Patient condition is a key element in communication between clinicians. However, there is no generally accepted definition of patient condition that is independent of diagnosis and that spans acuity levels. We report the development and validation of a continuous measure of general patient condition that is independent of diagnosis, and that can be used for medical-surgical as well as critical care patients. A survey of Electronic Medical Record data identified common, frequently collected non-static candidate variables as the basis for a general, continuously updated patient condition score. We used a new methodology to estimate in-hospital risk associated with each of these variables. A risk function for each candidate input was computed by comparing the final pre-discharge measurements with 1-year post-discharge mortality. Step-wise logistic regression of the variables against 1-year mortality was used to determine the importance of each variable. The final set of selected variables consisted of 26 clinical measurements from four categories: nursing assessments, vital signs, laboratory results and cardiac rhythms. We then constructed a heuristic model quantifying patient condition (overall risk) by summing the single-variable risks. The model's validity was assessed against outcomes from 170,000 medical-surgical and critical care patients, using data from three US hospitals. Outcome validation across hospitals yields an area under the receiver operating characteristic curve(AUC) of ≥0.92 when separating hospice/deceased from all other discharge categories, an AUC of ≥0.93 when predicting 24-h mortality and an AUC of 0.62 when predicting 30-day readmissions. Correspondence with outcomes reflective of patient condition across the acuity spectrum indicates utility in both medical-surgical units and critical care units. The model output, which we call the Rothman Index, may provide clinicians with a longitudinal view of patient condition to help address known challenges in caregiver communication, continuity of care, and earlier detection of acuity trends.

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An ultralow power analog CMOS chip and a silicon based microelectrode array have been fully integrated to a microminiaturized "neuroport" for brain implantable neuroengineering applications. The CMOS integrated circuit (IC) includes preamplifier and multiplexing circuitry, and a hybrid flip-chip bonding technique was developed to fabricate a functional, encapsulated microminiaturized neuroprobe device. Our neuroport has been evaluated using various methods, including pseudospike detection and local excitation measurement, and showed suitable characteristics for recording neural activities. As a proof-of-concept demonstration, we have measured local field potentials from thalamocortical brain slices of rats, suggesting that the new neuroport can form a prime platform for the development of a microminiaturized neural interface to the brain in a single implantable unit. An alternative power delivery scheme using photovoltaic power converter, and an encapsulation strategy for chronic implantation are also discussed.

This approach yields good to excellent discriminatory performance among adult inpatients for predicting sepsis present on admission or developed within the hospital and may aid in the timely delivery of care.