FRN Research Report August 2013: “Would You Recommend Us?” – Recommendation Scores and Patient Confidence
Background
As part of its commitment to provide evidence-based, integrated treatment, Foundations collects internal and external data to assess its programs and learn ways to improve its services. Patient satisfaction data are regularly collected, including data from a hallmark question: “Would you recommend us?”
High recommendation rates indicate a strong level of confidence in a service. Patients who respond “yes” to the question, “Would you recommend us?” provide positive word-of-mouth marketing for the company. They are the main drivers of growth for a business (Reichheld, 2003).
FRN facilities consistently report that more than 70% of alumni would recommend the treatment center they attended to others. High recommendation scores also indicate a company’s ability to meet customer needs. Data from the recommendation question along with responses to other evidence-based surveys offer valuable insights into growing and improving FRN’s ability to meet and exceed patient needs as well as informing treatment protocols.
Evaluating Patient Satisfaction at FRN
Because FRN’s mission is to be the leader in evidence-based, integrated treatment for co-occurring mental health and substance use disorders through clinical services, education and research, FRN is pioneering the first satisfaction survey specific to addiction and mental health treatment. All FRN alumni are offered the opportunity to provide valuable feedback to the treatment center they attend. This is done using a 36-item satisfaction scale consisting of three global items that measure overall satisfaction and 33 items measuring specific aspects of treatment satisfaction. In addition to overall satisfaction, the specific aspects of treatment measured include the following:
- Clinical experience
- Professionalism
- Medical/psychiatric services
- Communication and consistency
- Program features
- Ancillary services
Currently in progress are evaluations to validate the properties of the instrument used to collect this information. FRN’s research department is expected to release the survey and this information for publication in early 2014.
Patient Satisfaction and Loyalty
Determining customer needs and choices is a cornerstone of evidence-based treatment (McKibbon, A.K. 1998). Customer needs and wants are important to companies, and the most successful companies collect and analyze data from their customers directly to determine how to meet these needs. Data are challenging to collect, however. There are several pitfalls surrounding effective data collection (Reichheld, 2003):
- Customers may be unwilling or unable to spend time responding to surveys
- Company employees may not have time to put collected data into a usable form
- Company employees may not be able to use the data to make decisions
FRN’s commitment to data collection and analyses extends to continuously looking for ways to improve services and exceed customer expectations. The FRN research department’s mission statement is to develop and communicate reliable, valid and timely information to support decision-making by consumers, clinicians and organizational leadership.
Asking patients if they would recommend the treatment center they attended to another person is a strong measure of customer loyalty. Being able to assess a company’s ability to meet or exceed customer standards is intrinsically valuable, and the majority of America’s most successful companies rely on these metrics for customer input. For example, Satmetrix Systems, Inc. looks at recommendation scores for many industries, including financial services, insurance, online services, retail, technology, telecommunications and travel and hospitality. Companies with the highest scores in 2012 were these: USAA, Amazon.com, Costco, Virgin America, Apple, Trader Joe’s and Wegmans (Satmetrix, 2013).
Companies with high customer loyalty levels, measured by positive responses to the recommendation question, are on track for positive growth. Companies that receive negative responses are failing to build loyalty and are setting themselves up to lose business.
Why is a positive recommendation so important? When a customer says she will recommend a business to others, the response is more meaningful than answers to other types of questions, such as “Do you agree that company X makes it easy for you to do business with it?” A customer who encourages her friends and family to use a business is putting her own reputation at risk, while a customer who says a company is easy to work with may not give it the same level of encouragement (Reichheld, 2003).
Our Findings: Recommendation Ratings and FRN Patients
Upon discharge from all Foundations Recovery Network treatment centers, patients are asked to complete a survey providing feedback to the organization about their experience. Nearly all patients complete this survey. Surveys are then used as part of an overall quality monitoring program.
When patients at FRN’s residential facilities are asked if they would recommend the program to others, most responses average between agree and strongly agree. Patients are asked to provide one of the five responses to the statement, “I would recommend this program to others.” The available responses are strongly agree, agree, neutral, disagree or strongly disagree. Patients also are asked to rate their overall experience at the facility on a 1 to 5 scale, with one being least satisfied and five being most satisfied.
Patient responses are provided for treatment at these FRN residential facilities: The Canyon at Peace Park, Michael’s House and La Paloma.
Our Findings: The Canyon at Peace Park
Patients at The Canyon reported the highest levels of recommendation out of all three residential facilities. The higher scores are due in part to patient appreciation of the staff members’ effective communication and consistency. The Canyon encourages longer lengths of stay for patients and the therapeutic relationships that are built between staff and patients during longer stays are thought to be strongly associated with The Canyon’s high performance on satisfaction surveys.
From 2011 to 2012, the percentage of patients who responded, “strongly agree,” to the question, “I would recommend this program to others,” rose 10 percentage points from 59.2% to 69.1%. Similarly, in rating their overall experience at The Canyon, the average rating was 4.25 in 2011 and climbed to 4.45 in 2012.
The following chart represents recommendation scores for The Canyon during 2012.
Our Findings: Michael’s House
Michael’s House scores are also on the rise, demonstrating FRN’s continued commitment to excellence. From 2011 to 2012, the percentage of Michael’s House patients who responded, “strongly agree,” to the question, “I would recommend this program to others,” rose 10 percentage points to 52.4%. When patients described their overall experience at Michael’s House, the average rating was 4.1 out of 5 in 2011 and 4.3 in 2012.
The following chart represents recommendation scores for Michael’s House during 2012.
Our Findings: La Paloma
Patients at La Paloma consistently report that they are likely to recommend La Paloma to others with 52.1% of patients reporting that they “strongly agree” with the statement, “I would recommend La Paloma to others.” When patients described their overall experience at La Paloma, responses averaged 4.1 in 2012. The facility’s consistent ratings from year to year are evidence of La Paloma’s ability to meet and exceed patient needs as part of their service commitment.
The following chart represents recommendation scores for La Paloma during 2012.
Our Findings: Average Ratings Across Facilities
Across all three facilities, FRN met goals to achieve an average score of 4, representing “agree.” These scores represent the realization of FRN’s strong commitment to providing patient-centered care that meets the needs and choices of those whose lives we serve. The following chart represents overall recommendation scores for December 2012.
Foundations Recovery Network’s Integrated Treatment Model
FRN uses an integrated treatment model that treats a person’s addiction along with any mental health disorders. Integrated treatment approaches are more effective and produce better long-term outcomes than addiction treatment alone. The model allows FRN staff members to coordinate care across all treatment areas and address all of a person’s needs concurrently (Drake, O’Neal, & Wallach, 2008). FRN believes in meeting patients where they are and addressing patient needs in an environment of collaboration and patient choice.
Researchers have recognized for more than two decades the importance of screening individuals who need addiction treatment for mental illness. The Substance Abuse and Mental Health Services Administration (SAMHSA), the World Health Organization (WHO) and other public health entities consider Dual Diagnosis treatment a best practice therapy (McGovern, Lambert-Harris, Gotham, Claus, & Xie, 2012).
FRN’s integrated treatment model sets it apart from many other treatment facilities and places it in the top 5% of addiction treatment programs according to the Dual Diagnosis Capability in Addiction Treatment (DDCAT) index assessment.
Conclusion
Patients who are willing to recommend an addiction treatment program to friends or family are giving the treatment center a strong vote of confidence. FRN’s commitment to tracking recommendation scores and other patient data gives the company the ability to improve across all service areas. FRN’s research department tracks satisfaction data as part of FRN’s continuing commitment to providing quality services that meet and exceed patient expectations.
A patient’s experience during addiction treatment is an important part of long-term recovery. Foundations Recovery Network’s expertise in identifying patient needs and wants helps staff members offer treatment superior to traditional methods.
Foundations Recovery Network is committed to research that improves treatment for all addicted individuals. If you would like to speak with an admissions coordinator today or if you would like to learn more about our research methods and programs, please call us directly at 615-490-9376.
References
Drake, R., O’Neal, E., & Wallach, M. (2008). A systematic review of psychosocial research on psychosocial interventions for people with co-occurring severe mental and substance use disorders. Journal of Substance Abuse Treatment, 34 (1), 123-138.
Hser, Y-I. (1997). Self-reported drug use: Results of selected empirical investigations of validity. In L. Harrison & H. Hughes (eds.), The validity of self-reported drug use: Improving the accuracy of survey estimates (NIH Publication No. 97-4147, pp. 320-343). Rockville, MD: U.S. Department of Health and Human Services.
McKibbon, A.K. “Evidence-based Practice.” Bulletin of the Medical Library Association,1998 July; 86(3): 396–401.
McGahan, P. L., Griffith, J. A., Parente, R., & McLellan, A. T. (1986). Addiction severity index: Composite scores manual. Philadelphia, PA: The University of Pennsylvania, Veterans Administration Center for Studies of Addiction.
McGovern, M. P., Lambert-Harris, C., Gotham, H., Claus, R., & Xie, H. (2012). Dual diagnosis capability in mental health and addiction treatment services: An assessment of programs across multiple state systems. Administration and Policy in Mental Health and Mental Health Services Research. Published online.
McGregor, J. (2006, January 29). Would you recommend us? Businessweek.
McLellan, A. T., Kushner, H., Metzger, D., Peters, R., Smith, I., Grisson, G., et al. (1992). The fifth edition of the addiction severity index. Journal of Substance Abuse Treatment, 9, 199–213.
McLellan, A.T., Cacciola, J.C., Alterman, A.I. Rikoon, S.H., Carise, D. (2006). The addiction severity index at 25: Origins, contributions and transitions. The American Journal on Addictions. 15 (2), 113-24.
Reichheld, F. F. (2003). The one number you need to grow. Harvard Business Review, 1-11.
Satmetrix. (2013). The net promoter score and system. Retrieved July 31, 2013, from Satmetrix.com: satmetrix.com
Van Doorn, J., Leeflang, P. S., & Tijs, M. (2013). Satisfaction as a predictor of future performance: A replication. International Journal of Research in Marketing, 30 (3), 314-318.
