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SW 6942
MARTIN HAMMAR
“Patient attendance and no-show behavior in the
Primary Care setting”
NO ONE LIKES “NO SHOWS”
MOTIVATION (OUR DEPENDENT VARIABLE) IS OPERATIONALIZED BY ATTENDANCE AND NO-SHOW RATES
1. The intervention will improve patient attendance and decrease patient no-show
2. Satisfied patients will be more motivated to return.3. The more health problems you have, the more likely
you’ll come back, but not necessarily for chronic problems.
4. The more someone reminds you about your appointment, the more likely you’ll keep it.
5. It doesn’t matter how many times you’re told about the “attendance & no-show” policies, if you make it/you make it.
6. The farther you have to go, or if someone else is sending you, or paying the tab, the less likely you’ll be motivated to attend appointments, and more likely you’ll no-show.
7. Looking at certain demographics including marital status, age, gender, and income level, there’s a good bet you’ll blow off your appointment.
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No-Show Scheduled
FHI Scheduled Appointments & No-Show 2012/2013
Behavioral Health Consultant (BHC) Intervention Protocol
Information From medical record Patient self-report
Patient identifier #:
Control or Experimental Group
Initial Survey appointment date
Numbers of days between follow-up
appointment:
Number of clinic visits past 36 months
Number of unexcused no-show
appointments:
Number of excused/cancelled
appointments:
Age:
Race/Ethnicity:
Marital Status:
Income Range:
(based on sliding fee scale at FHI)
Payor Source:
Proximity from clinic
(in miles radius)
Mode of Transportation
Telephone – landline/mobile/both
Internet access – home/mobile/public
Number of diagnosed health problems from
last 3 clinic visits:
Number of chronic/persistent health
complaints (diagnosed/treated):
CSQ-8 score
(initial survey completed: ____/____/____)
CSQ-8 score
(second survey completed: ____/____/____)
Considerable demographic information was missing in the
paper chart & not everything
that was useful was transferred
to the EMR.
Table 1
Selected Nominal Level Variables of Study Group N=19 Frequency (Percent) Gender
Male 4 (21.1) Female 15 (78.9)
Marital Status
Married 6 (31.6) Un-Married 13 (68.4)
Sliding Fee Eligible
100% 12 (63.2) 75% 4 (21.1) 50% 0 (00.0) 25% 0 (00.0)
*Full pay 3 (15.8) Insurer type
Medicaid 4 (21.1) Medicare/Medicaid 5 (26.3)
Private 4 (21.1) Self-Pay 6 (31.6)
*Not enrolled defaults to full pay
Table 2 Mean Scores of Demographic Variables of the Study Group
N
Range
Mean (SD)
Age 19 21-68 44.11 (13.64)
Proximity (tenths of miles) 19 0.3-15.6 5.9 (5.6)
# Visits in previous 36 months 19 2-46 17.53(14.8)
# Diagnosed Health Problems 19 1-11 4.95(2.505)
# Chronic Health Problems 19 1-5 2.37(1.116)
# Prior Canceled Appointments 19 0-9 1.74(2.182)
# Prior No Shows 19 0-8 1.89(1.883)
# Days to 1st Follow-up 15 12-98 31.13(22.257)
# Outreach Attempts 13 1-4 2.08(0.954)
# Problems Keeping Appts. 10 0-2 0.7(0.675)
# Problems Helped 10 0-2 0.6(0.699)
# Questions Asked 10 0-1 0.1(0.316)
Total Intervention Time in Min. 10 2-9 5.6(2.011)
Experimental Group Intervention Procedures:
Call the patient at the current phone number and verify identity. “Hello, my name is Martin
Hammar, I am calling for <patient’s name>, who am I talking to right now? If not the patient,
then ask: “Can I speak with <patient’s name>? Ask: “Is this <patient’s name>?” If “yes,”
proceed to next section. If “no,” then tell the person “Thank you, I will try later.”
Note: date/time of call ___________ ; # of attempts _____; days before appointment _______.
Introduce yourself to the patient explaining: “I am the social worker from the clinic conducting a
follow-up phone call as part of the satisfaction survey you completed and returned during the
your last appointment.”
Get permission to continue the conversation and explain: “I would like to ask you a few more
questions?”
Explain: “This will only take a few moments to complete and I will be asking you some questions
related to what you understand about your care.”
Begin interview questions:
1. “Did you get a follow-up appointment when you left the clinic?” Yes / No
If “no,” ask: “Were you instructed to schedule a follow-up?” Yes / No
< If “yes,” offer to assist the patient with scheduling a follow-up appointment. >
2. “Can you tell me when your next appointment is scheduled?” Yes / No
< Verify if this is accurate & correct any scheduling discrepancies. >
< Provide the correct appointment information & ask the patient to confirm by repeating it back.>
3. “Do you have plans to keep this appointment?” Yes / No
If “no,” ask: “Have you notified the clinic of this choice?” Yes / No
If “no,” ask: “Do you know the clinic’s policy about cancelations & no-shows?’ Yes / No
< Restate: “The policy is “patients must give 24 hours advance notice of any cancellations to
avoid being counted as a “no-show.” >
< Correct any misunderstandings about this policy. >
Appendix C 1
< Offer to assist the patient with notifying the clinic of plans to keep or cancel the appointment and rescheduling the appointment. >
4. “Do you expect any problems keeping this appointment?” Yes / No
< If “yes,” note any patient specific problems. > _________________________________________________________________________________ _________________________________________________________________________________
5. “Can you tell me what problems you might have getting to your next appointment?” Yes / No < If “yes,” provide case specific recommendations for helping the patient keep the scheduled appointment and advice the patient: “These recommendations will be noted in your medical record so your provider may be alerted to any specific problems you might be having related to getting to your next visit.” > ________________________________________________________________________________ ________________________________________________________________________________
6. Ask the patient: “Are there any concerns or questions you have that you feel I should know about, related to your care, that I can forward to your provider?” Yes / No
< Note any case specific concerns> _______________________________________________________________________________ _______________________________________________________________________________
7. Advise the patient: “A ‘Behavioral Health Consultant’ (social worker) is available at this clinic to assist you with any concerns you may have about your care or needs.”
Explain: “You may ask your Primary Care Provider for a referral to the BHC.”
8. Conclude the interview “Thank you for you for taking the time to talk with me”
Note time ________
Duration ________
Scripted BHC intervention
Standardized survey instrument good validity & reliability.
There were NO statistically different mean scores of satisfaction between providers;
Or for days of the week;
Using the ANOVA (1-way Analysis of variance) on the CSQ-8…
… but Monday’s still sucked.
Using the ANOVA (1-way Analysis of variance) to look at the frequency of no-show & cancellation behavior pre-intervention and post-study …
There was NO statistical difference in mean scores based on payor or source.
Satisfied patients will be more motivated to return.
Paired Sample t-test of pre & post survey of study group N=6, valid percent 31.5 - no statistically significant differences.Independent Sample t-test for Variable Question #6: Have the services you received helped you to deal more effectively with your problems? t = 6.587, Sig(2-tailed) 0.000; Levene’s Test for Equality of Variance F= 16.970 p= 0.000
Table 3 Comparison of Mean Scores of pre & post intervention Study Group members; and post-intervention Study Group members & non-intervention General Adult Patients Population
Study Group
Pre- Intervention
Post-
Intervention
General Adult Patient Population
CSQ-8 N Mean (SD) Mean (SD) N Mean (SD)
Question #1 6 4.00 (0.000) 3.83 (0.408) 127 3.69 (0.584) Question #2 6 4.00 (0.000) 3.83 (0.408) 126 3.67 (0.563) Question #3 6 3.83 (0.408) 3.83 (0.408) 126 3.67 (0.506) Question #4 6 3.83 (0.408) 3.83 (0.408) 124 3.82 (0.443) Question #5 6 4.00 (0.000) 3.83 (0.408) 126 3.56 (0.854) Question #6 6 3.83 (0.408) 4.00 (0.000) 125 3.71 (0.489) Question #7 6 4.00 (0.000) 3.83 (0.408) 125 3.75 (0.486) Question #8 6 3.83 (0.408) 3.83 (0.408) 125 3.83 (0.435) TOTAL 6 31.33 (0.816) 30.83 (2.858) 125 29.35 (3.995) Questions #1 thru #8: Score ranges 1-4 Total Score range 1-32
Reminding you about your appointment will improve attendance and decrease no-shows …
…fuggta bout it!…neither will your age or the # of diagnosed or chronic health problems.
An indicator that +correlates with no-shows is the # of scheduled appointments
Chronic problems +correlate with cancellations & F/U’s kept.
Previously cancelled appointments +correlates w F/U’s.
F/U’s negatively correlates w/proximity.
Table 4 Correlation of significant variables from Study Group participants Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 1. Prev. No Shows 1.00 2. Prev. Cancelled .318 1.00 3. Prev. Visits < 3yrs .640** .440 1.00 4. Diagnosed Problems .069 .384 .362 1.00 5. Chronic Problems .099 .704** .445 .782** 1.00 6. Outreach Attempts .318 .068 .393 -.139 -.135 1.00 7. Problem Keeping Appt .168 .018 -.153 .528 .440 -.202 1.00 8. Age -.207 .188 .337 .449 .311 -.009 -.459 1.00 9. Proximity -.264 -.253 -.171 . 276 .006 .067 .168 .244 1.00 10. F/U Appts .201 .567* .201 -.035 .447 -.025 -.123 -.166 -.543* 1.00 11. Missed F/U Appts .177 -.065 -.179 -.360 -.161 -.470 .220 -.268 -.470 .548* 1.00 12. Cancelled F/U Appts -.077 -.172 -.069 -.101 .050 -.245 -.156 -.266 -.130 .248 .137 1.00 13. F/U Appts Kept .079 .749** .202 -.059 .546* .194 -.105 .052 -396 .786** .083 -.086 1.00 Pearson’s r = -1< 0 < 1 (indicates direction & strength) *Sig. (2-tailed) < 0.05 **Sig. (2-tailed) < 0.01
Table 5 Independent Sample t-test of Select Variables on Cancellations & No-show previous 36 months Pre- intervention
N Mean (SD) F Sig. t
Sig. (2-tailed)
# No-shows Male 4 1.25 (0.957) 0.834 0.374 -0.762 0.457 Female 15 2.07 (2.052) # Cancelled Male 4 0.75 (1.500) 0.325 0.576 -1.019 0.322 Female 15 2.00 (2.299) # No-shows Single 13 2.15 (2.15) 1.022 0.326 0.877 0.392 Married 6 1.33 (1.03) # Cancelled Single 13 1.85 (2.51) 0.841 0.372 0.313 0.758 Married 6 1.50 (1.37) # No-shows Aware of NSP 7 1.86 (1.069) 0.312 0.594 1.651 0.143 Un-Aware of NSP 2 0.50 (0.707) # Cancelled Aware of NSP 7 2.43 (3.155) 0.614 0.459 0.180 0.862 Un-Aware of NSP 2 2.00 (1.414) Equal variance assumed
Test of Hypothesis #1 & #2
The intervention will improve patient attendance and decrease patient no-show.
Table 6 Association between BHC intervention and No-Show & Attendance Behavior - Post-Intervention
Intervention Group N=10 Non-Intervention Group N=5
No-Show Yes 2 (20%) 2 (40%) (𝑥2 = 0.682, p = 0.409) No 8 (80%) 3 (60%)
Cancelled Follow-up Yes 2 (20%) 2 (40%) (𝑥2 = 0.682, p = 0.409) No 8 (80%) 3 (60%) Note: 3 cells (75.0%) in each crosstab have expected count less than 5. The minimum expected count is 1.33
Table 7 Independent Sample t-test of Select Variables on Follow-up Cancellations, No-show, and Kept Appointments
Post Study
N Mean (SD) F Sig. t
Sig. (2-tailed)
# No-shows - Male 2 0.00 (0.000) 4.496 0.054 -0.808 0.434 Female 13 0.62 (1.044) # Cancelled Male 2 0.50 (0.707) 0.708 0.415 0.763 0.459 Female 13 0.23 (0.439) # Kept Male 2 1.00 (0.000) 1.400 0.258 -1.068 0.305 Female 13 2.08 (1.382) # No-shows Single 9 0.89 (1.167) 21.638 0.00* 2.286 0.052 Married 6 0.00 (0.000) # Cancelled Single 9 0.22 (0.441) 0.727 0.409 -0.447 0.662 Married 6 0.33 (0.516) # Kept Single 9 2.11 (1.616) 0.640 0.438 0.618 0.547 Married 6 1.67 (0.816) # No-shows Aware yes 7 0.43 (0.787) 3.743 0.094 0.734 0.487 Aware no 2 0.00 (0.000) # Cancelled Aware yes 7 0.29 (0.488) 6.914 0.034* 1.890 0.108 Aware no 2 0.00 (0.000) # Kept Aware yes 7 2.29 (1.799) 2.120 0.189 0.963 0.368 Aware no 2 1.00 (0.000) # No-shows Intervention 10 0.30 (0.675) 8.653 0.011* -1.049 0.343 NonIntervention 5 1.00 (1.414) # Cancelled Intervention 10 0.20 (0.422) 1.778 0.205 -0.787 0.446 NonIntervention 5 0.40 (0.548) # Kept Intervention 10 2.00 (1.563) 0.440 0.519 0.264 0.796 NonIntervention 5 1.80 (0.837) *Unequal variance assumed
Close!!
Can a BHC social worker improve patient attendance & reduce no-shows?
The data suggests we can improve patient satisfaction with treatment to a small degree. Previous studies have demonstrated that satisfaction is one variable that positively
influences utilization. There was not enough study participants & survey results post-study to demonstrate a
statistically significant outcome but it is trending in the right direction.
SUMMARY