The effects of user fees on quality and utilization of primary care services in Afghanistan Laura Steinhardt, David Peters, Sahibullah Alam, Krishna Rao, Peter Hansen July 15, 2009

Background I Rapid rebuilding of health care infrastructure in Afghanistan since 2001 Development of Basic Package of Health Services (BPHS) for primary care BPHS delivery contracted to NGOs in most provinces Vastly expanded access to BPHS services from 2001-present BPHS heavily donor-dependent Reliant for nearly all BPHS services on 3 major donors Funded at ~$2 US to $5 US per capita (avg.= $4)

Rapid rebuilding of health care infrastructure in Afghanistan since 2001

Development of Basic Package of Health Services (BPHS) for primary care

BPHS delivery contracted to NGOs in most provinces

Vastly expanded access to BPHS services from 2001-present

BPHS heavily donor-dependent

Reliant for nearly all BPHS services on 3 major donors

Funded at ~$2 US to $5 US per capita (avg.= $4)

Background II No standard guidelines on cost sharing Most BPHS facilities charged some type of fees Little evidence from post-conflict settings on effects of fees on revenues, quality and utilization Source: National Health Services Performance Assessment (NHSPA) facility surveys, 2004-2007.

No standard guidelines on cost sharing

Most BPHS facilities charged some type of fees

Little evidence from post-conflict settings on effects of fees on revenues, quality and utilization

Health financing pilot objectives and description Objectives: Evaluate different community financing mechanisms on ability to: Improve quality of care Increase financial access to care Raise revenue for health sector Enhance community ownership Pilot types: User fees (standard fee for services and for drugs) Community health fund (voluntary pre-payment scheme) Free services Control facilities (continued current cost sharing scheme – 60% charged fees at baseline)

Objectives: Evaluate different community financing mechanisms on ability to:

Improve quality of care

Increase financial access to care

Raise revenue for health sector

Enhance community ownership

Pilot types:

User fees (standard fee for services and for drugs)

Community health fund (voluntary pre-payment scheme)

Free services

Control facilities (continued current cost sharing scheme – 60% charged fees at baseline)

User fee pilot description Average visit fee: 11.5 Afs (~ $0.23 US) Service fee: 2-7 Afs. Drug charge: 10-50% wholesale price Fees retained at facility Managed by user fee subcommittee Used to make quality improvements (small repairs, drug purchases, improve infrastructure) Waiver card system for very poor and female-headed households Community leaders identified poor in each village All preventive, promotive care free* * Includes EPI, well-baby visits, ANC, deliveries, family planning and TB care and emergencies.

Average visit fee: 11.5 Afs (~ $0.23 US)

Service fee: 2-7 Afs.

Drug charge: 10-50% wholesale price

Fees retained at facility

Managed by user fee subcommittee

Used to make quality improvements (small repairs, drug purchases, improve infrastructure)

Waiver card system for very poor and female-headed households

Community leaders identified poor in each village

All preventive, promotive care free*

Quasi-experimental pre/post design Pilots implemented in 10 provinces (7 managed by NGOs, 3 by MoPH) 5-6 facilities eligible in each province 2 of 3 interventions implemented/province Facilities randomized within provinces Piloted from 2005-2007 Design of health financing pilots Province 1 Facility 1 Facility 5 Facility 4 Facility 3 Facility 2 n=27 n=10 n=10 Free Services User Fees Control

Quasi-experimental pre/post design

Pilots implemented in 10 provinces (7 managed by NGOs, 3 by MoPH)

5-6 facilities eligible in each province

2 of 3 interventions implemented/province

Facilities randomized within provinces

Piloted from 2005-2007

Evaluation data sources Pre/post facility assessments Pre/post patient exit interviews Pre/post catchment area surveys Health Management Information System (HMIS) utilization data In-depth interviews with: Facility staff Community leaders

Pre/post facility assessments

Pre/post patient exit interviews

Pre/post catchment area surveys

Health Management Information System (HMIS) utilization data

In-depth interviews with:

Facility staff

Community leaders

Evaluation analytic methods Construction of observed and perceived quality scales from binary and Likert-scale questions Despite randomization of facilities within provinces, differences across provinces in: Managing service provider (NGO) Baseline fee levels Difference-in-Difference (DD) cross-tabs and regression models used, where appropriate Line-by-line coding of key themes in qualitative transcripts

Construction of observed and perceived quality scales from binary and Likert-scale questions

Despite randomization of facilities within provinces, differences across provinces in:

Managing service provider (NGO)

Baseline fee levels

Difference-in-Difference (DD) cross-tabs and regression models used, where appropriate

Line-by-line coding of key themes in qualitative transcripts

Results – observed quality of care +6.4 +5.8 +12.1 +8.3 Note: Each line represents one facility.

Difference-in-difference linear regression of perceived quality, among households

Percent of households rating facility as affordable Notes: Affordability efined as 3 or 4 on Likert-scale question: “The cost of the facility is reasonable” (3=agree; 4=strongly agree). Perceived affordability significantly lower at Free Services facilities at baseline (p<0.05). The only significant change in affordability (from DD logistic regression, adjusted for province, wealth, and walking time) was for User Fee-District Hospitals (p<0.01).

Results – staff and community leaders’ thoughts on quality and affordability Important sources of discretionary income Allows greater autonomy in day-to-day functioning Wide variations in percent of revenues spent and what they were spent on across user fee facilities Drugs to prevent stock-outs Infrastructure upgrades (female waiting room, heaters) Small staff incentives (<10% revenues) User fees generally affordable by all, but exceptions at a few facilities In Badghis province, patients w/o waiver cards had to borrow from shopkeepers to pay fees Source: In-depth interviews.

Important sources of discretionary income

Allows greater autonomy in day-to-day functioning

Wide variations in percent of revenues spent and what they were spent on across user fee facilities

Drugs to prevent stock-outs

Infrastructure upgrades (female waiting room, heaters)

Small staff incentives (<10% revenues)

User fees generally affordable by all, but exceptions at a few facilities

In Badghis province, patients w/o waiver cards had to borrow from shopkeepers to pay fees

Change in average monthly OPD visits, one year pre- vs. one year post Source: HMIS data. +102% +11% +22% +33% +52%

Percent of sick household members seeking care first from pilot facility* * Among those seeking care Note: Lower % at free facilities seek care first at pilot facility at baseline (p<0.05); No significant change over time, by study group, adjusted for province, walking time, age, sex, wealth, and illness type. Source: Baseline and follow-up Catchment area surveys.

Results – staff and community leaders’ thoughts on utilization Free services are good for patients (increased access) but bad for facilities (overcrowding) Now mildly ill or non-patients come for care Less staff time and drugs left for “real patients” When there are fees, “only the real patients come” Patients value medicines more when they pay for them

Free services are good for patients (increased access) but bad for facilities (overcrowding)

Now mildly ill or non-patients come for care

Less staff time and drugs left for “real patients”

When there are fees, “only the real patients come”

Patients value medicines more when they pay for them

Summary of results of user fees No differential effect on quality (observed or perceived) Generally considered affordable, but not always by the poorest Staff positive about fees Revenues useful for making real-time repairs Fees decrease patient loads Suppressive effect on curative care utilization Large rise in visits when fees removed Stronger effects of medication fees than service fees

No differential effect on quality (observed or perceived)

Generally considered affordable, but not always by the poorest

Staff positive about fees

Revenues useful for making real-time repairs

Fees decrease patient loads

Suppressive effect on curative care utilization

Large rise in visits when fees removed

Stronger effects of medication fees than service fees

Conclusions Fees have few beneficial effects in rapidly changing post-conflict setting Other factors, such as regular performance monitoring (Balanced Scorecard), may have greater impacts on quality Fees – even at nominal levels – reduce access to care Removing all barriers to access important in low-utilization, post-conflict settings Limited revenues raised (average = 3.6% facility operating costs), but important source of discretionary income

Fees have few beneficial effects in rapidly changing post-conflict setting

Other factors, such as regular performance monitoring (Balanced Scorecard), may have greater impacts on quality

Fees – even at nominal levels – reduce access to care

Removing all barriers to access important in low-utilization, post-conflict settings

Limited revenues raised (average = 3.6% facility operating costs), but important source of discretionary income

Policy results and recommendations Ministry of Public Health banned user fees at BPHS facilities in 2008 Visits increased by 13% in following 3 months In light of blanket policy decision, need to consider: Flexibility for BPHS providers to increase staffing, funding, at facilities Possible alternative mechanisms for discretionary funds at facilities Continued monitoring to ensure no unintended consequences or under-the-table payments

Ministry of Public Health banned user fees at BPHS facilities in 2008

Visits increased by 13% in following 3 months

In light of blanket policy decision, need to consider:

Flexibility for BPHS providers to increase staffing, funding, at facilities

Possible alternative mechanisms for discretionary funds at facilities

Continued monitoring to ensure no unintended consequences or under-the-table payments

Thank you Acknowledgments: Ministry of Public Health, Kabul, Afghanistan; Johns Hopkins University, Kabul, Afghanistan; Future Health Systems ( www.futurehealthsystems.org ) Author contact info: Laura Steinhardt: [email_address] David Peters: [email_address] Sahibullah Alam: [email_address] Krishna Rao: [email_address] Peter Hansen: [email_address]

Acknowledgments: Ministry of Public Health, Kabul, Afghanistan; Johns Hopkins University, Kabul, Afghanistan; Future Health Systems ( www.futurehealthsystems.org )

Author contact info: Laura Steinhardt: [email_address]

David Peters: [email_address]

Sahibullah Alam: [email_address]

Krishna Rao: [email_address]

Peter Hansen: [email_address]

Additional Slides

Difference-in-difference linear regression of average monthly OPD visits, pre- vs. post Model uses Huber-White robust standard errors (White 1980). Data on up to 10 additional non-pilot facilities/province added to control group to yield N=98 facilities at baseline (one year pre-HFP) and N=98 at follow-up (one year post-HFP). Source: HMIS data. Free facilities increase the most, but Starting fee levels matter Prior medication fees have large impacts on subsequent use Facilities randomized to free services that had prior service and drug fees had huge increases after fees removed

Free facilities increase the most, but

Starting fee levels matter

Prior medication fees have large impacts on subsequent use

Facilities randomized to free services that had prior service and drug fees had huge increases after fees removed

Table 1: Baseline study groups