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Staff Turnover and Change in Co-Occurring CapabilityRon Claus, Steven Winton, Mary E. Homan, and Edward Riedel

Missouri Institute of Mental Health

Addiction Health Services Research Conference October 2830, 2009

Background

Annual turnover rates for public sector behavioral healthprograms, an often overlooked concern, are estimated to range

from 25-50% (Gallon et al, 2003; Glisson et al, 2006; McLellanet al, 2003).

Little research has examined the consequences of turnover on anorganization, while a majority of turnover research has focused onantecedents of voluntary turnover such as climate, culture, orleadership.

High voluntary turnover is typically assumed to be dysfunctional,with organizational consequences that may include:

Increased costs due to hiring and training new employees

Reduced productivity, inconsistent services, poor staff morale amongstayers

Loss of high p erformers, loss of institutional knowledge

Turnover, however, can also be classified as functional. Lesser-studied organizational consequences may include:

Displacement of poor performers and improved service delivery

Infusion of new ideas, the stimulation of policy and p ractice changes ,

and increased ability to adapt to environmental concerns

Better overall person-organization fit

Despite a growing body of research on the translation of researchto practice, the effect of turnover on the implementation ofevidence-based practices has received little attention.

Woltmann et al (2008) found that IDDT fidelity scores at follow-upwere inversely related to turnover, with most (71%) treatment teams

reporting that turnover negatively affected implementation.

Turnover can be either functional or dysfunctional and its influenceon EBP implementation may be nonlinear, e.g., as turnover reacheshigh levels, it may have a decreasing effect on performance.

Recent findings suggest that turnovers impact on behavioral health

programs may be moderated by factors such as program size,clinical supervision, and training infrastructure.

Study Context: The Missouri Foundation for

Healths Co-Occurring Disorders Priority Area

Participating Programs

18 mental health programs and 9 substance abuse programsproviding services to adults.

Measure: Staff Changes Inventory

Interview conducted with Change Agent or Program Director

Asked whether the program had turnover in t hree staff categories:Change Agent, Key Personnel (as defined by the program), and

Front-Line Staff. If yes, What was the overall effect of the change on the co-occurring

program? (positive, neutral, or negative)

Was the change related to differences in values or beliefs about

treatment for co-occurring disorders? (not at all or a little; some; a

lot)

Results: Program Turnover

Programs who hired a new Change Agent during the year had lessimprovement in COD capability than others (0.54 vs. 0.89, d=0.5). Controlling for initial COD capability, this inverserelationship accounted for 7.8% of COD capability change (F(1,24) = 3.41, p < .10).

Neither annualized turnover rate nor program size directlyaffected COD implementation. However, turnover interacted withprogram size to predict change in COD capability (see Figure).Smaller programs with low turnover made noticeably moreprogress than did larger programs with low turnover (d= 1.40).

Turnover and Program Size Predict

Co-Occurring Capability Change

Discussion

Acknowledgements

Average turnover at participating substance abuse and mentalhealth programs was slightly lower than observed in previousnational reports. In less than two years, the programs madesubstantial progress in building capacity to deliver treatment forco-occurring disorders.

Treatment staff reported that the consequences of turnover werelargely positive or neutral, commonly noting that incomingreplacements had better skills or were more involved in COD

treatment.

Turnover was not linearly related to change in COD capability. Inthis sample, turnover may have had mixed positive and negativeeffects.

Small programs improved more when turnover was low, whilelarge programs made bigger strides when turnover was high. Thisdemonstrates differences in the way change occurs at large andsmall programs.

Small programs, which have fewer and more concentratedresources, may be more affected when staff leave. Largeprograms offer more complex systems but often have more

resources; turnover may lead to more rapid improvement,perhaps through identifying, hiring and training more ableemployees.

Programs that brought on new Change Agents improved, butnoticeably less than those with consistent implementationmanagers. This finding suggests the importance of leadershipfunctions in creating program change.

Although the current study relies upon a small agency sample, itexamines real-life change processes in community-basedprograms. The study findings highlight the importance of tailoringhiring practices to established COD and managementcompetencies.

Future work will examine the role of leadership, staff attitudestoward EBPs, and organizational readiness to change in turnoverand program change.

An initiative to support the implementation of evidence-based

practices for co-occurring substance use and mental healthdisorders

Publicly-funded treatment providers received support for systemchange:

14 programs awarded 3-year grants in Dec 2006

13 programs awarded 3-year grants in June 2007

The Co-Occurring Capability of each program was assessed atYear 1 and Year 2.

Staff changes and their relationship to co-occurring capabilitychange during that period were investigated.

Study Aims

1. Describe staff turnover at 27 behavioral health programsimplementing integrated treatment for co-occurring disorders

2. Examine the relationship between turnover and change in co-occurring capability

3. Explore whether organizational characteristics such as programsize affect the relationship between turnover and change in co-occurring capability

Characteristic Mean SD Range

Agency Age 27.7 years 8.7 441

Agency Annual Operating Expenses $10.6M $9.7M $1.934.6M

Clients below Federal Poverty Level 77.4% 24.5% 19.6 -100%

Most located in urban areas:

Urban Core: 3 SA providers, 11 MH providers, 51.9%

Large Town: 4 SA providers, 6 MH providers, 37.0%

Small Town: 1 SA provider, 1 MH provider, 7.4%

Isolated Small Census Tract: 1 SA provider, 3.7%Measuring Rurality: Rural-Urban Commuting Area Codes, USDA, 2007

Measure: Co-Occurring Capability

Dual Diagnosis Capability in Addiction Treatment (DDCAT) Index -McGovern, Matzkin, & Giard, 2007

Dual Diagnosis Capability in Mental Health Treatment (DDCMHT)IndexGotham et al., 2009

Semi-structured questions to elicit ratings on 35 items across 7subscales:

Continuity of Care

Staffing

Training

Based on the American Society of Addiction Medicines Patient Placement Criteria (ASAM -PPC-2R)

Program Structure

Program Milieu

Clinical Process: Assessment

Clinical Process: Treatment

Programs received domain and global scores along a continuum:

Addiction Only or Mental Health Only Services (AOS/MHOS, 1)

Programs that by choice or lack of resources cannot accommodate clientswith co-occurring disorders, no matter how stable the illness and howeverwell-functioning the client

Dual Diagnosis Capable (DDC, 3)

Programs that have a primary focus on one disorder but are capable oftreating clients who have relatively stable diagnostic or sub-diagnostic co-

occurring problems

Dual Diagnosis Enhanced (DDE, 5)

Programs that are designed to treat clients who have more disabling orunstable co-occurring disorders

Results: Co-Occurring Capability

Effect on Implementation (%)

Category ( # programs) Positive Neutral Negative

Change Agent (n=5) 20 60 20Key Personnel (n=12) 60 30 10

Front-line Staff (n=26) 34.6 61.5 3.8

Staff reported that changes had largely positive or neutral effectson COD implementation:

In each staff category, turnover was viewed as unrelated to valuedifferences regarding COD treatment.

Program Size: Clinical & Administrative staff

Mean = 38.7, Median = 24, SD = 34.5

Varied widely, from 5-137 employees

Turnover was calculated by dividing the number of clinical andadministrative staff who left the program between DDCATadministrations by the number of staff at Year 1.

Time between visits varied between programs (11-15 months), soan Annualized Turnover Rate was calculated.

Annualized Turnover Rate

Mean = 22.5%, Median = 15.0%, SD = 20.6%

Ranged widely, 094.5%

1

2

3

4

5

Year1

Year2

Mean DDCAT Change = 0.82 (SD = .67)

Support for this presentation was provided by the MissouriFoundation for Health, a philanthropic organization whose vision isto improve the health of the people in the community it services.

2 programs improved substantially (change > X+2SD)2 programs had lower scores at Year 2

Results: Turnover & COD Capability Change

Variable B SE R2

Step 1 .372**

COD Capability (Yr 1) -.690 .192 -.572**

Step 2 .074

Program Size -.011 .005 -.586*

Turnover -.016 .011 -.504

Step 3 .047

Program Size X Turnover .00 04 .0 003 .59 7

p < .01**, p < .05*

Results: Program Turnover

Hierarchical Regression Predicting COD Capability

Change from Year 1 to Year 2