Pay-for-Performance and Distributional Effects in Tanzania: A Supply-side Assessment

Peter Binyaruka

Nov, 2015

IntroductionBackground • P4P is expected to close the gap between poorly

performing and well performing facilities • But the gap could also widen if better performing or

better off facilities are better able to meet the targets

What we know No evidence from low and middle income countries. Studies in high income countries (US, UK) found: • Performance was positively associated with facility

economic status, workforce resources, facility size, etc. • Decreasing trend in performance inequality

Objectives

Our study had 2 objectives:

1. To assess how the P4P payouts are distributed across health facilities in Pwani region • By socio-economic status • Identify contributing factors to any inequity in payouts

2. To examine whether there was any difference in the effect of P4P on service utilization outcomes between facilities • Based on analysis of household and facility data from Pwani

region and control sites before and 13 months after the intervention.

Bonus Payouts Made every 6 months (in USD)

Total % staff % facility improvement

Hospitals 6,790 60 (RCH) 30 (non-RCH)

10

Upgraded health centres 4,380 75 25

Health centres 3,220 75 25

Dispensaries 820 75 25

Health worker incentive + 10% of salary. Extra 0.30 USD per capita

MethodsDefinition of outcome variables:

(1) Facility payouts –payout score -% of payout received relative to potential payouts if all targets achieved by 100% -Since there is a maximum potential amount by level of care

-Score for each payment cycle [1-7] …[2011 -2014] -Data source: P4P implementing agency (CHAI)

(2) Utilization outcomes –service coverage (%) • Facility-based deliveries (FBD) • Antimalarial provision during pregnancy (IPT2)

-Data source: from household surveys (2012 -2013) cycles 1-4

Methods: facility characteristics considered

Facility characteristics (predictors) “Better-off” “Worse-off”

Facility socio-economic status (SES) Higher SES Lower SES

Ownership Public owned Non-public

Level of care Hospital & HC Dispensary

Insurance scheme (CHF) With CHF Without CHF

Infrastructure With clean water, electricity Without

Drug stock-out (binary for 50% of 9 drugs) Lower stock-out Higher stock-out

Equipment availability (binary for 50% of 19 items) Higher availability Lower availability

Baseline coverage group level (5 groups by P4P design) Higher level Lower level

• Predictors were measured at baseline • Grouping based on: capacity to enhance demand, resource capacity, organization and size • Expecting better-off to have higher payouts and more utilization effects than worse-off

Statistical Analysis

Distribution of facility payouts (benefits) • Bivariate analysis [Payout score vs. Facility SES]

✓ Equity gap, ratio and concentration indices

• Decomposition analysis –on significant inequality

Distribution of utilization effects • Difference-in-difference (DD) regression analysis

✓ Sub-group analysis [Better vs. Worse-off] ✓ Full sample analysis [Interaction term]

RESULTS (1): Payout scores by facility SES (inequalities)

“Pro-rich pay outs, but improves over time”

Payout scores †

All Facility SES Equity Conc. Index (CI)

Mean [SD] Higher Lower Gap Ratio

(1) (2) (3) (4) (5) (6)

CYCLE 1 (%) 50.1 [19.4] 53.8 46.5 7.3 (0.157) 1.16 0.045

CYCLE 2 (%) 50.3 [19.1] 57.2 43.3 13.9 (0.000) 1.32 0.087***

CYCLE 3 (%) 64.6 [18.8] 69.5 59.8 9.7 (0.015) 1.16 0.036*

CYCLE 4 (%) 67.5 [19.5] 68.5 66.5 2.0 (0.414) 1.01 0.006

CYCLE 5 (%) 74.5 [18.5] 75.1 74.0 1.1 (0.829) 1.01 0.006

CYCLE 6 (%) 69.6 [20.1] 73.5 65.8 7.7 (0.154) 1.12 0.035

CYCLE 7 (%) 77.7 [16.3] 78.2 77.2 1.0 (0.871) 1.01 0.006

Average score cycles (1-3) (%) 54.9 [13.7] 60.8 51.7 9.1 (0.068) 1.18 0.054**

Average score cycles (1-7) (%) 64.7 [11.7] 67.7 61.8 5.9 (0.071) 1.09 0.027*

Notes: † =(Actual/Potential) x 100%, where potential is the payout amount entitled to be given for reaching 100% of pre-defined target; p-values in parentheses in equity gap are from t-test; SD=Standard Deviation; Gap=Higher-Lower; Ratio=Higher/Lower

RESULTS (2): Decomposition of Inequality in Payouts (during first 3 cycles)

Predictors

Conc. Index -CI (P-value)

OLS –regression (P-value)

Elasticity ContributionCI %

(1) (2) (3) (4) (5)

Facility in lower SES -0.493 (0.000) -5.9 (0.310) -0.054 0.028 49.8%Dispensary level -0.130 (0.014) -4.4 (0.160) -0.056 0.007 13.7%

Baseline coverage 0.029 (0.556) 3.8 (0.000) 0.188 0.005 10.2%Public owned -0.050 (0.041) -5.5 (0.250) -0.083 0.004 7.8%Facility with CHF 0.028 (0.495) 6.4 (0.275) 0.091 0.003 4.8%Higher Drug stock-out -0.026 (0.137) -5.2 (0.190) -0.042 0.001 2.0%Higher Equipment 0.030 (0.386) 2.4 (0.600) 0.028 0.001 1.6%Infrastructure available 0.153 (0.011) -0.1 (0.980) -0.001 -0.000 -0.3%Residual 0.005 10.4%Total N=75

R-squared=40.9 0.054** 100.0%

Note: Drug stock-out includes nine drugs (antimalarial and delivery drugs); Equipment is binary (high and low availability); infrastructure is availability of both electricity and clean water; OLS estimates using bootstrapping approach in data clustering; same pattern in % contribution if other predictors are added –distance (3.5%), patient-staff ratio (-9.0%) and intrinsic motivation (0.02%).

RESULTS (3): Distribution of service utilization effects Outcome variable/ Grouping variable

Baseline level   Difference in differences, effect

Intervention arm (1)

Comparison arm (2)

  Better-off (3)

Worse-off (4)

Differential (5)

Better Worse Gap Better Worse Gap   N N

Facility based delivery

                       

Facility SES 90.6 81.4 9.2 (0.004) 89.1 82.6 6.5 (0.018)

  2886 3.6* 2861 10.0*** -6.4 (0.141)

Ownership 84.6 85.2 -0.6 (0.868) 86.6 87.9 -1.3 (0.716)

  4716 9.1*** 1031 4.9 4.2 (0.228)

Level of care 89.4 82.7 6.7 (0.134) 90.9 85.0 5.9 (0.020)

  1712 5.4 4035 8.9*** -3.5 (0.584)

CHF 84.9 84.1 0.8 (0.795) 88.9 84.1 4.8 (0.059)

  3833 7.6*** 1914 7.0* 0.6 (0.911)

Infrastructure 87.2 81.7 5.5 (0.118) 88.3 85.2 3.1 (0.223)   3077 7.0** 2670 9.0*** -2.0 (0.545)

Drug stock out 85.9 83.7 2.2 (0.532) 87.3 85.9 1.4 (0.561)   3095 5.2** 2652 11.0*** -5.8 (0.205)

Equipment 88.0 78.5 9.5 (0.032) 86.4 87.4 -1.0 (0.710)

  2192 13.0*** 3555 5.6** 7.4 (0.164)

                         

IPT2                        

Facility SES 45.6 51.6 -6.0 (0.100) 54.6 60.6 -6.0 (0.074)

  2430 9.8** 2329 13.0*** -3.2 (0.659)

Ownership 50.2 46.3 3.9 (0.531) 57.6 53.0 4.6 (0.313)   3904 10.0*** 855 11.0 -0.9 (0.916)

Level of care 42.4 52.7 -10.3 (0.009)

60.5 54.9 5.6 (0.124)   1450 14.0** 3309 8.3** 5.7 (0.250)

CHF 49.5 49.8 -0.3 (0.950) 60.4 52.2 8.2 (0.023)

  3162 12.0*** 1597 9.2 2.8 (0.656)

Infrastructure 47.4 52.4 -4.9 (0.159) 57.9 55.2 2.7 (0.453)   2609 11.0*** 2150 10.0** 1.0 (0.761)

Drug stock out 47.0 52.8 -5.8 (0.107) 55.5 57.9 -2.4 (0.499)

  2539 11.0*** 2220 8.6** 2.4 (0.628)

Equipment 48.2 52.3 -4.3 (0.254) 55.8 57.9 -2.1 (0.552)

  3000 11.0*** 1759 8.3 2.7 (0.608)Notes: P-values in parentheses; Better-off facilities are those in high SES, public, non-dispensary, with CHF and infrastructure, low drug stock-out and high equipment availability; the coefficient is the estimated intervention effect controlling for a year dummy, facility-fixed effects, individual-level and household characteristics; * p<0.10, ** p<0.05, *** p<0.01;

ConclusionsDistribution of facility payouts [payout score]

• Payout scores were increasing over time among all facilities • Payouts were initially pro-rich, but improved over time • Main contributors to initial inequality in payouts (decomposition)

▪ Facility SES, level of care, baseline level of performance, ownership

Distribution of utilization effects [deliveries & IPT2] • No evidence of differential effects, but indication of:

▪ Stronger effect on lower SES facilities (both outcomes) ▪ Stronger effect on deliveries among dispensaries ▪ Stronger effect on IPT among better resourced facilities

Thank you..!!