Capitation

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Do doctors tailor the care they provide based on the patient’s health plan?

October 12, 2011 in Physician Compensation | 1 comment

Many studies (including my own) have shown that physicians paid via capitation  perform fewer services than those paid via fee-for-service (FFS).  In the current health care world, however, most physicians treat patients from a variety of different insurance systems (notable exceptions are doctors working at Kaiser and the VA).

Two important research questions come to mind:

  • Do doctors tailor the care they provide to individual patients based on their insurance or is care provided based on the overall mix of a physician’s panel?
  • Are these same effects observed for physicians who own their own practice compared to those who are employees?

According to a paper by Landon et al. (2011), “ Physicians in highly capitated practices had the lowest total costs and intensity of care, suggesting that these physicians develop an overall approach to care that also applies to their FFS patients.”  The authors used data from the Community Tracking Study Physician Survey to reach this conclusion.

This result, however, was only shown to hold for primary care physicians.  The reimbursement differences for each individual patient may be smaller than the physician’s time (and psychic) cost to determine each patient’s payor and alter their recommended treatment regimen accordingly.  Thus, this conclusion makes sense for PCPs.

For specialists, however, this conclusion may or may not hold.  Particularly, for specialists who generally provide expensive procedures, altering care recommendations for individual patients based on their insurance coverage could have a very significant effect on the practice’s bottom line.

Thus, although I think this is an interesting study, it would also be interesting to see how the results were similar or different in the case of specialist compensation.

Source:

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Does Physician income increase from treating more complex patients?

July 18, 2011 in International Health Care Systems, Physician Compensation, Supply of Medical Services | 2 comments

In Denmark at least, the answer is no.

“From the theoretical model we find that higher levels of patient complexity lead GPs [General Practitioners] to choose a lower list size, whereas the effect on income is ambiguous. The effect on total utility (income and leisure) is, however, shown to be negative. Using empirical datafrom 1039 solo practices we find that patient complexity reduces both list size and income and conclude that amixed per capita and fee for service remuneration system does not fully compensate practices with more complexpatients. Differentiated per capita payment may represent a means of ensuring fair and equal income of GPs.”

Differentiated per capita payments may provide a fairer mechanism for compensating physicians for treating more complex patients. This type of reform, however, would also incentivize providers to upcode patient diagnoses in order to increase their per capita payments. Thus, this paper may provide the optimal solution in the case where providers are honest, but this same solution may not be optimal in the case where physicians are potentially dishonest.

The remainder of this post reviews how the authors arrived at the conclusions discussed below.

Read the rest of this entry »

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How does managed care affect physician incentives to reduce care?

October 30, 2008 in Physician Compensation, Supply of Medical Services | Permalink

Patients generally believe that managed care systems are put in place to restrict their access to care.  Many patients believe that physicians who receive capitation compensation will provide less care to their patients than physicians who are paid on a fee-for-service basis.  A paper by Fang and Rizzo (2008) investigates whether or not this is really they case.

The authors find that “both capitated and noncapitated managed care significantly increased physician incentives to reduce care during 2000-2001.”  This is just what economists would predict.  When physicians receive capitation payment, they receive non-positive marginal revenue, giving them an incentive to reduce care.

By 2004-2005, however, Fang and Rizzo found no statistically significant difference in physician desire to reduce care between physicians in managed care organizations and those who were not.  Capitation compensated doctors still were more likely to reduce care levels than other doctors but this was only marginally statistically significant (p<.08) and of a much smaller magnitude.

What can we conclude from this?  Likely it is the case that over time, managed care organizations have become less managed; non-managed care organizations have put in place more restrictions over time.  Separately identifying how managed care incentives (e.g., referral restrictions) and physician compensation incentives (i.e., capitation vs. fee-for-service) impact care levels is very important as insurance plans become more homogeneous.

If you are interested in how physician compensation affects surgery rates, you can read my paper “Operating on Commission: How physician financial incentives affect surgery rates.”

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Cochrane Review: The effect of capitation, fee-for-service (FFS) and mixed payment systems on primary care physician behavior

July 21, 2008 in Academic Articles, Physician Compensation | Permalink

Primary care physicians can be compensated in a number of ways. The most popular are capitation, fee-for-service, salary, or some mixture of the three. But how does the physician compensation method affect care levels? This is the question Gosden et al. (2000) try to answer in their Cochrane review. The authors search the literature for randomized trials or controlled before and after studies in order to see how changing physician compensation affects the quantity and quality of care.

A summary of the 4 papers which met Gosden et al.’s criteria is below.

Category Davidson 1992 Hickson 1987 Krasnik 1990 Hutchinson 1996
Country US US Denmark Canada
Type Randomized Trial Randomized Trial Before-and-After Before-and-After
Payment i) age-adjusted capitation; ii) Medicaid FFS; iii) more lucrative FFS i) FFS; ii) Salary Control: Cap/FFS mix; Intervention: Capitation only, changes to Cap/FFS mix Before: FFS; After: mixed capitation, ambulatory care incentive
Physicians Primary Care Providers (PCPs) Residents General Practitioners (GPs) GPs/Family Physicians
Results Comparing FFS and capitation, there was no difference in the number of PCP visits. There was no difference in the number of patients attended The number of face-to-face and phone visits was higher in the control group than the intervention group. Hospital days decrease in all groups, but the change is similar across all payment types.

Controlling for covariates, there were 0.5-0.6 more visits for the capitation group compared to the Medicaid FFS. There were more ER visits for the salaried group compare to the FFS group. After the FFS was implemented in the intervention group, visits increased and converged to that of the control group.

The new, more lucrative FFS increase PCP visits by .8-.9 per patient compared to the Medicaid FFS. Salaried doctors have fewer well-child visits per enrollee After the FFS implementation [intervention group], the number of diagnostic and curative services order increased.

PCPs paid via capitation used fewer specialist and hospital resources After the FFS implementation [intervention group], the number referrals to specialists fell

Patients were less likely to reach recommended visit levels in capitation compared to FFS

The original four articles:

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Health Insurance, Physician Compensation and the Quantity of Medical Care

May 30, 2008 in Health Insurance, Hospitals, Physician Compensation, Supply of Medical Services | Permalink

Many studies have attempted to determine how the manner in which physicians are compensated by health insurance companies affects the quantity of medical care provided. Today I will summarize some seminal studies in this field.

Epstein, Begg and McNeil (NEJM 1986)

In this study, the authors examine whether or not there is a difference in the rate of ambulatory testing between physicians in a large fee-for-service (FFS) group and a large prepaid group. The physicians were internists who were caring for patients with uncomplicated hypertension. The authors found that 50% more electrocadriograms (EKGs) were obtained in the FFS group and 40% more chest radiographs were obtained in the FFS group [compared to the prepaid group]. There did not seem to be any difference in testing rates between FFS and prepaid doctors for blood counts and urinalyses. This is not surprising, however, because the profit physicians earned from EKGs and chest radiographs was significantly higher than the profit they made from each blood count or urinalysis. Further, the cost of preforming EKGs and chest radiographs was much higher than the cost to preform blood counts and urinalyses.

Thus, this study concludes that patient testing rates are different between FFS and prepaid doctors, but this effect is only observed for high cost and/or high margin ambulatory tests.

Newhouse and Marquis (JHR 1978)

Physicians may treat patients differently based on how the patient’s insurance company pays them. However, the patient base of most physicians includes a wide variety of health plans and thus it may be difficult to discriminate care levels by insurance type. The “norms hypothesis” predicts that physicians treat patients in accordance with the average or modal insurance coverage in a given metropolitan area. In other words, “the level of a community’s insurance coverage determines physician norms.” If this were true, it would imply that there would be significant variation in medical care quantities across geographic regions but very little variations by patient for each physician.

The authors use data from the RAND Health Insurance Study in Dayton, Ohio. The authors test whether or not the patients own insurance rate will affect hospital admissions, the length of a hospital stay or the number of physician office visits. The authors find no evidence that community-level coinsurance rate impact hospital admissions, while the patient’s own coinsurance rate significantly affects hospital admission. In the 1963 data, neither the community insurance variable nor individual insurance variable had any affect on the length of a hospital stay or the number of physician visits, however in the 1970 data, individual coinsurance rates had a large impact on the length of a hospital stay or the number of physician visits, while the community level coinsurance rate had no impact on these dependent variables.

Hellerstein (RAND J Econ 1998)

Most health policy wonks believe we could significantly reduce health care costs without sacrificing quality by using more generic drugs. Many states have passed “permissive substitution laws” which allow pharmacists to substitute generic drugs in place of name-brand ones unless the physician explicitly instructs them not to do so. Other states use a “two-line” prescription method. With these prescription pads, doctors can sign their name in one of two spots: the first indicates that generic substitution is allowed and the other indicates that the brand name option is medically necessary.

Hellerstein uses data from the 1989 NAMCS, and finds that “30% of the unobserved (residual) variance in the prescription choice is physician-specific, rather than patient specific.” Does an individual’s health insurance influence the physician’s prescribing behavior? This paper finds that an individual’s health insurance does not influence prescribing decisions. However, “conditional on a patient’s insurance status, a patient who switches to a physician with a marginally greater fraction of HMO patients is 10.12% more likely to receive a generically written prescription.”

Summary

Why does the composition of the physician’s patient base seem to matter for Hellerstein (1998), but not for Marquis and Newhouse (1978) or Epstein, Begg and McNeil (NEJM 1986)? The main reason is likely that Hellerstein examines medical care in which physician do not receive any compensation. Physicians receive no more or less revenue from prescribing name brand compared to generic drugs and thus have no incentive to find out how they are being paid by each individual’s insurance company. On the other hand, Marquis and Newhouse found that hospital admissions, the length of the hospital stay, and the number of office visits is affected by an indvidiual’s health insurance variables since this type of medical care is high margin and high cost. Similarly, Epstein, Begg and McNeil (1986) found that how an individual’s insurance company compensates physicians matters for high margin, high cost EKGs and chest radiographs, but does not seem to matter for low margin, low cost blood counts and urinalyses.

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Physician Reimbursement and Technology adoption

December 3, 2007 in Academic Articles, Physician Compensation | Permalink

Economists and health researchers have generally shown that when doctors are paid on a fee-for-service basis, they will advice the patient to undergo more medical procedures than when the doctor is paid on a capitation or salaried basis (see my own paper: “Operating on Commission“). Which payment method maximizes welfare has not been proven and is likely to vary based on the medical procedure in question.

To add to the confusion, Astrid Selder writes in “Physician Reimbursement and Technology Adoption” that physician reimbursement mechanism may also affect the rate at which new technologies are adopted.

Selder lays out the following simple theoretical structure in which the social planner maximizes the following:

  • (1-π)U(Y-P)+πU(Y-P-acm-ε +G(m) -nm)
  • s.t.: P + πacm-%pi;R=πpm>=0
  • s.t.: R + (p-c)m>=0
  • s.t.: m<=B

The first constraints represent the zero-profit conditions for the insurer and the physician respectively and the third is a technology constraint. The probability of falling ill is π. Individuals have income Y, an insurance premium of P, and a coinsurance rate of a to may for the marginal cost, c, of a given level of medical treatment, m. Non monetary treatment costs (e.g.: side effects, time costs) are represented by the parameter n, while the benefits of the treatment are represented by the function G(m). The doctor receives a capitation payment of R and a marginal revenue amount given by p-c. B represents the technology constraint.

It seems obvious, but Selder shows that an increase in monetary medical costs (c) or non-medical costs (n) are welfare destroying. Technological innovations, represented as an increase in B are welfare improving if the technological constraint is binding or have no impact on welfare is the technological constraint is not binding. This results is intuitive: higher costs are bad, technological innovation is good.

This result, however, only holds when there is perfect information. With asymmetrical information, technological innovations may be welfare enhancing or welfare destroying. The welfare enhancing argument is similar to above: better technology leads to better medical care. If there is a moral hazard problem, however, using more basic technologies may actually help to counteract the tendency to over-consume medical care in the presence of insurance. Also, in the presence of moral hazard, technological innovations will cause insurance companies to charge higher premiums in order to cover the additional cost of this care.

How does the technological constraint, B, affect welfare in different physician compensation schemes?

  • “If B is a binding constraint and increases in B are welfare enhancing then a fee-for-service system should be used. Increases in B and reductions in [monetary medical costs] c are induced all of which are welfare improvements. Incentives with respect to [non-monetary costs] n cannot be improved upon.
  • If B is a binding constraint and increases in B are welfare reducing then a system of cost sharing [e.g.: capitation] should be implemented which induces reductions in B and c and gives no clearcut incentives with respect to n. Incentives with respect to B and c are thus optimal, and incentives with respect to n cannot be improved upon.
  • If B is not binding the optimal reimbursement system depends on the demand elasticities with respect to costs.”

In words:

“It has turned out that the state should classify diseases or treatments into subgroups which are reimbursed differently in order to achieve the desired welfare effects in each subgroup. Especially for the case of extremely severe illness shocks the introduction of a fee-for-service system may be socially desirable. It is these very severe diseases where the capitation system seems to induce negative welfare effects with respect to the technologically feasible boundary of treatment. Cost sharing/capitation systems are most suitable for treatments where a reduction of the amount of health care consumed is desirable.”

While the solution Selder proposes is logical, it does not take into account the cost to the state to collect information regarding these disease classes. Lobbying will likely influence whether a given treatment falls into the fee-for-service or cost-sharing grouping. Nevertheless, Selder’s general findings seems reasonable and applicable to the medical care finance design in the real world.

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