Literature DB >> 27805795

Piloting electronic medical record-based early detection of inpatient deterioration in community hospitals.

Gabriel J Escobar1,2, Benjamin J Turk3, Arona Ragins3, Jason Ha4, Brian Hoberman5, Steven M LeVine6, Manuel A Ballesca7, Vincent Liu3,8, Patricia Kipnis9.   

Abstract

Patients who deteriorate in the hospital outside the intensive care unit (ICU) have higher mortality and morbidity than those admitted directly to the ICU. As more hospitals deploy comprehensive inpatient electronic medical records (EMRs), attempts to support rapid response teams with automated early detection systems are becoming more frequent. We aimed to describe some of the technical and operational challenges involved in the deployment of an early detection system. This 2-hospital pilot, set within an integrated healthcare delivery system with 21 hospitals, had 2 objectives. First, it aimed to demonstrate that severity scores and probability estimates could be provided to hospitalists in real time. Second, it aimed to surface issues that would need to be addressed so that deployment of the early warning system could occur in all remaining hospitals. To achieve these objectives, we first established a rationale for the development of an early detection system through the analysis of risk-adjusted outcomes. We then demonstrated that EMR data could be employed to predict deteriorations. After addressing specific organizational mandates (eg, defining the clinical response to a probability estimate), we instantiated a set of equations into a Java application that transmits scores and probability estimates so that they are visible in a commercially available EMR every 6 hours. The pilot has been successful and deployment to the remaining hospitals has begun. Journal of Hospital Medicine 2016;11:S18-S24.
© 2016 Society of Hospital Medicine. © 2016 Society of Hospital Medicine.

Entities:  

Mesh:

Year:  2016        PMID: 27805795      PMCID: PMC5510649          DOI: 10.1002/jhm.2652

Source DB:  PubMed          Journal:  J Hosp Med        ISSN: 1553-5592            Impact factor:   2.960


  21 in total

1.  Rethinking rapid response teams.

Authors:  Eugene Litvak; Peter J Pronovost
Journal:  JAMA       Date:  2010-09-22       Impact factor: 56.272

2.  Matching methods for causal inference: A review and a look forward.

Authors:  Elizabeth A Stuart
Journal:  Stat Sci       Date:  2010-02-01       Impact factor: 2.901

3.  Rapid response teams--walk, don't run.

Authors:  Bradford D Winters; Julius Pham; Peter J Pronovost
Journal:  JAMA       Date:  2006-10-04       Impact factor: 56.272

4.  Methods for evaluating changes in health care policy: the difference-in-differences approach.

Authors:  Justin B Dimick; Andrew M Ryan
Journal:  JAMA       Date:  2014-12-10       Impact factor: 56.272

5.  Adverse outcomes associated with delayed intensive care unit transfers in an integrated healthcare system.

Authors:  Vincent Liu; Patricia Kipnis; Norman W Rizk; Gabriel J Escobar
Journal:  J Hosp Med       Date:  2011-10-28       Impact factor: 2.960

6.  Unplanned transfers to a medical intensive care unit: causes and relationship to preventable errors in care.

Authors:  Srinivas R Bapoje; Jennifer L Gaudiani; Vignesh Narayanan; Richard K Albert
Journal:  J Hosp Med       Date:  2010-12-13       Impact factor: 2.960

7.  Risk-adjusting hospital inpatient mortality using automated inpatient, outpatient, and laboratory databases.

Authors:  Gabriel J Escobar; John D Greene; Peter Scheirer; Marla N Gardner; David Draper; Patricia Kipnis
Journal:  Med Care       Date:  2008-03       Impact factor: 2.983

8.  Automated detection of physiologic deterioration in hospitalized patients.

Authors:  R Scott Evans; Kathryn G Kuttler; Kathy J Simpson; Stephen Howe; Peter F Crossno; Kyle V Johnson; Misty N Schreiner; James F Lloyd; William H Tettelbach; Roger K Keddington; Alden Tanner; Chelbi Wilde; Terry P Clemmer
Journal:  J Am Med Inform Assoc       Date:  2014-08-27       Impact factor: 4.497

9.  Risk-adjusting hospital mortality using a comprehensive electronic record in an integrated health care delivery system.

Authors:  Gabriel J Escobar; Marla N Gardner; John D Greene; David Draper; Patricia Kipnis
Journal:  Med Care       Date:  2013-05       Impact factor: 2.983

10.  Identifying patients at increased risk for unplanned readmission.

Authors:  Elizabeth H Bradley; Olga Yakusheva; Leora I Horwitz; Heather Sipsma; Jason Fletcher
Journal:  Med Care       Date:  2013-09       Impact factor: 2.983

View more
  28 in total

1.  Computer-aided National Early Warning Score to predict the risk of sepsis following emergency medical admission to hospital: a model development and external validation study.

Authors:  Muhammad Faisal; Donald Richardson; Andrew J Scally; Robin Howes; Kevin Beatson; Kevin Speed; Mohammed A Mohammed
Journal:  CMAJ       Date:  2019-04-08       Impact factor: 8.262

2.  Ensuring Fairness in Machine Learning to Advance Health Equity.

Authors:  Alvin Rajkomar; Michaela Hardt; Michael D Howell; Greg Corrado; Marshall H Chin
Journal:  Ann Intern Med       Date:  2018-12-04       Impact factor: 25.391

3.  Contemporary Risk Factors and Outcomes of Transfusion-Associated Circulatory Overload.

Authors:  Nareg H Roubinian; Jeanne E Hendrickson; Darrell J Triulzi; Jerome L Gottschall; Michael Michalkiewicz; Dhuly Chowdhury; Daryl J Kor; Mark R Looney; Michael A Matthay; Steven H Kleinman; Donald Brambilla; Edward L Murphy
Journal:  Crit Care Med       Date:  2018-04       Impact factor: 7.598

4.  Design and Implementation of a Pediatric ICU Acuity Scoring Tool as Clinical Decision Support.

Authors:  Eric Shelov; Naveen Muthu; Heather Wolfe; Danielle Traynor; Nancy Craig; Christopher Bonafide; Vinay Nadkarni; Daniela Davis; Maya Dewan
Journal:  Appl Clin Inform       Date:  2018-08-01       Impact factor: 2.342

5.  Prediction of Recurrent Clostridium Difficile Infection Using Comprehensive Electronic Medical Records in an Integrated Healthcare Delivery System.

Authors:  Gabriel J Escobar; Jennifer M Baker; Patricia Kipnis; John D Greene; T Christopher Mast; Swati B Gupta; Nicole Cossrow; Vinay Mehta; Vincent Liu; Erik R Dubberke
Journal:  Infect Control Hosp Epidemiol       Date:  2017-08-24       Impact factor: 3.254

Review 6.  Machine Learning and Artificial Intelligence in Neurocritical Care: a Specialty-Wide Disruptive Transformation or a Strategy for Success.

Authors:  Fawaz Al-Mufti; Michael Kim; Vincent Dodson; Tolga Sursal; Christian Bowers; Chad Cole; Corey Scurlock; Christian Becker; Chirag Gandhi; Stephan A Mayer
Journal:  Curr Neurol Neurosci Rep       Date:  2019-11-13       Impact factor: 5.081

7.  Machine Learning and Prediction in Medicine - Beyond the Peak of Inflated Expectations.

Authors:  Jonathan H Chen; Steven M Asch
Journal:  N Engl J Med       Date:  2017-06-29       Impact factor: 91.245

8.  Automated Identification of Adults at Risk for In-Hospital Clinical Deterioration.

Authors:  Gabriel J Escobar; Vincent X Liu; Alejandro Schuler; Brian Lawson; John D Greene; Patricia Kipnis
Journal:  N Engl J Med       Date:  2020-11-12       Impact factor: 91.245

9.  Effect of a Real-Time Electronic Dashboard on a Rapid Response System.

Authors:  Grant S Fletcher; Barry A Aaronson; Andrew A White; Reena Julka
Journal:  J Med Syst       Date:  2017-11-20       Impact factor: 4.460

10.  Hospital-Acquired Pressure Injury: Risk-Adjusted Comparisons in an Integrated Healthcare Delivery System.

Authors:  June Rondinelli; Stephen Zuniga; Patricia Kipnis; Lina Najib Kawar; Vincent Liu; Gabriel J Escobar
Journal:  Nurs Res       Date:  2018 Jan/Feb       Impact factor: 2.381

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.