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Successes and Challenges with the Expansion of Open Access Scheduling for Behavioral Health Across Integrated Care Settings David RM Trotter, PhD 1 Daniel.

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Presentation on theme: "Successes and Challenges with the Expansion of Open Access Scheduling for Behavioral Health Across Integrated Care Settings David RM Trotter, PhD 1 Daniel."— Presentation transcript:

1 Successes and Challenges with the Expansion of Open Access Scheduling for Behavioral Health Across Integrated Care Settings David RM Trotter, PhD 1 Daniel Mullin, PsyD 2 Christine Runyan, PhD 2 James Anderson, PhD 3 Jeanna Spannring, PhD 2 1 Texas Tech University Health Sciences Center, Department of Family and Community Medicine 2 UMass Medical School, Department of Family Medicine and Community Health 3 Hennepin County Medical Center, Family Medicine Residency Collaborative Family Healthcare Association 16 th Annual Conference October 16-18, 2014 Washington, DC U.S.A. Session # D1b Friday, October 17, 2014

2 Faculty Disclosure We have not had any relevant financial relationships during the past 12 months.

3 Objectives By the end of this talk, we hope you will be able to: Describe typical behavioral health no-show rates Describe the expansion of an open access schedule (OAS) system for BH providers into a diverse group of primary care health centers. Articulate three lessons learned about OAS through this expansion Estimate the potential impact of OAS on your behavioral health practice utilization rate.

4 One pressing problem The demand for behavioral health (BH) providers is outpacing the supply of professionals. Projected job growth, Psychologists Estimated number of new professionals: 16,400 Estimated number of new positions: 55,900 Clinical Social Workers Estimated number of new professionals: 26,000 Estimated number of new positions: 50,200 Masters Level Counselors: Estimated number of new professionals: 36,700 Estimated number of new positions: 64,000 (US Department of Labor Data: Retrieved on 10/9/2014 from:

5 An Opportunity for Quality Improvement: Our challenge! How can we improve our practice in ways that meet increasing demands? Our goal: To decrease the impact of “failed appointments” on our BH services Audience Assessment: In what ways do “failed appointments” impact your professional demands?

6 Background Wide range of no-show rates for mental health services: 30-75% no-show rate for initial appointments 20-60% no-show rate for follow-up appointments Positive correlation between no-show rates and delayed care. (Folkins et al., 1980, Williams et al, 2008)

7 Background Approximately 26% or missed appointments are the result of “Practical Matters.” (Defife et al., 2010)

8 Pilot Project: Barre, MA ( ) Goal: To create a patient-centered scheduling system that met the needs of our patients and increased access to care by reducing failed appointments. OAS in Barre, MA: Most appointments scheduled within 3 days of the visit All appointments were “frozen” more than 3 days in advance Patients were asked to schedule appointments when they want to be seen A few patients were allowed to “advanced book” appointments

9 Example SessionMondayTuesdayWednesdayThursdayFriday Morning 8:00- 8:30- 9:00- 9:30- 10:00- 10:30- 11:00- 11:30- 8:00- 8:30- 9:00- 9:30- 10:00- 10:30- 11:00- 11:30- No Clinic 8:00- 8:30- 9:00- 9:30- 10:00- 10:30- 11:00- 11:30- Afternoon 1:00- 1:30- 2:00- 2:30- 3:00- 3:30- 4:00- No Clinic 1:00- 1:30- 2:00- 2:30- 3:00- 3:30- 4:00- 1:00- 1:30- 2:00- 2:30- 3:00- 3:30- 4:00- Admin Evening 5:30- 6:00- 6:30- No Clinic

10 Example SessionMondayTuesdayWednesdayThursdayFriday Morning 8:00- 8:30- 9:00- 9:30- 10:00- 10:30- 11:00- 11:30- 8:00- 8:30- 9:00- 9:30- 10:00- 10:30- 11:00- 11:30- No Clinic 8:00- 8:30- 9:00- 9:30- 10:00- 10:30- 11:00- 11:30- Afternoon 1:00- 1:30- 2:00- 2:30- 3:00- 3:30- 4:00- No Clinic 1:00- 1:30- 2:00- 2:30- 3:00- 3:30- 4:00- 1:00- 1:30- 2:00- 2:30- 3:00- 3:30- 4:00- Admin Evening 5:30- 6:00- 6:30- No Clinic

11 Example SessionMondayTuesdayWednesdayThursdayFriday Morning 8:00- 8:30- 9:00- 9:30- 10:00- 10:30- 11:00- 11:30- 8:00- 8:30- 9:00- 9:30- 10:00- 10:30- 11:00- 11:30- No Clinic 8:00- 8:30- 9:00- 9:30- 10:00- 10:30- 11:00- 11:30- Afternoon 1:00- 1:30- 2:00- 2:30- 3:00- 3:30- 4:00- No Clinic 1:00- 1:30- 2:00- 2:30- 3:00- 3:30- 4:00- 1:00- 1:30- 2:00- 2:30- 3:00- 3:30- 4:00- Admin Evening 5:30- 6:00- 6:30- No Clinic

12 Pilot Data Provider 1: Utilization increase from 58.6% to 68.5% No-Shows decreased from 22.4% to 18.3% Cancelations decreased from 16.8% to 11.4% Provider 2: Utilization increase from 61.5% to 62.6% No-Shows decreased from 18.4% to 14.3% Cancelations decreased from 15.7% to 9.8% In summary: Both providers witnessed a 10% increase in utilization or availability

13 Expansion Project Goal: To demonstrate the portability of the OSA system for behavioral health in a diverse set of primary care health centers 3 Clinical Sites: Texas Tech Family Medicine Clinic, Lubbock, TX Hennepin County Medical Center, Minneapolis, MN Hahnemann Family Health Center, Worchester, MA

14 Texas Tech University HSC, Family Medicine Clinic Providers: 15 Attending Physicians, 29 Residents, 1 RD, 1 Acupuncturist, 1 BH Provider Issues Relevant to OSA implementation: – Previous OAS system for physicians – Physicians use a “traditional” scheduling model

15 Texas Tech University HSC, Family Medicine Clinic Guidelines for Booking – 7 appointment slots available each ½ day clinic – Follow-Up Appointments booked via OAS 5 “Frozen Slots” thaw 7 days in advance 2 “Frozen Slots” thaw 1 day in advance – Providers can authorize advanced booking

16 Texas Tech University HSC, Family Medicine Clinic

17 Lessons Learned Successes: Availability for same day access to care Positive feedback from patients and providers Needed Adjustments Labor intensive process: How can I monitor OAS drift? Critical Issues Can OSA work in the context of a low BHC to patient ratio?

18 Hennepin County Medical Center Guidelines for booking: – Each session contains eight, 30-minute slots – Schedule opens 8 days before day in question E.G., on Monday, 10/13, the Monday, 10/20 schedule will open – Dr. Anderson can schedule patients further out at his discretion

19 Hennepin County Medical Center Implementation process: – Worked closely with clinic manager – Differs from physician schedule Unfreezing schedule Appointment duration – No clear data on patient satisfaction Seems may be more patient-centered for new vs. established patients

20 Hennepin County Medical Center

21 Lessons learned: – Clinical lore challenges data – No clear data on patient satisfaction Seems may be more patient-centered for new vs. established patients – Must keep advocating for maintenance

22 UMass Memorial Hahnemann Family Health Center Urban Academic Health Center (Primarily serving Medicaid population) 13 Faculty (2 NPs, 2 BH Providers, 9 MDs) 12 Residents (4 per PGY) Additional BH: (1.5) – 3 Post-doctoral Fellows 1 Pre-doctoral Intern 1 Practicum student

23 UMass Memorial Hahnemann Family Health Center October 2013 Implemented Open Access Schedules frozen until 3 days prior Any provider could override the freeze and schedule a patient Instructed patients to the change and when to call vis-à-vis the agreed upon duration before next visit No open access for MDs when we began open access – More recently, one medical provider designated for same day acute care/urgent visits for the session

24 UMass Memorial, Hahnemann Family Health Center

25 UMass Memorial Hahnemann Family Health Center

26

27

28 Successes: – Excellent access for new patients – Providers were pleased at ease of quick scheduling Needed Adjustments: – Because of part time BH providers, 3 days was hard for patients to judge because they do not know our schedules (days in and out of clinic) – Frustrating process at time b/c of phones Where We Are Now: – Determined one week thawing was preferable for patients – Remains to be seen how this impacts no show rates/cancelations/utilization

29 Lessons Learned What is the most important thing we learned about OAS in our clinics?

30 Learning Assessment Audience Question & Answer

31 References Berg, B., Murr, M., Chermak, D., Wolldall, J., Pignone, M., Sandler, D., & Denton, B. (2013). Estimating the Cost of No-Shows and Evaluating the Effects of Mitigation Strategies. Medical Decision Making (Online only, Downloaded from mdm.sagepub.com on 10/7/2013) Defife, J., Conklin, C., Smith, J., & Poole, J. (2010). Psychotherapy Appiontment No-shows; Rates and Reasons. Psychotherapy Theory, Research, Practice, Training 47(3), Folkins, C., Hersch, P., Dahlen, D. (1980). Waiting time and No-Show Rate in a Community Mental Health Center. American Journal of Community Psychology, 8(1), Guck, T., Guck, A., Brack, A., Frey, D. (2007). No-Show Rates in Partially Integrated Models of Behavioral Health Care in a Primary Care Setting. Families, Systems, and Health, 25(2), Macharia, W., Leon, G., Roewe, B., Stephenson, B., & Haynes, R. (1992). An overview of interventions to improve compliance with appointment keeping for medical services. Journal of the American Medical Association, 267, Patrick, J. (2011). A Markov Decision Model for Determining Optimal Outpatient Scheduling. Health Care Management Science 15(2), Rose, K., Ross, J., & Horwitz, L. (2011). Advanced Assess Scheduling Outcomes. Archives of Internal Medicine 171(13), US Department of Labor, Bureau of Labor Statistics. Retrieved from on 10/9/2014http://data.bls.gov/projections/occupationProj Westra, H., Boardman, C., & Moran-Tynski, S. (2000). Regarding The impact of providing preassesssment information on no-show rates. Canadian Journal of Psychiatry, 6, 1-2. Williams, M. E., Latta, J., & Conversano, P. (2008). Eliminating the wait for mental health services. The Journal of Behavioral Health Services and Research, 35(1), 107–114.

32 Session Evaluation Please complete and return the evaluation form to the classroom monitor before leaving this session. Thank you!


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