By L. Gordon Moore, MD, Senior Medical Director, Clinical Strategy and Value based Care for 3M Health Information Systems
How might a health system use existing health information to inform a data-driven priority focussed model in response to COVID 19?
Health authorities globally are faced with gaps between supplies and the demands created by COVID 19 In the movie Contagion, countries distributed the limited supply of vaccine by means of a lottery What framework could help prioritise resource allocation better than the model from the movie?
Suppose that you oversee health policy and social security for the nearly five million people in the Valencian Community of Spain and you have about 3.6 million masks available for distribution to the public after the healthcare workforce have been supplied.
Published (but mostly not yet peer-reviewed) studies tell us that those most at risk of poor prognosis should they contract COVID 19 are older people and those with diabetes, chronic heart, lung, kidney disease and a few other conditions.
Because you have administrative data you might use diagnosis codes to flag everyone with diabetes, however you are aware that some people with diabetes are relatively healthy whereas others are desperately ill In addition to the wide variation in severity of diabetes, you know that a person’s total burden of illness (and risk of poor prognosis) is predicted by co morbidity the number of chronic conditions, the severity of those conditions, the number of organ systems involved etc
Another concern is that the list of conditions predicting poor prognosis for people who contractCOVID 19 is relatively short Clinicians suspect that additional similar conditions should be on the list because with this underlying condition, the risk of poor prognosis is high For example, if chronic obstructive lung disease puts a person at high risk, what about cystic fibrosis or systemic lupus erythematosus with lung involvement?
A potentially more stable framework, then would include age, a more extensive list of diagnoses and an indication of which combined co morbidities present in the same individual impact upon their likely prognosis 3 M™ Clinical Risk Groups ( is a classification methodology capable of
providing this level of information
The Ministry of Universal Health and Public Health of the Valencian Community resolved on April 15, 2020, to use the 3 M CRG methodology to prioritise mask distribution Using 3 M CRGs, the Region of Valencia will identify the most vulnerable members of the population, who, if infected, would be at the highest risk of hospitalisation and admission to ICU or in need of mechanical respirator That is, all people over 65 years old and those under 65 but with one of the following conditions significant chronic disease in multiple organ systems, dominant chronic disease in three
or more organ systems malignancies under active treatment or catastrophic conditions
This is evidence of the value of the use of data to achieve a more scientific approach to the priority of response to the current pandemic This framework is useful for individuals who choose to extend their social distancing or lockdown because of their high risk of poor prognosis It may also be useful for those who should seek help as soon as they suspect that they may have symptoms rather than try to stay at home
For more information please call 0800 626578 or visit this link to read more about 3 M Clinical Risk Groups