B4 understanding institutional and client level determinants of appointment no shows at a community

Reducing Appointment No-Shows: Understanding Social Determinants and Institutional Solutions AOHC Health Equity Action &Transformation Conference June 13, 2018 Susitha Wanigaratne, PhD Consultant Epidemiologist swanigaratne@accessalliance.ca

Yogendra Shakya, PhD Senior Research Scientist yshakya@accessalliance.ca

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Presentation Outline Background, Access Alliance context Project objectives Research questions and methods Quantitative results • Part 1: Appointment level data • Part 2: Client level data Qualitative results • Part 3: Focus Group Discussions Part 4: Recommendations Questions & Discussion 2

Why should we care about appointment no-shows?

(i.e., missed opportunities for care) Impacts Clients:

• Lost opportunity for prevention, intervention and continuity of care • Can lead to suboptimal primary care outcomes • Other clients cannot be seen

Impacts the Clinic/Health Care system: • Major source of inefficiency • Wasted health care dollars • Ineffective use of provider time Kaplan-Lewis et al, 2013; Hwang et al, 2015; Cashman et al, 2004 3

Access Alliance Project Context • Recurring concern about appointment no shows raised by managers and front line providers.

• AA began routinely implementing appointment reminder telephone calls from 2016.

• After our 2016 Client Experience Survey found that some clients were confused whether the telephone reminder message said “confirmed” or “cancelled,” we also began making sure that reminder calls included interpretation to avoid confusion.

• A quick pull of 2016 client data by Manager of Primary Care in 2017 found No Show rate at around 21%. We wanted to do a more robust study using multi-year data as well as client socio-demographic data to learn more about system levels causes and solutions.

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Project Team

• Research idea/need proposed by Manager of Primary Care and Executive Director.

• Research Design and implementation jointly led by an interdisciplinary team: • •

Decision Makers (Khanh Le, Cliff Ledwos, Axelle Janczur) IT/IS (Neil Mentuch)

• • • •

Frontline Primary Care Providers (Dr Avi Ramsaroop) Research Team (Akm Alamgir, Tayyeba Darr, Yogendra Shakya) Consultant Epidemiologist (Susitha Wanigaratne) Student (Stephanie Wong) 5

3 Research Questions 1. What are the current rates for appointment noshows at Access Alliance?

2. What are the key variables/determinants that are closely associated with appointment no-shows for Access Alliance clients?

3. What are the organizational solutions and unmet client level services/supports that can potentially reduce the appointment no-show rate at Access Alliance?

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Mixed Methods Research Quantitative

Retrospective Chart Review • client data (2014/15, 2015/2016, 2016/2017) • Schedule Module (e.g appointment date, status, cancellation reason etc) • Registration Module (socio-demographic) • CPP Module (Problem List - Assessments) • appointment and client level data analyses

Qualitative

Focus Group discussions: primary care providers (5 MDs, 3 NPs) and 4 members of secretary team In depth interview: 1 Nurse • Thematic analysis Telephone interviews with 30 clients • 10 each from three stratified group based on no show rate: i) those with high no show rates (>=90th percentile of no-show %), ii) those with moderate no show rates (50th-75th percentile of no-show %), iii) those that made all of their appointments (no no-shows).

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Part 1: Appointment Level Identifying no-show appointments • appointment status variable, Schedule Module No Show (NS) • “Auto No Show”, “No Show”, “To Be Confirmed” Attended Appts • “Arrived”, “OUT”, “Confirmed”

Excluded: “Rescheduled”, “Cancelled”, “Left Message” (~30%)

No Show (%) = NS

ALL INCLUDED APPOINTMENT TYPES 8

1a. No Show % (95% CI) by FY Rostered Clients, All Providers 24% 22%

23% 21%

% No Show

22% 21%

20%

20% 19% 18% 17% 16% 2014-15

2015-16

2016-17 9

1b. By Provider Type, each FY 45%

Statistical Increase/Decrease Across Fiscal Years Yes Yes Yes Yes

No

No

40% 35% No Show %

30% 25% 20% 15% 10% 5% 0% Primary Care

Settlement Counsellor External Registered Counsellor Therapist Dietician 2014-2015 2015-2016 2016-2017 Yes Yes Statiscal difference Yes between providers

Health Promoter

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1c. By Primary Care Provider, each FY Statistical Increase/Decrease Across Fiscal Years 25%

No Show %

20%

Yes 22%

19%

17% 19%

Yes 22% 22%

No 19% 18% 20%

15% 10% 5% 0% MD

Statistical Difference Between Providers

Nurse Practitoners Primary Care Provider 2014-2015 2015-2016 No

Yes

Nurses 2016-2017 Yes 11

1d. By Primary Care Provider Type Medical Doctors 40% 35%

No Show (%)

30% 25% 20% 15% 10% 5% 0%

14%

16%

16%

18%

20%

21%

21%

27%

29%

MD1

MD2

MD3

MD4

MD5

MD6

MD7

MD8

MD9 12

1di. Rostered MD vs other provider

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1e. By Primary Care Provider Type Nurse Practitioners Nurse Practitioners

35% 30%

No Show (%)

25% 20% 15% 10% 5% 0%

17%

19%

19%

21%

22%

22%

23%

26%

27%

NP1

NP2

NP3

NP4

NP5

NP6

NP7

NP8

NP10 14

1ei. Rostered NP vs. other provider

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1f. By Primary Care Provider Type Nurses Nurses 45% 40%

No Show (%)

35% 30% 25% 20% 15% 10% 5% 0%

17%

19%

20%

21%

23%

24%

25%

27%

N1

N2

N3

N4

N5

N6

N7

N8 16

1g. By Wait Time & Provider & Appointment Type 70%

Regular Appointments, all FYs

60%

No-Show (%)

50% 40% 30% 20% 10% 0%

0-6 days

7-13 days

Statistical Increase Across Wait Times

14-20 days MD NP Yes Yes

21-27 days

>=28 days

Nurse Yes 17

1g. By Wait Time (0-6 days) & Provider & Appointment Type 50%

No Show (%)

40%

Regular Appointments, all FYs 0-6 days

30% 20% 10% 0%

2,3,4 days

0,1 days Statistical Increase Across Wait Times

MD

NP

Nurse

Yes

Yes

Yes

5,6 days

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1h. By Wait Time & Provider & Appointment Type 70% 60%

Follow-up Appointments, all FYs

No-Show (%)

50% 40% 30% 20% 10% 0%

7-13 days MD Statistical Increase Across Yes Wait Times 0-6 days

21-27 days 14-20 days NP Nurse Yes Yes

>=28 days

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1h. By Wait Time & Provider & Appointment Type 50%

No Show (%)

40%

Follow-up Appointments, all FYs 0-6 days

30% 20% 10% 0%

2,3,4 days

0,1 days Statistical Increase Across Wait Times

MD

NP

Nurse

Yes

Yes

Yes

5,6 days

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Part 2: Client Level Rostered Clients ≼1 scheduled primary care appointment n=3,286

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Client Level No-Show Appts 28% of clients missed no appointments 72% of clients missed at least one appointment • 21% missed 1 • 15% missed 2 • 10% missed 3 • 19% missed ≥ 4

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Measuring no-shows at the client level Used all FYs, primary care appointments only For each rostered primary care client No Show (%) = NS

ALL INCLUDED APPOINTMENT TYPES

Operationalizing client-level outcome •

clients who no-showed for ≥30% of appts

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Clients no-showing for ≥30% of appointments 25% of clients no-showed for ≥ 30% of appts (804 of 3,286 clients) • • • •

16% missed 1 15% missed 2 15% missed 3 54% missed 4 or more

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2a. By Age, Sex, Interpretation vs. 0-5 years olds All age groups ≼ 40 years less likely

vs. females males 20% more likely

30%

vs. Yes/Yes No/Yes 40% more likely No/No 75% more likely

25% 20% 15% 10%

15%

22%

27%

50 to 59

60+

Female

Male

Age on April 1, 2016

Sex

17%

14%

23%

29% No/No

16%

No/Yes

21%

Yes/No

26%

Yes/Yes

27%

40 to 49

27%

30 to 39

28%

20 to 29

0%

6 to 19

5%

0 to 5

Clients with >=30% no-show appointments

35%

Interpreter Indicated/Used 25

2b. By Immigration Status Clients with >=30% no-show appointments

*29% missing, interpret with caution 40% 35%

vs. Permanent Residents -refugee claimants 34% more likely -non-status, 36% less likely

30% 25% 20% 15% 10% 5% 0%

23%

9%

31%

15%

16%

29%

Permanent Temporary Refugee Non-Status DNK, PNTA, Citizen, Not Resident Resident Claimant Other Applicable

27% Missing

Immigration Status

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2c. By Chronic Disease & Mental Health Diagnoses

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Quantitative Summary • Wait 0-6 days, lowest no-show rate (~15%) • Wait ≤ 1 day, even lower no-show rate (~10%) • Initial Visits << Regular < Follow-up • 25% of clients no-showed ≥ 30% of appointments • Clients who no-showed ≥ 30% of their appointments:

• Less likely to be: ≥40 years (vs. 0-5), non-status (vs. PR), to have diabetes or high blood pressure • More likely: male, no need for interpreter/no interpreter encounters (vs. needed and used), refugee claimant (vs.

PR) 28

Part 3: Focus Group Discussions 5 MDs & 3 NPs; 1 Nurse; 4 secretarial staff Purpose To understand:

• why clients no-show for appointments • how no-show appointments affect day-to-day practice, client health and health services delivery • current strategies providers and secretary team uses to reduce no-show appointments • potential future strategies to reduce no-show appointments 29

Provider & Secretary Discussions: Synthesis of reasons for no-show appointments Not considered too big of a problem since can be used for same day access.

SAME DAY CANCELLATION 1

Tried to call to cancel appointment but couldn’t get through on the AA phone line or leave message.

3

4

NO-SHOW DID NOT CALL 5

Did not know about appointment.

REASONS

1-2 week wait (or longer) for appt.

Secretary too busy to take call. a) Two lines on hold, third line keeps ringing and cannot leave voicemail message. b) Client does not want to leave voicemail message (to ensure message is received) but secretaries too busy to answer phone.

4a

4b

Forgot about appointment. a) Health problem resolved b) Went to a walk-in clinic/ER

Late for appointment, comes in later in the day.

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NO-SHOW CATEGORY

Appointment cancelled by provider/AA, but many appointments booked back to back, client is not reminded that there are other appointments to attend.

2

6

KEY:

Appointment no longer needed.

May get triaged to see provider, but will be rushed/potentially unsafe.

Clients not schedulable, chaotic approach to life. =chronic no-shower.

RELATED TO ACCESS ALLIANCE SCHEDULING/REMINDER PROCESSES: a) Confusion associated with multiple appointment cards. b) Not knowing the purpose or understanding information on appointment cards. c) Expecting reminder phone call b/c of 45 minute appt reminder rule. d) Inconsistent reminder phone calls – secretaries take it upon themselves to call chronic noshowers, secretary dependent. e) Client does not have voicemail. f) Client does not understand English– appt card, talking with secretary and reminder phone calls/VM messages not understood.

Part 4: Recommendations Client (Micro) level  Develop targeted interventions for clients with one or more characteristics: <40, male, refugee claimant;  Target clients who may be less vulnerable: clients who do not require interpreter, no chronic disease;  Continue/strengthen client knowledge about appointment cancellation policy;  Ensure client understands the purpose of appointments, particularly for provider initiated appointments 31

Part 4: Recommendations Practice (Meso) level (1)  Continue/deepen equity commitments to vulnerable clients – i.e., non-status, requiring language interpretation, have chronic illnesses  In line with HQO/MSAA targets, provide same or next day appointments (or within the week)

• Literature indicates effective for reducing no-show rates when baseline no-show rates >16%

 Continue to improve appointment reminders including automated/electronic reminders (e.g., text messages) rather than use reminder cards • Literature indicates automated/digital reminders are effective in reducing no-show rates

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Part 4: Recommendations Practice (Meso) level (2)  Ensure medical secretaries are adequately supported and trained to effectively manage appointment reminder calls and rescheduling; and meaningfully engaged in developing solutions  Put recall system in for clients needing consistent follow-up care but may not remember to call to make own appointment  Promote client-initiated appointment scheduling for follow up appointments so the appointment time works for them.  Encourage team based sharing of best practices from MD/NP with low no-show rates and/or based on secondary evidence.

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Part 4: Recommendations System (Macro) level  Advocate for fair wages and decent work legislation, including equitable access to paid sick days, job protected personal emergency leave, not requiring sick notes, advance notice of work schedules  Advocate for accessible and affordable transportation; e.g. TTC’s “Fair Fare Pass Program” (2018) may reduce transportation barriers to attend appointments  Build health sector level capacity and solutions to improve data quality (see next slide); conduct sector level research to identify macro/system level causes and solutions.

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Part 4: Recommendations Chart Data Quality  Improve no-show measurement to enhance understanding • identify same day cancellations since these appointments are not as much of a concern • Identify clients who come late to their appointments (at AA often seen as a triaged assessment) Ensure consistent definitions for appointment types • e.g., “follow-up” definition consistent since 2016-2017 only Improve sociodemographic data completeness • improved over the 3 fiscal years of this study • but missing data rate still high for many variables (e.g., disability 61%; sexual orientation 57%; race/ethnicity 55%; gender 51%; English fluency 48%; current immigration status 29%; household income 21%) 35

Questions?

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Discussion 1. Which study results about appointment no show did you find most striking/interesting, and why?

2. Have similar studies been done at your/other CHCs? If so, how do findings from these studies compare to what we found?

3. Based on findings from our study, what are some evidence-based solutions for reducing appointment noshows (that we have not touched on yet)?

4. What else would you like to know or do we need to know about appointment no-show and its causes?

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Additional Information

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No Show rates: Community Health Centres CHC, Boston (Kaplan-Lewis et al, 2013) • 16.5 % of all appointments Urban Clinic, Geneva (Perron et al, 2010) • vulnerable patients including undocumented immigrants • 22% in 2007 4 Community Mental Health Clinics, London UK (Sims et al, 2012) • 27% of all appointments CHC, New England (Cashman et al, 2004) • 73% of clients no-showed for ≥1 appointments • 43% of clients missed 1 or 2 appointments • 30% of clients missed 3 or more appointments

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Factors Related to No-Show

(Community Health Centre Studies)

Kaplan-Lewis et al, 2013 • Younger • Black/Hispanic • have Medicaid

Perron et al, 2010 • • • • • •

Young Male Asylum-seeker Substance abuse problem Appointment booked a year in advance Junior doctor (vs. Senior doctor)

Cashman et al, 2004

• Psychological diagnosis • Documented addictions 40

Client Reasons for No-Show (Community Health Centre Studies)

Kaplan-Lewis et al, 2013:

• Forgot about appt (35%) • Miscommunication (32%) – thought they’d cancelled, thought it was at a different time, couldn’t get through to cancel, didn’t realize they needed to cancel

Lacy et al, 2004:

• Emotional barriers

• uncomfortable news or procedures

• Perceived disrespect by the health care system - patient beliefs and time • Waiting at all stages (for the appt, in waiting room, exam room)

• Lack of understanding of the scheduling system • did not understand the impact of a missed appt

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Potential Solutions Open Access Scheduling (Systematic Review - Rose et al; 2011, n=24) • targets long wait times, patient control • ↓ 0% to 24% (11 studies)

Telephone & SMS reminders (Systematic Review - Hasvold et al, 2011) • Targets forgetfulness and miscommunication • Manual reminders, ↓ 39% from baseline • Automated reminders, ↓ 29% from baseline

Patient education Other Solutions

• Overbooking – does not address client health • No-show fees – disproportionately affects lower income clients

Multiple interventions (Du Montier et al, 2013)

• targeting several reasons/causes for no-show may be most effective

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Interpreting 95% Confidence Intervals Rostered, All Providers

Significant –top of solid bar is not within the 95% CI of another solid bar • No additional test needed

24% 23% 22%

% No Show

Non-significant –top of bar is within the 95% CI of another bar • To be sure, specific statistical test should be done

21% 20% 19% 18% 17% 16% 2014-15

2015-16

2016-17

Other Notes: • wide confidence intervals = small sample size (or frequency) • narrow confidence intervals = large sample size • additional tests – difference in % across groups, trends over time

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By Wait Time & Provider & Appointment Type 70% 60%

Other MD/NP; Other RN/RPN; Initial Visits, all FYs

No-Show (%)

50% 40% 30% 20% 10% 0%

21-27 days >=28 days 14-20 days 7-13 days Other MD/NP Other RN/RPN Initial Visit Stastical Increase Across Yes Yes Yes Wait Times 0-6 days

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By Wait Time & Provider & Appointment Type 50%

No Show (%)

40%

Other MD/NP; Other RN/RPN; Initial Visits, all FYs 0-6 days

30% 20% 10% 0%

Statistical Increase Across Wait Times

0,1 days

2,3,4 days

Other MD/NP

Other RN/RPN

Yes

Yes

5,6 days Initial Visit Yes 45

By Provider Type & Appointment Type Category Name

Primary Care Provider

Appointment Type

Regular Visit (Client initiated)

MD NP Nurse

Regular visit

Follow-up Visit (Provider initiated)

MD NP Nurse

Follow up visit (consistent definition since 2016-2017 only)

Other MD/NP

MD NP

1st prenatal, CCP, Complex, PAP, PCPShort visit, periodic health review, Short Visit MD/NP, Smoking Cessation, Smoking Consultation, Smoking Followup, Wellness visit, wellness visit NP

Other Nursing

RN RPN

1st prenatal, CCP, Complex, Immunization visit, immunization visit (initial), PAP, periodic health review, RN Smoking Survey, RN/RPN Short Visit, Short Visit RN/RPN, Smoking Cessation, Smoking Consultation, Smoking Followup, Wellness visit

Initial Visit

Not Specified

Initial visit, initial visit MD, initial visit NP, MD initial visit, MD orientation/initial visit, NP initial visit, NP initial visit/orientation, Orientation, Part 1/Part2/Part3 â&#x20AC;&#x201C; Initial visit 46

Clients with >=30% no-show appointments

27% 23% 26% 24% 22% 23% 23% 23% 25% 31% 19% 25% 24%

Primary or equiv. (gr 1-8) Secondary or equiv. (gr 912) Post secondary or equiv.

Other Do not know, Prefer not to answer 0-$14999 $15000-$19999 $20000-$24999 $25000-$34999 $35000 or greater Do not know, Prefer not to answer

0% Too Young for Primary

10%

No formal education

By Education, Income 50%

40%

no association with education

Education

vs. lowest income $20-$25K 40% more likely

30%

20%

Income

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Clients with >=30% no-show appointments

By Duration of Residence (for immigrants) *23% missing, interpret with caution 35%

no association with duration of residence

30% 25% 20% 15% 10% 5% 0%

23%

26%

26%

20%

18%

24%

0-4 years

5-9 years

10-14 years

15-19 years

20+ years

Missing COB/arrival date

Duration of Residence (as of March 31, 2017) 48