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EVIDENCE BASED ASSESSMENT OF ADHD IN PRIMARY CARE SETTINGS

EVIDENCE BASED ASSESSMENT OF ADHD IN PRIMARY CARE SETTINGS. AMERICAN ACADEMY OF PEDIATRICS 2007 NATIONAL CONFERENCE AND EXHIBITION. Thomas K Pedigo Ed.D., NCSP. DISCLOSURE: Dr. Pedigo is co-owner of Targeted Testing, Inc., and co-developer of the PADDS Program

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EVIDENCE BASED ASSESSMENT OF ADHD IN PRIMARY CARE SETTINGS

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  1. EVIDENCE BASED ASSESSMENT OF ADHD IN PRIMARY CARE SETTINGS AMERICAN ACADEMY OF PEDIATRICS 2007 NATIONAL CONFERENCE AND EXHIBITION Thomas K Pedigo Ed.D., NCSP DISCLOSURE: Dr. Pedigo is co-owner of Targeted Testing, Inc., and co-developer of the PADDS Program which is referenced in this presentation.

  2. RELEVANCE TO PRIMARY CARE • ADHD is the most commonly diagnosed childhood psychiatric disorder affecting school age children with estimates ranging from 3 to 12 percent • (American Psychiatric Association, 1994). • Concern has been expressed for the these large numbers coupled with reportedly wide variations in clinical practice and research approaches; all point to the need to develop pragmatic assessment tools and approaches for use in the major systems of service entry. • (American Academy of Pediatrics, 2000) • Researchers and authorities have pointed out the weak Negative Predictive Power (good performance actually rules out attention disorders) of CPT’s and numerous neuropsychological measures traditionally used to evaluate ADHD in light of the base rate (conservative estimate of 4%), • (Barkley, R.A., & Grodzinksi, G. M., 1994)., • (Ellwood, R.W., 1993)., (Matier-Sharma, K., et.al., 1995).

  3. Other Comorbid conditions often occur with ADHD. These conditions may include but are not limited to Mood Disorders, Anxiety Disorders, Disruptive Behavior Disorders and Learning Disorders. Bipolar Disorder. Pliszka, S. R., Carlson, C. L., & Swanson, J. M., (1999). ADHD with Comorbid Disorders: Clinical assessment and Management. New York, N.Y. The Guilford Press. PG ADHD/ODD-CD 15% to 61% 90 ODD-CD/ADHD 35% to 87% 90 ADHD/Depression 0% to 38% 127 Depression/ADHD 0% to 57% 127 ADHD/Anxiety 23% to 30% 151 Anxiety/ADHD 9% to 35% 151 ADHD/LD 7% to 60% 192 (Across- Reading, Spelling, & Math) ADHD/OCD 6% to 33% 214

  4. RELEVANCE TO PRIMARY CARE  WHY THE PEDIATRIC ADD SCREENER WAS DEVELOPED The Development and Validation of Diagnostic Tools   During the 1998 NIH Consensus statements indicate a need to develop more objective assessment tools, rating scales and/or diagnostic interviews that map onto basic underlying processes as well as a need to supplement behavioral assessment tools with improved cognitive and/or neuropsychological measures. Consequently, there is a great need for the development of practical, reliable and valid procedures to be used in primary care settings to identify and manage ADHD symptoms, as well as to distinguish appropriate referral needs. (NIH conference, 1998)

  5. Recent developments within the field of ADHD have increasingly pointed to the need to evaluate the various executive operations and working memory of children suspected of Attention Disorders. (Biderman, J. et al 2004, Brown, T.E., 2002, 2000,1999; Barkley, R.A. 1997,1998; Denckla M, 1996.) • Difficulties in theseExecutive Processes • (planning, attending, organizing input, storing and retrieving information, modulating emotions and sustaining effort) • exemplify the complaints of teachers and parents.

  6. Basic Demands of the Classroom: • Attending to instruction • Assimilating information • Accommodating information • Organizing, sequencing, manipulating information • Monitoring emotional activity • Formulating a plan of action • Implementing the plan • Other Factors: • Working under time pressure • Avoiding distraction • Being adequately prepared • PADDS’ TARGET TESTS OF EXECUTIVE FUNCTIONS WERE DESIGNED TO PRODUCE WORK DEMANDS SIMILAR TO THOSE OUTLINED ABOVE.

  7. Clinical sampleconsists of 629 children age 6-12 (266 females and 367 males) evenly balanced between ADHD and Non-ADHD/Typical peers. Data was collected from 10 sites in 7 states with Institutional Review Board (IRB) approval for the overall project handled at Armstrong Atlantic State University in Savannah, Georgia. Specific sites included specialty ADHD assessment centers in Illinois, Georgia, Idaho, New Jersey, Tennessee, California, and Florida.

  8. PEDIATRIC ADD SCREENING SYSTEM Target Tests of Executive Functioning (TTEF) ASSESSES EXECUTIVE FUNCTIONS  COMPARES TO ADHD & TYPICAL PEERS  CAN EFFECTIVELY RULE IN & OUT ADHD  EFFECTIVELY CROSS VALIDATES BEHAVIOR RATINGS

  9. Computer Administered/Scored Diagnostic Interview (CADI) EFFECTIVELY ASSESSES FOR COMORBIDITY  ESTABLISHES A PRELIMINARY TREATMENT PLAN  CAN PROVIDE DOCUMENTATION TO SUPPORT REFERRALS AND OTHER TESTING REQUESTS

  10. CLINICAL & PRACTICAL UTILITY of (PADDS) This Evidenced based format compares these results in incremental fashion beginning with a base rate of 4 percent. By using a conservative base rate and multiple inputs the clinician is able to conduct an evidence-based analysis that along with clinical judgment can rule in or out a diagnosis of ADHD in the office setting. This standardized evidence-based approach efficiently provides a preliminary treatment plan that can support a diagnosis when combined with other procedures as deemed necessary by clinical input and judgment. This screening can also support decisions for further evaluation and referrals.

  11. Nomographic Evidenced Based Report Analysis Positive and/or Negative Predictive Power is developed through the combination of these lines of evidence by calculating a likelihood ratio for each measure. By applying the likelihood ratios incrementally using a Nomogram, we have effectively “Summed” the gathered evidence into a single, valid factor called the Post-test Probability. Using a nomogram for “charting” likelihood ratios is the best method to properly combine the results of different tests In the following examples we combined information from: Parent ratings of DSM-IV ADHD diagnostic criteria. Teacher ratings of DSM-IV ADHD diagnostic criteria. Results from the three Target Tests of Executive Functions.

  12. Case Example #1 Prior to any input from the PADDS system the ADHD base rate of 4 % is equal to the Post-test probability of 4 %. Input of a Parent rating meeting DSM-IV criteria producing a likelihood ratio of 9 moves the pre-test probability from 4% to a post-test probability of 25 %. We re-set the Likelihood Ratio to 1 and Pre-test Probability to 25% Input of a teacher rating meeting DSM-IV criteria producing a likelihood ratio of 9 moves the new pre-test probability of 25% to a post-test probability of 74%.

  13. The combined values of the Parent and Teacher Ratings alone calculates a probability of 74% There is clearly not sufficient evidence for a diagnosis at this point using rating scales alone. This is where it becomes important to collect further information along multiple lines of evidence. Any measures with known values for specificity and sensitivity may be used For this example we are using a set of newly developed cognitive tests called Target Tests of Executive Functions, from our PADDS program

  14. Input of the Target Recognition subtest performance produces a likelihood ratio of 6 moves the new pre-test probability of 74% to a post-test probability of 93%. Input of Target Sequencing subtest performance producing a likelihood ratio of 8 moves the new pre-test probability of 93% to a post-test probability of 99%. Input of Target Tracking Subtest performance producing a likelihood ratio of 1 maintains the pre-test probability of 99% to a posttest probability of 99%.

  15. This example illustrates how the Target Test scores can be used to support and validate the results of Behavioral Rating Scales. In this case the Target Tests of Executive Functions scores significantly modify the predictive index in a direction supporting a clinical diagnosis.

  16. Case Example #2 Prior to any input from the PADDS system the ADHD base rate of 4 % is equal to the Post-test probability of 4 %. Input of a Parent rating meeting DSM-IV criteria producing a likelihood ratio of 9 moves the pre-test probability from 4% to a post-test probability of 25 %. We re-set the Likelihood Ratio to 1 and Pre-test Probability to 25% Input of a teacher rating meeting DSM-IV criteria producing a likelihood ratio of 9 moves the new pre-test probability of 25% to a post-test probability of 74%.

  17. The combined values of the Parent and Teacher Ratings again calculates a probability of 74% This time however, the test scores will adjust the overall index in an entirely different direction, also clearly illustrating the weaknesses in using rating scales alone as the basis for a diagnosis.

  18. Input of the Target Recognition subtest performance produces a likelihood ratio of 0.7 moves the new pre-test probability of 74% to a post-test probability of 66%. Input of Target Sequencing subtest performance producing a likelihood ratio of ~1 moves the new pre-test probability of 66% to a post-test probability of 65%. Input of Target Tracking Subtest performance producing a likelihood ratio of 0.5 adjusting the pre-test probability of 65% to a post-test probability of 49%.

  19. In this case the Target Tests of Executive Functions scores significantly modify the predictive index away from supporting a clinical diagnosis. Thus, reviewing any other clinical information obtained becomes critical. The risks of over identification are evident when relying on behavioral rating scales alone. This examples subject had a hearing disability, not ADHD

  20. The Benefits of using Evidence - Based Assessments that Test Executive Functions Are clearly superior To rating scales alone EVIDENCE EVIDENCE EVIDENCE EVIDENCE The way to Reduce ADHD Over-Identification is with More Accurate Assessments, Based on more lines of evidence

  21. EVIDENCE BASED ASSESSMENT OF ADHD IN PRIMARY CARE SETTINGS AMERICAN ACADEMY OF PEDIATRICS 2007 NATIONAL CONFERENCE AND EXHIBITION Thomas K Pedigo Ed.D., NCSP For more information on PADDS and Evidence Based ADHD Assessment Please Visit http://www.targettest.com

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