DATE: OCTOBER 5, 2017 PRESENTED BY: TIMOTHY GEBHART, DNP, FNP-C

No-Show Appointments in Primary Care

“a doctor ’s wai t ing room” by Vanessa CC BY-NC-ND 2.0

DisclosureI have no actual or potential conflict of interest in relation to this presentation.

Objectives for Today• Describe the impact of no-shows on clinic performance

and patient health• Describe patient and appointment characteristics that

have been seen to lead to missed appointments in the literature

• Describe interventions to reduce or reduce the impact of no-show appointments

• Case study: No-show appointments at OHSU Family Medicine at Richmond Clinic

Ceremonial dei ty, Phi l ippines c i rca 1930

No-Show AppointmentAn appointment where the patient fails to appear, arrives too late for the appointment, or cancels with too short a notice to schedule a different patient during their appointment time

(Cameron, Sadler, & Lawson, 2010)

Clinic Impact

•Overall 14-50% of primary care appointments are no-shows

•VA: Overall 19% no-show rate with majority in primary care clinics with each average $196 loss in revenue for clinic

•Academic FM clinic: 25% of clinic time wasted, 14% revenue loss

(Daggy et al., 2010; Kheirkhah, Feng, Travis, Tavakoli-Tabasi, & Sharafkhaneh, 2015)

Patient Impact•Less likely to be screened for cancers

•Worse control of chronic illness

•Higher rates ED visits, hospitalization

•Study: Every 10% rate of missed appointments increased chance of poor DM control by 24%

(Hwang et al., 2015; Nguyen & DeJesus, 2010; Nuti et al., 2012; Schectman, Schloring & Voss, 2008)

Arhat , J in Dynasty c i rca 1180

Literature Search• Studies investigating no-show appointments

between 2001-2016

–Bennett, Moore (Academic FM South Carolina)

–Chariatte (Swiss adolescent primary care)

–Daggy (VA medical center midwestern US)

–Kaplan-Lewis (Adult low-income Massachusetts)

–Lehmann (Internal med Switzerland)

–Miller (ENT outpatient Detroit)

–Moscrop (Urban young adult UK)

–Samuels (Academic pediatric primary care urban US)

–Shimotsu (Safety net clinic Baltimore)

–Sorita (Academic internal medicine Manhattan)

Patient Characteristics•Age

•Gender

•Ethnicity

•Poverty

•Psychiatric co-morbidity

•Previous no-shows

Age

•Younger adults

–Daggy: ≤ 50yo OR: 4.57

–Kaplan-Lewis: ≤40 OR 1.47

–Lehmann: <65 OR: 1.94

–Miller: Increased age OR 0.80

–Moore: Increased age OR 0.85

–Sorita: Increased age OR 0.97

•Older children

–Chariatte: Increased age OR 1.05

–Samuels: Increasing age OR 1.11

Gender

•Not significant

–Kaplan-Lewis

–Lehmann

–Moore

•Males

–Chariatte: OR 1.13

•Females

–Miller: OR 1.60

–Sorita: OR 0.5

Ethnicity• African American

– Bennett: OR 1.60

– Kaplan-Lewis: not significant

– Miller: OR 5.21

– Moore: OR 2.20

– Shimotsu: 1.82

• Latino

– Kaplan-Lewis: OR 1.15

– Shimotsu: OR 2.02

• American Indian/Alaskan Native

– Shimotsu: OR 2.29

• Asian

– Kaplan-Lewis: OR 0.56

– Shimotsu: OR 1.00

Poverty

•Lower SES

–Miller: Income level OR 0.75

–Moscrop: 4th quartile OR 1.53

Co-morbidity• Cardiac condition:

–Daggy: OR 0.54

• Major mental illness

–Moscrop: OR 4.72

–Shimotsu: OR 1.42

• Prescribed psych meds

–Moscrop: OR 5.76

• Known heroin/methadone use

–Moscrop: OR 14.60

• Diabetes

–Sorita: OR 1.80

• Asthma

–Sorita 2.0

Previous No-shows

•Bennett: Each previous no-show increases odds of future no-show by 3%

•Daggy: Increase of 10% in prior no-show increases the no-show OR by 1.2 (1-3 previous visits), 1.5 (4-6 previous visits), and 1.4 (>6 previous visits)

Appointment Characteristics•Payor

•Appointment lead time

•Routine appointment

•Establish care visit

•Day of week

Payor• Medicare:

–Bennett: OR 1.31

–Kaplan-Lewis: not significant

–Sorita: OR 4.2

• Medicaid:

–Bennett: OR 1.29

–Kaplan-Lewis: OR 3.36

–Miller: OR 1.77

–Sorita: OR 3.70

• Self-pay:

–Bennett: OR 1.38

–Kaplan-Lewis: OR 2.92

Appointment Lead Time

•Greater than 2 weeks:

–Bennet: OR 1.02

–Daggy: OR 2.68

Routine Appointment

•Follow-up

–Lehmann: OR 1.22

•Well-child visit

–Samuels: OR 2.56

Establish Care Visit

•Moore: OR 1.23

•Lehmann: OR 0.39

Day of Week

•Any day except Tuesday:

–Chariatte: OR 1.20, 1.35, 1.13, 1.20 for MWthF

•Not significant

–Lehmann

Reasons for No-Shows• Lack of transport

–Daggy, Samuels, Shimotsu

• Forgetfulness

–Kaplan-Lewis, Samuels

• Unable to take time off work/lack of childcare

–Samuels

• Health

–Too ill – Kaplan-Lewis

–Too well - Samuels

Bishamonten, Guardian King of the North , Japan c i rca 1615

Interventions for No-Shows

•Patient reminders

•Advanced access scheduling

•Schedule overbooking

•Probation

•Patient education

•Patient incentives

•Discharge from clinic

Patient Reminders• Mailed reminders (7.6% no-show

reduction)

• Voice phone reminder (9.4% reduction)

• Text message reminders shows (8.6% reduction)

• Email reminders – insufficient evidence

• Multiplicative effect when multiple reminders used – 70% more effective than individual methods if additive

(Stubs et al., 2012; Hasvold & Wootton, 2011; Guy et al., 2012; Atherton et al., 2012)

Advanced Access Scheduling• Only show benefit for no-show reduction

when base level is >15%

• Overall modest reduction in no-show appointments of 6.1%

• Mixed reports of other benefits – patient satisfaction improved in some studies, no change in others, and clinicians reported many concerns with losing patients to follow-up and impacts on continuity of care

(Stubs et al., 2012; Rose, Ross, & Horwitz, 2011)

Schedule Overbooking• Many programmatic methods developed

using local patient and appointment characteristics to intelligently overbook

• Interesting simulation of a busy academic practice predicted that an overall 50% reduction in no-shows led to a 14% increase in patient length of stay, and that reducing the no-show rate to 0% would lead to “overcrowding that would require several hours to clear out”

(Perac-Lima et al., 2015; LaGanga & Lawrence, 2012; Zacharias & Pinedo, 2014; Bard et al., 2014)

Probation• Patients with highest levels of no-shows

placed into probationary cohort, and only schedule appointments with a “virtual provider” – when they arrive, they are worked into next available provider at the clinic

• If attendance improved while on probation, could be returned to normal scheduling

• At one center, cohort no-show rate dropped from 33.3% baseline to 17.7% (baseline for clinic 7.1%)(DuMontier, Rindfleisch, Pruszynski, & Frey, 2013)

Ineffective Methods

• Patient education

• Limited prescription refills

• Patient incentives

• No-show fees

(Sorita et al., 2014; Stanley et al., 2016; Smith et al., 1990; Chariatte et al., 2007; Welsch et al., 1987)

The Foxes ’ Wedding , Tachibana Minko, 1765

Richmond Clinic

•OHSU Family Medicine in southeast Portland, OR

•Federally Qualified Health Center

• 10 mile service area

•Patients predominately below 200% Federal Poverty Level

•Majority insured through Oregon Health Plan

(Angier et al., 2015)

Past Policy Not Effective

0%

5%

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25%

-

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-SHO

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MONTH

Appointments by Month

Completed No-show Cancelled No-show Rate

Policy Enacted Policy Ended

Top 5% of Patients Account for Majority of No-Shows

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-SHO

WS

RANK ORDER OF PATIENTS BY NO-SHOWS

0%

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0-9 10-19 20-29 30-39 40-49 50-59 60-69 70-79 80-89 90-99 100+

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-SHO

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ATE

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AGE DECADE

Appointments by Decade of Age

Completed No-show Cancelled No-show Rate

Age of Patient Matters

Day and Time Makes Little Difference Unless it’s Saturday

0%

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APPOINTMENT TIME

Appointments by Time

Completed No-show Cancelled No-show Rate

Lead Time Doesn’t Matter

0%

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1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82 85 88 91

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Lead Days to Appointment

Appointments by Lead Time

Completed No show Cancelled No-show Rate

Other Findings• Increasing numbers of prior no-shows

predicts future no-shows

• Few coded disease conditions relevant to no-shows (drug & alcohol addiction, liver disease, schizophrenia, atrial fibrillation

• Privately insured patients best rates of kept appointments; Medicaid, self-pay, and workman’s comp the lowest

• Appointments with faculty physicians best

Race (reference = White)Alaskan NativeAmerican IndianAsianBlackNative HawaiianPacific IslanderUnknown/Decline

Sex (reference = Female)MaleTrans-Female to MaleTrans-Male to Female

Age (reference = 30-39)0-910-1920-2940-4950-5960-6970-7980-8990-99100+

Num. Medications

BMI

Charlson Score

Diagnosis Coded in EMRAsthmaAtrial FibrillationBipolarCerebrovascular DiseaseChronic PainCongestive Heart DiseaseCOPDCoronary Artery DiseaseCystic FibrosisDementiaDepressionDevelopmental DelayDiabetesDrug or Alcohol AddictionHemiplegiaHypertensionInflammatory Bowel DiseaseLiver DiseaseMyocardial InfarctionPeptic Ulcer DiseasePeripheral Vascular DiseaseRenal DiseaseRheumatic DiseaseSchizophreniaSkin Ulcers or Cellulitis

Total Appointments in 3y PeriodCancelledCompletedNo-show

0.0150.121<0.001<0.0010.6440.6680.012

0.5600.1720.588

<0.001<0.001<0.001<0.001<0.001<0.001<0.0010.0020.3810.193

0.015

0.019

0.691

0.915<0.0010.7900.927<0.0010.0480.0300.4160.2820.8900.1100.0460.187<0.0010.0330.8190.138<0.001<0.0010.6370.0170.0850.321<0.0010.004

0.005<0.001<0.001

-1 0 1 2 3 4

ppVariable

Visit Type (reference = Office Visit)CounsellingEstablish CareImmunizationsLabs/ImagingProcedureTelemedicine

Provider Type (reference = Faculty Physician)AdministrativeCounsellingDiagnosticsFNPGroupImmunization clinicLabMAPAPMHNPPrenatal ClinicProcedure ClinicPsyDResident PhysicianRNRPHSocial Worker

Payor (reference = Medicaid)MedicareOtherPrivateSelf-PayTRICAREWorker's Comp

Time (reference = Tuesday Afternoon)Monday MorningMonday AfternoonMonday EveningTuesday MorningTuesday EveningWednesday MorningWednesday AfternoonWednesday EveningThursday MorningThursday AfternoonThursday EveningFriday MorningFriday AfternoonFriday EveningSaturday MorningSaturday Afternoon

Lead Days to Appointment <14 days

0.028<0.0010.570<0.0010.163<0.001

0.021<0.001<0.001<0.001<0.001<0.001<0.0010.007<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001<0.001

<0.001<0.001<0.001<0.0010.491<0.001

<0.0010.1780.8060.0190.1040.9530.0130.7870.0950.8960.1120.0080.1640.3500.865<0.001

<0.001

-1 0 1 2 3 4

ppVariable

Financial Case to Improve• Back-of-envelope figures place a lost

income of $107 per missed visit

–Represents a loss of over $1.1 millionto clinic per year (out of net revenue of $5.7 million)

–$68,500 for each 1% reduction in overall no-show rate (from 17%)

• Faculty compensation includes 55% that is based upon RVU

–Potential loss of over 8% for faculty physicians

–Potential loss of over 9% for staff FNPs

Demon soldiers of Mara’s army, Burma c i rca 1470

Many thanks toOHSU Family Medicine at Richmond Clinic• Rachel Postman, DNP, FNP-C• Erin Kirk• Julie French• Isha Van Gelder

OHSU School of Nursing, Doctor of Nursing Practice Program• Mandy McKimmy, DNP, FNP-C• Kaitlin Haws, DNP, ANP, WHCNP-BC

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Photos“a doctor’s waiting room” by Vanessa CC BY-NC-ND 2.0https://www.flickr.com/photos/takeitez/4785039758

Asian art from author’s photos taken at Asian Art Museum of San Francisco (2015)

Text sidebar image detail from “Pediment with the demon magician Mayaravana”, Cambodia circa 1750, also from author photo