Ken FyieUniversity of Calgary and Alberta Bone and Joint Health Institute

Waiting Time Management Strategies for Scheduled Health Care ServicesOttawa, Ontario – March 28, 2012

Motivation and research question

Methodology

Results

Discussion and next steps

Involuntary WaitsA system-related wait, caused by inability to meet demand

Voluntary WaitsPatient-related factors directly impacting the system’s ability to deliver care in a specified timeframe

Source: Marshall et al. (2012) – under submission

Referral DateReferral

Received DateMSK Consult

DateActual Surgeon

Consult Date

T Surgeon T Referral T Received T MSK

Involuntary Waits

Voluntary Waits

Involuntary Waits

Source: Marshall et al. (2012) – under submission

Inconsistent and incomplete measurement of waiting times From referral made to musculoskeletal (MSK)

assessment to surgical consultation

Little analysis about the context of delays

Few published analyses of referral processing inside clinics – a “black box” from the outside

Can the hip and knee referral process from primary care providers to orthopaedic specialists in Alberta be positively impacted by the introduction of an electronic referral tool?

We: Qualitatively evaluate current referral practices Quantitatively evaluate three system measures

reflecting current quality of care

Data collected in three stages: Initial clinic visits, with semi-structured

interviews Retrospective patient chart sampling Time and motion study of clinical staff

Patients are consulting for hip and knee osteoarthritis for first time Primarily referred to clinics by GPs

Three volunteer hip and knee clinics in Alberta

 Settin

g

Number of

surgeons

MSK screeni

ng option availab

le

Integration

between surgeon

s and clinics

Complexity of

patients

Degree of

Electronic Usage

Clinic 1~4000-5000

referrals per year

UrbanMulti-

surgeon (10-20)

YesHighly

integrated

Handle all complexiti

es

Very advanced

Clinic 2~200-300 referrals per year

RuralSingle-

surgeonNo

Moderate integrati

on

Low complexiti

es

Moderately

advanced

Clinic 3~400-500 referrals per year

Midsized city

Multi-surgeon (2-9)

YesModerate integrati

on

Handle all complexiti

es

Moderately

advanced

Alberta total: ~15,000 referrals across 9 hip and knee clinics

• Accessibility:– 1) Waiting times (business days) –

• Time referral made to time referral deemed complete• Time referral deemed complete to time of first surgical consult

– 2) % of patients seeking next available surgical consult– 3) Estimate of involuntary and voluntary waiting times

• Referral Appropriateness:– 4) % of referrals initially arriving complete and

correctly directed– 5) Clinical rules for accepting referrals– 6) MSK screening usage

• Efficiency:– 7) Time spent by clinic staff evaluating each referral

11-15% of the referral made to surgical consultation waiting time is involuntary

Scheduling rules vary across clinics

 From:Referral

made

Referral deemed

complete

Referral made

To:Referral deemed

complete

Surgical consultation

Surgical consultation

Clinic 1Mean

Median

90th %

235

60

8176

129

9786

178

Clinic 2Mean

Median

90th %

74

29

413251

5135

104

Clinic 3Mean

Median

90th %

231346

131134182

139145212

05

01

00

05

01

00

05

01

00

0 100 200 300 0 100 200 300

0 100 200 300

Clinic 1 Clinic 2

Clinic 3Pe

rcen

t

Work days between referral date and date accepted/complete referralGraphs by Site

Red line: 90th percentile timeTan line: Mean waiting timeGreen line: Median waiting time

Note: few patients with long waiting time drive results

Red line: 90th percentile timeTan line: Mean waiting timeGreen line: Median waiting time

Note: few patients with long waiting time drive results

This is much higher than in literature (only 40%-70% in previous studies)

% of referrals with next available

surgeon option chosen

% of referrals with specific surgeon

selected

% less waiting time: when next available

is chosen

Clinic 1 71% 21% 36% (20 days)

Clinic 2 Only one surgeon

Clinic 3 80% 20% 14% (21 days)

Why are referrals rejected? Incomplete: referral

variables not filled out▪ Rules vary depending on

clinic▪ Most rejected referrals

are due to incompleteness

Incorrectly directed: cannot be treated at specific clinic▪ Longest delays

associated with this

% of initially rejected referrals

Primary Reason

Clinic 1 13%Missing x-

rays

Clinic 2 49%Missing BMI (height/weig

ht)

Clinic 3 No information

MSK screening results in fewer “currently non-surgical” patients seeing a surgeon

Clinic 1 Clinic 3% of

patients referred to

MSK asssessment

87% (105 of

121)

38% (19 of

50)

% of MSK patients assessed surgical

67% (70 of 105)

32% (6 of 19)

% of MSK patients assessed nonsurgical

33% (35 of 105)

68% (13 of

19)

These assessments resulted in:- 29% of referred patients at clinic 1 - 26% of referred patients at clinic 3

not seeing a surgeon for a surgical consultation

Clinic staff Most referrals take ~9-14 minutes Referrals with missing information take

longer Most staff have other work areas in

addition to referral processing Technology could increase efficiency

(duplicate data entry, scanning information)

Clinical time tracking is consistent Bone and Joint Clinical Network defined

waiting times Clinical processing rules vary

What is necessary on a referral form How patients are prioritized Whether triaging (MSK assessment) is

available Requirements prior to consult or surgery Feedback to GPs

Reduced waiting times: cut initial involuntary times by up to 20 days

All Alberta patients can choose next available surgeon

Consistent referral forms to minimize missing information: eliminate the 10-50% not initially accepted

Urgency scoring: get care to worse-off patients quicker

Reductions in certain tasks by clinic staff: save 8 minutes in scanning time

Electronic referral should be evaluated to determine how system outcomes change Must account for multiple changes occurring at

once

Voluntary waiting times should be separated

Basic standardization of the referral process should occur Differing clinic processing rules need to be

considered Reduces variation, creates one consistent queue

for patients

Current referral practices show some inefficiencies and gaps in knowledge, producing worse system outcomes

Electronic referral and central intake can potentially improve referral processing and system outcomes

Future analysis needed when electronic referral is implemented

Alberta Bone and Joint Health Institute: Tanya Christiansen Karen Phillips Stephen Weiss Christopher Smith Cy Frank Betty Smith

University of Calgary: Deborah Marshall Tom Noseworthy Aish Sundaram

Staff at three volunteer hip and knee clinics in Alberta

Funding provided in part from hSITE/NSERC and Alberta Health Services, and the

Alberta Osteoarthritis AIHS Team Grant