Assessing new patient access to mental health providers in HMO networks

Psychiatr Serv. 2008 Dec;59(12):1413-8. doi: 10.1176/ps.2008.59.12.1413.

Abstract

Objective: This study examined access to mental health providers in health maintenance organization (HMO) networks.

Methods: A telephone survey was conducted with a stratified random sample of mental health providers listed as being in a network for at lease one of six HMOs operating in Connecticut (response rate=72%; N=366). Data were collected between December 2006 and March 2007. Measures included the accuracy of network listings, acceptance rates of new patients, and reasons for not accepting new patients. Acceptance of new patients was defined as scheduling an appointment within two weeks from the time of the initial contact. Logistic regression was used to examine acceptance rates of new patients while controlling for type of provider (social worker, nurse, psychologist, or psychiatrist) and practice characteristics.

Results: Findings indicate that 17% of sampled HMO network listings were inaccurate. Among the providers with an accurate listing, 73% were accepting new HMO patients and 76% were accepting new self-pay patients. These aggregate acceptance rates of new patients mask differences among providers, with psychiatrists significantly less likely than other providers to accept new patients (55% of psychiatrists were accepting new patients). The most common reason for not accepting new patients was the lack of available appointments.

Conclusion: Results indicate that access to mental health providers in HMO networks varied by type of provider. For HMO enrollees seeking treatment for mental health problems from a provider with a master's degree in social work (M.S.W. degree), network access was not a major problem. Scheduling an appointment with a psychiatrist, particularly a psychiatrist treating children only, was more difficult.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Connecticut
  • Health Maintenance Organizations
  • Health Services Accessibility*
  • Humans
  • Interviews as Topic
  • Logistic Models
  • Mental Health Services*