This document provides guidance on the integrated analysis and use, at national level, of data collected from health facilities though routine health information systems (RHIS). The integrated approach provides general health service planners and managers with an overarching or “cross-cutting” view of health services, based on a limited set of tracer indicators that represent multiple health programmes and service components. Objectives: The guidance will promote an understanding of: the concept of integrated analysis of health services, using RHIS data; the advantages of using a limited set of standardized indicators and visualizations; analysis and presentation of the data in ways that are easily understood and useful to health service planners and managers; the importance of and approaches to assessing data quality; some considerations for interpretation of RHIS data. Target audience: This guidance targets workers in ministries of health as well as other organizations, including: decision-makers using RHIS data for general planning, management and review of health services; programme staff wanting to share key programme findings with a general audience; staff responsible for the analysis and presentation of health data, including analysts and monitoring and evaluation officers; health information systems staff involved in data management and data quality improvement staff of national health observatories; research institutes and academic institutions involved in RHIS data.

This document provides guidance on the integrated analysis and use, at district and facility levels, of data collected from health facilities through routine health information systems (RHIS). The guidance includes a sample set of indicators, with recommended ways of visualizing these indicators in standard dashboards, as well as guidance on interpretation and use of the indicators. Objectives: The guidanceillustrates integrated analysis of RHIS data at district and facility levels. It aims to build understanding and skills in a recommended analytic approach that: focuses on a minimum set of indicators organized into three cross-cutting groups; uses standard visualizations to facilitate data interpretation: charts and tables organized into integrated dashboards that can be automatically updated in an electronic database; supports use of dashboards for decision-making as part of district meetings, supervision visits and feedback to health facilities. Target audience: This guidance targets managers and analysts at the level of the district health system. It may also be useful to staff making operational decisions at any subnational level. The guidance may also be useful to implementing partners, donors, academics and others involved in using data to strengthen health service delivery at subnational levels.

The routine health information system (RHIS) is an integral part of the overall national health information system (HIS). RHIS collects health service data directly from the health facilities, where they are produced regularly by the healthcare workers and community health workers.

"This reference set provides a complete understanding of the development of applications and concepts in clinical, patient, and hospital information systems"--Provided by publisher.

This training package aims to improve the quality of routine health facility data through building capacity in the monthly use of District Health Information Software (DHIS)2-based data quality (DQ) tools at district level. The package includes tutorials with related exercises and uses a website (https://who-demos.dhis2.org/dq) to demonstrate the tools.

This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.