Data Sources

 
XII.2
The primary sources of data used in this publication were the Healthcare Cost and Utilization Project (HCUP) National Databases from the Agency for Healthcare Research and Quality (AHRQ), and the National Health Care Surveys (NHCS) family of provider-based surveys conducted by the National Center for Health Statistics (NCHS). Additional data was used from the United States Census Bureau on population counts; The Bureau of Labor Statistics on injuries; Centers for Disease Control (CDC) Web-based Injury Statistics Query and Reporting Systems (WISQARS)  on injuries; The SEER Cancer Statistics Review and the National Cancer Database on tumors. The Economic Cost section utilized the Medical Expenditures Panel Survey (MEPS), Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services, 1996-2011  SAS source: 008Table1_series.

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The small size of some databases precludes analysis at a detailed level. In most cases, ICD-9-CM codes were combined into major musculoskeletal disease classifications to provide sufficient sample size for reliable estimates.
 
Extensive use was also made of published studies in scientific and epidemiological journals as secondary sources of data.

It is important to recognize that no one source of data provides a complete view of the frequency and impact of a disease or condition. Interview surveys, for instance, generally underestimate the frequency of most musculoskeletal diseases. However, information obtained through the use of interviews is essential when assessing the impact of musculoskeletal disease on individuals, knowing that these individuals react differently to symptoms and pain. In addition, for some conditions, this may be the only means available to collect data on specific diseases.

In contrast, the use of objective methods such as physical examination, laboratory measurements, and radiographs for the detection and diagnosis of disease and injury is not dependent on the subjective reporting of symptoms. However, the objective evidence used to establish the presence or absence of a condition does not always correlate with reported symptoms. It is known that some individuals who report symptoms do not have evidence of disease upon examination and, conversely, some individuals who have objective evidence of disease do not experience symptoms. Thus, although objective measures are valuable tools, they may yield an incomplete picture of the impact of a given disease. This type of study is also more expensive, involves a smaller number of individuals, and may under-represent less frequently occurring disorders.

Data obtained from medical records are also subject to certain limitations. Many persons affected with certain musculoskeletal diseases do not seek medical care. Although records of visits to physicians and hospitals provide estimates of the volume of visits, these records do not include those who do not seek medical care. Therefore, data based on existing records will yield only a partial representation of how various musculoskeletal diseases affect the population.

Medical records do not necessarily indicate the underlying musculoskeletal condition. For instance, fractures at various sites, especially hip fractures, are a major consequence of osteoporosis. When admitted to the hospital, a fracture diagnosis is usually listed rather than osteoporosis. Medical records may also be subject to “upcoding” to maximize reimbursement and may overstate the frequency of more severe conditions.

Through the analysis and inclusion of data from a wide range of sources, each with its own strength and weaknesses, it is our goal to present an integrated and comprehensive understanding of the impact of musculoskeletal diseases on the United States population.

Edition: 

  • 2014

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