DECREASING LOST TO FOLLOW-UP : AN INFORMATICS ASSISTED APPROACH (AND HOW TO BUILD A REPORTING APP)

Daniel OchiengJonathan Dick

AMRS HAS LOTS OF DATA…

Majority of AMRS data in two tables: encounter and obs4.8 million encounters, 180 million observations

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AMPATH Encounter and Patient Data Since 2002

Encounters Patients

BUT HOW DO YOU ACCESS YOUR DATA? How do you get data from AMRS right now?Is there an intermediary who gets you your data?If obtaining on your own, what is the process? Import into SAS?Which dataset do you use?What are your challenges?

A NEW WAY TO GET YOUR DATA….

Introducing AMRS Reporting v1.0 A web based application to assist with the reporting of data as well as the creation of tools to improve the management of interventions.

CREATING YOUR OWN AMRS REPORTING APP1. Design the sql to make a derived table

of the data you need using SQL.

2. Design the sql queries to get the data you need from your derived table and upload to AMRS Reporting

3. Design the templates you need to display your data.

4. Work with your team to integrate the application into the management of your project

CREATING YOUR OWN APP – STEP 1 Design the sql to make a derived table of

the data you need using SQL. Allows for faster querying compared to directly

working on the AMRS tables Will still take a bit of time to create the table –

ideally though table creation should be < 1 hour *May be possible to use another group’s data –

will have repository available Size of tables vary but generally 1 – 2 GB

CREATING YOUR OWN APP – STEP 2Design the sql queries to get the data you need from your derived table and upload to AMRS ReportingShould be able to be executed in <= 15 secondsProvides the meat to be used for reporting/intervention

CREATING YOUR OWN APP – STEP 3Design the templates you need to display your data.Currently done using Django template systemRequires programmingDefault system exists to automate display of report data

CREATING YOUR OWN APP – STEP 4Work with your team to integrate the application into the management of your projectPerhaps the trickiest part!

CASE STUDY: LOST TO FOLLOW-UPLTFU definition: Patient has not had contact with any AMPATH service provider in > 90 days from last RTC dateCurrent LTFU across AMPATH: 30%Previous study to evaluate LTFU:

RESULTSOutcomes from chart reviews Adults

N=2179ChildrenN=361

TotalN=2540

Deceased 42 (1.9%)

8 (2.2%) 50 (2.0%)

HIV-negative 0 (0%) 16 (4.4%) 16 (0.6%)

Has a recent visit at original AMPATH clinic

39 (1.8%)

6 (1.7%) 45 (1.8%)

Documentation of transfer out of AMPATH

146 (6.7%)

22 (6.1%) 168 (6.6%)

File missing/insufficient contact info 83 (3.8%)

8 (2.2% 91 (3.6%)

Total not tracked 352 (16%)

65 (18%) 417 (16%)

Outcomes of tracked patients AdultsN=1540

ChildrenN=260

TotalN=1800

Still in care at AMPATH clinic 37 (2%) 10 (4%) 47 (3%)

In care somewhere else 286 (19%)

33 (12%) 319 (18%)

Deceased 363 (24%) 12 (5%) 375 (21%)

Moved away 403 (26%) 55 (21%) 458 (25%)

Disengaged from care 405 (26%) 119 (46%) 524 (29%)

Other 46 (3%) 31 (12%) 77 (4%)

CURRENT METHODS FOR FINDING LTFU Currently there is no regular identification and follow-up of LTFU patients

Only patients who qualify as “no shows’ as per the program definition are followed up.

CURRENT CHALLENGES FOR FINDING LTFU PATIENTSAppointment lists provided to clinics are incompleteNo efficient way to identify patients who have not been to clinic recently or are about to become LTFUThe program currently has no enrollment protocol in placeLack of access to community resources even where they exist

REDUCING LTFU : WHAT INFORMATION DO WE NEED? Reducing existing LTFUObtain list of existing LTFU patients from AMRS

Reducing about to be LTFUPatients scheduled to come to clinic within 30 days Manual DiariesPatients scheduled to come to clinic after 30 days AMRS data

Provide a method to measure progress over timeCompare clinicsMeasure work habits of outreach workers

Incorporate geographical data : catchment from non-catchment

TIMELINE FOR DEVELOPING THE LTFU APP… Creation of derived table ~ 1 – 2 weeks to come up with query 4.8 million rows where every row represents one encounter

Creation of queries of the derived table ~ 2 weeks Key queries include:

Ampath level LTFU data; By clinic level LTFU data; Ranking query to assess the performance of clinics overtime; about to be LTFU patients

Creation of templates to display data ~ 1 week

Total Development time: ~1 month Integration on the ground: about to be started

LTFU APP HOME PAGE

USING THE LTFU APP AT THE CLINICS PILOTFocus on the 14 clinics which account for 90% of all LTFUWill use a sample of these clinics as pilot sites

Pilot to take place over 1 year – expectation/hope is to reduce LTFU by 50%

USING THE LTFU APP AT THE CLINIC: CURRENT IDEASFocus on preventing LTFU using while slowly doing chart reviews of current LTFU patientsRestructuring of current outreach worker work planFocus on preventing LTFU : 70% of patients with recent clinic visits (in past 3-6 months) able to be contacted“Extra time” to be used to do chart reviews. Will assess over initial month to help understand resource limitations.

Once Chart Review Complete move to tracking in community

CURRENT IDEAS CONT

Development of AMRS forms to document outreach LTFU accountingDevelopment of AMRS Reporting app to track patients tracked by outreach teamExpand taxonomy to describe patients not coming to clinicWe need a way of categorizing and documenting patients’ multitude of legitimate reasons for not coming to clinic, e.g voluntary disengagement, as this represents a substantial percent of LTFU

Better death documentation

FUTURE DIRECTIONS FOR AMRS REPORTING Installation of AMRS Reports onto the AMPATH system (currently only runs on my computer) I am looking for clinicians/researchers who want to develop new apps I am looking for geeks who want to learn how to do code the sql and template design Find me:jonathan.j.dick@gmail.com0724 679 898