Читать книгу Demystifying Research for Medical and Healthcare Students - John L. Anderson - Страница 48

John McKinlay is an old teacher, friend, and mentor of mine. We met in Aberdeen in 1966, and he left there to go to MIT in Boston (USA) where he established the New England Research Institute and has become one of the most prolific and successful sociologists of all time. Along with others in his Institute, he conducted a series of studies of diabetes – including some very interesting and innovative experiments. In one (McKinley et al. 2012), they were interested in finding out if there were race/ethnic differences in the diagnosis of diabetes when physicians are experimentally presented with signs and symptoms of diabetes.

Previous work in the USA had found that Type‐2 Diabetes Mellitus (T2DM) varied considerably by race/ethnicity. They noted that:

Both the National Institutes of Health ( NIH ) and the American Diabetes Association ( ) report race/ethnicity to be a major independent contributor to T2DM. Assuming the race/ethnic disparity in T2DM to be real, researchers seek its explanation in either: (a) social and behavioral risk factors or life styles; or increasingly, (b) genetic contributions and family history. We consider a third possible contributor to race/ethnic disparities in T2DM – the racial/ethnic patterning resulting from diagnostic decisions, principally by primary care providers. Notwithstanding the possibility of a modest race/ethnic contribution, we question whether the reported wide race/ethnic variation in the prevalence of physician diagnosed T2DM accurately reflects its actual distribution in the general population. We hypothesize the actual prevalence of signs and symptoms of T2DM, when undiagnosed in the community, is patterned far more strongly by SES (than by race/ethnicity), but when eventually diagnosed by physicians it is patterned more by race/ethnicity (than by SES).

To investigate the size and distribution of undiagnosed T2DM in the community, they designed and conducted a random sample survey in the general population in the Boston area – The Boston Area Community Health (BACH) Survey. This was an epidemiological survey of Boston residents aged between 30 and 79 years. A ‘stratified two‐stage cluster sample was used to recruit residents of Boston with approximately equal numbers of participants by gender, race/ethnicity (non‐Hispanic black, Hispanic, non‐Hispanic white), and age group (30–39, 40–49, 50–59, 60–79)’. Altogether, 5503 adults participated (1767 black, 1877 Hispanic, 1859 white; 2301 men and 3202 women) – a response rate of 63.3% of eligible participants. Anyone who reported five of the six cardinal symptoms – fatigue; being overweight; frequent urination; thirst; not feeling well; hypertension – was considered to be highly likely to have undiagnosed T2DM.

This part of the study showed ‘no significant race/ethnic differences in the prevalence of the (undiagnosed) signs and symptoms indicative of diabetes within a socioeconomic level (lower class χ2 p = 0.79, middle class χ2 p = 0.34, upper class χ2 p = 0.40). However, significant differences are evident by SES (χ2 p < 0.0001), and they are consistent within each race/ethnic category’. So – no racial differences in the prevalence of T2DM, but there were differences according to socio‐economic status. This set the scene for the experimental study.

In the experimental part of the study, they used video scenarios of real clinical cases, with professional actors and actresses, trained to realistically simulate a ‘patient’ presenting to a primary care doctor. There were 24 identical versions of the clinical scenario. These varied only with the patients' age, gender, socio‐economic status, and race. The vignettes simulated an initial consultation of five to seven minutes.

The ‘subjects’ were 192 primary care doctors who viewed the vignettes and were asked to give the most likely diagnosis and their degree of certainty. They were then interviewed and asked to say how they would manage the case in their practice.

As they describe:

A factorial experiment is a research design consisting of two or more factors (e.g. race/ethnicity, gender, and socioeconomic status) each with discrete values (or ‘levels’). All possible combinations of these levels across the factors are then randomly assigned to subjects. Such experiments permit estimation of the effect of each factor on the response variable, as well as the effects of interactions between factors and the response variable. This approach permits estimation of the unconfounded effect of a ‘patient's’ race/ethnicity (also age, gender and SES) on diagnostic decision making when primary care physicians encounter different randomly assigned patients presenting with exactly the same signs and symptoms strongly suggesting undiagnosed diabetes.

An ordered version of a clinical vignette varying only the ‘patient's’ race/ethnicity (non‐Hispanic black, Hispanic, or non‐Hispanic white), age (35 or 65 years), gender, and SES (as depicted by their dress and occupation as a janitor or a lawyer) was shown to each of 192 licensed internists, family physicians, or general practitioners practicing in New Jersey, New York, or Pennsylvania. Physicians were also required to be graduates of an accredited medical school in the US and to be providing clinical care at least half time. Since this study was part of a larger international study concerning the management of T2DM in different countries (health care systems) it was not possible to include international medical graduates ( IMGs ). We stratified physician subjects according to gender and level of clinical experience (graduated from medical school between 1993–1999 (less experience) or between 1969–1983 (more experience)) (there were 2 × 2 = 4 strata) and recruited eligible physicians until each of the 4 strata was complete. Each of 24 vignette pairs was viewed twice in each of the 4 strata for a total of (24 × 2 × 4=) 192 physicians.

Sampling of physicians was done using a purposive sample to fill each design cells (male/female; more/less experienced) – rather than a straight random sample of physicians. In this way, they were more quickly able to get the required numbers to fit the profiles they needed for the study.

Thus, the permutations were as shown in Table 3.1:

Their results showed that doctors were significantly more likely to diagnose diabetes in the black and the Hispanic ‘patients’, 73.4% of the physicians' diagnosed T2DM when the ‘patient’ was black, 60.9% when Hispanic and 48.4% when white (p = 0.009) – when fully adjusted for the ‘patient's’ age, gender, and SES, the percentage of physicians giving a diabetes diagnosis was 64.5% for lower SES patients (janitor) versus 57.3% for upper SES patients (lawyer) (p = 0.265) and the corresponding level of certainty for lower SES patients was 24.4 compared to 20.4 for upper SES patients (p = 0.241). In other words, in making an initial diagnosis, physicians focus more on the ‘patient's’ race/ethnicity rather than their SES.

They concluded: ‘this paper suggests that the signs and symptoms of T2DM, when undiagnosed in the general community, are patterned by SES and not race/ethnicity and that following diagnosis by a physician they are patterned by race/ethnicity’.

Don't you think that is interesting? It raised, for them, the question about whether the higher rates of black and Hispanic persons diagnosed with T2DM was a result of a racially‐skewed stereotype rather than a true profile of the population in need of care.

Remember Mick Bloor's saying: ‘Research is the art of the possible’? John's study was well‐funded. Thus, they were able to hire and train actresses. They were able to develop the scenarios of the ‘patients’. They were able to conduct the sampling in a very professional manner. They were able to get the physicians to spend their time taking part in the experiment. Thus, they were able to go beyond the laboratory. They were able to do the experiment with real, practising physicians, rather than with medical students. And they had the expert statistical expertise required for their very complex analyses within their organisation. Well done them!