Scott Gottlieb, MD contributor to Forbes has a rather lengthy analysis of Obamacare and how It will hurt cancer patients. Dr. Gottlieb goes into great detail to make the point.
First, Obamacare is going to block the ability of patients to seek out the specialist doctors who are most likely to prescribe these cutting edge treatments.
Obamacare tries to coerce doctors to cut down on their use of costlier drugs and tests by changing the way that they’re paid. The law uses “bundled” payments, where doctors get lump sums of money to care for patients with particular medical problems. The idea is to pit the cost of the treatments doctors prescribe directly against their earnings and give doctors a potent incentive to use cheaper remedies.
Obamacare targets cancer drugs directly, by expanding a program called 340B, which siphons money away from drug developers in order to subsidize hospitals. The Obama Administration sees the program as a way to prop up the hospitals (a favored constituency) on the dime of less popular drug makers. But the oblique way the money is extracted from drug companies spawns a lot of harmful consequences that are increasing the cost of cancer care, and lowering its quality.
Gottlieb further makes the case that over 20 years total spending on cancer care was stable at 5%. And further how inpatient cancer admissions fell from 64% in 1987 to 27% in 2001 to 2005.
His closing thoughts are focused on the cost of cancer drugs and the high cost of developing thuds drugs.
Instead, Obamacare limits access to specialist doctors in order to cheapen insurance products, uses financial schemes that pay doctors more to do less, and targets the drugs that represent so much of our recent progress against cancer.
I agree with this thought and logic but I am not familiar enough with the 1,220 pages in the law to debate the overall message he is presenting. And I would trust his logic and data but I must say the conservative press has picked up on this and is running like crazy with the headline and not looking at the message of cost of drugs. If anyone out there has more information on this please share.
Neiger, Thackeray, et. al from Brigham Young University Department of Health Science publishing in JMIR examined how local health departments (LHD) used Twitter to share information, engage with followers, and drove action behavior. In addition they looked at differences between LHD’s by size of populations served.
While some evidence suggests that broad dissemination of information characterized by traditional mass media campaigns can improve population health, effective campaigns require simultaneous availability of and access to programs, services, and products that facilitate change . Furthermore, broad dissemination of information ignores the fact that messages should be targeted to the intended audience. In the case of Twitter, LHDs may know nothing or very little about their followers unless they engage in dialogic communication to establish relationships. To indiscriminately post information on Twitter is inefficient. In fact, this contributes to what has been described as a fractured and cluttered media environment that can be resolved only through careful planning and testing of campaign content with intended audiences .
It was encouraging that at least one-third of LHD tweets attempted to engage followers, foster relationships, create networks, or build communities. These results are similar to those found by Lovejoy and Saxton in their analysis of how nonprofit organizations use social media . Use of personal pronouns was present over a third of the time and more common among smaller LHDs. Additionally, evidence of effort toward dialogic communication included tweets that tended to be conversational in nature and may have used personal pronouns but were not necessarily intended for the purpose of engagement. This evidence of more conversational posting indicates LHDs may be trying to create a Twitter persona that is warm and friendly, thus making it more inviting for Twitter users to follow.
Are we beginning to see the fruition of social media (i.e. Twitter) in healthcare providing a welcomed and valued dialogue with health departments that improve the health of populations? I hope this data is only the start.
van den Berg, Peters et. al from Radbound Rniversity Nijmegen Medical Center in the Netherlands publishing in JMIR have a fascinating and important look at how generic Web-sites are used and can be better designed for breast cancer survivors. This is an important study in my view because we are beginning to look at patients as learners based on usage statistics. This is providing ‘realistic estimation of exposure to intervention content“. Further the authors note “results suggest that investigating how generic fully automated Web-based interventions are used is far more informative than the amount of exposure. Usage statistics should be chosen accordingly.”
This is an important a first step. I believe we need to look at how these survivors are using this information to learn and what problems they are seeking to solve.
The stated objective
To gain insight into meaningful usage parameters to evaluate the use of generic fully automated Web-based interventions by assessing how breast cancer survivors use a generic self-management website. Final aim is to propose practical recommendations for researchers and information and communication technology (ICT) professionals who aim to design and evaluate the use of similar Web-based interventions.
This study underscores the added value of evaluating usage statistics of generic Web-based interventions as a realistic estimation of exposure to intervention content. To the best of our knowledge, the present study gained first insight into the design of technical usage evaluations of generic fully automated Web-based interventions. Overall, and in concordance with research on more interactive eHealth applications , results suggest that investigating how generic fully automated Web-based interventions are used is far more informative than the amount of exposure. Usage statistics should be chosen accordingly. Further, it is recommended to collect both singular and composite usage statistics, include self-reported usefulness, and to pilot test a variety of usage statistics to aid decision making of meaningful usage parameters. Last, shared knowledge about ICT and conducting research is helpful in developing a meaningful rationale of technically recorded usage statistics of generic Web-based interventions.