Part 1:
1.Choose a paper describing the development or validation of a measure of relevance in health disparities research (please give the full citation and/or upload the paper if that's possible).
Vigen, C, et al. Validation of self-reported comorbidity status of breast cancer patients with medical records: the California Breast Cancer Survivorship Consortium (CBCSC). Cancer Causes Control (2016) 27:391–401 DOI 10.1007/s10552-016-0715-8
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2.What was the definition of the construct?
The authors wanted to compare information self-reported patient information to electronic medical records for four common comorbidities (diabetes, hypertension, myocardial infarction, and other heart diseases). Using cohorts of patients that made up he California Breast Cancer Survivorship Consortium, they defined concordance date as the date that the comorbidity was asked in the questionnaire (usually the year of breast cancer diagnosis) and compared this to the presence or absence of a correlating ICD-9 code in the patient’s chart.
3.How did the authors provide evidence on the validity of the measure? Could you think of additional approaches to validating the measure?
The authors did not provide specific details regarding the validity of this measure, but they could have compared these measures to treatment and overall patient outcomes in this population. For instance, examining if those with high perceived co-morbidities fared worse than those with low perceived co-morbidities.
4.How did the authors provide evidence on the reliability of the measure? Could you think of additional approaches to evaluating the reliability of the measure?
The authors noted that the medical record is subject to error but is generally considered the most reliable source of patient comorbidity information, they did not explicitly provide evidence on the reliability of this measure. One way to test for reliability of this information could be by comparing ICD-9 lists of patients who receive care in different facilities. This might be challenging and only represent a small fraction of the population, but could be interesting nonetheless.
5.Describe the implications of a lack of measurement validity or reliability for future research applications.
While this study did not explicitly provide measurement validity or reliability, I believe comparing patient-level data to EHR data will continue to be applied to medical research based on historical context and the fact that despite its shortcomings, the electronic medical record is the sole source for individual patient-level health care data at this time. I believe studies such as this are important as they reveal the gaps between physician and patient concordance regarding medical conditions and will hopefully encourage providers to communicate more effectively with patients.
Part 2:
1.Find a paper describing a health disparity (please give the full citation or, even better, upload the paper so everyone else can look at it too)
Singh, JA, et al. Racial disparities in knee and hip total joint arthroplasty: an 18-year analysis of national Medicare data. Ann Rheum Dis 2014;73:2107–2115. doi:10.1136/annrheumdis-2013-203494
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2.Summarize the construct and measurement of the dimension of disparity (e.g., racial inequalities, SES inequalities?) and the outcome measured (e.g., self-rated health).
The authors sought to identify differences in usage of total knee arthroplasty (TKA) / total hip arthroplasty (THA) and post-surgical outcomes between self-identified African Americans and non-Hispanic Caucasians.
3.What is the evidence for the validity and reliability of the measures?
The most commonly used categories for race are those defined by the Office of Management and Budget (OMB). This includes five race categories (Black or African American, White, Asian, American Indian or Alaska Native, and Native Hawaiian or Other Pacific Islander) as well as one ethnicity choice (Hispanic/Latino or non-Hispanic/Latino). There can be challenges in using this construct even if through self-identification, as OMB allows selection of multiple races and there is debate about considering race separately from ethnicity.
4.What is the reference category used for the disparity measure (ie, who is the comparison group)? Why does this reference category make sense (or not) for this research question?
The comparison group was Caucasians which makes sense for this research question.
5.How is the disparity quantified or measured? Is this an absolute or relative measure or are both provided? Describe which type of measure you would prefer for this research area, or, if both, why.
TKA/THA usage and related outcomes (hospital stay, 30-day mortality, 30-day readmission, 30-day composite score, discharged to home, etc.) were all reported in absolute terms. The authors also reported usage in relative terms, which is also a useful way to see the data.