Title of Presentation - Collaborative Family Healthcare Association

Report
Session # D1b
Friday, October 17, 2014
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 Medicine
Medical School, Department of Family Medicine and Community Health
3Hennepin County Medical Center, Family Medicine Residency
2UMass
Collaborative Family Healthcare Association 16th Annual Conference
October 16-18, 2014
Washington, DC U.S.A.
Faculty Disclosure
We have not had any relevant financial relationships
during the past 12 months.
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.
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
40%
Williams et al, 2008)
35%
No-Show Rate
• Positive correlation between
no-show rates and delayed
care. (Folkins et al., 1980,
30%
25%
20%
15%
10%
5%
0%
<3 days 6-8 days
16-19
days
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
8:008:309:009:3010:0010:3011:0011:30-
8:008:309:009:3010:0010:3011:0011:30-
No Clinic
No Clinic
8:008:309:009:3010:0010:3011:0011:30-
Afternoon
1:001:302:002:303:003:304:00-
No Clinic
1:001:302:002:303:003:304:00-
1:001:302:002:303:003:304:00-
Admin
Evening
5:306:006:30-
No Clinic
No Clinic
No Clinic
No Clinic
Example
Session
Monday
Tuesday
Wednesday
Thursday
Friday
Morning
8:008:309:009:3010:0010:3011:0011:30-
8:008:309:009:3010:0010:3011:0011:30-
No Clinic
No Clinic
8:008:309:009:3010:0010:3011:0011:30-
Afternoon
1:001:302:002:303:003:304:00-
No Clinic
1:001:302:002:303:003:304:00-
1:001:302:002:303:003:304:00-
Admin
Evening
5:306:006:30-
No Clinic
No Clinic
No Clinic
No Clinic
Example
Session
Monday
Tuesday
Wednesday
Thursday
Friday
Morning
8:008:309:009:3010:0010:3011:0011:30-
8:008:309:009:3010:0010:3011:0011:30-
No Clinic
No Clinic
8:008:309:009:3010:0010:3011:0011:30-
Afternoon
1:001:302:002:303:003:304:00-
No Clinic
1:001:302:002:303:003:304:00-
1:001:302:002:303:003:304:00-
Admin
Evening
5:306:006:30-
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
90
80
85.4%
70
60
50
% Booked
55.6%
% Utilization
40
30
20
10
0
%No-Show
29.8%
Texas Tech University HSC, Family
Medicine Clinic
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?
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
Percentages
(3 Month)
70.0
60.0
50.0
40.0
30.0
% Utilization
60.4%
% No-Showed
20.0
10.0
25.6%
34.6% 31.4%
0.0
OSA
Traditional
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 Fellows
1 Pre-doctoral Intern
1 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
Provider 1, Percentages
(6 Months Pre, 8 Months Post)
90.0
85.3
80.0
70.0
66.1
60.0
50.0
52.2
40.0
42.8
30.0
20.0
10.0
24.1
% Booked
% Utilization
% Canceled
21.2
17.3
10.7
0.0
Pre-OSA
Post-OSA
% No-Showed
UMass Memorial
Hahnemann Family Health Center
Provider 1, Raw Data
(6 Months Pre, 8 Months Post)
160.0
140.0
134
120.0
Allocated
100.0
Booked
80.0
60.0
40.0
20.0
70.2
58
77
65.8
51
32
14
0.0
Pre-OSA (Average)
16
13
Post-OSA (Average)
Utilized
Canceled
No-Showed
UMass Memorial
Hahnemann Family Health Center
Provider 2, Percentages
(3 months pre, 8 months post)
100%
90%
86.34%
84.05%
80%
70%
%booked
63.35%
62.76%
60%
NSH%
50%
40%
30%
20%
% utilization
33.75%
26.79%
23.58%
20.48%
10%
0%
Pre-OSA
Average Percentage
Post-OSA
cancel%
UMass Memorial
Hahnemann Family Health Center
Provider 2, Raw Data
(3 months pre, 8 months post)
70
60
50
40
59.33
50
42.50
36
35.125
30
26.625
20
14.125
10
13.67
14
available
booked
arrived
canceled
no showed
8.375
0
Pre-OSA
Post-OSA
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
Lessons Learned
What is the most important
thing we learned about OAS
in our clinics?
Learning Assessment
Audience Question & Answer
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.
Session Evaluation
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to the classroom monitor before leaving this session.
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