Difference between revisions of "EMR Benefits and Return on Investment Categories"

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# Systematic review of clinical decision support interventions with potential for inpatient cost reduction
  
  

Revision as of 20:02, 26 February 2015

The Electronic Medical Record may consist of computer order entry, decision support, electronic medication administration, documentation, and so much more. [1]

The sections below detail the benefits, costs, and barriers in evaluating EMR implementations. Selecting, financing, and launching an EHR system is difficult. Product certification seeks to make the first step a little easier. [2]


Informational

EMR Benefits: Informational

Security

EMR Benefits: Security

Environmental

EMR Benefits: Environmental

Medical Education

EMR Benefits: Medical education

Financial

EMR Benefits: Financial

Improving patient care

EMR Benefits: Healthcare quality

Research

EMR Benefits: Research

Health Information Exchange (HIE)

EMR Benefits: HIE

Personal Health Records

EMR Benefits: PHR

Telehealth

EMR Benefits: Telehealth

Mobile EMRs

EMR_Benefits: mHealth

Physicians

EMR Benefits: Physicians

Costs

Return on investment

Cost benefit analysis is categorized into 3 fields [70]:

  1. Direct, one-time costs
    1. Hardware & Peripherals
    2. Packaged and customized software
    3. Network, peripherals, supplies, equipment
    4. Initial data collection and conversion of archival data
    5. Facilities upgrades, including site preparation and renovation
    6. End-user project management
    7. Project planning, contract negotiation, procurement
    8. Application development and deployment
    9. Configuration management
    10. Office accommodations, furniture, related items
    11. Initial user training
    12. Workforce adjustment for affected employees
    13. Transition costs (parallel systems, converting legacy systems)
    14. Quality assurance and post implementation reviews
  1. Direct, ongoing costs
    1. Salaries for IT and assigned end user staff
    2. Software maintenance, subscriptions, upgrades,
    3. Equipment leases
    4. Facilities rental and utilities
    5. Professional services, Ongoing training and
    6. Reviews and audits
  1. Indirect, ongoing costs.
    1. Data integrity
    2. Security
    3. Privacy
    4. IT policy management
    5. Help Desk

The financial commitment of implementing a CPOE system varies amongst facilities and depends on the facility's current hardware and software systems. The institution's current system needs to have a strong infrastructure in order to be able to enhance it's capabilities. The license for the software is but a small portion of the total cost. The larger expenses incurred will be a result of training healthcare professionals and support activities. Customer service and technical support should be available everyday 24 hours a day.

For more information, see EMR Cost Categories.

Challenges to Identifying a Return on Investment (ROI)

Evidence of a strong ROI business case for EHR implementation is confounded by anecdotal evidence in peer reviewed research and trade journals. Furthermore, environmental differences across provider settings make it challenging to replicate information system strategies and dependence on disparate legacy applications [48]. For organizational stakeholders to embrace EHR adoption, they need assurance that adopting an EHR system would positively impact business performance [58].

Additional barriers include:

  • Vendor supplied benefits data may not be objective
  • Few vendors maintain a structured database of benefits information
  • Peer reviewed studies are difficult to compare due to the complexity of health services delivery and variety of provider settings.
  • Differences in system architecture
  • Trade journals tend to focus on anecdotal evidence rather then empirical evidence
  • No standardized domain method exists to measure the ROI of electronic health records
  • Lack of information regarding maintenance and optimization costs [48]

Consequently, providers frequently lack the necessary information to make sound financial decisions regarding Health IT capital investments. Uncovering the true cost and benefit of EHR adoption will require a national effort to standardize and centralize evidence in a national database. [48]

Return on Investment (ROI) Estimates

While barriers of determining actual ROI for EMR implementations exist, companies such as Dr. Cloud EMR are providing EMR and EHR ROI estimates based on each practice's details. This however does not suggest that it is entirely accurate and is only an estimate. DrCloudEMR is built by DrCloud Healthcare Solutions Inc, a wholly owned EnSoftek, Inc. subsidiary. [65] There are 2 main postulates for ROI which KOSH’s postulate and Sir Austin Bradford Hill’s criteria for Causation. Kosh’s postulate for CIS is i. The system or feature must be present in every case in which the benefit is observed. ii. The system must be isolated from the organization. iii. The benefit must be reproduced when the system is implemented in a new organization. iv. We must demonstrate that the system was used in the new organization. Hill’s Criteria for Causation includes (a) Strength of Association (b) Consistency of findings (c) Specificity of Association (d) Temporality (e) Dose-response (f) Plausibility (g) Coherence (h) Experimental Evidence and Analogy.

(a) Strength of Association tells us that the greater the change observed, the more likely the association is to be causal (e.g. If a EHR system is implemented and the CPOE feature greatly reduces medication errors, we could say that the implementation of the system had a causal effect on the reduction of medication errors and the strength of association is great).

(b) Consistency of Findings explains that if a change has been observed by different groups in different places with different circumstances and systems, the change is valid, so to speak. For example, if Company A (London, England, UK) implements System A , Company B (Houston, TX, USA) implements System B, and Company C (Guadalajara, Jalisco, Mexico) implements System C, and all three companies reduce medication errors using their respective systems, we can, again say that the CPOE feature of EHR systems can help reduce medication errors. It is important to note that the more consistent findings amongst different groups in different places, the better.

(c) Specificity of Association requires us to ask if there are any other factors which may have affected the change that we've observed. In regards to medication errors being reduced, one would have to ask if CPOE was the only factor involved. If errors could have been reduced due to other mechanisms in place besides CPOE alerts (e.g. better workflow in departments, new policies, etc.), the specificity of association could be considered weak. Weak does not imply wrong, but it does mean that more research has to be initiated.

(d) Temporality addresses the evaluation after an EHR system is implemented. Temporality asks us "were there any changes AFTER the system was implemented?" Usually this is harder to prove due to lack of data prior to EHR implementation, however, Sittig rates temporality as "strong."

(e) Dose-Response asks if the size of changes are directly correlated with the increase of system use (e.g. were medication errors greatly reduced due to the use of many medication alerts in the EHR system?). Usually, there is a strong and direct correlation between system use and the reduction of medication errors, as one example of a dose response in an EHR system.

(f) Plausibility must be shown; There must be some way to demonstrate that the EHR system was used the way it was intended to deliver certain results (e.g. Physicians must have used clinical support decisions the way the EHR system intended to reduce medication errors, in order to demonstrate plausibility.)

(g) Coherence simply states that changes caused by EHR systems should be caused by other EHR systems elsewhere. So, if medication errors are reduced by the use of one EHR system and that happens with the use of many other EHR systems, coherence exists.

(h) Experimental Evidence and Analogy is proving that when the system is not used properly or at all, that certain changes stop. So, if an EHR system is not being used properly or at all (after initial proper use), does a rise in medication errors resume? Experimental evidence is hard to obtain after EHR implementation because it requires not using the system for quite some time (which many would view as wasted money).


Sources of Funding

  1. Organizational Reserves – provider organization make investments in affiliated organizations
  2. Bank and other financial service – short term loans
  3. Capital leases – used for large equipment acquisitions but can be negotiated for a major IT investment
  4. Vendor discounts and incentives – requires something in return
  5. Joint venture or partnership – tighter relationship
  6. Health plans and plan sponsors – contractual arrangement
  7. Private philanthropy – fellowships or university chairs
  8. Pharmaceutical companies – willing to conduct clinical trials
  9. Public grants – government initiatives
  10. State legislative initiatives – local and state initiatives
60. Interviews with John Kansky, Laura Adams (2014, 8) by Mark Braunstein, GA Tech.
61. What is the DIRECT project (2010, 10) by The Direct Project. http://wiki.directproject.org/file/view/DirectProjectOverview.pdf

References (old, to edit)

  1. What Is an Electronic Medical Record (EMR)? http://www.healthit.gov/providers-professionals/electronic-medical-records-emr
  2. Heubusch, K. (2008). Certified EHRs. Journal of AHIMA, 79(8), 34-36. Retrieved from http://ezproxyhost.library.tmc.edu/login?url=http://search.proquest.com/docview/212569443?accountid=7034


Committee on Quality of Health Care in America, Institute of Medicine. "Front Matter." Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: The National Academies Press, 2001. Full text

  1. msdc benefits of emr
  2. about ehrs
  3. malpractice 2008
  4. http://www.cdc.gov/about/grand-rounds/archives/2011/july2011.htm
  5. http://www.mayoclinic.org/emr/benefits.html
  6. Integrated Centre for Care Advancement through Research (iCARE); Canada Health Infoway (Infoway); Canadian Patient Safety Institute (CPSI). (2007). The Relationship Between Electronic Health Records and Patient Safety: A Joint Report On Future Directions For Canada. 1-31.
  7. Crane, R. M., Raymond, B., (Winter 2003). Fulfilling the Potential of Clinical Information Systems. The Permanente Journal. 7 (1), pp.62-67
  8. Hersh, W. R., (2002). Medical Informatics: Improving Health Care Through Information. Journal of American Medical Association. 288 (16), pp.1955-1958
  9. http://library.ahima.org/xpedio/groups/public/documents/ahima/bok1_046429.hcsp?dDocName=bok1_046429
  10. http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/index.html?redirect=/EHRIncentivePrograms/56_DataAndReports.asp
  11. http://www.ischool.drexel.edu/faculty/ssilverstein/AJM-Himmelstein-Hospital-Computing.pdf
  12. http://www.himss.org/content/files/jhim/20-2/16_original_evidence.pdf
  13. http://www.markle.org/publications/403-achieving-health-it-objectives-american-recovery-and-reinvestment-act
  14. http://www.cdc.gov/ehrmeaningfuluse/
  15. http://healthit.ahrq.gov/portal/server.pt/document/958478/barriers_to_meaningful_use_in_medicaid_final_report_pdf?qid=82968838&rank=5
  16. Evidence on the Costs and Benefits of Health Information Technology. A Congressional Budget Office Paper. Congress of the United States. Congressional Budget Office. Available at: http://www.cbo.gov/publication/41690. Acessed September 30, 2013.
  17. Kuperman GJ, Gibson RF. Computer Physician Order Entry: Benefits, Costs and Issues. Ann Intern Med. 2003;139:31-39.
  18. Shapiro JS, Kannry J, et al. Approaches to patient health information exchange and their impact on emergency medicine. Ann Emerg Med. 2006 Oct;48(4):426-432.
  19. Kaushal R, Jha AK, Franz C, Glaser J, Shetty KD, Jaggi T, Middleton B, Kuperman GJ, Khorasani R, Tanasijevic M, Bates DW; Brigham and Women's Hospital CPOE Working Group. (2006). Return on investment for a computerized physician order entry system. J Am Med Inform Assoc. 13(3):261-6.
  20. tierney 2013
  21. http://www.hhs.gov/news/press/2013pres/08/20130805a.html
  22. http://www.fierceemr.com/story/new-york-looks-ehrs-enhance-public-health-surveillance/2013-08-27
  23. http://ehrintelligence.com/2012/12/10/engaging-patients-through-ehr-access-open-notes/
  24. The effect of electronic medical record-based clinical decision support on HIV care in resource-constrained settings: A systematic review Tom Oluocha,*,Xenophon Santasb, Daniel Kwaroc, Martin Wered, Paul Biondichd,
  25. Driessen J,CioffiM, Alide N,et al. J Am Med Inform Assoc 2013;20:743–748.
  26. Overcoming barriers to electronic medical record (EMR) implementation in the US healthcare system: A comparative study Sameer Kumar, Krista Aldrich
  27. http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Basics.html
  28. http://www.ncbi.nlm.nih.gov/pubmed/9576410
  29. Study of the factors that promoted the implementation of electronic medical record on iPads at two emergency departments. Rao AS, Adam TJ, Gensinger R, Westra BL. AMIA Annu Symp Proc. 2012;2012:744-52. Epub 2012 Nov 3.
  30. Connelly, D. P., Park, Y. T., Du, J., Theera-Ampornpunt, N., Gordon,B. D., Bershow, B. A., ... & Speedie, S. M. (2012). The impact of electronic health records on care of heart failure patients in the emergency room. Journal of the American Medical Informatics Association, 19(3), 334-340.
  31. Pinsonneault, A., Dakshinamoorthy, V., Reidel, K., & Tamblyn, R. (2012, January). The impact of IT on quality of care: Evaluation of an integrated chronic disease management system. In System Science (HICSS), 2012 45th Hawaii International Conference on (pp. 2947-2956). IEEE.
  32. McGinn, C. A., Grenier, S., Duplantie, J., Shaw, N., Sicotte, C., Mathieu, L., ... & Gagnon, M. P. (2011). Comparison of user groups' perspectives of barriers and facilitators to implementing electronic health records: a systematic review. BMC medicine, 9(1), 46.
  33. Mintz, MD, M., Narvarte, MD, H. J., OBrien, MD, K. E., Papp, PhD, K. K., Thomas, MD, M., & Durning, MD, S. J. (2009). Use of electronic medical records by physicians and students in academic internal medicine settings. Academic Medicine, 84(12), 1698-1704.
  34. http://www.practicefusion.com/ehrbloggers/2010/10/return-on-investment-for-emrs.html
  35. http://jama.jamanetwork.com/article.aspx?articleid=1737043#ArticleInformation
  36. Kuperman, G.J. and Gibson, R.F. (2003) “Computer Physician Order Entry: Benefits, Costs & Issues” Am Intern Med 2003; 139:31-39
  37. Crane, R.M. and Raymond, B. (2003) “Fulfilling the Potential of Clinical Information Systems: The Permanente Journal Winter/2003/Vol.7No1
  38. Kaushal, R.; Jha, A.K.; Franz, C. et al. (2006) J Am Med Inform Assoc 2006;13:261-266 doi 10.1197/jamia.J1984
  39. http://www.nejm.org/doi/full/10.1056/NEJMp1211315#t=article
  40. Menachemi N, Collum H.T. Benefits and drawbacks of electronic health record systems.Risk Manag Healthc Policy. 2011; 4: 47–55.
  41. http://www.healthit.gov/sites/default/files/pdf/privacy/privacy-and-security-guide-chapter-2.pdf
  42. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2978883/
  43. Thompson, D., Osheroff, J., Classen, D., & Sittig, D. (2007). A Review of Methods to Estimate the Benefits of Electronic Medical Records in Hospitals and the Need for a National Benefits Database. Journal of Healthcare Information Management, 21 (1), 62-68.
  44. Butcher L. Hospitals strengthen bonds with post-acute providers. http://www.hhnmag.com/hhnmag/jsp/articledisplay.jsp?dcrpath=HHNMAG/Article/data/01JAN2013/0113HHN_Feature_strategy&domain=HHNMAG
  45. Voigt, C. & Torzewski, S. (2011). Direct results: An HIE simple information exchange using the direct project. Journal of AHIMA, 38-41.
  46. Kohn, L. T., Corrigan, J. M., & Donaldson, M. S., eds. (2000). To err is human. Institute of Medicine Committee on Quality of Health Care in America. Washington, DC: National Academic Press.
  47. McGeath, J. (2012). The Team Dynamics of Connecting Medical Devices with EMR Systems. 24X7, 17(10), 34-41
  48. Mulherin, D. P., Zimmerman, C. R., & Chaffee, B. W. (2013). National standards for computerized prescriber order entry and clinical decision support: The case of drug interactions. American Journal Of Health-System Pharmacy, 70(1), 59-64. doi:10.2146/ajhp120217
  49. Otte-Trojel, T., de Bont, A., Rundall, T. G., & van de Klundert, J. (2014). How outcomes are achieved through patient portals: a realist review. Journal of the American Medical Informatics Association, amiajnl-2013.
  50. http://www.healthit.gov/providers-professionals/2-install-and-enable-encryption
  51. http://www.dialogmedical.com/informed-consent-2-3/
  52. http://library.ahima.org/xpedio/groups/public/documents/ahima/bok1_047866.hcsp?dDocName=bok1_047866
  53. Hayek S1 et al. End-of-Life Care Planning: Improving Documentation of Advance Directives in the Outpatient Clinic using Electronic Medical Records. J Palliat Med. 2014 Jul 2.
  54. Gummadi S1. Electronic medical record: a balancing act of patient safety, privacy and health care delivery. Am J Med Sci. 2014 Sep;348(3):238-43.
  55. Ojeleye O1 et al. The evidence for the effectiveness of safety alerts in electronic patient medication record systems at the point of pharmacy order entry: a systematic review. BMC Med Inform Decis Mak. 2013 Jul 1;13:69.
  56. https://www.drchrono.com/meaningful-use-ehr/
  57. EMR Effectiveness: The Positive Benefit Electronic Medical Record Adoption has on Mortality Rates. http://apps.himss.org/content/files/HAHealthgradesEMRStudyWhitePaper.pdf
  58. Integrating Clinical Practice and Public Health Surveillance Using Electronic Medical Record Systems. http://www.ajpmonline.org/article/S0749-3797(12)00249-8/fulltext
  59. EMR ROI / EHR ROI Calculator. http://www.drcloudemr.com/roi/
  60. http://www.academia.edu/4083826/An_Adaptive_Evidence_Based_Medicine_System_Based_on_a_Clinical_Decision_Support_System
  61. http://www.cdc.gov/ehrmeaningfuluse/introduction.html
  62. http://www.healthit.gov/providers-professionals/faqs/how-can-electronic-health-records-improve-public-and-population-health-
  63. http://www.esi-bethesda.com/ncrrworkshops/clinicalresearch/pdf/MichaelKahnPaper.pdf
  64. http://www.forbes.com/sites/hbsworkingknowledge/2014/03/26/how-electronic-patient-records-can-slow-doctor-productivity/
  65. Bhargava, Hemant K., and Abhay Mishra. "Electronic Medical Records and Physicians Productivity: Insights from Panel Data Analysis and Design Implications." 2nd round at Management Science (2011).
  66. http://effectivehealthcare.ahrq.gov/index.cfm/search-for-guides-reviews-and-reports/?productid=1855&pageaction=displayproduct
  67. Shortliffe, E. H., & Cimino, J. J. (2006). Biomedical informatics. Springer Science+ Business Media, LLC.
  68. http://www.healthit.gov/providers-professionals/faqs/what-are-advantages-electronic-health-records
  69. Kim, Y., Kim, S. S., Kang, S., Kim, K., & Jun Kim. (2014). Development of Mobile Platform Integrated with Existing Electronic Medical Records. Health Infrormatics Research.
  70. Zaroukian, M. (n.d.). EMR Cost-Benefit Analysis: Managing ROI into Reality. Retrieved from http://www.himss.org/files/HIMSSorg/content/files/EMRCost-BenefitReality.pdf
  71. Ajami, S., & Arabchadegani, R. (n.d.). Barriers to implement Electronic Health Records (EHRs). Materia Socio Medica, 213-213. Retrieved September 10, 2014, from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3804410/
  72. http://hitconsultant.net/2014/08/19/patient-portal-features-which-is-the-most-beneficial-frustrating/
  73. http://www.cms.gov/Medicare/E-Health/Eprescribing/index.html?redirect=/EPrescribing
  74. https://www.drchrono.com
  75. turley 2011
  76. Menachemi N, Powers TL, Brooks RG. The role of information technology usage in physician practice satisfaction. Health Care Manage Rev. 2009;34(4):364–371.
  77. Elder KT, Wiltshire JC, Rooks RN, et al. Health information technology and physician career satisfaction. Perspect Health Inf Manag. 2010;7:1d.
  78. http://www.himss.org/ResourceLibrary/ResourceDetail.aspx?ItemNumber=17246
  79. http://www.ihealthbeat.org/insight/2013/physicians-divided-on-cloudbased-ehrs
  80. Systematic review of clinical decision support interventions with potential for inpatient cost reduction



6. Harrington, L., Porch, L., Acosta, K., & Wilkens, K. (2011). Realizing electronic medical record benefits: an easy-to-do usability study. The Journal of Nursing Administration, 41(7-8), 331–5. doi:10.1097/NNA.0b013e3182250b23

7. Hillestad, R., Bigelow, J., Bower, A., Girosi, F., Meili, R., Scoville, R., & Taylor, R. (2005). Can electronic medical record systems transform health care? Potential health benefits, savings, and costs. Health Affairs (Project Hope), 24(5), 1103–17. doi:10.1377/hlthaff.24.5.1103

References

  1. Bailey JE, Pope RA, Elliott EC, Wan JY, Waters TM, Frisse ME. Health Information Exchange Reduces Repeated Diagnostic Imaging for Back Pain. Annals of Emergency Medicine 2013 Jul;62(1):16-24.
  2. bates 1997
  3. Johnston D, Pan E, Walker J. The value of CPOE in ambulatory settings. J Healthc Inf Manag 2004;18(1):5-8.
  4. Berger RG, Kichak JP. Computerized physician order entry: helpful or harmful? J Am Med Inform Assoc 2004 Mar;11(2):100-3.
  5. Stage DRMU. 3; Meaningful Use Work Group; Paul Tang, chair and George Hripcsak, co-chair. 2013. August.
  6. Singh H. Editorial: Helping Health Care Organizations to Define Diagnostic Errors as Missed Opportunities in Diagnosis. Joint Commission Journal on Quality and Patient Safety 2014 Mar;40(3):99-101.
  7. Bogua¡eviaius A, Maleckas A, Pundzius J, Skaudickas D. Prospective randomised trial of computer‐aided diagnosis and contrast radiography in acute small bowel obstruction. European Journal of Surgery 2002;168(2):78-83.
  8. 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. JAMA 2005;293(10):1223-38.
  9. McDonald KM, Matesic B, Contopoulos-Ioannidis DG, Lonhart J, Schmidt E, Pineda N, et al. Patient safety strategies targeted at diagnostic errors: a systematic review. Ann Intern Med 2013 Mar 5;158(5 Pt 2):381-9.
  10. Radley, D. C., Wasserman, M. R., Olsho, L. E., Shoemaker, S. J., Spranca, M. D., & Bradshaw, B. ( 2013). Reduction in medication errors in hospitals due to adoption of computerized provider order entry systems. Journal of the American Medical Informatics Association : Jamia, 20, 3, 470-6.

11. Kuperman,G.J.,Gibson,R.F. (2003)Computer Order Physician Entry: Benefits, Costs, and Issues. Annals of Internal Medicine,139,31-19

  1. Sittig, D. (2014, September). Return on Investment Calculations. Lecture conducted from University of Texas Health Science Center at Houston, Houston, TX.
  2. The American Journal of Medicine , Volume 114 , Issue 5 , 397 - 403
  3. Jamoom E, Beatty P, Bercovitz A, et al. (2012) Physician adoption of electronic health record systems: United States, 2011. NCHS data brief, no 98. Hyattsville, MD: National Center for Health Statistics.
  4. http://www.healthit.gov/providers-professionals/patient-participation
  5. AHRQ Daignostic errors”http://psnet.ahrq.gov/primer.aspx?primerID=12.
  6. EHRS and other technology can reduce diagnostic errors http://www.exscribe.com/orthopedic-e-news/ehremr/ehrs-and-other-technology-can-reduce-diagnostic-errors.
  7. McGregor JC, Weekes E, Forrest GN, et al. Impact of a Computerized Clinical Decision Support System on Reducing Inappropriate Antimicrobial Use: A Randomized Controlled Trial.http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1513678/.
  8. Top 5 Benefits of Clinical Decision Support in the ED http://www.govhealthit.com/blog/top-5-benefits-clinical-decision-support-ed.
  1. Hoyt, R., & Yoshihashi, A. (2014). Health Informatics: Practical guide for healthcare and information technology professionals.(6th ed.). Informatics Education.
  2. Hibbs, SP, Nielsen, ND, Brunskill, S, Doree, C, Yazer , MH Kufman RM, Murphy MF.
  (Jan 2015). The Impact of Electronic Decision Support on Transfusion Practice: A systemic Review [Abstruct]. Transfusion Medicine Review, 29(1),14-23 doi: 10.1016/j.tmrv.2014.10.002
  1. Nitrosi, A, Borasi, G, Nicoli, F, Modigliani, G, Botti, A, Bertolini, M, Notari, P.
  (June, 2007). A Filmless Radiology Department in a Full Digital Regional Hospital: Quantitative Evaluation of the Increased Quality and Efficiency [Abstract]. Journal of Digital Imaging, 20(2), 140-148. doi:  10.1007/s10278-007-9006-y
  1. Tolomeo, C, Shiffman, R, Bazzy-Asaad, A (Nov, 2008). Electronic medical records in a sub-specialty practice: one asthma center’s [Abstract]. Journal of Asthma, 45
  (9), 849-51 doi: 10.1080/02770900802380803