Improving the Primary Care
Specialty Care Interface
through eReferrals
AH Chen MD MPH, M Kushel MD, R
Kimes BA
BA, Y Kim MD
MD, HF Yee Jr MD PhD
UCSF/San Francisco General Hospital
Funded by San Francisco Health Plan
P bl
Problem

Significant variation in specialty referral rates,
with cost implications.

Referral process characterized by lack of clarity
in consultative question, inadequate pre-referral
evaluation and antiquated processes
evaluation,
processes.

In safety net settings, problems with access to
and timeliness of specialty care
care.
• Functionally integrated delivery system
• Access to SFGH EMR
• Specialists salaried faculty at UCSF
S tti
Setting
12 SF DPH
primary care clinics
~50,000 patients
5 UCSF-staffed
UCSF staffed
primary care clinics
~30,000 patients
10 independent
primary care clinics
~70,000 patients
17% Medicare, 27% Medi-Cal, 36% Uninsured
Comprehensive Specialty Services
Full-time Academic UCSF Faculty & Trainees
>500,000 ambulatory visits annually
28% specialty care, 20% diagnostics
I t
Intervention
ti

HIPAA compliant
li
web-based
bb
d referral/consultation
f
l/
l i system

Integrated into existing EMR
 Clinical q
question entered in free text format
 Auto-population of relevant data from EMR
 Mandatory use for enrolled specialty clinics and services (26)

Individualized review and response by specialist clinician

1-2 designated physician or nurse practitioner reviewers per clinic
 Reviewers can schedule
schedule, overbook
overbook, request additional information or
clarification, or provide management guidance via portal
 Allows asynchronous, repeated communication between referring and
reviewing clinicians on a given patient which is part of medical record

Functions as centralized, integrated referral and consultation portal
eReferral Schematic
PCP submits electronic referral
Consult reviewed electronically by specialist
Includes all relevant clinical data from EMR
Nott scheduled
N
h d l d
or more
information
requested
q
Appropriate specialty referral
AND
Pre-referral work-up complete
PCP can manage with guidance
OR
Pre-referral work-up incomplete
Nonurgent
Schedule Next Available
Urgent
Overbook
E l ti
Evaluation
Does the implementation of a specialist
specialist-staffed
staffed electronic
referral and consultation system for ambulatory specialty
care clinics improve the quality and efficiency of specialty
care?
?

Is there a decrease in wait times for specialty care
appointments?

Does eReferral improve specialists’ ability to provide
consultation?

Do primary care providers experience an improvement in
the quality
q alit of care for their patients?
M th d
Methods

Secondary data analyses


eReferral and hospital databases
Primary data collection

Clinic-based questionnaires affixed to new patient appointments
i specialty
in
i lt clinics
li i b
before
f
and
d after
ft iimplementation
l
t ti off eReferral
R f
l


Unit of analysis patient visit
Web-based
Web
based survey of all referring primary care providers



Acceptability
Assessment of quality
Systems improvements
R
Results
lt
Reduction in wait times despite intentional expansion of safety net

As of 6/13/09, Healthy San Francisco has enrolled 42,580 patients,
11,325 (26.6%) of whom are new to the system.
M edicine Clinics: Median Wait Time for Routine New Patient
Appointments January 2007- December 2008
140
Cardiology (129% increase)
Num
mber of Days
120
Percent of referrals
“never scheduled
ranged from 11% to
40%; average 23%
23%.
100
Pulmonary (34% decrease)
80
60
Endocrine ((50% decrease))
40
20
Rates of “overbooked”
appointments ranged
from 6% to 55%.
Rheumatology (29% decrease)
(Data from 2/07-2/08)
0
J an Mar May J uly Sep Nov J an Mar May J uly Sep Nov
t
t
Month
R
Results
lt
Reduction in the proportion of specialists for whom it was somewhat
or very difficult
diffi lt to
t identify
id tif the
th consultation/clinical
lt ti / li i l question
ti
Surgical Specialty Clinic Referrals
Medical Specialty Clinic Referrals
100
80
Diffiicult (%)
Diffi cult (% )
100
60
40
19.4
9.7
20
80
60
40
38.5
20
10
0
0
Prior Method (n=145)
eReferral (n=268)
Prior Method (n=105)
eReferral (n=100)
p-value <0.05 for difference in percentage of consultative questions considered somewhat or very difficult to identify between
new patients referred via eReferral versus prior method referrals for medical and surgical referrals
R
Results
lt
High ratings from primary care providers compared to prior methods

Web-based survey with 81% response rate (298 of 368)
Overall, how has eReferral changed
Overall
clinical care for your patients?
eReferral compared with prior method:
Percent of responsees
P
100
Consortium
COPC
SFGH
Overall
80
60
40
20
79
68
50
30
17
71
24
16
21
8 4 7
0
worse
no difference
better
Kim Y, Chen AH, Keith E, Yee HF, Kushel MB. “Not perfect, but better: primary care providers’ experiences with electronic referrals in
a safety net health system.” Journal of General Internal Medicine 2009; 24(5):614-619.
C
Conclusion
l i

Using a specialist clinician reviewer to
provide clinical g
p
guidance and triage
g
through an electronic interface can both
p
reduce wait times and increase specialist
efficiency, with high levels of primary care
provider acceptability.
p
p
y
P li IImplications
Policy
li ti

Potential for HIT to improve communication and
efficiency of primary-specialty care interface

Primary
P
i
care and
d co-managementt supportt (versus
(
gatekeeper role) enhances medical home model

Role of specialists in reducing variations in clinical care
care,
promoting evidence-based medicine

Useful model for accountable care organizations

Intriguing model for payers (Medicaid, UK)
Questions?