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1
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84904997061
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EMR vs EHR—what is the difference?
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Garret P, Sideman, J. EMR vs EHR—what is the difference? HealthIT.gov Buzz. 2011; http://www.healthit.gov/buzz-blog/electronic-health-and-medical-records/emr-vs-ehr-difference/.
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(2011)
HealthIT.gov Buzz
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Garret, P.1
Sideman, J.2
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2
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77649126524
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Heart disease and stroke statistics—2010 update a report from the American heart association
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PID: 2001932
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Lloyd-Jones D, Adams RJ, Brown TM, et al. Heart disease and stroke statistics—2010 update a report from the American heart association. Circulation. 2010;121(7):e46–e215.
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(2010)
Circulation
, vol.121
, Issue.7
, pp. e46-e215
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Lloyd-Jones, D.1
Adams, R.J.2
Brown, T.M.3
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3
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84889664945
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Use of health information technology (HIT) to improve statin adherence and low-density lipoprotein cholesterol goal attainment in high-risk patients: proceedings from a workshop
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PID: 2431435
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Cohen JD, Aspry KE, Brown AS, et al. Use of health information technology (HIT) to improve statin adherence and low-density lipoprotein cholesterol goal attainment in high-risk patients: proceedings from a workshop. J Clin Lipidol. 2013;7(6):573–609.
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(2013)
J Clin Lipidol
, vol.7
, Issue.6
, pp. 573-609
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Cohen, J.D.1
Aspry, K.E.2
Brown, A.S.3
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4
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79952444246
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Forecasting the future of cardiovascular disease in the United States
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Heidenreich PA, Trogdon JG, Khavjou OA, et al. Forecasting the future of cardiovascular disease in the United States. Circulation. 2011;1(8):933–44.
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(2011)
Circulation
, vol.1
, Issue.8
, pp. 933-944
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Heidenreich, P.A.1
Trogdon, J.G.2
Khavjou, O.A.3
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5
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84855353573
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Heart disease and stroke statistics—2012 update
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PID: 2217953
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Roger VL, Go AS, Lloyd-Jones DM, et al. Heart disease and stroke statistics—2012 update. Circulation. 2012;125(1):e2.
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(2012)
Circulation
, vol.125
, Issue.1
, pp. e2
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Roger, V.L.1
Go, A.S.2
Lloyd-Jones, D.M.3
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6
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84873881942
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Lifestyle and primordial prevention of cardiovascular disease: challenges and opportunities
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Foraker RE, Olivo-Marston S, Allen NB. Lifestyle and primordial prevention of cardiovascular disease: challenges and opportunities. Curr Cardiovasc Risk Rep. 2012;6(6):520–7.
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(2012)
Curr Cardiovasc Risk Rep
, vol.6
, Issue.6
, pp. 520-527
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Foraker, R.E.1
Olivo-Marston, S.2
Allen, N.B.3
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7
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84888363703
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Risk-adjusted comparison of blood pressure and low-density lipoprotein (LDL) noncontrol in primary care offices
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PID: 2420406
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Hammermeister K, Bronsert M, Henderson WG, et al. Risk-adjusted comparison of blood pressure and low-density lipoprotein (LDL) noncontrol in primary care offices. J Am Board Fam Med. 2013;26(6):658–68.
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(2013)
J Am Board Fam Med
, vol.26
, Issue.6
, pp. 658-668
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Hammermeister, K.1
Bronsert, M.2
Henderson, W.G.3
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8
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84901243402
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Assessment of life’s simple 7™ in the primary care setting
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PID: 2472148
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Foraker RE, Shoben AB, Lopetegui MA, et al. Assessment of life’s simple 7™ in the primary care setting. Contemp Clin Trials. 2014;38(2):182–9.
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(2014)
Contemp Clin Trials
, vol.38
, Issue.2
, pp. 182-189
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Foraker, R.E.1
Shoben, A.B.2
Lopetegui, M.A.3
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9
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84896509284
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E-care for heart wellness: a feasibility trial to decrease blood pressure and cardiovascular risk
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PID: 2465083
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Green BB, Anderson ML, Cook AJ, et al. E-care for heart wellness: a feasibility trial to decrease blood pressure and cardiovascular risk. Am J Prev Med. 2014;46(4):368–77.
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(2014)
Am J Prev Med
, vol.46
, Issue.4
, pp. 368-377
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Green, B.B.1
Anderson, M.L.2
Cook, A.J.3
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10
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84891691978
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Improving cardiovascular outcomes using electronic health records
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Roumia M, Steinhubl S. Improving cardiovascular outcomes using electronic health records. Curr Cardiol Rep. 2014;16(2):1–6.
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(2014)
Curr Cardiol Rep
, vol.16
, Issue.2
, pp. 1-6
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Roumia, M.1
Steinhubl, S.2
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11
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84889676179
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Effect of health information technology interventions on lipid management in clinical practice: a systematic review of randomized controlled trials
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PID: 2431435
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Aspry KE, Furman R, Karalis DG, et al. Effect of health information technology interventions on lipid management in clinical practice: a systematic review of randomized controlled trials. J Clin Lipidol. 2013;7(6):546–60.
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(2013)
J Clin Lipidol
, vol.7
, Issue.6
, pp. 546-560
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Aspry, K.E.1
Furman, R.2
Karalis, D.G.3
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12
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84900866391
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New insights into the management of hypertension and cardiovascular risk with angiotensin receptor blockers: observational studies help us?
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PID: 24847388, This meta-analysis by Goudev sheds light on how EMRs allow for the possibility of increased sample sizes, enable faster algorithm generation, and intervention testing. These studies cover multiple countries and illustrate how the increased dissemination of findings from observational studies may help fill the knowledge gap created by the longevity of randomized control trial result
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Goudev A. New insights into the management of hypertension and cardiovascular risk with angiotensin receptor blockers: observational studies help us? Open Cardiovasc Med J. 2014;8:35. This meta-analysis by Goudev sheds light on how EMRs allow for the possibility of increased sample sizes, enable faster algorithm generation, and intervention testing. These studies cover multiple countries and illustrate how the increased dissemination of findings from observational studies may help fill the knowledge gap created by the longevity of randomized control trial results.
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(2014)
Open Cardiovasc Med J
, vol.8
, pp. 35
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Goudev, A.1
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13
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84901258032
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Kleinberg S, Elhadad N. Lessons learned in replicating data-driven experiments in multiple medical systems and patient populations. AMIA Annual Symposium Proceedings. 2013:786 The authors’ research examined the longitudinal raw EMR data of 46299 patients to study CVD risk factors in both a rural and urban environment. Their study looked for mutual findings from the differing populations through the common EMR infrastructure
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Kleinberg S, Elhadad N. Lessons learned in replicating data-driven experiments in multiple medical systems and patient populations. AMIA Annual Symposium Proceedings. 2013:786 The authors’ research examined the longitudinal raw EMR data of 46299 patients to study CVD risk factors in both a rural and urban environment. Their study looked for mutual findings from the differing populations through the common EMR infrastructure.
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14
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84883671640
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Effect of pay-for-performance incentives on quality of care in small practices with electronic health records: a randomized trial
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COI: 1:CAS:528:DC%2BC3sXhsFGnu7z
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Bardach NS, Wang JJ, De Leon SF, et al. Effect of pay-for-performance incentives on quality of care in small practices with electronic health records: a randomized trial. J Am Med Assoc. 2013;310(10):1051–9.
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(2013)
J Am Med Assoc
, vol.310
, Issue.10
, pp. 1051-1059
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Bardach, N.S.1
Wang, J.J.2
De Leon, S.F.3
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15
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84892659033
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Small practices’ experience with EHR, quality measurement, and incentives
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PID: 2451188
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Begum R, Smith RM, Winther CH, et al. Small practices’ experience with EHR, quality measurement, and incentives. Am J Manag Care. 2013;19(10 Spec No):eSP12–8.
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(2013)
Am J Manag Care
, vol.19
, Issue.10 Spec No
, pp. eSP12-eSP18
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Begum, R.1
Smith, R.M.2
Winther, C.H.3
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16
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84884241659
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Sustained improvement in clinical preventive service delivery among independent primary care practices after implementing electronic health record systems
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Wang JJ, Sebek KM, McCullough CM, et al. Sustained improvement in clinical preventive service delivery among independent primary care practices after implementing electronic health record systems. Preventing Chronic Disease. 2013;10.
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(2013)
Preventing Chronic Disease
, pp. 10
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Wang, J.J.1
Sebek, K.M.2
McCullough, C.M.3
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17
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84885174107
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The feasibility and accuracy of evaluating lipid management performance metrics using an electronic health record
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PID: 2409385
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Danford CP, Navar-Boggan AM, Stafford J, et al. The feasibility and accuracy of evaluating lipid management performance metrics using an electronic health record. Am Heart J. 2013;166(4):701–8.
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(2013)
Am Heart J
, vol.166
, Issue.4
, pp. 701-708
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Danford, C.P.1
Navar-Boggan, A.M.2
Stafford, J.3
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18
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84889808799
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The COSEHC™ global vascular risk management quality improvement program: first follow-up report
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PID: 2390128
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Ferrario CM, Joyner J, Colby C, et al. The COSEHC™ global vascular risk management quality improvement program: first follow-up report. Vasc Health Risk Manag. 2013;9:391.
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(2013)
Vasc Health Risk Manag
, vol.9
, pp. 391
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Ferrario, C.M.1
Joyner, J.2
Colby, C.3
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19
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84892604198
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Effects of changing guidelines on prescribing aspirin for primary prevention of cardiovascular events
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PID: 2439088
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Hissett J, Folks B, Coombs L, et al. Effects of changing guidelines on prescribing aspirin for primary prevention of cardiovascular events. J Am Board Fam Med. 2014;27(1):78–86.
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(2014)
J Am Board Fam Med
, vol.27
, Issue.1
, pp. 78-86
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Hissett, J.1
Folks, B.2
Coombs, L.3
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20
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84891717424
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EHR‐based medication support and nurse‐led medication therapy management: rationale and design for a three‐arm clinic randomized trial
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PID: 2415764
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Persell SD, Eder M, Friesema E, et al. EHR‐based medication support and nurse‐led medication therapy management: rationale and design for a three‐arm clinic randomized trial. J Am Heart Assoc. 2013;2(5):e000311.
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(2013)
J Am Heart Assoc
, vol.2
, Issue.5
, pp. e000311
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Persell, S.D.1
Eder, M.2
Friesema, E.3
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21
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84877742577
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Heart beat connections: a rural community of solution for cardiovascular health
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PID: 23657698, The authors illustrate a common challenge related to EMR use. The original study aim was to identify individuals at CVD risk and manage through intervention through the EMR, but the EMR could not be utilized as planned. This was in large part because although it theoretically had the capability of tracking interventions, in reality the EMR did not function well for this aim in practical applicatio
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Benson GA, Sidebottom A, VanWormer JJ, et al. Heart beat connections: a rural community of solution for cardiovascular health. J Am Board Fam Med. 2013;26(3):299–310. The authors illustrate a common challenge related to EMR use. The original study aim was to identify individuals at CVD risk and manage through intervention through the EMR, but the EMR could not be utilized as planned. This was in large part because although it theoretically had the capability of tracking interventions, in reality the EMR did not function well for this aim in practical application.
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(2013)
J Am Board Fam Med
, vol.26
, Issue.3
, pp. 299-310
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Benson, G.A.1
Sidebottom, A.2
VanWormer, J.J.3
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22
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84893692925
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Population prevalence and control of cardiovascular risk factors: what electronic medical records tell us
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PID: 24325864, This study shows the capability of EMR collected data for use in determining CVD prevalence rates. This study in Spain included 2.1 million patient’s data to determine a 40% rate of hypertension and hypercholesterolemia prevalence. It was also discovered that 66% of the patient population had adequately controlled hypertension and hypercholesterolemi
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Catalán-Ramos A, Verdú JM, Grau M, et al. Population prevalence and control of cardiovascular risk factors: what electronic medical records tell us. Aten Primaria. 2014;46(1):15–24. This study shows the capability of EMR collected data for use in determining CVD prevalence rates. This study in Spain included 2.1 million patient’s data to determine a 40% rate of hypertension and hypercholesterolemia prevalence. It was also discovered that 66% of the patient population had adequately controlled hypertension and hypercholesterolemia.
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(2014)
Aten Primaria
, vol.46
, Issue.1
, pp. 15-24
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Catalán-Ramos, A.1
Verdú, J.M.2
Grau, M.3
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23
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84901808693
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Blood pressure and incidence of twelve cardiovascular diseases: lifetime risks, healthy life-years lost, and age-specific associations in 1·25 million people
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PID: 24881994, This study was conducted in the UK and examined over 1.25 million patients from 225 primary care practices looking at the association between blood pressure and incidence of CVD. Their results surrounding associations between blood pressure and CVD were inconsistent with previous studies and suggested that blood pressure does not hold the association with as many CVD occurrences as was previously believed. Their results revealed that even with treatment through medication, the burden of hypertension is substantia
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Rapsomaniki E, Timmis A, George J, et al. Blood pressure and incidence of twelve cardiovascular diseases: lifetime risks, healthy life-years lost, and age-specific associations in 1·25 million people. Lancet. 2014;383(9932):1899. This study was conducted in the UK and examined over 1.25 million patients from 225 primary care practices looking at the association between blood pressure and incidence of CVD. Their results surrounding associations between blood pressure and CVD were inconsistent with previous studies and suggested that blood pressure does not hold the association with as many CVD occurrences as was previously believed. Their results revealed that even with treatment through medication, the burden of hypertension is substantial.
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(2014)
Lancet
, vol.383
, Issue.9932
, pp. 1899
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Rapsomaniki, E.1
Timmis, A.2
George, J.3
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24
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84893097016
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Preemptive genotyping for personalized medicine: design of the right drug, right dose, right time—using genomic data to individualize treatment protocol
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Bielinski SJ, Olson JE, Pathak J, et al. Preemptive genotyping for personalized medicine: design of the right drug, right dose, right time—using genomic data to individualize treatment protocol. Circulation. 2014;89(1):25–33.
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(2014)
Circulation
, vol.89
, Issue.1
, pp. 25-33
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Bielinski, S.J.1
Olson, J.E.2
Pathak, J.3
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25
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84875142183
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Comparison of the information provided by electronic health records data and a population health survey to estimate prevalence of selected health conditions and multimorbidity
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Violán C, Foguet-Boreu Q, Hermosilla-Pérez E, et al. Comparison of the information provided by electronic health records data and a population health survey to estimate prevalence of selected health conditions and multimorbidity. BMC Public Health. 2013;1:251.
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(2013)
BMC Public Health
, vol.1
, pp. 251
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Violán, C.1
Foguet-Boreu, Q.2
Hermosilla-Pérez, E.3
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26
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84882266047
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Development of a multi‐institutional cohort to facilitate cardiovascular disease biomarker validation using existing biorepository samples linked to electronic health records
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PID: 2374053
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Cross DS, McCarty CA, Steinhubl SR, et al. Development of a multi‐institutional cohort to facilitate cardiovascular disease biomarker validation using existing biorepository samples linked to electronic health records. Clin Cardiol. 2013;36(8):486–91.
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(2013)
Clin Cardiol
, vol.36
, Issue.8
, pp. 486-491
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Cross, D.S.1
McCarty, C.A.2
Steinhubl, S.R.3
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27
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84969427453
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Risk assessment tool. National Heart, Lung
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NIH. Risk assessment tool. National Heart, Lung, and Blood Institute. 2013. http://cvdrisk.nhlbi.nih.gov/.
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(2013)
and Blood Institute
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28
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80053048372
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Electronic health records, clinical decision support, and blood pressure control
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PID: 2190244
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Samal L, Linder JA, Lipsitz SR, et al. Electronic health records, clinical decision support, and blood pressure control. Am J Manag Care. 2011;17(9):626–32.
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(2011)
Am J Manag Care
, vol.17
, Issue.9
, pp. 626-632
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Samal, L.1
Linder, J.A.2
Lipsitz, S.R.3
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29
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84868026799
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The knowledge program: an innovative, comprehensive electronic data capture system and warehouse
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Katzan I, Speck M, Dopler C, et al. The knowledge program: an innovative, comprehensive electronic data capture system and warehouse. AMIA Annual Symposium Proceedings. 2011:683.
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(2011)
AMIA Annual Symposium Proceedings
, pp. 683
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Katzan, I.1
Speck, M.2
Dopler, C.3
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30
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84902086763
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Clinical decision support alert appropriateness: a review and proposal for improvement
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PID: 2494012
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McCoy AB, Thomas EJ, Krousel-Wood M, et al. Clinical decision support alert appropriateness: a review and proposal for improvement. Ochsner J. 2014;14(2):195–202.
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(2014)
Ochsner J
, vol.14
, Issue.2
, pp. 195-202
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McCoy, A.B.1
Thomas, E.J.2
Krousel-Wood, M.3
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31
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79551675666
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A “Smart” heart failure sheet: using electronic medical records to guide clinical decision making
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PID: 2129519
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Battaglia L, Aronson MD, Neeman N, et al. A “Smart” heart failure sheet: using electronic medical records to guide clinical decision making. Am J Med. 2011;124(2):118–20.
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(2011)
Am J Med
, vol.124
, Issue.2
, pp. 118-120
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Battaglia, L.1
Aronson, M.D.2
Neeman, N.3
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