Universal Health Coverage—Big Thinking versus Big Data
Jan 1, 2013, 00:00
10.1016/j.jval.2012.10.016
https://www.valueinhealthjournal.com/article/S1098-3015(12)04170-8/fulltext
Title :
Universal Health Coverage—Big Thinking versus Big Data
Citation :
https://www.valueinhealthjournal.com/action/showCitFormats?pii=S1098-3015(12)04170-8&doi=10.1016/j.jval.2012.10.016
First page :
S1
Section Title :
Editorial
Open access? :
No
Section Order :
11
These days we hear a lot about “big data” and how comparative effectiveness research (CER) is going to help us make better decisions (big data refers in the health care context to longitudinal medical claims data for millions of patients linked to their electronic health records). Most of us working in pharmacoeconomics and outcomes research rely on data—both randomized and observational—to generate and assess evidence with the aim of supporting better decision making about resource allocation. Most articles in Value in Health are research or methodology articles: the number of policy articles is very limited. My quick search for “universal health coverage” (UHC) found only 11 citations in the journal, but none focusing on UHC. The articles in this special supplement, based on a conference held at Bocconi University in Milan, Italy, earlier this year, remind us that there are large and important policy issues that rely on “big thinking”—with less hard evidence—to understand and try to reform what is going on in health systems and health policy. Nonetheless, as we often emphasize to others, decisions will have to be made—with or without good information—and making no decision is itself a choice.
Categories :
- Coverage with Evidence Development & Adaptive Pathways
- Health Disparities & Equity
- Health Policy & Regulatory