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This paper examines services in which customers encounter a gatekeeper who makes an initial diagnosis of the customer's problem and then may refer the customer to a specialist. The gatekeeper may also attempt to solve the problem, but the probability of treatment success decreases as the problem's complexity increases. Given the costs of treatment by the gatekeeper and the specialist, we find the firm's optimal referral rate from a particular gatekeeper to the specialists. We then consider the principal-agent problem that arises when the gatekeeper, but not the firm, observes the gatekeeper's treatment ability as well as the complexity of each customer's problem. We examine the relative benefits of compensation systems designed to overcome the effects of this information asymmetry and show that bonuses based solely on referral rates do not always ensure first-best system performance and that an appropriate bonus based on customer volume may be necessary as well. We also consider the value of such output-based contracts when gatekeepers are heterogeneous in ability, so that two gatekeeper types face different probabilities of treatment success when given the same problem. We show that the firm may achieve first-best performance by either offering two contracts that separate the gatekeeper types or by offering a single contract that coordinates the treatment decisions of both gatekeepers.