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Keywords:

  • angiotensin-converting enzyme inhibitors;
  • angiotensin II receptor blockers;
  • diabetes;
  • hypertension;
  • Medicare

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Declarations
  9. References

Objectives

The proportion of patients with diabetes and hypertension receiving angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (ACEs/ARBs), is one of the quality measures for medication management employed by the Centers for Medicare and Medicaid Services to rate Medicare Part D plans. The objectives of this study were to determine the rate and predictors of receiving ACEs/ARBs in physician-office and outpatient visits made by Medicare beneficiaries with diabetes and hypertension.

Methods

The study population was Medicare beneficiaries with diabetes and hypertension from the National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey Outpatient Department, from 2007 to 2009. Predictors of receiving ACEs/ARBs were determined using bivariate and multivariate logistic regression analysis.

Key findings

Of the 6311 Medicare outpatient and physician-office visits with hypertension and diabetes, 40.7% patient visits were associated with receiving ACEs/ARBs. Bivariate analysis found that higher proportions of ACEs/ARBs were received during visits made to primary care physicians compared to visits to non-primary care physicians (48.39 compared with 32.56%; P < 0.05). Adjusted multivariate analyses indicated that ACEs/ARBs were more likely to be received during visits to primary care physicians than visits to non-primary care physicians (odds ratio 1.96, 95% confidence interval 1.59–2.43), and ACEs/ARBs were more likely to be received during visits by patients residing in zip codes with a median household income in quartile 2 (US$32 794–40 626), compared to visits by patients residing in zip codes with a median household income in quartile 1 (<$32 793; odds ratio 1.45, 95% confidence interval 1.13–1.87).

Conclusions

Fewer than half of the patient visits were associated with receiving ACEs/ARBs. Promoting evidence-based medicine and increasing access to primary care may have the potential to increase the rate of receiving ACEs/ARBs in this population.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Declarations
  9. References

The US Medicare Prescription Drug, Improvement, and Modernization Act (MMA) implemented in 2006 introduced outpatient prescription drug (Part D) coverage for Medicare beneficiaries. The Part D programme was implemented to reduce out-of-pocket prescription drug expenses, lower the cost of prescription drugs and improve access.[1, 2] To ensure appropriate medication management, the Centers for Medicare and Medicaid Services (CMS) have created a quality evaluation system called Star Ratings to indicate the quality of Medicare Part D. This rating is based on a scale of one to five stars, with five stars being the highest rating. One of the measures included in the Medicare Part D Star Rating is the appropriate treatment of hypertension in patients with diabetes. This is one of the six measures under the domain of Patient Safety and Accuracy of Drug Pricing.[3] The measure indicates the percentage of patients with diabetes and hypertension who receive angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (ACEs/ARBs).[3] The use of ACEs/ARBs has been shown to reduce cardiovascular disease and progression of nephropathy[4-6] and has been recommended as the first-line therapy for patients with diabetes and hypertension.[7]

It has been found that the percentage of patients with diabetes and hypertension among adults 65 and older increased from 9 to 15% from 2000 to 2010.[8] However, previous studies found low rates of utilization of ACEs/ARBs in patients with diabetes and hypertension.[9-11] Because of the overall increase in medication utilization after Medicare Part D implementation,[12-14] it is important to determine the status of the receipt of ACEs/ARBs among Medicare beneficiaries with diabetes and hypertension after Part D implementation. The specific objectives of this study were (1) to determine the rate of receipt of ACEs/ARBs in physician-office and outpatient visits by Medicare beneficiaries with diabetes and hypertension and (2) to identify the patient- and community-level characteristics that predict the receipt of ACEs/ARBs.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Declarations
  9. References

Data source

This was a retrospective cross-sectional analysis of Medicare beneficiaries with diabetes and hypertension in the secondary databases, National Ambulatory Medical Care Survey (NAMCS) and National Hospital Ambulatory Medical Care Survey Outpatient Department (NHAMCS-OPD), from 2007 to 2009. NAMCS is a national probability sample survey conducted by the Division of Health Care Statistics, National Center for Health Statistics. NAMCS contains a sample of visits to non-federally employed office-based physicians who are primarily engaged in direct patient care.[15] It utilizes a multistage probability design that involves probability samples of primary sampling units (PSUs), physicians in PSUs and patient visits in practices. PSUs are geographical segments composed of counties, groups of counties, county equivalents (such as parishes or independent cities) or towns and townships in the 50 states of the USA and the District of Columbia.[15]

NHAMCS is conducted by the Ambulatory and Hospital Care Statistics Branch of the National Center for Health Statistics. The survey collects data from a sample of patient records selected from the emergency departments and outpatient departments of a national sample of hospitals. NHAMCS uses a four-stage probability design with samples of geographically defined areas, hospitals within these areas, clinics/emergency service areas within outpatient/emergency departments and patient visits in clinics/emergency service areas. This study utilized the outpatient department component of the NHAMCS.[15]

The basic sampling unit for NAMCS and NHAMCS is the physician–patient encounter or visit, which is defined as a direct, personal exchange between a patient and a physician, or a staff member acting under a physician's direction, for the purpose of seeking care and rendering health services. Each physician is randomly assigned to a 1 week reporting period. During this period data are collected from physicians or office staff, who record the data of a random sample of visits on the patient record form. Data are obtained on patient demographics, insurance status and clinical information such as the physicians' diagnosis and medications ordered or provided.[15] The most recent complete data were from the year 2009 at the time this study was conducted. The physician-office visits data (NAMCS) from 2007 to 2009 and the outpatient department visits data (NHAMCS-OPD) for the same period were combined to represent all US office-based and outpatient visits. The data could be combined from these two settings because they both belong to the Ambulatory Health Care Survey and they represent two different practice settings.[15]

Study sample

The final sample consisted of visits by Medicare beneficiaries with diabetes and hypertension. Patient visits were included in the analysis if the expected source of payment was Medicare for a given visit. Furthermore, visits by patients with diabetes and hypertension were selected based on the physician diagnosis codes (ICD-9-CM codes 401.XX–405.XX for hypertension and 250.XX for diabetes) in the database or a check mark on a list of 14 chronic conditions. NAMCS and NHAMCS provided up to three physician diagnoses. Both databases also included a list of 14 chronic conditions a patient may have, including hypertension and diabetes, starting from 2006. Patient visits with the following contraindications for ACEs/ARBs were excluded from the analyses: angioedema (ICD-9-CM 277.6, 995.1), aortic stenosis (ICD-9-CM 093.22, 395.0, 395.3, 396.2, 396.8, 424.1, 746.3), hypertrophic cardiomyopathy (ICD-9-CM 425.4, 746.84) and hyperkalaemia (ICD-9-CM 276.7).[10] As a result 89 patient visit records were excluded from the sample.

Outcome variable

The databases used in this study include medications that were ordered, supplied, administered or continued during a visit. Therefore, the outcome variable of interest was receiving ACEs/ARBs, defined as a record of these medications being ordered, supplied, administered or continued during a visit. This definition helped us to capture not only the ACEs/ARBs received during the first visit but also if these medications were continued in subsequent visits. In this study, ACEs/ARBs were determined by using the Multum Lexicon therapeutic classification system included in the databases. Additionally, the medication combinations of ACE inhibitors (ACE inhibitors with calcium channel blockers, ACE inhibitors with diuretics) and the medication combinations of ARBs (ARBs with diuretics) were selected based on the recommendations in the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure.[16] Under the Multum classification system each combination was assigned a single generic code. Ten combinations for ACE inhibitors and seven combinations for ARBs were included in this study, which were then identified using their respective generic codes.

Predictor variables

The present study used Andersen's behavioural model of health services utilization. This model defines the utilization of health services as a function of (1) predisposing, (2) enabling and (3) need factors. Predisposing factors refer to the characteristics of the individual that are present before the illness, including demographic characteristics, social structure characteristics and health beliefs. Enabling characteristics refer to community and personal resources and need characteristics refer to a patient's need to seek healthcare services.[17] Predisposing characteristics included in this study were age, sex and race/ethnicity. Race/ethnicity was recoded into a new variable consisting of categories including non-Hispanic whites (whites), non-Hispanic blacks (blacks), Hispanics and others. The enabling characteristics included in this study were private insurance, Medicaid, education, income, region, metropolitan statistical area and whether the provider was a primary care physician. Education was defined as the percentage of the population with a Bachelor's degree or higher in a patient's zip code, which was categorized as quartile 1 (Less than 12.84%), quartile 2 (12.84–19.66%), quartile 3 (19.67–31.68%) and quartile 4 (31.69% or more). Income was defined as median household income in a patient's zip code which was categorized as quartile 1 (US$32 793 or less), quartile 2 ($32 794–40 626), quartile 3 ($40 627–52 387) and quartile 4 ($52 388 or more). The need characteristic included in this study was patient's total number of chronic conditions, which was a count variable ranging from 0 to 14. These 14 chronic conditions were arthritis, asthma, cancer, cerebrovascular disease, chronic renal failure, congestive heart failure, chronic obstructive pulmonary disease, depression, diabetes, hyperlipidaemia, hypertension, ischaemic heart disease, obesity and osteoporosis. They were determined based on the list of 14 chronic conditions in the databases.

Data analyses

The physician-office visits data from 2007 to 2009 and the outpatient department visits data from 2007 to 2009 were combined. Bivariate and multivariate analyses were conducted to determine the factors associated with receiving ACEs/ARBs. For bivariate analyses, survey-weighted Wald chi-square tests were conducted to determine the statistical differences in the likelihood of receiving ACEs/ARBs by the predisposing, enabling and need factors. For the multivariate analyses, survey-weighted logistic regression analyses were conducted.

The complex survey design of NAMCS and NHAMCS survey were accounted for in all analyses. Observations with any missing values for the study variables were excluded from the analyses. The data analyses of this study were conducted using SAS 9.3 (SAS Institute, Cary, NC, USA). The statistical significance level was set a priori at 0.05.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Declarations
  9. References

Patient visit characteristics

Between the years 2007 and 2009 the total numbers of visits were 6311 among Medicare beneficiaries with diabetes and hypertension. Characteristics of Medicare beneficiaries with diabetes and hypertension who made visits to physician offices and outpatient departments were analysed (Table 1). A higher proportion of these patient visits was made by Medicare beneficiaries in the age group 65–74 years (42.19%) compared to the age groups younger than 65 years (16.86%), 75–84 years (32.22%) and 85 years and above (8.73%). Females accounted for a higher proportion of visits than males (54.36 compared with 45.64%). Whites accounted for a higher proportion of visits (71.27%) than blacks (15.76%), Hispanics (9.8%) and others (3.17%). The majority of the Medicare beneficiaries who made visits to the physician office and outpatient department did not have private insurance (60.8%) or Medicaid (88.93%). A higher proportion of the visits was made by patients who resided in the zip codes with the lowest education level, quartile 1 (29.49%), compared to visits made by patients who resided in quartile 2 (27.15%), quartile 3 (23.84%) and quartile 4 (19.52%) for education level. Similarly, a higher proportion of the visits was made by patients who resided in zip codes with a median household income in quartile 1 (28.69%) in comparison to zip codes with a median household income in quartile 2 (26.36%), quartile 3 (24.8%) and quartile 4 (20.15%) for income level. A higher proportion of patient visits was made to physician practices located in the south (42.53%) compared to the midwest (22.24%), northeast (19.75%) and west (15.48%) regions. The majority of patient visits was made to physician practices located in a Metropolitan Statistical Area (83.19%). More visits were made to primary care physicians (53.31%) than non-primary care physicians (46.69%). Regarding health status, a higher proportion of visits was made by patients who had three chronic conditions (31.99%) compared to visits made by patients with two (17.97%), four (25.1%) and five or more (24.93%) chronic conditions.

Table 1. Characteristics of Medicare beneficiaries with diabetes and hypertension who made visits to physician offices and outpatient departments in 2007–2009
CharacteristicGroupNumber of visitsFrequencya
UnweightedWeighted%
  1. MSA, Metropolitan Statistical Area.

  2. a

    Percentage of visits.

  3. b

    Information on 237 visits were missing for the variable Bachelor's degree or higher in patient's zip code.

  4. c

    Information on 237 visits were missing for the variable Median household income in patient's zip code.

  5. d

    Information on 237 visits were missing for the variable Primary care physician visit.

Age (years)<65153419 479 74416.86
65–74251248 749 22642.19
75–84179637 235 51832.22
85 and above46910 091 7328.73
SexFemale345362 822 05054.36
Male285852 734 17045.64
Race/ethnicityNon-Hispanic white412481 916 01570.89
Non-Hispanic black124318 100 15815.66
Hispanic63111 526 4459.98
Other3134 013 6023.47
Private insuranceNo429070 263 90660.80
Yes202145 292 31439.20
MedicaidNo5283102 766 76788.93
Yes102812 789 45311.07
Bachelor's degree or higher in patient's zip codebQuartile 1186032 908 30929.49
Quartile 2157730 301 12927.15
Quartile 3148226 603 95823.84
Quartile 4115521 775 14719.52
Median household income in patient's zip codecQuartile 1202532 017 11128.69
Quartile 2157229 412 07026.36
Quartile 3134627 675 21424.80
Quartile 4113122 484 14820.15
RegionNortheast167422 822 81519.75
Midwest149425 704 88222.24
South221749 142 11842.53
West92617 886 40515.48
MSANon-MSA90119 430 69916.81
MSA541096 125 52183.19
Primary care physician visitdNo392051 810 86746.69
Yes215459 159 87953.31
Number of chronic conditions2118820 762 94817.97
3194936 965 43831.99
4161728 989 55625.09
5 or more155728 796 68424.95

Of the 6311 Medicare outpatient and physician-office visits made by patients with hypertension and diabetes, 40.7% patient visits were associated with receiving ACEs/ARBs. The association of patient- and community-level characteristics with the receipt of ACEs/ARBs was analysed (Table 2). It was found that ACEs/ARBs were more likely to be received during visits to primary care physicians than in visits to non-primary care physicians (48.39 versus 32.56%; P < 0.05). Apart from the variable for primary care physician, none of the patient- and community-level characteristics were significantly associated with receiving ACEs/ARBs. Multivariate logistic regression analysis was conducted to identify the patient- and community-level characteristics that predicted the receipt of ACEs/ARBs (Table 3). It was found that ACEs/ARBs were 45% more likely to be received during visits made by patients residing in zip codes with a median household income in quartile 2 than during visits made by patients residing in zip codes with a median household income in quartile 1 (odds ratio 1.45, 95% confidence interval 1.13–1.87). Visits to primary care physicians had 96% higher likelihood of receiving ACEs/ARBs compared to visits to non-primary care physicians (odds ratio 1.96, 95% confidence interval 1.59–2.43). None of the other factors were found to be significantly associated with receiving ACEs/ARBs.

Table 2. Bivariate association of patient characteristics with receipt of ACEs/ARBs during visits by Medicare beneficiaries with diabetes and hypertension in 2007–2009
CharacteristicGroupVisits receiving ACEs/ARBsVisits not receiving ACEs/ARBs
Frequency%Frequency%
  1. ACEs/ARBs, angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers; MSA, Metropolitan Statistical Area.

  2. a

    P < 0.05.

Age (years)<6549634.56103865.44
65–74102342.79148957.21
75–8468942.06110757.94
85 and above16637.4030362.60
SexFemale131140.48214259.52
Male106340.95179559.05
Race/ethnicityNon-Hispanic white153640.13258859.87
Non-Hispanic black50140.0574259.95
Hispanic23044.8740155.13
Other10743.1820656.82
PrivateNo161240.12267859.88
InsuranceYes76241.59125958.41
MedicaidNo203440.84324959.16
Yes34039.5268860.48
Bachelor's degree or higher in patient's zip codeQuartile 169440.37116659.63
Quartile 260042.1397757.87
Quartile 355042.6093257.40
Quartile 443637.3271962.68
Median household income in patient's zip codeQuartile 172036.90130563.10
Quartile 259946.1397353.87
Quartile 352840.7181859.29
Quartile 443339.4369860.57
RegionNortheast66739.49100760.51
Midwest56542.2092957.80
South81340.91140459.09
West32939.4959760.51
MSANon-MSA35940.2754259.73
MSA201540.78339559.22
Primary care physician visitaNo124132.56267967.44
Yes104548.39110951.61
Number of chronic conditions238737.9780162.03
375440.31119559.69
465843.6795956.33
5 or more57540.1698159.84
Table 3. Multivariate logistic regression for the association of patient characteristics with the likelihood of receiving ACEs/ARBs during visits made by Medicare beneficiaries with hypertension and diabetes
ParameterEstimateStandard errorWald chi-squareP valueOdds ratio95% Confidence interval for odds ratio
  1. ACEs/ARBs, angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers; MSA, Metropolitan Statistical Area. Variables based on the Andersen's model: predisposing factors (age, sex and race/ethnicity), enabling factors (private insurance, Medicaid, education, income, region, metropolitan statistical area and primary care physician visit), and need factor (number of chronic conditions).

Intercept−1.470.3715.83<0.01
Age0.01<0.013.700.051.011.001.01
Female
Male0.020.080.050.821.020.861.20
Non-Hispanic white
Non-Hispanic black0.100.160.420.521.110.821.50
Hispanic0.150.141.110.291.160.881.53
Other0.190.270.500.481.210.712.05
No private insurance
Private insurance0.120.140.780.381.130.861.48
No Medicaid
Medicaid−0.050.140.130.710.950.721.25
Education quartile 1
Education quartile 2−0.020.130.030.860.980.751.26
Education quartile 3−0.030.130.040.840.970.751.26
Education quartile 4−0.210.191.190.280.810.561.18
Income quartile 1
Income quartile 20.370.138.31<0.011.451.131.87
Income quartile 30.150.150.930.331.160.861.56
Income quartile 40.200.210.890.341.220.811.84
Northeast
Midwest<0.010.22<0.010.961.000.651.55
South0.050.200.170.791.060.711.58
West−0.110.270.160.690.900.531.52
Non-MSA
MSA0.120.190.370.551.120.771.64
Non-primary care physician visit
Primary care physician visit0.670.1138.68<.00011.961.592.43
Number of chronic conditions−0.020.040.410.520.980.911.05

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Declarations
  9. References

Our analysis of US national survey data revealed that fewer than half of the outpatient visits were associated with receiving ACEs/ARBs. This relatively low level of receipt of ACEs/ARBs during visits by the Medicare population is a major concern, because ACEs/ARBs are considered the first-line therapy and are one of the CMS's quality measures for medication management to rate Medicare Part D plans.[3, 7] A recent report from the CMS showed the rate of utilization of ACEs/ARBs to be between 56.5 and 91.9% in 2011 for Medicare Advantage Prescription Drug Plans (MAPDs) and Prescription Drug Plans (PDPs).[18] The CMS annually raises the required threshold for the plans to achieve higher ratings for this measure with the objective of continuous quality improvement. For 2011 the four-star threshold for the rate of ACE/ARB use for MAPDs was ≥86% and for PDPs was ≥83%. The proposed four-star threshold for 2012 data for MAPDs was >87% and for PDPs was >84%.[18]

The lower rates of receiving ACEs/ARBs in the present study in comparison to the rates reported by the CMS may partly be explained by different methods of calculating these rates. The CMS defines appropriate treatment of hypertension in patients with diabetes as the proportion of patients who receive an ACE/ARB among patients who fill a prescription for diabetes and hypertension.[3] However, the sample in this study was selected based on a diagnosis for diabetes and hypertension and was not limited to individuals with a medication filled for diabetes and hypertension. Previous population-based studies found the use of ACEs/ARBs among patients with diabetes and hypertension to be between 46 and 64%.[9-11, 19] Although studies conducted after implementation of Medicare Part D have shown an overall increase in medication use,[12-14] the present study found that ACEs/ARBs were not received during the majority of physician-office and outpatient department visits made by Medicare beneficiaries with diabetes and hypertension.

The lower rates of receiving these medications might also be due to physicians failing to prescribe ACEs/ARBs. The 2010 US Patient Protection and Affordable Care Act (ACA) has directed efforts at physicians to promote the practice of evidence-based medicine. One ACA provision is to allow providers organized as Accountable Care Organizations (ACOs) that voluntarily meet quality thresholds to share in the cost savings they achieve for the Medicare programme. To qualify as an ACO organizations must agree to be accountable for the overall care of their Medicare beneficiaries, have adequate participation of primary care physicians, define processes to promote evidence-based medicine, report on quality and costs, and coordinate care.[20] This provision may increase the receipt of ACEs/ARBs among patients with diabetes and hypertension.

Another approach to achieving a high plan rating for the measure of receiving ACEs/ARBs among Medicare beneficiaries with diabetes and hypertension would be to provide medication therapy management (MTM) services by pharmacists and other qualified healthcare providers.[21] Being one of the most accessible types of healthcare professional, pharmacists are in a prime position to provide these services.[22] Studies have reported the benefit of incorporating pharmacists as a part of the healthcare team for managing chronic diseases.[23, 24] One study reported a 41.41% prescriber approval rate for guideline-adherent recommendations by pharmacists.[25] The same study also found that primary care physicians had higher rates of approving pharmacist recommendations than specialists.[25] Since primary care physicians are in short supply, pharmacists may take a more active role in the healthcare team. The National Quality Strategy, which is required by the ACA, addresses a range of quality concerns affecting individuals.[26] Although there are many accepted quality measures, it has been found that inadequate measures exist in some areas, such as care coordination and patient engagement. [26] Providing MTM services can be one of the ways to address issues with care coordination and patient engagement.

The bivariate and multivariate findings revealed that patients who made visits to primary care physicians were more likely to receive ACEs/ARBs. This finding is consistent with other studies, which have found positive patient outcomes associated with having access to a primary care physician.[27, 28] The US healthcare system has been facing a decline in its primary care workforce. Lack of financial incentives and poor reimbursement have resulted in many physicians choosing to train and practice specialty medicine.[29] Studies have found that although 56% of patient visits in America are to primary care, only 37% of physicians practice primary care medicine and only 8% of the nation's medical school graduates go into family medicine.[29, 30] The ACA also has several provisions aimed at improving access to primary care, including a 10% bonus for primary care providers under the Medicare fee schedule and an additional $230 million in award grants which will go to teaching health centres to start primary care residency programmes.[20] One challenge in the successful implementation of these provisions would be the long time period required to train new primary care physicians.

This study found that visits made by patients from the zip codes with a median household income in quartile 2 were more likely to be associated with receiving ACEs/ARBs than visits made by patients from zip codes with quartile 1 median household incomes. None of the other patient- and community-level factors were associated with receiving ACEs/ARBs. In contrast, other population-based studies found the use of ACEs/ARBs to be associated with sociodemographic factors. These factors included gender, age and race in previous studies.[9-11, 19] Since this study was based on a sample of physician-office and outpatient visits, the patients already had access to health care. Additionally, unlike other population-based studies, the enabling characteristics such as education and income denote the education and income level of an area rather than the individual. These might be some reasons for the lack of significant association between sociodemographic characteristics and receiving ACEs/ARBs.

The present study has made new contributions to the existing research. First, the study updates previous research on the rate of ACEs/ARBs among Medicare beneficiaries by using data after the implementation of Medicare Part D. Second, in this study the data were collected from the patient record form completed by the provider, and were not based on recall by patients, which may provide a better assessment of the quality of care provided during routine visits to physician-office and outpatient department settings.[15] Thus, findings from this study provide updated information to policy makers, health plans and physicians regarding the adequacy of evidence-based pharmacotherapy in patients with diabetes and hypertension. In addition, this study also highlights the positive association between visits made to primary care physicians and receiving the recommended pharmacotherapy for the treatment of hypertension among diabetic patients. The findings of this study add to the body of evidence, indicating the importance of primary care physicians, and may provide policy makers with further justification to increase the supply of these providers.

Our study has some limitations. First, the data did not contain patient identifiers so they cannot be used to determine prevalence estimates. Since the data were based on visits, it is possible that sicker patients and those making more frequent follow-up visits may have been repeated in the sample. Second, this study used the NAMCS and NHAMCS-OPD databases (2007–2009), which are secondary in nature. As a result, this study had to rely on only those variables which are available in the databases. Third, the results of this study are only applicable to patients making physician-office and outpatient visits and do not represent the entire US population. Fourth, the databases include only eight prescribed medications; thus it is possible that ACEs/ARBs could have been omitted for patients treated with more than eight drugs. Finally, the NAMCS and NHAMCS databases do not report income at the individual level, which can be a more reliable measure than income level according to zip code.

Conclusion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Declarations
  9. References

Fewer than half of outpatient visits by Medicare beneficiaries with diabetes and hypertension were associated with receiving ACEs/ARBs. Promoting evidence-based medicine, increasing access to primary care physicians and increasing the role of pharmacists in patient care may have the potential to increase the rate of receiving ACEs/ARBs in visits made by this population. Future studies should also consider other physician-related factors that might contribute to better understanding of the barriers to patients receiving ACEs/ARBs among Medicare beneficiaries with diabetes and hypertension.

Declarations

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Declarations
  9. References

Conflict of interest

The Author(s) declare(s) that they have no conflicts of interest to disclose.

Funding

This project was supported by grant number R01AG040146 from the National Institute On Aging. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute On Aging or the US National Institutes of Health.

Authors' contributions

Drs J Wang and JW Kuhle designed the study along with S Surbhi. S Surbhi conducted data analysis and drafted the paper with guidance and revisions by Drs J Wang and JW Kuhle. All Authors state that they had complete access to the study data that support the publication.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conclusion
  8. Declarations
  9. References