Calls for Help: Examining Scheduling Processes and Barriers in Addiction Treatment

The Affordable Care Act (ACA) makes substance abuse treatment available to millions of new patients. Substance abuse treatment will be considered an “essential service,” which means that health plans will be required to provide it. More options for prevention and treatment will be available to more people than ever before.

With full implementation of the ACA, coverage of substance abuse disorders is likely to be comparable to that of other chronic illnesses such as hypertension, asthma, and diabetes. According to the Substance Abuse and Mental Health Services Administration (SAMHSA), over thirty million previously uninsured people will be eligible for coverage (2011).

SAMHSA, along with other federal agencies and national associations that train and support substance abuse treatment providers, has been encouraging treatment organizations to examine their business processes to ensure that they have the capacity to treat more clients. Treatment providers who have heeded this advice are taking a closer look at their business models as well as their ability to take advantage of new reimbursement options that include third-party payers rather than block grants. Many are learning how to market their services for the first time, both to potential payers and to behavioral health care consumers. Developing efficient systems for getting eligible consumers enrolled in a health care plan is a high priority, as is implementing health information technology systems.

While the ACA removes one of the most significant barriers to substance abuse treatment—the lack of health insurance coverage—other barriers persist. One barrier that is often overlooked is the phone scheduling system that patients encounter when seeking addiction treatment.

NIATx 200, a study of organizational change in health care, took a look at phone scheduling systems in substance abuse treatment organizations. Researchers made more than six thousand phone calls to 201 treatment organizations in five states to get a better idea of what patients experience when they call a treatment agency seeking help for a substance use disorder. The results of this examination have implications for treatment providers to consider as they adjust to the changes underway with full implementation of the ACA.

NIATx, formerly the Network for the Improvement of Addiction Treatment, is a process improvement and research collaborative based at the University of Wisconsin-Madison. As part of the Center for Health Enhancement Systems Studies, NIATx is dedicated to improving the quality of behavioral health services.

Founded in 2003 and led by Dr. David H. Gustafson, NIATx works with behavioral health organizations to help them get more people into treatment, and keep them in treatment long enough to experience the benefits of recovery. NIATx resulted from two national initiatives: Paths to Recovery, funded by the Robert Wood Johnson Foundation, and Strengthening Treatment Access and Retention, funded by SAMHSA’s Center for Substance Abuse Treatment. In these two projects, thirty-nine organizations followed the NIATx model of process improvement to change the business practices that were making it hard for them to deliver good care (McCarty et al., 2007).

NIATx 200 built on the success of the thirty-nine providers in the first NIATx projects. This randomized controlled trial, funded by the National Institute on Drug Abuse (NIDA), aimed to evaluate the cost-effectiveness of different components of the NIATx process improvement model and at the same time, test dissemination of the NIATx model on a wider scale (Quanbeck et al., 2011). The project enrolled 201 clinics across five states. Massachusetts recruited forty-three clinics; Michigan, forty-two; New York, forty-one; Oregon, thirty-seven; and Washington, thirty-eight. The majority of the clinics (81 percent) were private, nonprofit, community addiction treatment agencies. Most (54 percent) were freestanding clinics. Overall, median clinic admissions were 339 per year and the clinics treated a patient population that was 29 percent non-white, non-Hispanic. Recruitment efforts were targeted at nonprofit organizations; only three of the recruited clinics were for-profit. Each of the 201 agencies was randomly assigned to one of four study groups, each with a different combination of NIATx services, to determine which combination of services produced the greatest improvement for the economic investment.

Providers committed to an eighteen-month engagement in which they participated in the services provided to their randomly assigned study group. At the same time, they tested promising practices, collected and reported their data, and responded to questionnaires and surveys. The participating providers, with support from their SSA, focused their efforts in three areas: providing same-day treatment, increasing client continuation in treatment, and transitioning clients between levels of care.

To track progress on one of the study goals, reducing waiting time, researchers began to call participating treatment agencies to record when a prospective client first calls about treatment. Identifying themselves as NIATx 200 staff, the researchers said they wanted to know the agency’s next available appointment for a patient with a specific profile: a woman, not pregnant, without insurance, seeking help with an alcohol or drug problem. The date of the call and the date of the first available appointment were recorded for each clinic every month. Waiting time was defined as time from contact to appointment, corresponding to the difference in calendar days between the date of the first available appointment and the date the appointment was made, which could be the date of a return call from the clinic or the last call placed by a researcher, if multiple calls were required. Researchers called clinics during standard business hours—9 am to 4 pm, Monday through Friday—adjusted for each clinic’s time zone. The day of the month that the first call was placed to each clinic was varied randomly, so the same clinic wasn’t called on the same date every month.

Early in the data collection process, the research team was surprised that phone calls often went unanswered, and multiple callbacks were required to collect data. If calls or messages went unanswered, researchers called clinics up to seven times per month until an appointment date could be confirmed. Six months into the project, a field was added to the researchers’ database to record the date of each attempt to reach clinics, enabling a count of the monthly callbacks required to schedule an appointment. The researchers noted the reasons for unanswered calls.

Over twenty-seven months, the researchers made and tracked data on more than six thousand calls. This dataset provides an unprecedented opportunity to examine phone scheduling systems in addiction treatment. Placing thousands of phone calls to clinics revealed a picture of what it is like for patients to access treatment.

At baseline, average waiting time from contact to first appointment across all clinics waiting time from contact to the first appointment was 7.26 days; it ranged from zero days (patients could walk in at any time) to thirty-eight days. While it is impossible to say exactly how long is “too long” for a patient to wait, the research suggests that getting patients into treatment quickly is clinically important (Appel, Ellison, Jansky, & Oldak, 2004; Best et al., 2002). Delaying access by days or weeks for patients seeking urgent medical treatment would not be tolerated, and such delays are difficult to reconcile with the idea that addiction can be a life-threatening medical condition that deserves immediate attention. Patients with addiction may lose their motivation for recovery before a treatment slot opens, and some addicted patients view waiting lists as an indication of the view society has of them (Battjes, Onken, & Delany, 1999; Redko, Rapp, & Carlson, 2006).

Clinics’ phone scheduling processes should facilitate rather than impede getting into treatment. From a patient’s perspective, the desired result of the first call is getting an appointment as easily as possible, without having to call several times or wait for a return phone call. The researchers made 804 additional callbacks to obtain appointment information when they were unable to talk to a staff member, leave a message, or get a message returned. The results suggest that nearly half of the time (47 percent), a patient’s first phone call is met by voicemail or not answered at all, leaving the patient waiting for a return call or forced to call back. In these instances, the researchers noted reasons that multiple calls were required. Examples of these reasons included clinics whose phone lines were busy; clinics that left calls unanswered for ten or more rings without going to voicemail; clinics using dysfunctional voicemail systems that made it impossible to leave messages; clinics that repeatedly instructed callers to call back because the person responsible for making appointments was unavailable; and clinics putting the researcher on hold for more than ten minutes. An example of the process encountered in one of the clinics requiring the most callbacks further illustrates the types of problems encountered by the researchers:

While this example is extreme, phone scheduling problems that could hinder patient access were fairly widespread; thirty-four of 192 clinics (18 percent of the sample) averaged at least one callback for each monthly attempt to request an appointment. The research team encountered severe access problems in several clinics, but these were relatively isolated cases. Six of 192 clinics (3 percent) averaged more than two callbacks per month, and were rarely if ever reachable with one phone call. In cases such as the example above, problems remained unresolved and perhaps undetected for several months, even though the problems might be easily remedied once identified. Encouragingly, forty-three of 192 clinics (22 percent) had “perfect” phone access over the evaluation period, meaning that nine out of nine appointment requests were fulfilled with one phone call.

The undertaking left the research team with the distinct impression that the quality of clinics’ phone scheduling processes varied, an observation consistent with anecdotal reports made in other evaluations (Capoccia et al., 2007; Ford et al., 2007; McCarty et al., 2007; Hoffman, Ford, Choi, Gustafson, & McCarty, 2008). Quality is a difficult concept to define in health care and often a matter of subjective perception. For example, measures such as “patient satisfaction” provide a numerical basis for assessing quality, but still rely upon subjective ratings of experience. Previously, phone scheduling processes in addiction treatment have been subjectively described. The results described here confirm the existence of problems in clinics’ phone scheduling systems and indicate a range of responses across clinics in both waiting time and phone access. In their qualitative analysis, Ford et al. (2007) report that 30 percent of clinics had problems with phone access or first contact; this rate was based on content analysis of written reports, so the methods are quite different from those employed in this study. However, the rate and types of problems reported in Ford et al.’s (2007) study are fairly consistent with results reported here. Our results suggest that the majority of clinics studied provide reasonably good service, while a relative handful of clinics have significant room to improve on one or both measures.

NIATx 200 participants had access to a secure website that offered a variety of process improvement information, tools, and promising practices. A team of expert NIATx coaches developed the promising practices specifically for the NIATx 200 project. These practices, which were designed for use in the study, are now available to the general public.

The promising practices to reduce waiting time such as “establish walk-in hours,” “centralize appointment scheduling,” and “make appointments during the first call” offer guidance on ways to improve the phone scheduling system and thwart some of the delays to treatment that researchers encountered when attempting to schedule an appointment. These promising practices also include examples of specific actions other organizations have taken to improve their phone scheduling systems. For example:

• St. Christopher’s Inn in Garrison, New York answered more than 80 percent of calls live and returned phone calls within ten minutes by prioritizing incoming phone calls. They changed their phone routing system so that callers are presented with three options in priority order: if seeking treatment (press 1), if a referring agency (press 2), and if seeking information (press 3). They answered priority 1 calls live whenever possible and returned priority 2 and 3 calls, if necessary. They staggered admissions office lunch schedules so that someone was always available to answer phones during the lunch hour.

 

• Kentucky River Community Care in Jackson, Kentucky decreased the call volume in the front office from one thousand to 150 calls per day by providing a direct line for clients requesting an appointment, relocating the switchboard to a private area, and routing clinical and business calls to different locations. These changes decreased the number of clients who needed to leave a voicemail, were told to call back later or were transferred to another extension, to zero. Clients calling for an appointment now reach the appointment scheduler directly and front office staff has more time to focus on clients who are actually in the office (NIATx, 2009).

 

While NIATx 200 concluded in 2010, and improvements in telephone technology have the potential to make it easier for patients to connect with a treatment agency without encountering a busy signal or an endless series of voicemail prompts, phone access and scheduling systems remain areas in need of continual improvement. When training organizations in the NIATx model, coaches typically task organizations with calling their own agencies to schedule an intake appointment. “Organizations we coach today are just as surprised as the ones we trained in 2003 to discover that their phones often go unanswered,” says NIATx coach Elizabeth Strauss (M. Fitzgerald, personal communication, February 26, 2014). She continues to stress the need for staff to actively try to put themselves in their patients’ shoes, and experiencing agency processes firsthand, rather than glossing over potentially significant obstacles and assuming you know what patients experience.

This article presents a method for measuring waiting time and phone access to addiction treatment based on methods used in primary care clinics (Murray & Berwick, 2003). The method is relatively easy to employ and may be useful for addiction treatment clinics, policymakers, and payers in assessing the quality of phone scheduling processes. The results confirm the existence of phone access problems that can hinder access to treatment—in previous research, evidence of these problems has been largely anecdotal or based on isolated examples—and provide an indication of their prevalence. The initial phone call a patient places to request help with addiction may be the most important call that person ever makes. Clinics that make patients call multiple times and wait for extended periods for their appointment have opportunities to improve their services.

As consumers in everyday life, we generally expect responsive customer service from the organizations we patronize. Organizations must continually examine their processes to uncover barriers to treatment. Leaders of addiction treatment clinics are encouraged to pick up the phone to experience what it is really like to seek treatment in their organizations. Experiencing the scheduling process as a patient can provide an expedient method for exposing organizational problems that can be rectified through quality improvement.

Appel, P. W., Ellison, A. A., Jansky, H. K., & Oldak, R. (2004). Barriers to enrollment in drug abuse treatment and suggestions for reducing them: Opinions of drug injecting street outreach clients and other system stakeholders. American Journal of Drug and Alcohol Abuse, 30(1), 129–53.

Battjes, R. J., Onken, L. S., Delany, P. J. (1999). Drug abuse treatment entry and engagement: Report of a meeting on treatment readiness. Journal of Clinical Psychology, 55(5), 643–57.

Best, D., Noble, A., Ridge, G., Gossop, M., Farrell, M., & Strang, J. (2002). The relative impact of waiting time and treatment entry on drug and alcohol use. Addiction Biology, 7(1), 67–74.

Capoccia, V. A., Cotter, F., Gustafson, D. H., Cassidy, E. F., Ford, J. H., II, Madden, L., . . . Molfenter, T. (2007). Making “stone soup”: Improvements in clinic access and retention in addiction treatment. Joint Commission Journal on Quality and Patient Safety, 33(2), 95–103.

Ford, J. H., II, Green, C. A., Hoffman, K. A., Wisdom, J. P., Riley, K. J., Bergmann, L., & Molfenter, T. (2007). Process improvement needs in addiction treatment: Admissions walkthrough results. Journal of Substance Abuse Treatment, 33(4), 379–89.

Hoffman, K. A., Ford, J. H., II, Choi, D., Gustafson, D. H., & McCarty, D. (2008). Replication and sustainability of improved access and retention within the Network for the Improvement of Addiction Treatment. Drug and Alcohol Dependence, 98(1–2), 63–9.

McCarty, D., Gustafson, D. H., Wisdom, J. P., Ford, J. H., II, Choi, D., Molfenter, T., . . . Cotter, F. (2007). The Network for the Improvement of Addiction Treatment (NIATx): Enhancing access and retention. Drug and Alcohol Dependence, 88(2–3), 138–45.

Murray, M., & Berwick, D. M. (2003). Advanced access: Reducing waiting and delays in primary care. JAMA, 289(8), 1035–40.

Network for the Improvement of Addiction Treatment (NIATx). (2009). Promising practice: Making appointments during the first call. Retrieved from http://www.niatx.net/toolkits/provider/PP_MakeAppointmentsFirstCall.pdf

Quanbeck, A. R., Gustafson, D. H., Ford, J. H., II, Pulvermacher, A., French, M. T., McConnell, K. J., & McCarty, D. (2011). Disseminating quality improvement: Study protocol for a large cluster randomized trial. Implementation Science, 6, 44.

Quanbeck, A., Wheelock, A., Ford, J. H., II, Pulvermacher, A., Capoccia, V., & Gustafson, D. (2013). Examining access to addiction treatment: scheduling processes and barriers. Journal of Substance Abuse Treatment, 44(3): 343–8.

Redko, C., Rapp, R. C., & Carlson, R. G. (2006). Waiting time as a barrier to treatment entry: Perceptions of substance users. Journal of Drug Issues, 36(4), 831–52.

Substance Abuse and Mental Health Services Administration (SAMHSA). (2011). SAMHSA strategic initiatives fact sheet. Retrieved from http://store.samhsa.gov/shin/content//SMA11-4666/SMA11-4666.pdf

Editor’s Note: This article was adapted from an article by the same authors previously published in the Journal of Substance Abuse Treatment (JSAT). This article has been adapted as part of Counselor’s memorandum of agreement with JSAT. The following citation provides the original source of the article:

Quanbeck, A., Wheelock, A., Ford, J. H., II, Pulvermacher, A., Capoccia, V., & Gustafson, D. (2013). Examining access to addiction treatment: scheduling processes and barriers. Journal of Substance Abuse Treatment, 44(3): 343–8.