Concept: Arthritis - Measuring Prevalence

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Concept Description

Last Updated: 2020-05-15

Definition of Arthritis
    Arthritis is a group of conditions that affect the health of the bone joints in the body. One in three adult Americans suffer from some form of arthritis and the disease affects about twice as many women as men. Arthritic diseases include rheumatoid arthritis (RA) and psoriatic arthritis, which are autoimmune diseases; septic arthritis, caused by joint infection; and the more common osteoarthritis (OA), or degenerative joint disease. Arthritis can be caused from strains and injuries caused by repetitive motion, sports, overexertion, and falls. Unlike the autoimmune diseases, OA largely affects older people and results from the degeneration of joint cartilage. See MedlinePlus® - Health Topics - Arthritis for more information.
Literature Review
    A number of studies have used administrative data to measure the prevalence of arthritis in the population. Medical services/physician claims were primarily used to identify cases of arthritis, although the Powell et al. (2003), Rector et al. (2004), and Singh et al. (2004) studies also identified cases of RA using prescriptions for disease-modifying anti-rheumatic drugs (DMARDS). A wide variety of other administrative sources have been used to identify disease cases, including hospital separations, emergency department records, and laboratory results. While some studies suggest that administrative data can validly be used to identify individuals with arthritis, there is a lack of consistency in the observations.

    The majority of the studies retrieved through a review of the literature used ICD-9-CM codes 714 to identify RA cases and 715 to define OA cases, although a few used more specific sets of four- or five-digit codes for each of these forms of arthritis. For all forms of arthritis, a wide variety of ICD-9-CM codes were adopted in previous research and procedure codes were also used in some studies (i.e., Katz et al., 1997).

    Table 1 summarizes seven studies, published prior to 2006, that used administrative data to identify cases with all forms of arthritis, RA or OA.
Manitoba Arthritis Algorithms
    This section describes the arthritis algorithms used in MCHP studies over time.
1. Lix et al. (2006)
    In the Defining and Validating Chronic Diseases: An Administrative Data Approach deliverable by Lix et al. (2006) the following ICD-9-CM codes were used to define Arthritis cases:

    • 714: rheumatoid arthritis
    • 715: osteoarthritis
    • 446, 710: connective tissue disorders (446 = Polyarteritis nodosa and allied conditions; 710 = Diffuse diseases of connective tissue)
    • 720: ankylosing spondylitis
    • 274: gout
    • 711-713, 716, 717, 718, 719, 721, 725-729, 739: other arthritis and related conditions.

    The codes selected for all forms of arthritis are the same as those adopted in a national report on arthritis prepared by Health Canada (Badley & DesMeules, 2003).

    Pharmacological treatment of RA is primarily by: (1) DMARDS, which include xenobiotic agents and biologic agents, (2) anti-inflammatory agents including glucocorticoids and non-steroidal anti-inflammatory agents (NSAIDs), and (3) analgesics such as acetaminophen, opiates, and topical agents. Pharmacological treatment of OA is primarily by anti-inflammatory agents and analgesics. The following process was used to select the prescription drugs for inclusion in this research. A set of relevant ATC codes was identified through the literature search and consultations with experts (i.e., rheumatologist and pharmaco-epidemiological researchers). Then, all of the DINs associated with these ATC codes were identified from the MCHP Master Formulary. Since the list of drugs was very extensive, it was reviewed again with the experts to ensure that no relevant drugs had been missed. Table 2 contains a complete list of the fourth- or fifth-level ATC codes that were selected for the research, and the generic drug names associated with these codes.

    In Lix et al. (2006), 16 algorithms were investigated for all forms of arthritis, RA, and OA. These algorithms are based on up to five years of administrative data because Powell et al. (2003) observed that multiple years of data are required to obtain a valid algorithm. None of the arthritis algorithms relied solely on the prescription drug data for the identification of arthritis cases. That is, at least one contact in hospital discharge abstracts data or medical services/physician claims data had to occur in combination with two or more prescription drug records for an individual to be classified as a disease case. This requirement was implemented because there are no unique marker drugs for arthritis. Many of the prescription drugs, such as NSAIDs are used to treat several other diseases. A possible exception, as noted above, is DMARDs.

    Tables 3, 4, and 5 report sensitivity, specificity, kappa, Youden's index, PPV ( positive predicted value) and NPV ( negative predicted value) for each of the investigated algorithms. The validation was conducted using self-report of arthritis from the Canadian Community Health Survey cycle 1.1. There were 1,344 adult survey respondents who reported having any form of arthritis, 459 respondents who reported having RA, and 601 respondents who reported having OA.

    Calculating Population-based Prevalence Rates
    The population registry was used by Lix et al. (2006) to define population cohorts to derive numerator and denominator data for calculating crude provincial prevalence estimates for each algorithm from 1998/99 to 2002/03. (Note: Lix et al. (2006) estimates are based on the population 19 years of age and older).
2. Lix et al. (2008)
    The report Defining and Validating Chronic Disease: An Administrative Data Approach. An Update with ICD-10-CA by Lix et al. (2008) provided an update to the 2006 study. 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 evaluation cohort consisted of 5,099 adults 19+ years of age.

    The following ICD-10-CA codes were used to define arthritis in administrative hospital separation data from April 1, 2004 to March 31, 2006:

    • M05-M06: rheumatoid arthritis
    • M15-M19: osteoarthritis
    • M07, M10, M11-M14, M30-M36: other inflammatory and connective tissue diseases
    • M00-M03, M20-M25, M65-M79: Other arthritis and rheumatic conditions

    Table 6, 7, and 8 contain the estimates of agreement (?), sensitivity, specificity, Youden's Index, PPV (positive predictive value) and NPV (negative predictive value) for all forms of arthritis algorithms, for rheumatoid arthritis algorithms, and for osteoarthritis algorithms, respectively.

    Discussion of the validation results for arthritis can be found in the full report: Chapter 3: Arthritis

    Calculating Population-based Prevalence Rates
    Crude provincial prevalence estimates for the 16 algorithms for all forms of arthritis, rheumatoid arthritis and osteoarthritis are reported in Table 9 .

    Discussion of the prevalence rates for arthritis can be found in the full report: Chapter 3: Arthritis
3. Finlayson et al. (2010)
    In The Additional Cost of Chronic Disease in Manitoba deliverable by Finlayson et al. (2010) they defined arthritis as one or more hospitalizations OR two or more physician visits over a five-year time period for those aged 19+ where the events are coded with an ICD code representing arthritis.

    For more information, please read the section titled Arthritis in this report.
4. Martens et al. (2010)
    In the Profile of Metis Health Status and Healthcare Utilization in Manitoba: A Population-Based Study deliverable by Martens et al. (2010) they defined arthritis for all Manitoba residents aged 19 and older over a five-year period as:

    • one or more hospitalizations with a diagnosis of arthritis: ICD-9-CM codes 274, 446, 710-721, 725-729, 739; ICD-10-CA codes M00-M03, M05-M07, M10-M25, M30-M36, M65-M79; OR
    • two or more physician visits with a diagnosis of arthritis (ICD-9-CM codes as above); OR
    • one physician visit with a diagnosis of arthritis (ICD-9-CM codes as above) and two or more prescriptions for medications to treat arthritis (see medication list used in the 2010 report).

    For more information, please read section 5.2 Arthritis in this report.
5. Chartier et al. (2012), Fransoo et al. (2013) and Fransoo et al. (2019)
6. Martens et al. (2015)
    In The Cost of Smoking: A Manitoba Study deliverable by Martens et al. (2015), they used administrative health data and self-reported responses from three surveys - the Canadian Community Health Survey (CCHS), the National Population Health Survey (NPHS), and the Manitoba Heart Health Survey (MHHS) - to measure the weighted crude prevalence of arthritis for survey respondents aged 12 and older in the two years prior to the survey date.

    Arthritis was defined using the same algorithm (data sources and ICD codes) listed above in Martens et al. (2010). The list of medications used in this definition is available through the following link: List of Drugs Used to Treat Arthritis to this report.

    Drug Program Information Network (DPIN) data were not available for respondents of the MHHS, so a different algorithm was chosen with similar sensitivity and specificity: one or more hospitalizations or two or more physician visits in the three years prior to survey date.

    In the survey data, a question about arthritis was asked in the NPHS and nearly all the CCHS waves with the exception of CCHS 2.2. Respondents were asked, "Do you have arthritis or rheumatism excluding fibromyalgia?" ("Or rheumatism" was dropped from the question after 2005.) Possible responses include "yes", "no" or "don't know."

    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 arthritis from survey (self-reported) and administrative data found in this report.
Cautions
    NOTE: The list of medications used to treat diseases change all the time: new drugs are added, drugs are taken off the market, etc. Sometimes, the lists of drugs are research specific. The medication lists presented in this concept represent a starting point to identifying the medications used to treat arthritis. It is always suggested to consult with a clinician or pharmacist about the list of medications that will be used in your study.

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Related terms 

References 

  • 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. [Summary] [Full Report] (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. [Summary] [Full Report] (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. [Summary] [Full Report] [Data extras] (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. [Summary] [Full Report] [Data extras] [Errata] (View)
  • Harrold LR, Yood RA, Andrade SE, Reed JI, Cernieux J, Straus W, Weeks M, Lewis B, Gurwitz JH. Evaluating the predictive value of osteoarthritis diagnoses in an administrative database. Arthritis and Rheumatism 2000;43(8):1881-1885. [Abstract] (View)
  • Katz JN, Barrett J, Liang MH, Bacon AM, Kaplan H, Kieval RI, Lindsey SM, Roberts WN, Sheff DM, Spencer RT, Weaver AL, Baron JA. Sensitivity and positive predictive value of medicare part B physician claims for rheumatologic diagnoses and procedures. Arthritis Rheum 1997;40(9):1594-1600. [Abstract] (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. [Summary] [Full Report] (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. [Full Report] (View)
  • Losina E, Barrett J, Baron JA, Katz JN. Accuracy of medicare claims data for rheumatologic diagnoses in total hip replacement recipients. J Clin Epidemiol 2003;56(6):515-519. [Abstract] (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. [Summary] [Full Report] [Errata] (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. [Summary] [Full Report] [Data extras] [Errata] (View)
  • Powell KE, Diseker RA, 3rd, Presley RJ, Tolsma D, Harris S, Mertz KJ, Viel K, Conn DL, McClellan W. Administrative data as a tool for arthritis surveillance: Estimating prevalence and utilization of services. J Public Health Manag Pract 2003;9(4):291-298. [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)
  • Ruof J, Hulsemann JL, Mittendorf T, Handelmann S, Aultman R, der Schulenburg JM, Zeidler H, Merkesdal S. Comparison of estimated medical costs among patients who are defined as having rheumatoid arthritis using three different standards. Eur J Health Econ 2004;5(1):64-69. [Abstract] (View)
  • Singh JA, Holmgren AR, Noorbaloochi S. Accuracy of veterans administration databases for a diagnosis of rheumatoid arthritis. Arthritis Rheum 2004;51(6):952-957. [Abstract] (View)

Keywords 

  • chronic disease
  • Health Measures
  • Validation