The future of outcomes measurement: item banking,tailored short-forms,and computerized adaptive assessment

The use of item banks and computerized adaptive testing (CAT) begins with clear definitions of important outcomes, and references those definitions to specific questions gathered into large and well-studied pools, or “banks” of items. Items can be selected from the bank to form customized short scales, or can be administered in a sequence and length determined by a computer programmed for precision and clinical relevance. Although far from perfect, such item banks can form a common definition and understanding of human symptoms and functional problems such as fatigue, pain, depression, mobility, social function, sensory function, and many other health concepts that we can only measure by asking people directly. The support of the National Institutes of Health (NIH), as witnessed by its cooperative agreement with measurement experts through the NIH Roadmap Initiative known as PROMIS (www.nihpromis.org), is a big step in that direction. Our approach to item banking and CAT is practical; as focused on application as it is on science or theory. From a practical perspective, we frequently must decide whether to re-write and retest an item, add more items to fill gaps (often at the ceiling of the measure), re-test a bank after some modifications, or split up a bank into units that are more unidimensional, yet less clinically relevant or complete. These decisions are not easy, and yet they are rarely unforgiving. We encourage people to build practical tools that are capable of producing multiple short form measures and CAT administrations from common banks, and to further our understanding of these banks with various clinical populations and ages, so that with time the scores that emerge from these many activities begin to have not only a common metric and range, but a shared meaning and understanding across users. In this paper, we provide an overview of item banking and CAT, discuss our approach to item banking and its byproducts, describe testing options, discuss an example of CAT for fatigue, and discuss models for long term sustainability of an entity such as PROMIS. Some barriers to success include limitations in the methods themselves, controversies and disagreements across approaches, and end-user reluctance to move away from the familiar.     

Prospective Cohort Study of Enterotoxigenic Escherichia coli Infections in Argentinean Children

In a follow-up study, enterotoxigenic Escherichia coli (ETEC) infections in 145 children from two communities located in northeastern Argentina were monitored for 2 years. The occurrence of diarrhea was monitored by weekly household visits. Of 730 fecal specimens collected, 137 (19%) corresponded to diarrheal episodes. ETEC was isolated from a significantly higher proportion of symptomatic (18.3%) than asymptomatic (13.3%) children (P = 0.04541). Individuals of up to 24 months of age were found to have a higher risk of developing ETEC diarrhea than older children (odds ratio [OR], 3.872; P = 0.00021). When the toxin profiles were considered, only heat stable enterotoxin (ST)-producing ETEC was directly associated with diarrhea (P = 0.00035). Fifty-five percent of the ETEC isolated from symptomatic children and 19% of the ETEC isolated from asymptomatic children expressed one of the colonization factors (CFs) investigated, i.e., CF antigen I (CFA/I), CFA/II, CFA/III, and CFA/IV; coli surface antigens CS7 and CS17; and putative CFs PCFO159, PCFO166, and PCFO20, indicating a clear association between diarrhea and ETEC strains that carry these factors (P = 0.0000034). The most frequently identified CFs were CFA/IV (16%), CFA/I (10%), and CS17 (9%). CFs were mostly associated with ETEC strains that produce ST and both heat-labile enterotoxin and ST. Logistic regression analysis, applied to remove confounding effects, revealed that the expression of CFs was associated with illness independently of the toxin type (OR, 4.81; P = 0.0003). When each CF was considered separately, CS17 was the only factor independently associated with illness (OR, 16.6; P = 0.0151). Most CFs (the exception was CFA/IV) fell within a limited array of serotypes, while the CF-negative isolates belonged to many different O:H types. These results demonstrate that some CFs are risk factors for the development of ETEC diarrhea.