The diabetes electronic medical record (DEMR) has emerged as an effective information management tool with the potential to improve diabetes care and research. This study reports on the usefulness of the DEMR system at Dr. Mohan's Diabetes Specialities Centre (DMDSC), Chennai, India, for clinical and research purposes.
Methods:
The DEMR, set up in 1996 at DMDSC, connects data of nine centers/clinics in different geographical areas in Southern India. The present data analysis is based on a total of 226,228 patients registered in the DEMR system at DMDSC between the years 1991 and 2010.
Results:
The DEMR included data of 139,906 male and 86,322 female patients, of whom 92.6% had type 2 diabetes mellitus (T2DM), 1.4% had type 1 diabetes mellitus (T1DM), and the rest had other types. Patients with T2DM had higher prevalence rates of neuropathy (33.1% vs 13.0%, p < .001), microalbuminuria (25.5% vs 20.0%, p < .001), coronary artery disease (17.5% vs 9.2%, p < .001) and peripheral vascular disease (3.9% vs 2.8%, p = .017) compared with T1DM patients, while prevalence of diabetic retinopathy was similar (37.9% vs 35.7%, p = .06). Prevalence of microvascular and macrovascular complications of diabetes increased with increasing glycated hemoglobin levels (p for trend < .001) and increasing diabetes duration (p for trend < .001).
Conclusions:
The DEMR helps track diabetes care and is a valuable tool for research.
TaylorD Wayne. The burden of non-communicable diseases in India. Hamilton: The Cameron Institute; 2010.
2.
RaviglioneMCGuptaRDyeCMEspinalMA. The burden of drug-resistant tuberculosis and mechanisms for its control. Ann N Y Acad Sci.2001;953: 88–97.
3.
International Diabetes Federation diabetes atlas. In: UnwinNWhitingDGanDJacqmainOGhyootG, editors. IDF diabetes atlas, 4th ed.Belgium: International Diabetes Federation; 2009. p. 12.
4.
KristianFHanssenKF. The determinants of microvascular complications in diabetics: An overview. In: PickupJWilliamsG, eds. Textbook of diabetes mellitus. Vol 2. London: Blackwell Scientific Publishers; 1991.
5.
ShojaniaKGRanjiSRMcDonaldKMGrimshawJMSundaramVRushakoffRJOwensDK. Effects of quality improvement strategies for type 2 diabetes on glycemic control: A meta-regression analysis. JAMA.2006;296 (4): 427–40.
6.
WuRCStrausSE. Evidence for handheld electronic medical records in improving care: A systematic review. BMC Med Inform Decis Mak.2006;6: 26.
7.
MeigsJBCaglieroEDubeyAMurphy-SheehyPGildesgameCChuehHBarryMJSingerDENathanDM. A controlled trial of web-based diabetes disease management: The MGH diabetes primary care improvement project. Diabetes Care.2003;26 (3): 750–7.
8.
O'ConnorPJCrainALRushWASperl-HillenJMGutenkaufJJDuncanJE. Impact of an electronic medical record on diabetes quality of care. Ann Fam Med.2005;3 (4): 300–6.
9.
SelbyJ VKarterAJAckersonLMFerraraALiuJ. Developing a prediction rule from automated clinical databases to identify high-risk patients in a large population with diabetes. Diabetes Care.2001;24 (9): 1547–55.
10.
BarahonaPAzevedoFVelosoMEstêvãoNGallegoR. Computerising a guideline for the management of diabetes. Int J Med Inf.2001;64 (2–3): 275–84.
11.
WeberVBloomFPierdonSWoodC. Employing the electronic health record to improve diabetes care: A multifaceted intervention in an integrated delivery system. J Gen Intern Med.2008;23 (4): 379–82.
12.
BodenheimerTGrumbachK. Electronic technology: A spark to revitalize primary care?JAMA.2003;290 (2): 259–64.
13.
ConwayPHClancyC. Transformation of health care at the front line. JAMA.2009;301 (7): 763–5.
14.
BrissetPRGilmanCSMorganMTShabotMMHallmanE. Who are your CPOE users and how do you train them? Lessons learned at Cedars-Sinai Health System. Medinfo., 2004; 1536.
15.
PetersALLegorretaAPOssorioRCDavidsonMB. Quality of outpatient care provided to diabetic patients. A health maintenance organization experience. Diabetes Care.1996;19 (6): 601–6.
16.
HoMMargerMBeartJYipIShekelleP. Is the quality of diabetes care better in a diabetes clinic or in a general medicine clinic?Diabetes Care.1997;20 (4): 472–5.
17.
MorrisADBoyleDIMacAlpineREmslie-SmithAJungRTNewtonRWMacDonaldTM; DARTS/MEMO Collaboration. The diabetes audit and research in Tayside Scotland (DARTS) study: Electronic record linkage to create a diabetes register. BMJ.1997;315 (7107): 524–8.
18.
SandifordPAnnettHCibulskisR. What can information systems do for primary health care? An international perspective. Soc Sci Med.1992;34 (10): 1077–87.
19.
BrailerDJ. Management of knowledge in the modern health care delivery system. J Qual Improv.1999;25 (1): 6–19.
20.
AhmanAJ. Guideline and performance measures for diabetes. Am J Manag Care.2007;13: S41–6.
21.
NeaseDEJrGreenLA. ClinfoTracker: A generalizable prompting tool for primary care. J Am Board Fam Pract.2003;16 (2): 115–23.
22.
RendersCMValkGDGriffinSWagnerEHEijkJTAssendelftWJ. Interventions to improve the management of diabetes mellitus in primary care, outpatient and community settings. Cochrane Database Syst Rev.2001; (1): CD001481.
23.
MontoriVMDinneenSFGormanCAZimmermanBRRizzaRABjornsenSSGreenEMBryantSCSmithSA; Translation Project Investigator Group. The impact of planned care and a diabetes electronic management system on community-based diabetes care: The Mayo Health System Diabetes Translation Project. Diabetes Care.2002;25 (11): 1952–7.
24.
O'ConnorPJ. Electronic medical records and diabetes care improvement: Are we waiting for Godot?Diabetes Care.2003;26 (3): 942–3.
25.
KerrEAGerzoffRBKreinSLSelbyJ VPietteJDCurbJDHermanWHMarreroDGNarayanKMSaffordMMThompsonTMangioneCM. Diabetes care quality in the Veterans Affairs health care system and commercial managed care: The TRIAD study. Ann Intern Med.2004;141 (4): 272–81.
26.
HuntDLHaynesRBHannaSESmithK. Effects of computer-based clinical decision support systems on physician performance and patient outcomes: A systematic review. JAMA.1998;280 (15): 1339–46.
27.
MillerRHSimI. Physicians' use of electronic medical records: Barriers and solutions. Health Aff (Millwood).2004;23 (2): 116–26.
28.
GormanCLookerJFiskTOelkeWEricksonDSmithSZimmermanB. A clinically useful diabetes electronic medical record: Lessons from the past; pointers toward the future. Eur J Endocrinol.1996;134 (1): 31–42.
29.
GandhiTKSequistTDPoonEGKarsonASMurffHFairchildDGKupermanGJBatesDW. Primary care clinician attitudes towards electronic clinical reminders and clinical practice guidelines. AMIA Annu Symp Proc. 2003: 848.
30.
GaneshAAl-MujainiA. Electronic medical record system: Have we bitten off more than we can chew?OMJ.2009;24 (1): 1–3.
31.
LehmannED. Electronic medical records in clinical diabetes care. Diabetes Technol Ther.1999;1 (4): 555–7.
32.
CollenMF. Clinical research databases–a historical review. J Med Syst.1990;14 (6): 323–44.
National Cancer Institute. Confidentiality, data security, and cancer research: Perspectives from the National Cancer Institute. www3.cancer.gov/Confidentiality.html. Accessed November 23, 2010.
35.
MillerRHSimI. Physicians' use of electronic medical records: Barriers and solutions. Health Aff (Millwood)2004;23 (2): 116–26.
36.
JhaAKDesRochesCMCampbellEGDonelanKRaoSRFerrisTGShieldsARosenbaumSBlumenthalD. Use of electronic health records in U.S. hospitals. N Engl J Med.2009: 360 (16): 1628–38.
37.
MohanVDeepaRRemaMNatarajanADevanathanS. Diabetes electronic medical record system — Experience at a M.V. Diabetes Specialities Centre, Chennai India. Int Diabetes Monit.2000;5: 35–9.
38.
AlbertiKGZimmetPZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: Diagnosis and classification of diabetes mellitus provisional report of a WHO Consultation. Diabet Med.1998;15 (7): 539–53.
39.
MohanVVijayaprabhaRRemaMPremalathaGPoongothaiSDeepaRBhatiaEMackayIRZimmetP. Clinical profile of lean NIDDM in South India. Diabetes Res Clin Pract.1997;38 (2): 101–8.
40.
RemaMDeepaRMohanV. Prevalence of retinopathy at diagnosis among type 2 diabetic patients attending a diabetic centre in South India. Br J Ophthalmol.2000;84 (9): 1058–60.
41.
MohanVMeeraRPremalathaGDeepaRMirandaPRemaM. Frequency of proteinuria in Type 2 diabetes mellitus seen at a diabetes centre in southern India. Postgrad Med J.2000;76 (899): 569–73.
42.
VargheseADeepaRRemaMMohanV. Prevalence of microalbuminuria in type 2 diabetes mellitus at a diabetes centre in southern India. Postgrad Med J.2001;77 (908): 399–402.
43.
AshokSRamuMDeepaRMohanV. Prevalence of neuropathy in type 2 diabetic patients attending a diabetes centre in South India. J Assoc Physicians India.2002;50: 546–50.
44.
PremalathaGRavikumarRSanjayRDeepaRMohanV. Comparison of colour duplex ultrasound and ankle-brachial pressure index measurements in peripheral vascular disease in type 2 diabetic patients with foot infections. J Assoc Physicians India.2002;50: 1240–4.
45.
MohanVDeepaRRemaM. Correlation between fasting plasma glucose and two-hour plasma glucose during oral glucose tolerance test in South Indians. Metabolism.2000;49 (4): 455–7.
46.
DeepaRMohanARemaMHaranathSPSaravananGMohanV. Lipoprotein(a) in South Indian type 2 diabetic subjects in relation to diabetic vascular complications. J Assoc Physicians India.2002;50 (5): 657–61.
47.
BarmanK KantaPadmanabhanMPremalathaGDeepaRRemaMMohanV. Prevalence of diabetic complications in fibrocalculous pancreatic diabetic patients and type 2 diabetic patients: A cross-sectional comparative study. J Diabetes Complications.2004;18 (5): 264–70.
48.
RemaMSujathaPPradeepaR. Visual outcomes of pan-retinal photocoagulation in diabetic retinopathy at one-year follow-up and associated risk factors. Indian J Ophthalmol.2005;53 (2): 93–9.
Early Treatment of Diabetic Retinopathy Study Research Group. Grading diabetic retinopathy from stereoscopic color fundus photographs–an extension of the modified Airlie House classification. ETDRS report number 10. Ophthalmology.1991;98 (5 Suppl): 786–806.
51.
PradeepaRRemaMVigneshJDeepaMDeepaRMohanV. Prevalence and risk factors for diabetic neuropathy in an urban south Indian population: The Chennai Urban Rural Epidemiology Study (CURES-55). Diabet Med.2008;25 (4): 407–12.
52.
PremalathaGShanthiraniSDeepaRMarkovitzJMohanV. Prevalence and risk factors of peripheral vascular disease in a selected South Indian population: The Chennai Urban Population Study. Diabetes Care.2000;23 (9): 1295–300.
53.
MohanVDeepaRRaniSSPremalathaG; Chennai Urban Population Study (CUPS No. 5). Prevalence of coronary artery disease and its relationship to lipids in a selected population in South India: The Chennai Urban Population Study (CUPS No. 5). J Am Coll Cardiol.2001;38 (3): 682–7.
