Allen J. Flynn

Loop Movement and Catalysis in Creatine Kinase

Recently the crystal structure of creatine kinase from Torpedocalifornica was determined to 2.1 Å. The dimeric structure revealed two different forms in the unit cell: one monomer was bound to a substrate, MgADP, and the other monomer was bound to a transition‐state analogue complex composed of MgADP, nitrate and creatine. The most striking difference between the structures is the movement of two loops (comprising residues 60 ‐ 70 and residues 323 ‐ 333) into the active site in the transition state structure. This loop movement effectively occludes the active site from solvent, and the loops appear to be locked into place by a salt bridge formed between His66 and Asp326. His66 is of particular interest as it is located within a PGHP motif conserved in all creatine kinases but not found in other guanidino kinases. We have carried out alanine‐scanning mutagenesis of each of the residues in the PGHP motif and determined that only the His66 plays a significant role in the creatine kinase reaction. Although neither residue interacts directly with the substrate, the interaction His66 and Asp326 appears to be important in providing the precise alignment of substrates necessary for phosphoryl group transfer. Finally, it is clear that neither His66 nor Asp326 are responsible for the pKs observed in the pH‐rate profile for HMCK. IUBMB Life, 57: 355‐362, 2005

The science of Learning Health Systems: Foundations for a new journal

Department of Learning Health Sciences, Medical School, University of Michigan, Ann Arbor, Michigan Taubman Health Sciences Library, University Library and Department of Learning Health Sciences, Medical School, University of Michigan, Ann Arbor, Michigan Medical Informatics and Decision Making, Imperial College, London, UK Medical Informatics, Tempus and Kanter Health Foundation, Chicago, Illinois Department of Computer Science, School of Engineering and Applied Science, University of Virginia, Charlottesville, Virginia Correspondence Charles P. Friedman, PhD, Department of Learning Health Sciences, Medical School, University of Michigan, Ann Arbor, MI 48109. Email: cpfried@umich.edu

Clinical decision support for atypical orders: detection and warning of atypical medication orders submitted to a computerized provider order entry system.

The specificity of medication-related alerts must be improved to overcome the pernicious effects of alert fatigue. A systematic comparison of new drug orders to historical orders could improve alert specificity and relevance. Using historical order data from a computerized provider order entry system, we alerted physicians to atypical orders during the prescribing of five medications: calcium, clopidogrel, heparin, magnesium, and potassium. The percentage of atypical orders placed for these five medications decreased during the 92 days the alerts were active when compared to the same period in the previous year (from 0.81% to 0.53%; p=0.015). Some atypical orders were appropriate. Fifty of the 68 atypical order alerts were over-ridden (74%). However, the over-ride rate is misleading because 28 of the atypical medication orders (41%) were changed. Atypical order alerts were relatively few, identified problems with frequencies as well as doses, and had a higher specificity than dose check alerts.

The need for collaborative engagement in creating clinical decision-support alerts.

Clinical decision support (CDS) encompasses a broad array of technology and approaches, all of which involve the provision and use of clinical information in medical processes. [1][1] Medication-focused CDS is frequently used in the context of inpatient computerized prescriber order entry (CPOE) and

Opportunity cost of pharmacists’ nearly universal prospective order review

Dollars can only be spent once. The value of the next-best, but forfeited, alternative purchase is called the opportunity cost. Opportunity costs apply to scarce resources including work time. To minimize opportunity costs for work time, we prioritize. We are to provide pharmaceutical care, which is

ASHP Guidelines on the Design of Database-Driven Clinical Decision Support: Strategic Directions for Drug Database and Electronic Health Records Vendors.

ASHP believes that use of clinical decision support (CDS) tools can make patient care more efficient and effective.[1][1] Currently available pharmacotherapy CDS systems are not as effective as they need to be at helping all practice settings achieve the goal of safe and effective pharmacotherapy.

The Knowledge Object Reference Ontology (KORO): A formalism to support management and sharing of computable biomedical knowledge for learning health systems

Health systems are challenged by care underutilization, overutilization, disparities, and related harms. One problem is a multiyear latency between discovery of new best practice knowledge and its widespread adoption. Decreasing this latency requires new capabilities to better manage and more rapidly share biomedical knowledge in computable forms. Knowledge objects package machine‐executable knowledge resources in a way that easily enables knowledge as a service. To help improve knowledge management and accelerate knowledge sharing, the Knowledge Object Reference Ontology (KORO) defines what knowledge objects are in a formal way.

Pharmacists’ requirement for continuity of the clinical narrative in the electronic medical record

Continuity of patient care documentation is an established electronic medical record (EMR) requirement for health-system pharmacists.[1][1] EMRs should be designed and implemented in ways that ensure the completeness of each patient’s longitudinal, online clinical narrative.[2][2] A complete EMR

Architecture and Initial Development of a Digital Library Platform for Computable Knowledge Objects for Health

Throughout the world, biomedical knowledge is routinely generated and shared through primary and secondary scientific publications. However, there is too much latency between publication of knowledge and its routine use in practice. To address this latency, what is actionable in scientific publications can be encoded to make it computable. We have created a purpose-built digital library platform to hold, manage, and share actionable, computable knowledge for health called the Knowledge Grid Library. Here we present it with its system architecture.

Tell it Like it Seems: Challenges Identifying Potential Requirements of a Learning Health System

This paper provides a review of some previously identified requirements of a learning health system, a post hoc analysis of narrative artifacts describing a learning health system, and some new potential requirements of a learning health system. Engaging a transdisciplinary group of researchers and health care practitioners, we used a method of group conceptualization to elicit potential requirements of a learning health system. Several unresolved challenges of creating and using narrative stories, diagrams and storyboards to elicit and share the potential requirements of a learning health system amongst a diverse group of researchers are discussed.