What questions about the health system keep you awake at night?
Maybe: Who isn’t receiving quality services? What drives system costs up? What treatments are the most effective for the population, and which ones should be discontinued? How do we get patients to attend their follow-up appointments? What works and what doesn’t in national health care?
Whatever the question, the right data can both provide answers (and hopefully keep you from losing sleep) and help make more impactful decisions.
A DT’s core contribution is providing the right information to the right people at the right time so they can take action. This includes each step of the process. Without the right information, policy designs and national health practices will be ineffective, or even catastrophic in crisis situations.
The IDB report Detect, Prevent, Respond, and Recover Digitally: Evidence from Applying Digital Interventions in Past and Present Public Health Emergencies and Considerations for the Future describes how information was the most frequent challenge during interventions in public health emergencies like Ebola, cholera, MERS, and COVID-19 outbreaks. The study identified 3 specific kinds of shortcomings: lack of quality and reliable data, communication barriers, and decisions based on insufficient information.
“If you do not know how to ask the right question, you discover nothing.”
- William Edwards Deming -
These challenges are not limited to pandemic situations. Informationrelated challenges persist, with serious consequences for the region. For example, many national information systems still do not identify people by their name or identification number. Others lack interoperability, creating silos of duplicated data that is often poor quality. Also, the available data is frequently only used for reporting, not to make decisions about patient care, management processes, or information policies. This creates a vicious cycle of information that is poor quality because it isn’t used and information that isn’t used because it is poor quality.
State of Bahia Health Command and Control Centrer
The starting point for improvements
Designing informed health policy begins with asking questions about the problem to be solved and the needs of other key strategies like continuous quality improvement or results-based management. Without the right questions, the data collected cannot effectively inform decisions.
When the right questions about the challenges and needs are clear, the digital infrastructure and tools can be used to collect, process, exchange, and apply information to enhance the health system’s efficiency and quality, and also make it learn. In other words, it can enable a system where knowledge generation practices are integrated into daily work to constantly improve care. Tools in this dimension include, for example, business intelligence dashboards; data repositories for statistics, analysis, and research; big data; and open-data tools.
Several LAC countries, including Uruguay and Argentina have created online knowledge centers for digital transformation that share content, experiences, and implementation guidelines for the national ecosystem. The PAHO portal Knowledge Management and Access to Health Information in the Americas offers technical information on policies, programs, and official documents; statistics and metrics from the scientific output of the main bibliographic databases; and trainings and workshops. Some countries have also created data analytics units to maximize the practical usefulness of the information collected. One example is the work done by the Information Management Area of the public health subsystem of the City of Buenos Aires on health information management.
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To have a real impact on decisionmaking, these tools need to be aligned with a health analysis strategy for decision-making. Under the PAHO’s IS4H model, such strategy requires a systematic approach to assessing health needs and making essential information accessible, as well as advanced analytical techniques to support policy, management, and clinical decisions in real time.
Actions in other dimensions of the model for digitally transforming health, like people and culture and governance, are key to ensuring that health professionals have the skills and incentives they need to interpret and use data at all levels of the system, and that citizens have access to and are trained on using the data to improve their own Only available in Spanish. health.
The following additional resources give more information and tools for achieving informed health policy and practice:
- From Information To Intelligence: How To Adapt Institutions For Data Analysis In Government? This publication describes different models for, and experiences of, public sector data analysis units.
- Detect, Prevent, Respond, Recover Digitally: Evidence from Applying Digital Interventions to Past and Present for Future Public Health Emergencies. This document describes how technology was used to respond to past emergencies like Ebola, MERS, and SARS.
- The IDB’s National Maturity Model for EHR. This tool helps measure systems’ maturity level in terms of using information from electronic health records to make decisions and perform other tasks
- The PAHO’s Maturity Model for Information Systems for Health. This tool measures a country’s level of maturity in managing digital health information
- Learning Health Systems: Pathways to progress. This WHO publication analyzes how we learn at the individual, team, and organizational level; why we need health systems that learn from themselves; and how to build a system that will do this.