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Organizational Context & Organizational Context & Penetration of QI Interventions: Penetration of QI Interventions: Case Studies from Implementing Depression Case Studies from Implementing Depression Collaborative Care Collaborative Care Elizabeth Yano PhD Elizabeth Yano PhD 1, 2 1, 2 ; JoAnn Kirchner MD ; JoAnn Kirchner MD 3, 4 3, 4 ; ; Jacqueline Fickel PhD Jacqueline Fickel PhD 1 ; Louise Parker PhD ; Louise Parker PhD 3 ; ; Mona Ritchie MSW Mona Ritchie MSW 3 ; Chuan-Fen Liu PhD ; Chuan-Fen Liu PhD 5,6 5,6 ; ; Edmund Chaney PhD Edmund Chaney PhD 5,6 5,6 ; ; Lisa Rubenstein MD Lisa Rubenstein MD 1,7,8 1,7,8 1 VA Greater Los Angeles HSR&D Center of Excellence; VA Greater Los Angeles HSR&D Center of Excellence; 2 UCLA School of Public UCLA School of Public Health; Health; 3 Center for Mental Health Outcomes Research, Little Rock AR; Center for Mental Health Outcomes Research, Little Rock AR; 4 University of Arkansas Medical Sciences; University of Arkansas Medical Sciences; 5 Northwest Center for Outcomes Northwest Center for Outcomes Research, Seattle WA; Research, Seattle WA; 6 University of Washington, Seattle; University of Washington, Seattle; 7 UCLA School of Medicine; UCLA School of Medicine; 8 RAND Health RAND Health

Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

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Organizational Context & Penetration of QI Interventions: Case Studies from Implementing Depression Collaborative Care. Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ; Jacqueline Fickel PhD 1 ; Louise Parker PhD 3 ; Mona Ritchie MSW 3 ; Chuan-Fen Liu PhD 5,6 ; Edmund Chaney PhD 5,6 ; - PowerPoint PPT Presentation

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Page 1: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

Organizational Context & Penetration of QI Organizational Context & Penetration of QI Interventions: Interventions: Case Studies from Implementing Case Studies from Implementing

Depression Collaborative CareDepression Collaborative Care

Elizabeth Yano PhDElizabeth Yano PhD1, 21, 2; JoAnn Kirchner MD; JoAnn Kirchner MD3, 43, 4; ;

Jacqueline Fickel PhDJacqueline Fickel PhD11; Louise Parker PhD; Louise Parker PhD33; ;

Mona Ritchie MSWMona Ritchie MSW33; Chuan-Fen Liu PhD; Chuan-Fen Liu PhD5,65,6; ;

Edmund Chaney PhDEdmund Chaney PhD5,65,6; ;

Lisa Rubenstein MDLisa Rubenstein MD1,7,81,7,8

11VA Greater Los Angeles HSR&D Center of Excellence; VA Greater Los Angeles HSR&D Center of Excellence; 22UCLA School of Public Health; UCLA School of Public Health; 33Center for Center for Mental Health Outcomes Research, Little Rock AR; Mental Health Outcomes Research, Little Rock AR; 44University of Arkansas Medical Sciences; University of Arkansas Medical Sciences;

55Northwest Center for Outcomes Research, Seattle WA; Northwest Center for Outcomes Research, Seattle WA; 66University of Washington, Seattle; University of Washington, Seattle; 77UCLA School of Medicine; UCLA School of Medicine; 88RAND Health RAND Health

Page 2: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

BackgroundBackground

““It’s not your father’s Army any more…”It’s not your father’s Army any more…”– It’s not your father’s VA any more eitherIt’s not your father’s VA any more either

VA’s quality transformation VA’s quality transformation (1990s to current)(1990s to current)

– Reorganization towards primary careReorganization towards primary care– Adoption of electronic medical recordsAdoption of electronic medical records– Incentivized performance audit-and-feedbackIncentivized performance audit-and-feedback– Capitated budgets/resource allocation Capitated budgets/resource allocation

Parallel with substantial HSR investmentParallel with substantial HSR investment

Page 3: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

Quality Enhancement Research Quality Enhancement Research Initiative (QUERI)Initiative (QUERI)

National disease targetsNational disease targetsQUERI CentersQUERI Centers

Research-clinical partnerships designed to Research-clinical partnerships designed to implement research into practiceimplement research into practice

Mental Health QUERIMental Health QUERI– Depression particularly common and disablingDepression particularly common and disabling– Implementation of depression collaborative care Implementation of depression collaborative care

as national strategic priority for primary careas national strategic priority for primary care

Page 4: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

Depression Collaborative CareDepression Collaborative Care

Forges shared care between PC and MHForges shared care between PC and MH

PC provider education PC provider education

Informatics-based decision supportInformatics-based decision support

Leadership supportLeadership support

Depression care managerDepression care manager– Telephone assessment of + screensTelephone assessment of + screens– Telephone management and follow-upTelephone management and follow-up– Based in PC but supervised by MH specialistBased in PC but supervised by MH specialist

Page 5: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

Substantial Evidence Base DemonstratesSubstantial Evidence Base DemonstratesEffectiveness of Collaborative CareEffectiveness of Collaborative Care

Feasible, cost-effective care models showFeasible, cost-effective care models show– Improved quality of life for up to five yearsImproved quality of life for up to five years– Reduced job lossReduced job loss– Improved financial statusImproved financial status– Higher satisfaction and participation in careHigher satisfaction and participation in care– Reduced disparities in care and outcomesReduced disparities in care and outcomes– Improved chronic disease status (HbA1C)Improved chronic disease status (HbA1C)

More than 10 randomized controlled trialsMore than 10 randomized controlled trials

Page 6: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

Models Increase Efficiency…Models Increase Efficiency…

Reduce primary care visitsReduce primary care visits

Maintain current rate of MHS visitsMaintain current rate of MHS visits

Use MHS resources more effectivelyUse MHS resources more effectively

Cost-saving (due to reduced medical care Cost-saving (due to reduced medical care costs) after first yearcosts) after first year– One randomized trial, included VAOne randomized trial, included VA

Page 7: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

Research ObjectiveResearch Objective

Routine-care implementation of Routine-care implementation of depression collaborative care in VA depression collaborative care in VA primary care practicesprimary care practices– Little known about factors underlying Little known about factors underlying

intervention penetrationintervention penetration– Objective:Objective: To evaluate influences of To evaluate influences of

organizational characteristics on degree of organizational characteristics on degree of penetration during implementationpenetration during implementation

Page 8: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

INDIVIDUAL (LEADER)CHARACTERISTICS

EXTERNALCHARACTERISTICS OF

THE ORGANIZATIONSystem openness

INTERNALCHARACTERISTICS OF

ORGANIZATIONALSTRUCTURE

Collaborative Care forDepression in VAInterconnectedness (+)

Organizational slack (+)Size (+)

Centralization (-)Complexity (+)Formalization (-)

Factors Associated with Adoption and Diffusion of Collaborative Care as an Organizational Innovation

Source: Adapted from Rogers EM. Diffusion of innovations. New York: The Free Press, 1995.

ORGANIZATIONALINNOVATION

Page 9: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

Study Design & SampleStudy Design & Sample

Part of larger group RCT of collab carePart of larger group RCT of collab careImplementation thru evidence-based QIImplementation thru evidence-based QI– Expert-panel consensus development among Expert-panel consensus development among

PC and MH leadersPC and MH leadersImplementation priorities Implementation priorities Care model specifications Care model specifications

Seven 1Seven 1stst-generation primary care -generation primary care practicespractices– Across 3 VA networks spanning 5 statesAcross 3 VA networks spanning 5 states

Page 10: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

Data Sources & MeasuresData Sources & Measures

VA administrative data (“Austin”) (caseload)VA administrative data (“Austin”) (caseload)Organizational site surveysOrganizational site surveys– Measures of internal organizational structure (e.g., Measures of internal organizational structure (e.g.,

centralization, complexity)centralization, complexity)– Measures of external organizational context (e.g., Measures of external organizational context (e.g.,

urban/rural location)urban/rural location)

Intervention penetration reportsIntervention penetration reports– % PC providers referring patients, # consults/FTE% PC providers referring patients, # consults/FTE

Validated by qualitative data from semi-Validated by qualitative data from semi-structured stakeholder interviews structured stakeholder interviews – Senior/mid-level health care managers, PC/MH Senior/mid-level health care managers, PC/MH

providers, depression care managersproviders, depression care managers

Page 11: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

Principal FindingsPrincipal Findings

Practices ranged from 4,600-14,000 patientsPractices ranged from 4,600-14,000 patients among 4-11 PCPsamong 4-11 PCPs

Depression diagnosis ranged from 1-10% of Depression diagnosis ranged from 1-10% of population of PC patientspopulation of PC patientsReported level of implementation high (7-9 out of Reported level of implementation high (7-9 out of 9-point scale)9-point scale)Sense of PC-MH collaboration variableSense of PC-MH collaboration variable– Difficulty deciding if PC or MH responsibleDifficulty deciding if PC or MH responsible

Penetration highly variablePenetration highly variableLimited regional consistency Limited regional consistency – One VISN high penetration but different approachesOne VISN high penetration but different approaches

Page 12: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

PC Provider PenetrationPC Provider Penetration

0

10

20

30

40

50

60

70

80

90

100

A1 A2 B1 B2 B3 C1 C2

% PCPs Started 1st 6 Months

Network #1 Network #2 Network #3

Page 13: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

PC Provider PenetrationPC Provider Penetration

0

10

20

30

40

50

60

70

80

90

100

A1 A2 B1 B2 B3 C1 C2

0

5

10

15

20

25

30% PCPs StartedConsults/FTE

% PCPs Started 1st 6 Months

Network #1 Network #2 Network #3

Referrals/PCP FTEs

Page 14: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

Organizational Context & PenetrationOrganizational Context & Penetration

0

5

10

15

20

25

30

A1 A2 B2 C1 C2 B3 B1

Referrals/PCP FTE

MEDMED

MED

HIGH HIGHHIGH

LOW

# Months: 16 20 18 2 6 9 21

Small Small Rural Small Small Semi- Rural city city city city rural

Levels of early PCP penetration

Page 15: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

Organizational Context & PenetrationOrganizational Context & Penetration

High PenetrationHigh Penetration Low PenetrationLow Penetration

Low practice authorityLow practice authority

Variable resourcesVariable resources

QI activity variableQI activity variable

PC education PC education ~low~low

No PC-MH case confsNo PC-MH case confs

Med-to-high authorityMed-to-high authority

Variable resourcesVariable resources

QI activity variableQI activity variable

PC education med-hiPC education med-hi

No PC-MH case confsNo PC-MH case confs

Page 16: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

Organizational Context & PenetrationOrganizational Context & Penetration

Speed or extent of penetration not influenced by:Speed or extent of penetration not influenced by:– PC and MH provider relationshipsPC and MH provider relationships– Area characteristics (eg, urban/rural location)Area characteristics (eg, urban/rural location)– Practice size Practice size

Except for largest practice (>14,000 patients)Except for largest practice (>14,000 patients)

Initiating early collaborative care referral did not Initiating early collaborative care referral did not predict future referral behaviorpredict future referral behavior

Highest referral rates typically among practices Highest referral rates typically among practices with lowest perceived MH staffingwith lowest perceived MH staffing

Page 17: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;

ImplicationsImplications

VA an exceptional laboratory in which to VA an exceptional laboratory in which to translate research into practicetranslate research into practice– Common electronic medical recordsCommon electronic medical records– Identifiable management structuresIdentifiable management structures– Common policies and proceduresCommon policies and procedures

Effective penetration may have less to do with Effective penetration may have less to do with these enablers than local clinic characteristics, these enablers than local clinic characteristics, needs and approachneeds and approach– Moderate penetration Moderate penetration time for PDSA time for PDSA– Time to adopt/adapt Time to adopt/adapt as opposed to “high burn” as opposed to “high burn”

Page 18: Elizabeth Yano PhD 1, 2 ; JoAnn Kirchner MD 3, 4 ;