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PROGRESSIVE CLINICAL PRACTICE

Non–Emergency Department Interventionsto Reduce ED Utilization: A SystematicReviewSofie Rahman Morgan, MD, MBA, Anna Marie Chang, MD, MSCE, Mahfood Alqatari, MD, and JesseM. Pines, MD, MBA, MSCE

AbstractObjectives: Recent health policy changes have focused efforts on reducing emergency department (ED)visits as a way to reduce costs and improve quality of care. This was a systematic review of interventionsbased outside the ED aimed at reducing ED use.

Methods: This study was designed as a systematic review. We reviewed the literature on interventions infive categories: patient education, creation of additional non-ED capacity, managed care, prehospitaldiversion, and patient financial incentives. Studies written in English, with interventions administeredoutside of the ED, and a comparison group where ED use was an outcome, were included. Twoindependent reviewers screened search results using MEDLINE, Cochrane, OAIster, or Scopus. Thefollowing data were abstracted from included studies: type of intervention, study design, population,details of intervention, effect on ED use, effect on non-ED health care use, and other health and financialoutcomes. Quality of individual articles was assessed using Grading of Recommendations Assessment,Development, and Evaluation (GRADE) guidelines.

Results: Of 39 included studies, 34 were observational and five were randomized controlled trials. Two offive studies on patient education found reductions in ED use ranging from 21% to 80%. Out of 10 studiesof additional non-ED capacity, four showed decreases of 9% to 54%, and one a 21% increase. Bothstudies on prehospital diversion found reductions of 3% to 7%. Of 12 studies on managed care, 10 haddecreases ranging from 1% to 46%. Nine out of 10 studies on patient financial incentives founddecreases of 3% to 50%, and one a 34% increase. Nineteen studies reported effect on non-ED use withmixed results. Seventeen studies included data on health outcomes, but 13 of these only included data onhospitalizations rather than morbidity and mortality. Seven studies included data on cost outcomes.According to the GRADE guidelines, all studies had at least some risk of bias, with four moderatequality, one low quality, and 34 very low quality studies.

Conclusions: Many studies have explored interventions based outside the ED to reduce ED use invarious populations, with mixed evidence. Approximately two-thirds identified here showed reductionsin ED use. The interventions with the greatest number of studies showing reductions in ED use includepatient financial incentives and managed care, while the greatest magnitude of reductions were found inpatient education. These findings have implications for insurers and policymakers seeking to reduce EDuse.

ACADEMIC EMERGENCY MEDICINE 2013; 20:969–985 © 2013 by the Society for Academic EmergencyMedicine

From the Department of Emergency Medicine, Emory University (SRM), Atlanta, GA; the Department of Emergency Medicine,Oregon Health and Science University (AMC), Portland, OR; the Department of Emergency Medicine, George Washington Univer-sity (MA), Washington, DC; and the Departments of Emergency Medicine and Health Policy, George Washington University Hos-pital (JMP), Washington, DC.Received January 25, 2013; revision received April 14, 2013; accepted April 16, 2013.Presented at the American College of Emergency Physicians Scientific Assembly, Denver, CO, October 2012.Dr. Chang is generally supported by Award Number 1K12HL108974-01 from the National Heart, Lung, and Blood Institute. Dr.Pines is an associate editor for this journal, but had no involvement with the review or publication decision for this manuscript.Supervising Editor: Shahriar Zehtabchi, MD.Address for correspondence and reprints: Sofie Rahman Morgan, MD, MBA; e-mail: [email protected] related commentary appears on page 1062.

doi: 10.1111/acem.12219 PII ISSN 1069-6563583 969© 2013 by the Society for Academic Emergency Medicine ISSN 1069-6563 969

Growing health care costs in the United Stateshave made patients, providers, and payersexamine the value of services delivered.1 Con-

cepts such as accountable care organizations and medi-cal homes are gaining momentum with the goal oflimiting avoidable, redundant, ineffective, or harmfultreatments in favor of expanding effective care, accessto care, and care coordination.

Many programs aimed at improving efficiency focuson the use of hospital-based emergency departments(ED) for care. EDs care for critically ill patients andacute unscheduled conditions and serve as a safety netfor those with limited access to health care due to insur-ance status, the timely availability of clinic-based physi-cians, and the need for care outside of traditionalbusiness hours.2 The focus on the ED as a place toimprove efficiency stems from observations that EDcare for low-acuity conditions results in higher chargesthan for similar diagnoses seen in other settings.3 Inaddition, an ED visit may be a marker of a potentiallyavoidable injury or illness that could have been pre-vented with better primary care, patient education, orenhanced public health measures.

Studies have examined the effect of interventions toreduce ED use that are performed outside the ED, suchas patient education, improved clinic access, care coor-dination, patient-centered care, and others. While ED-based interventions also exist, they are fundamentallydifferent because of their location and their focus (e.g.,follow-up vs. prevention). Our group recently conducteda systematic review of ED-based care coordinationinterventions.4 Therefore, this review focuses specifi-cally on interventions based outside of the ED lookingat systems-level changes, rather than ED-specificchanges. Prior reviews of aggregated non-ED interven-tions have either focused only on one type of interven-tion or excluded some subsets of visits such as pediatricpatients or categories of intervention such as prehospi-tal diversion.5–7 To our knowledge, there has been nobroad-based inclusive review of the comparative effec-tiveness of the myriad interventions tested to reduce EDuse. The goal of this investigation was to review the evi-dence on the effectiveness of interventions based out-side of the ED aimed at reducing ED use and,ultimately, to explore themes about which interventionsmay be most effective, along with any undesired conse-quences.

METHODS

Study DesignWe systematically reviewed the literature on the effec-tiveness of non-ED interventions aimed at reducing EDuse. Non-ED interventions were defined as those imple-mented outside of an ED or hospital (e.g., insurance-based, outpatient clinic-based). No human subjects ormedical records were reviewed as a part of this studyso institutional review board approval was notrequired.

The databases MEDLINE, Cochrane, OAIster, andScopus were examined from 1966 to the present. Key-words used included emergency department, emer-gency medical services, utilization, demand, patient

education, primary care, capacity, extended hours,advanced access, telephone triage, general practitioner,care coordination, copayment, and payment reform(MEDLINE search terms in Appendix A). Searches werelimited to English language publications. Because of thevariety in the interventions and outcome measurementsin the results, we performed a qualitative rather thanquantitative systematic review.

Data Collection and ProcessingTwo independent reviewers (MA, SRM) screened searchresults and excluded those with titles that did not fitinclusion criteria (next section). The two reviewers thenscreened the abstracts of the remaining citations, againexcluding those that did not fit inclusion criteria. Theremaining articles underwent full-text review to excludeany remaining studies that did not fit inclusion criteria.Intrarater reliability was measured with a 10% sampleof citations, resulting in a kappa of 0.92. Each articlewith conflicting opinion from reviewers was discussedwith a third reviewer (JMP) for a final resolution.

The following data were abstracted from all eligiblestudies: type of intervention, study design, population,details of intervention, effect on ED use, effect on non-ED health care use, and other health and financial out-comes. Reviewers used a standard format to abstractdata; this format mirrors the categories in the tablespresented here. We attempted to standardize resultsacross studies. In studies with data available for abso-lute number of ED visits before and after the interven-tion was implemented (as opposed to, for example,number of visits per person, etc.), we calculated apercentage reduction of ED visits. When visit numberswere reported, the difference between number of visitsbefore and after the intervention was divided by thenumber of ED visits prior to intervention to standardizethe comparison of study results.

We followed guidelines created in the PreferredReporting Items for Systematic Reviews and Meta-Anal-yses (PRISMA) statement to create a four-phase flowdiagram (Data Supplement S1, available as supportinginformation in the online version of this paper) showingthe number of records included and excluded at eachphase.8

Inclusion and Exclusion CriteriaStudies were included if they had interventions adminis-tered outside of the ED, had a comparison group whereED use was an outcome, and were in English. Whilestudies in other languages were excluded, studies wereincluded regardless of country and health care system ifpublished in English. Five categories of interventionswere included: 1) patient education on medical condi-tions and appropriate medical care use for low-acuityconditions, 2) creation of additional capacity in non-EDsettings (e.g., expanded hours or same-day access), 3)managed care (e.g., primary care physician capitationor gatekeeping), 4) prehospital diversion, and 5) patientfinancial incentives (e.g., copayments or deductibles).Two other interventions, telephone triage and casemanagement, were initially searched for but becauserecent systematic reviews have compiled the results ofthose topics; these were excluded.5,6

970 Morgan et al. • SYSTEMATIC REVIEW OF NON-ED INTERVENTIONS TO REDUCE ED USE

Studies with ED-based interventions were excluded,as were studies without measurable objective outcomes.Studies with outcomes assessed through patient or pro-vider subjective surveys were also excluded.

Quality AssessmentQuality assessment was done using the portion of theGrading of Recommendations Assessment, Develop-ment, and Evaluation (GRADE) criteria aimed at assess-ing the risk of bias in individual articles.9 Because of theheterogeneity in study designs, other components of theGRADE criteria, including the formal overall evaluationof the body of literature, were not used. Additionally,studies with risk-adjusted results and where significancewas measured are reported.

RESULTS

Literature SearchThe search yielded 793 titles. After removing duplicatesand exclusions based on title or abstract, 62 studiesremained and underwent full-text review (Data Supple-ment S1). An additional 19 references were identifiedand also underwent full-text review, which resulted in atotal number of included studies of 39 that ranged frompublication dates of 1986 to 2011. The number ofincluded studies per category is as follows: patient edu-cation on medical conditions and health care use, fivestudies10–14; creation of additional non-ED capacity, 10studies15–24; prehospital diversion of low-acuity patients,two studies25,26; managed care, 12 studies27–38; andpatient financial incentives, 10 studies.39–47

Description of Included StudiesPatient Education on Medical Conditions Health CareUse. Two out of five studies found significant reduc-tions in the use of the ED after interventions, withreductions ranging from 21% to 80% (Table 1).10–14 Allstudies were based in the United States. Interventionsincluded use of booklets or in-person educational ses-sions. Both pediatric and adult patients are included.Three studies reported data on non-ED use with onefinding 0.03 fewer clinic visits per person.10–12 Threearticles reported health outcomes and no significantadverse events were noted.11–13 No studies reportedrisk-adjusted data.

Capacity Increase in Non-ED Settings. Of 10 studies,three examined interventions that expanded capacitythrough new community clinics, while the remainderinvolved existing physician practices expandingappointments and/or hours of care. Four studies foundsignificant decreases in the use of the ED after increasesin non-ED capacity, with reductions ranging from 9%to 54%, while five were nonsignificant and one foundan increase of 21% (Table 2).15–24 Four studies werebased in the United States and the remaining six inCanada or Europe. Regarding effect on non-ED use,five studies reported data with four showing increasesin non-ED use ranging from 1% to 102%.16,17,20–23 Ofthese, one article reported that while there was anincrease in primary care use, there was a concurrentdecrease in urgent care use.20 Two articles reported

health outcomes.20,21 Three studies reported cost datashowing 10% to 20% savings with the interven-tion.15,18,20 Two studies risk-adjusted data.20,21

Prehospital Diversion of Low-acuity Patients. Bothstudies examining the effects of emergency medical ser-vices (EMS) diversion of low-acuity patients away fromthe ED found significant decreases in the use of the EDafter interventions, with reductions ranging from 3% to7% (Table 3).25,26 One study was conducted in the Uni-ted States, and the other, in the United Kingdom. Oneintervention involved EMS offering either home orclinic care to low-acuity patients.25 The other involvedtransportation of such patients to clinic care withouthome care as an option.26 Regarding effect on non-EDuse, both studies found increases in use of other caresettings. No studies directly addressed other health orcost outcomes. No data were risk adjusted.

Managed Care. Of the 12 studies examining theeffects of managed care on ED use, six had interven-tions with capitated payment of primary care physician,five had a requirement of primary care physicianapproval or gatekeeping, and one was a hybrid of thesetwo (Table 4).27–38 Ten studies were based in the UnitedStates, one in Canada, and one in Ireland. The majorityof U.S. studies were in Medicaid populations andincluded pediatric patients. Overall, nine studies (sixwith capitation and four with gatekeeping as interven-tions) found significant decreases in the use of the EDafter managed care interventions, with reductions rang-ing from 1% to 46%, while two did not find any signifi-cant difference.27–31,33–38 The final study found mixedresults with no change in ED use when comparing phy-sicians pre- and postcapitation, but with an increase inED use among physicians compensated through capita-tion versus fee-for-service.32

Regarding the effect on non-ED use, six studies didreport data, with only four reporting significance andmixed results.28,30,32,35,37,38 Six articles included healthoutcome data, five in the form of effect on hospitaliza-tions and one on morbidity indices; results were mixedand did not always assess for significance.27,30,32,34,37,38

Two studies reported cost data with both showingdecreases with capitation.28,30 No studies reported risk-adjusted data.

Patient Financial Incentives. Of the 10 studies usingcosts to influence patients to use certain sites for care,or to use care efficiently, nine studies found significantdecreases in the use of the ED after implementation ofthe intervention, with reductions ranging from 3% to50% (Table 5).39–47 The remaining study found a signifi-cant relative increase of 34% in ED visits.48 All studiestook place in the United States. The intervention inseven studies was the requirement for patient copay-ment or coinsurance, and in three it was the implemen-tation of a high deductible. Half of the studies were inMedicaid populatons, with the majority of those single-state interventions, while the others involved commer-cial insurers.

Regarding effect on non-ED use, two studies didreport data with one showing no change in urgent care,

ACADEMIC EMERGENCY MEDICINE • October 2013, Vol. 20, No. 10 • www.aemj.org 971

Table

1PatientEduca

tiononHealthCare

Use

Author/Year

Design

Population

Intervention

Effect

onED

Use

Effect

onNon-ED

Use

OtherOutcomes

Intervention:Booklet

Glavanetal.

(1998)10

Pre–p

ost

interventional

study

UnitedStates

6months

Air

Forcebase

Interventiongroup:

1,555su

bjects

Controlgroup:

972su

bjects

Subjectsin

intervention

groupwere

given

ase

lf-care

bookwith

aninform

ation

sess

iononhow

touse

thebook

Interventiongroup:

reductionin

ED

use

rate

perperson

from

0.353to

0.279(p

=0.02)

Controlgroup:

increase

inED

use

rate

perpersonfrom

0.386to

0.421

Interventiongroup:

reduction

inclinic

use

rate

per

personfrom

1.072to

1.038

Controlgroup:increase

inclinic

visitsrate

perperson

from

1.040to

1.168

Notreported

Rectoretal.

(1999)14

Randomized,parallel

groupstudy

UnitedStates

January–J

uly

1998

TwourbanMedicaid

health

plans(PlanA

andB)

Interventiongroup:

house

holds

senteduca

tionalbroch

ure

Controlgroup:

house

holdsnot

senteduca

tionalbroch

ure

House

holdswere

randomizedto

rece

ive

abooklet,First

Look,

aboutca

reof

commonnonurgent

conditions

Nonsignifica

nt

reductionsin

ED

use

of1.1%

(PlanA,95%

CI=–3

.1%

to0.8%)

and–1

.2%

(PlanB,95%

CI=

–4.1%

to1.4%)

Nodifference

ineitherplan

inphysicianoffice

visits

Intervention:TrainingSess

ions

McW

illiams

etal.

(2008)11

Retrosp

ective

cohort-control

study,difference

-in-

difference

model

UnitedStates

12months

Primary

care

practicesat

aca

demic

healthce

nter

Interventiongroup:191

patients

inpractice

Controlgroups:

•168patients

at

samepractice

from

previousyear

•2co

hortsfrom

same

yearatprimary

care

siteswithout

intervention,

133and126patients

Nursesprovided

standardizededuca

tion

alongwith

presc

riptionfor

pain

relievingeardrops

Parents

remindedof

24-hourmedical

advicetelephoneaccess

Reductionin

ED

use

forearpain

by80.3%

(p=0.009)

atinterventionsite.

Concu

rrentco

ntrol

site

had25%

nonsignifica

nt

increase

inED

use

Nonsignifica

ntreductionsin

urgentca

rece

nteruse

by40.3%

(p=0.33),and

primary

care

centeruse

by27.8%

(p=0.14)at

interventionsite.In

controlsite,28%

reduction

inurgentca

reuse

,anda4%

reductionin

primary

care

use

3-yearmedicalreco

rdreview

ofallch

ildren

intheintervention

grouprevealedno

episodesofmastoiditis

Rettig

etal.

(1986)12

Randomized

controlledtrial

UnitedStates

Oneyear

Multiple

homehealth

nursingagencies

Interventiongroup:180

diabeticpatients

Controlgroup:193

diabeticpatients

Diabeticpatients

inthe

interventiongroup

underw

enthome

teach

ingse

ssions

ondiabetichealth

problems

Nonsignifica

nt

reductionin

ED

visitsin

intervention

vs.

control

group(0.06vs.

0.08)

(nonsignifica

nt)

Nonsignifica

ntincrease

inprimary

care

visitswithin

6monthsby

interventionvs.

controlgroup

(3.11vs.

2.78)

Nonsignifica

ntch

anges

inhosp

italizationrates/

1,000members/yearin

interventiongroupvs.

controlgroup:


pediatric office, adult office, and ambulatory care visits,but one showed an increase in hospital outpatientdepartment use.42,43 Six studies reported health out-comes in the form of ED visits resulting in hospitaliza-tion, which decreased or were unchanged.39–42,44,47 Ofthese six, two also reported effects on morbidity, oneshowing no change and one showing a decrease.39,42

Three studies reported cost data with mixed results.43–45

Five studies risk-adjusted data.39,42,45,46,48

Quality AssessmentQuality assessment for risk of bias in individual articlescan be found in Table 6 and Data Supplement S2 (avail-able as supporting information in the online version ofthis paper). All 34 observational studies were of verylow quality according to GRADE guidelines, in whichobservational studies are at best low quality and anyserious risk of bias lowers the quality to very low. Fourof the randomized trials were of moderate quality andone of low quality.

DISCUSSION

In 2003, Asplin et al.2 identified input, throughput, andoutput factors associated with crowding in the ED. Inthis paper, we explore primarily the effect of how sys-tems outside the ED can influence demand for ED careand focused entirely on “input.” This expands on previ-ous work where we conducted a systematic review ofcare coordination within the ED.4 With respect to non-ED interventions, we found there have been many stud-ies exploring non-ED interventions to reduce ED use invarious populations across more than two decades withmixed evidence. Over two-thirds (27 of 39, 69%) of theidentified studies in the five categories of interventionincluded showed reductions in ED use, with reductionsranging from 1% to 80%. Nearly all of the studies wereobservational, many coinciding with systemic changeswithin the region, and only five out of the 39 were ran-domized trials. Only seven of 39 studies (17.9%)reported risk-adjusted data.

The areas with the largest number of studies showingreductions in ED use include patient financial incentivesand managed care interventions, with nine of 10 (90%)and 10 of 12 (83%) of those studies showing reductions,respectively. By contrast, less than half (four of 10) ofthe studies on increasing capacity found reductions inED use, and one even found an increase, suggestingthat adding capacity could potentially have the oppositeeffect. This may be due to issues with supply-induceddemand. Findings on capacity should be interpretedcarefully, however, as the majority of articles on thistopic are international, and several take place in single-payer health care systems. The area showing the largestmagnitude of reduction is patient education, with amaximum of an 80% reduction in one study.

We hope to build on the growing body of literaturethat addresses the overall aim to reduce ED use. Priorreviews exist on two topics not included here, telephonetriage and case management. For telephone triage, aCochrane review of nine studies included seven studiesthat examined the effect on ED use.5 Of these, sixshowed no difference, and one showed an increase inT

able

1Continued

Author/Year

Design

Population

Intervention

Effect

onED

Use

Effect

onNon-ED

Use

OtherOutcomes

•Non–d

iabetesrelated

(544.4

vs.

440.4)

•Nonpreventable

diabetesrelated

(66.7

vs.

82.9)

•Preventable

diabetes

related(94.4

vs.

41.5)

Sch

onlau

etal.

(2005)13

Pre–p

ost

interventional

study

UnitedStates

Primary

healthca

rece

nters

recruited

throughBreakthrough

SeriesCollaborative

Interventiongroup:three

siteswith109patients

Controlgroup:tw

ositeswith76patients

Asthmaticpatients

at

interventionsites

underw

ent

educa

tionalse

ssions

Nonsignifica

nt

difference

sin

acu

teca

revisitsbetw

een

groups(1.72vs.

0.92average

visits;

p=0.08)

Notreported

Nosignifica

ntdifference

inquality

oflife,number

ofbeddays,

andacu

teca

rese

rviceuse


Table

2Capacity

Increase

inNon-ED

Settings

Author(Year)

Design;Country;

DurationofStudy

Population

Intervention

Effect

onED

Use

Effect

onNon-ED

Use

OtherOutcomes

Intervention:AdditionalClinic(s)

Chalderetal.

(2003)2

2Matchedtime-series

analysis

England

Oneyearbefore

andafter

NHS

developedwalk-ince

nters

withdrop-inse

rvice

Interventiongroup:10towns

withwalk-ince

nter

Controlgroup:10similar

size

townsin

same

regionwithoutwalk-ince

nters

Walk-ince

nters

provided

nurse-led,

drop-inse

rvicewith

broadhours

ofoperation

Decrease

of173.3

visits/month

vs.

decrease

ofthreevisits/

month

inco

ntrolgroup

(p=0.11)

Before

andafterincrease

of3.9

visitsto

primary

care

facility

vs.

23.7

visitsin

controlgroup(p

=0.25)

None

Hsu

etal.

(2003)2

4Before-and-after

obse

rvationalstudy

withco

ntrolgroup

England

6monthsbefore

andafter

NHS

developedwalk-ince

nters

withdrop-inse

rvice

Interventiongroup:onetown

withwalk-ince

nter

Controlgroup:onenearby

townin

thesa

me

regionwithoutwalk-ince

nter

Walk-ince

nters

providednurse-led,

drop-inse

rvicewith

broadhours

ofoperation

ED

visitsincrease

dby10%

(adjustedRR

=1.10;95%

CI=1.00to

1.21)

0.10feweremergency

consu

ltationsperday

(95%

CI=–3

.75to

3.55)

None

O’Kellyetal.

(2010)1

6Retrosp

ectivestudy

Ireland

1999–2

007

Single,largeED

andout-of-hours

generalpractice

emergency

serviceclinic

associatedwithsa

mehosp

ital

Interventiongroup:Dubdocpatients

Controlgroup:low-triage-level

ED

patients

“Dubdoc”

isan

out-of-hours

general

practiceemergency

servicesclinic

Significa

ntdecrease

low-triage-levelED

visitsduringDubdoc

hours

(54%

decrease

inlow-acu

ityED

visitsvs.

52%

decrease

outside

Dubdochours;p<0.033)

Increase

of102%

in“Dubdoc”

visits(3,810in

1999to

7,696in

2007)

Notreported

Rust

etal.

(2009)1

9Cohort

study

UnitedStates

2003–2

005

Ruralco

untiesin

state

ofGeorgia

Interventiongroup:co

unties

withCHCs(n

=24)

Controlgroup:co

untieswithout

federallyfundedCHCs(n

=93)

CHCsprovideca

reto

theuninsu

red

withoutmedicalhomes

Non-CHC

countieshad

higherratesofED

visits

(RR

=1.21;95%

CI=

1.02to

1.41)

Nonereported

Nonereported

Intervention:Changein

scheduling/hours

Hudecetal.

(2010)1

5Case

-compariso

nstudy

before-and-after

advance

access

implementation

Canada

3months

Fourfamilyphysicianpractices

Interventiongroup:patients

of

generalpractice

withadvance

daccess

booking

Controlgroup:patients

ofthreegeneral

practiceswithtraditionalbooking

Practiceinstituteda

modelin

which

most

appointm

ents

are

same-dayaccess

28%

reductionin

low-acu

ity

ED

visitsin

group

None

7%

revenueincrease

forpractice

Improvedse

lf-reported

patientsa

tisfaction

(p<0.05)

Philipsetal.

(2010)2

3Before-and-after

obse

rvational

studywith

controlgroup

Belgium

2006–2

007

Form

ationofGPCs

Interventiongroup:city

(Turnhout)

that

implementedGPC

Controlgroup:tw

oother

largecitiesthat

did

nothaveGPC

(GhentandAntw

erp)

GPC

reorganized

providers

forthatregion

andce

ntralizedout-of-hours

primary

healthce

nter,

openon

weeke

ndsandholidays

815visitsto

ED

before

and

791visitspost

(no

significa

ntch

ange)

Primary

care

visitsincrease

din

theinterventionregion

(714to

1197visits)

(OR

=1.37;95%

CI=1.20

to1.57),whilestayed

relatively

constantin

controlregion

(734to

850visits)

Solberg

etal.

(2004)2

0Retrosp

ective

pre–p

ost

study

UnitedStates

1999–2

001

Riskadjusted

Large,multispecialtymedicalgroup

Patients

withthreese

lect

chronic

conditions

(heart

disease

,diabetes,

depression)

Interventiongroup:

17,376patients

in2001afterim

plementation

ofopenaccess

Controlgroup:16,099

patients

in1999before

implementationofopenaccess

Fulladvance

daccess

appointm

ents

introduce

d,which

included

standardizationof

schedule

slots

andextravisittime

forclinicians

Nosignifica

ntdifference

inrisk-adjustedproportionof

patients

visitingED

(during

this

timeperiod,ED

visits

alsoincrease

dby7.8%

for

themedicalgroup)

(allp>0.05)

Increase

inprimary

care

visits(allp<0.01)

Significa

ntdecrease

inrisk-adjustedproportion

ofpatients

visitingurgent

care

(allp<0.001)

Totalco

stperpatients

increase

d10%–2

0%

dependingonco

ndition

Significa

ntreductionof

proportionofpatients

with

hosp

italizations(1%)

andlength

ofstay>3days

(4%)forheart

disease

patients

only

(nonsignifica

ntch

anges

forotherco

nditions)


Table

2Continued

Author(Year)

Design;Country;

DurationofStudy

Population

Intervention

Effect

onED

Use

Effect

onNon-ED

Use

OtherOutcomes

Solberg

etal.

(2006)2

1Retrosp

ective

pre–p

ost

study

UnitedStates

1999–2

001

Riskadjusted

Large,multispecialtymedicalgroup

ownedbyhealthplan

Interventiongroup:6,609

patients

with

depressionin

2001after

implementation

ofopenaccess

Controlgroup:7,284patients

withdepression

in1999before

implementation

ofopenaccess

Advance

daccess

appointm

ents

instituted(third

next-dayavailable

appointm

ent

reduce

dfrom

19.4

to4.5

days)

Nosignifica

ntch

ange

inED

visits

1%

increase

inprimary

care

visits(p

<0.01)

2%

increase

inhosp

italizations(p

<0.05)

17.6%

reductionin

proportion

ofpatients

withnofollow-up

afterstartingnew

medication

(p=0.001)

Majority

ofvisitswithone

physician(continuityofca

re)

increase

dby6.7%

(p<0.001)

vanUden

etal.

(2004)1

7

Retrosp

ective

pre–p

ost

cohort

study

Lim

burg,

theNetherlands

Regionalgeneralpractitioner

cooperatives


patientco

ntacts

afterim

plementationofGPCs

Controlgroup:11,781

patientco

ntacts

before

implementationofGPCs

Largeco

operativesof

generalpractitioners

toofferoutofhours

primary

care,alsoact

as

gateke

eperforED

visits

9%

decrease

inED

visits

afterhours

13.7%

abso

lute

reduction

numberofse

lf-referrals

toED

10%

increase

inprimary

care

visitsafterhours

4.6%

increase

inoverall

patientco

ntactsafterhours

3.6%

shiftin

use

from

ED

toprimary

care

(p<0.001)

None

Wangetal.

(2005)1

8Pre–p

ost

intervention

studywith

compariso

ngroup

UnitedStates

12months

Large,private,primary

care

pediatric

practicewithMedicaid

patients


childrenin

the

enhance

daccess

program

Controlgroup:26,066

Medicaid-eligible

childrenwhorece

ived

servicesfrom

other

loca

lco

mmunityprimary

care

providers

Increase

dca

reco

ordination,ca

semanagement,expanded

after-hours

clinicsandwalk

inhours

atclinic

20%

reductionin

ED

utilizationforthe

intervention

group(p

=0.007)

Cost

permember

permonth

was

$8.53wasfoundin

the

controlgroup

and$7.17in

intervention

group,

thusaco

mparative

savingsof16%

CHCs=co

mmunityhealthce

nters;GPCs=grouppractitionerco

operatives;

RR

=rate

ratio.


ED use. A review of interventions targeted at frequentED use included 11 studies, of which the intervention inseven was case management.6 The results were mixed,with the majority of observational trials showing reduc-tions in ED use, but one showing an increase, and onlyone out of three randomized trials showing a reduction.

More recently, Flores-Mateo et al.7 examined inter-ventions that increased the supply of non-ED servicesand those that reduced demand. Similar to our findings,the authors concluded that increasing the supply of pri-mary care physicians and cost sharing with patientswere effective in reducing ED use, but increased out-of-hours primary care was not. However, there were dif-ferences in our methods, especially inclusion criteria.We included different types of studies, specifically pedi-atric studies, physician capitation, advanced accessscheduling, and prehospital diversion and excludedED-based studies, telephone triage, those with surveydata, and those without controls. As a result, theauthors of the prior review found that educational inter-ventions did not appear to reduce ED use, while wefound the opposite.

We also reviewed the articles for the effect on utiliza-tion of other health care settings. About half of the arti-cles reported this data, although the results werepresented in different ways (primary care visits, urgentcare visits, specialist visits, etc.) and varied significantlyby category. Two of five (40%) of the education studiesthat examined non-ED use found decreases in use,while the others found no significant effect, suggestingthat perhaps education may reduce use in general,rather than the possibility of induced demand by addingcapacity. Both of the studies on prehospital diversionand five of 10 (50%) of those on capacity increasesfound increases in non-ED use, which may represent atype of substitution effect in which patients do notreduce their overall consumption of health care, butinstead shift it to other settings. Again, many of thesestudies took place in single-payer systems wherepatients may have more access to primary care settings,whereas in the United States, access could limit thisshift. Only two of 10 (20%) studies on patient financialincentives examined non-ED use, and these showedreductions. Often, though, copayments were imple-mented both inside and outside the ED, so it is difficultto tease apart direct and indirect effects on ED use.Interventions involving managed care showed mixedresults with some increasing and some decreasing non-ED use.

Seventeen of the 29 studies (43.5%) reported adverseevents, and the outcomes used varied widely, althoughno significant adverse events were attributed to inter-ventions. The health outcome that was generally mea-sured was hospitalization, and this is really a secondaryoutcome, with morbidity and mortality being the pri-mary health outcome of interest. Similarly, only eight ofthe 39 articles (20.5%) reported any cost data, whichwas both limited and mixed. Some of the interventionsmay have ethical questions. For one, those with finan-cial implications for patients may result in patientsavoiding needed care and could result in worse healthoutcomes, and in the long run, possibly increased coststo the health care system. Another example is systemsT

able

3Prehosp

italDiversionofLow-acu

ityPatients

Author(Year)

Design

Population

Intervention

Effect

onED

Use

Effect

onNon-ED

Use

Sch

aeferetal.

(2002)25

Cohort

studywithmatched

historica

lco

ntrols

UnitedStates

August

2000–J

anuary

2001

TwoEMS

Interventiongroup:

1,016patients

Control(historica

l)group:2,617patients

Low-acu

itypatients

intheintervention

groupwere

offered

analternate

care

sources(clinic

orhome

care)ratherthan

ED

use

bytheEMSstaff

There

was7%

fewerED

use

bytheinterventiongroup

comparedto

theco

ntrolgroup

(44.6%

vs.

51.8%)(p

=0.001)

Clinic

use

:there

was3.5%

more

clinic

use

bytheintervention

groupco

mparedto

theco

ntrol

group(8%

vs.

4.5%)(p

=0.001)

Notransp

ort

(homeca

re):there

was3.7%

more

homeca

re(no

transp

ort)bytheintervention

groupco

mparedto

theco

ntrol

group(47.4%

vs.

4.5)(p

=0.043)

Snooks

etal.

(2004)26

Clusterrandomized

controlledtrial

UnitedKingdom

6months

TwoEMS.

Interventiongroup:

409patients

Controlgroup:

425patients

Low-acu

itypatients

intheintervention

groupwere

tran

sportedto

aMIU

bytheEMSstaff

There

was2.8%

fewerED

use

bytheinterventiongroup

comparedto

theco

ntrol

group(74.1%

vs.

76.9%)

MIU

use

:there

was1.3%

more

MIU

use

bythe

interventiongroupco

mpared

totheco

ntrolgroup(10%

vs.

8.7%)

MIU

=minorinjuriesunit.


Table

4ManagedCare

(CapitationorGateke

eping)

Author(Year)

Design

Population

Intervention

Effect

onED

Use

Effect

onNon-ED

Use

OtherOutcomes

Intervention:Gateke

eping

Badgett

(1986)2

7Before-and-after

study

UnitedStates

3years

1983–1

985

Single,pediatric

ED

Interventiongroup:patients

assignedto

PCPunder

AFDC

recipients,

estim

ated~4

0,000

Controlgroup:sa

megroup

ofpatients,1yearprior

tostart

ofprogram

Citicare

program

(PCPapproval

requiredforED

services),

providedphysicianco

verage

24hours

aday,7daysaweek

TotalED

visits:

Pre:35,704

During:25,543

Post:31,248

TotalED

use

decrease

d23%

during

thestudyperiod

comparedto

periodafterend

ofprogram,for

patients

enrolledin

AFDC

program,

ED

use

decrease

d46%

Notreported

Totalhosp

italadmissionsfrom

ED

(nosignifica

ntch

ange):

Pre:3,545

During:3,555

Post:3,922

Franco

etal.

(1997)3

1

Prosp

ective

cohort

studywith

historica

lco

ntrols

Single,university-base

dpediatric

clinic.

Medicaid

patients.


patients

(July

1–A

ugust

30,1991)

Controlgroup:2,798

patients

(July

1–A

ugist

30,1981)

Program

requiringPCP

approvalforED

use

ED

visitsdeclined

2.4%

(p=0.00005)

Inappropriate

ED

visits

declined33%

(p<0.00001)

Notreported

Notreported

Hurley

etal.

(1989)3

3

Retrosp

ective

cohort

study

FourMedicaid

demonstration

programs

Interventiongroup:AFDC

inprogram

requiring

gateke

eperapproval

Controlgroup:recipients

oftraditionalMedicaid

programs

AssignedPCPwithapproval

requiredforED

services

Proportionofpatients

withone

ED

visitsh

owedreductions

from

27.5%

to36.7%

inch

ildren,

andbetw

een30.6%

to44%

foradults

None

None

Murphy

etal.

(1997)3

5

Before-and-after

study

Ireland

1993–1

995

Large,single

ED

Interventiongroup:Patients

were

GMS

ineligible

did

not

qualify

forfreeca

rein

Ireland

Controlgroup:allpatients

whovisitedED

Patients

whowere

GMS

ineligible

were

chargeda

certain

amountforeach

visit

totheED

insteadoftheir

GP.

Ifthepatienthadaletterof

referralfrom

aGP,they

were

exemptedfrom

thech

arge.

Thetotalnumberof

GMS

ineligible

visitedtheED

duringtheyear

before

theim

plantationofthe

copaymentwas19,562/43,202

(45.3%)andin

the

yearafterwas

19,947/45,302(44%),

whichsh

ows

areductionby1.3%

(95%

CI=–0

.6to

–1.9)

AmongtheGMS-ineligible

patients

referredbya

GPto

theED,thetotal

numberofthis

groupin

theyearbefore

was

2,619/19,562(13.4%)and

theyearafter3,156/19,947

(15.8%),anincrease

of

2.4%

(95%

CI=1.73to

3.1)

Notreported

Sch

illinger

etal.

(2000)3

8

Randomized

controltrial

UnitedStates

1997–1

998

Single,university-affiliated

primary

care

practice

Interventiongroup:

1,121patients


Interventiongrouprequired

PCPapprovalforaccess

tosp

ecialtyandED

services

Nonsignifica

ntincrease

inrisk-adjusted,nonurgentED

visitsin

interventiongroup

(0.06visits/patient/year,

p=0.42)

PCPvisits:

nonsignifica

nt

increase

inintervention

group(0.27visits/patient/

year,

p=0.14)

Specialtyvisits:

significa

nt

reductionin

visitsin

interventiongroup

(0.57visits/patient/

year,

p=0.04)

Inpatientca

re:significa

ntreduction

inhosp

italizationsin

intervention

group(0.14hosp

italizations/

patient/year,

p=0.02)


Table

4Continued

Author(Year)

Design

Population

Intervention

Effect

onED

Use

Effect

onNon-ED

Use

OtherOutcomes

Intervention:Capitation/PhysicianPayment

Catalano

etal.

(2000)2

8

Interrupted

time-series

quasi-

experiment

Pediatric

Medicaid

patients,

single

state

Interventiongroup:recipients

inareaswithca

pitation


inareaswithoutca

pitation

Communitymentalhealth

centers

underca

pitated

agreementwithMedicaid.

Centers

billedbyhosp

ital

EDsforpsy

chiatric

emergency

services.

Nosignifica

ntincrease

inthelevelofED

usa

ge

Decrease

ininpatient

psy

chiatric

admission

Increase

inoutpatient

visitsin

forfor-profit

capitatedareas

Estim

ateddecrease

by$17–$

21

millionover1yearin

total

(inpatientandoutpatient)

costs

Catalano

etal.

(2005)2

9

Interrupted

time-series

quasi-

experiment

Single-state,Medicaid

patients

yearpriorandafter

intervention

Interventiongroup:recipients

inareaswithca

pitation


inareaswithoutca

pitation

Communitymentalhealth

centers

underca

pitated

agreementwithMedicaid.

Centers

billedbyhosp

ital

EDsforpsy

chiatric

emergency

services

28%

declinein

psy

chiatric

ED

visitsco

mpared

toexpected

Notreported

Notreported

Dicke

yetal.

(1996)3

0

Before-

and-after

quasi-

experiment

Single-state,Medicaid

patients

Interventiongroup:

10,685patients

(1993)

7,541patients

(1994)

Controlgroup:

6,614patients

(1991)

7,295patients

(1992)

Single

providerofpsy

chiatric

services(inpatients

and

outpatient)

contractedwith

state

underca

pitatedagreement

19%

decrease

inED

visits

inyears

afterintervention

comparedto

years

prior

Nonquantifiedincrease

inoutpatientvisits

Inpatientadmission

decrease

dby4%

Medianlength-of-stay

decrease

dby3.3

days

Increase

in30-dayreadmissions

by1.9%

Reductionin

expenditures

perbeneficiary

$420

Glazier

etal.

(2009)3

2

Retrosp

ective

cohort

study

Canada

2005–2

006

Single

province

inco

untrywith

universalhealthca

resy

stem


patients

inprimary

care

practices

ofphysicianswhoch

ose

capitatedsy

stem

Controlgroup:

2,517,527patients

inprimary

care

practicesof

physicianswhoch

ose

fee-for-se

rvicesy

stem

Physiciansreim

bursedby

age-andse

x-adjusted

capitationpayments

and

requiredpatientenrollment

(stilleligible

forfee-for-se

rvice

payments

forhosp

italse

rvices)

Noch

angein

ED

visitsin

capitationgroupvs.

same

physicianspreca

pitation

Increase

like

lihoodof

OR

=1.20,95%

CI=1.15

to1.25)forca

pitation

groupvs.

fee-for-se

rvice

group(4%

more

patients

inca

pitationgroupmade

visitsto

ED

Higherratiooflow-acu

ity

visitsamongca

pitation

(1.6)vs.

control(0.9)groups

Less

after-hours

care

inca

pitationpractices

(OR

=0.68,95%

CI=0.61to

0.75)

Lowermorbidityandco

morbidity

indicesin

capitationpractices

Jose

phso

netal.

(1997)3

4

Retrosp

ective

cohort

study

Members

offiveinsu

rers

inonecity

Interventiongroups:

22,316

patients

infully

capitatedHMO

38,030patients

inany

ofthreeIPA


inatraditionalindemnity

insu

rance

plan(estim

ated)

Capitationin

HMO.In

IPA,

capitatedpayments

tothe

associationbutfee-for-se

rvice

compensa

tionofphysician

ED

use

rates(p

<0.05):

70per1000members

inca

pitatedpanel,

363per1000members

inIPA

panel,

466per1000members

inindemnitypanel(85%

lowerED

use

ratesin

capitatedvs.

indemnitypanel)

None

Admissionforfiveambulatory

sensitiveco

nditions

0.8

per1000members

inca

pitatedpanel,

2.7

per1000members

inIPA

panel,

2.9

per1000members

inindemnitypanel


designed with physician or nurse gatekeepers who takeaway the patient’s autonomy by dictating whetherinsurance will cover an ED visit. Our findings, takenalong with prior reviews, are promising that non-EDinterventions designed to reduce ED visits may be suc-cessful; however, it is clear that more study is needed tounderstand the most effective ways to reduce ED use.

When organizations decide that reducing ED visits isa priority, the choice must be made which interventionsshould be implemented. We think that the choice shouldbe made based on organization priorities and consider-ing the profile of pros and cons for each intervention.For example, education is simple, can be inexpensive,and has an added benefit of improving health literacy;however, it is difficult to standardize. On the otherhand, managed care and patient financial incentives arepowerful tools but may have unintended consequences,like deferring needed care or limiting patient choice. Inaddition, adding capacity may have the opposite effectas desired. However, we can conclude that reducing EDuse will require broad, organizational changes. Changecould include a careful multilayered approach integrat-ing several interventions along with a feedback mecha-nism to monitor outcomes and adverse events.

Future research should attempt to delineate thebalance of intended and unintended effects of theseinterventions. Across all categories, more exploration ofthe effect on health outcomes and costs would be bene-ficial. Regarding education, researchers should considerfurther study of specific educational materials, frombooklet to in-person teaching, or even technology-basedsolutions. EMS diversion has such limited data that anydeeper examination of this area would add to ourknowledge, especially focusing on the safety and accu-racy of EMS assessments. Most of the managed carestudies are observations of large-scale systemic changesover several years. More randomized controlled trialsare needed across all categories to reduce confoundingand improve the generalizability of results.

LIMITATIONS

Many of the studies reported were observational withthe potential for confounders, and few studies reportedrisk-adjusted data. In addition, some of the paymentreform interventions were part of a bundle of changes,and it was impossible to unwind which specific inter-vention (or just the combination) was responsible forthe changes in utilization. Many studies were similarlyrestricted to a single site, which reduces the generaliz-ability to other settings.

Our primary audience was EDs in English-speakingparts of the world; therefore, we included only studiespublished in English. As a result, this study may missimportant findings from non-English studies. Also, eightof the 39 studies were based in Canada or Europe,while the rest were in the United States, and differencesin health care systems, in particular the presence ofsingle payer versus multipayer systems, may affectoutcomes.

There was also variability in the interventions admin-istered as well as the outcomes reported. For example,some studies reported total ED visits whereas othersT

able

4Continued

Author

(Year)

Design

Population

Intervention

Effect

onED

Use

Effect

onNon-ED

Use

OtherOutcomes

Piehl

etal.

(2000)3

6

Before-and-after

study

UnitedStates

1995–1

997

Pediatric

visitsattw

oco

mmunity

EDsover2year,

determ

inedrates

ofED

visitsafterim

plementation

ofmanagedca

replan

Interventiongroup:

Medicaid-m

anagedca

rewith20,663

ED

visitsControlgroup:non-M

edicaid

group:34,079ED

visits

Managedca

reprogram

(recipients

haveassigned

PCPand24-houraccess,at

least

telephone);PCPrece

ived

monthly

feeforeach

enrollee

inadditionto

fee

foreach

service

Medicaid

group:24%

reductionin

overall

ED

visits(p

<0.001)(33.5

[SD

�5.3]

reduce

dto

25.6

[SD

�2.3]monthly

ED

visitper1,000enrollees);37%

reduction

innonurgentED

visits(p

<0.001)

Non–M

edicaid-insu

redgroup:

8%

increase

inoverallED

visits(p

<0.001)

8%

increase

innonurgentED

visits(p

notgiven)

Notreported

Notreported

Price etal.

(1999)3

7

Retrosp

ective

cohort

study

UnitedStates

Oneyear

Threeasthmatic

pediatric

patients

groupsbase

dontheir

typeofinsu

rance

Fee-for-se

rvicegroup:

47patients

Capitated(H

MO)group:

24patients

Medicaid

group:22patients

Theeffect

ofthetypeof

insu

rance

onthemedical

care

use

in1year

ED

use

:Feeforse

rvice,2/47(4%);

Capitated,6/24(25%);

Medicaid,7.5/22(34%);

p=0.038

Physicianvisits

Feeforse

rvice,12/47

(25%);Capitated,12/24

(50%);Medicaid,9.5/22

(43%);p=0.56

Specialist

visits

Feeforse

rvice,6/47

(12.7%);Capitated,

7.5/24(31%);Medicaid,

3/22(13.6%);p=0.118

Hosp

italvisits

Feeforse

rvice,2/47(4%);

Capitated,2/24(8.3%);

Medicaid,3/22(13.6%);

p=0.14

AFDC

=Aid

toFamilieswithDependentChildren;GMS

=GeneralMedicalServices;

GP=generalpractitioner;

HMO

=healthmaintenance

organization;IPA

=independentprac-

tice

associations;

PCP=primary

care

clinic.


Table

5PatientFinancialInce

ntives

Author(Year)

Design

Population

Cost

Intervention

Effect

onED

Use

Effect

on

Non-ED

Use

OtherOutcomes

Intervention:Copayment/Coinsu

rance

Hsu

etal.

(2006)3

9Quasi-experimental,

longitudinal,

concu

rrentco

ntrols

UnitedStates

1999–2

001

Riskadjusted

Prepaid

integrateddelivery

system,

19medicalce

nter

Interventiongroup:

commercially

insu

red,2,257,445patients

(copaymentlevels:$0,$1–$

5,

$10–$

15,

$20–$

35,and$50–$

10perED

visit)

Controlgroup:

Medicare,withemployer

supplementation,261,091

patients

(copaymentlevels:$0,$1–$

15,

and$20–$

50perED

visit)

•Compariso

nofvarious

copayment

levels

over36-m

onth

timeperiod

•Copaymentlevelch

ose

nbyemployer,

notpatient

•In

commerciallyinsu

red

group,risk-adjustedRR

of

ED

visitco

mparedto

no

copaymentgroupwas0.96

for$1–5

copaymentgroup

(CI=0.96–0

.97),0.93for$10

–15(CI=0.92–0

.94)0.88for

$20–3

5(CI=0.87–0

.89)0.77

for$50–1

00(CI=0.76–0

.77)

•In

Medicare

group,RR

ofED

visitco

mparedto

noco

pay-

mentgroupwas0.97for$1–

15co

paymentgroup

(CI=0.96–9

9)0.96for$20–

50(CI=0.94–0

.97)

Notreported

•Nosignifica

ntch

angein

hosp

italizations,

ICU

admission,anddeathswith

higherco

paymentrates

exce

ptthefollowing:

•In

commerciallyinsu

red

group,death

rate

was

significa

ntlyhigherin

lowest

copaymentlevelof

$1–$

5co

mparedto

no

copaymentwithRR

=1.09

(CI=1.02–1

.16)

•In

Medicare

group,highest

copaylevel($20–$

50)with

decrease

dmortality

rate

(RR

=0.87,CI=0.83–0

.91)

Loweetal.

(2008)4

7Before-and-after

obse

rvational

study

UnitedStates

48months

26EDs,

purposivesa

mple

of

thestate

Interventiongroup:post–

Oregon

healthplancu

tbacks

Controlgroup:pre–O

regon

healthplancu

t-backs

Fivegroupsofpatients

base

dontheclass

ofpayer:

•Commerciallyinsu

red

•Oregonhealthplan

•Uninsu

red

•Medicare

•Others

payers

Medicaid

cutback,Oregon:the

beneficiariesoftheOregon

healthplanrece

ivenew

policy

changesthatinclude

copaymentformost

ofthe

healthse

rvices(PCPvisits,

ED

use

,andhosp

italization);

decrease

denrollmentin

healthplanwithincrease

dnumberofuninsu

redpatients

•Oregon

health

plan

20%

reductionin

ED

visits/month

(CI=13–1

8)

•Uninsu

red

20%

increase

inED

visits/

month

(CI=13to

18)

Notreported

Hosp

italizationfrom

ED

visit

(adjustedORs):

•Commercial

0.99(CI=0.95–1

.04)

•Oregonhealthplan

1.09(CI=1.03–1

.16)

•Uninsu

red

1.50(CI=1.39–1

.62)

•Medicare

1.10(CI=1.06–1

.13)

Loweetal.

(2010)4

0Before-and-after

study

UnitedStates

2001–2

004

State

populationstudy

Interventiongroup:

Medicaid

enrolleeswiththe

standard

plan

Controlgroup:Medicaid

enrollees

withtheplusplan(not

affected

bycu

tbacks)

Medicaid

cutback,Oregon:

Thebeneficiariesofthe

Oregonhealthplanrece

ive

new

policy

changesthat

includeco

payment

formost

ofthehealth

services(PCPvisits,

ED

use

,andhosp

italizationand

eliminatedoutpatient

behavioralhealth

services

Decrease

inED

use

rates

(RR

=0.84;95%

CI=0.83–

0.86).Comparedto

PlusPlan

members,use

alsodecrease

d(RR

=0.82;95%

CI=0.80–

0.84)

Injury-relatedvisitsalso

decrease

d(p

<0.001).

Notreported

ED

visitsleadingto

hosp

ital

admissionalsodecrease

d:

(RR

=0.83;95%

CI=0.79–

0.86).Comparedto

Plus

Planmembers,utilization

alsodecrease

d(RR

=0.85;

95%

CI=0.82–0

.89).

Mortense

n(2010)4

8Quasi

experimental,

pre–p

ost

design

(difference

s-in-

difference

smethodology)

24months

Riskadjusted

State-levelstudyamong

Medicaid

enrolleesin

29states.

Interventiongroup:Medicaid

enrollees

instateswithco

payment

increase

(ninestates)

Controlgroup:Medicaid

enrolleesin

stateswithoutno

copaymentornoco

payment

change(20states)

•Medicaid

ED

visit

copayment

increase

inninestates,

rangingfrom

$3to

$50

Significa

ntincrease

inprobabilityofanyED

visitsin

ayear(33.1

perperson-m

onth

forch

angegroupvs.

24.7

for

controlgroup,p=0.000)

Notreported

Notreported


Table

5Continued

Author(Year)

Design

Population

Intervention

Effect

onED

Use

Effect

onNon-ED

Use

OtherOutcomes

Intervention:HDHP

O’G

rady

etal.

(1985)4

1

Randomized

controlledtrial

UnitedStates

State-levelamongsix

geographic

areasin

fourstates

Interventiongroup:

3,973personswere

assignedrandomly

todifferentfee-for-

serviceinsu

rance

planswithco

payment

ratesof0,25,50,or95%

Aco

insu

rance

rate

of

25,50,or95%—

upto

maxim

um

of$1,000

asout-of-pocket

costs

TheprobabilityofED

use

amongtheco

payment

groupswasfewerthanthefreegroup

•25%

copaymentgroupfewerby15%

(p=0.05)

•50%


•95%


(p=0.01)

•Individual-deductible

planfewerby19%

(p=0.05)

•TheED

use

amongtheco

paymentgroupswas

fewerthanthefreegroup

•25%


(p=0.01)

•50%


•95%


(p=0.01)

•Individual-deductible

planfewerby20%

(p=0.05)

Notreported

TheED

visitresu

ltingin

hosp

italizationamong

theco

paymentgroups

wasfewerthanthefree

group

•25,50,and95%

copaymentgroups

fewerby33%

(p<0.05)

Selbyetal.

(1996)4

2Matchedco

hort

study

Riskadjusted

Group-m

odelHMO,

15medicalce

nters

Interventiongroup:

30,276patients

Controlgroup:60,408

patients

(matchedfor

age,se

x,andloca

tion);

seco

ndgroup37,539

patients

(matched

forsa

me+employer)

Introductionofa

$25–$

35

copaymentforED

use

inanHMO

•Abso

lute

decrease

inED

usa

geby28visits/

100person-yearin

copaymentgroup

•Risk-adjusteddecrease

inED

visits14.6%

more

inco

paymentgroupthaneitherco

ntrol

group(p

<0.001)

•Significa

ntdecrease

sin

visitsforless

emer

gentco

nditionsco

mparedto

emergent

•Nosignifica

ntch

angein

urgentca

reuse

andpediatric

office

visitsovertimebetw

een

groups

•4.4%

decrease

inrate

of

adultoffice

visitsin

copayment

group

•Nonsignifica

ntreduction

inpotentiallyavoidable

hosp

italizationsin

copay

mentgroupco

mparedto

controlgroups

•Significa

ntlylower

adjustedmortality

rate

intheco

paymentgroup

(1.6/1,000)thanin

control

group1(2.2/1,000,

p=0.001)andco

ntrol

group2(2.6/1,000,

p=0.06)

Wallace

etal.

(2008)4

3Retrosp

ective

cohort

study,

difference

-in-

difference

smethodology

UnitedStates

2001–2

004

State

populationstudy,

propensity

score

matchedpopulation

Interventiongroup:

Medicaid

enrollees

withtheStandard

Plan,10,176su

bjects

ControlGroup:

Medicaid

enrollees

withthePlusPlan,

10,319su

bjects

Additionof$50

copaymentforED

visitsthatdid

not

resu

ltin

admission.

Interventionalso

includedelimination

ofce

rtain

benefits

(dental,mentalhealth,

etc.)aswellasother

copayments

(outpatientvisits,

inpatientadmissions,

pharm

acy

,etc).

ED

visitsdecrease

dby7.9%

(p=0.03)in

the

standard

(copayment)

grouprelativeto

the

plusgroup.ED

visitexpendituresbyuse

rincrease

d7.9%

(p=0.03)overthesa

me

timeperioddesp

itethedecrease

Invisits.

Pharm

acy

:decrease

inuse

and

expenditures(–2.2%,

p<0.001;–1

0.5%,p<0.001).

Inpatient:increase

inuse

and

expenditures(+27.3%,p<0.001;

+20.1,p<0.001)

Hosp

italoutpatient:

increase

inuse

andexpenditures

(+13.5%,p<0.001;19.7%,

p<0.001)

Ambulatory:decrease

inuse

(–7.7%,p<0.001)butincrease

inexpendituresbyuse

r(+6.6%,

p=0.75)

Totalexpenditures(+2.2%,

p=0.47)byperson

unch

angeddesp

iteoverall

reductionin

use

(–2.2%,

p<0.001)


Table

5Continued

Author(Year)

Design

Population

Intervention

Effect

onED

Use

Effect

onNon-ED

Use

OtherOutcomes

Intervention:HDHP

Waters

etal.

(2011)45

Retrosp

ective

cohort

study

Riskadjusted

Majorinsu

rerin

single

state,propensity

score

matchedsa

mple

Interventiongroup:1,354HDHPgroup

initiallyin

PPO,thensw

itch

ed

andmaintained

inHDHPforall3studyyears

Controlgroup:1,354members

of

enrolledin

PPO

plan

HDHPwithdeductiblesranging

from

$1,700to

$6,000vs.

PPO

plan.HDHPenrolleesuse

dstandard

PPO

contracted

amounts

before

meeting

their

deductible.

HDHPenrolleeshad

lowerprobabilityof

use

andlevelofuse

(p<0.05)

HDHPenrolleesappeared

tohavedecrease

dprimary

care

use

(p<0.01),but

greatersp

ecialtyphysician

use

(p<0.05)

HDHPenrolleeshadsignifica

ntly

higherprescriptiondrug

utilizationandexpenditures

(p<0.05)

Wharam

etal.

(2007)44

Before-and-after

study

UnitedStates

2001–2

005

Single-state,single-insu

rance

carrier

offeringHDHPandHMO

plans

Interventiongroup:8,724enrolleeswith

HDHPforatleast

6months,

after1year

oftraditionalHMO

Controlgroup:59,557enrolleeswith

traditionalHMO,matchedon

adult/childstatus.

Individuals

intheHDHPgroup

haveannualindividual

deductiblesrangingfrom

$500to

$2,000.Ifthe

expenditure

exce

edsthedeductible,

individuals

payaco

payment

($100)foreach

ED

use

.Individuals

intheintervention

grouphadco

paymentfor

each

ED

($20-$100)and

outpatientvisit($5–$

25).

ED

visitswith10.0%

relativedecrease

(abso

lute

change,20.2

visitsper1,000)in

the

HDHPgroupco

mpared

withco

ntrols

from

base

lineto

follow-up

(95%

CI=–1

6.6%

to–2

.8%;p=0.007)

ED

visitsresu

ltingin

hosp

italizationswith24.7%

relativedecrease

(withan

abso

lute

rate

difference

of

�2.6%

intheHDHPgroup

(95%

CI=�4

1.0%

to�3

.9%;

p=0.02)

ED

expense

perHDHPmember

decrease

dfrom

$75in

the

base

lineyearto

$36in

the

follow-upperiod,anabso

lute

declineof$52,represe

ntinga

58.5%

relativedecline(95%

CI=–6

4.4%

to–5

1.5%;

p<0.001)

Intervention:HealthSavingsAccount

Wilso

netal.

(2008)46

Multiyearcross-

sectionalstudy

UnitedStates

2004–2

006

Riskadjusted

Commercialinsu

rance

planwithboth

comprehensivemajor

medicalandCDHP

Interventiongroup:enrolleesofCDHP

planforthestudyyear

Controlgroup:enrolleesoftraditional

comprehensivemajormedicalplan

CDHPincludesavariety

of

productsincludinghealth

reim

bursementaccounts

and

healthsa

vingsaccounts,

whichare

portable

ifan

employeeleaves

his

orheremployer.

Alloffer

first-dollarco

veragefor

preventivese

rvices.

Afterrisk

adjustment,

CDHPplanmembers

had

129.1

vs.

141.2

ED

visits/

1,000members/year

CDHP=co

nsu

mer-driven

health

plan;HDHP=high-deductible

health

plan;HMO

=health

maintenance

organization;ICU

=intesive

care

unit;PCP=primary

care

provider;

PPO

=preferredproviderorganization;RR

=rate

ratio.


reported ED visits per user. This made comparisonbetween the studies difficult and limits the ability todraw robust conclusions from the findings of thereview.

CONCLUSIONS

We found that about two-thirds of the studied interven-tions showed reductions in ED use. Future studiesshould attempt to reduce confounding through robustdesign (i.e., randomization) and should measure unin-tended consequences of increased demand for othertypes of health care services, health outcomes, andfinancial effects.

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Table 6Quality Assessment of Selected Observational Studies on Non-ED Interventions to Reduce ED Utilization Using the Grading ofRecommendations Assessment, Development, and Evaluation(GRADE) Criteria

Possible limits of observational studies

1. Failure to develop and apply appropriate eligibility criteria(inclusion of control population)

2. Flawed measurement of both exposure and outcome3. Failure to control confounders and to measure all known

prognostic factors4. Imprecision of outcomes (i.e., wide CIs)5. Incomplete follow-up

First Author (Reference)Existing

LimitationsOverall Qualityof Evidence

Patient educationGlavan (10) 1, 3, 4 Very lowMcWilliams (11) 1, 3 Very lowSchonlau (13) 1, 3 Very low

Non-ED capacity increaseChalder (22) 1, 2, 3 Very lowHsu (24) 1, 3, 4 Very lowHudec (15) 1, 3, 4 Very lowO’Kelly (16) 1, 2, 3, 4 Very lowPhilips (23) 1, 2, 3 Very lowRust (19) 1, 2, 3 Very lowSolberg (20) 1,2,3 Very lowSolberg (21) 1,2,3,4 Very lowvan Uden (17) 1, 2, 3 Very lowWang (18) 2, 3 Very low

Prehospital diversionSchaefer (25) 1, 3, 5 Very low

Managed careBadgett (27) 1, 3, 4 Very lowCatalano (28) 1, 3 Very lowCatalano (29) 1,3, 4 Very lowDickey (30) 1, 3, 4 Very lowFranco (31) 1, 2, 3 Very lowGlazier (32) 1, 3 Very lowHurley (33) 1, 2, 3, 4 Very lowJosephson (34) 1,3, 4 Very lowMurphy (35) 1, 3 Very lowPiehl (36) 3, 4 Very lowPrice (37) 2, 4 Very low

Patient financial incentivesHsu (39) 3 Very lowLowe (47) 1, 2, 3 Very lowLowe (40) 2, 3 Very lowMortensen (48) 1, 2, 3, 5 Very lowSelby (42) 3 Very lowWallace (43) 3 Very lowWaters (45) 2, 3,4 Very lowWharam (44) 1,3,5 Very lowWilson (46) 2, 3 Very low


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APPENDIX

MEDLINE SEARCH TERMS

(((“emergency medical services” [all fields] OR “emer-gency medicine” [all fields] OR “emergency department”[all fields]) AND ((“utilization” [subheading] OR “utiliza-

tion” [all fields]) OR demand [all fields] OR visits [allfields])) AND (“intervention” [all fields] OR “solutions”[MeSH Terms] OR “solutions” [all fields])) AND(“advanced access” [all fields] OR “primary care” [allfields] OR capacity [all fields] OR “extended hours” [allfields] OR “telephone triage” [all fields] OR “care man-agement” [all fields] OR “patient education” [all fields]OR “general practitioner” [all fields] OR “care coordina-tion” [all fields] OR copayment [all fields] OR diversion[all fields] OR acuity [all fields]) AND English [lang]AND English [lang].

Supporting Information

The following supporting information is available in theonline version of this paper:

Data Supplement S1. PRIMSA flow diagram.Data Supplement S2. Quality assessment of selected

randomized trials on non-ED interventions to reduceED use using the Grading of Recommendations Assess-ment, Development, and Evaluation (GRADE) criteria.


emergency department interventions to reduce ed ... · non–emergency department interventions to...

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