Increasing Use of Facility-level Data to Address HRH Barriers to Service Delivery Using the PEPFAR Rapid Site-Level Health Workforce Assessment Tool Samson Kironde, HRH2030/URC November 13, 2017
Session Overview Brief overview of PEPFAR HRH rapid site-level assessment activity implemented in two countries (Malawi and Zambia) Illustrative results from the assessments that helped guide HRH decision-making at the national level Q&A
Tool Objective The PEPFAR Rapid Site-Level Health Workforce Assessment Tool provides PEPFAR-supported countries and other stakeholders with quick, site-level information on HRH availability for HIV service delivery in order to identify areas for further investigation and intervention.
What the Tool Addresses Types, number, and availability of HRH at the facility Issues affecting retention and productivity Current health worker allocation per service point Health worker capacity and preparation for providing quality HIV services HRH barriers pertaining to service delivery
Activity Background From April to August 2016, two rapid site-level HRH assessments were undertaken Aim was to conduct rapid site-level health workforce assessment of PEPFAR-supported facilities using a questionnaire developed by the PEPFAR HRH Technical Working Group and tailored to the specific needs of in-country PEPFAR teams HRH2030 conducted assessments in the PEPFAR-supported, high HIV burden countries Malawi and Zambia
Activity Background, continued In Malawi,110 health facilities participated from the districts of Blantyre (37 sites), Lilongwe (42 sites), and Zomba (31 sites) In Zambia,100 health facilities participated from the provinces of Central (19 sites), Copperbelt (36 sites), Lusaka (27 sites), and Southern (18 sites) Data collection utilized both hard copy and electronic versions of the questionnaire. Electronic data collection utilized mobile devices (tablets) and used free, open source software platforms (Open Data Kit in Malawi and CSPro in Zambia) Outputs from the assessment included a site-level dataset, country-specific reports, a shell database for use elsewhere, and recommendations for global application of the Excel tool.
Data Collection Tool
Data Collection Tool
Data Collection Tool
A hybrid paper-based and electronic system was used for data collection. Option 1 Web-based system Real-time data collection Web-based data management Web-based reporting system Option 2 Hybrid system Real-time data collection Web-based data management Off-line data processing, cleaning, and analysis (Excel) Off-line reporting system Option 3 Offline system Paper-based data collection Off-line data management Off-line data processing, cleaning, and analysis (Excel)
Electronic Data Management Process
Database Structure Zambia Example
Illustrative Results
Malawi Example The majority of health workers are health surveillance assistants (HSAs) and nurse midwife technicians in Malawi. No. of Health Workers by Cadre and District Medical Officers Clinical Officers Medical Assistants Registered Nurses Nurse Midwife Technicians Nursing Assistants Health Surveillance Assistants HIV Diagnostic Assistants Pharmacy Technicians Pharmacy Assistants Laboratory Technicians Laboratory Assistants Clerks Expert Clients Other Cadres* Total (%) District Blantyre 131 44 61 98 451 4 535 110 11 9 32 8 79 31 402 2,006 (31%) Lilongwe 28 91 66 89 362 29 675 144 23 21 57 19 89 244 790 2,727 (42%) Zomba 10 93 32 76 289 7 527 48 7 9 23 7 30 100 508 1,766 (27%) Total 169 228 159 263 1,102 40 1,737 302 41 39 112 34 198 375 1,700 6,499 Percent 3% 4% 2% 4% 17% <1% 27% 5% <1% <1% 2% <1% 3% 6% 26% * Other cadres include hospital attendants, TB volunteers, ward attendants, CHWs, clinic aides, guards etc.
Malawi Example Less than half of health workers (46%) are available to provide HIV services. HIV Service Delivery by District in Comparison to Total Staff Available District Staff Providing Service Total Staff HIV Services (any) HTC ART Initiation Viral Load/EID Blantyre 2,006 853 (42%) 148 (17%) 143 (17%) 130 (15%) Lilongwe 2,727 1,505 (55%) 594 (39%) 415 (28%) 517 (34%) Zomba 1,766 629 (36%) 149 (24%) 115 (18%) 132 (21%) Total 6,449 2,987 (46%) 891 (30%) 673 (22%) 779 (26%) Percentages for HTC, ART initiation, and viral load (VL)/early infant diagnosis (EID) testing are derived from the denominator of those who provide any HIV services. The percentages in columns 4-6 do not total 100 because only three of several services provided under the HIV service delivery cascade are presented in the table.
Malawi Example The majority of staff who provide HIV services are HSAs, nurse midwife technicians, other cadres, and expert clients. No. of Health Workers engaged in HIV Service Delivery by Cadre and District Medical Officers Clinical Officers Medical Assistants Registered Nurses Nurse Midwife Technicians Nursing Assistants Health Surveillance Assistants HIV Diagnostic Assistants Pharmacy Technicians Pharmacy Assistants Laboratory Technicians Laboratory Assistants Clerks Expert Clients Other Cadres Total District Blantyre 30 31 46 37 191 0 230 80 8 6 16 7 39 32 100 853 Lilongwe 17 69 54 66 278 25 219 143 19 18 31 8 83 223 252 1,505 Zomba 1 24 22 21 72 0 172 60 1 6 15 4 18 94 119 629 Total 48 124 122 124 541 25 621 283 28 30 62 19 140 349 471 2,987 Percent 2% 4% 4% 4% 18% <1% 20% 9% 1% 1% 2% <1% 5% 12% 16% * Other health workers include hospital attendants, TB volunteers, ward attendants, CHWs, clinic aides, guards, etc.
There was evidence of task-shifting of key HIV service delivery functions to lower level cadres. Zambia Example
Zambia Example Staff attrition over time is high at many sites the reasons are diverse. No. of Sites Where a Health Worker Resigned or Quit His/Her Job by no. of Months Passed When They Quit 35 30 25 20 15 10 5 Social workers Pharmacists Peer educators/navigators Other Nurses Midwives Medical licentiates Lay counsellors Doctors Clinical officers Cleaners 0 Less than a month ago Less than 6 months ago More than 6 months ago
Zambia Example Top Reasons Health Workers Quit Their Jobs or Ask to be Transferred Province Central Copperbelt Top Reasons provided by Health Workers First Reason(s) Second Reason(s) Third Reason(s) Not doing job tasks trained for Remoteness of area Better opportunities in private sector Not doing job trained for Better opportunities in private sector Insufficient salary and benefits Remoteness of area Not doing job tasks trained for Better opportunities in private sector Lack of professional advancement opportunities Not doing job tasks trained for Insufficient salary and benefits Insufficient salary and benefits Better opportunities in private sector Inadequate facility infrastructure and equipment Not doing job tasks trained for Lusaka Not doing job tasks trained for Insufficient salary and benefits Reassigned by government Not doing job tasks trained for Better opportunities in the private sector Burnout Insufficient salary and benefits Insufficient housing and utilities Southern Better opportunities in private sector Burn out Not doing job tasks trained for Not doing job tasks trained for Reassigned by government Lack of professional advancement opportunities Not doing job tasks trained for
Zambia Example No. of Sites where Job Positions are Still Vacant by Cadre and Duration 8 7 6 5 4 3 2 1 It is harder to fill positions for clinical officers once they leave. Social workers Pharmacists Peer educators/navigators Other Nurses Midwives Medical licentiates Lay counsellors Doctors Clinical officers Cleaners 0 For less than a month For less than 6 months For more than 6 months