I want to learn and practice…

I want to learn and practice…
Where should I go after lunch? Choosing a Level for Overview & Prep for MER 2.0 Analysis Level I want to learn and practice… I am familiar with… 1 Cycads 5-6 The structure and organization of MER data in DATIM How to modify DATIM pivot favorites and create new ones to review disaggregate completeness and quarterly trends for TX_NEW Panorama Intro How to log into DATIM What MER indicators are Wait - I’m new to PEPFAR! Level 1 is right for you. We also encourage you to attend the Systems Jump-start session today from 5:45-6:45pm. 2 Cycad 7 Using DATIM group sets to analyze MER 2.0 data – latest enhancements! Focus on HTS analytics MER 2.0 in Panorama: latest visual tools to support POART prep MER 2.0 indicators and data elements Creating a DATIM pivot table 3 Cycad 4 The context and purpose of MER Fact View analytic datasets Accessing Fact View analytic datasets and performing analysis using Excel to review treatment and testing progress Data manipulation to answer analytic questions MER 2.0 indicators and data elements produced from DATIM How to make a pivot table in Excel

Overview and Preparation for Analysis of MER 2.0 Data: Level 1
2017 PEPFAR Data and Systems Applied Learning Summit Overview and Preparation for Analysis of MER 2.0 Data: Level 1 Notes Introduce the title of the course and give a brief, 1-2 sentence summary of what you will be covering. September 12, 2017

Welcome & Introductions
Notes According to the Department of Psychology at UCLA, you have 7 seconds to have an audience determine whether or not they trust you. The first moment you stand up in front of the audience will set the tone for the next 1.5 hours or however long your session it. Make it count. To set a positive tone for the session, welcome participants to the course and thank them for attending. Introduce yourself: name, agency, program, title (if appropriate) and say why you are glad to be at the Summit and what you’re looking forward to. If there is time, encourage one of the following ice breakers: Learners to introduce themselves to the person sitting to their immediate left or right. Allow a few minutes for them to do this and then begin the session. Have each learner find a partner (person to their left/right). Tell participants to take a coin out of their pocket. Tell participants to look at the date on the coin and share a personal memory or historical event associated with the year on the coin (if they were alive, of course). Have learners share with the person next to them what they hope to get out of the training. Pose a question of your choice: i.e. favorite sport, favorite data system, best vacation, etc.

Agenda Topic Estimated Time Session overview and Introductions 5
1. Introduction to MER 2.0 and DATIM 45 2a. Practice with DATIM Pivots 25 Energizer Break 2b. Practice with DATIM Pivots, continued 3. DATIM Group Sets 15 4. Panorama Intro 10 5. Fact View Data Sets and ICPI Tools 6. Summary and Conclusion By 3:25/3:30 Scope: we will only briefly cover Panorama today; there will be take-home exercises and in Day 2 training, will cover more.

Session Learning Objectives
In this session participants will: Describe the relationship amongst MER, DATIM, and Panorama Describe and use the core features of DATIM for data extraction, analysis and interpretation Practice using DATIM pivots to review program performance for patients newly enrolled on ART in Fiscal Year 2017 (FY17) State the best and most accurate method for pulling HTS from DATIM pivots Notes Providing the learning objectives is important to participants are aware of the purpose and goals of the sessions and therefore are able to understand the relevance to their daily work and how they will use the skills learned to apply on the job. Please see the Training Development Resources section of this deck for further information and guidance on writing learning objectives.

Introduction to MER 2.0 and DATIM
Speaker Notes Provide detailed notes on the topic you will cover and how it fits in to the overall structure of the course. When writing speaker notes, please consider the following: What would someone need to know about this content if they are teaching it for the first time? What concepts are most important for the audience to understand on each slide? Where might the learners have some confusion about the content, and can you anticipate what that would be and how to remedy it? Are there any case studies, personal examples, or stories you’ve heard of certain experiences with the topic? If there is an exercise associated with this topic, how can you set it up so the learners know what to expect (i.e. “You will have the opportunity to practice [skill y] in an activity we will do later in the session.”) Where can learners go for further information about the topic? This will be expanded upon at the end of the deck, but feel free to mention resources throughout the session as reminders. Remember: repetition is not a bad thing!

DATIM Workflow Important to understand how data is entered in DATIM; how data is entered has an affect on how we access the data DATIM through apps such as the DATIM Pivot Table App.

Structure & Organization of Data in DATIM
Levels Periods Categories of data elements Facility Quarterly Numerators/ Denominators vs Disaggregates Community Semi-Annual Results vs Targets Notes Consider the questions below as you craft and present your content: How much do learners already know about what you are presenting? What are the key terms they need to know in order to understand a concept? Are you trying to teach them too much in the amount of time you have? Where can you provide real-world examples/case studies/story from your experience to highlight a learning concept? What kind of questions might learners ask about this content? Are you going to provide time for Q&A during or after your course, or both? How much text do you need on this slide to communicate the main idea without overwhelming the learners? How can you use visuals to support the learning concept? Can you use visual metaphors? OU level Fiscal Year DSD vs TA

Each MER 2.0 indicator within DATIM
Data at a different level Facility, Community or OU level Data associated with specific time periods Quarterly, Semi-annual, Annual 3. Categories of data elements Numerators/Denominators vs Disaggregates Results vs Targets DSD vs TA

Site – Facility or Community
How Data are Organized in DATIM OU District or Province Site – Facility or Community Interagency or Agency IP for their sites only IP Bottom-up pyramid reporting structure Data associated with source location (site) District, Province, OU indicator totals all aggregate from site-level data—including community and facility targets/results Your DATIM account type will define/limit what MER Data Set locations you have access to. This affects your access to view specific indicators and specific SNU levels. Your DATIM account settings will define/limit what MER Data Set locations you can access

Data Flow Data Flow: Facility, Community, OU and Military level
Operating Unit (OU) Total Data Flow Province (Military) Health Facility Community Site

DATIM Organizational Structure for Data Entry
Global “Tree” Structure (Global, Region, OU, etc.) Mozambique Cabo Delgado Province Ancuabe District Ancuabe CS I Healthcare facility

Time Periods Depends on frequency of indicator reporting
Refer to MER Reporting Timeline

Results vs. Targets Targets set for the full Fiscal year -> use “Financial October” period to retrieve in DATIM COP16 / FY17 Targets October 2016-September 2017 Results reported QUARTERLY -> use fiscal year quarter periods to retrieve in DATIM FY17Q1 Oct. 1- Dec. 31 FY17Q2 Jan. 1 – Mar 31 FY17Q3 Apr 1 – June 30 FY17Q4 July 1 – Sept. 30 9/16/2018

Results vs. Targets, continued
Results and targets are entered as separate data sets in DATIM by the implementing partner. This is what the drop-down menu looks like for the IP.

Direct Service Delivery/Technical Assistance
Both refer to site-level activities (facility site, community-site) Technical Assistance – minimum annual TA touch at a site to improve the quality of services Direct Service Delivery – minimum annual TA touch at the site PLUS funding key commodities or staff. Definitions for relevant activities differ slightly – see each indicator in MER guidance. $

MER Definition – New on Treatment
DATIM Dimensions: Translating MER Indicators to Data Elements MER Definition – New on Treatment DATIM Data elements Victoria starts

Data Element Structure in DATIM
Before we look at the results of our favorite, let’s quickly review data elements Talking Points DATA sets at OU, country, regional level have above-site indicators. Community. Facility – hospitals, clinics. Targets and results sit in different data sets. Data associated specifically with time periods. Targets associated with fiscal year (Oct-Sept).

TX_NEW Data Entry (MER 2.0)
TX_NEW (N, DSD): New on ART Pregnancy / Breastfeeding Status TX_NEW (N, DSD, Preg/Feeding): New on ART Tuberculosis TX_NEW (N, DSD, TB Diagnosis): New on ART Talking Points Red text: Data entered in each box is translated into a data element that you will see in DATIM or in a data export from DATIM For many indicators, the numerator and disaggregates are entered separately. For some indicators, the disaggregates are entered first and will sum automatically to create the numerator Each of these disaggs is entered separately and although they SHOULD align both with the numerator and each other, they may not. The analyses you can perform are based on which disaggs are entered. Certain disaggs are REQUIRED by HQ. The default requirement is finer age/sex disagg reporting Key Populations Type TX_NEW (N, DSD, KeyPop): New on ART

…but wait, there’s more…
Fine Age/Sex Detail: TX_NEW (N, DSD, AgeAboveTen/Sex): New on ART 20-24, Male TX_NEW (N, DSD, Age/Sex): New on ART Coarse Age/Sex TX_NEW (N, DSD, Aggregated Age/Sex) v2: New on ART

Contextualizing MER data
Narratives at OU and IM level Clarify challenges with program or data quality New overall PEPFAR Reporting Guidance will specify narrative requirements Implementation Attributes (IMPATT) and Host Government Results PLHIV, prevalence, SNU prioritization category Entered by USG

DATIM Workflow: Review and Validation
Important to understand how data is entered in DATIM; how data is entered has an affect on how we access the data DATIM through apps such as the DATIM Pivot Table App.

Building and Using DATIM Pivots
1 DATIM Apps: Pivots and Visualizer 2 Using Favorites 3 Refresher: Data Element Structure 4 Data Dimensions: Data 5 Data Dimensions: Period 6 Data Dimensions: Organization Hierarchy Notes Consider the questions below as you craft and present your content: How much do learners already know about what you are presenting? What are the key terms they need to know in order to understand a concept? Are you trying to teach them too much in the amount of time you have? Where can you provide real-world examples/case studies/story from your experience to highlight a learning concept? What kind of questions might learners ask about this content? Are you going to provide time for Q&A during or after your course, or both? How much text do you need on this slide to communicate the main idea without overwhelming the learners? How can you use visuals to support the learning concept? Can you use visual metaphors?

DATIM Apps: Pivot and Visualizer
Both Pivot Table and Visualizer Apps Can examine performance vs targets and completeness at more granular levels Can build own data views, BUT requires additional knowledge about Data availability How you should combine data How to interpret and understand completeness Pivot Table Helpful for more detailed analysis using granular disaggregates Best for spot-checking SNU and site-level data Basic (but limited) data export capabilities Data Visualizer (Charts) Quick, visual breakdowns Best for aggregate data review

DATIM Pivot Table: 2 Ways to Pull Data
Two ways to pull up data in pivot table app: Use favorites - EASIER! Open favorites Manipulate the table From Scratch - selecting data elements/dimensions

DATIM Pivot table: Opening a Favorite

Refresher: Data Element Structure in DATIM
Before we look at the results of our favorite, let’s quickly review data elements Talking Points DATA sets at OU, country, regional level have above-site indicators. Community. Facility – hospitals, clinics. Targets and results sit in different data sets. Data associated specifically with time periods. Targets associated with fiscal year (Oct-Sept).

TX_NEW Favorite And here is the result of our TX_NEW completeness review

DATIM Pivot Table Data Dimensions
MER indicators in DATIM are a series of data elements/dimensions and their disaggregations (DHIS2 category combinations) Pivot table data dimensions can each be filtered/”drilled down” to show different data views On the left here you see a select number of key data elements/dimensions, which can be selected and filtered to attain data that you want to see. We will go over these in closer detail in the next few slides.

Key Data Dimension: Data (What?)
“Data Elements” rather than “Indicators” “[All data elements]” Totals vs. Details Let’s go through the different data dimensions Indicators vs. data elements: Choose “data elements,” rather than “indicator” (indicator = default listed). Most often you will use data elements, the components that make up an indicator (numerator, denominator, disaggregates). There are few calculated indicators available at this time, though HTC yield is available. Data element groups: First select the data element group “all data elements.” This allows you to search the complete list of data elements from all data sets and periods entered in DATIM Type in your data element of interest in the search bar Start by typing the indicator code (e.g. HTC_TST, TX_NEW) The diagram at right denotes the components of a data element for a simple default numerator. Disaggregate data elements will have additional information contained with the parentheses (). For a complete list of data elements, go to the DATIM Support page. Type into the search bar: “DATIM Data Exchange Instructions and Code Lists” and open the page. Scroll down to “Code Lists” section. Data elements are organized by ‘data sets’ – grouped by fiscal year results and targets; and within those groupings, as facility and community indicators. Download as “.csv” to be able to open in Excel and filter/sort. You will see each individual data element as well as the category option combo name (detailed disaggregate information). Totals vs. details: “Totals” displays numerators and the SUMS of various disaggregate categories (e.g. sum of wide age bands, sum of finer age bands). “Details” displays values of distinct disaggregate slices (e.g. males between ages 1-4 who tested positive for HIV).

Key Data Dimension: Periods (When?)
MER Reporting Period Periods Check MER Guidance “Appendix 4: Frequency of Reporting Table” to see how frequently an indicator is reported, and how it is calculated over time. Results data is associated with the QUARTER in which it was entered, so select “quarterly” from the drop-down menu and then select the quarter you need. Targets are associated with a fiscal year (e.g. October 2016-September 2017) – so for targets, select “Financial October” as the period. If creating a table from scratch, uncheck “last financial year” Reminder: you must de-select “last financial year”. This default selection will always need to be changed

Key Data Dimension: Organization Units
Where? To navigate, first uncheck “User org unit” Organization Units: DATIM uses the term “OU” in various ways. Organization Unit (OU) – a general term referring to a unit within any level of the hierarchy (from Global down to facility level). Depending on the administrative subdivisions or health district subdivisions in a country, units may sit at different levels in one country compared to another. Mozambique levels: Province/Region = Mozambique provinces In Country level 3 = District (also the COP planning prioritization level, the priority subnational unit or PSNU) In Country level 3 = community site level (e.g. for community level indicators like OVC_SERV) In Country level 4 = facility Country/ Operating Unit (OU) – to refer to PEPFAR operating unit, usually country level (e.g. PEPFAR/Mozambique). The hierarchy of units is different across countries. OU Hierarchy Tips: Uncheck “user org unit.” Use gear symbol, click “select levels,” and in drop-down menu at right select the level(s) you wish to view. Drill down to select your organization unit of choice (country; subnational units down to community and facility level by clicking “+” next to the folder symbols. Alternatively, you can select your unit of interest directly from the list by clicking on it. You can select multiple options by using either ‘shift’ (sequential lists) or ‘control’ keys. And as we already mentioned, there are two ways to select OU levels: Uncheck “user org unit” Use navigation wheel, click “select levels,” and in drop-down menu at right select the level(s) you wish to view. Then select a country > drill down to select your organization unit of choice by clicking “+”  DATIM uses the term “OU” in two ways Organization Unit (OU) – to refer to a unit within any level of the hierarchy (from Global down to facility level) Country/ Operating Unit (OU) – to refer to PEPFAR operating unit, usually country level

Talking Points

Practice with DATIM Pivots to review TX_NEW
Speaker Notes Provide detailed notes on the topic you will cover and how it fits in to the overall structure of the course. When writing speaker notes, please consider the following: What would someone need to know about this content if they are teaching it for the first time? What concepts are most important for the audience to understand on each slide? Where might the learners have some confusion about the content, and can you anticipate what that would be and how to remedy it? Are there any case studies, personal examples, or stories you’ve heard of certain experiences with the topic? If there is an exercise associated with this topic, how can you set it up so the learners know what to expect (i.e. “You will have the opportunity to practice [skill y] in an activity we will do later in the course.”) Where can learners go for further information about the topic? This will be expanded upon at the end of the deck, but feel free to mention resources throughout the session as reminders. Remember: repetition is not a bad thing!

Remember Your DATIM User settings/’Privileges’ define the datasets you can see Close all applications, browsers ( etc) Clear your Google Chrome Browser Cache Clear your DATIM cache Wifi and DATIM support right outside

For this exercise, we will
Outline: DATIM Pivot Table App Exercises For this exercise, we will Modify a DATIM pivot table favorite to answer: How complete were TX_NEW disaggregates at the OU and SNU level in FY17Q2? Create a new pivot table to assess quarterly trends in TX_NEW from FY16Q2 to FY17Q2. This includes practice changing layout and format of a table, saving a favorite, exporting, and sharing a favorite. Notes Consider the questions below as you craft and present your content: How much do learners already know about what you are presenting? What are the key terms they need to know in order to understand a concept? Are you trying to teach them too much in the amount of time you have? Where can you provide real-world examples/case studies/story from your experience to highlight a learning concept? What kind of questions might learners ask about this content? Are you going to provide time for Q&A during or after your course, or both? How much text do you need on this slide to communicate the main idea without overwhelming the learners? How can you use visuals to support the learning concept? Can you use visual metaphors?

Step A1 1) Navigate to the Pivot Table App either searching for it or using the App Icon

Step A2 2) Use the Favorites drop-down menu and select the open option

Step A3 3) In the Search feature, type “PEPFAR FY17 Q2 TX_NEW” and select the “PEPFAR FY17 Q2 TX_NEW Completeness Review Pivot” Click on the option presented PEPFAR FY17 Q2 TX_NEW Completeness Review Pivot_vdr

Step A4 4) Review the Data Presented: First look at the setup
Time Period: Jan to March 2017 (Q2) Organization Unit: Mozambique Data: Includes all of the “Total” Data Dimensions for TX_NEW for (both TA and DSD data, separately) Numerator AgeLessThanTen AgeAboveTen/Sex Aggregated Age/Sex KeyPop Preg/Feeding)

Step A5 5) Next look at the data, comparing the disaggregates to the Total Numerator, checking logic and completeness, and answer the questions. Completeness: The Total Numerator greater than or equal to the sum of the age&sex disaggregate totals. 68, 223 TX_NEW (N, DSD) ≥ TX_NEW (N, DSD, AgeLessThanTen) + TX_NEW (N, DSD, AgeAboveTen/Sex

Answer question: OU-Level Completeness
1. Question: How complete were the TX_NEW Age/Sex disaggregates for both TA and DSD compared to the numerator? Answer: 2. Question: How can I use this information about completeness? What does it tell me, and what can I do next? Note, that if the logic checks out, it may or may not be necessary to look at a more granular level If incomplete: depends on where we are in the data review cycle. Drill down further to identify the issue. May need to contact the partner. Check narratives. If data is complete for some SNUs and very incomplete for others, may need to narrow the age/sex analysis you do just to those SNUs that had complete data. If complete: safe to analysis the age/sex disaggregates.

Step A6 6) Modify the data to make it easier to review in Excel. Select Layout  Switch Organisation Units field with the Data field  Select Update 1 3 2

Step A7 In this format, it is now easier to review the data at a more granular organization level 7) Click on Organisation Units on the Left Sidebar  Select the Region of interest directly or select User Sub-units

8) Manipulating Pivot Table Options
Step A8 8) Manipulating Pivot Table Options 1. Select Options 2. Select Hide empty rows 3. Select Show hierarchy 4. Select Update In this example we are only changing the “hide empty rows” and “show hierarchy” options, but as you can see there are several options that you can modify

Step A9 9) Download to Excel. To perform completeness checks at the SNU level, it might be easier to pull the data into Excel. a. Click the “Download” dropdown option from the top tool bar. Select the first “Microsoft Excel (.xls) option from the menu. b. If it asks “Do you want to leave this site?” select Leave. This will allow the spreadsheet to download. c. Save using relevant naming convention in appropriate location. TIME CHECK.

Answer question: SNU-Level Completeness
Question: Pick 2-3 SNUs to review completeness. Are there any SNUs where age and sex disaggregates are incomplete? Answer: Optional Step A9. If you want practice with Excel, time permitting, please see example for how to export and review with formulas on next slide.

Step A10 Optional 10) In the spreadsheet, review the downloaded data. How would you add calculations to complete the completeness check for each SNU? Which SNUS appear to be incomplete? Example of a completeness check calculation comparing Age/Sex Disaggregate to the Total Numerator We will not cover this in the demo. If you went through the earlier part of the exercise quickly, try this!

5 minute ENERGIZER break
Speaker Notes Provide detailed notes on the topic you will cover and how it fits in to the overall structure of the course. When writing speaker notes, please consider the following: What would someone need to know about this content if they are teaching it for the first time? What concepts are most important for the audience to understand on each slide? Where might the learners have some confusion about the content, and can you anticipate what that would be and how to remedy it? Are there any case studies, personal examples, or stories you’ve heard of certain experiences with the topic? If there is an exercise associated with this topic, how can you set it up so the learners know what to expect (i.e. “You will have the opportunity to practice [skill y] in an activity we will do later in the course.”) Where can learners go for further information about the topic? This will be expanded upon at the end of the deck, but feel free to mention resources throughout the session as reminders. Remember: repetition is not a bad thing!

Step B1 – create a new pivot table
Let’s try looking at TX_NEW trends from FY16 Q2 to FY17Q2 using the Data Dimensions on the Left-Hand Tool Bar. In your DATIM Pivot Table App, select the Favorites Dropdown Menu and click on “New.” This will open a blank pivot table Note: If you still want to work in the same pivot table, you can duplicate the window in the chrome browser opening two pivot tables at the same time

Steps B2,3,4: Selecting Indicators
2) Select the Data tab to expand its options. 3) Select “Data Elements” from the first drop-down menu 4) Select [All Data Elements] from the second drop-down menu. (Leave Totals for now)

Steps B5: Selecting Indicators, continued
5) After the indicators have loaded, click the Magnify glass and Search for: TX_NEW (N, DSD): New on ART TX_NEW (N, TA): New on ART Double click each one to add it to the box on the right side Note: This same method can be used to look at the disaggregates. “Totals” can be switched to “Details” to look at the distribution of age bands within disaggregates

Steps B6,7,8: Select a timeframe.
6) Select the “Periods” tab after the “Data” tab to expand the options. Unclick “Last Financial Year” under Financial Years (If it is currently selected) 7) From the dropdown menu select quarterly Use these options to scroll for the quarters and years of interest 8) Select January to March 2016 April-June 2016 July-September 2016 October- December 2016 January to March 2017

Step B9 Select the location
9) Select “Organization Units” Tab  Levels  OU/Country Select your OU. Update.

Step B10 10) Your table should look similar to this.

Answer Question Now we can see the numerator results for TX_NEW for four quarters of data: FY16Q2 through FY17Q2. Question B10a: What is the trend over time for DSD? For TA? Answer: Question B10b: For both DSD and TA, what is the percent increase or decrease between FY16Q2 and FY17Q2?

Step B11. Modify Layout 11) Select the “Layout” Tab on the top bar. –Move “Data” to “Report filter” box (this will lump DSD and TA together) -Move Periods to the “Column” box -Move Organisation units to the “Row” box Update

Knowledge Check Now that you have Trend Table for TX_NEW at the National level, how would you look at the same trend at a lower SNU level?

Step B12. Adjust to in-country level 3 and display hierarchy
12a) In OU hierarchy, select a subnational unit below province/region review. Update 12b) Under options, mark “Show hierarchy”  Update FY16Q2 - FY17Q2 TX_NEW Trend In country level 3 vdr

Step B13. Review Table You should now have a table with SNU3 data, with DSD and TA summed together. Let’s save this one!

B14. Saving Pivot Table Favorites
1. To save an updated favorite select “Favorites” > “Save As” 2. Rename the favorite with a memorable name  Save. Recommend starting with the initials of your name. This will help you search for it later if needed. Example: vdr FY16Q2 - FY17Q2 TX_NEW Trend In country level 3 Once you have saved the favorite under a new name, you will see it populate when you try to search for it in the favorites again

B15. Sharing Pivot Table Favorites
Best way to share is to share the link Copy and paste the URL. You can share this with your colleague who has a DATIM account. Recipient must be logged into DATIM to view.

Logic check: TX_NEW with TX_CURR
We’ve been looking at single indicators in DATIM, but we can also pull multiple indicators. Logic Check: TX_CURR ≥ TX_NEW See take-home exercise to complete a logic check for TX_CURR and TX_NEW.

Caveats to Using the Pivot Table Data Dimensions
We recommend most users not create pivot tables from scratch (using data elements); instead use pre-existing DATIM favorites No inherent relationship or grouping between data elements and disaggregations Aggregate total may not equal sum of disaggregate “slices” Not all disaggregates will be entered by IP DATIM cannot “fix” bad or incomplete data entry Limited data validation rules in DATIM System not as restrictive as you might expect Few cross-indicator validations Choose the wrong data elements for analysis, get the wrong answer So now that we’ve covered using Favorites to pull up, manipulate, save, and share pivot table views in DATIM, let’s turn to using data elements within the pivot table app to pull up and view/modify/download data

Improved Analytics: DATIM Group Sets Speaker Notes
Provide detailed notes on the topic you will cover and how it fits in to the overall structure of the course. When writing speaker notes, please consider the following: What would someone need to know about this content if they are teaching it for the first time? What concepts are most important for the audience to understand on each slide? Where might the learners have some confusion about the content, and can you anticipate what that would be and how to remedy it? Are there any case studies, personal examples, or stories you’ve heard of certain experiences with the topic? If there is an exercise associated with this topic, how can you set it up so the learners know what to expect (i.e. “You will have the opportunity to practice [skill y] in an activity we will do later in the course.”) Where can learners go for further information about the topic? This will be expanded upon at the end of the deck, but feel free to mention resources throughout the session as reminders. Remember: repetition is not a bad thing!

Analytic Improvements
Section 3 HTS Group Sets Analytic Improvements Using DATIM Dimensions Facilitate accurate extraction and review of HTS data Best way to look at HTS data (by overall numerator, modality and age/sex) Notes DATIM Cheatsheet for Group Sets Consider the questions below as you craft and present your content: How much do learners already know about what you are presenting? What are the key terms they need to know in order to understand a concept? Are you trying to teach them too much in the amount of time you have? Where can you provide real-world examples/case studies/story from your experience to highlight a learning concept? What kind of questions might learners ask about this content? Are you going to provide time for Q&A during or after your course, or both? How much text do you need on this slide to communicate the main idea without overwhelming the learners? How can you use visuals to support the learning concept? Can you use visual metaphors?

HTS_TST Facility Modalities
Tip: any modality with “Mod” in the name is a community testing modality Modalities PITC Inpatient PITC Pediatric PITC Malnutrition PITC TB PICT PMTCT (ANC Only) VMMC Other PITC VCT Index Testing

Within each modality, enter Age/Sex disaggregates

Separate Key Population Disaggregate
KP is not a modality. You should ‘double enter’ data here (optional)

How do HTS modalities appear in a Pivot Table?
Numerator Modality&age&sex&result KeyPopType & Result Modality&age&sex&result HTS Completeness Favorite Find the HTS_TST Completeness Favorite for FY17 Q2 using the Favorites Toolbar Search for “PEPFAR FY17 Q2 HTC_TST Completeness Review Pivot” This is a ton of work. Can’t we make this easier??

HTS Group Sets Types Refer to the Group Sets Cheat Sheet for Step by Step Guide to choosing a ‘group set’ Refer to Level 2 HTS Exercise to Practice on your own

No data element selected! Selected Technical area, HTS Cascade sex
HIV Facility Index Testing: Using DATIM Group Sets No data element selected! Selected Technical area, HTS Cascade sex Cascade age bands Test Results Example of HTS completeness favorite using with a modified group sets favorites. Ready example from Moz using global account: PEPFAR FY17 Q2 HTC_TST Completeness Review Pivot_PALSDay1MERL1groupsets Open a new pivot table. Important: Do not select any data element. Leave this tab blank Select Time Period - select “January- March 2017” and Don’t forget to deselect the financial year checkboxes if starting from a new pivot table Selection of Period and OU is similar to the method you just learned – but selection of other items is different. 3) Select the OU of Interest (National, Provincial or District) 4) Select Cascade Age Bands. Initially, when exploring the data, it is important to select all Cascade Age Bands. Note: For the Pediatric and Malnutrition Modalities, these age bands will not be used 5) Select Cascade Sex. Use the “Cascade Sex” Data Dimension to select “Male”, “Female” and “Unspecified Gender”. Note: “Unspecified gender” must be selected to see the data for children under the age of 10. Additionally, for VMMC and PMTCT, the genders are assumed. To see those modalities, no gender should be entered 6) Select the testing Modalities. For this exercise, we are only looking at the results of the facility Index testing modality. Select “Modality: Index” *Can select multiple modalities at once, but remember that if the request is too specific of age and sex, it might not include all of the modalities (Malnutrition, Peds, VMMC, ANC etc.) 7) Select DSD and TA from “Support Type” 8) Select “Results” from the Targets/Results tab 9) Select Technical Area. For this exercise select HTS_TST. *Note that even if HTC is not selected, it will still populate with the same data after we select for “Test Results” 10) Select the Test Results, pos and neg 11) Adjust the Layout - Rearrange the layout (you may want to put a lot of items in the “report filter” section) With <15 and >=15 age band

When we add “ Cascade Sex,” VMMC, Pediatric, and PMTCT ANC disappear.
When age is specified, Peds modalities will disappear (PITC Pediatric, PITC Malnutrition)

Using Group Sets: Common Errors
Example Missteps There are more opportunities for missteps with addition of new dimensions Think of using these new analytic dimensions like filters on an Excel-based pivot table: if you do not filter elements out, they will be automatically summed Make sure that you check your data dimension selections carefully before using the data in analyses

Take-Home Practice For more practice with Group Sets, access the presentation and exercises from the Day 1 MER Level 2 session. Exercise 1: PRINT_MERPrepforAnalysis_Level 2_DATIMExercise_FINAL Exercise 2: PRINT_MERPrepforAnalysis_Level 2_DATIMExercise Advanced_FINAL

Panorama: Access and Exercises
Know Your Data, Know Your Program

What is Panorama? What is the Panorama tool? What do you use it for?
Web-based visualizer tool used for PEPFAR analytics What do you use it for? Standard data views/visuals meaningful to many audiences Can easily compare MER and SIMS indicators What does it not do? (yet!) No EA data Does not show historical data prior to FY15 OU SNU DSD/TA Year/Quarter Agency Mechanism Partner Age Sex

Panorama Quarterly Data Flow

The link to PEPFAR Panorama:
Panorama Orientation The link to PEPFAR Panorama: Public Dashboard

Panorama Orientation

OU Level Analysis: Targets and Results
We are going to start by navigating to our OU Level Targets and Results page. We’ll get there by selecting the “OU & SNU Analysis” dropdown menu, and choosing the “OU Level” tab.

OU: Targets and Results

You will learn about many of these in Day 2 MER Analytics!
More analysis using Panorama… What visualizations or tools are standard in Panorama? In Panorama, you can find analysis related to…. Full Clinical Cascade Net New Analysis HTS TB/HIV OVC PMTCT Cascade VMMC You will learn about many of these in Day 2 MER Analytics! The next few slides will orient you to these analyses. During the Day 2 MER Analytics, we’ll dive into many of these tools. However, there are simultaneous breakout sessions and you may not be able to take the time to test your knowledge in each area. Feel free to explore these slides on your own, and we’ll get into more detail tomorrow!

Panorama Support Page The Panorama Support Page has a list of FAQ and tutorials to help you navigate the platform.

Fact View Datasets Notes
You have the opportunity to summarize the main concepts learned throughout the course so learners can feel a sense of accomplishment for the work they’ve done, in addition to triggering what they’ve learned so they can ask any remaining questions about elements of the session that might have been unclear to them.

Fact View Datasets: What are they?
Data text files that contain MER data that are created by the ICPI Can be imported into Excel or statistical software packages (eg. STATA, SAS, SPSS) Follow a standard structure and are updated with the same frequency as Panorama. Created to make analysis easier and creating visualizations easier

Fact View Datasets: More information?
Release notes, user’s guide, data dictionary, training materials On PEPFAR Sharepoint at: -> ICPI -> ICPI Data Store -> MER folder -> ICPI Fact View See Level 3 Slides and Exercises

Summary Notes You have the opportunity to summarize the main concepts learned throughout the course so learners can feel a sense of accomplishment for the work they’ve done, in addition to triggering what they’ve learned so they can ask any remaining questions about elements of the session that might have been unclear to them.

Summary During today’s session we discussed how to:
Describe the relationship amongst MER, DATIM, and Panorama Describe and use the core features of DATIM for data extraction, analysis and interpretation Practice using DATIM pivots to review program performance for patients newly enrolled on ART in Fiscal Year 2017 (FY17). Notes Provide a summary of what learners achieved by reviewing the objectives from the beginning of the course. Please see further examples of how to write learning objectives in the Training Development Resources section of this deck.

Questions? Notes Provide an opportunity for learners to ask any questions they may have about the content before you move on to providing information about further learning resources and key contacts. You may also encourage learners to ask questions throughout the course, but determine how you want to handle this given the amount of time you have to present and the amount of content you need to get through.

Further Resources Train the Trainer Online Resources (for this session) Right Tool, Right Analysis 1 pager Upcoming PALS Sessions Data Cleaning Session at PALS (Tuesday evening) PALS Day 1 Level 2 and Level 3 MER Group Sets Exercises and Group Sets Cheat Sheet Panorama: Access & Exercises – Know Your Data, Know Your Program FactView Datasets DATIM Support Page Training Resources DATIM Demoland training.datim.org PEPFAR MER Guidance and new overall PEPFAR Reporting Guidance PEPFAR Data Calendar Notes Provide resources where learners can go for additional information about the topics covered. For example, websites, tutorials, books, etc. Additionally, one of the goals of the Summit is to weave in elements of Training of Trainers (ToT). This section should focus on tools participants will have furnished to them to help spread the message once they get back to their countries. Provide information about where learners can find the slide deck after the training is over where to find TOT materials to teach this course to colleagues.

Key Contacts Shabeen Ally, CDC/ATL, xlk1@cdc.gov
Victoria Ryan, USAID/OHA, Your Interagency HQ SI Advisor Your Agency SI/M&E POC

Thank You! Thank you all for your time, participation, and attention during the session!

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