District team problem solving as an approach to district health programme planning: a review, and survey of its status in selected districts in Indonesia.

District team problem solving (DTPS) was developed by WHO in the 1980s to explicitly engage local stakeholders in decentralized planning and, in later iterations, budgeting of health services. It became WHO's global flagship approach to district-level health priority-setting and planning. DTPS entails multisectoral stakeholders (the team) using local data to prioritize and fund services, and should enhance capacity in management of decentralized healthcare. From the late 1990s, DTPS evolved through several phases in Indonesia. Multiple donors supported its use for planning maternal and child health (MCH) services, with substantive national government input, despite no formal assessment of its sustained uptake or benefits. In the context of new interest to promote DTPS for MCH in Indonesia, we assessed its status there in 2013-14, focussing on its implementation status and on associated MCH data collection (PWS-KIA). We used mixed methods to capture local challenges to and opportunities for DTPS in seven sub-national locations in 6 of Indonesia's 31 provinces. DTPS remained active only in the two locations whose local government ever allocated funds to the process; in the others, it stopped once the initial non-government funding ceased. An official decree establishing DTPS and team membership was only issued in four locations, and it was not evident that the intended multisectoral representation was achieved in any site. Trained DTPS facilitators remained available in only four locations. In all districts, interviewees described PWS-KIA as potentially serving a revived DTPS, but insufficiently robust to underwrite local advocacy for investment in MCH. Although efforts to introduce DTPS as a uniform approach to district MCH planning in Indonesia have not been sustained, strong commitment to evidence-based planning remains. Decentralized health planning processes require quality data, local government buy-in and associated funding, and should link explicitly to broader administrative planning processes and budget cycles.