1. Introduction
About 74 million Americans, or one in three adults, have high blood pressure. Hypertension is a silent disease that does not show symptoms until it has caused permanent damage to the heart, brain, kidneys or eyes [
1,
2]. Unfortunately, about a quarter of people with high blood pressure do not know they have the condition. Half of the people being treated for the disease gradually increase the dose to reach the target blood pressure, which is 130/80 mmHg for patients with no clinical Cardiovascular Disease CVD and having a less than 10% 10-year Atherosclerotic Cardiovascular Disease (ASCVD) risk, and 130/80 mmHg for patients with diabetes, chronic kidney disease, or any type of atherosclerosis, such as peripheral artery disease, aortic aneurysm, and coronary artery disease [
3,
4].
Control of hypertension is one of the most important health care priorities and is expected to increase with an aging population and increasing burden of obesity and other risk factors related to lifestyle. Hypertension is primarily managed in ambulatory settings accounting for an estimated 79% of primary care visits [
5]. Better hypertension control can positively impact cardiovascular health [
6,
7]. Recent studies have identified increased use of antihypertensive agents coincides with increased control over blood pressure both in younger and older populations and decreased cardiovascular mortality, myocardial infarction and stroke rates [
8,
9,
10].
Appropriate antihypertensive therapy in outpatient care is important for optimal treatment outcomes. According to recent guidelines, there are different blood pressure goals using an age cutoff of 50 years. National Ambulatory Medical Care Survey (NAMCS) data analysis for the years 2003–2010 revealed antihypertensive medication prescription increased from 69.2% in 2003–2004 to 78.8% in 2009–2010 (P = 0.001) with increased blood pressure control from 39.1% to 48.8% (P < 0.001). The trend was consistent in patients younger, as well as older than 60. Prescription for beta-blocker has increased from 25.4% to 34.7% while ARB prescription increased 17% to 22.1. African American patients, those with other comorbidities, insufficient insurance coverage and younger patients are less likely to control their blood pressure. Adults aged 18–39 have the lowest hypertension control rates among adults with hypertension in the US [
11]. Surprisingly, older patients are more likely to control their blood pressure than the younger population, which may be due to lack of disease awareness and management or resistance to initiation and escalation of antihypertensive therapy [
12].
The goal of this study is to determine prescribing pattern for patients with hypertension for the year of 2015 and determine if they are being prescribed first-line therapy and evaluate the adherence of prescribers to current guidelines.
Non-adherence to first-line therapy is one of the drivers for economic implications as it may lead to treatment failure, disease progression and more complex treatments, resulting in increased cost of treatment. According to AHA, the estimated direct and indirect cost of hypertension in the US was 76.6 billion dollars in 2010 [
13]. The direct medical costs of CV disease may be substantially higher than this estimate since it includes secondary hospitalizations, which accounts for 18,953 dollars per patient annually as direct medical costs. Additionally, patients with secondary hospitalizations coat 4.5 times higher than those with no hospitalizations [
14].
2. Materials and Methods
Data from 2015 NAMCS were used in the study. Patients data with primary diagnoses of essential hypertension were extracted by using ICD-9 code “401”. The National Ambulatory Medical Care Survey (NAMCS) is designed to meet the need for objective, reliable information about the provision and use of ambulatory medical care services in the United States.
A total of 595 patients were found which represented the study sample. Patient age, sex, race, as well as the source of payment, and the provider type were among the operational factors used in data analysis. Sources of payment were defined as coverage through either private insurance, Medicaid, Medicare, or other state-based programs, self-pay, work compensation, and charity. All variables were categorized as “patient” or “physician” factors. Geographic region was the only variable categorized as both patient and physician.
Data analysis was performed using SPSS software for descriptive data analyses and statistical coding. Various demographic variables were analyzed using frequencies, means and other descriptive statistics. The data was further analyzed using chi-square to compare proportions between groups. The extracted data set was checked for integrity, equality and distribution of a number of records in every phase of analysis. The hypothesis focused on physician variables to determine whether the number of non-first-line antihypertensive agents prescribed was related to physician’s specialty, geographic region and other demographic variables, such as age, gender, race and payment type. The definition of prescribing appropriateness was determined by 2017 AHA/ACC guidelines. Thiazides, ACE inhibitors, ARBs and CCBs were defined as first-line and appropriate treatment agents, whereas loop diuretics, beta-blockers, direct renin inhibitor, alpha-1 blockers, direct vasodilators, central alpha-1 agonists and other centrally acting drugs were defined as non-first line agents.
3. Results
Females and white patients represented over half of the sample. Patients aged 65 and older represented half of the sample, followed by those aged 45. Majority of the patients had Medicare as primary insurance (64.45%), and 39.3% were private insurance holders. General doctors (34.8%), cardiovascular specialists (32.1%) and internal medicine physicians (21.8%) were the majority. Most of the visits occurred in the South (36.5%) and Midwest (26.9%) (
Table 1). After analyzing the data, 51.4% of prescriptions turned out to be non-first-line prescriptions.
Female patients (X
2 = 0.376) and those aged 65 and older (X
2 = 0.073) received more non-first-line agents. White, African American patients (X
2 = 0.208), as well as Medicare and private insurance holders (X
2 = 0.145) were prescribed more non-first-line antihypertensive agents. Chi-square analysis showed that South and Midwest received more non-adherent prescriptions (X
2 = 0.023). Cardiovascular specialists, family doctors and internal medicine specialists prescribed more non-first-line agents (X
2 = 0.222) (
Table 2).
4. Discussion
This study reveals not only significant differences in antihypertensive drug utilization among various demographics and physician specialties but also lack of adherence to the prescribing guidelines. Female and white patients, representing the majority of the sample, were prescribed more non-first-line treatments, as was the case with patients 65 and older. Since this population represented half of the sample, they also represented the subgroup having Medicare. South and West had more cases of non-first-line prescribing pattern due to being the majority (X2 = 0.023). This corresponds to data from other studies about the South being one of the geographical areas with poor health and wellness.
Primary (essential) hypertension is diagnosed in the absence of an identifiable secondary cause. It is characterized by severe headache, fatigue or confusion, vision problems, difficulty breathing among other symptoms. The rise in antihypertensive drug utilization represents a potentially favorable development in terms of increased numbers of patients undergoing drug treatment.
Cardiovascular specialists and general doctors who were the most common provider seen by the patients, were also one of the provider specialties prescribing the majority of non-first-line agents, which corresponds to hypertension being a cardiovascular condition.
The data analysis showed that half of the antihypertensive prescriptions are not first-line agents, which can imply less effective drug therapy and worse clinical outcomes. This is where the issue of medication non-adherence comes into play to ensure the effectiveness of first-line therapy if there are no contraindications, to avoid side effects associated with non-first-line agents, such as beta-blockers and loop diuretics and to reach a better blood pressure control.
Over 25% of people prescribed antihypertensive medications stop taking them 6 months after initiation of therapy. Medication adherence is influenced by physician communication and medical management skills, even though they can be improved by educational and practice interventions [
15]. The risk of non-adherence can be reduced with better medical management, communication skills, early therapy changes, more follow-up visits, and lastly, starting therapy with nondiuretic agents. A study by Tamblyn et al. found that medical management can reduce non-adherence by 15.8% [
16]. Understanding barriers in hypertension management will inform the development of interventions to control blood pressure in the young adult population. Such barriers include altered self-identity, greater blood pressure variability, possible side effects initiating a medication, gender differences among young adults were also barriers to follow-up and new hypertension medication initiation. The pressure of having an effective motivational interview with productive outcomes, cost of the medication and the lack of motivation from the patient to schedule a follow-up visit can make hypertension management even harder. Thus, taking measures directed to young adults are essential to improve hypertension care in this population [
11].
Conn et al. suggest that habit-focused interventions reduce blood pressure more effectively because they examine participants’ daily routines and incorporate medication administration to routine events. Such interventions improve clinical outcomes by improving adherence. Habit-based interventions can also be tailored into a patient’s daily routine to enhance a healthy lifestyle, which in turn will positively impact blood pressure control. Interventions delivered by pharmacists were found to be most effective, as patients see them as experts in medication therapy and are very receptive to their recommendations [
17].
The study was limited by the operational definitions of the study variables and the data collection period. Another limitation was the number of ambulatory care visits during the year of 2015. The variable selection was based on the available NAMCS database. In addition, the patients were assumed to have an initial diagnosis of hypertension, rather than a recurrent visit.
Another limitation of the study was that the 2015 guidelines include beta-blockers along with ACE inhibitors or ARBs, and thiazide or thiazide-like diuretics in the first-line treatment in those with a history of MI. The 2017 ACC/AHA guidelines did not indicate beta-blockers as first-line treatments. Although the analysis criteria for this study were for essential hypertension, there may have been few patients who were prescribed only a beta-blocker and were considered as non-first line therapy. No allergy information was available, and the patients not given the first-line agent because of the allergy were not identified. Lastly, treatments consisted of agents other than ACEI, thiazides, CCBs, ARB or a combination of any of the above agents along with the treatments with a primary diagnosis of hypertension and not receiving any therapy were considered non-first-line.
Large differences in the utilization of different groups of antihypertensive agents were noted in this study. Underutilization of valuable, efficacious, and cost-effective thiazide diuretics and overuse of expensive ACE inhibitors is unjustifiable. Therefore, more attention should be paid to their implementation in order to improve health gains. Clinicians may use these findings to tailor antihypertensive therapy to the needs of each patient.
Author Contributions
Conceptualization, Y.S.; methodology, Y.S.; software, B.B.; validation, Y.S. and A.R.; formal analysis, Y.S.; investigation, Y.S.; resources, Y.S. and B.B.; data curation, Y.S., B.B., and A.R.; writing-original draft preparation, Y.S., B.B., and A.R.; writing—review and editing, Y.S., B.B., and A.R.; visualization, Y.S.; supervision, Y.S. and A.R.; project administration, Y.S., B.B., and A.R.; funding, N/A.
Funding
This research received no external funding.
Conflicts of Interest
The authors declare no conflicts of interest.
References
- Ong, K.L.; Cheung, B.M.Y.; Man, Y.B.; Lau, C.P.; Lam, K.S.L. Prevalence, awareness, treatment, and control of hypertension among United States adults 1999–2004. Hypertens 2007, 49, 69–75. [Google Scholar] [CrossRef] [PubMed]
- Ostchega, Y.; Yoon, S.; Hughes, J.; Louis, T. Hypertension Awareness, Treatment, and Control—Continued Disparities in Adults: United States, 2005–2006 Highlights Data from the National Health and Nutrition Examination Surveys. NCHS Data Brief. Available online: https://www.cdc.gov/nchs/data/databriefs/db03.pdf (accessed on 10 July 2018).
- Healthwatch, editorial, Treating hypertension: Are two meds better than one? Harv. Mens Health Watch 2010, 15, 5–6. Available online: https://eds-a-ebscohost-com.ezproxy.rosalindfranklin.edu/eds/detail/detail?vid=0&sid=d69bc3e2-5a174048a4e608d41daa6713%40sessionmgr4008&bdata=JnNpdGU9ZWRzLWxpdmUmc2NvcGU9c2l0ZQ%3D%3D#db=edb&AN=54985255 (accessed on 9 July 2018).
- Whelton, P.K.; Carey, R.M.; Aronow, W.S.; Casey, D.E.; Collins, K.J.; Himmelfarb, C.D.; DePalma, S.M.; Gidding, S.; Jamerson, K.A.; Jones, D.W.; et al. 2017 Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults. Am. Coll. Cardiol. Hear Assoc. 2017, 71, 4–28. Available online: https://www.acc.org/latest-in-cardiology/ten-points-to-remember/2017/11/09/11/41/2017-guideline-for-high-blood-pressure-in-adult (accessed on 5 June 2019). [CrossRef]
- Margolius, D.; Bodenheimer, T. Controlling hypertension requires a new primary care model. Am. J. Health Pharm. 2010, 16, 648–650. [Google Scholar]
- Moran, A.E.; Odden, M.C.; Thanataveerat, A.; Tzong, K.Y.; Rasmussen, P.W.; Guzman, D.; Williams, L.; Bibbins-Domingo, K.; Coxson, P.G.; Goldman, L. Cost-Effectiveness of Hypertension Therapy According to 2014 Guidelines A BS TR AC T. N. Engl. J. Med. 2015, 5, 447–455. [Google Scholar] [CrossRef] [PubMed]
- Psaty, B.M.; Smith, N.L.; Siscovick, D.S.; Koepsell, T.D.; Weiss, N.S.; Heckbert, S.R.; Lemaitre, R.N.; Wagner, E.H.; Furberg, C.D. Health Outcomes Associated With Antihypertensive Therapies Used as First-Line Agents: a systematic review and meta-analysis. JAMA J. Am. Med. Assoc. 1997, 277, 739. [Google Scholar] [CrossRef]
- Gu, Q.; Burt, V.L.; Dillon, C.F.; Yoon, S. Trends in antihypertensive medication use and blood pressure control among United States adults with hypertension: The National Health And Nutrition Examination Survey, 2001 to 2010. Circulation 2012, 126, 2105–2114. [Google Scholar] [CrossRef] [PubMed]
- Guo, F.; He, D.; Zhang, W.; Walton, R.G. Trends in Prevalence, Awareness, Management, and Control of Hypertension Among United States Adults, 1999 to 2010. J. Am. Coll. Cardiol. 2012, 60, 599–606. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Egan, B.M.; Zhao, Y.; Axon, R.N. US Trends in Prevalence, Awareness, Treatment, and Control of Hypertension, 1988–2008. JAMA 2010, 303, 2043. [Google Scholar] [CrossRef] [PubMed]
- Johnson, H.M.; Warner, R.C; Bartels, C.M.; LaMantia, J.N. “They’re younger… it’s harder.” Primary providers’ perspectives on hypertension management in young adults: A multicenter qualitative study. BMC Res. Notes 2017, 10, 9. [Google Scholar] [CrossRef] [PubMed]
- Gu, A.; Yue, Y.; Argulian, E. Age Differences in Treatment and Control of Hypertension in US Physician Offices, 2003-2010: A Serial Cross-sectional Study. Am. J. Med. 2016, 129, 50–58. [Google Scholar] [CrossRef] [PubMed]
- Roger, V.L.; Go, A.S.; Lloyd-Jones, D.M.; Adams, R.J.; Berry, J.D.; Brown, T.M.; Carnethon, M.R.; Dai, S.; De Simone, G.; Ford, E.S.; et al. Heart Disease and Stroke Statistics—2010 Update A Report From the American Heart Association. Circulation 2010, 121, e46–e215. [Google Scholar] [CrossRef]
- Nichols, G.A.; Bell, T.J.; Pedula, K.L.; O’Keeffe-Rosetti, M. Medical Care Costs Among Patients With Established Cardiovascular Disease. Circulation 2009, 120 (Suppl. 18), S470. Available online: https://www.ahajournals.org/doi/abs/10.1161/circ.120.suppl_18.S470-b (accessed on 12 July 2018).
- Perreault, S.; Lamarre, D.; Blais, L.; Dragomir, A.; Berbiche, D.; Lalonde, L.; Laurier, C.; St-Maurice, F.; Collin, J. Persistence with Treatment in Newly Treated Middle-Aged Patients with Essential Hypertension. Ann. Pharmacother. 2005, 39, 1401–1408. [Google Scholar] [CrossRef] [PubMed]
- Tamblyn, R.; Abrahamowicz, M.; Dauphinee, D.; Wenghofer, E.; Jacques, A.; Klass, D.; Smee, S.; Eguale, T.; Winslade, N.; Girard, N.; et al. Influence of Physicians’ Management and Communication Ability on Patients’ Persistence With Antihypertensive Medication. Arch. Intern. Med. 2010, 170, 1064. [Google Scholar] [CrossRef] [PubMed]
- Conn, V.S.; Ruppar, T.M.; Chase, J.A. Blood pressure outcomes of medication adherence interventions: Systematic review and meta-analysis. J. Behav. Med. 2016, 39, 1065–1075. [Google Scholar] [CrossRef] [PubMed]
Table 1.
Demographics.
Demographic Variables | Frequency (n) | Percentage |
---|
Gender | | |
Female | 324 | 54.5 |
Male | 271 | 45.5 |
Age Range | | |
15–44 years | 50 | 8.4 |
45–64 years | 245 | 41.2 |
65–74 years | 156 | 26.2 |
75 and older | 144 | 24.2 |
Race | | |
White | 347 | 58.3 |
African American | 124 | 20.8 |
Other | 21 | 3.5 |
Blank | 103 | 17.3 |
Type of Payment | | |
Private Insurance | 234 | 39.3 |
Medicare | 268 | 45 |
Medicaid | 38 | 6.4 |
Other | 55 | 9.3 |
Physician Specialty | | |
General/Family practice | 207 | 34.8 |
Internal medicine | 130 | 21.8 |
Cardiovascular diseases | 191 | 32.1 |
Physician assistant | 15 | 2.5 |
Nurse practitioner | 8 | 1.3 |
Other specialties | 44 | 7.4 |
Region | | |
Northeast | 102 | 17.1 |
Midwest | 160 | 26.9 |
South | 217 | 36.5 |
West | 116 | 19.5 |
Table 2.
Prescribing patterns.
Table 2.
Prescribing patterns.
Prescribing Pattern Based on Demographic Variables | First-Line Therapy (n) (%) | Non-First-Line Therapy (n) (%) | Significance |
---|
(P) |
---|
Percentage | 48.60% | 51.40% | |
Gender | | | 0.376 |
Female | 172 (28.9%) | 152 (25.5%) |
Male | 134 (22.5%) | 137 (23.0%) |
Age | | | 0.073 |
15–44 | 20 (3.3%) | 30 (5.0%) |
45–64 | 130 (21.8%) | 115 (19.3%) |
65–74 | 78 (13.1%) | 78 (13.1%) |
75 and older | 78 (13.1%) | 66 (11.0%) |
Race | | | 0.208 |
White | 175 (29.4%) | 172 (28.9%) |
African American | 70 (11.7%) | 54 (9.0%) |
Other | 61(10.2%) | 63 (10.5%) |
Insurance type | | | 0.145 |
Private Insurance | 119 (20.0%) | 115 (19.3%) |
Medicare | 145 (24.3%) | 123 (20.6%) |
Medicaid | 15 (2.5%) | 23 (3.8%) |
Other | 27 (4.5%) | 28 (4.7%) |
Region | | | 0.023 |
Northwest | 55 (9.2%) | 47 (7.8%) |
Midwest | 90 (15.1%) | 70 (11.7%) |
South | 116 (19.4%) | 101 (11.6%) |
West | 45 (7.5%) | 71 (11.9%) |
Physician | | | 0.222 |
General/Family practice | 95 (15.9%) | 112 (18.8%) |
Internal medicine | 65 (10.9%) | 65 (10.9%) |
Cardiovascular diseases | 112 (18.8%) | 79 (13.2%) |
Other specialties | 33 (5.5%) | 34(5.6%) |
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).