Local Attention to Disease and the ���Global Disparity of Health Knowledge���

james evans (jevans@uchicago.edu) jae-mahn shim (jaemahn.shim@gmail.com)

University of Chicago john p. ioannidis (jioannid@stanford.edu)

Stanford University

Where does knowledge come from?

Where does knowledge come from?

•  Needs? •  Markets? (needs with $) •  Movements? (needs with organization) •  Access (mixture of distributions of producers

with needs)

•  Idiosyncrasies of scientific advance •  Perceptions of scientific generality

 

National and global health disparities

1)  differences in biology (e.g., genetics) 2)  differences in socioeconomic experience and

environmental exposures 3)  differences in the opportunity to access

health care and receive quality medical attention

 

National and global health disparities

1)  differences in biology (e.g., genetics) 2)  differences in socioeconomic experience and

environmental exposures 3)  differences in the opportunity to access

health care and receive quality medical attention

Most U.S. examinations emphasize last

Distribution of health knowledge

Less consideration given to the relevance of medical knowledge to the health needs of different groups even if health care was equal Diagnostics and therapies (over)fit to certain bodies / environments with –  different disease / disability profiles –  different genetic profiles

If so, the same care would not be the same; The same resources would not be equitable

Global inequality of health knowledge

Design 1)  Assess global health knowledge Assess how much explained by… 2)  the global health burden imposed by these

conditions 3)  the global market for therapies 4)  the local health burden

Health Knowledge

# articles produced relevant to each disease / condition

f(MEDLINE articles for 111 disorders by researchers in 192 countries) Censorship of non-English, low-circulation research

Health Burden

Disability-adjusted life years (DALYs) •  World Health Organization 1990, 2002, 2004

(at global, regional and country level)

•  Incorporate cultural values placed on different aspects of physical, mental and social function to convert time spent in various states of health into “healthy year equivalent”

•  healthy years lost to disease/disability Alternatives: incidence, prevalence, hospital days, mortality, years lost, …

Linkage"

WHO Global burden of disease codes "" "~ "" "ICD-9 disease and disability codes"

" " "~ "" " "UMLS Metathesaurus"" " " "~"" " " "MeSH headings"" " " " "~ "" " " " "MEDLINE abstracts"

Health Market

The amount of income that could be generated by health from curing disease

= The $ that could be spent on health (if all earned from health were spent on health)

f(GNI per capita * DALY for each disease / country)

Modeling framework

 Articlesdt ~ NegativeBinomial(μdt)

Log(μdt) = DALYdt-1 + market sizedt-1 + Articlesdt-1 + Broad disease category + εdt

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Conclusions

•  Global DALYs had NO significant influence on the production of published health knowledge

•  Global treatment market for each condition did. •  Likely driven by local processes of health research.

–  Case reports and clinical trials within countries were strongly guided by local DALYs. Systematic reviews and clinical trials were slightly more responsive to global DALYs, and reviews were not influenced by country conditions.

•  Rich and poor countries had very different disease profiles •  Rich countries publish much more than poor countries. •  Accordingly, conditions common to rich countries

garnered more case and clinical research than those common to poor countries.

Implications

Many health needs in poor countries do not attract attention among rich country researchers Rich country researchers dominate the production of global health knowledge •  How much health knowledge relevant to poor country

diseases? •  What is the efficacy of health care resources currently

extended to poor populations? Inequality of health knowledge should be addressed as an additional dimension of current global health inequality

Limitations

•  The empirical distribution of “other papers”: Human vs. Mammal models vs. Yeast

•  Citations with longer lag to enable Fixed-effect modeling and tighter identification

•  GNI/GDP adjusted for purchasing power parity •  More (recent) years •  National health research funding data

Next Steps

Detailed institutional configuration: OECD countries funding by area United States (with Bhaven Sampat) funding, activism/earmarks, expenditures, medical exposures, scientific relevance/generality, opportunistic swarming, etc.

Thank you

•  Program on Health and health policy research for disadvantaged populations at the Center for Health Administration