The other side of innovation

2013 ◽  
Vol 19 (1) ◽  
Author(s):  
Peter J. Pitts
Keyword(s):  
Comparative Effectiveness Research ◽  
Comparative Effectiveness ◽  
The Other ◽  
Effectiveness Research ◽  
Chilling Effect ◽  
Single Payer ◽  
The Future ◽  
Healthcare Rationing ◽  
Healthcare Innovation

Government sponsored comparative effectiveness research is the first step towards allowing Uncle Sam to push a restrictive formulary on more and more Americans – with step one in the process being unfettered (and unregulated) communications efforts. Unless we are aware and vigilant, such cost-think may very well lead to a single-payer system referred to in cost-think as “universal coverage” – but in reality will be nothing short of healthcare rationing. There are many dangerous implications, but the most frightening is the chilling effect so-called comparative effectiveness programs will have on the future of healthcare innovation.

Comparative effectiveness research: policy and politics

2012 ◽  
Vol 33 (1) ◽  
pp. E6 ◽  
Author(s):  
Edie E. Zusman
Keyword(s):  
Health Care ◽  
Health Care Providers ◽  
Comparative Effectiveness Research ◽  
Comparative Effectiveness ◽  
Research Policy ◽  
Effectiveness Research ◽  
Care Providers ◽  
Future Health ◽  
The Future ◽  
Key Aspects

Comparative effectiveness research (CER) is the basis for some of the fiercest rhetoric of the current political era. While it is a relatively old and previously academic pursuit, CER may well become the foundation upon which the future of health care in the US is based. The actual impact of CER on—and uptake among—doctors, patients, hospitals, and health insurers, however, remains to be seen. Political considerations and compromises have led to the removal of key aspects of CER implementation from policy legislation to prevent alienating stakeholders critical to the success of health care reform. Health care providers, including specialists such as neurosurgeons, will need to understand both the policies and political implications of CER as its practices becomes an indelible part of the future health care landscape.

Will Comparative Effectiveness Research Lead to Healthcare Rationing?

2011 ◽  
pp. 1-21
Author(s):  
Mary Brown
Keyword(s):  
Comparative Effectiveness Research ◽  
Comparative Effectiveness ◽  
Data Exchange ◽  
Health Data ◽  
Effectiveness Research ◽  
Advisory Committees ◽  
Healthcare Data ◽  
Practice Approach ◽  
Electronic Health ◽  
Healthcare Rationing

The Affordable Healthcare for America Bill that was signed into law in March 2010 includes support for activities that come under the heading of ‘comparative effectiveness’ research. The bill attempts to accelerate the conversion to electronic health records by all payers and providers who participate in the healthcare payment data stream. Conversion to electronic health data collection and storage solutions will create a large amount of treatment and payment data that is increasingly standardized by health standards organizations which reduces integration issues between technologies. There are federal advisory committees at work on designing the infrastructure needed to support a National Health Information Network (NHIN) that will support the healthcare data exchange required for comparative effectiveness research. The theory behind this work is that the availability of a large portion of existing health data will make it possible for researchers to identify therapies that lead to superior patient outcomes. It is assumed that the superior therapy would become the ‘best practice’ approach to treating a particular ailment. Supporters of comparative effectiveness see this as a strategy for making the system more effective both in terms of good medicine and also in terms of decreased cost. Opponents of comparative effectiveness see it as healthcare rationing and an inappropriate injection of government into the healthcare decision making process. Supporters and opponents have identified both positive and negative consequences to comparative effectiveness and this chapter will analyze the impact and propose some ways to optimize the results of this work.

Will Comparative Effectiveness Research Lead to Healthcare Rationing?

2012 ◽  
pp. 1487-1507
Author(s):  
Mary Brown
Keyword(s):  
Comparative Effectiveness Research ◽  
Comparative Effectiveness ◽  
Data Exchange ◽  
Health Data ◽  
Effectiveness Research ◽  
Advisory Committees ◽  
Healthcare Data ◽  
Practice Approach ◽  
Electronic Health ◽  
Healthcare Rationing

The Affordable Healthcare for America Bill that was signed into law in March 2010 includes support for activities that come under the heading of ‘comparative effectiveness’ research. The bill attempts to accelerate the conversion to electronic health records by all payers and providers who participate in the healthcare payment data stream. Conversion to electronic health data collection and storage solutions will create a large amount of treatment and payment data that is increasingly standardized by health standards organizations which reduces integration issues between technologies. There are federal advisory committees at work on designing the infrastructure needed to support a National Health Information Network (NHIN) that will support the healthcare data exchange required for comparative effectiveness research. The theory behind this work is that the availability of a large portion of existing health data will make it possible for researchers to identify therapies that lead to superior patient outcomes. It is assumed that the superior therapy would become the ‘best practice’ approach to treating a particular ailment. Supporters of comparative effectiveness see this as a strategy for making the system more effective both in terms of good medicine and also in terms of decreased cost. Opponents of comparative effectiveness see it as healthcare rationing and an inappropriate injection of government into the healthcare decision making process. Supporters and opponents have identified both positive and negative consequences to comparative effectiveness and this chapter will analyze the impact and propose some ways to optimize the results of this work.

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