PIHOA-SPC-WHO-FNU-RAPID-CDC Joint EpiTech-Data for Decision Making Training Program

Transcription

1 PIHOA-SPC-WHO-FNU-RAPID-CDC Joint EpiTech-Data for Decision Making Training Program Data for Decision Making II: Basic Applied Epidemiology and Data Analysis Meeting Report Palau, May 2014 Location: Palau Community College, Republic of Palau, Western Pacific Dates: May 2014 Additional Sponsors: Training Programs in Epidemiology and Public Health Interventions Network (TEPHINET), Palau Ministry of Health, CDC Center for Chronic Disease Prevention & Health Promotion Course Goals: 1) Reinvigorate of EpiNet teams in the USAPI through building of knowledge and skills of EpiNet team members 2) Strengthen capacity of teams through developing non-communicable disease surveillance plans at the jurisdiction level 3) Obtain academic course credit for students toward formal credentials in applied epidemiology through Fiji National University 4) Build a mid-level Epi-tech track to complement advanced applied epidemiology training to be offered within a Pacific SHIP/FETP fellowship program Facilitators: 1

2 George Kahlil, Centers for Disease Control and Prevention (CDC); Sevil Huseynova World health Organization (WHO); Kate Hardie, Response and Analysis for Pacific Infectious Diseases (RAPID); Beverly Paterson, Response and Analysis for Pacific Infectious Diseases (RAPID); Adam Roth, Secretariat of the Pacific Community (SPC); Damian Hoy, Secretariat of the Pacific Community (SPC); Haley Cash, Palau Ministry of Health; Dawn Fitzgibbons, Palau Ministry of Health; Mark Durand, PIHOA; Thane Hancock, PIHOA; Participants: 30 Participants from the U.S. Associated Pacific Islands including CNMI, Guam, Palau, Yap, Chuuk, Pohnpei, Kosrae, RMI, and American Samoa [See attached Participant List] Background: In 2010 and 2012, the Declaration of Health Emergency for NCDs and the heightened threats of dengue and influenza outbreaks in the Northern Pacific demonstrated a need to improve the epidemiologic capacity of the region, both for outbreak prone diseases (via EpiNet teams) and for other public health surveillance officers, including those responsible for NCDs. The EpiTech-Data for Decision Making series for the Pacific is a collaborative project of PIHOA, the Secretariat for the Pacific Community (SPC), the Centers for Disease Control and Prevention (CDC), the World Health Organization (WHO), the Fiji National University (FNU) and AusAID-funded Response and Analysis for Pacific Infectious Diseases Project (RAPID) of Hunter-New England Health District. A version of Module 1 (of 5) of CDC s Data for Decision Making curriculum was used for this workshop. This module was recently updated by technical staff from SPC and RAPID, and had been pilot tested in previous workshops. This was the fourth time that Module 1 has been delivered in the Pacific in the past 12 months. The Data for Decision Making curriculum is a set of 5 courses (four instructional and one independent project) that originated with a set of US Centers for Disease Control and Prevention workshop modules and was converted to an accredited applied epidemiology curriculum in the early 2000s through the then Fiji School of Medicine, Department of Public Health (by Dr. Naren Singh of the then Fiji School of Medicine, and Dr. Mike O Leary, of WHO). In 2013, a revision of the course package was undertaken in partnership by a group of epidemiologists from Fiji National University School of Medicine, Nursing, and Health Sciences Department of Public Health (FNU), Secretariat for the Pacific Community, PIHOA, WHO, RAPID project of Hunter-New England Health District/Univ. of Newcastle, WHO, and CDC. Students must formally register with FNU for each course. Course faculty will have appointments with FNU (as adjunct faculty for epidemiologists working for regional associations). Student performance will be measured against course learning objectives through end of course examinations and student projects. Full time faculty at FNU will perform final assessment of student based on examinations and 2

3 projects, and award course credit. Students who pass all 5 courses will be awarded a post-graduate certificate in applied epidemiology from FNU. With 4 additional courses students can be awarded a post graduate diploma and with an additional 4 courses, a Master s degree. Courses passed can also count toward Bachelor degrees for those who do not yet have a BA or BS. The 5 courses are as follows: DDM1- Outbreak Surveillance and Response DDM2- Basic Applied Epidemiology and Data Analysis DDM3- Advanced Applied Epidemiology and Data Analysis DDM4- Public Health Surveillance DDM5- Surveillance Project or Research Project Work Shop Details: The workshop was conducted at the Palau Community College Conference Hall. In order to achieve the goals the following objectives and methods were utilized: Objectives: 1. Define epidemiology, uses and outline the general principles 2. Describe basic measurements in epidemiology and calculate basic indices of health status. 3. Describe and explain the various measures of disease frequency- measures of morbidity, mortality, including performing adequate descriptive epidemiology, 4. Describe the concepts of life expectancy, age specific life expectancy, years of potential life lost, disability adjusted life years and person time rates, and age-adjusted rates 5. Outline concepts in public health demography 6. Describe various sources of data and their limitations 7. Describe methods of scientific enquiry in epidemiology i.e. the concept of study designs in epidemiology; key features and applications, particularly those study designs used commonly in field epidemiology 8. Explain the principles of data organization, analysis and presentation 9. Introduction to electronic file management 10. Undertake the following processes in Excel: save file, add filter, sort, basic formulae, cleaning data, dealing with missing data/data entry errors/outliers, constructing tables/graphs, inserting tables/graphs in word and PowerPoint 11. To understand how to communicate the results of data analysis 12. To understand the differences between Excel and Epi-Info 13. To become familiar with Epi-Info and some of the following functions: create database (questionnaire); enter data/ create filters or check codes; import data from excel; analyze data; present data or report using relevant tools; inserting tables/graphs in word and PowerPoint. Methods: 3

4 Multiple teaching methods were utilized to deliver the course content and achieve the identified objectives. These included: 1) Lectures: a. Course Background and Expectations b. General Principles of Epidemiology c. Measures in Epidemiology and Demography Part I d. Measures in Epidemiology and Demography Part II e. Measures in Epidemiology and Demography Part III f. Data sources g. BRFSS and NCD STEPs Survey Comparisons h. Data Dissemination and Use i. Study Design j. Introduction to Epi-Info 2) Group work/exercises a. Excel Refresher I b. Excel Refresher II c. Cleaning, analyzing and reporting on own data set d. Mapping/developing NCD surveillance plan or framework for each jurisdiction 3) Group presentations- evaluation a. Presentation and constructive critique of jurisdictions NCD surveillance plan b. Presentation on own data project 4) Written examination- evaluation a. 90 minute written exam b. 90 minute retest 4

5 Agenda: 5

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7 Workshop Evaluation: Participant evaluation of the workshop was conducted through a form developed and analyzed by Bev Paterson. Her summary findings are: The DDM2 course run in Palau was very well received by participants. I'm so happy that I've learned a lot from this course and will apply it to my work. All areas of the course rated highly as did the different formats used in the course. For each of the key taught areas (excel, data, calculations and own data) there was a participant selfassessed improvement during the course. Key areas identified as particularly useful by participants were excel (pivot tables and filters, data analysis mean, mode and median), data cleaning (identifying and documenting errors, making a working copy) and data analysis (rates, percentages and proportions). Key aspects of the course likely to be used in the workplace included data collection, cleaning, quality, analysis and interpretation. Course Which were the most useful parts of the course to you? n/a Excel Data analysis Own data Epi concepts Surveillance plan 7

8 Which formats used in this course were most useful in helping you learn the concepts? Lectures Individual work Group work Facilitators working through problems Roaming faciliators n/a Excel How would you rate your Excel skills? Excel pre-course Excel post-course n/a Excel pre-course Excel post-course

9 What were the key things you learnt in Excel that you would use in your workplace? Track changes Age groups Sums Equations Mean, median, mode Shortcuts Data dictionary Coding Saving Files Pivots Tables Charts Sort Filters Data cleaning Data How would you rate your data cleaning skills? Data pre-course Data post-course n/a Data pre-course Data post-course

10 What were the key things you learnt about data cleaning that you will use in your workplace? Importance of data cleaning Create codes Make a working copy Use data dictionary Filtering outliers Document errors and changes Data cleaning process Fix/edit errors Diagnose errors Screen data Type of data error Data scope Data dissemination Identify your audience Interpretation of data Format table using sort/ filter Makes analysis easier Finding outliers Identify errors Calculations How would you rate you re your ability to calculate rates? n/a Calculation pre-course Calculation post-course Calculation pre-course Calculation post-course 10

11 What were the key things that you learnt about any calculations that you will use in your workplace? Reference variables Sum/if functions in excel Ranges Numerator/ denominator Use populations Using excel bar to show totals All calculations Attack rate Incidence Prevalence Indicators Ratio Means, mode, median Fractions Dividing Percentages/ proportions Rates Own data How would you rate your understanding of your own data? Own data pre-course Own data post-course n/a Own data pre-course Own data post-course

12 What are the key things that you've learnt about your own data that you will use in your workplace? Telling the story of the data/presenting data Coding Rates Data collection, cleaning and data quality Filtering/sorting Unique identifier Save a working copy Data screening Data analysis and interpretation Understand data from an epi perspective Excel Variables Improve data Know where to start See the whole picture Incidence and prevalence The data Comparisons Continued uncertainty Is there anything that was covered in the course that you re still unsure about? How to use the data for policy change Variance (standard deviation) Calculating rates Which graphs to use Epidemiological concepts Everything Data interpretation Study design Comparing and analysing different data sets Presentations Excel Epinfo

13 Participant Outcomes: All participants were evaluated on three sets of criteria the presentation of the analysis of their own data, the presentation on their NCD surveillance plan, and a written exam. The analysis of the participant grades was performed by Adam Roth. Total Number of Participants: 30 Mean Score: 79% Range: 66%-95% Mode: 74% Grading breakdown and evaluation criteria: 1) Own Data Presentation (20%) Presentation of results/findings of analysis own data set Mean Score: 86% Range: 70%-96% Evaluation criteria: 1) Correctly name what indices their own data describe or could describe: ratio, rate, proportion, mortality rate, cancer incidence/prevalence etc. 2) Presents appropriate descriptive epidemiology: relevant basic analysis of data main variables by age group, sex etc.; were graphs and tables correctly designed and labeled 3) Identifies sources of data and limitations: describe what source of data is used, its construction and purpose and limitations 4) Provides proper description of the study design behind the data: it's benefits and limitations 5) Organization and presentation of data: Was the analysis and presentation clear and understandable while identifying the quality and importance of the data 6) Were the results presented in an informative and concise way 7) Future data plan: Is it realistic and relevant 13

14 2) NCD Surveillance Plan Presentation (20%) Develop written draft NCD surveillance plan to share with jurisdiction leadership Presentation of NCD surveillance plan Mean Score: 74% Range: 70%-94% Evaluation criteria: i. Plan and address essential elements of NCD surveillance 1. Youth risks 2. Adult risks 3. NCD mortality ii. Specific NCD plan: 1. Which surveys to be done 2. How often 3. Who is responsible for what iii. Describe important NCD indicators and data sources iv. Understand difference between survey and routine data v. Present and discuss a NCD surveillance plan, understanding the concepts of: 1. timeliness 2. validity 3. resource constraints vi. Good and clear presentation with clear messages. vii. A clear distribution plan and products. viii. Realistic understanding of external assistance needed ix. The importance of buy in and endorsement 3) Written Exam (60%) 90 minutes Collection of multiple choice, short answer, calculations and matching Mean Score: 72% Range: 42%-96% 11 students took retest (90 minute exam made up of all new questions) i. Mean Score for Retest: 76% ii. Range: 63%-89% 14

15 Conclusions/Next Steps: The workshop appears to have been successful in achieving its four main goals. 1) Reinvigorate of EpiNet teams in the USAPI through building of knowledge and skills of EpiNet team members This was the first time DDM2 was provided. The participants demonstrated continued enthusiasm for EpiNet that was demonstrated in DDM1. There were several participants who had not yet attended DDM1, but were successful in obtaining the knowledge and skills targeted in this training. Each participant worked in a group to clean, evaluate, analyze, display and present public health data. Examples of these presentations included: BMI rates in Yapese youth, prevalence of NCD 15

16 risk factors in CNMI, measles outbreak in Kosrae, and health screening results from Pohnpei. These all helped build knowledge and skills in applied epidemiology and data analysis. 2) Strengthen capacity of teams through developing non-communicable disease surveillance plans at the jurisdiction level All teams were successful in creating an NCD surveillance plan tailored for their jurisdiction. This included a written draft proposal to be shared with health leadership upon returning from the workshop. Additionally each team created and delivered a PowerPoint presentation detailing their NCD plan. These presentations can also be utilized by the teams when returning to their work settings. 3) Obtain academic course credit for students toward formal credentials in applied epidemiology through Fiji National University All participants were given the opportunity to register with FNU to receive course credit. Paperwork was completed and submitted to FNU with the assistance of PIHOA. Guidance was provided by FNU during the development of the training and evaluation to help ensure the course meets all accreditation requirements. FNU is currently reviewing work submitted to determine if credit can be given to passing participants. 4) Build a mid-level Epi-tech track to complement advanced applied epidemiology training to be offered within a Pacific SHIP/FETP fellowship program The workshop was the first time DDM2 was provided as part as the Epi-Tech track of training. It reaffirms that the DDM series delivers the appropriate knowledge and skills for training EpiNet team members. A cohort of USAPI EpiNet team members is developing from which individuals for further training can be identified. The training was also successful in bringing together the key partners in Pacific public health and epidemiology. The close collaboration and commitment between these partners to develop, deliver, and evaluate the training is extraordinary. During the training it benefits the participants to have all partners involved, and after the training, strengthens communication and cooperation in regional public health work. It is a model that should be utilized more frequently. Next Steps: 1) Partners -PIHOA, WHO, CDC, SPC, RAPID, FNU- together to: a. continue to collaborate and pilot test revisions of other DDM modules, b. deliver the other 3 DDM modules to EpiNet team members, c. provide further input for Pacific FETP (SHIP) development and be ready to provide mentoring to SHIP fellows once the program is up and running, 16

17 2) Follow-up with FNU on the accreditation of the courses and registration of participants, 3) Support other deliveries of DDM2 in the Pacific region as requested by PICTs, 4) Continue to expand epidemiology competencies in NCD surveillance and response; consider development of a companion manual to the Pacific Outbreak Manual for NCDs, 5) Check back with jurisdiction EpiNet teams in late August to determine progress on developing, revising or maintaining NCD surveillance systems. Submitted: W. Thane Hancock July 26,