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National Resource Center for Health IT

Research and Projects: AHRQ THQIT and SRD Portfolio

Massachusetts

EMS Based TIPI-IS Cardiac Care QI-Error Reduction System

Description:  Implements the time-insensitive predictive instruments built into the computerized electrocardiograph in emergency medical service settings and emergency departments; also evaluates its impact on reducing errors and avoidable delays in emergency care.

Abstract:  DESCRIPTION (provided by the applicant): Key to saving lives of patients with acute cardiac ischemia (ACI: including acute myocardial infarction [AMI] and unstable angina pectoris [UAP]) is the timeliness of treatment, a major focus of emergency medical service (EMS) systems and emergency departments (EDs). Time is especially critical for patients with evolving electrocardiogram (ECG) ST elevation MI (STEMI), for whom coronary reperfusion therapy (CRT), i.e., thrombolytic therapy (TT) and primary percutaneous transluminal coronary angioplasty (PTCA), can be life-saving, if given promptly. EMS personnel have an appreciation of the importance of time and identification of patients who need acute CRT, but unlike in hospitals, EMS settings have not had requirements for, nor the growth of, quality-improvement (QI) and error-reduction systems. Based on a system we have implemented in hospitals, we propose to implement and demonstrate a cardiac care medical error-reduction/QI system in EMS systems, targeting time to treatment for ACI/STEMI. Our approach to Ql/error reduction is based on the use of time-insensitive predictive instruments (TIPIs) built into the tool used in the first evaluation of the patient with suspected ACI, the computerized electrocardiograph. These electrocardiographs provide the 0-100 percent predicted probabilities of key diagnoses or outcome by printing them on the ECG to aid the clinician's real-time decision-making. The ACI-TIPI computes a patient's probability of having ACI and the thrombolytic predictive instrument (TPI), the probabilities of key CRT outcomes. Also, these probabilities can be saved in a TLPI information system (TIPI-IS) database to be used to generate retrospective reports for feedback. These will be used to target lapses in timeliness of treatment of ACI/STEMI by EMS and receiving hospitals' EDs. Partnering with the country's largest ambulance company (AMR) and largest EMS electrocardiograph manufacturer (Medtronic), and EMS systems and receiving hospitals in Brockton and Springfield (urban and rural settings), Massachusetts, we aim to implement and measure the impact of this EMS cardiac care Ql/error-reduction system on the occurrence of errors and avoidable delays in EMS care and in use of CRT for STEMI in hospitals. As we have done in ED settings, using a before-after time-series quasi-experimental design, we intend to demonstrate the usefulness of an EMS TIPI-IS cardiac Ql/error-reduction system for care for EMS patients with symptoms suggestive of ACI and for the use of CRT for patients with STEMI. Also, based on detailed assessment of user and organizational barriers and incentives for using the system, and intentional transfer of the system's operations and data collection processes to the EMS and hospital sites, we intend that the project make significant steps toward the wider adoption of the approach.

Year 1 Funding:  $500,000

Estimated Total Funding:  $1,499,998

Principal Investigator:  Harry Selker

Applicant Institution:  New England Medical Center

City/Town:  Boston, Massachusetts

State:  Massachusetts

Grant Number:  UC1 HS15124

Category:  Implementation Grants (THQIT)

Thesaurus Terms:  computer assisted medical decision making, emergency care, emergency service, health care quality, myocardial ischemia /hypoxia, patient care management, patient safety /medical error, angina pectoris, computer assisted diagnosis, cooperative study, cost effectiveness, early diagnosis, electrocardiography, heart disorder diagnosis, myocardial infarction, behavioral /social science research tag, clinical research, health services research tag, human subject

Project Start Date:  Sep 30, 2004

Project End Date:  Sep 29, 2007

 
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