OJNI

Diabetes population management with an electronic health record

by Sondra Santana, MSN, ARNP, FNC, CEN, ANP-BC

  Citation

Santana, S. (2013). Diabetes population management with an electronic health record. Online Journal of Nursing Informatics (OJNI), 17 (1). Available at http://ojni.org/issues/?p=2378

Abstract

Diabetes care in the United States is insufficient.  Studies illustrate that there are two primary obstacles to adequate diabetes care: clinical inertia and continued reliance on paper medical records.  A review of several studies strongly suggests that electronic health records and EHR-based clinical decision support (CDS) systems have the potential to exponentially improve diabetes care by promoting adherence to evidence-based guidelines, improving key outcomes of diabetes, and streamlining care coordination while providing real-time clinical decision support with a high level of provider satisfaction.  Health care providers need to leave the paper medical records behind and move into the twenty-first century; the time to implement an electronic health record is now.

Key words: clinical decision support, clinical inertia, diabetes, electronic health records, population management

Introduction

An expanding body of evidence suggests that the quality of diabetes care in the United States is insufficient (Ciemins, Coon, Fowles, & Min, 2009; O’Connor et al., 2011; Weber, Bloom, Pierdon, & Wood, 2007).  Many of the complications of diabetes can be prevented through adequate control of low-density lipoprotein (LDL), hemoglobin A1c, and systolic blood pressure.  The American Diabetes Association (ADA) has developed evidence-based practice guidelines to facilitate a consistent approach to diabetes management through episodic visits with their health care provider (American Diabetes Association, 2011).  Despite the existence of the ADA guidelines, diabetes care remains grossly inadequate with less than 20 percent of diabetic patients in the U.S. managed in accordance with the ADA’s guidelines (Curry, 2010; O’Connor et al., 2011; Sperl-Hillen et al., 2010).

Barriers to Diabetes Care

Studies illustrate that there are two primary obstacles to adequate diabetes care: clinical inertia and continued reliance on paper medical records (Cebul, Love, Jain, & Herbert, 2011; Sperl-Hillen et al., 2010).  Clinical inertia is the failure to intensify treatment when it is clinically indicated (Samal, Linder, Lipsitz, & Hicks, 2011).  Evidence suggests that clinical inertia related to glycemic control and glucose management is a significant problem and occurs in 30 percent of patients with diabetes (Sperl-Hillen et al., 2010).

Another common problem in diabetes care is the continued reliance on paper medical records.  Paper medical records exponentially compound the problem clinical inertia and they have a number of inherent disadvantages.  Paper medical records are cumbersome and require costly space for storage (Friedman, 2010).  Tracking, analyzing and charting medial information is difficult with paper records and they cannot be searched easily (Roukema et al., 2006).  Entries into the paper medical records must be completed manually.  Many times this data is misfiled, missing, incomplete, or illegible.  When paper medical records are checked out for one provider, they are unavailable to other members of the health care team (Friedman, 2010).

Electronic Health Records and Diabetes Care

Electronic health records (EHRs) are readily available and extremely valuable in diabetes care.  An expanding body of evidence suggests that EHR-based diabetes clinical support systems have the potential to mitigate the problem of clinical inertia and the shortcomings of paper medical records.  The concept of EHR based health care and diabetes management extends far beyond the concept of computerized charting.  From individual records to population insights an EHR permits providers to quickly and efficiently access and generate clinical information pertaining to their individual patients.  EHR-based clinical decision support (CDS) systems have the potential to exponentially improve diabetes care by promoting adherence to evidence-based guidelines, improving key outcomes of diabetes, and streamlining care coordination while providing real-time clinical decision support with a high level of provider satisfaction (Chen, Garrido, Chock, Okawa, & Liang, 2009; Joos, Chen, Jirjis, & Johnson, 2006; Koopman et al., 2011).

Clinical Decision Support Systems

EHRs that are embedded with CDS systems are impressive contrivances in diabetes disease management.  CDS systems ensure that the latest patient information and most current evidence are available to the provider during the patient encounter.  CDS systems can quickly analyze a patient’s vital signs and laboratory results and synthesize recommendations for diagnosis and treatment.  CDS systems can also provide individualized patient education, disease specific monitoring indicators, and suggestions for follow-up that enhance treatment decisions (Roshanov et al., 2011).

A randomized control study conducted by Sperl-Hillen, et al. (2010) evaluated the impact of the Diabetes Wizard, an EHR-based CDS, with promising results.  Targeting hemoglobin A1c, blood pressure, and low density cholesterol levels, this study implied that EHR-based CDS systems significantly improve glucose and blood pressure control in adults with diabetes (Sperl-Hillen et al., 2010). In another study analyzing EHR-based CDS systems in chronic disease management, 55 percent of the CDS systems reported improvements in diabetes care and monitoring (Roshanov et al., 2011).  This review also revealed that 62.5% of the sites utilizing EHR-based CDS systems for diabetes care reported improvements in patient outcomes including blood pressure, hemoglobin A1C, and low-density lipoprotein levels (Roshanov et al., 2011).

Efficiency and Streamlined Care

Improved efficiency, streamlined reimbursement, and enhanced communications are byproducts of EHRs.  Integrated scheduling systems link progress notes directly with appointments.  Once patient visits are documented, many EHRs automatically generate a list of codes for billing purposes, so that claims are submitted and managed electronically (Mann, Sadawarti, Verma, & Gupta, 2010).  Charts are readily available and multiple staff members can view the same chart simultaneously.  EHRs streamline the sharing of patient information between providers and consultants ensuring necessary background information are readily available during specialty visits (Ciemins et al., 2009).  They also provide automated formulary checks, visit templates, and order entry functions.

EHRs can also help monitor and trend patient data such as vital signs, body mass index, and laboratory values (Mann et al., 2010).  This is especially important when caring for patients with diabetes.  A recent study conducted by the eHealth Initiative, Sanofi-Aventis, and Health & Technology Vector found that diabetes care was superior in health care practices that utilized EHRs than those relying on paper records (Care Coordination Model Positively Impacts Diabetes, 2011).  Providers were able to observe trends, evaluate the effects of certain treatments or medications, track patient progress, and make informed treatment decisions at the point of service (Care Coordination Model Positively Impacts Diabetes, 2011).

Improved Outcomes and Adherence to Guidelines

Clinics that utilize EHRs have also reported better population management and diabetes specific outcomes (Cebul et al., 2011; Ciemins et al., 2009; Curry, 2010; Joos et al., 2006; Mann et al., 2010; O’Connor et al., 2011; Roshanov et al., 2011; Roukema et al., 2006; Samal et al., 2011; Weber et al., 2007).  EHR systems improve patient tracking and coordination of care (MacPhail, Neuwirth, & Bellows, 2009; Weber et al., 2007).  A study of adult diabetes care in the greater Cleveland region reported significantly higher adherence to diabetes care standards and improved patient outcomes among providers who utilized EHRs.  Researchers used four national quality standards related to diabetes, including: 1) eye exams, 2) pneumonia vaccinations, 3) outcome measures such as blood sugar, blood pressure, and cholesterol control, and 4) patient-driven issues such as obesity and smoking to determine adherence to standards (Cebul et al., 2011).  Nearly 51 percent of patients who received care in health care practices that utilized EHRs received care according to all four quality standards, compared to just 7 percent of patients who received care at paper-based practices.  After adjusting for differences in patient characteristics, patients receiving care in practices that utilized EHRs were still 35 percent more likely to receive care in accordance with ADA standards (Cebul et al., 2011).  This study also revealed that diabetic patients receiving care in health care practices that utilized EHRs had better outcomes.  Nearly 44 percent of patients in practices that utilized EHRs attained at least four of five of the outcome standards, compared to about 16 percent of patients at paper-based practices (Cebul et al., 2011).

Improved Provider Satisfaction

EHR-based CDS can lead to measurable improvement in diabetes outcomes while obtaining a high level of provider satisfaction (O’Connor et al., 2011).  The results of a randomized trial that evaluated the implementation of Diabetes Wizard in a primary care found that the EHR was associated with improvements in communications, efficiency, and the ability to synthesize patient data.  Overall the providers in this study were satisfied with the Diabetes Wizard and reported that they would recommend it to their peers (Sperl-Hillen et al., 2010).  Indicative of the value of the EHRs embedded with CDS systems, providers continued to use the Diabetes Wizard for more than a year after feedback and incentives to encourage its use were discontinued (Sperl-Hillen et al., 2010).

Conclusion

If not managed properly, diabetes can be a devastating disease.  The key to preventing the complications of diabetes is proper disease management and timely treatment intensifications.  EHRs and CDS systems are the collective answer in preventing the complications of diabetes.  When employed appropriately these systems can facilitate appropriate diabetes management.  EHRs and CDS systems improve diabetes specific disease management processes and patient outcomes through real-time access to patient information, comprehensive documentation, analysis of results, and decision support.  Recent evidence shows utilizing an EHR in diabetes management can effectively combat the problems associated with clinical inertia and paper medical records to improve outcomes for diabetic patients.  Health care providers need to leave the paper medical records behind and move into the twenty-first century; the time to implement an EHR is now.

References

American Diabetes Association (2011). Standards of medical care in diabetes-2011. Diabetes Care, 34, S11-S61. doi: 10.2337/dc11-S011

Cebul, R. D., Love, T. E., Jain, A. K., & Herbert, C. J. (2011, September 1). Electronic health records and quality of diabetes care. The New England Journal of Medicine, 365(9), 825-833. Retrieved from www.nejm.org

Chen, C., Garrido, T., Chock, D., Okawa, G., & Liang, L. (2009). The Kaiser Permanente electronic health record: Transforming and streamlining modalities of care. Health Affairs, 28(2), 323-333. doi: 10.1377/hlthaff.28.2.323

Ciemins, E. L., Coon, P. J., Fowles, J. B., & Min, S. (2009). Beyond health information technology: Critical factors necessary for effective diabetes disease management. Journal of Diabetes Science and Technology, 3(3), 452-460.

Curry, A. (2010). Assessing the impact of electronic health records. Diabetes Forecast: The Healthy Living Magazine . Retrieved from http://forecast.diabetes.org/magazine/your-ada/assessing-impact-electronic-health-records

Friedman, A. (2010, February 12). A doctor’s problem with electronic records. The Wall Street Journal. Retrieved from The Wall Street Journal website

Joos, D., Chen, Q., Jirjis, J., & Johnson, K. B. (2006). An electronic medical record in primary care: Impact on satisfaction, work efficiency and clinic processes. AMIA 2006 Symposium Proceedings, 394-398. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1839545/

Koopman, R. J., Kochendorfer, K. M., Moore, J. L., Mehr, D. R., Wakefield, D. S., Yadamsuren, B.,…Belden, J. L. (2011). A diabetes dashboard and physician efficiency and accuracy in accessing data needed for high-quality diabetes care. Annals of Family Medicine, 9(5), 398-405.

MacPhail, L. H., Neuwirth, E. B., & Bellows, J. (2009). Coordination of diabetes care in four delivery models using an electronic health record. Medical Care, 47(9), 993-999. doi: 10.1097/MLR.0b013e31819e1ffe

Mann, K. S., Sadawarti, H., Verma, R., & Gupta, E. (2010). An information modeling using EHR. International Journal of Computer Science and Communication, 1(2), 19-22.

New report shows care coordination model positively impacts people living with type 2 diabetes and heart disease (Press Release eHealth Initiative US.GLA.11.05.263). (2011). Retrieved from eHealth Initiative website: www.ehealthinitiative.org

O’Connor, P. J., Sperl-Hillen, J. M., Rush, W. A., Johnson, P. E., Amundson, G. H., Asche, S. E.,…Gilmer, T. P. (2011). Impact of electronic health record clinical decision support on diabetes care: A randomized trial. Annals of Family Medicine, 9, 12-21. doi: 10.1370/afm.1196

Roshanov, P. S., Mirsa, S., Gerstein, H. C., Garg, A. X., Sebaldt, R. J., Mackay, J. A.,…Haynes, R. B. (2011). Computerized clinical decision support systems for chronic disease management: A decision maker-researcher partnership systematic review. Implementation Science, 6(92). doi: 10.1186/1748-5908-6-92

Roukema, J., Los, R. K., Bleeker, S. E., Van Ginneken, A. M., Van der Lei, J., & Moll, H. A. (2006). Paper versus computer: Feasibility of an electronic medical record in general pediatrics. Pediatrics, 117, 15-22. doi: 10.1542/peds.2004-2741

Samal, L., Linder, J. A., Lipsitz, S. R., & Hicks, L. S. (2011). Electronic health records, clinical decision support, and blood pressure control. The American Journal of Managed Care, 17(9), 626-632.

Smith, S. A., Murphy, M. E., Huscka, T. R., Dinneen, S. F., Gorman, C. A., Zimmerman, B. R.,…Naessens, J. M. (1998). Impact of a diabetes electronic management system on the care of patients seen in a subspecialty diabetes clinic. Diabetes Care, 21(6), 972-976.

Sperl-Hillen, J. M., Averbeck, B., Palatto, K., Amundson, J., Ekstrom, H., Rush, B., & O’Connor, P. (2010). Outpatient EHR-based diabetes clinical decision support that works: Lessons learned from implementing Diabetes Wizard. Diabetes Spectrum, 23(3), 150-154.

Weber, V., Bloom, F., Pierdon, S., & Wood, C. (2007). Employing the electronic health record to improve diabetes care: A multifaceted intervention in an integrated delivery system. Journal of General Internal Medicine, 24(4), 379-382. doi: 10.1007/s11606-007-0439-2

 Author Bio

Sondra Santana, MSN, ARNP, FNC, CEN, ANP-BC

Ms. Santana is a Commander in the United States Navy and is serving as a Nurse Corps Officer.  She is currently a post-master’s Family Nurse Practitioner and Doctor of Nursing Practice student at the University of North Florida in Jacksonville, Florida in the Navy’s Duty Under Instruction program.  Ms. Santana  began her career in nursing in 1996 when she graduated from Jacksonville University with her BSN. She completed her MSN from the University of Phoenix in 2000 and earned a post-master’s certificate as an Adult Nurse Practitioner in 2007.  Her military assignments include Naval Hospital Jacksonville, Florida; U.S. Naval Hospital Roosevelt Roads, Puerto Rico; Naval Medical Center, Portsmouth, Virginia; Fleet Surgical Team Two; and the USS ENTERPRISE (CVN-65).

Disclaimer

I am a military service member.  This work was prepared as part of my official duties while a student at the University of North Florida studying for a Doctor of Nursing Practice Degree.  The views expressed in this article are mine and do not reflect the official policy or position of the Department of the Navy, Department of Defense, nor the U.S. Government.

 

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