title: An algorithmic computerised order entry approach to assist in the prescribing of new therapeutic agents: case study of activated protein C at an academic medical centre.
abstract: BACKGROUND
  Academic medical centres face the need to care for patients with complex medical conditions, educate physicians-in-training and conduct research, all with increasingly constrained budgets. The adoption of new therapeutic technology presents challenges and opportunities in each of these areas. Severe sepsis remains a major cause of morbidity and mortality, especially in tertiary-care facilities. Recombinant human activated protein C reduces mortality in patients with severe sepsis, but trial data indicate that the benefit of the drug is confined to the more seriously ill patients, while the risk of bleeding complications can be considerable. The cost of the drug is approximately USD 6000-8000 per treated patient. Integration of this product into routine care has produced unique challenges concerning clinical decision making, safety and cost.
  
  
  OBJECTIVE
  To describe one hospital's multidisciplinary approach to the adoption of this new medication.
  
  
  METHODS
  Before activated protein C was approved for use, Brigham and Women's Hospital (BWH) convened a working group to formulate clinical guidelines proactively. This new agent did not fit into an obvious therapeutic category but cut across multiple clinical disciplines requiring the involvement of several hospital departments in developing policy. As new data on efficacy emerged during the US FDA review of the drug, the working group had to devise a method for using the available information to assist clinical decision making while placing appropriate restrictions on the use of activated protein C. The goal was to make accurate information available to guide ordering physicians' decision making interactively, 24 hours a day.
  
  
  RESULTS
  The committee developed a utilisation policy for activated protein C that provided guidance on patient selection, contraindications and risk stratification. Interactive computer-based order entry screens were developed to guide physicians through a complex set of clinical criteria to ensure appropriate evidence-based use. A careful review of contraindications is required as a second step. To risk stratify patients in accordance with the trial subset analyses and the FDA labelling guidelines, ordering physicians are guided in calculating an APACHE II (Acute Physiology and Chronic Health Evaluation) score for the patient. Physicians from several specialties are available for advice and consultation on patients with difficult or controversial conditions. Approximately two-thirds of completed orders passed the clinical algorithm; an additional 35% of patients did not meet the medication criteria but received the drug after the attending physician requested an override of the guidelines.
  
  
  CONCLUSIONS
  The BWH approach to activated protein C used an innovative multidisciplinary approach and computer-assisted order entry to guide clinical use of a new agent with substantial clinical efficacy, risks and costs. This approach provides a model for strategies to deal with other new and complex medical technologies.
authors.affiliation: Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02120, USA. mfischer@partners.org
authors.forename: Michael A
authors.initials: MA
authors.lastname: Fischer
authors.forename: Craig M
authors.initials: CM
authors.lastname: Lilly
authors.forename: William W
authors.initials: WW
authors.lastname: Churchill
authors.forename: Lindsey R
authors.initials: LR
authors.lastname: Baden
authors.forename: Jerry
authors.initials: J
authors.lastname: Avorn
mesh_terms: D000046:Academic Medical Centers; D000465:Algorithms; D006801:Humans; D033183:Interdisciplinary Communication; D050316:Medical Order Entry Systems / Q000191:economics / Q000592:standards* / Q000639:trends; D008510:Medication Systems, Hospital / Q000592:standards / Q000706:statistics & numerical data / Q000639:trends; D017410:Practice Guidelines as Topic; D011486:Protein C / Q000627:therapeutic use*; D015203:Reproducibility of Results
chemical_list: D011486:Protein C