Association between Electronic Health Records and Health Care Utilization

R. Kaushal; A. Edwards; L.M. Kern; with the HITEC Investigators

doi:10.4338/ACI-2014-10-RA-0089

Applied Clinical Informatics, Table of Contents

Appl Clin Inform 2015; 06(01): 42-55
DOI: 10.4338/ACI-2014-10-RA-0089

Research Article

Schattauer GmbH

Association between Electronic Health Records and Health Care Utilization

Authors

R. Kaushal

¹Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY.

²Health Information Technology Evaluation Collaborative, New York, NY.

³Center for Healthcare Informatics and Policy, Weill Cornell Medical College, New York, NY.

⁴Department of Pediatrics, Weill Cornell Medical College, New York, NY.

⁵Department of Medicine, Weill Cornell Medical College, New York, NY.

⁶New York-Presbyterian Hospital, New York, NY.
A. Edwards

¹Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY.

²Health Information Technology Evaluation Collaborative, New York, NY.

³Center for Healthcare Informatics and Policy, Weill Cornell Medical College, New York, NY.
L.M. Kern

¹Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY.

²Health Information Technology Evaluation Collaborative, New York, NY.

³Center for Healthcare Informatics and Policy, Weill Cornell Medical College, New York, NY.

⁵Department of Medicine, Weill Cornell Medical College, New York, NY.

with the HITEC Investigators

Abstract

Summary

Background: The federal government is investing approximately $20 billion in electronic health records (EHRs), in part to address escalating health care costs. However, empirical evidence that provider use of EHRs decreases health care costs is limited.

Objective: To determine any association between EHRs and health care utilization.

Methods: We conducted a cohort study (2008–2009) in the Hudson Valley, a multi-payer, multi-provider community in New York State. We included 328 primary care physicians in predominantly small practices (median practice size four primary care physicians), who were caring for 223,772 patients. Data from an independent practice association was used to determine adoption of EHRs. Claims data aggregated across five commercial health plans was used to characterize seven types of health care utilization: primary care visits, specialist visits, radiology tests, laboratory tests, emergency department visits, hospital admissions, and readmissions. We used negative binomial regression to determine associations between EHR adoption and each utilization outcome, adjusting for ten physician characteristics.

Results: Approximately half (48%) of the physicians were using paper records and half (52%) were using EHRs. For every 100 patients seen by physicians using EHRs, there were 14 fewer specialist visits (adjusted p < 0.01) and 9 fewer radiology tests (adjusted p = 0.01). There were no significant differences in rates of primary care visits, laboratory tests, emergency department visits, hospitalizations or readmissions.

Conclusions: Patients of primary care providers who used EHRs were less likely to have specialist visits and radiology tests than patients of primary care providers who did not use EHRs.

Citation: Kaushal R, Edwards A, Kern LM, with the HITEC Investigators. Association between electronic health records and health care utilization. Appl Clin Inf 2015; 6: 42–55

http://dx.doi.org/10.4338/ACI-2014-10-RA-0089

Keywords

Electronic health records - health services - health utilization - primary health care

Full Text

References

References
1 Berwick DM, Hackbarth AD. Eliminating waste in US health care. J Am Med Inform Assoc 2012; 307 (14) 1513-1516. PubMed PMID: 22419800. Epub 2012/03/16.
2 Keehan SP, Sisko AM, Truffer CJ, Poisal JA, Cuckler GA, Madison AJ. et al. National health spending projections through 2020: economic recovery and reform drive faster spending growth. Health Aff (Mill-wood) 2011; 30 (08) 1594-1605. PubMed PMID: 21798885. Epub 2011/07/30.
3 Halamka JD. Health information technology: shall we wait for the evidence?. Ann Intern Med 2006; 144 (10) 775-776. PubMed PMID: 16702595.
4 Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J. et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. J Am Med Inform Assoc 2005; 293 (10) 1223-1238. PubMed PMID: 15755945. Epub 2005/03/10.
5 Steinbrook R. Health care and the American Recovery and Reinvestment Act. N Engl J Med 2009; 360 (11) 1057-1060. PubMed PMID: 19224738. Epub 2009/02/20.
6 New York State Department of Health.. Office of Health Information Technology Transformation. (Accessed December 12, 1014 http://www.health.state.ny.us/technology. )
7 Kellermann AL, Jones SS. What it will take to achieve the as-yet-unfulfilled promises of health information technology. Health Aff (Millwood) 2013; 32 (01) 63-68. PubMed PMID: 23297272. Epub 2013/01/09.
8 Low AFH, Phillips AB, Ancker JS, Patel AR, Kern LM, Kaushal R. Financial effects of health information technology: a systematic review. The American journal of managed care 2013; 19 10 Spec No SP369-SP376. PubMed PMID: 24511891.
9 Congressional Budget Office.. Evidence on the costs and benefits of health information technology. 2008 (Accessed December 12, 2014, at www.cbo.gov/sites/default/files/cbofiles/ftpdocs/91xx/doc9168/05–20-healthit.pdf. )
10 Bates DW, Gawande AA. Improving safety with information technology. N Engl J Med 2003; 348 (25) 2526-2534. PubMed PMID: 12815139.
11 Kern LM, Barron Y, Dhopeshwarkar RV, Edwards A, Kaushal R. Electronic health records and ambulatory quality of care. J Gen Intern Med 2013; 28 (04) 496-503. PubMed PMID: 23054927. Epub 2012/10/12.
12 Tierney WM, McDonald CJ, Martin DK, Rogers MP. Computerized display of past test results. Effect on outpatient testing. Ann Intern Med 1987; 107 (04) 569-574. PubMed PMID: 3631792.
13 Poissant L, Pereira J, Tamblyn R, Kawasumi Y. The impact of electronic health records on time efficiency of physicians and nurses: a systematic review. J Am Med Inform Assoc 2005; 12 (05) 505-516. PubMed PMID: 15905487. Epub 2005/05/21.
14 Cheriff AD, Kapur AG, Qiu M, Cole CL. Physician productivity and the ambulatory EHR in a large academic multi-specialty physician group. Int J Med Inform 2010; 79 (07) 492-500. PubMed PMID: 20478738. Epub 2010/05/19.
15 Abelson R, Creswell J, Palmer G. Medicare bills rise as records turn electronic. New York Times. September 22, 2012; Sect. A1.
16 Grieger DL, Cohen SH, Krusch DA. A pilot study to document the return on investment for implementing an ambulatory electronic health record at an academic medical center. J Am Coll Surg 2007; 205 (01) 89-96. PubMed PMID: 17617337. Epub 2007/07/10.
17 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 (05) 1127-1137. PubMed PMID: 16162555. Epub 2005/09/16.
18 Welch WP, Bazarko D, Ritten K, Burgess Y, Harmon R, Sandy LG. Electronic health records in four community physician practices: impact on quality and cost of care. J Am Med Inform Assoc 2007; 14 (03) 320-328. PubMed PMID: 17329734. Epub 2007/03/03.
19 Byrne CM, Mercincavage LM, Pan EC, Vincent AG, Johnston DS, Middleton B. The value from investments in health information technology at the U. S. Department of Veterans Affairs. Health Aff (Millwood) 2010; 29 (04) 629-638. PubMed PMID: 20368592. Epub 2010/04/07.
20 Chen C, Garrido T, Chock D, Okawa G, Liang L. The Kaiser Permanente Electronic Health Record: transforming and streamlining modalities of care. Health Aff (Millwood) 2009; 28 (02) 323-333. PubMed PMID: 19275987. Epub 2009/03/12.
21 Garrido T, Jamieson L, Zhou Y, Wiesenthal A, Liang L. Effect of electronic health records in ambulatory care: retrospective, serial, cross sectional study. BMJ 2005; 330 7491 581. PubMed PMID: 15760999. Epub 2005/03/12.
22 Wang SJ, Middleton B, Prosser LA, Bardon CG, Spurr CD, Carchidi PJ. et al. A cost-benefit analysis of electronic medical records in primary care. Am J Med 2003; 114 (05) 397-403. PubMed PMID: 12714130. Epub 2003/04/26.
23 THINC: Taconic Health Information Network and Community. (Accessed December 12, 2014, at www.thinc.org
24 New York State Department of Health. Health Information Technology (HIT) Grants –HEAL NY Phase 1. (Accessed December 12, 2014, at www.health.ny.gov/technology/awards/ .)
25 New York State.. New York State provides $9.5 million for incentive program to promote high-quality, more affordable health care. 2007. (Accessed December 12, 2014, http://www.state.ny.us/governor/press/0913071.html
26 Taconic IPA. (Accessed December 12, 2014, at www.taconicipa.com. )
27 Hofer TP, Hayward RA, Greenfield S, Wagner EH, Kaplan SH, Manning WG. The unreliability of individual physician “report cards” for assessing the costs and quality of care of a chronic disease. J Am Med Inform Assoc 1999; 281 (22) 2098-2105. PubMed PMID: 10367820. Epub 1999/06/15.
28 MedAllies. (Accessed December 12, 2014, at www.medallies.com. )
29 Centers for Medicare and Medicaid Services.. Medicare Advantage –Rates and Statistics –Risk Adjustment. (Accessed December 12, 2014, http://www.cms.gov/Medicare/Health-Plans/MedicareAdvtgSpecRateStats/Risk-Adjustors.html. )
30 Verisk Health.. DxCG Risk Analytics. (Accessed December 12, 2014, at www.veriskhealth.com/answers/population-answers/dxcg-risk-analytics .)
31 Ash AS, Ellis RP, Pope GC, Ayanian JZ, Bates DW, Burstin H. et al. Using diagnoses to describe populations and predict costs. Health Care Financ Rev 2000; 21 (03) 7-28. PubMed PMID: 11481769.
32 Long JS, Freese J. Regression models for categorical dependent variables using Stata, 2nd ed. College Station, TX: Stata Press; 2006
33 McCullagh P, Nelder JA. Generalized linear models, 2nd ed. New York: Chapman and Hill; 1989
34 National Committee for Quality Assurance.. Standards and guidelines for Physician Practice Connections –Patient-Centered Medical Home (PPC-PCMH), 2008. (Accessed December 12, 2014 http://www.ncqa.org/Portals/0/Programs/Recognition/PCMH_Overview_Apr01.pdf .)
35 Adler-Milstein J, Salzberg C, Franz C, Orav EJ, Newhouse JP, Bates DW. Effect of electronic health records on health care costs: longitudinal comparative evidence from community practices. Ann Intern Med 2013; 159 (02) 97-104. PubMed PMID: 23856682. Epub 2013/07/17.
36 Bates DW, Kuperman GJ, Rittenberg E, Teich JM, Fiskio J, Ma’luf N. et al. A randomized trial of a computer-based intervention to reduce utilization of redundant laboratory tests. Am J Med 1999; 106 (02) 144-150. PubMed PMID: 10230742.
37 Goldzweig CL, Towfigh A, Maglione M, Shekelle PG. Costs and benefits of health information technology: new trends from the literature. Health Aff (Millwood) 2009; 28 (02) w282-w293. PubMed PMID: 19174390. Epub 2009/01/29.
38 Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E. 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. PubMed PMID: 16702590.
39 Classen DC, Bates DW. Finding the meaning in meaningful use. N Engl J Med 2011; 365 (09) 855-858. PubMed PMID: 21879906. Epub 2011/09/02.
40 Blumenthal D. Launching HITECH. N Engl J Med 2010; 362 (05) 382-385. PubMed PMID: 20042745. Epub 2010/01/01.
41 Jamoom E, Beatty P, Bercovitz A, Woodwell D, Palso K, Rechtsteiner E. Physician adoption of electronic health record systems: United States, 2011. NCHS data brief, no. 98. Hyattsville, MD: 2012.
42 Ancker JS, Kern LM, Edwards A, Nosal S, Stein DM, Hauser D. et al. How is the electronic health record being used? Use of EHR data to assess physician-level variability in technology use. J Am Med Inform Assoc 2014; 21 (06) 1001-1008. PubMed PMID: 24914013.
43 Isaac T, Weissman JS, Davis RB, Massagli M, Cyrulik A, Sands DZ. et al. Overrides of medication alerts in ambulatory care. Arch Intern Med 2009; 169 (03) 305-311. PubMed PMID: 19204222. Epub 2009/02/11.
44 Grinspan ZM, Banerjee S, Kaushal R, Kern LM. Physician specialty and variations in adoption of electronic health records. Applied Clinical Informatics 2013; 4 (02) 225-240. PubMed PMID: 23874360.