There are complex informatics issues involved in using HIT to improve delivery of care for aging patients with multiple comorbidities. A recent topic of interest in developing practice guidelines is consideration of patients with multiple medical conditions, an increasingly important issue as the population ages and many guidelines are developed for the management of a single disease. This session will discuss approaches to the informatics challenges to the management of patients with multiple morbidities.

Patient-centered care calls for coordinating recommendations for the patient across multiple comorbidities, while taking account of patient preferences and prognoses for both life expectancy and also other patient-important outcomes such as mobility and functional status. Challenges and opportunities abound in developing new architectures to enable interaction of multiple disease guidelines and standardization of relevant patient data.

Implicit in the vision for Personalized Genomic Medicine is that Genomic and other Omic (e.g. proteomic, metabolomics, etc.) data will need to be integrated into the Electronic Health Records (EHRs) of the future. Omic data breaks the conventional EHR paradigm in a number of ways. The greatest paradigm shifts is that next-generation sequencing allows the collection of large amount of data about a patient, before the clinical significance of that data is known. Another shift is that the raw data are essentially uninterruptable without the aid of computer analysis, even for a domain expert. The multiple comorbidities of most elderly patients and the interactions among the treatments for these conditions further complicate the picture. A number of groups, including the The Electronic Medical Records and Genomics (eMERGE) Network, the Pharmacogenomics Research Network (PGRN) and the HL7 Clinical Genomics Workgroup, as well as individual EHR vendors, are tackling these challenge. This talk will discuss both the challenges and the progress that has already been made in incorporation high throughput Omics into clinical care.

Practice guidelines represent an important knowledge resource for diminishing inappropriate practice variation. But most guidelines are developed for the management of a single disease, rather than for people with several diseases. Combining such guideline recommendations sometimes leads to conflicting recommendations for care. Clinical trials, which serve as the highest quality evidence sources for practice guidelines often eliminate multiple morbidity patients. Might large clinical databases that include information about patients with multiple morbidities over time serve as a preferable knowledge source for developing practice guidelines?