Health Care Fragmentation and Blood Pressure Control Among Adults Taking Antihypertensive Medication

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The American Journal of Managed Care, March 2022, Volume 28, Issue 3

Among older Black adults taking antihypertensive medication, fragmented ambulatory health care was associated with an increased likelihood of apparent treatment-resistant hypertension with uncontrolled blood pressure.

ABSTRACT

Objectives: To determine the association of fragmented ambulatory health care with uncontrolled blood pressure (BP) and apparent treatment-resistant hypertension (aTRH) among older adults taking antihypertensive medication, overall and by race and gender.

Study Design: Cross-sectional study using data from 2868 REasons for Geographic And Racial Differences in Stroke (REGARDS) study participants 66 years and older who completed a study examination in 2013-2016, had Medicare fee-for-service coverage, and were taking antihypertensive medication.

Methods: We used logistic regression to analyze the association of fragmented health care with uncontrolled BP and aTRH. Fragmented health care was operationalized as a reversed Bice-Boxerman Index score in the 75th percentile or higher, calculated using the number of ambulatory providers and health care visits in the year preceding the study examination. Uncontrolled BP was defined by systolic BP of at least 140 mm Hg or diastolic BP of at least 90 mm Hg. aTRH was defined by taking 3 or more classes of antihypertensive medication with uncontrolled BP or 4 or more classes with controlled BP.

Results: The overall adjusted odds ratios (95% CIs) for uncontrolled BP, aTRH with controlled BP, and aTRH with uncontrolled BP associated with fragmented health care were 1.10 (0.89-1.37), 1.08 (0.80-1.47), and 1.32 (0.96-1.81), respectively. Fragmented health care was not associated with uncontrolled BP or aTRH among White participants, women, or men. Among Black participants, the odds ratio (95% CI) associated with fragmented health care was 1.21 (0.81-1.82) for uncontrolled BP, 1.22 (0.72-2.07) for aTRH with controlled BP, and 1.82 (1.07-3.11) for aTRH with uncontrolled BP.

Conclusions: Fragmented health care may increase the likelihood of aTRH with uncontrolled BP among older Black adults taking antihypertensive medication.

Am J Manag Care. 2022;28(3):108-115. https://doi.org/10.37765/ajmc.2022.88837

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Takeaway Points

  • In the current analysis including adults 66 years and older with Medicare fee-for-service coverage in a large population-based cohort who were taking antihypertensive medication in 2013-2016:
  • Fragmented health care was not associated with uncontrolled blood pressure (BP) or apparent treatment-resistant hypertension (aTRH) in the overall study population or among White participants, men, or women.
  • Among Black participants, fragmented health care was associated with an increased odds of aTRH with uncontrolled BP (odds ratio, 1.82; 95% CI, 1.07-3.11).

Among older Black adults taking antihypertensive medication, fragmented health care may increase the likelihood of aTRH with uncontrolled BP.

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Antihypertensive medication reduces the risk of cardiovascular disease (CVD) and all-cause mortality in adults with hypertension.1-3 However, 35.2% of US adults with hypertension taking antihypertensive medication have uncontrolled blood pressure (BP).4 In addition, 17.7% of US adults taking antihypertensive medication have apparent treatment-resistant hypertension (aTRH), defined as uncontrolled BP while taking 3 or more classes of antihypertensive medication or taking 4 or more classes of antihypertensive medication with controlled BP.5 Adults with aTRH have a higher risk of CVD and all-cause mortality compared with their counterparts with hypertension without aTRH.6,7

Several factors contribute to uncontrolled BP among adults taking antihypertensive medication, including medication nonadherence, an unhealthy diet, and low physical activity.8-10 Fragmented ambulatory health care, wherein a patient’s care is spread across many health care providers without a dominant provider, is common and may increase the likelihood of gaps in communication across providers caring for the same patient.11-13 Findings of prior studies suggest that fragmented health care may increase the likelihood of uncontrolled BP among adults taking antihypertensive medication.14,15 Fragmented health care may also increase the likelihood that adults with hypertension are prescribed medicines that raise BP or counteract their antihypertensive medication, leading to aTRH.16,17 Among older US adults, uncontrolled BP is more frequent among those of Black vs White race and among women compared with men.18,19 Whether fragmented ambulatory health care differentially influences BP control by race and gender is unclear.

The aim of the current study was to determine the association of fragmented ambulatory health care with uncontrolled BP and aTRH among older US adults, overall and by race and gender. To accomplish this goal, we analyzed data from the REasons for Geographic And Racial Differences in Stroke (REGARDS) study linked to Medicare claims.

METHODS

Study Population

The REGARDS study enrolled a population-based cohort of 30,239 Black and White adults 45 years and older who were recruited from all 48 contiguous US states and the District of Columbia between January 2003 and October 2007. Black adults and adults residing in the Southeastern region of the United States were oversampled by design.20 Participants completed a computer-assisted telephone interview (CATI) and an in-home study visit at baseline and were followed through phone contacts to identify study outcomes.21-24 Study data from participants were linked to their claims in Medicare.25 Medicare is an insurance program that provides health care coverage to US adults 65 years and older and those younger than 65 years who have disabilities or end-stage renal disease (ESRD). The REGARDS study was approved by institutional review boards at the participating institutions, and all participants provided written informed consent.

We included REGARDS study participants who completed a second CATI and in-home study visit between May 2013 and November 2016 and (1) were 66 years or older; (2) had continuous Medicare fee-for-service coverage for the 365 days preceding the date of their second in-home study visit, inclusive (ie, the health care assessment period); (3) did not have ESRD,26 defined by an ESRD indicator in Medicare; (4) had at least 4 ambulatory care visits during their health care assessment period; and (5) had hypertension and were taking antihypertensive medication, defined by self-report in addition to having at least 1 antihypertensive medication class identified during a study medication inventory.

We excluded participants younger than 66 years on their second in-home study visit (ie, younger than 65 years when the health care assessment period started) because this population may have qualified for Medicare on the basis of disability and have ambulatory care patterns that are sufficiently distinct to merit being considered separately.27 Participants with Medicare Advantage do not have fee-for-service coverage and were excluded because claims to assess ambulatory health care fragmentation were not available. We restricted the analysis to participants with 4 or more ambulatory visits because using fewer visits could produce unreliable estimates of health care fragmentation.12,28 Only 159 (5%) of 3027 participants with hypertension were excluded because they were not taking antihypertensive medication. After these criteria were applied, 2868 REGARDS study participants taking antihypertensive medication were included in the current study (Figure).

Health Care Fragmentation

Health care fragmentation was assessed based on the number of ambulatory visits and ambulatory providers that each participant had during their health care assessment period (ie, the year preceding each participant’s second in-home study visit) using the reversed Bice-Boxerman Index (rBBI) (eAppendix 1 [eAppendices available at ajmc.com]).29 Ambulatory visits, including visits to federally qualified health care centers and rural clinics, were defined using a modified version of the definition by the National Committee for Quality Assurance, restricting the definition to evaluation-and-management visits in office or clinic settings.30 Ambulatory providers were defined by National Provider Identifier codes. The BBI captures the “dispersion” of care (the spread of care across multiple health care providers) and the “density” of care (the share of visits to each health care provider) received by patients.31 The rBBI score ranges from 0, all visits with the same provider or no health care fragmentation, to 1, each visit with a different provider or maximum health care fragmentation. Fragmented ambulatory care was defined by an rBBI score in the 75th percentile of the distribution in the overall study population or higher, informed by prior analyses.32-34 All participants included in the analysis had at least 4 ambulatory visits in their health care assessment period.

BP Measurements and Antihypertensive Medication Use

During each participant’s second in-home study visit, trained staff performed 2 BP measurements after a 5-minute rest using an aneroid sphygmomanometer, which were averaged for all analyses. Trained staff also conducted an inventory of medications taken in the previous 2 weeks, including antihypertensive medication classes (eAppendix 2). Following the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure, we defined uncontrolled BP as a systolic BP (SBP) of at least 140 mm Hg or a diastolic BP (DBP) of at least 90 mm Hg. aTRH was defined as taking 3 or more classes of antihypertensive medication with uncontrolled BP (aTRH with uncontrolled BP) or taking 4 or more classes of antihypertensive medication with controlled BP (aTRH with controlled BP).

Participant Characteristics

Participant characteristics that were defined using data collected at the REGARDS study baseline included gender, race, geographic region of residence, rural residence, and education. Participant characteristics that were defined using data collected at the second REGARDS study examination included age, annual household income, body mass index (BMI), current smoking, diabetes, chronic kidney disease (CKD), atrial fibrillation, total and high-density lipoprotein (HDL) cholesterol, statin use, and self-rated health. History of coronary heart disease (CHD), stroke, and heart failure were defined using data collected at baseline and the second in-home study visit, supplemented with adjudicated outcome events. We provide definitions for participant characteristics in eAppendix 3 and a figure detailing when data used for the current analysis were collected in eAppendix 4.

Statistical Analysis

We used descriptive statistics to estimate characteristics of participants overall and stratified by fragmented health care. We also calculated the prevalence of uncontrolled BP and aTRH overall and stratified by fragmented health care. We used 2 logistic regression models with progressive adjustment for covariates to calculate odds ratios (ORs) and 95% CIs for uncontrolled BP associated with fragmented health care. Model 1 included adjustment for age, gender, race, geographic region of residence, rural residence, annual household income, and education. Model 2 included adjustment for variables in model 1 and BMI, smoking, diabetes, CKD, history of CHD, stroke or heart failure, atrial fibrillation, total and HDL cholesterol, statin use, and self-rated health. We also calculated the prevalence and ORs for uncontrolled BP associated with quartiles of the rBBI distribution. The analysis described above was repeated for the outcome of aTRH. In a separate analysis, we divided the study population into 3 mutually exclusive groups—those with no aTRH, aTRH with controlled BP, and aTRH with uncontrolled BP—and used multinomial logistic regression models with adjustment for covariates as described above to calculate ORs and 95% CIs for aTRH with controlled and uncontrolled BP, separately, vs no aTRH associated with fragmented health care.

We repeated the analysis described above by race and gender subgroups, separately. Because Black adults have lower rBBI scores than White adults, we repeated the analysis among Black and White participants using race-specific 75th percentiles of the rBBI distribution to define fragmented health care.35 In exploratory analyses, we repeated the analyses described above excluding participants with an rBBI score of 0 or 1 and examined effect modification by education, income, and region of residence. We used chained equations to impute 10 data sets to keep participants with missing covariates in the regression models (eAppendix 5).36,37 For a secondary analysis, we repeated calculations described above using the definition of uncontrolled BP in the 2017 American College of Cardiology (ACC)/American Heart Association (AHA) BP guideline. Under this definition, uncontrolled BP was defined as an SBP of at least 130 mm Hg or a DBP of at least 80 mm Hg.38 Analyses were conducted using SAS version 9.4 (SAS Institute Inc).

RESULTS

Participant Characteristics and Health Care Utilization Patterns

Participants with fragmented health care were more likely to be White and had higher education and income vs those without fragmented health care (Table 1). Compared with participants without fragmented health care, those with fragmented health care had more ambulatory visits, saw more ambulatory providers, and had a lower percentage of visits with the most commonly seen provider during the health care assessment period (Table 2).

Uncontrolled BP and aTRH

Overall, 18.4% of participants had uncontrolled BP (Table 3). Also, 16.4% of participants had aTRH, including 9.0% who had aTRH with controlled BP and 7.4% who had aTRH with uncontrolled BP. After adjustment, there was no evidence of a difference in the likelihood of uncontrolled BP (model 2: OR, 1.10; 95% CI, 0.89-1.37) or aTRH (model 2: OR, 1.18; 95% CI, 0.93-1.49) between participants with vs without fragmented health care. Also, there was no evidence of an association between fragmented health care and aTRH with controlled BP (model 2: OR, 1.08; 95% CI, 0.80-1.47) or aTRH with uncontrolled BP (model 2: OR, 1.32; 95% CI, 0.96-1.81). There was no evidence of a difference in the likelihood of uncontrolled BP, aTRH, aTRH with controlled BP, or aTRH with uncontrolled BP across quartiles of the rBBI distribution (eAppendix 6). After excluding participants with rBBI scores of 0 or 1, the OR for aTRH with uncontrolled BP associated with health care fragmentation after adjustment for the variables in model 2 was 1.37 (95% CI, 1.00-1.89) (eAppendix 7).

Subgroup Analyses by Race and Gender

Among Black participants, there was no evidence of an association of fragmented health care with uncontrolled BP (model 2: OR, 1.21; 95% CI, 0.81-1.82). Fragmented health care was associated with a higher likelihood of aTRH (model 2: OR, 1.51; 95% CI, 1.01-2.26) (Table 4) and aTRH with uncontrolled BP (model 2: OR, 1.82; 95% CI, 1.07-3.11) among Black participants. There was no evidence of an association between fragmented health care and aTRH with controlled BP among Black participants. Among White participants, there was no evidence of an association of fragmented health care with uncontrolled BP, aTRH, or aTRH with controlled or uncontrolled BP, separately (Table 4). Results among Black and White participants using race-specific 75th percentiles of the rBBI distribution to define fragmented health care and excluding participants with rBBI scores of 0 or 1 are shown in eAppendices 8 and 9, respectively. Among Black participants, fragmented health care was associated with aTRH with controlled BP among those with less than high school education or annual household income less than $35,000, but not among those with a high school education or greater or annual household income of $35,000 or higher (eAppendices 10 and 11). There was no evidence of an effect modification by region of residence among Black participants (eAppendix 12) or by education, income, or region of residence among White participants (eAppendices 13 through 15).

There was no evidence of a difference in the association of fragmented health care with uncontrolled BP, aTRH, or aTRH with controlled or uncontrolled BP, separately, across gender subgroups (eAppendix 16). Results among men and women excluding participants with rBBI scores of 0 or 1 are shown in eAppendix 17. Fragmented health care was associated with aTRH and aTRH with controlled BP among women with less than high school education, but no association was present among those with a high school education or greater. Also, fragmented health care was associated with aTRH among women with annual household income less than $35,000, but no association was present among those with annual household income of $35,000 or more. There was no evidence of an effect modification by region of residence among women (eAppendices 18 through 20) or by education, income, or region of residence among men (eAppendices 21 through 23).

Secondary Analysis Following the 2017 ACC/AHA BP Guideline

Overall, 45.6% of participants had uncontrolled BP as defined in the 2017 ACC/AHA BP guideline. According to this guideline, 22.8% of participants had aTRH, including 6.0% with aTRH with controlled BP and 16.8% with aTRH with uncontrolled BP. There was no evidence of a difference in the likelihood of uncontrolled BP, aTRH, or aTRH with controlled or uncontrolled BP, separately, among participants with vs without fragmented health care (eAppendices 24 and 25). There was no evidence of an association of fragmented health care with uncontrolled BP, aTRH, or aTRH with controlled or uncontrolled BP, separately, among Black or White participants (eAppendices 26 and 27) or men or women (eAppendix 28).

DISCUSSION

In the current analysis of older adults taking antihypertensive medication, fragmented health care was not associated with uncontrolled BP or aTRH in the overall study population. Also, no association was present between fragmented health care and uncontrolled BP or aTRH among men and women and among White adults. However, fragmented health care was associated with a higher likelihood of aTRH with uncontrolled BP among Black adults.

Prior studies have suggested an association between fragmented health care and BP control.14,15 In an analysis of 5886 adults with hypertension in the Third National Health and Nutrition Examination Survey, participants who reported having a doctor or health care professional who they usually saw were more likely to have controlled BP (multivariable-adjusted OR, 2.29; 95% CI, 1.74-3.02).14 The higher likelihood of BP control associated with seeing 1 particular doctor or health professional was present among non-Hispanic White, non-Hispanic Black, and Mexican American participants. This prior analysis included participants who did not see a health care provider in the previous year. Therefore, some participants not seeing a particular health care provider may not have been receiving any health care, including antihypertensive medication, which may explain their lower likelihood of BP control. In the current study of 2868 adults taking antihypertensive medication who had 4 or more ambulatory visits in the preceding 365 days, the multivariable-adjusted OR for uncontrolled BP associated with health care fragmentation was 1.10 (95% CI, 0.89-1.37). Results from the current study suggest that fragmented health care is not associated with BP control among adults taking antihypertensive medication.

Black adults have lower health care fragmentation compared with White adults.35 Despite this, fragmented health care was associated with a higher likelihood of aTRH with uncontrolled BP among Black participants, but not among White participants. Several factors could explain the association between fragmented health care and aTRH with uncontrolled BP. If providers caring for the same patient are unaware of the complete medication regimen that the patient is taking, this could increase the likelihood that the patient is prescribed therapies that counteract their antihypertensive medication, necessitating the addition of more medications for BP control.11,16,17 Also, fragmented health care has been associated with lower medication adherence.39 Minimizing health care fragmentation may reduce the prevalence of aTRH among Black adults.

In an exploratory analysis, fragmented care was associated with a higher likelihood of aTRH with controlled BP among Black participants with less than high school education or annual household income less than $35,000. Fragmented health care was also associated with a higher likelihood of aTRH and aTRH with controlled BP among women with less than high school education and with a higher likelihood of aTRH among women with annual household income less than $35,000. Given the exploratory nature of these analyses, these results should be interpreted with caution and need to be confirmed in future studies.

There are multiple reasons why patients may have fragmented care, including patient-, provider-, organization-, and environment-level factors. However, most causes of fragmented care are unrelated to medical needs (eg, patient preference for geographic proximity, the widespread availability of urgent care centers).11 Therefore, it may be possible to reduce health care fragmentation without affecting the care that a patient is receiving. Among those with 12 ambulatory visits, to decrease fragmentation from an rBBI score of 0.9 (the mean among participants with fragmented care) to an rBBI score of 0.7 (the mean among participants without fragmented care), an intervention would need to increase the proportion of visits with the most frequently seen provider from 25% to 50%.40 Such a change may be feasible, but very few interventions have been designed to change fragmentation of care. One previous pilot study decreased fragmentation by using alerts in the electronic health record to inform providers if they were seeing patients with fragmented care in real time; however, this study was conducted in a single clinic among pediatric patients and may not be generalizable to adults.41 More interventions need to be designed and evaluated to address patient-, provider-, organization-, and environment-level drivers of fragmentation.

Strengths and Limitations

The current study has several strengths. BP was measured by trained staff following a standardized procedure. Participants’ health care fragmentation was assessed using a validated index and claims data.28,42 This study also has limitations. Results from the current study may not be generalizable to older adults without Medicare fee-for-service coverage. We used the definitions of uncontrolled BP and aTRH in the 2017 ACC/AHA BP guideline in the secondary analysis.38 However, this guideline was published after the data for the current study were collected. Future studies should examine the association of fragmented health care with BP control using data collected after this guideline was published. Lastly, we cannot exclude the possibility of reverse causation (ie, that participants with uncontrolled BP were more likely to be referred to more doctors). However, we attempted to minimize that possibility by assessing participants’ ambulatory care in the 365 days preceding their BP measurement.

CONCLUSIONS

No association was present between fragmented health care and uncontrolled BP or aTRH in the overall study population of older adults taking antihypertensive medication. However, fragmented health care was associated with a higher likelihood of aTRH with uncontrolled BP among Black participants. Results from the current study suggest that fragmented health care may be a risk factor for aTRH with uncontrolled BP among older Black adults.

Acknowledgments

The authors thank the other investigators, the staff, and the participants of the REGARDS study for their valuable contributions. A full list of participating REGARDS investigators and institutions can be found at http://www.regardsstudy.org.

Author Affiliations: University of Alabama at Birmingham (CLC, PM, LDC), Birmingham, AL; Weill Cornell Medicine (MMS, LMK), New York, NY.

Source of Funding: This REasons for Geographic And Racial Differences in Stroke (REGARDS) study is supported by cooperative agreement U01 NS041588 cofunded by the National Institute of Neurological Disorders and Stroke and the National Institute on Aging, National Institutes of Health, HHS. The ancillary study on health care fragmentation and cardiovascular outcomes was funded by the National Heart, Lung, and Blood Institute (R01 HL135199). The funding agencies did not have any role in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; or the preparation or approval of the manuscript. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This manuscript was reviewed and approved by the REGARDS Executive Committee prior to submission, ensuring adherence to standards for describing the REGARDS study.

Author Disclosures: Dr Safford receives funding from Amgen Inc for investigator-initiated research on large databases to understand patterns of lipid-lowering strategies. Dr Colantonio receives research support from Amgen Inc. Dr Kern is a consultant to Mathematica Inc. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (CLC, MMS, LDC, LMK); acquisition of data (LMK); analysis and interpretation of data (CLC, MMS, PM, LDC, LMK); drafting of the manuscript (CLC); critical revision of the manuscript for important intellectual content (PM, LDC, LMK); statistical analysis (CLC); obtaining funding (LMK); administrative, technical, or logistic support (PM, LMK); and supervision (MMS).

Address Correspondence to: Lisa M. Kern, MD, MPH, Department of Medicine, Weill Cornell Medicine, 420 E 70th St, Box 331, New York, NY 10021. Email: lmk2003@med.cornell.edu.

REFERENCES

1. Bundy JD, Li C, Stuchlik P, et al. Systolic blood pressure reduction and risk of cardiovascular disease and mortality: a systematic review and network meta-analysis. JAMA Cardiol. 2017;2(7):775-781. doi:10.1001/jamacardio.2017.1421

2. Brunström M, Carlberg B. Association of blood pressure lowering with mortality and cardiovascular disease across blood pressure levels: a systematic review and meta-analysis. JAMA Intern Med. 2018;178(1):28-36. doi:10.1001/jamainternmed.2017.6015

3. Ettehad D, Emdin CA, Kiran A, et al. Blood pressure lowering for prevention of cardiovascular disease and death: a systematic review and meta-analysis. Lancet. 2016;387(10022):957-967. doi:10.1016/S0140-6736(15)01225-8

4. Muntner P, Hardy ST, Fine LJ, et al. Trends in blood pressure control among US adults with hypertension, 1999-2000 to 2017-2018. JAMA. 2020;324(12):1190-1200. doi:10.1001/jama.2020.14545

5. Carey RM, Sakhuja S, Calhoun DA, Whelton PK, Muntner P. Prevalence of apparent treatment-resistant hypertension in the United States. Hypertension. 2019;73(2):424-431. doi:10.1161/HYPERTENSIONAHA.118.12191

6. Kaczmarski KR, Sozio SM, Chen J, Sang Y, Shafi T. Resistant hypertension and cardiovascular disease mortality in the US: results from the National Health and Nutrition Examination Survey (NHANES). BMC Nephrol. 2019;20(1):138. doi:10.1186/s12882-019-1315-0

7. Irvin MR, Booth JN III, Shimbo D, et al. Apparent treatment-resistant hypertension and risk for stroke, coronary heart disease, and all-cause mortality. J Am Soc Hypertens. 2014;8(6):405-413. doi:10.1016/j.jash.2014.03.003

8. Butler MJ, Tanner RM, Muntner P, et al. Adherence to antihypertensive medications and associations with blood pressure among African Americans with hypertension in the Jackson Heart Study. J Am Soc Hypertens. 2017;11(9):581-588.e5. doi:10.1016/j.jash.2017.06.011

9. Cherfan M, Vallée A, Kab S, et al. Unhealthy behaviors and risk of uncontrolled hypertension among treated individuals—the CONSTANCES population-based study. Sci Rep. 2020;10(1):1925. doi:10.1038/s41598-020-58685-1

10. Fagard RH, Cornelissen VA. Effect of exercise on blood pressure control in hypertensive patients. Eur J Cardiovasc Prev Rehabil. 2007;14(1):12-17. doi:10.1097/HJR.0b013e3280128bbb

11. Kern LM, Safford MM, Slavin MJ, et al. Patients’ and providers’ views on causes and consequences of healthcare fragmentation in the ambulatory setting: a qualitative study. J Gen Intern Med. 2019;34(6):899-907. doi:10.1007/s11606-019-04859-1

12. Kern LM, Seirup JK, Rajan M, Jawahar R, Miranda Y, Stuard SS. Extent of health care fragmentation in different payer populations: evidence from the Hudson Valley of New York. Popul Health Manag. 2018;22(2):138-143. doi:10.1089/pop.2018.0073

13. O’Malley AS, Reschovsky JD. Referral and consultation communication between primary care and specialist physicians: finding common ground. Arch Intern Med. 2011;171(1):56-65. doi:10.1001/archinternmed.2010.480

14. He J, Muntner P, Chen J, Roccella EJ, Streiffer RH, Whelton PK. Factors associated with hypertension control in the general population of the United States. Arch Intern Med. 2002;162(9):1051-1058. doi:10.1001/archinte.162.9.1051

15. Fisher M, Sloane P, Edwards L, Gamble G. Continuity of care and hypertension control in a university-based practice. Ethn Dis. 2007;17(4):693-698.

16. Elliott WJ. Drug interactions and drugs that affect blood pressure. J Clin Hypertens (Greenwich). 2006;8(10):731-737. doi:10.1111/j.1524-6175.2006.05939.x

17. Guo JY, Chou YJ, Pu C. Effect of continuity of care on drug-drug interactions. Med Care. 2017;55(8):744-751. doi:10.1097/MLR.0000000000000758

18. Daugherty SL, Masoudi FA, Ellis JL, et al. Age-dependent gender differences in hypertension management. J Hypertens. 2011;29(5):1005-1011. doi:10.1097/HJH.0b013e3283449512

19. Foti K, Wang D, Appel LJ, Selvin E. Hypertension awareness, treatment, and control in US adults: trends in the hypertension control cascade by population subgroup (National Health and Nutrition Examination Survey, 1999-2016). Am J Epidemiol. 2019;188(12):2165-2174. doi:10.1093/aje/kwz177

20. Howard VJ, Cushman M, Pulley L, et al. The REasons for Geographic And Racial Differences in Stroke study: objectives and design. Neuroepidemiology. 2005;25(3):135-143. doi:10.1159/000086678

21. Luepker RV, Apple FS, Christenson RH, et al; AHA Council on Epidemiology and Prevention; AHA Statistics Committee; World Heart Federation Council on Epidemiology and Prevention; European Society of Cardiology Working Group on Epidemiology and Prevention; Centers for Disease Control and Prevention; National Heart, Lung, and Blood Institute. Case definitions for acute coronary heart disease in epidemiology and clinical research studies: a statement from the AHA Council on Epidemiology and Prevention; AHA Statistics Committee; World Heart Federation Council on Epidemiology and Prevention; the European Society of Cardiology Working Group on Epidemiology and Prevention; Centers for Disease Control and Prevention; and the National Heart, Lung, and Blood Institute. Circulation. 2003;108(20):2543-2549. doi:10.1161/01.CIR.0000100560.46946.EA

22. Thygesen K, Alpert JS, White HD; Joint ESC/ACCF/AHA/WHF Task Force for the Redefinition of Myocardial Infarction. Universal definition of myocardial infarction. Circulation. 2007;116(22):2634-2653. doi:10.1161/CIRCULATIONAHA.107.187397

23. Prineas RJ, Crow RS, Zhang ZM. The Minnesota Code Manual of Electrocardiographic Findings. Springer Science & Business Media; 2009.

24. Stroke—1989. recommendations on stroke prevention, diagnosis, and therapy. report of the WHO Task Force on Stroke and Other Cerebrovascular Disorders. Stroke. 1989;20(10):1407-1431. doi:10.1161/01.str.20.10.1407

25. Xie F, Colantonio LD, Curtis JR, et al. Linkage of a population-based cohort with primary data collection to Medicare claims: the Reasons for Geographic and Racial Differences in Stroke study. Am J Epidemiol. 2016;184(7):532-544. doi:10.1093/aje/kww077

26. United States Renal Data System. Healthcare expenditures for persons with ESRD. In: United States Renal Data System. 2017 USRDS Annual Data Report: Epidemiology of Kidney Disease in the United States. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases; 2017:433-440.

27. Cubanski J, Neuman T, Damico A. Medicare’s role for people under age 65 with disabilities.Kaiser Family Foundation. August 12, 2016. Accessed March 25, 2020. https://www.kff.org/medicare/issue-brief/medicares-role-for-people-under-age-65-with-disabilities/

28. Nyweide DJ, Anthony DL, Bynum JPW, et al. Continuity of care and the risk of preventable hospitalization in older adults. JAMA Intern Med. 2013;173(20):1879-1885. doi:10.1001/jamainternmed.2013.10059

29. Bice TW, Boxerman SB. A quantitative measure of continuity of care. Med Care. 1977;15(4):347-349. doi:10.1097/00005650-197704000-00010

30. Kern LM, Seirup JK, Casalino LP, Safford MM. Healthcare fragmentation and the frequency of radiology and other diagnostic tests: a cross-sectional study. J Gen Intern Med. 2017;32(2):175-181. doi:10.1007/s11606-016-3883-z

31. Jee SH, Cabana MD. Indices for continuity of care: a systematic review of the literature. Med Care Res Rev. 2006;63(2):158-188. doi:10.1177/1077558705285294

32. Kern LM, Ringel JB, Rajan M, et al. Ambulatory care fragmentation and subsequent hospitalization: evidence from the REGARDS study. Med Care. 2020;59(4):334-340. doi:10.1097/MLR.0000000000001470

33. Kern LM, Ringel JB, Rajan M, et al. Ambulatory care fragmentation and incident stroke. J Am Heart Assoc. 2021;10(9):e019036. doi:10.1161/JAHA.120.019036

34. Kern LM, Rajan M, Ringel JB, et al. Healthcare fragmentation and incident acute coronary heart disease events: a cohort study. J Gen Intern Med. 2021;36(2):422-429. doi:10.1007/s11606-020-06305-z

35. Kern LM, Rajan M, Colantonio LD, et al. Differences in ambulatory care fragmentation by race. BMC Health Serv Res. 2021;21(1):154. doi:10.1186/s12913-021-06133-9

36. Sterne JAC, White IR, Carlin JB, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 2009;338:b2393. doi:10.1136/bmj.b2393

37. White IR, Royston P, Wood AM. Multiple imputation using chained equations: issues and guidance for practice. Stat Med. 2011;30(4):377-399. doi:10.1002/sim.4067

38. Whelton PK, Carey RM, Aronow WS, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension. 2018;71(6):e13-e115. doi:10.1161/HYP.0000000000000065

39. Chen CC, Tseng CH, Cheng SH. Continuity of care, medication adherence, and health care outcomes among patients with newly diagnosed type 2 diabetes: a longitudinal analysis. Med Care. 2013;51(3):231-237. doi:10.1097/MLR.0b013e31827da5b9

40. Kern LM, Seirup JK, Rajan M, Jawahar R, Stuard SS. Fragmented ambulatory care and subsequent emergency department visits and hospital admissions among Medicaid beneficiaries. Am J Manag Care. 2019;25(3):107-112.

41. Christakis DA, Wright JA. Can continuity of care be improved? results from a randomized pilot study. Ambul Pediatr. 2004;4(4):336-339. doi:10.1367/A03-166R.1

42. Pollack CE, Hussey PS, Rudin RS, Fox DS, Lai J, Schneider EC. Measuring care continuity: a comparison of claims-based methods. Med Care. 2016;54(5):e30-e34. doi:10.1097/MLR.0000000000000018