Evaluation of a patient communication pilot program and patient appointment reminder calls

(1)

The information contained in this presentation is intended for this audience only.

Evaluation of a patient communication pilot

program and patient appointment reminder calls

(2)

Presenters

• Leah Picardi Gallivan, M.S.W., M.S., Chief

Operating Officer, Edward M. Kennedy CHC

• Deborah Gurewich, Ph.D., Associate Director,

Research & Evaluation, UMass Medical School

• Susan West Levine, M.P.H., Managing Director,

UHealthSolutions, Inc. – an affiliate of UMass

Medical School

(3)

Presentation Outline

• Background:

Patient Communications Pilot Program

• Evaluation Aims and Methods

• Evaluation Findings

(4)

(5)

The Health Center Challenge

• High call volumes, abandonment rate

• Balancing in-person and phone support

• Cost of no shows

• Limited resources available for outbound calls

• Quality monitoring, reporting, and analytics

• Maintaining protocols and call flows

• Providing ongoing, dedicated training

(6)

The Solution

• Establish a

pilot

program to

centralize communication

functions across all sites

and begin the identification

and implementation of best

practices to improve patient

access and satisfaction.

(7)

The Partners

• Edward M. Kennedy Community Health Center

(EMK CHC)

• UHealthSolutions, Inc.,

a nonprofit affiliate of UMass

Medical School

(UHS)

• Mass League of Community Health Centers and

(8)

Pilot Goals

• Improve access to primary and preventive care

• Enhance and improve the quality of the patient

experience

• Decrease no-show rates and optimize schedule

efficiency

• Increase completion rate of outbound calls

(9)

Core Services Provided

• Outbound live appointment reminders

• After-hours answering service

• Inbound call management

–

Answering call during normal operating hours

–

Appointment scheduling

• Clinic cancellation notifications

(10)

Pilot Approach: UHS as an extension of

health center services

• Outsource and centralize communication

functions

• Leverage linguistically diverse and culturally

competent workforce

• Use patient’s preferred communication mode

and language

• Dedicate

patient communication specialists

to help patients navigate care

(11)

Implementation

• Executive Sponsorship

• Joint Working Group

–

Guiding principles

–

Shared culture/mission alignment

–

Communication plan

–

Provider meetings

–

Site visits/pictures by UHS staff

–

Best practices

• Phased implementation plan

• Committing time and resources

• Ongoing quality improvement

(12)

Joint Guiding Principles

• Ensure open, informal, timely, and responsive

communication

• Overcome issues and challenges

together

• Operate as one, seamless operation

• Serve as champions of the pilot program

• Embrace change

• Celebrate successes

• Utilize data to drive operational decisions

• Commit to continuous improvement

(13)

Phased Implementation

Live Appointment Reminder Calls

April 2012

EMK CHC Framingham Inbound Call Management

May 2012

After-Hours Answering Service

May 2012

(14)

Operational Benefits

• Dedicated staff making all reminder calls

• Detailed call reporting and analytics to pinpoint

trouble spots

• Workforce management to assign staff

according to call arrival patterns

• Tailored patient communications quality

(15)

Early Operational Metrics

• Average of 937 incoming calls/day

• Average of 619 appointment reminder calls/day

• Achieved 80/20 service level

(16)

Areas of Interest and Next Steps

• “Mini Pilots” for outreach and follow-up

–

Well-child visits

–

Women’s preventive care screening

–

Referral follow-ups

• Text and email appointment reminders

• Filling cancelled slots

• Leveraging grant funding

–

Additional areas of study

–

Support targeted initiatives

(17)

Lessons Learned

Challenges

Opportunities

• Organic growth led to

incomplete documentation

• Managing expectations

• Developing and improving

workflows once calls are

transferred to the health center

• Overcoming potential technical

limitations

• Measuring cost and investing

appropriately

• Developing call flows, best

practices, and written

procedures

• Learning together and making

real-time adjustments

• Dedicating staff to other

essential patient care functions

• Increasing revenues by

optimizing schedule

• Building a communication

infrastructure for success in

new payment models

(18)

(19)

Evaluation Aims

• Assess

appointment reminder system

–

Call reminder completion rates

–

Factors associated with patient no-show rate

• Pinpoint conditions that support and impede

(20)

Study Approach

• Quantitative Methods

–

Study aims related to call reminder system

performance

• Qualitative Methods

–

Study aims related to program implementation

• Funded by UMMS Commonwealth Medicine

(21)

Quantitative Analysis

• Data

–

Call disposition data (UHS)

–

Patient demographic and appointment status data

(EMK CHC)

• Sample

–

Six-month call disposition data (Jul.–Dec. 2012)

–

Two-week call disposition data merged with patient

demographic data (Feb.–Mar. 2013)

(22)

Quantitative Analysis (cont.)

• Descriptive

–

Call disposition completion and outcome rates

–

Comparison of show and no-show patients

• Multivariate Analysis

–

Dependent variable: Appointment (show v. no-show)

–

Independent variables:

• Call disposition

• Patient age, gender, race/ethnicity, and language

(23)

Qualitative Data

• Key Informant Interviews (N=10)

–

Heads of administration, clinical, front desk

• Data Collection and Analysis

–

One-hour interviews

–

Semi-structured interview guides

(24)

(25)

Call Disposition (6 months)

*Busy signal, hung up, wrong number, no answer, number changed, phone disconnected

44%

39%

12%

3%

1%

0%

10%

20%

30%

40%

50%

(n=77,002 appointments)

Missing data

Disposition not

specified

Patient cancelled/

rescheduled

Did not get through*

Left voice or live

message

(26)

Show vs. No-Show and Call Disposition

54%

6%

31%

8%

1%

37%

6%

36%

19%

2%

0%

10%

20%

30%

40%

50%

60%

Patient

confirmed

Left message

(person)

Left message

(voicemail)

Could not get

through

Other

Kept Appts

No Show Appts

p<0.001

N=4,506 Appointments (2 weeks)

(27)

Show vs. No-Show (cont.)

Total Population = 4,506 | Appointment Status, n (%)

Age

Show

No-Show

Chi-Square (α=0.05)

<9

324 (9.2)

111 (11.3)

<0.0001

10–19

253 (7.2)

104 (10.6)

20–44

1409 (39.9)

436 (44.6)

45–64

1239 (35.1)

264 (27.0)

65+

303 (8.6)

63 (6.4)

Gender

Show

No-Show

Chi-Square (α=0.05)

Female

2186 (62.0)

589 (60.2)

0.3232

Male

1342 (38.0)

389 (39.8)

Race

Show

No-Show

Chi-Square (α=0.05)

White

2392 (67.8)

650 (66.5)

0.1314

Black

558 (15.8)

174 (17.8)

Multi-Racial

398 (11.3)

109 (11.1)

Asian

162 (4.6)

35 (3.6)

Other

18 (0.5)

10 (1.0)

(28)

Show vs. No-Show (cont.)

Total Population = 4,506 | Appointment Status, n (%)

Ethnicity

Show

No-Show

Chi-Square (α=0.05)

Hispanic

1778 (50.4)

516 (52.8)

0.1907

Non-Hispanic

1750 (49.6)

462 (47.2)

Language

Show

No-Show

Chi-Square (α=0.05)

English

1516 (43.0)

493 (50.4)

<0.0001

Spanish

1112 (31.5)

301 (30.8)

Portuguese

594 (16.8)

116 (11.9)

Other

306 (8.7)

68 (6.9)

Day of the Week

Show

No-Show

Chi-Square (α=0.05)

Monday

951 (27.0)

282 (28.8)

0.0222

Tuesday

777 (22.0)

196 (20.0)

Wednesday

703 (19.9)

163 (16.7)

Thursday

704 (19.9)

206 (21.1)

Friday

300 (8.5)

91 (9.3)

Saturday

93 (2.6)

40 (4.1)

(29)

Show vs. No-Show (cont.)

Total Population = 4,506 | Appointment Status, n (%)

Location

Show

No-Show

Chi-Square (α=0.05)

Clinton

160 (4.5)

37 (3.8)

<0.0001

Framingham

548 (15.5)

76 (7.8)

Worcester

2820 (79.9)

865 (88.4)

Type of Service

Show

No-Show

Chi-Square (α=0.05)

Behavioral Health

540 (15.3)

127 (13.0)

<0.0001

Dental

977 (27.7)

291 (29.7)

Medical

1618 (45.9)

378 (38.6)

Other

393 (11.1)

182 (18.6)

(30)

Multivariate Analysis Results:

Determinants of Appointment Show

• Patient more likely to show if:

–

Older

(44 years and older) compared to younger

(20–44 years)

–

Non-English

speaking vs. English speaking

–

Received

reminder call

that confirmed

appointment or left message vs. call reminder

that could not get through (busy, disconnected,

etc.)

(31)

Multivariate Analysis Results:

Determinants of Appointment Show (cont.)

• Patient less likely to show if:

–

Appointment for

specialty care

(optical,

specialty, other) compared to routine medical

care

–

Appointment scheduled on

Monday

or

Thursday

(32)

Implementation Facilitators

• Cultural alignment

–

Centralization already in the air

–

Strong quality improvement

• Leadership and key stakeholder support

• Proximity between EMK and UHS

–

Sense of joint mission

–

Hire existing CHC staff

• Technical capacity (electronic health record and

(33)

Implementation Challenges

• Call protocol development and maintenance

–

After-hour calls especially (more customization)

• Remote call center limitations

–

Limited ability to route calls to phone extensions

–

Can’t physically track people down

• On-going call center staff training

(34)

Implications

• Implementation not easy but worth it

–

Frees up staff time for patients (not phones)

–

Improved tracking to support QI

• Appointment show rate varies across patient and

health center-level characteristics

(35)

Study Limitations

• Unknown factors associated with patients that

can’t be reached by phone

• Small sample (single site, etc.)

• Not all stakeholders represented

(36)

(37)

Next Steps

• Target interventions based on study findings

–

Adjust Monday appointment calls from Thursdays to

Fridays or Saturdays

–

Focus on the 12% “did not get through”

–

Implement alternative methods for appointment

reminders

• Identify areas for further study & secure grant

funding

(38)

Thank you.

Questions?