WHAT REALLY STANDS IN THE WAY OF CUTTING HEALTH CARE COSTS
(Part 1 out of 2)

by Ngan MacDonald and Walter Linde-Zwirble 

When forced to choose between abstract evidence and experience, many physicians tend to rely on experience. This keeps health care costs high, write consultants Ngan MacDonald and Walter Linde-Zwirble in this opinion piece

A study of Blue Cross insurers released on July 9 by the plans’ trade association reported that health insurers are slowly moving toward “value-based” payments to doctors and hospitals. Instead of basing payments on the number of tests and procedures performed, they are experimenting with a system that rewards providers for improving care and lowering costs. The goal, says Blue Cross, is to move away from a system that rewards high cost over high-quality, efficient treatments.

That laudable goal, however, is likely to encounter resistance in a place you might least expect it: The highly rational, scientifically trained minds of physicians.

Consider, for example, the treatment of severe sepsis, the leading cause of death in non-cardiac intensive care units (ICUs). Some years ago a new drug showed great promise for treating these massive infections – if it was administered almost immediately upon the patient’s admission. Though the drug cost thousands of dollars, it had the potential to produce better outcomes – more patients surviving and experiencing fewer complications requiring additional treatment. Despite the drug’s high price, these better patient outcomes would have made the treatment more cost-effective in the long run – saving lives and money.

Nevertheless, physicians just couldn’t bring themselves to go against their years of experience in treating sepsis. Nor were they eager to upend the “escalator” model of care in which response to a condition is proportionately increased if the patient does not respond to the current treatment. You don’t start with the heroic, like a multi-thousand dollar drug; you stick to basics. In addition, they had an inherent mistrust of the data about the drug because they knew it came out of clinical trials that controlled for other complicating factors. How could they be sure that the same effect would be achieved in a hospital setting?Consider, for example, the treatment of severe sepsis, the leading cause of death in non-cardiac intensive care units (ICUs). Some years ago a new drug showed great promise for treating these massive infections – if it was administered almost immediately upon the patient’s admission. Though the drug cost thousands of dollars, it had the potential to produce better outcomes – more patients surviving and experiencing fewer complications requiring additional treatment. Despite the drug’s high price, these better patient outcomes would have made the treatment more cost-effective in the long run – saving lives and money.

As a result, despite strong evidence that the drug was both clinically and economically effective, the manufacturer could not convince ICU physicians to initiate treatment with it. Hospitals, too, don’t like to be outliers, fearing that an unorthodox treatment protocol will invite lawsuits. The drug was abandoned.

What this suggests is that the problem of controlling health care costs is partly in our minds.

As recent books such as Daniel Kahneman’s Thinking, Fast and Slow and Dan Ariely’s Predictably Irrational have taught us, what we think we are absolutely sure of often turns out to be wrong. And we often cling to those certainties even in the face of strong evidence to the contrary. When faced with a choice between experience and abstract evidence physicians will, like a great many other people, tend to rely on experience.What this suggests is that the problem of controlling health care costs is partly in our minds.

For physicians, that impulse made sense in the days before massive computing power and advanced data science. But now we can go far beyond yesterday’s analytical models built on insurance data or on tightly controlled clinical trials. We can build models that take into account many variables, identify only those variables that are statistically significant, and help clinicians provide the right treatment to the right patients.

Fuente: KNOWLEDGE@WHARTON

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(translator on page)

¿Cómo INCORPORAR y APLICAR Modelos de
PENSAMIENTO ESTRATÉGICO?
(aplicado al Sector Salud y Farma, con resolución de casos reales en tiempo real)

http://msg-latam-meic.blogspot.com.ar/2014/06/capacitacion-in-company-programa_6246.html

¿Cómo GERENCIAR EFICAZMENTE a partir del

MANAGEMENT ESTRATÉGICO?

(aplicado al Sector Salud y Farma, con resolución de casos reales en tiempo real)

http://msg-latam-meic.blogspot.com.ar/2014/06/capacitacion-in-company-programa_3.html

¿Cómo GERENCIAR PROCESOS DE CAMBIO

y no sufrir en el intento?

(aplicado al Sector Salud y Farma, con resolución de casos reales en tiempo real)

http://msg-latam-meic.blogspot.com.ar/2014/06/capacitacion-in-company-programa.html

¿Cómo IMPLEMENTAR ESTRATEGIAS EFECTIVAS?

Recetas para Escenarios Turbulentos

(aplicado al Sector Salud y Farma, con resolución de casos reales en tiempo real)

http://msg-latam-meic.blogspot.com.ar/2014/06/capacitacion-in-company-taller-de.html

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