before ecd can be used for analysis , they must first be prepared so that they accurately represent the health risks and outcomes of the patients studied , as well as the care provided by health care system .
davis and colleagues report on a retrospective observational study in veterans with rheumatoid arthritis to validate diagnostic and procedural codes for identification of acute cardiovascular events . beyond the specific population and set of outcomes in this example ,
reimer and madigan demonstrate how the development of a fully integrated medical transport record for patients undergoing medical transport  as an example  will offer the ability to address complex questions related to patients clinical outcomes in a real - world clinical setting while providing an electronic data infrastructure that can enable high - quality , clinically rich , prospective , and multisite data collection to support cer .
stuart and colleagues outline the challenges in estimating causal effects using electronic health data generally , and offer some solutions , with particular attention to propensity score methods .
the methods are illustrated with a case study showing how medicare and medicaid administrative data can be used to estimate the effect of the medicare part d prescription drug program among individuals with serious mental illness .
zurovac and colleagues demonstrate how the concept of multifactorial experiments , drawn from the evaluation literature , offers promise for cer with ehrs .
they examine some of the unique aspects of such missing data , present some statistical advice about how to handle these issues , and provide some suggested areas for future methodological research . a more specific challenge in using ecd
is that observations are not scheduled as they would be in a designed randomized clinical trial , but rather occur at irregular intervals coincident with patient visits , which potentially depend on outcomes .
luo and colleagues show how discrete - time hidden markov models can be used to estimate transition rates in this context , using chronic kidney disease as an example .
a final paper in this issue provides an example of how methods for preparing and analyzing ecd can come together to enable rigorous cer .
written in the form of a protocol for a prospective , longitudinal cohort study , sills and colleagues demonstrate how survey methodologies and secondary analysis of existing structured clinical , administrative , and claims data can be used to estimate the effects of patient - centered medical home characteristics on asthma control in adults and children .
the setting for this research is the scalable architecture for federated translational inquiries network ( saftinet ) , an ahrq - funded safety net - oriented practice - based research network , which is designed to measure these variations in delivery system characteristics .
as useful as they are , these papers only begin to address the methodological developments needed to advance the national dialogue on the use of ecd to conduct cer , support qi , and generally to improve outcomes in a learning health care system .
these papers offer a beginning snapshot of some critical ideas and innovations shaping the field .
egems remains interested in publishing researcher perspectives on methodological challenges resulting from using ecd and lessons learned from facing these challenges , and welcomes future methods - related submissions to our general issue . for more information on submitting papers
i encourage you to read the papers in this collection and think about whether your organization has developed similar approaches  or radical alternatives  and write about them .
you might also try some of the approaches discussed here , and let us know how they work out .
we are particularly interested in papers that address key topics raised in prior edm forum discussions , including strategies for evaluating and addressing missing data and other data quality issues ; analytic strategies that can account for granular temporal or spatial information ; and new , rigorous methodological approaches to maximizing the use of  big data  to generate new evidence and determine what works best for whom and under what conditions .
 whether one reads computerworld or institute of medicine issue briefs , it s clear that most now accept the idea that existing electronic clinical data ( ecd ) and other health records can be used to manage and improve the processes , outcomes , and the quality of health care . 
 indeed the increasing popularity of the term  learning healthcare system  signals the broad acceptance of the idea that routinely collected clinical data can  indeed should  
 be used to advance knowledge and support continuous learning . but despite what the big data enthusiasts say , none of this is easy without the appropriate analytical methods.this commentary introduces the seven papers in egems second special issue , which are the result of invitations to researchers who have participated in edm forum activities as well as an open call for paper in early summer 2013 . 
 these papers offer a beginning snapshot of the ways innovative thinkers across the country are developing methodology to advance the national dialogue on the use of ecd to conduct cer , support qi , and generally to improve outcomes in a learning healthcare system . 