title: Design for validation of acute myocardial infarction cases in Mini-Sentinel.
abstract: OBJECTIVE
  To describe the acute myocardial infarction (AMI) validation project, a test case for health outcome validation within the US Food and Drug Administration-funded Mini-Sentinel pilot program.
  
  
  METHODS
  The project consisted of four parts: (i) case identification-developing an algorithm based on the International Classification of Diseases, Ninth Revision, to identify hospitalized AMI patients within the Mini-Sentinel Distributed Database; (ii) chart retrieval-establishing procedures that ensured patient privacy (collection and transfer of minimum necessary amount of information, and redaction of direct identifiers to validate potential cases of AMI); (iii) abstraction and adjudication-trained nurse abstractors gathered key data using a standardized form with cardiologist adjudication; and (iv) calculation of the positive predictive value of the constructed algorithm.
  
  
  RESULTS
  Key decision points included (i) breadth of the AMI algorithm, (ii) centralized versus distributed abstraction, and (iii) approaches to maintaining patient privacy and to obtaining charts for public health purposes. We used an algorithm limited to International Classification of Diseases, Ninth Revision, codes 410.x0-410.x1. Centralized data abstraction was performed because of the modest number of charts requested (<155). The project's public health status accelerated chart retrieval in most instances.
  
  
  CONCLUSIONS
  We have established a process to validate AMI within Mini-Sentinel, which may be used for other health outcomes. Challenges include the following: (i) ensuring that only minimum necessary data are transmitted by Data Partners for centralized chart review, (ii) establishing procedures to maintain data privacy while still allowing for timely access to medical charts, and (iii) securing access to charts for public health uses that do not require approval from an institutional review board while maintaining patient privacy.
authors.affiliation: Fallon Community Health Plan and Fallon Clinic, Meyers Primary Care Institute, University of Massachusetts Medical School, Worcester, MA, USA. Sarah.cutrona@umassmemorial.org
authors.forename: Sarah L
authors.initials: SL
authors.lastname: Cutrona
authors.forename: Sengwee
authors.initials: S
authors.lastname: Toh
authors.forename: Aarthi
authors.initials: A
authors.lastname: Iyer
authors.forename: Sarah
authors.initials: S
authors.lastname: Foy
authors.forename: Elizabeth
authors.initials: E
authors.lastname: Cavagnaro
authors.forename: Susan
authors.initials: S
authors.lastname: Forrow
authors.forename: Judith A
authors.initials: JA
authors.lastname: Racoosin
authors.forename: Robert
authors.initials: R
authors.lastname: Goldberg
authors.forename: Jerry H
authors.initials: JH
authors.lastname: Gurwitz
mesh_terms: D000465:Algorithms; D003219:Confidentiality; D016208:Databases, Factual / Q000706:statistics & numerical data; D006801:Humans; D038801:International Classification of Diseases; D009203:Myocardial Infarction / Q000453:epidemiology*; D017063:Outcome Assessment, Health Care / Q000379:methods*; D010865:Pilot Projects; D011237:Predictive Value of Tests; D013997:Time Factors; D014481:United States / Q000453:epidemiology; D014486:United States Food and Drug Administration