New WHO Guidelines on Person centred monitoring New WHO Guidelines on Person centred monitoring Daniel Low-Beer, WHO 2017 Paris, July 2017

Contents Strengthening and securing person centred data Fifteen key recommendations How to implement the guidelines

Data is part of the package of the primary HIV response: at all levels for decision making Global impact: measure and manage programs Impact surveys Epi and impact reviews: regular, practical evaluation District and facility: focus and differentiation Standard dashboards: testing, treatment, viral load Individual and community: linkage, retention, quality of care 60% of decisions which affect HIV Benefits and tackle security of data Countries that achieve impact use data differently: Thailand, Uganda, Brazil, Malawi, Zimbabwe, Kenya, compared to those that have not

Needs of local health facility Adherence support – ‘When we follow up patients lost to follow up as many as 75% have gone to another clinic, we need to phone up, find them. In terms of time and cost, what took two days can take four or five hours, we can save 50% of our time, we also can’t distinguish new and old patients” (Kuwadzana clinic, Zimbabwe) Drug and Diagnostics - “If they want to come and collect new drugs, they will just get tested again elsewhere. There is retesting, viral load, a new care booklet, follow up every month for six months. We also don’t pick up if they were defaulters. Someone is given first line when they were already on second line. Our forecasting will be more accurate, we can improve stocks by 20%” Differentiated care and people living with HIV – patients who move between clinics, and between community and clinic, receiving HIV and health services. Need a person centred monitoring system to deliver person centred healthcare.

2. New guidelines: strengthen person centred monitoring Strengthen and secure individual basis of M&E systems

Strengthen and secure data for HIV cascade of services 1. 2. 3.

15 key recommendations Minimum dataset for patient care – guidance on standard data set Transitioning to “treat all” – guidance on updated cards, registers, reports transition Simplification of tools – generic tools for adaptation for paper and electronic systems Integration and linkages – generic patient card and link to health folder or passport Data quality review and for quality of care – guidance on annual monitoring review Standardisation of sentinel events and indicators – core information on a standardisation set of sentinel events, a minimum of six, of value for routine care and reporting De-duplication of records to support facilities and improve data – HIV case surveillance should provide de-duplicated counts of diagnosis, treatment and retention to facilities Country situation analysis – tool for country situation analysis for improvements HIV diagnosis and building on patient monitoring – consolidate from diagnosis, treatment to viral suppression. Provides guidance on HIV case definitions Key population data – confidentiality and security are paramount. In most settings patient monitoring should not include KP category, guidance on issues around KP data

15 key recommendations (continued) Promote and use unique identifiers with anonymous codes for sharing of data within and across the national HIV and health programme Transition progressively from paper to electronic information systems – countries should used a tiered approach for transition starting with high volume sites Strengthen and establish different data security levels – differentiate security levels for data elements and invest in robust databases and policies to strengthen security Invest in data systems and ensure interoperability – strengthen investments and security of data systems, with recommended 5-10% of program budget on M&E Use individual data to improve programmes and long term chronic health care Strengthen retention and transfer by sharing information between clinics Ensure linkage by supporting routine sharing between testing, treatment, lab, pharmacy and other health service programs Strengthen integration with long-term chronic health care by using unique identifiers Invest in data analyst capacity: central and district analysis team and routine, simple dashboards to feed back data in real time for programme improvement

Conclusions – the data 90s Global Impact – 90% of fast track programs evaluated causatively for impact on incidence and mortality, using data and some modeling District: 90% of countries have routine, real time district data on testing, treatment and viral load with analyst capacity to feed back to programs Individual M&E: 90% of patients covered by robust, secure patient monitoring and case surveillance from testing to outcomes Combination prevention, care and data is primary public health package