract. Early Changes in Billing and Notes After 2021 E/M Guideline Change.
Regulatory changes to billing codes for outpatient evaluation and management (E/M) visits were intended to reduce documentation requirements and account for provider time spent coordinating care for patients. This study analyzes national data on changes in E/M visits, note length, and time spent in electronic health records before and after regulatory changes in 2021.

Abstract

Background:

The American Medical Association updated guidance in 2021 for frequently used billing codes for outpatient evaluation and management (E/M) visits. The intent was to account for provider time outside of face-to-face encounters and to reduce onerous documentation requirements.

Objective:

To analyze E/M visit use, documentation length, and time spent in the electronic health record (EHR) before and after the guideline change.

Design:

Observational, retrospective, pre–post study.

Setting:

U.S.-based ambulatory practices using the Epic Systems EHR.

Participants:

303 547 advanced practice providers and physicians across 389 organizations.

Measurements:

Data from September 2020 through April 2021 containing weekly provider-level E/M code and EHR use metadata were extracted from the Epic Signal database. We descriptively analyzed overall and specialty-specific changes in E/M visit use, note length, and time spent in the EHR before and after the new guidelines using provider-level paired t tests.

Results:

Following the new guidelines, level 3 visits decreased by 2.41 percentage points (95% CI, −2.48 to −2.34 percentage points) to 38.5% of all E/M visits, a 5.9% relative decrease from fall 2020. Level 4 visits increased by 0.89 percentage points (CI, 0.82 to 0.96 percentage points) to 40.9% of E/M visits, a 2.2% relative increase. Level 5 visits (the highest acuity level) increased by 1.85 percentage points (CI, 1.81 to 1.89 percentage points) to 10.1% of E/M visits, a 22.6% relative increase. These changes varied by specialty. We found no meaningful changes in measures of note length or time spent in the EHR.

Limitation:

The Epic ambulatory client base may underrepresent smaller and independent practices.

Conclusion:

Immediate changes in E/M coding contrast with null findings for changes in both note length and EHR time. Provider organizations are positioned to respond more rapidly to billing process changes than to changes in care delivery and associated EHR use behaviors. Fully realizing the intended benefits of this guideline change will require more time, facilitation, and scaling of best practices that more directly address EHR documentation practices and associated burden.

Primary Funding Source:

None.

Get full access to this article

View all available purchase options and get full access to this article.

References

1.
Rotenstein LS, Torre M, Ramos MA, et al. Prevalence of burnout among physicians: a systematic review. JAMA. 2018;320:1131-1150. [PMID: 30326495] doi: 10.1001/jama.2018.12777
2.
Wright AA, Katz IT. Beyond burnout - redesigning care to restore meaning and sanity for physicians. N Engl J Med. 2018;378:309-311. [PMID: 29365301] doi: 10.1056/NEJMp1716845
3.
Downing NL, Bates DW, Longhurst CA. Physician burnout in the electronic health record era: are we ignoring the real cause. Ann Intern Med. 2018;169:50-51. [PMID: 29801050] doi: 10.7326/M18-0139
4.
Ratwani RM, Savage E, Will A, et al. A usability and safety analysis of electronic health records: a multi-center study. J Am Med Inform Assoc. 2018;25:1197-1201. [PMID: 29982549] doi: 10.1093/jamia/ocy088
5.
Gardner RL, Cooper E, Haskell J, et al. Physician stress and burnout: the impact of health information technology. J Am Med Inform Assoc. 2019;26:106-114. [PMID: 30517663] doi: 10.1093/jamia/ocy145
6.
Adler-Milstein J, Zhao W, Willard-Grace R, et al. Electronic health records and burnout: time spent on the electronic health record after hours and message volume associated with exhaustion but not with cynicism among primary care clinicians. J Am Med Inform Assoc. 2020;27:531-538. [PMID: 32016375] doi: 10.1093/jamia/ocz220
7.
Hettinger AZ, Melnick ER, Ratwani RM. Advancing electronic health record vendor usability maturity: progress and next steps. J Am Med Inform Assoc. 2021;28:1029-1031. [PMID: 33517394] doi: 10.1093/jamia/ocaa329
8.
Sinsky C, Colligan L, Li L, et al. Allocation of physician time in ambulatory practice: a time and motion study in 4 specialties. Ann Intern Med. 2016;165:753-760. [PMID: 27595430] doi: 10.7326/M16-0961
9.
Tai-Seale M, Olson CW, Li J, et al. Electronic health record logs indicate that physicians split time evenly between seeing patients and desktop medicine. Health Aff (Millwood). 2017;36:655-662. [PMID: 28373331] doi: 10.1377/hlthaff.2016.0811
10.
Arndt BG, Beasley JW, Watkinson MD, et al. Tethered to the EHR: primary care physician workload assessment using EHR event log data and time-motion observations. Ann Fam Med. 2017;15:419-426. [PMID: 28893811] doi: 10.1370/afm.2121
11.
Young RA, Burge SK, Kumar KA, et al. A time-motion study of primary care physicians' work in the electronic health record era. Fam Med. 2018;50:91-99. [PMID: 29432623] doi: 10.22454/FamMed.2018.184803
12.
Melnick ER, Ong SY, Fong A, et al. Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis. J Am Med Inform Assoc. 2021;28:1383-1392. [PMID: 33822970] doi: 10.1093/jamia/ocab011
13.
Overhage JM, McCallie D Jr. Physician time spent using the electronic health record during outpatient encounters: a descriptive study. Ann Intern Med. 2020;172:169-174. [PMID: 31931523] doi: 10.7326/M18-3684
14.
Overhage JM, Johnson KB. Pediatrician electronic health record time use for outpatient encounters. Pediatrics. 2020;146. [PMID: 33139456] doi: 10.1542/peds.2019-4017
15.
Holmgren AJ, Downing NL, Bates DW, et al. Assessment of electronic health record use between US and non-US health systems. JAMA Intern Med. 2021;181:251-259. [PMID: 33315048] doi: 10.1001/jamainternmed.2020.7071
16.
Berenson RA, Goodson JD. Finding value in unexpected places---fixing the medicare physician fee schedule. N Engl J Med. 2016;374:1306-9. [PMID: 26959109] doi: 10.1056/NEJMp1600999
17.
Song Z, Goodson JD. The CMS proposal to reform office-visit payments. N Engl J Med. 2018;379:1102-1104. [PMID: 30110241] doi: 10.1056/NEJMp1809742
18.
Landon BE. A step toward protecting payments for primary care. N Engl J Med. 2019;380:507-510. [PMID: 30726687] doi: 10.1056/NEJMp1810848
19.
O’Reilly KB. E/M office-visit changes on track for 2021: what doctors must know. American Medical Association. 5 August 2020. Accessed at www.ama-assn.org/practice-management/cpt/em-office-visit-changes-track-2021-what-doctors-must-know on 10 August 2021.
20.
Adler-Milstein J, Adelman JS, Tai-Seale M, et al. EHR audit logs: a new goldmine for health services research. J Biomed Inform. 2020;101:103343. [PMID: 31821887] doi: 10.1016/j.jbi.2019.103343
21.
Top 10 Ambulatory EHR Vendors by 2019 Market Share. Definitive Healthcare; May 2019. Accessed at www.definitivehc.com/blog/top-ambulatory-ehr-systems on 4 August 2021.
22.
Baxter SL, Apathy NC, Cross DA, et al. Measures of electronic health record use in outpatient settings across vendors. J Am Med Inform Assoc. 2021;28:955-959. [PMID: 33211862] doi: 10.1093/jamia/ocaa266
23.
Cohen G, Brown L, Fitzgerald M, et al. To measure the burden of EHR use, audit logs offer promise—but not without further collaboration. Health Affairs. 28 February 2020. Accessed at www.healthaffairs.org/do/10.1377/hblog20200226.453011/full on 28 February 2020.
24.
Rule A, Chiang MF, Hribar MR. Using electronic health record audit logs to study clinical activity: a systematic review of aims, measures, and methods. J Am Med Inform Assoc. 2020;27:480-490. [PMID: 31750912] doi: 10.1093/jamia/ocz196
25.
McPeek-Hinz E, Boazak M, Sexton JB, et al. Clinician burnout associated with sex, clinician type, work culture, and use of electronic health records. JAMA Netw Open. 2021;4:e215686. [PMID: 33877310] doi: 10.1001/jamanetworkopen.2021.5686
26.
Hron JD, Lourie E. Have you got the time? Challenges using vendor electronic health record metrics of provider efficiency. J Am Med Inform Assoc. 2020;27:644-646. [PMID: 32016394] doi: 10.1093/jamia/ocz222
27.
Basu S, Song Z, Phillips RS, et al. Implications of changes in medicare payment and documentation for primary care spending and time use. J Gen Intern Med. 2021;36:836-839. [PMID: 32495087] doi: 10.1007/s11606-020-05857-4
28.
American Medical Association. Are commercial health plans required to adopt revisions to the E/M codes? Accessed at www.ama-assn.org/practice-management/cpt/are-commercial-health-plans-required-adopt-revisions-em-codes on 27 December 2021.
29.
Rule A, Hribar MR. Frequent but fragmented: use of note templates to document outpatient visits at an academic health center. J Am Med Inform Assoc. 2021;29:137-141. [PMID: 34664655] doi: 10.1093/jamia/ocab230
30.
Polites GL, Karahanna E. Shackled to the status quo: the inhibiting effects of incumbent system habit, switching costs, and inertia on new system acceptance. MIS Quarterly. 2012;36:21-42. doi: 10.2307/41410404
31.
Peckham C, Kane L, Rosensteel S. Medscape EHR Report 2016: Physicians Rate Top EHRs. Medscape. 25 August 2016. Accessed at www.medscape.com/features/slideshow/public/ehr2016 on 4 August 2021.
32.
Mamykina L, Vawdrey DK, Stetson PD, et al. Clinical documentation: composition or synthesis. J Am Med Inform Assoc. 2012;19:1025-31. [PMID: 22813762] doi: 10.1136/amiajnl-2012-000901

Information & Authors

Information

Published In

cover image Annals of Internal Medicine
Annals of Internal Medicine
Volume 175Number 4April 2022
Pages: 499 - 504

History

Published online: 22 February 2022
Published in issue: April 2022

Keywords

Authors

Affiliations

Perelman School of Medicine and Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, and Regenstrief Institute, Indianapolis, Indiana (N.C.A.)
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania (A.J.H., S.F.)
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania (A.J.H., S.F.)
Dori A. Cross, PhD
Health Policy & Management, School of Public Health, University of Minnesota, Minneapolis, Minnesota (D.A.C.).
Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health National Center for Advancing Translational Sciences.
Acknowledgment: The authors thank Debra Laumer, Santana Briones, and Sarah LaMar from the PennMedicine EHR Transformation team for their assistance in acquiring pilot data for this study. The authors thank Drs. Bill Hanson, John McGreevey, J.T. Howell, and Rachel Werner for their support for the project. Finally, the authors thank Chris Gates from Epic Systems for his assistance in extracting the data for this study.
Grant Support: By training grant T32-HS026116-04 from the Agency for Healthcare Research and Quality (Dr. Apathy) and by National Institutes of Health National Center for Advancing Translational Sciences grants KL2TR002492 and UL1TR002494 at the University of Minnesota (Dr. Cross).
Reproducible Research Statement: Study protocol: Not available. Statistical code: Available from Dr. Apathy (e-mail, [email protected]). Data set: Data available pending release approval from Epic Systems; contact Dr. Apathy if interested.
Corresponding Author: Nate C. Apathy, PhD, Perelman School of Medicine, University of Pennsylvania, 3641 Locust Walk, Philadelphia, PA 19104; e-mail, [email protected].
Author Contributions: Conception and design: N.C. Apathy, S. Fendrich, D.A. Cross.
Analysis and interpretation of the data: N.C. Apathy, A.J. Hare, S. Fendrich, D.A. Cross.
Drafting of the article: N.C. Apathy, A.J. Hare, D.A. Cross.
Critical revision of the article for important intellectual content: N.C. Apathy, A.J. Hare, D.A. Cross.
Final approval of the article: N.C. Apathy, A.J. Hare, S. Fendrich, D.A. Cross.
Statistical expertise: N.C. Apathy.
Administrative, technical, or logistic support: N.C. Apathy, A.J. Hare.
Collection and assembly of data: N.C. Apathy.
This article was published at Annals.org on 22 February 2022.

Metrics & Citations

Metrics

Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. For an editable text file, please select Medlars format which will download as a .txt file. Simply select your manager software from the list below and click Download.

For more information or tips please see 'Downloading to a citation manager' in the Help menu.

Format





Download article citation data for:
Nate C. Apathy, Allison J. Hare, Sarah Fendrich, et al. Early Changes in Billing and Notes After Evaluation and Management Guideline Change. Ann Intern Med.2022;175:499-504. [Epub 22 February 2022]. doi:10.7326/M21-4402

View More

Get Access

Login Options:
Purchase

You will be redirected to acponline.org to sign-in to Annals to complete your purchase.

Create your Free Account

You will be redirected to acponline.org to create an account that will provide access to Annals.

View options

PDF/ePub

View PDF/ePub

Related in ACP Journals

Full Text

View Full Text

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share on social media