Max Rady College of Medicine

Concept: Hypertension - Measuring Prevalence

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Concept Description

Last Updated: 2020-04-28

Introduction

    This concept contains information on how hypertension has been defined in MCHP research in order to measure the prevalence of this medical condition. This includes the data sources that are used, the ICD codes that define this condition, and the antihypertensive prescription drugs that are used to treat hypertension.

    Hypertension is a disorder characterized by high blood pressure; generally this includes systolic blood pressure consistently higher than 140, or diastolic blood pressure consistently over 90. "Essential" hypertension has no identifiable cause. It may have genetic factors and environmental factors, such as salt intake or others. Essential hypertension comprises over 95% of all hypertension. "Secondary" hypertension is hypertension caused by another disorder.

Literature Review

    A number of studies have used administrative data to measure the prevalence of hypertension. Both narrow and broader ranges of ICD-9-CM codes have been used in previous research.

    Table 1 summarizes six studies, published prior to 2006, that used administrative data to ascertain cases of hypertension.

Manitoba Hypertension Algorithms

1. Robinson et al. (1997)

    In Robinson et al. (1997) , the following ICD-9-CM codes were used to define hypertension cases:
    • 401: Essential hypertension
    • 402: Hypertensive renal disease
    • 403: Hypertensive renal disease
    • 404: Hypertensive heart and renal disease
    • 405: Secondary hypertension
    • 642: Hypertension in pregnancy
    • 362.11: Hypertensive retinopathy
    • 416.0: Primary pulmonary hypertension
    • 437.2: Hypertensive encephalopathy
    • 796.2: Elevated blood pressure without hypertension.

    Robinson used both hospital and physician data to identify hypertension cases, and investigated the effect of the change in the number of years of data and the number of required diagnoses on agreement between administrative data and Manitoba Heart Health Survey data. The respondents were 18 to 74 years of age.
2. Muhajarine et al. (1997)
    In Muhajarine et al. (1997) , the following ICD-9-CM codes were used to define hypertension cases:
    • 401: Essential hypertension
    • 402: Hypertensive renal disease

    Muhajarine used physician claims data from Manitoba Health to identify hypertension cases. The estimates were based on the population aged 18 to 74 years.

3. Lix et al. (2006)

    In Lix et al. (2006) , preliminary assessment of administrative data for 2002/03 revealed that 99.5% of individuals who had a hospital separation or physician claim with an ICD-9-CM code in the range 401 to 405 were assigned the single ICD-9-CM code of 401. Thus, a single ICD-9-CM code, 401, was used to define hypertensive cases from Manitoba's hospital and physician data. Based on the literature review and consultations with pharmacists and clinical experts, five second-level Anatomical Therapeutic Chemical (ATC) codes were used to identify cases from Drug Program Information Network (DPIN) Data. These were C02 (anti-hypertensives), C03 (diuretics), C07 (beta-blockers), C08 (calcium channel blockers), and C09 (inhibitors). All of the Drug Identification Numbers (DINs) associated with these ATC codes were selected from the MCHP Master Formulary.

    Eighteen hypertension algorithms were evaluated. These algorithms were based on one, two, or three years of administrative data. Some of the algorithms were based solely on the physician data, others relied on both the hospital and physician data, and the remainder combined all three data sources. Five years of data were not used to define disease cases because no previous studies used this many years of data to define hypertension algorithms. The algorithms varied in terms of the number of occurrences of a diagnostic code in the physician claims and the number of occurrences of a medication code in prescription drug data. Table 2 reports sensitivity, specificity, kappa, Youden's index, PPV(positive predicted value) and NPV (negative predicted value) for each of the investigated algorithms.

4. Lix et al. (2008)

    Lix et al. (2008) provided an update to the 2006 study with a report titled Defining and Validating Chronic Disease: An Administrative Data Approach. An Update with ICD-10-CA. The purpose of the 2008 report is to examine the validity of administrative data for monitoring the prevalence of chronic disease in Manitoba. Specific objectives are:

    • Report relevant ICD-10-CA codes for ascertaining cases of chronic disease in administrative health data;
    • Evaluate the validity of multiple algorithms for identifying disease cases from Manitoba administrative data.

    The 2008 report uses the same methods and algorithms as described in the 2006 report, with the following modifications:

    • ICD-10-CA codes were used to define specific chronic diseases from hospital separation data, beginning April 1, 2004. This is due to a change in coding systems used in Manitoba hospitals. The same ICD-9-CM codes identified in the 2006 report were used to identify hospital cases prior to April 1, 2004.
    • data from the Canadian Community Health Survey (CCHS), cycle 3.1, collected from January 2005 to January 2006 were used to evaluate the validity of the administrative data. The cohort consisted of 5,099 adults 19+ years of age.
    • additional algorithms looking at different combinations of hospital cases, or physician claims and/or prescriptions over one, two and three years, as well as additional algorithms using five years of data.

    In this project, ICD-10-CA code I10 - essential hypertension was used to define hypertension in administrative hospital separation data from April 1, 2004 to March 31, 2006.

    Table 3 contains the estimates of agreement kappa(κ), sensitivity, specificity, Youden's Index, PPV (positive predictive value) and NPV (negative predictive value) for each of the 28 algorithms that were investigated for hypertension.

    Discussion of the validation results for hypertension can be found in the full report: Chapter 7: Hypertension

5. Fransoo et al. (2009), Martens et al. (2010), Fransoo et al. (2011), Chartier et al. (2012), and Fransoo et al. (2013)

Further Information

6. Finlayson et al. (2010)

    Finlayson et al. (2010) define hypertension as one or more hospitalizations OR one or more physician visits OR two or more prescriptions over a two-year time period for those aged 19+ where the events are coded with an ICD code representing hypertension or a prescription is dispensed for a hypertension medication.

7. Heaman et al. (2012)

    In Heaman et al. (2012), a woman was considered to have maternal hypertension if in the one year prior to giving birth she had:

    • at least one physician visit or one hospitalization (ICD-9-CM codes 401-405 or ICD-10-CA codes I10-I13, I15); OR
    • at least one physician visit or one hospitalization in the gestation period (ICD-9-CM code 642 or ICD-10-CA codes O10-O16); OR
    • two or more prescriptions for hypertension drugs:
      • Anti-hypertensives (C02AB01, C02AB02, C02AC01, C02CA04, C02CA05, C02DB02, C02DC01, C02KX01, C02LA01, C02LB01, G04CA03);
      • Diuretics (C03AA03, C03BA04, C03BA11, C03CA01, C03CA02, C03CC01, C03DA01, C03DB01, C03DB02, C03EA01);
      • Beta Blocking Agents (C07AA02, C07AA03, C07AA05, C07AA06, C07AA12, C07AB02, C07AB03, C07AB04, C07AB07, C07AG01, C07BA05, C07BA06, C07CA03, C07CB03);
      • Calcium Channel Blockers (C08CA01, C08CA02, C08CA04, C08CA05, C08CA06, C08DA01, C08DB01);
      • Agents Acting on the Renin-Angiotensin System (C09AA01, C09AA02, C09AA03, C09AA04, C09AA05, C09AA06, C09AA07, C09AA08, C09AA09, C09AA10, C09BA02, C09BA03, C09BA04, C09BA06, C09BA08, C09CA01, C09CA02, C09CA03, C09CA04, C09CA06, C09CA07, C09DA01, C09DA02, C09DA03, C09DA04, C09DA06, C09DA07)

8. Katz et al. (2013)

    In Katz et al. (2013) they investigated the patterns of ambulatory care services (see Ambulatory Visits - Physician) delivered by primary care and specialist physicians to Manitobans with one of six chronic conditions, including hypertension. This study focused on Manitobans aged 19 and older over a three-year period (plus one-year follow-up) and measured how these patterns of care impact on the quality of care received. They defined hypertension as:

    • at least one hospital diagnosis: hypertensive diseases (ICD10-CA codes: I10-I15) in three years OR
    • at least two ambulatory visit diagnoses: hypertensive diseases (ICD-9-CM codes: 401-405) in three years OR
    • at least two prescriptions for any of the following: anti-hypertensives (ATC codes: C02AB01, C02DC01), diuretics (ATC codes: C03BA11, C03DB02), beta blocking agents (ATC codes: C07AA12, C07AB03, C07CA03), calcium channel blocker (ATC codes: C08DA01), angiotensin converting enzyme inhibitors (ACEI; ATC codes: C09AA05, C09BA02), angiotensin II antagonists (ATC codes: C09CA01, C09DA01) in three years.

9. Martens et al. (2015)

    In The Cost of Smoking: A Manitoba Study deliverable by Martens et al. (2015) they calculated hypertension prevalence rates two ways; one using administrative data and the other using self-reported survey data. Using the administrative data, the weighted crude prevalence of hypertension was calculated for survey respondents aged 12 and older in the two years before their survey date. Hypertension was defined by one of the following conditions:

    • one or more hospitalizations with a diagnosis of hypertension, ICD-9-CM codes 401-405; ICD-10-CA codes I10-I13, I15; or
    • two or more physician visits with a diagnosis of hypertension (ICD-9-CM codes as above).

    Using the survey data, a question about hypertension was asked in all the survey waves. In the Manitoba Heart Health Survey (MHHS) respondents were asked, "Have you been told by a doctor or nurse that you have high blood pressure?" Possible responses include "yes", "no", or "not sure". In the National Population Health Survey (NPHS) and Canadian Community Health Survey (CCHS) respondents were asked, "Do you have high blood pressure?" Possible responses include "yes", "no", or "don't know". The weighted crude self-reported prevalence of hypertension was calculated for survey respondents aged 12 and older as the percentage of respondents who answered "yes" out of all respondents who gave a valid answer. Respondents who answered "don't know" or "not sure", and those with missing or invalid data were excluded from the prevalence calculation.

    For more information, Table 4.8 Chronic Diseases of Estimated-Population-Based Sample* at Time of Survey by Smoking Status Categories lists the prevalence rates of hypertension from survey (self-reported) and administrative data found in this report.

10. Chartier et al. (2015)

    In the Care of Manitobans Living with Chronic Kidney Disease deliverable by Chartier et al. (2015) they investigated the prevalence and relative risk of hypertension as a comorbidity to chronic kidney disease (CKD) and end stage kidney disease (ESKD). Hypertension was defined as Manitoba residents receiving one of the following diagnoses or prescriptions in the one-year fiscal period 2011/12, using the following algorithm:

    • Age groups:
      • Children: 0-17 years old
      • Adults: 18 years and older

    • Codes and Conditions:

      • one or more inpatient hospitalizations for hypertensive disease (ICD-9-CM: 401-405 OR ICD-10-CA: I10-I13, I15); or
      • one or more physician claims for hypertensive disease (prefix=7, ICD-9-CM: 401-405); or
      • one or more prescriptions for antihypertensive drugs, diuretics, beta blocking agents, calcium channel blockers, agents acting on the renin-angiotensin system, atorvastatin, or terazosin with the following ATC codes: C02AB01, C02AB02, C02AC01, C02CA04, C02CA05, C02DB02, C02DC01, C02LA01, C02LB01, C03AA03, C03BA04, C03BA11, C03CA01, C03CA02, C03CC01, C03DA01, C03DB01, C03DB02, C03EA01, C07AA02, C07AA03, C07AA05, C07AA06, C07AA12, C07AB02, C07AB03, C07AB04, C07AB07, C07AG01, C07BA05, C07BA06, C07CA03, C07CB03, C08CA01, C08CA02, C08CA04, C08CA05, C08CA06, C08DA01, C08DB01, C09AA01, C09AA02, C09AA03, C09AA04, C09AA05, C09AA06, C09AA07, C09AA08, C09AA09, C09AA10, C09BA02, C09BA03, C09BA04, C09BA06, C09BA08, C09BB10, C09CA01, C09CA02, C09CA03, C09CA04, C09CA06, C09CA07, C09CA08, C09DA01, C09DA02, C09DA03, C09DA04, C09DA06, C09DA07, C09DA08, C09DB02, C09XA02, C09XA52, C10BX03, G04CA03

      • Drug Exclusions:
        • Generic name spironolactone
        • Drug Identification Numbers (DINs): 00028606, 00180408, 00285455, 00594377, 00613215, 00613223, 00613231, 00657182

    For more information on prevalence and relative risk of hypertension in adults, see:

    For more information on prevalence and relative risk of hypertension in children, see:

11. Fransoo et al. (2019)

Calculating Population-based Prevalence Rates

    Robinson et al. (1997) did not calculate prevalence estimates using their validated algorithms.

    Lix et al. (2006) calculated crude prevalence estimates for each of the investigated algorithms. These estimates were developed for the period 1995/96 to 2002/03, for the population 19 years of age and older. Only crude prevalence estimates were reported.

    From Lix et al. (2008), Table 4 reports the crude provincial prevalence estimates for the 28 hypertension algorithms investigated. Discussion of the prevalence rates for hypertension can be found in Chapter 7 of the full report, available through a link from the Lix et al. (2008) reference.

Cautions

    NOTE: Lists of drugs to treat diseases change all the time: new drugs are added, drugs are taken off the market, etc. Also it is very research specific. The medication lists presented in this concept represent a starting point to identifying the medications used to treat hypertension. It is always preferable to consult a clinician or pharmacist.

Related concepts 

Related terms 

References 

  • Borzecki AM, Wong AT, Hickey ED, Ash AS, Berlowitz DR. Identifying hypertension-related comorbidities from administrative data: What's the optimal approach? American Journal of Medical Quality 2004;19(5):201-206. [Abstract] (View)
  • Chartier M, Dart A, Tangri N, Komenda P, Walld R, Bogdanovic B, Burchill C, Koseva I, McGowan K-L, Rajotte L. Care of Manitobans Living with Chronic Kidney Disease. Winnipeg, MB: Manitoba Centre for Health Policy, 2015. [Report] [Summary] [Updates and Errata] [Additional Materials] (View)
  • Chartier M, Finlayson G, Prior H, McGowan K, Chen H, de Rocquigny J, Walld R, Gousseau M. Health and Healthcare Utilization of Francophones in Manitoba. Winnipeg, MB: Manitoba Centre for Health Policy, 2012. [Report] [Summary] (View)
  • Finlayson G, Ekuma O, Yogendran M, Burland E, Forget E. The Additional Cost of Chronic Disease in Manitoba. Winnipeg, MB: Manitoba Centre for Health Policy, 2010. [Report] [Summary] (View)
  • Fransoo R, Martens P, Prior H, Chateau D, McDougall C, Schultz J, McGowan K, Soodeen R, Bailly A. Adult Obesity in Manitoba: Prevalence, Associations, and Outcomes. Winnipeg, MB: Manitoba Centre for Health Policy, 2011. [Report] [Summary] (View)
  • Fransoo R, Martens P, Burland E, The Need to Know Team, Prior H, Burchill C. Manitoba RHA Indicators Atlas 2009. Winnipeg, MB: Manitoba Centre for Health Policy, 2009. [Report] [Summary] [Additional Materials] (View)
  • Fransoo R, Martens P, The Need to Know Team, Prior H, Burchill C, Koseva I, Bailly A, Allegro E. The 2013 RHA Indicators Atlas. Winnipeg, MB: Manitoba Centre for Health Policy, 2013. [Report] [Summary] [Additional Materials] (View)
  • Fransoo R, Mahar A, The Need to Know Team, Anderson A, Prior H, Koseva I, McCulloch S, Jarmasz J, Burchill S. The 2019 RHA Indicators Atlas. Winnipeg, MB: Manitoba Centre for Health Policy, 2019. [Report] [Summary] [Updates and Errata] [Additional Materials] (View)
  • Heaman M, Kingston D, Helewa M, Brownell M, Derksen S, Bogdanovic B, McGowan K, Bailly A. Perinatal Services and Outcomes in Manitoba. Winnipeg, MB: Manitoba Centre for Health Policy, 2012. [Report] [Summary] [Updates and Errata] (View)
  • Katz A, Martens P, Chateau D, Bogdanovic B, Koseva I, McDougall C, Boriskewich E. Understanding the Health System Use of Ambulatory Care Patients. Winnipeg, MB: Manitoba Centre for Health Policy, 2013. [Report] [Summary] (View)
  • Lix L, Yogendran M, Burchill C, Metge C, McKeen N, Moore D, Bond R. Defining and Validating Chronic Diseases: An Administrative Data Approach. Winnipeg, MB: Manitoba Centre for Health Policy, 2006. [Report] [Summary] (View)
  • Lix L, Yogendran M, Mann J. Defining and Validating Chronic Diseases: An Administrative Data Approach. An Update with ICD-10-CA. Winnipeg, MB: Manitoba Centre for Health Policy, University of Manitoba, 2008. [Report] (View)
  • Martens P, Nickel N, Forget E, Lix L, Turner D, Prior H, Walld R, Soodeen RA, Rajotte L, Ekuma O. The Cost of Smoking: A Manitoba Study. Winnipeg, MB: Manitoba Centre for Health Policy, 2015. [Report] [Summary] [Updates and Errata] [Additional Materials] (View)
  • Martens PJ, Bartlett J, Burland E, Prior H, Burchill C, Huq S, Romphf L, Sanguins J, Carter S, Bailly A. Profile of Metis Health Status and Healthcare Utilization in Manitoba: A Population-Based Study. Winnipeg, MB: Manitoba Centre for Health Policy, 2010. [Report] [Summary] [Updates and Errata] [Additional Materials] (View)
  • Muhajarine N, Mustard C, Roos LL, Young TK, Gelskey DE. Comparison of survey and physician claims data for detecting hypertension. J Clin Epidemiol 1997;50(6):711-718. [Abstract] (View)
  • Quam L, Ellis LB, Venus P, Clouse J, Taylor CG, Leatherman S. Using claims data for epidemiologic research. The concordance of claims-based criteria with the medical record and patient survey for identifying a hypertensive population. Med Care 1993;31(6):498-507. [Abstract] (View)
  • Rector TS, Wickstrom SL, Shah M, Thomas Greenlee N, Rheault P, Rogowski J, Freedman V, Adams J, Escarce JJ. Specificity and sensitivity of claims-based algorithms for identifying members of medicare plus choice health plans that have chronic medical conditions. Health Services Research 2004;39(6):1839-1857. [Abstract] (View)
  • Robinson JR, Young TK, Roos LL, Gelskey DE. Estimating the burden of disease: Comparing administrative data and self-reports. Med Care 1997;35(9):932-947. [Abstract] (View)
  • Wilchesky M, Tamblyn RM, Huang A. Validation of diagnostic codes within medical services claims. Journal of Clinical Epidemiology 2004;57(2):131-141. [Abstract] (View)

Keywords 

  • Blood Pressure
  • cardiovascular disease
  • chronic disease
  • Health Measures
  • renal disease
  • Validation


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