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Vaccine Logistics

March 19, 2008 in HC Economist Models, Vaccinations

Vaccination is one of the most cost effective medical treatments we have.  It is important that providers vaccines in a timely manner.

In attempt to streamline vaccine distribution systems, the CDC created Vaccine Management Business Improvement Project (VMBIP).  Instead of having providers place orders with the grantee (i.e.: state health department), and then having the grantee ship them to a local distributor, VMBIP is an attempt to reduce warehouse costs by shipping vaccines from a centralized warehouse directly to the provider.  This may save money, if the vaccines are sent in a timely manner.

My presentation at the National Immunization Conference analyzed some data from southern California providers and found that the time from the vaccine order being place to delivery increased from 1.6 work days to 13.5 workdays after VMBIP was implemented.  I received other anecdotal evidence that these delays were affecting the vaccine supply of many California providers, but I did not know how efficiently the VMBIP program was operating in other states.

I found that California’s 13.5 day delay may not be so bad compared to the rest of the country.  One nurse from Texas said that vaccines delivery could take as long as 6 weeks.  There was significant variability so that the clinic would run out of vaccines occasionally so would have to place their orders early.  Sometime the vaccines would arrive within 2 days, but since the provider had anticipated a 2-4 week delay, there was no room in the refrigerator to store the vaccine.

Another conference attendee explained to me her experience in Minnesota.  Vaccines must be stored at a certain temperature to ensure they do not spoil.  Some winter days are so cold in Minnesota that the state public health department would advise distributors not to ship on those days to insure that they would not freeze.  Under the new, centralized VMBIP system, the national warehouse–which is run by McKesson–was not sensitive to these regional variations.  Minnesota providers have received frozen vaccines since McKesson did not know about how Minnesota winters effect vaccines.  These frozen vaccines are completely useless and must be discarded.

Overall, I doubt that centralized vaccine distribution is a good model.  Wal-mart can operate a centralized distribution system because all the stores are on the same computer network, they work under the centralized location, and receive extensive logisitcs training.  Further, Wal-mart is a hierarchical organization.  On the other hand, physicians are not integrated into a public health IT database–VACMAN not withstanding.  Further, providers are well trained on medical issues, but not logistics or filling out forms.  Since vaccine distribution is not a hierarchical system, a more flexible, less centralized, system would likely be optimal.

I would like to thank all the people who attended my presentation today at the National Immunization Conference and all the helpful feedback I have received.

Should all children get flu shots?

February 29, 2008 in Current Events, HC Economist Models, Vaccinations

According to Reuters (”All U.S. kids…“), the CDC’s Advisory Committee on Immunization Practices (ACIP) is recommending that all kids should receive an influenza vaccination. Previously, the CDC recommended that all children 0-6 receive a flu shot. Now, all children 18 and under should get the shot.

In addition to the direct health benefits the children will receive from a decreased likelihood of getting the flu, the probability that they will spread it to adults, teachers, other children, and senior citizens will decrease.

However, there will be costs to the flu vaccine expansion. According to the U.S. Census, there were 61.3 million children aged 5-19 in the U.S. Getting all these children vaccinated will be very costly and since the vaccines will be given in the fall, the logistics of providing 61 million additional flu shots will be difficult to manage.

Further, one of my working papers (”Adam Smith meets Jonas Salk: Estimating the Social Cost of Third-Party Influenza Vaccination Restrictions“) finds that when kids 0-18 year old must receive a flu vaccine efficiency losses could increase to as much as $560 million if insurance companies continue to prohibiting reimbursement to pediatricians for vaccinating adults.

EEA Conference

February 21, 2007 in Economics - General, HC Economist Models | 1 comment

Tonight I will be leaving for New York in order to present a paper at the Eastern Economic Association Annual Conference.

The paper is titled “Adam Smith meets Paulus Salk: Estimating the social cost of influenza vaccination regulation.” This research has been performed in conjunction with John Fontanesi (UCSD), Mark Messonnier (CDC), and Bo-Hyun Cho (CDC). Below is an abstract from the paper. The Healthcare Economist blog will return with new posts next week.

Influenza is the 7th leading killer in the United States. Center for Disease Control and Prevention (CDC) guidelines recommend that all parents of children between 0 and 60 months old should be vaccinated. Insurance companies, however, will not compensate pediatricians who administer influenza vaccinations to adults. This seemingly innocuous insurance company regulation, however, is creating large costs for society. Using an new observational data from a standardized workflow analysis tool, the cost of vaccination and the cost of the prohibition of pediatrician vaccination of adults is estimated. This paper finds the cost of the regulation to be between $4.4 and $140.5 million. If CDC policies altered its policies so that all parents of children 0 to 18 years old were required to receive and annual influenza vaccination, the cost of the regulation could increase to a figure as large as $417.5 million.

PPS Economic Model

April 16, 2006 in HC Economist Models

In an attempt to reduce costs, Medicare enacted a Prospective Payment System (PPS) in 1983. Medicare aimed to pay hospitals a fixed rate based on the Diagnosis Related Group (DRG) plus/minus an adjustment for location and local wage. Although this system gives hospitals the incentive to misclassify patients into high profit DRG, I will assume for simplicity that the hospital diagnose the patient’s illness with perfect accuracy. I briefly outline a model in order to analyze how PPS effects hospital (or providers) incentives.

The Model

The hospital makes a profit on each patient of: P-C(s)-c(q(s))

  • P is the reimbursement rate from Medicare based on the DRG; C(s) is a cost function depending on sickness, c(q(s)) is the additional cost incured by the hospital for additional quality of care. C’,C”,c’,c”,D’,D” are all strictly positive.

Total profits for the hospital are: D(q)*[P-C(s)-c(q)]; where D(q) is the consumer’s demand function. Firms maximize profits by choosing the quality level for each sickness type. The first order condition for the firm is:

  • D’[P-C(s)-c(q)]=D*c’(q)

If we totally differentiate the above equation (remember q is a function of s), we have:

  • d(q(s))/d(s)=[D''(P-C-c)-2D'c'-Dc'']/[D'C'] <0

Discussion
What does all this math mean? Well since dq(s)/ds<0, this means that discretionary quality falls with severity for all profitable patients and is set to zero for unprofitable patients. Since the PPS payment system does not reimburse providers for additional quality of their work with patients, these providers have an incentive to decrease quality. On the other hand, if we construct a 'cost-plus' system where hospitals are reimbursed at (1+x%) of cost, hospitals have an incentive to treat the most severe illnesses since they are the most profitable.

Models as developed in: Meltzer and Chung (2002) “Effects of Competition Under Prospective Payment on Hospital Costs Among High- and Low-Cost Admissions: Evidence from California in 1983 and 1993″ Forum for Health Economics and Policy, Vol 5(4).

A simple model giving some justification for Medicaid

March 11, 2006 in HC Economist Models, Medicaid/Medicare

While many poor people do not have insurance, a great majority have access to some type of care.  For instance, all people have access to emergency room services.  I currently volunteer at one of the many free clinics located in San Diego county.  Thus, lack of insurance is not equivalent to absence of medical care.

A brief model I have created may help explain how poor individuals choose their optimum number of work hours and amount of health care consumption.

Individuals are utility maximizers and maximize the following function:

U(C,h,l), s.t.:

  • C+p*s+=I+wL;   if p*s
  • C=c; if p*s>I+wL-c
  • h=f(s);
  • l+L=N
  • p=P+t

‘C‘ is total consumption, ‘h‘ is a person’s health which is a function of health care spending ‘s‘.  ‘l‘ is leisure and ‘L‘ is hours of work; these two variables must sum to the total hours in a year ‘N‘.  ‘I‘ is non-wage income.  ‘c‘ is the lower bound of consumption.  ‘p‘ is the price of health care.

A middle class or wealth person will generally want a C>c and will maximize subject to the first budget constraint.  The first order conditions for them are:

  • U_c = (U_l)/w = ((U_h)*f‘)/p

Poor individuals will generally choose another option.  I assume that one can get as much medical services as one pleases by going to free clinics or the emergency room; by doing so, however, one is relegated to a minimal consumption level since a hospital or medical services provider will be able charge a patient for its services, unless the person is extremely poor.  The provider could not collect an amount which would lower a person’s consumption below ‘c‘.

Thus, people using the second budget constraint (generally the poor), will have:

  • C=c; L=0; s=infinity.

Since any money earned by the poor individual will simply be used to pay medical bills, this person has no incentive to work.  Further, since health care is free, the person will want to consume an infinite amount of services.  In reality, medical care is not completely free to an individual since there are travel and time costs so ‘s‘ will be finite.

Nevertheless, this simple model would provide some rational for the Medicaid program.  I am not generally in favor of government administered health insurance, however, if the poor are able to force suppliers of medical services to provide their services free of charge, this will imply a higher price for those able to pay for the services.  Another option would be to not offer the poor medical services unless they paid.  Fortunately for the disadvantaged, our society has rejected this notion.

A model of Medicaid’s poverty trap

February 16, 2006 in HC Economist Models

The design of legislation which regulates Medicaid eligibility creates a poverty trap. In California, generally those who have income below 250% of the federal poverty level and who have limited assets are eligible for Medicaid. (In reality California’s Medicaid eligibility is more complicated than this. For full details of eligibility requirements see “Medi-Cal Facts and Figuresâ€? produced by the California HealthCare Foundation.)

Let me explain how the poverty trap functions. Let us examine an individual which earns 249% of the federal poverty level. The individual may desire to work more hours, but by doing so, he/she will lose the Medicaid benefit. Thus, by working more, the individual is actually worse off.

Here is my model which will describe this phenomenon mathematically. Consumers are utility maximizers:

max(c,h,l) U; U=(1-p)c + p[c-S-a*ln (1+ h +M*)]+g(l)

  • s.t.: c+p(1+j)h+wl=w{L_bar}
  • c>=0, h>=0, 0<=l<={L_bar}
  • c: consumption
  • S: disutility from being sick
  • p: probability of getting sick
  • M*: Medicaid Benefit, M*=0 if wL>E. Otherwise M*=M
  • E: Eligibility limit on Medicare, in California 250% of the poverty line
  • h=health insurance purchased
  • w= wage
  • l=leisure, L=hours worked, {L_bar}=total hours in time period
  • gamma=shadow price of income
  • g’>0; g”<0

 

The first order conditions are:

    • d c: gamma=1
    • d h: h*=a/(1+j) – 1 – M*
    • d l: g’(l)=w; L={L_bar} - g’_^{-1}(w)

Since h* does not depend on c, L, or w; dc/dL>0 on the support where c, L are continuous. However, if L=(E-e)/w where e is an arbitrarily small positive number, then increasing L by a non-differential amount will decrease consumption. Since h* does not depend on l or c, the individual will choose the same h* with or without the Medicaid benefit (assuming h*>=M). Thus, the poor individual near the Medicare eligibility limit will actually be worse off by working more. This is a poverty trap.

Conservatives often claim that the poor are lazy. While this is certainly true in some cases, and while drugs are an overwhelming problem for the poor, the vast majority of the poor are hard working individuals. They are not stupid, however. As this model shows, when working more hours leads to less disposable income, it is entirely rational to limit hours worked in order to collect the government benefit.

A voucher program could eliminate this problem. The voucher program would have the following model:

max(c,h,l) U; U=(1-p)c + p[c-S-a*ln (1+ h)]+g(l)

  • s.t.: c+p(1+j)h+wl=w{L_bar} + V*
  • c>=0, h>=0, 0<=l<={L_bar}
  • V*={h_bar}p(1+j) if h>={h_bar} and V*=0 if h<{h_bar}

In essence, this would allow the government to pay for an individual’s insurance up to {h_bar}, but workers who decide not to purchase insurance would not receive this subsidy. Since, the government will be giving free health insurance, it is irrational to not choose h*>={h_bar}. V* does not depend on earnings and thus there is no disincentive to work.

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