Medication Adherence Does Not Explain Black-White Differences in Cardiometabolic Risk Factor Control among Insured Patients with Diabetes
Background Among patients with diabetes, racial differences in cardiometabolic risk factor control are common. The extent to which differences in medication adherence contribute to such disparities is not known. We examined whether medication adherence, controlling for treatment intensification, cou...
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| Published in | Journal of general internal medicine : JGIM Vol. 31; no. 2; pp. 188 - 195 |
|---|---|
| Main Authors | , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.02.2016
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Background
Among patients with diabetes, racial differences in cardiometabolic risk factor control are common. The extent to which differences in medication adherence contribute to such disparities is not known. We examined whether medication adherence, controlling for treatment intensification, could explain differences in risk factor control between black and white patients with diabetes.
Methods
We identified three cohorts of black and white patients treated with oral medications and who had poor risk factor control at baseline (2009): those with glycated hemoglobin (HbA1c) >8 % (
n
= 37,873), low-density lipoprotein cholesterol (LDL-C) >100 mg/dl (
n
= 27,954), and systolic blood pressure (SBP) >130 mm Hg (
n
= 63,641). Subjects included insured adults with diabetes who were receiving care in one of nine U.S. integrated health systems comprising the SUrveillance, PREvention, and ManagEment of Diabetes Mellitus (SUPREME-DM) consortium. Baseline and follow-up risk factor control, sociodemographic, and clinical characteristics were obtained from electronic health records. Pharmacy-dispensing data were used to estimate medication adherence (i.e., medication refill adherence [MRA]) and treatment intensification (i.e., dose increase or addition of new medication class) between baseline and follow-up. County-level income and educational attainment were estimated via geocoding. Logistic regression models were used to test the association between race and follow-up risk factor control. Models were specified with and without medication adherence to evaluate its role as a mediator.
Results
We observed poorer medication adherence among black patients than white patients (
p
< 0.01): 50.6 % of blacks versus 39.7 % of whites were not highly adherent (i.e., MRA <80 %) to HbA1c oral medication(s); 58.4 % of blacks and 46.7 % of whites were not highly adherent to lipid medication(s); and 33.4 % of blacks and 23.7 % of whites were not highly adherent to BP medication(s). Across all cardiometabolic risk factors, blacks were significantly less likely to achieve control (
p
< 0.01): 41.5 % of blacks and 45.8 % of whites achieved HbA1c <8 %; 52.6 % of blacks and 60.8 % of whites achieved LDL-C <100; and 45.7 % of blacks and 53.6 % of whites achieved SBP <130. Adjusting for medication adherence/treatment intensification did not alter these patterns or model fit statistics.
Conclusions
Medication adherence failed to explain observed racial differences in the achievement of HbA1c, LDL-C, and SBP control among insured patients with diabetes. |
|---|---|
| AbstractList | Background
Among patients with diabetes, racial differences in cardiometabolic risk factor control are common. The extent to which differences in medication adherence contribute to such disparities is not known. We examined whether medication adherence, controlling for treatment intensification, could explain differences in risk factor control between black and white patients with diabetes.
Methods
We identified three cohorts of black and white patients treated with oral medications and who had poor risk factor control at baseline (2009): those with glycated hemoglobin (HbA1c) >8 % (
n
= 37,873), low-density lipoprotein cholesterol (LDL-C) >100 mg/dl (
n
= 27,954), and systolic blood pressure (SBP) >130 mm Hg (
n
= 63,641). Subjects included insured adults with diabetes who were receiving care in one of nine U.S. integrated health systems comprising the SUrveillance, PREvention, and ManagEment of Diabetes Mellitus (SUPREME-DM) consortium. Baseline and follow-up risk factor control, sociodemographic, and clinical characteristics were obtained from electronic health records. Pharmacy-dispensing data were used to estimate medication adherence (i.e., medication refill adherence [MRA]) and treatment intensification (i.e., dose increase or addition of new medication class) between baseline and follow-up. County-level income and educational attainment were estimated via geocoding. Logistic regression models were used to test the association between race and follow-up risk factor control. Models were specified with and without medication adherence to evaluate its role as a mediator.
Results
We observed poorer medication adherence among black patients than white patients (
p
< 0.01): 50.6 % of blacks versus 39.7 % of whites were not highly adherent (i.e., MRA <80 %) to HbA1c oral medication(s); 58.4 % of blacks and 46.7 % of whites were not highly adherent to lipid medication(s); and 33.4 % of blacks and 23.7 % of whites were not highly adherent to BP medication(s). Across all cardiometabolic risk factors, blacks were significantly less likely to achieve control (
p
< 0.01): 41.5 % of blacks and 45.8 % of whites achieved HbA1c <8 %; 52.6 % of blacks and 60.8 % of whites achieved LDL-C <100; and 45.7 % of blacks and 53.6 % of whites achieved SBP <130. Adjusting for medication adherence/treatment intensification did not alter these patterns or model fit statistics.
Conclusions
Medication adherence failed to explain observed racial differences in the achievement of HbA1c, LDL-C, and SBP control among insured patients with diabetes. Among patients with diabetes, racial differences in cardiometabolic risk factor control are common. The extent to which differences in medication adherence contribute to such disparities is not known. We examined whether medication adherence, controlling for treatment intensification, could explain differences in risk factor control between black and white patients with diabetes.BACKGROUNDAmong patients with diabetes, racial differences in cardiometabolic risk factor control are common. The extent to which differences in medication adherence contribute to such disparities is not known. We examined whether medication adherence, controlling for treatment intensification, could explain differences in risk factor control between black and white patients with diabetes.We identified three cohorts of black and white patients treated with oral medications and who had poor risk factor control at baseline (2009): those with glycated hemoglobin (HbA1c) >8 % (n = 37,873), low-density lipoprotein cholesterol (LDL-C) >100 mg/dl (n = 27,954), and systolic blood pressure (SBP) >130 mm Hg (n = 63,641). Subjects included insured adults with diabetes who were receiving care in one of nine U.S. integrated health systems comprising the SUrveillance, PREvention, and ManagEment of Diabetes Mellitus (SUPREME-DM) consortium. Baseline and follow-up risk factor control, sociodemographic, and clinical characteristics were obtained from electronic health records. Pharmacy-dispensing data were used to estimate medication adherence (i.e., medication refill adherence [MRA]) and treatment intensification (i.e., dose increase or addition of new medication class) between baseline and follow-up. County-level income and educational attainment were estimated via geocoding. Logistic regression models were used to test the association between race and follow-up risk factor control. Models were specified with and without medication adherence to evaluate its role as a mediator.METHODSWe identified three cohorts of black and white patients treated with oral medications and who had poor risk factor control at baseline (2009): those with glycated hemoglobin (HbA1c) >8 % (n = 37,873), low-density lipoprotein cholesterol (LDL-C) >100 mg/dl (n = 27,954), and systolic blood pressure (SBP) >130 mm Hg (n = 63,641). Subjects included insured adults with diabetes who were receiving care in one of nine U.S. integrated health systems comprising the SUrveillance, PREvention, and ManagEment of Diabetes Mellitus (SUPREME-DM) consortium. Baseline and follow-up risk factor control, sociodemographic, and clinical characteristics were obtained from electronic health records. Pharmacy-dispensing data were used to estimate medication adherence (i.e., medication refill adherence [MRA]) and treatment intensification (i.e., dose increase or addition of new medication class) between baseline and follow-up. County-level income and educational attainment were estimated via geocoding. Logistic regression models were used to test the association between race and follow-up risk factor control. Models were specified with and without medication adherence to evaluate its role as a mediator.We observed poorer medication adherence among black patients than white patients (p < 0.01): 50.6 % of blacks versus 39.7 % of whites were not highly adherent (i.e., MRA <80 %) to HbA1c oral medication(s); 58.4 % of blacks and 46.7 % of whites were not highly adherent to lipid medication(s); and 33.4 % of blacks and 23.7 % of whites were not highly adherent to BP medication(s). Across all cardiometabolic risk factors, blacks were significantly less likely to achieve control (p < 0.01): 41.5 % of blacks and 45.8 % of whites achieved HbA1c <8 %; 52.6 % of blacks and 60.8 % of whites achieved LDL-C <100; and 45.7 % of blacks and 53.6 % of whites achieved SBP <130. Adjusting for medication adherence/treatment intensification did not alter these patterns or model fit statistics.RESULTSWe observed poorer medication adherence among black patients than white patients (p < 0.01): 50.6 % of blacks versus 39.7 % of whites were not highly adherent (i.e., MRA <80 %) to HbA1c oral medication(s); 58.4 % of blacks and 46.7 % of whites were not highly adherent to lipid medication(s); and 33.4 % of blacks and 23.7 % of whites were not highly adherent to BP medication(s). Across all cardiometabolic risk factors, blacks were significantly less likely to achieve control (p < 0.01): 41.5 % of blacks and 45.8 % of whites achieved HbA1c <8 %; 52.6 % of blacks and 60.8 % of whites achieved LDL-C <100; and 45.7 % of blacks and 53.6 % of whites achieved SBP <130. Adjusting for medication adherence/treatment intensification did not alter these patterns or model fit statistics.Medication adherence failed to explain observed racial differences in the achievement of HbA1c, LDL-C, and SBP control among insured patients with diabetes.CONCLUSIONSMedication adherence failed to explain observed racial differences in the achievement of HbA1c, LDL-C, and SBP control among insured patients with diabetes. BackgroundAmong patients with diabetes, racial differences in cardiometabolic risk factor control are common. The extent to which differences in medication adherence contribute to such disparities is not known. We examined whether medication adherence, controlling for treatment intensification, could explain differences in risk factor control between black and white patients with diabetes.MethodsWe identified three cohorts of black and white patients treated with oral medications and who had poor risk factor control at baseline (2009): those with glycated hemoglobin (HbA1c) >8 % (n = 37,873), low-density lipoprotein cholesterol (LDL-C) >100 mg/dl (n = 27,954), and systolic blood pressure (SBP) >130 mm Hg (n = 63,641). Subjects included insured adults with diabetes who were receiving care in one of nine U.S. integrated health systems comprising the SUrveillance, PREvention, and ManagEment of Diabetes Mellitus (SUPREME-DM) consortium. Baseline and follow-up risk factor control, sociodemographic, and clinical characteristics were obtained from electronic health records. Pharmacy-dispensing data were used to estimate medication adherence (i.e., medication refill adherence [MRA]) and treatment intensification (i.e., dose increase or addition of new medication class) between baseline and follow-up. County-level income and educational attainment were estimated via geocoding. Logistic regression models were used to test the association between race and follow-up risk factor control. Models were specified with and without medication adherence to evaluate its role as a mediator.ResultsWe observed poorer medication adherence among black patients than white patients (p < 0.01): 50.6 % of blacks versus 39.7 % of whites were not highly adherent (i.e., MRA <80 %) to HbA1c oral medication(s); 58.4 % of blacks and 46.7 % of whites were not highly adherent to lipid medication(s); and 33.4 % of blacks and 23.7 % of whites were not highly adherent to BP medication(s). Across all cardiometabolic risk factors, blacks were significantly less likely to achieve control (p < 0.01): 41.5 % of blacks and 45.8 % of whites achieved HbA1c <8 %; 52.6 % of blacks and 60.8 % of whites achieved LDL-C <100; and 45.7 % of blacks and 53.6 % of whites achieved SBP <130. Adjusting for medication adherence/treatment intensification did not alter these patterns or model fit statistics.ConclusionsMedication adherence failed to explain observed racial differences in the achievement of HbA1c, LDL-C, and SBP control among insured patients with diabetes. Among patients with diabetes, racial differences in cardiometabolic risk factor control are common. The extent to which differences in medication adherence contribute to such disparities is not known. We examined whether medication adherence, controlling for treatment intensification, could explain differences in risk factor control between black and white patients with diabetes. We identified three cohorts of black and white patients treated with oral medications and who had poor risk factor control at baseline (2009): those with glycated hemoglobin (HbA1c) >8 % (n = 37,873), low-density lipoprotein cholesterol (LDL-C) >100 mg/dl (n = 27,954), and systolic blood pressure (SBP) >130 mm Hg (n = 63,641). Subjects included insured adults with diabetes who were receiving care in one of nine U.S. integrated health systems comprising the SUrveillance, PREvention, and ManagEment of Diabetes Mellitus (SUPREME-DM) consortium. Baseline and follow-up risk factor control, sociodemographic, and clinical characteristics were obtained from electronic health records. Pharmacy-dispensing data were used to estimate medication adherence (i.e., medication refill adherence [MRA]) and treatment intensification (i.e., dose increase or addition of new medication class) between baseline and follow-up. County-level income and educational attainment were estimated via geocoding. Logistic regression models were used to test the association between race and follow-up risk factor control. Models were specified with and without medication adherence to evaluate its role as a mediator. We observed poorer medication adherence among black patients than white patients (p < 0.01): 50.6 % of blacks versus 39.7 % of whites were not highly adherent (i.e., MRA <80 %) to HbA1c oral medication(s); 58.4 % of blacks and 46.7 % of whites were not highly adherent to lipid medication(s); and 33.4 % of blacks and 23.7 % of whites were not highly adherent to BP medication(s). Across all cardiometabolic risk factors, blacks were significantly less likely to achieve control (p < 0.01): 41.5 % of blacks and 45.8 % of whites achieved HbA1c <8 %; 52.6 % of blacks and 60.8 % of whites achieved LDL-C <100; and 45.7 % of blacks and 53.6 % of whites achieved SBP <130. Adjusting for medication adherence/treatment intensification did not alter these patterns or model fit statistics. Medication adherence failed to explain observed racial differences in the achievement of HbA1c, LDL-C, and SBP control among insured patients with diabetes. |
| Author | Schmittdiel, Julie A. Butler, Melissa G. Reynolds, Kristi Waitzfelder, Beth Raebel, Marsha A. Thomas, Abraham Lafata, Jennifer Elston Pathak, Ram D. O’Connor, Patrick J. Steiner, John F. Karter, Andrew J. Ratliff, Scott Newton, Katherine M. Morris, Heather |
| Author_xml | – sequence: 1 givenname: Jennifer Elston surname: Lafata fullname: Lafata, Jennifer Elston email: jelstonlafat@vcu.edu organization: School of Medicine, Virginia Commonwealth University, Henry Ford Health System, Department of Social and Behavioral Health, Virginia Commonwealth University – sequence: 2 givenname: Andrew J. surname: Karter fullname: Karter, Andrew J. organization: Division of Research, Kaiser Permanente Northern California – sequence: 3 givenname: Patrick J. surname: O’Connor fullname: O’Connor, Patrick J. organization: HealthPartners Institute for Education and Research – sequence: 4 givenname: Heather surname: Morris fullname: Morris, Heather organization: University of Florida – sequence: 5 givenname: Julie A. surname: Schmittdiel fullname: Schmittdiel, Julie A. organization: Division of Research, Kaiser Permanente Northern California – sequence: 6 givenname: Scott surname: Ratliff fullname: Ratliff, Scott organization: School of Medicine, Virginia Commonwealth University – sequence: 7 givenname: Katherine M. surname: Newton fullname: Newton, Katherine M. organization: Group Health Research Institute – sequence: 8 givenname: Marsha A. surname: Raebel fullname: Raebel, Marsha A. organization: Kaiser Permanente Colorado Institute for Health Research, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences – sequence: 9 givenname: Ram D. surname: Pathak fullname: Pathak, Ram D. organization: Marshfield Clinic – sequence: 10 givenname: Abraham surname: Thomas fullname: Thomas, Abraham organization: Lutheran HealthCare – sequence: 11 givenname: Melissa G. surname: Butler fullname: Butler, Melissa G. organization: Kaiser Permanente Georgia Center for Health Research- Southeast – sequence: 12 givenname: Kristi surname: Reynolds fullname: Reynolds, Kristi organization: Department of Research and Evaluation, Kaiser Permanente Southern California – sequence: 13 givenname: Beth surname: Waitzfelder fullname: Waitzfelder, Beth organization: Kaiser Permanente Hawaii, Center for Health Research – Hawaii – sequence: 14 givenname: John F. surname: Steiner fullname: Steiner, John F. organization: Kaiser Permanente Colorado Institute for Health Research |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26282954$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | Society of General Internal Medicine 2015 Journal of General Internal Medicine is a copyright of Springer, (2015). All Rights Reserved. |
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| DOI | 10.1007/s11606-015-3486-0 |
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| Keywords | racial disparities cardiometabolic risk factors diabetes care medication adherence |
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| References | Nichols (CR25) 2012; 9 CR37 Raebel (CR35) 2014; 23 Osterberg, Blaschke (CR45) 2005; 353 Berlowitz (CR12) 2005; 40 Karter (CR14) 2009; 44 Law, Wald, Thompson (CR30) 1994; 308 Shah (CR10) 2005; 28 Trinacty (CR23) 2009; 9 Lafata (CR42) 2009; 32 Bullock (CR40) 2013; 39 CR7 Deyo, Cherkin, Ciol (CR36) 1992; 45 Gaede (CR1) 2003; 348 Karter (CR52) 2007; 13 Harsha, Bray (CR31) 2008; 51 Raebel (CR60) 2012; 27 Ross, Ng, Brown, Pardee, Hornbrook, Hart, Steiner (CR27) 2014; 2 Hicks (CR39) 2005; 5 (CR56) 2015; 38 Phillips (CR8) 2005; 28 Ho, Bryson, Rumsfeld (CR34) 2009; 119 Tseng (CR24) 2008; 31 Harle, Harman, Yang (CR50) 2013; 15 Nathan (CR5) 2009; 32 Kirk (CR20) 2006; 29 Ali, Bullard, Gregg (CR4) 2013; 369 Kulik (CR22) 2011; 107 Warnecke (CR58) 2008; 98 Nathan (CR38) 2009; 32 Gaede (CR2) 2008; 358 Bosworth (CR16) 2006; 119 Rehman (CR15) 2005; 165 Schmittdiel (CR44) 2008; 23 CR57 Heisler (CR18) 2007; 167 Krousel-Wood (CR21) 2009; 93 Heisler (CR19) 2003; 41 Grant, Buse, Meigs (CR9) 2005; 28 Chaudhry, Berlowitz, Concato (CR49) 2005; 53 Raebel (CR59) 2011; 45 Schmittdiel, Uratsu, Karter, Heisler, Subramanian, Mangione (CR13) 2008; 23 Karter (CR51) 2005; 11 Trivedi (CR17) 2011; 30 CR29 Steiner, Prochazka (CR32) 1997; 50 Gazmararian (CR46) 2006; 21 CR28 CR26 Gregg (CR55) 2014; 370 Aguilar (CR6) 1999; 16 Chapman (CR47) 2005; 165 Rodondi (CR48) 2006; 144 Casagrande (CR3) 2013; 36 Hess (CR33) 2006; 40 Bolen (CR41) 2009; 32 CR61 Rodondi (CR11) 2006; 144 Voorham (CR54) 2010; 19 Virani (CR43) 2011; 162 Saffar (CR53) 2012; 18 AN Trivedi (3486_CR17) 2011; 30 JK Kirk (3486_CR20) 2006; 29 A Kulik (3486_CR22) 2011; 107 SS Casagrande (3486_CR3) 2013; 36 3486_CR37 MR Law (3486_CR30) 1994; 308 M Heisler (3486_CR18) 2007; 167 JA Schmittdiel (3486_CR44) 2008; 23 LS Hicks (3486_CR39) 2005; 5 RA Deyo (3486_CR36) 1992; 45 SU Rehman (3486_CR15) 2005; 165 MA Krousel-Wood (3486_CR21) 2009; 93 MA Raebel (3486_CR59) 2011; 45 L Osterberg (3486_CR45) 2005; 353 SD Bolen (3486_CR41) 2009; 32 3486_CR28 DM Nathan (3486_CR5) 2009; 32 3486_CR29 JE Lafata (3486_CR42) 2009; 32 P Gaede (3486_CR2) 2008; 358 M Aguilar (3486_CR6) 1999; 16 AJ Karter (3486_CR51) 2005; 11 3486_CR26 LM Hess (3486_CR33) 2006; 40 HB Bosworth (3486_CR16) 2006; 119 TR Ross (3486_CR27) 2014; 2 3486_CR61 EW Gregg (3486_CR55) 2014; 370 D Saffar (3486_CR53) 2012; 18 N Rodondi (3486_CR48) 2006; 144 N Rodondi (3486_CR11) 2006; 144 SI Chaudhry (3486_CR49) 2005; 53 DW Harsha (3486_CR31) 2008; 51 KC Bullock (3486_CR40) 2013; 39 MA Raebel (3486_CR35) 2014; 23 J Voorham (3486_CR54) 2010; 19 3486_CR57 BR Shah (3486_CR10) 2005; 28 GA Nichols (3486_CR25) 2012; 9 P Gaede (3486_CR1) 2003; 348 DR Berlowitz (3486_CR12) 2005; 40 M Heisler (3486_CR19) 2003; 41 CW Tseng (3486_CR24) 2008; 31 PM Ho (3486_CR34) 2009; 119 RW Grant (3486_CR9) 2005; 28 SS Virani (3486_CR43) 2011; 162 DM Nathan (3486_CR38) 2009; 32 3486_CR7 RH Chapman (3486_CR47) 2005; 165 RB Warnecke (3486_CR58) 2008; 98 AJ Karter (3486_CR52) 2007; 13 American Diabetes Association (3486_CR56) 2015; 38 JF Steiner (3486_CR32) 1997; 50 JA Gazmararian (3486_CR46) 2006; 21 MK Ali (3486_CR4) 2013; 369 LS Phillips (3486_CR8) 2005; 28 MA Raebel (3486_CR60) 2012; 27 CM Trinacty (3486_CR23) 2009; 9 JA Schmittdiel (3486_CR13) 2008; 23 CA Harle (3486_CR50) 2013; 15 AJ Karter (3486_CR14) 2009; 44 26791537 - J Gen Intern Med. 2016 Feb;31(2):223 |
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Poor adherence versus lack of treatment intensification publication-title: J Gen Intern Med doi: 10.1007/s11606-008-0554-8 – volume: 2 start-page: 1049 issue: 1 year: 2014 ident: CR27 article-title: The HMO research network virtual data warehouse: a public data model to support collaboration publication-title: eGEMs (Generating Evidence & Methods to improve patient outcomes) doi: 10.13063/2327-9214.1049 – volume: 39 start-page: 335 issue: 3 year: 2013 end-page: 343 ident: CR40 article-title: Race as a factor for intensification of diabetes medications publication-title: Diabetes Educ doi: 10.1177/0145721713479145 – volume: 28 start-page: 600 issue: 3 year: 2005 end-page: 606 ident: CR10 article-title: Clinical inertia in response to inadequate glycemic control do specialists differ from primary care physicians? publication-title: Diabetes Care doi: 10.2337/diacare.28.3.600 – volume: 41 start-page: 1221 issue: 11 year: 2003 end-page: 1232 ident: CR19 article-title: Racial disparities in diabetes care processes, outcomes, and treatment intensity publication-title: Med Care doi: 10.1097/01.MLR.0000093421.64618.9C – volume: 32 start-page: 193 issue: 1 year: 2009 end-page: 203 ident: CR38 article-title: Medical management of hyperglycemia in type 2 diabetes: a consensus algorithm for the initiation and adjustment of therapy: a consensus statement of the American Diabetes Association and the European Association for the Study of Diabetes publication-title: Diabetes Care doi: 10.2337/dc08-9025 – volume: 119 start-page: 70 e9 issue: 1 year: 2006 end-page: 70 e15 ident: CR16 article-title: Racial differences in blood pressure control: potential explanatory factors publication-title: Am J Med doi: 10.1016/j.amjmed.2005.08.019 – volume: 13 start-page: 598 issue: 11 year: 2007 end-page: 606 ident: CR52 article-title: Glycemic response to newly initiated diabetes therapies publication-title: Am J Manag Care – volume: 358 start-page: 580 issue: 6 year: 2008 end-page: 591 ident: CR2 article-title: Effect of a multifactorial intervention on mortality in type 2 diabetes publication-title: N Engl J Med doi: 10.1056/NEJMoa0706245 – volume: 51 start-page: 1420 issue: 6 year: 2008 end-page: 1425 ident: CR31 article-title: Weight loss and blood pressure control (Pro) publication-title: Hypertension doi: 10.1161/HYPERTENSIONAHA.107.094011 – volume: 36 start-page: 2271 issue: 8 year: 2013 end-page: 2279 ident: CR3 article-title: The prevalence of meeting A1C, blood pressure, and LDL goals among people with diabetes, 1988–2010 publication-title: Diabetes Care doi: 10.2337/dc12-2258 – volume: 44 start-page: 1640 issue: 5 Pt 1 year: 2009 end-page: 1661 ident: CR14 article-title: New prescription medication gaps: a comprehensive measure of adherence to new prescriptions publication-title: Health Serv Res doi: 10.1111/j.1475-6773.2009.00989.x – ident: CR57 – volume: 40 start-page: 1836 issue: 6p1 year: 2005 end-page: 1853 ident: CR12 article-title: Developing a quality measure for clinical inertia in diabetes care publication-title: Health Serv Res doi: 10.1111/j.1475-6773.2005.00436.x – volume: 45 start-page: 1053 issue: 9 year: 2011 end-page: 1060 ident: CR59 article-title: Importance of including early nonadherence in estimations of medication adherence publication-title: Ann Pharmacother doi: 10.1345/aph.1Q146 – volume: 9 start-page: E110 year: 2012 ident: CR25 article-title: Construction of a multisite DataLink using electronic health records for the identification, surveillance, prevention, and management of diabetes mellitus: the SUPREME-DM project publication-title: Prev Chronic Dis – ident: CR26 – volume: 98 start-page: 1608 issue: 9 year: 2008 end-page: 1615 ident: CR58 article-title: Approaching health disparities from a population perspective: the National Institutes of Health Centers for Population Health and Health Disparities publication-title: Am J Public Health doi: 10.2105/AJPH.2006.102525 – volume: 23 start-page: 699 issue: 7 year: 2014 end-page: 710 ident: CR35 article-title: Intensification of antihyperglycemic therapy among patients with incident diabetes: a Surveillance Prevention and Management of Diabetes Mellitus (SUPREME-DM) study publication-title: Pharmacoepidemiol Drug Saf doi: 10.1002/pds.3610 – volume: 38 start-page: S5 issue: Supplement 1 year: 2015 end-page: S7 ident: CR56 article-title: Strategies for improving care publication-title: Diabetes Care doi: 10.2337/dc15-S004 – volume: 162 start-page: 725 issue: 4 year: 2011 end-page: 732 e1 ident: CR43 article-title: Frequency and correlates of treatment intensification for elevated cholesterol levels in patients with cardiovascular disease publication-title: Am Heart J doi: 10.1016/j.ahj.2011.07.013 – ident: CR37 – volume: 23 start-page: 588 issue: 5 year: 2008 end-page: 594 ident: CR44 article-title: Why don’t diabetes patients achieve recommended risk factor targets? 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for important clinical outcomes publication-title: Health Aff (Millwood) doi: 10.1377/hlthaff.2011.0074 – volume: 32 start-page: 25 issue: 1 year: 2009 end-page: 31 ident: CR41 article-title: Factors associated with intensification of oral diabetes medications in primary care provider-patient dyads: a cohort study publication-title: Diabetes Care doi: 10.2337/dc08-1297 – volume: 21 start-page: 1215 issue: 12 year: 2006 end-page: 1221 ident: CR46 article-title: Factors associated with medication refill adherence in cardiovascular-related diseases: a focus on health literacy publication-title: J Gen Intern Med doi: 10.1111/j.1525-1497.2006.00591.x – ident: CR7 – volume: 53 start-page: 1214 issue: 7 year: 2005 end-page: 1216 ident: CR49 article-title: Do age and comorbidity affect intensity of pharmacological therapy for poorly controlled diabetes mellitus? publication-title: J Am Geriatr Soc doi: 10.1111/j.1532-5415.2005.53370.x – volume: 28 start-page: 337 issue: 2 year: 2005 end-page: 442 ident: CR9 article-title: Quality of diabetes care in US Academic Medical Centers low rates of medical regimen change publication-title: Diabetes Care doi: 10.2337/diacare.28.2.337 – ident: CR28 – volume: 16 start-page: 716 issue: 9 year: 1999 end-page: 730 ident: CR6 article-title: A desktop guide to type 2 diabetes mellitus publication-title: Diabet Med doi: 10.1046/j.1464-5491.1999.00166.x – volume: 50 start-page: 105 issue: 1 year: 1997 end-page: 116 ident: CR32 article-title: The assessment of refill compliance using pharmacy records: methods, validity, and applications publication-title: J Clin Epidemiol doi: 10.1016/S0895-4356(96)00268-5 – volume: 348 start-page: 383 issue: 5 year: 2003 end-page: 393 ident: CR1 article-title: Multifactorial intervention and cardiovascular disease in patients with type 2 diabetes publication-title: N Engl J Med doi: 10.1056/NEJMoa021778 – volume: 144 start-page: 475 issue: 7 year: 2006 end-page: 484 ident: CR11 article-title: Therapy 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Among patients with diabetes, racial differences in cardiometabolic risk factor control are common. The extent to which differences in medication... Among patients with diabetes, racial differences in cardiometabolic risk factor control are common. The extent to which differences in medication adherence... BackgroundAmong patients with diabetes, racial differences in cardiometabolic risk factor control are common. The extent to which differences in medication... |
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| SubjectTerms | Adhesion Adolescent Adult Adults African Americans - psychology African Americans - statistics & numerical data Aged Blood pressure Blood Pressure - physiology Cardiovascular Diseases - ethnology Cardiovascular Diseases - prevention & control Cholesterol Cholesterol, LDL - blood Consortia Diabetes Diabetes mellitus Diabetes Mellitus - blood Diabetes Mellitus - drug therapy Diabetes Mellitus - ethnology Diabetes Mellitus - psychology Dispensing Drugs Electronic health records Electronic medical records European Continental Ancestry Group - psychology European Continental Ancestry Group - statistics & numerical data Female Follow-Up Studies Glycated Hemoglobin A - metabolism Health risks Hemoglobin Humans Internal Medicine Low density lipoprotein Male Medication adherence Medication Adherence - ethnology Medication Adherence - statistics & numerical data Medicine Medicine & Public Health Middle Aged Original Research Patient compliance Patients Racial differences Regression analysis Regression models Retrospective Studies Risk analysis Risk Factors Risk management Socioeconomic Factors United States Young Adult |
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| Title | Medication Adherence Does Not Explain Black-White Differences in Cardiometabolic Risk Factor Control among Insured Patients with Diabetes |
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