8/3/2014. Objectives. Purpose of the Toolkit. Disclosure. Parts of the Toolkit

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1 Objectives Leverage Existing Resources with the Chlamydia and Gonorrhea Prevalence Monitoring Toolkit National Reproductive Health Conference Monday, August 4 Charlie Shumate, MPH, CHES Wendy Nakatsukasa-Ono, MPH Upon completion of the workshop, participants will be able to: Describe the importance of using local data under STD AAPPS Define and differentiate between the key indicators for prevalence monitoring Use the interactive Excel worksheets to evaluate their own organizations/practices Develop an action plan for implementing PM practices introduced in the toolkit Disclosure Cardea was funded to produce The Chlamydia and Gonorrhea Prevalence Monitoring Toolkit by a cooperative agreement by the Office of Population Affairs, within the Office of the Assistant Secretary for Health in collaboration with the Division of STD Prevention within the Centers for Disease Control and Prevention (Federal Grant # 5 FPTPA ). The planners and presenters of this CE activity have disclosed no conflict of interest including no relevant financial relationships with any commercial companies pertaining to this activity. Purpose of the Toolkit The purpose of this toolkit is to support state and local STD and FP program clinic administrators and managers in monitoring and evaluating CT/GC screening efforts. We introduce key indicators for assessing screening efforts, explain how each indicator is useful and how to calculate it, and provide examples of each indicator. Parts of the Toolkit Introduction Context & Interpretation Tools and References Key Indicators Ask the Epidemiologist Materials for today s workshop can be accessed at 1

2 Key Terms! All patients CT Tests Positivity Tests, not patients (allows for multiple tests per person) Screened patients CT+ Key Terms Continued! All patients CT Tests Screened patients Positivity Tests*, not patients (allows for multiple tests per person) # positive tests # screened tests CT+ *excludes invalid/inconclusive test results from numerator and denominator All patients Screened patients Screening Coverage = # screened patients All patients HOW HAVE YOU USED PREVALENCE MONITORING? CT+ 2

3 Benefits of Prevalence Monitoring Health Equity Support Quality Improvement Promote Health Equity Ensure Cost Effectiveness Benefits of Prevalence Monitoring Cost Effectiveness: Why 3% positivity? Evidence Honey, et al. Cost effectiveness of screening for Chlamydia trachomatis: a review of published studies. Sex Transm Infect Dec;78(6): Review. Gift TL, et al. The program cost and cost-effectiveness of screening men for chlamydia to prevent pelvic inflammatory disease in women. Sex Transm Dis 2008; 35(11suppl):S66- S75. Roberts TE, et al. Screening for Chlamydia trachomatis: a systematic review of the economic evaluations and modeling. Sex Transm Infect 2006; 82(3): Continuous Quality Improvement Prevalence Monitoring Collect Trend Data Analysis Service Gaps Screening Criteria The importance of periodic review of screening coverage Assess provider adherence to clinical screening protocols Identify trends Evaluate the success of quality improvement initiatives to increase screening Training 3

4 Indicator Screening Coverage The percent of unduplicated sexually active patients screened for CT/GC within the past year Definition Data Source Screening Coverage Practice Management System/clinic EHR Prevalence Monitoring The importance of periodic review of positivity Identify trends Reveal shifts in infection patterns/prevalence Assess disease burdens between groups/populations Serve as a proxy for CT prevalence in clinical settings Patient ID Visit date Provider ID, tested for CT/GC, sexually active Variables Needed Stratification Tips Demographic/ Behavioral Calculating Screening Coverage Indicator Positivity The percent of valid CT/GC tests with a positive result Lab test results or clinic EHR Definition Data Source Positivity Variables Needed Stratification Tips Total number of valid CT/GC tests Number of positive CT/GC tests Demographic/ Behavioral Calculating Positivity OPPORTUNITIES & CHALLENGES SCREENING COVERAGE 4

5 Variables for Stratification Demographic Behavioral OPPORTUNITIES & CHALLENGES POSITIVITY Age Sex SES Multiple Sex Partners New Sex Partner Condom Use Race/ Ethnicity Partner Concurrency Visit Type Sex With Men, Women, Both Example: Stratifying Positivity USING THE INDICATORS Stratifying Positivity Data Example: Stratifying Screening Coverage Screening Criteria & Protocols Know Your Data Clearly Defined Less is More Happy Strata 5

6 Questions? Context Matters: Challenges to Data Interpretation Further, screening coverage does not consider which patients were screened 50% coverage 33% CT+ 50% coverage 66% CT+ 50% coverage 0% CT+ Tell Us Which of the following could affect positivity in a clinic? INTERPRETING YOUR DATA A. Changes to screening policies/protocols B. Changes in client mix (e.g.,closure of nearby clinic) C. Provider/staff turnover D. Scaling up retesting or other targeted screening efforts E. All of the above Context Matters: Challenges to Data Interpretation Positivity considers only patients who were tested Low screening coverage could affect accuracy of measured positivity 100% coverage 33% CT+ Section contains: Common questions Brief answers Recommended resources for further reading Webinar archives, articles, etc. Tools interactive tools for visualizing your data 50% coverage 66% CT+ 6

7 OPPORTUNITIES & CHALLENGES INCREASING POSITIVITY Chlamydia and/or Gonorrhea-infected women and men should be retested approximately 3 months after treatment. If retesting at 3 months is not possible, clinicians should retest whenever persons next present for medical care in the 12 months following initial treatment. Slide source: Evidence-Based Interventions for Increasing Chlamydia and Gonorrhea Retesting Rates Howard, H. and Nakatsukasa-Ona, W. July 2012 Q: Our clinic s CT positivity for female patients is under 3%. How can we increase it? A: Assess your screening practices Stratify by age & consider retesting Repeat CT/GC Infections are Common Overall median reinfected CT = 13.9%; range of 0 32% GC = 11.7%; range of % Peak rates of reinfection at 8-10 months Slide source: Evidence-Based Interventions for Increasing Chlamydia and Gonorrhea Retesting Rates Howard, H. and Nakatsukasa-Ona, W. July 2012 CT Prevalence Among Sexually Active Persons, By Age Group Studies Show Low Retesting Rates Retesting Rates Overall: 43% Howard H, et al. (Female CT+ California Family PACT-Quest Clients, ). Family Planning Waiver: 24% Managed Care: 51% Chow J. CA (NSTDP 2010) Family Planning and STD Clinics: 28% Opdyke K. Region II IPP (NSTDP 2010) Family Planning Clinic: 28% STD Clinic: 34% Goldenkranz S. Region X IPP (NSTPD 2010) Source: CDC Grand Rounds: Chlamydia Prevention: Challenges and Strategies for Reducing Disease Burden and Sequelae, April 2011 Unpublished data from National Health and Nutrition Examination Survey cycles

8 Interactive Test Allocation Worksheet In-Touch Study Results Models allocation of screening resources according to age/risk algorithm: Screen all adolescents Use remaining tests to screen age Diagnostic testing only for women >26 Computes estimated increase in screening yield MS Excel-based % CT Positive Baseline CT Positivity Rate CT Reinfection Rate >35 Age Group (female patients only) 10 Slide source: Evidence-Based Interventions for Increasing Chlamydia and Gonorrhea Retesting Rates Howard, H. and Nakatsukasa-Ona, W. July 2012 Retesting Cascade Positive CT result Informed to return for rescreening Returns for rescreening Retested OPPORTUNITIES & CHALLENGES MAXIMIZING RESOURCES Low client return rates + many missed opportunities = few women retested Analyzing Retesting Rates Challenging to compute QI initiatives can target patients and/or providers Important to monitor both return rates & missed opportunities Increasing retesting will increase overall positivity Q: Our clinic s CT positivity is above 3%, but testing resources are limited and we can t screen all women under age 25. How can we maximize resources? A: Always room for improvement Allocating resources to those with the highest positivity ensures maximum impact Stratify! Assess your screening practices examine age & retesting 8

9 Q: Our providers are so busy. We just don t have enough time to screen all of our patients. How can we increase screening coverage? A: Look for ways to improve clinic efficiency: self-collected specimens & patient flow analysis Q: Are there different ways to obtain the data I need to calculate positivity and screening coverage? A: Practice management (screening coverage) Electronic Health Record (positivity) Lab reports (positivity) Stratifying to Identify Service Gaps Comprehensive visit Total # tested for CT Total # of patients Screening coverage Yes % No (e.g., pregnancy test only, birth control pick-up, other visit type) % Positivity Alternative Options Requires test result data Numerator and denominator are tests, not patients Can be challenging to extract from some EHRs Request a report from each of the laboratories you use for CT/GC testing Request a line-listed Excel or.csv file Clinical Resources Tool A: Sample Line-Listed CT/GC Data Region X IPP patient self-obtained vaginal swabs Instruction placards patients Vaginal swabs toolkit for providers Basic Tenets of Clinic Efficiency: Best Practices and Lessons Learned (webinar) Patient Flow Analysis 9

10 Continuous Quality Improvement Develop a plan to routinely summarize and review data Use summary data to guide programmatic decisionmaking Positivity Alternative Options If only one lab is used, you may be able to request an aggregate summary report Specify how data should be stratified e.g. by sex and age groups (15-19, 20-24, 25-30, 31+) Annotated Positivity & Screening Coverage Graphs MS Excel-based Enter monthly data and notes Annotated graphs are automatically generated Female Positivity by Race/Ethnicity, 2010 Race/Ethnicity % of female tests % CT+ % GC+ Non-Hispanic white Non-Hispanic black Asian Hawaiian/Pacific Islander American Indian Hispanic ethnicity Other/Multi Missing Tests vs. Patients Some EHRs can export user data but not test record data User data can be used to calculate clinic prevalence (% of patients with positive test result) If most patients are tested only once per year, prevalence and positivity will be similar 10

11 Q: Do you really expect individual clinics to perform their own prevalence monitoring? ACTION PLANNING Who Should be Doing Prevalence Monitoring? Clinic? Agency? Local health department? State? Questions? What are your existing data reporting procedures? Who has staffing capacity to analyze data? Where are line-listed data stored/accessible? Who Should be Doing Prevalence Monitoring? Involve the clinics Stratify results by clinic Share & discuss results with clinics Set achievable goals and assess progress Resources by Cardea Visit our STDRHTTAC webpage: Join our Online Learning Community: Contact us: Charles Shumate, MPH, CHES 11