Utilizing Algorithms & Systems of Care: Improving Outcomes in Mental Health Treatment

Utilizing Algorithms & Systems of Care:Improving Outcomes

in Mental Health Treatment

Neal Adams MD MPHDirector of Special Projects

California Institute for Mental Health

Objectives

• At the conclusion of the training, participants will better understand….role of medication algorithms in overall

quality improvement experience to date in algorithm

implementationdata on apparent algorithm impactsthe role of psychoeducation in algorithms

and disease managementstakeholder concerns

NEJM, June 2003

• Quality of Health Care Delivered to Adults in The United States“the deficits in adherence to recommended

processes for basic care pose serious threats to the health of the American public”

overall patients received recommended care only 55% of the timerange from 11% to 79%

Six Imperative Challenges in Redesigning Health Care

• Redesign care processes• Effective use of information technologies• Knowledge and skills management• Development of effective teams• Coordination of care across patient

conditions, services, & settings over time• Use of performance & outcome measures

for CQI & accountability

Institute of Medicine, Crossing the Quality Chasm, 2001

The Necessity of Process Improvement

"The definition of insanity is…

…continuing to do the same thing over and over again and expecting a different result.”

Albert Einstein

Informed,ActivatedPatient

ProductiveInteractions

Prepared,ProactivePractice Team

Improved Outcomes

DeliverySystemDesign

DecisionSupport

ClinicalInformation

Systems

Self-Management

Support

Health System

Resources and Policies

Community

Health Care Organization

Chronic Care Model

Chronic Illness Management Program ElementsGuidelines

Evidence-Based Planned Care

Adapted from Katon, W. et al., Gen Hosp Psychiatry, 19:169-178, 1997.

CalMAP is an Illness Management Program

• Evidence based algorithms• Uniform brief clinical rating scales• Optimal data set for decision support• Reduction in practice variability• Intensive patient/family education

increase participation in treatment and decision making

• Clinical coordinator to enhance implementation and care

Rush AJ, Crismon ML, et al J Clin Psych 2003.

Keys to Success

• Effective implementation knowledge, skills abilities and competenciesmodel/practice fidelity

• Requires redesign of system processes!!!workflowproject management

• Quality management is critical to successful implementation

• Change management attitudes and behavior

Goals of Treatment Algorithms

• Decrease variation in patient care• Provide framework for clinical decision-

making• Deliver consistent treatment across

clinicians and environments• Improve documentation of care• Improve patient outcomes

Rush AJ, Crismon ML, et al. J Clin Psych 1998.

Extreme Variability

Upper Control Limit

Lower Control Limit

Quality Management

Upper Control Limit

Lower Control Limit

Goals of Treatment Algorithms (cont’d)

• Provide basis for evaluating care• Provide basis for evaluating costs• Define costs related to specific

treatments or outcomes• Provide metric for evaluating new

treatments• Improve cost-effectiveness of care

Gilbert D, et al. J Clin Psych 1998; Rush AJ, Crismon ML, et al. J Clin Psych 1998.

Potential Benefits of Algorithms

• Patient condition = symptom severity + psychosocial functioning-- = Patient condition at initiation of treatment.

+ = Improvement during course of treatment.

Patient Condition

Time in Treatment

Algorithm

No Algorithm

++

––

Rush AJ, Crismon ML, et al. J Clin Psych 1998.

Algorithm Philosophy

• Goal of treatment should be remission• Most efficacious/safest treatments first

(i.e., evidence based)• Simplest interventions first• Subsequent interventions tend toward

increased complexity and increased risk• Multiple options when appropriate• Patient preference

Crismon ML, et al. J Clin Psych 1999.

Medication Algorithms

• Evidence based, expert consensus derivedStrategies (What treatments?)Tactics (How to treat?)

• Adult populationMajor depressive disorderSchizophreniaBipolar disorder

• Childhood disorders ADHDDepression

Development Process

• Review of the evidence on a specific topic• Consensus panel process

academic content expertspracticing cliniciansconsumers/family members

• Present research evidence• Reaction panels• Discuss evidence & develop algorithms• Review and revise Crismon ML, et al. J Clin Psych 1999;

Suppes T, et al. J Clin Psych 2002;

Miller AL, et al. J Clin Psych 2004

Evidence Based Decision-Making

• Levels of evidenceLevel A

randomized, controlled clinical trialsLevel B

epidemiologic studies, cohort studies, retrospective analyses, etc.

Level Ccase reports, expert opinion

Crismon ML, et al. J Clin Psych 1999.

Formulary Considerations

• Algorithms should drive formularyQuestion is not: ‘Is drug on formulary?’

‘When should it be used?’

• Acquisition cost vs health care costs?acquisition cost should only considered after

efficacy, safety, and tolerability are addressedusing preferred meds within an algorithm

stage helps address both issues

• Use of preferred meds when there is no clinical reason to use a different med

Monotherapy with agent withpositive efficacy/side effect profile

(chosen among list of Stage 1 meds)

Monotherapy with agent withpositive efficacy/side effect profile

(chosen among list of Stage 1 meds)

Monotherapy with alternate meds from above. May have added agents with less

favorable efficacy/side effect profile or new agent with limited clinical experience

Monotherapy with alternate meds from above. May have added agents with less

favorable efficacy/side effect profile or new agent with limited clinical experience

Patient with appropriate diagnoses,baseline evaluations, judged

suitable for algorithm

Stage 1

Stage 2

Exemplar Algorithm Strategies

Different combination therapy than above (Medications with different mechanisms)

Different combination therapy than above (Medications with different mechanisms)

Other interventions as scientific data and clinical experience dictate

Other interventions as scientific data and clinical experience dictate

Exemplar Algorithm Strategies (cont’d)

(1) Different two-medication combination than above OR

(2) Triple medication combination

(1) Different two-medication combination than above OR

(2) Triple medication combination

(1) Monotherapy with different alternates(s) from above (May have more agents added to list)

OR(2) Combination therapy with two agents with

different mechanisms of action and favorable side effect profile when combined

(1) Monotherapy with different alternates(s) from above (May have more agents added to list)

OR(2) Combination therapy with two agents with

different mechanisms of action and favorable side effect profile when combined

Stage 3

Stage 4

Stage 5

Stage 6

Tactical Issues

• How is the treatment stage optimally implemented?how often should the patient be seenhow should symptom improvement and

side effects be monitored?• What are the critical decision points

to make treatment decisions?• How long should treatment continue

before declaring the treatment a failure?

• How long should a successful treatment be continued?how should a successful treatment be

discontinued?

Characteristics of Algo Psychoeducation Program

• Phased simple to more complex

• Targeted to individual needs• Multiple learning modalities

written, aural, visual, experiential• Repetition of key information • Individual and group formats• Consumer/family participation as educators• All materials available in Spanish

TMAP Research

• GoalEvaluate the clinical and economic

outcomes of implementing an algorithm driven disease management program for the medical portion of care for individuals with bipolar disorder, major depressive disorder, or schizophrenia, treated in the public mental health sector, as compared with treatment as usual.

Rush AJ, Crismon ML, et al. J Clin Psych 2003.

TMAP Comparison Groups

ALGO+ED

Schizophrenia

Bipolar disorder

Major depressive disorder

TAUinALGO clinic

TAUnonALGO

clinic

ALGO+ED

TAUinALGO clinic

TAUnonALGO

clinic

ALGO+ED

TAUinALGO clinic

TAUnonALGO

clinic

ED=education TAU=treatment-as-usual

Selected TMAP

Results

SCZ: Sum of Cognition Z Scores:

All Subjects

00

1

2

Baseline 1st Quarter 3rd Quarter

Sum

of z

Sco

res

TAUnonALGO (n=122)ALGO+ED (n=137)

SCZ Adjusted Mean Symptoms (BPRS18): All Subjects

41.8

25

30

35

40

45

50

55

Baseline 1 2 3 4

TAUnonALO (n=144)ALO+ED (n=165)

Quarter

BPR

S1

8

SCZ Adjusted Mean Symptoms (BPRS18)(Moderately Ill)

26.3

25

30

35

40

45

50

55

Baseline 1 2 3 4

Quarter

BPR

S 18

TAUnonALGO (n=12)

ALGO+ED (n=39)

Miller AL, et al. Schiz Bull (in press)

SCZ Adjusted Mean Negative Symptoms (SANS) (Low Baseline Score)

Miller AL, et al. Schiz Bull (in press)

TMAP Costs Compared with

Treatment as Usual

CalMAP Cost Calculations

• Unit costs based upon VA regional charges• Includes organizational overhead and not

just provider time• Includes costs for all patient encounters• Utilization based upon all administrative

files, medical records review, and structured clinical interviews

Overall TMAP Costs

• ALGO was associated with higher medication costs (primarily due to

increased potential for patient to possess an Rx)

greater frequency of physician visits, but not necessarily higher physician costs:

BP - lower physician costs SCZ - no difference in physician costsMDD – higher physician costs

Value = Quality Cost

• Healthcare economicsvalue is usually examined in terms of cost

effectiveness• Cost effectiveness

can be increased by improving outcomes, by decreasing costs, or a combination of the two

• Need to consider the difference in the outcomes and costs achieved with two different sets of interventions

SchizophreniaCost-Effectiveness

• For BPRS as the clinical outcome, cost effectiveness is greater with ALGO intervention than TAU.

• Cost effectiveness is even greater with cognition as the outcome

From TMAP to CalMAP

• San Diego• Phase I

HumboldtKern

• Phase III• State Hospitals

Adaptations

• Optimal Data Set decision support model

• Training• Implementation strategies• Fidelity measures

MedMAP study

CompetencyKnowledge, skills and abilities

Project Management

work and business flow

Change Management

behavior and attitude

Consumer Concerns

• Proscriptive treatmentLack of individualizationLack of choice

• ECT• Cultural/ethnic adaptation

cultural competence of psychoeducationEthnopsychopharmacotherapy

• Polypharmacy• Doctor to doctor variation in practice

Provider Concerns

• Cookbook medicineToo proscriptiveLack of choiceLoss of professional autonomy

• BurdenIncreased tasksIncreased documentation

• Cost savings only

Medi-Cal and DMH concerns

• Poor quality pharmacotherapy• Rising costs• Lack of practice standards• Maintenance of an open formulary• Improved continuity of care

Conclusions

• Algorithms provide a valuable tool in the management of chronic disease states

• Implementation strategies and tactics are crucial to successful implementation

• Best done in the context of a disease management program

• System process redesign is likely necessary to successfully achieve implementation