David RM Trotter, PhD 1 Daniel Mullin, PsyD 2 Christine Runyan , PhD 2 James Anderson, PhD 3
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Transcript of David RM Trotter, PhD 1 Daniel Mullin, PsyD 2 Christine Runyan , PhD 2 James Anderson, PhD 3
Successes and Challenges with the Expansion of Open Access Scheduling for Behavioral Health Across Integrated Care Settings
David RM Trotter, PhD1
Daniel Mullin, PsyD2
Christine Runyan, PhD2
James Anderson, PhD3
Jeanna Spannring, PhD2
1Texas Tech University Health Sciences Center, Department of Family and Community Medicine2UMass Medical School, Department of Family Medicine and Community Health3Hennepin County Medical Center, Family Medicine Residency
Collaborative Family Healthcare Association 16th Annual ConferenceOctober 16-18, 2014 Washington, DC U.S.A.
Session # D1b Friday, October 17, 2014
ObjectivesBy 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.
One pressing problem
• The demand for behavioral health (BH) providers is outpacing the supply of professionals.
• Projected job growth, 2012-2022• 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: http://data.bls.gov/projections/occupationProj)
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?
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)
<3 days 6-8 days 16-19 days
0%
5%
10%
15%
20%
25%
30%
35%
40%
No-
Show
Rat
e
Background• Approximately 26% or missed appointments are
the result of “Practical Matters.” (Defife et al., 2010)
Pilot Project: Barre, MA (2012-2013)
• 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
Example
Session Monday Tuesday Wednesday Thursday Friday
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 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 No Clinic No Clinic No Clinic
Example
Session Monday Tuesday Wednesday Thursday Friday
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 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 No Clinic No Clinic No Clinic
Example
Session Monday Tuesday Wednesday Thursday Friday
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 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 No Clinic No Clinic No Clinic
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
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
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
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
Texas Tech University HSC, Family Medicine Clinic
Series10
10
20
30
40
50
60
70
80
90
85.4%
55.6%
29.8%
% Booked% Utilization%No-Show
Texas Tech University HSC, Family Medicine Clinic
Lessons LearnedSuccesses:
• Availability for same day access to care• Positive feedback from patients and providersNeeded 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?
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
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
Hennepin County Medical Center
OSA Traditional0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
60.4%
34.6%25.6% 31.4%
Percentages (3 Month)
% Utilization% No-Showed
Hennepin County Medical Center
• 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
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 Fellows1 Pre-doctoral Intern1 Practicum student
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
UMass Memorial, Hahnemann Family Health Center
Pre-OSA Post-OSA0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
52.2
85.3
42.8
66.1
24.1 21.2
10.717.3
Provider 1, Percentages (6 Months Pre, 8 Months Post)
% Booked% Utilization% Canceled% No-Showed
UMass MemorialHahnemann Family Health Center
Pre-OSA (Average) Post-OSA (Average)0.0
20.0
40.0
60.0
80.0
100.0
120.0
140.0
160.0
134
7770.2 65.858 51
32
1614 13
Provider 1, Raw Data (6 Months Pre, 8 Months Post)
AllocatedBookedUtilizedCanceledNo-Showed
UMass Memorial Hahnemann Family Health Center
Pre-OSA Post-OSA0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%86.34% 84.05%
62.76% 63.35%
23.58% 20.48%26.79%
33.75%
Provider 2, Percentages(3 months pre, 8 months post)
%booked % utilization
NSH% cancel%
Average Percentage
UMass MemorialHahnemann Family Health Center
Pre-OSA Post-OSA0
10
20
30
40
50
60
7059.33
42.50
50
35.12536
26.625
13.6666666666667 14.125
148.375
Provider 2, Raw Data(3 months pre, 8 months post)
availablebookedarrivedcanceledno showed
Monthly Average
UMass Memorial Hahnemann Family Health Center
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
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), 413-417.
• 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), 121-123.
• 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), 137-146.
• 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, 1813-1817.
• Patrick, J. (2011). A Markov Decision Model for Determining Optimal Outpatient Scheduling. Health Care Management Science 15(2), 91-102
• Rose, K., Ross, J., & Horwitz, L. (2011). Advanced Assess Scheduling Outcomes. Archives of Internal Medicine 171(13), 1150-1159.
• US Department of Labor, Bureau of Labor Statistics. Retrieved from http://data.bls.gov/projections/occupationProj on 10/9/2014
• 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.