F inancing and Managing the Health Workforce in the Public Sector
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Financing and Managing the Health Workforce in the Public Sector Marko Vujicic and Susan Sparkes The World Bank Geneva, Switzerland October 21, 2008 Outline of Presentation What staffing levels are fiscally sustainable in the public sector? What are training costs to staff up to these levels? Would all migrants be able to find jobs if they did not migrate? What are the major fiscal and managerial bottlenecks to scaling up staffing? • Wage bill policies • Management policies and practices What staffing levels are fiscally sustainable in the public sector? Total Economically Sustainable Staffing Levels Health spending scenarios HRH scenarios Annual Economic Growth (%) Public Health Expenditures as % of Gov. Expenditures by 2015 (%) Insurance Effect (as % of Out-ofPocket Spending) Worst case -5 -5% change 0 Best case 5 15% 60 Projection of past trends Average growth 19962005 Average HE 1996-2005 0 Scenario Scenario Shift to low skill mix No wage change Least expensive largest number of staff 20% wage increase No skills mix change Shift to highs skills mix Most expensive smallest number of staff See: A. Preker, M. Vujicic, Y. Dukhan, C. Ly, H. Beciu, and P.N. Materu, “Scaling up Health Professional Education: Opportunities and Challenges for Africa, The World Bank, DRAFT, January 2008. Total Economically Sustainable Staffing Levels 5 4.5 per 1,000 population 4 3.5 Baseline 3 Worst Case Best Case 2.5 Projections of past trends 2 1.5 1 0.5 0 No wage change, no skill mix change No wage No wage 25%wage increase, no change, skill change, skill mix shifts to mix shifts to skill mix low skill high skill change 25%wage increase, skill mix shifts to high skill 50%wage 25%wage increase, increase, no skill mix skill mix change shifts to low skill What are training costs to staff up to these levels? Total Additional Training for All Staff millions corrected for zeros 3 2.5 2 Best Case 1.5 Projections of past trends 1 0.5 0 No w age 25% No w age change, w age change, no skill increase, skill mix no skill shifts to mix mix high skill change change No w age 25% 25% 50% change, w age w age w age skill mix increase, increase, increase, shifts to skill mix skill mix no skill low skill shifts to shifts to mix high skill low skill change Total Additional Doctors to Be Trained 600,000 500,000 400,000 300,000 Best Case 200,000 Projection of Past Trends 100,000 0 50% 25% 25% No w age No w age 25% No w age w age w age w age change, change, w age change, skill mix increase, increase, increase, no skill increase, skill mix no skill skill mix skill mix shifts to shifts to no skill mix mix high skill low skill shifts to shifts to mix change change high skill low skill change Total training Costs for IDA Countries under the Projection of Past Trends (millions, 2006 USD) IDA, Projection of Past Trends Public expenditures on Tertiary Education 18,000 16,000 14,000 12,000 10,000 8,000 6,000 4,000 2,000 - CHW, PH, and other Nurses and midwives Dentists and Pharmacists Doctors No wage change, no skill mix change 25% wage increase, no skill mix change No wage change, skill mix shifts to high skill No wage 25% wage 25% wage Public change, skill increase, skill increase, skill expenditures mix shifts to mix shifts to mix shifts to on tertiary low skill high skill low skill education Cost of Training Additional Health Workers All, Best Case 60,000 Public expenditures on Tertiary Education 50,000 CHW, PH, and other 40,000 Nurses and midwives 30,000 Dentists and Pharmacists 20,000 Doctors 10,000 0 No wage change, no skill mix change 25% wage increase, no skill mix change No wage No wage 25% wage 25% wage 50% wage Public change, skill change, skill increase, skill increase, skill increase, no expenditures mix shifts to mix shifts to mix shifts to mix shifts to skill mix shift on tertiary high skill low skill high skill low skill education Would all migrants be able to find jobs if they did not migrate? Nurse migration trends Nurse out migrations as sha re of domestic stock EAP LAC SAS SSA Fiji Indonesia Philippines Belize Nicaragua Chile Peru Haiti Nepal Pakistan India 0.01 0.00 0.08 0.04 0.00 0. 00 0.00 0.29 0. 01 0.01 0.01 Uganda Cameroon Gambia Liberia Sierra Leone Senegal Malawi Ethiopia Zimbabwe Kenya Ghana 0 0. 00 0. 00 0.01 0.04 0.02 0.01 0.01 0. 01 0.02 0.01 0. 02 .1 .2 Outflow of Nurses as share of Domestic Stock of Nurses .3 See: “The Nurse Education and Labor Market in the English-Speaking CARICOM: Issues and Options for Reform,” The World Bank, DRAFT June 2008. Fiscal Space and Nurse Migration GHE/GE in different scenarios EAP LAC 9.10 9. 21 Fiji Indonesia Philippines 5.00 5.00 6.30 7.54 6. 50 6.94 Belize Nicaragua Chile Peru Haiti 12.00 12.08 13.10 13.20 9. 00 9.08 23.90 42.09 8.10 8.51 SAS Nepal Pakistan India SSA Uganda Cameroon Gambia Liberia Sierra Leone Senegal Malawi Ethiopia Zimbabwe Kenya Ghana 1.90 1. 98 2.90 3.01 0 10.00 10.02 10.50 10. 53 5. 90 6.17 20.10 21. 36 7.80 8.05 9.80 10.13 28.80 29.02 9.40 9.51 8. 90 9.31 8.20 8.31 8. 40 8.82 10 Baseline 20 30 Government absorbs all nurses who migrate 40 What are the major fiscal and managerial bottlenecks to scaling up staffing? What is the impact of government wage bill policies on the health workforce? Are current human resources management policies and practices strategic? Working in Health: Financing and Managing the Public Sector Health Workforce Marko Vujicic, Kelechi Ohiri, and Susan Sparkes The World Bank Forthcoming in spring 2009 Background Large gap between the workforce level needed to deliver essential services and current employment levels in developing countries Within the public sector a major issue is often lack of resources available to pay the salary costs of an expanded health workforce due, in turn, to restrictive policies on the overall public sector wage bill While the debate has been intense there is a lot of misinformation and little documented country experience Objectives Geographic Distibution Government Health Health Fiscal Wage Workforce Policy Bill Staffing Levels Productivity Absenteesim Analyisis of Analysis of Analyisis of Other Human Wage Bill Recruitment Resource Budgeting Process Management Process Policy Question #1 in Report: What is the impact of government wage bill policies on the size of the health wage bill and on health workforce staffing levels in the public sector? Functions Policy Question #2 in Report: Within the current health wage bill envelope, do the existing human resources management policies and practices lead to strategic use of wage bill resources? Better than average Worse than average -3 -2 -1 0 1 2 Performance relative to income Source: WDI 3 Health Workers per 1000 relativ e to income & health spending, 2005 -2 -1.5 RWA DOM ZMB KEN Worse than average Better than average -1 -.5 0 .5 1 1.5 Performance relative to income Source: WDI 2 Better than average DOM KEN RWA ZMB Worse than average DOM KEN Births attended by skilled attendant relativ e to income & health spending, 2005 Better than average Worse than average -2 -1.5 -1 -.5 0 .5 Performance relative to income Source: WDI 1 Doctors per 1000 relativ e to income & health spending, 2005 Worse than Better than average average Performance relative to health spending -2 -1 0 1 ZMB RWA Performance relative to health spending -3 -2 -1 0 1 2 3 Better than Worse than average average Maternal mortality relativ e to income & health spending, 2005 Worse than Better than average average Performance relative to health spending -2 -1 0 1 Performance relative to health spending -3 -2 -1 0 1 2 3 Country Case Studies Worse than average -3 -2 DOM KEN ZMB RWA Better than average -1 0 1 2 Performance relative to income Source: WDI 3 Wage Bill Budgeting Separate Budgeting Process Fully Flexible Budgeting Process Ministry Ministry of Finance of Finance Overall Non-wage Provincial Wage Bill Expenditure Health Authority Ministry Ministry District of Health of Health Health Wage Bill Non-wage Authority Health Non-Labor Workers Inputs DISCONNECT Facility Health Non-Labor Workers Inputs Public Sector Wage Bill as Share of GDP 10.0% 8.0% 4.0% 2.0% Kenya • “Wage policy measures will include … Zambia Rw anda 2008 2007 2006 2005 2004 2003 2002 0.0% 2000 implemented a hiring freeze as part of its program with the IMF, but explicitly excluded doctors and nurses. 6.0% 2001 Zambia • In 2002, the Government of Zambia Dominican Republic Kenya Health Wage Bill as Share of Overall Wage Bill flexibility to allow for recruitment of medical personnel in order to aim at 20.0% reaching the optimum level of personnel for the health sector and to move toward 15.0% achieving the MDGs.” 10.0% 5.0% Zambia Rw anda Dominican Republic 2007 2006 2005 2004 2003 2002 2001 2000 0.0% Kenya Recruitment Zambia • 1,700 funded positions • MOH was able to fill only 1,400 positions within the budgetary timeframe • Funding for 300 positions had to be returned to the Ministry of Finance Kenya – different story Current Status Unemployed Employed Private Other Employed FBO Employed MOH Employed NGO Total Number 2064 1110 661 465 166 0 4466 Wage Bill Budgeting Distibution of Civil Service Employees by Sector (all levels of government) 100% 90% 80% 70% 60% Other 50% Education 40% Health 30% 20% 10% Source: World Bank Government Wages and Employment Dataset Turkey Rwanda Philippines Pakistan Nicaragua Morocco Mexico Madagascar Lebanon Kenya Indonesia Egypt Cambodia Bulgaria Brazil Botswana Belarus 0% Impact on the overall public sector wage bill of changing staffing and wages in the health sector – Kenya Health Wage Bill/Total Wage Bill BASELINE Health Wage Bill/Total Wage Bill NEW Increase Increase doctors' salaries by 25% (or Increase number of doctors by 25%) 9.63% 9.87% 0.24% Increase nurses' salaries by 25% (or Increase number of nurses by 25%) 9.63% 10.82% 1.19% Increase salaries for all health workers by 25% (or increase number of all health workers by 25%) 9.63% 12.04% 2.41% Scenario Sources: World Bank calculations based on Kenya Case Study Impact on the overall public sector wage bill of changing staffing and wages in the health sector – Zambia Health Wage Bill/Total Wage Bill BASELINE Health Wage Bill/Total Wage Bill NEW Increase Increase doctors' salaries by 25% (or Increase number of doctors by 25%) 10.80% 11.04% 0.24% Increase nurses' salaries by 25% (or Increase number of nurses by 25%) 10.80% 11.70% 0.90% Increase salaries for all health workers by 25% (or increase number of all health workers by 25%) 10.80% 13.50% 2.70% Education Wage Bill/Total Wage Bill BASELINE Education Wage Bill/Total Wage Bill NEW Increase 12.38% 15.04% 2..66% Scenario Increase teacher salaries by 25% (or Increase number of teachers by 25%) Sources: World Bank calculations based on Zambia Case Study, Zambia Education Public Expenditure Review 2006 Key HRH management policies and practices Creation of vacancies • Often top down, not needs-based, no linked to geographic areas Recruitment of workers • Takes too long (14 months in Kenya) to recruit new staff and to fill up vacancies • Centrally managed Terms of service (mostly related to civil service constraints) • Tenure • Very little use of term contracts • Remuneration • Salary and non-performance based allowances • Promotion and transfers • Policies are not implemented • Not carried out in a strategic way • Sanctions • Rare Process for Filling a Vacancy in Kenya Emergency Hiring Program - Kenya Characteristic Remuneration GOK Tenure Recruitment process Permanent Through Public Service Commission (PSC) Recruitment conditions Deployment conditions Length of funding Funding channel Monitoring and evaluation Time to fill a position Recruited to public service, so can be deployed anywhere Unlimited None Varied; in some cases 10 months from advertisement to interview Emergency Hiring Program As GOK without pension but with gratuity of 31% of basic salary per annum 3-year contract Delegated by PSC to MOH with technical support from the Capacity Project and Deloitte & Touche. Tight control to ensure no interference in selection process Merit-based for all who meet job criteria except staff currently employed by faith-based organizations (FBOs) Can only be deployed to designated districts selected by MOH and Capacity on the basis of staff shortage 3 years Salaries paid directly to employees (PEPFAR funds) Direct to government (Clinton Foundation, GFATM) Detailed monthly follow up to monitor numbers and location of staff Letters of appointments sent within 4 months of advertisement; first batch of staff in post within 5 months after receiving a 2-week induction course; second batch within 8 months Is Money Scarce? Not always. Wage bill budget execution rates can be very low Year 2004 2005 2006 2007 Dominican Republic 95% 93% 107% - Kenya Rwanda Zambia 101% 99% - 99% 91% 91% - 50% 70% Are People Scarce in Kenya? Total Applicants M/F Total Qualified Applicants (Shortlisted) Total Selected Applicants (Deployed MOH) 6566 4466 677 Nairobi Central Province 494 1197 338 898 7 71 Coast 224 143 49 Eastern 1138 834 36 North Eastern 100 72 110 Nyanza 1050 441 98 Rift Valley 1674 1247 149 Western 689 493 99 Location of Residence Conclusions In the case studies… • Fiscal constraints were not relevant in all countries • Public sector management issues were a major constraint everywhere Policy options Strengthening accountability and improving human resources management capacity within the Ministry of Health; Using allowances more strategically and payment mechanisms other than salary; Enhancing the position of the Ministry of Health in the wage bill negotiation process; Improving the predictability of health wage bill budgets; Easing the fiscal constraint on the overall wage bill; Making better use of donor assistance for health; Transferring control of certain human resource management functions to the Ministry of Health while keeping the health workforce within the civil service; Decentralizing certain human resource management functions to the local level; Removing the health workforce from the civil service and the overall wage bill;
