Knowledge of and perceived need for evidence-based education about antipsychotic medications among nursing home leadership and staff.

Background/objectives: Antipsychotic use is common in US nursing homes, despite evidence of increased risk of morbidity and mortality, and limited efficacy in older adults with dementia. Knowledge, attitudes, and beliefs regarding antipsychotic use among nursing home staff are unclear. The study aim was to describe nursing home leadership and direct care staff members' knowledge of antipsychotic risks, beliefs and attitudes about the effectiveness of antipsychotics and nonpharmacologic management of dementia-related behaviors, and perceived need for evidence-based training about antipsychotic medication safety.

Validation of anaphylaxis in the Food and Drug Administration's Mini-Sentinel.

Purpose: We aim to develop and validate the positive predictive value (PPV) of an algorithm to identify anaphylaxis using health plan administrative and claims data. Previously published PPVs for anaphylaxis using International Classification of Diseases, ninth revision, Clinical Modification (ICD-9-CM) codes range from 52% to 57%.

Methods: We conducted a retrospective study using administrative and claims data from eight health plans.

Validation of acute myocardial infarction in the Food and Drug Administration's Mini-Sentinel program.

Purpose: To validate an algorithm based upon International Classification of Diseases, 9(th) revision, Clinical Modification (ICD-9-CM) codes for acute myocardial infarction (AMI) documented within the Mini-Sentinel Distributed Database (MSDD).

Methods: Using an ICD-9-CM-based algorithm (hospitalized patients with 410.x0 or 410.

Design for validation of acute myocardial infarction cases in Mini-Sentinel.

Purpose: 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.