matthew lamb mrl2013@columbia.edu icap-m&e barriers to retention and factors associated with ltf...

Matthew Lamb mrl2013@columbia.eduICAP-M&E

Barriers to Retention and

Factors Associated with LTF in HIV Programs

The literature and ICAP

Barriers to retention

Structural• Financial

• Transportation• Competing priorities

Biomedical• Illness• Health

• Clinical issues

Psychosocial• Forgetfulness• Drug abuse• Stigma/disclosure• Available support

systems• Knowledge/beliefs

Questions asked by Geng et al.

1. What happened to patients who were LTF?• vital status• current care and ART status

2. What reasons do patients LTF give for no longer attending clinic?

Study design and sampling frame

3,628 ART patients

77% (2,799) remained in care

23% (829) LTF

15% (128) tracked

13% (17) not found 25% (32) died 62% (79) alive

61% (48) patient interviewed

39% (31) informant interviewed

Questionnaire: reasons for LTF; current care and

ART status

Automatically generated from electronic medical records when patient has not been

seen for 6 monthsOutreach Worker:

Visits location of patient, asks around~ 1 afternoon/patient

Cumulative LTF Incidence:12 mo: 16%24 mo: 30%36 mo: 39%

Reasons for LTF among 48 patients directly interviewed

Patient characteristics associated with Death among those LTF

32 died (25%) 79 alive

111 tracked and vital status ascertained

Clinical measure at last visit

Hazard Ratio 95% CI

Increasing Age Per 10 yr increase 2.0 (1.1-3.8)

Low blood pressure

< 75 mm HG vs. > 75 mm HG

3.0 (1.2-7.7)

CNS syndrome Yes vs. no 2.9 (1.1-7.4)

Pre-ART CD4 count Per 50 cells/mm3 increase

0.6 (0.4-0.9)

* death rate highest 1-3 mo > last clinic visit

Predictors of Survival in LTF Patients

Study design and sampling frame

3,628 ART patients

77% (2,799) remained in care

23% (829) LTF

15% (128) tracked

13% (17) not found 25% (32) died 62% (79) alive

61% (48) patient interviewed

39% (31) informant interviewed

83% (40) in care elsewhere in last 3 months71% (34) taking ART in the last month

*self report

Extrapolating to all LTF patients

Patient attends clinic

Recorded survival and

retention

Unknown (LTF)

Recorded transfer

Recorded death

Unrecorded withdrawal

Unrecorded death

Self-reported transfer

~ 50% ~ 25% ~ 25%

Conclusions and points for future discussion

• Structural barriers to retention dominate the given reasons in this study– Are there program characteristics that address enablers

to retention?• Among those LTF later ascertained to be dead, highest

death rate shortly after last clinic visit

• Clinical/demographic factors associated with death among LTF patients suggests areas of potential intervention– How can this inform clinic monitoring of patients at high

risk of death?

• LTF is a mix of undocumented deaths (bad!), unknown (bad!) and transfers (problematic!)

Program characteristics associated with non-retention,

LTF, and death at ICAP sitesPreliminary workMatthew Lamb

Aims

• Are program-level characteristics (e.g., adherence support, outreach) associated with retention, LTF, or death at ICAP-supported sites?

• Are the observed associations similar when using aggregate (URS) and patient-level data?

Program characteristics

• Measured from PFaCTS• Only gets at program availability, not quality

or coverage• Reliability study ongoing, results soon!

• Current ICAP ‘retention’ programs focus primarily on psychosocial interventions to improve adherence to ART in addition to retention

Data sources

URS: 349 sites, 10 countries,

233,000 patients

URS: 242 sites, 5 countries,

156,000 patients

PLD: 84 sites, 5 countries, 80,000

patients

Program characteristics: PFaCTS

Study Design

• Aggregate estimates of LTF, Death, and Non-retention (LTF + Death) rates obtained from Track 1.0 indicators reported to URS• Cumulative number on ART – cumulative number LTF or dead• Excluding known transfers

• Patient-level estimates based on person-years since ART initiation until (a) documented death or (b) 6 months with no visit

• Excluding known transfers

• Information combined with PFaCTS to assess association between characteristics targeting adherence and retention and the two measures of LTF rates

Program characteristics associated with LTF: aggregate data

N = 384 sites with PFaCTS and URS care and treatment data through July, 2009 (10 countries)N = 242 sites with PFaCTS in countries providing electronic PLD, to ICAP-NY (5 countries)

N = 84 sites with PFaCTS, electronic PLD, and URS care and treatment data through July, 2009 (5 countries)

Educational materials

>1 directedcounseling

Frequentcounseling

Supportgroups

Peereducators

Remindertools

Food support

Outreach

Through June 2009. Adjusting for urban/rural, facility type, year facility began providing ART care, cumulative number of patients seen in care

LTF

Rat

e R

atio

(95

% C

I)

Preliminary results: focusing on two programmatic services (active patient outreach and food support): 84 sites with patient-level data

Aggregate analysis

1st bar = crude, 2nd bar = adjusted

Patient-level analysis

1st bar = crude, 2nd bar = adjusted for

site-level factors3rd bar = adjusted for

site- and patient-level factors

LTF since ART initiation, by urban/rural:100 ICAP sites with patient-level data

LTF since ART initiation, by facility type:100 ICAP sites with patient-level data

LTF since ART initiation, by year of ART initiation:100 ICAP sites with patient-level data

ICAP analysis: Strengths and limitations

• Routinely-collected data• Aggregate analyses can

use all ICAP care and treatment sites

• Patient-level analyses show that results from aggregate are largely reliable

• Routinely-collected data• PFaCTS doesn’t get at

program quality or coverage

• Potential misclassification in PFaCTS harder to detect true associations

Strengths Limitations

Conclusions

• Routinely-collected data provide evidence that program services may influence patient retention

• Structural barriers may be important (Geng), and one intervention aimed at these barriers (food support) is associated with reduced LTF

• Use of routinely collected data for program evaluation can provide insights for further research

Acknowledgements• ICAP country programs• ICAP M&E Advisors• Ministries of Health, provincial and district-level

programs• Non-governmental organizations and partners• PEPFAR• Doris Duke Charitable Foundation ORACTA program• ICAP M&E NY team• Molly McNairy• Denis Nash