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).
Callaghan, W. M., Creanga, A. A., & Kuklina, E. V. (2012). Severe Maternal Morbidity Among Delivery and Postpartum Hospitalizations in the United States. Obstetrics & Gynecology, 120:5. doi:10.1097/aog.0b013e31826d60c5
2. What was the definition of the construct?
Severe maternal morbidity is challenging to track since the conditions contributing to severe morbidity are rare, however, the list of ICD-9 diagnosis and procedure codes was developed on the bases of previously proposed conceptual models and frameworks for identification of severe maternal morbidity in the United States. This algorithm sought to update condition not captured by previous lists for severe complications.
3. How did the authors provide evidence on the validity of the measure? Could you think of additional approaches to validating the measure?
Line listings of ICD-9 CM diagnosis and procedure codes for all pregnancy and postpartum discharge records within hospital mortality from the Nationwide Inpatient Sample that did not use a previous code were reviewed independently. Then, the association of codes with in-hospital mortality became a new criteria to consider the diagnosis/procedure as an indicator of severe morbidity. The two lists were collated using the individual lists and by consensus.
While they utilized data from the Nationwide Inpatient Sample which is a stratified sample representing 20% of U.S. community hospitals, the validation in terms of variables to include largely rested on two reviewers consensus – how this consensus was reached was not discussed in the article. Furthermore, it would be interested to apply this algorithm to selected populations (institution, state, and regional levels) to better assess its reliability.
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?
Reliability testing was not really performed here. It is generally challenging to investigate severe maternal morbidity as the definition and causal factors have constantly evolved. Additionally, what represents a severe morbidity is not ubiquitous. While they tried to represent all possible options, expounding on measures previously evaluated 1998-1999, it would be important to test this algorithm in specific institutions – not only will this method be more reflective of the morbidity of that institution but it will also provide a more realistic idea for intervention.
5. Describe the implications of a lack of measurement validity or reliability for future research applications.
Maternal morbidity disproportionately affects women of color and those from a lower socioeconomic status. By understanding the morbidity that is reflected within these populations (whether it is a systematic increase in hypertensive disorders of pregnancy vs being less likely to receive an intervention to combat morbidity experienced) one can better design interventions to combat these disparities. While this algorithm assesses most, if not all, causes of severe maternal morbidity, its ecological construct weakens its ability to provide guidance at the local level.
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)
Howell, E. A., Egorova, N., Balbierz, A., Zeitlin, J., & Hebert, P. L. (2016). Black-white differences in severe maternal morbidity and site of care. American Journal of Obstetrics and Gynecology, 214(1), 122.e1–122.e7. doi:10.1016/j.ajog.2015.08.019.
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 measurement of the dimension of disparity directly reflected racial inequalities and the outcome measure was severe maternal morbidity (using the earlier algorithm discussed above). This reflected deliveries in the Nationwide Inpatient Sample from 2010 and 2011.
3. What is the evidence for the validity and reliability of the measures?
For the validation and reliability of the outcome, this paper used the published algorithm detailed above. There is no reported evidence for the validity and reliability of this measure except that was derived by investigators from the Centers for Disease Control and thus represents national data. For the hospital characteristics, they used similar methods to that proposed by Jha et al in which the proportion of black deliveries among all deliveries would be classified using two cut points (top 5% - high black serving, 5-25% medium black serving, and remaining 75% as low black serving).
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
They compared characteristics of black versus white women with severe maternal morbidity; this makes sense as black women have persistently been shown to have worse outcomes compared to Non-Hispanic white women even after adjustment for known socioeconomic factors.
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.
The disparity of severe maternal morbidity included 25 categories that captured indicators of organ system dysfunction. For this measurement, they utilized the Rao-Scot chi square test for categorical data which I was unfamiliar with. Essentially, since this data represents complex sampling with individuals in the population having different probability of being selected into the sample, you must incorporate this into the analysis. This reflects a relative measure which is preferably for me since the absolute risk of morbidity is relatively low in general.