Association of telemedicine for remote monitoring of intensive care patients with mortality, complications, and length of stay

JAMA

Volumn 302, Issue 24, 2009, Pages 2671-2678

  Thomas, Eric J ^a,b   Lucke, Joseph F ^a   Wueste, Laura ^a,b   Weavind, Lisa ^a   Patel, Bela ^a  

^a UNIVERSITY OF TEXAS MEDICAL SCHOOL   (United States)

^b UNIVERSITY OF TEXAS   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; ARTICLE; CRITICALLY ILL PATIENT; DISEASE SEVERITY; FEMALE; HUMAN; INTENSIVE CARE; LENGTH OF STAY; MAJOR CLINICAL STUDY; MALE; MORTALITY; OBSERVATIONAL STUDY; OUTCOME ASSESSMENT; PATIENT MONITORING; PRIORITY JOURNAL; SURVIVAL RATE; TELEMEDICINE; TELEMONITORING; UNITED STATES; CLINICAL TRIAL; CRITICAL ILLNESS; EMPIRICAL RESEARCH; HOSPITALIZATION; INTENSIVE CARE UNIT; METHODOLOGY; MIDDLE AGED; MULTICENTER STUDY; STATISTICS; TELEMETRY;

ADULT; AGED; CRITICAL ILLNESS; EMPIRICAL RESEARCH; FEMALE; HOSPITAL MORTALITY; HUMANS; INTENSIVE CARE; INTENSIVE CARE UNITS; LENGTH OF STAY; MALE; MIDDLE AGED; SEVERITY OF ILLNESS INDEX; TELEMEDICINE; TELEMETRY;

EID: 73949116486     PISSN: 00987484     EISSN: 15383598     Source Type: Journal    
DOI: 10.1001/jama.2009.1902     Document Type: Article

References (23)

1. Chalfin DB, Cohen L, Lambrinos J. The economics and cost-effectiveness of critical care medicine. Intensive Care Med. 1995;21(11):952-961.
2. Pronovost PJ, Miller M, Dorman T, Berenholtz S, Rubin H. Developing and implementing measures of quality of care in the intensive care unit. Curr Opin Crit Care. 2001;7(4):297-303.
3. Pronovost PJ, Angus DC, Dorman T, Robinson K, Dremsizov T, Young T. Physician staffing patterns and clinical outcomes in critically ill patients: a systematic review. JAMA. 2002;288(17):2151-2162.
4. Young M, Birkmeyer J. Potential reduction in mortality rates using an intensivist model to manage intensive care units. Eff Clin Pract. 2000;6:284-289.
5. Angus DC, Kelley M, Schmitz R, White A, Popovich JJ Jr; Committee on Manpower for Pulmonary and Critical Care Societies (COMPACCS). Caring for the critically ill patient: current and projected workforce requirements for care of the critically ill and patients with pulmonary disease: can we meet the requirements of an aging population? JAMA. 2000;284(21):2762-2770.
6. Breslow MJ, Rosenfeld BA, Doerfler M, et al. Effect of a multiple-site intensive care unit telemedicine program on clinical and economic outcomes: an alternative paradigm for intensivist staffing. Crit Care Med. 2004;32(1):31-38.
7. New England Healthcare Institute. Tele-ICUs: Remote Management in Intensive Care Units. Cambridge: Massachusetts Technology Collaborative and Health Technology Center; 2007.
8. Tang Z, Weavind L, Mazabob J, Thomas EJ, Chu-Weininger M, Johnson TR. Workflow in intensive care unit remote monitoring: a time-and-motion study. Crit Care Med. 2007;35(9):2057-2063.
9. Le Gall JR, Lemeshow S, Saulnier F. A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study. JAMA. 1993;270(24):2957-2963.
10. Jung SH, Kang SH, Ahn C. Sample size calculations for clustered binary data. Stat Med. 2001;20(13):1971-1982.
11. Hoenig JM, Heisey DM. The abuse of power: the pervasive fallacy of power calculations for data analysis. Am Stat. 2001;55:19-24.
12. Kollef MH. Ventilator-associated pneumonia: a multivariate analysis. JAMA. 1993;270(16):1965-1970.
13. Loader C. Local Regression and Likelihood. New York, NY: Springer; 1999.
14. Little RJA, Rubin DB. Statistical Analysis With Missing Data. New York, NY: John Wiley & Sons; 2002.
15. Bozdogan H. Model selection and the Akaike information criterion (AIC): the general theory and its analytical extensions. Psychometrika. 1987;52(3):345-370.
16. Gelman A, Hill J. Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge, UK: Cambridge University Press; 2007.
17. R Development Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2008.
18. Lapsley M, Ripley BD. RODBC: ODBC Database Access. R package version 1.2-3; 2008.
19. James D, Hornik K. Chron: Chronological objects which can handle dates and times. R package version 2.3-23; 2008.
20. Venables WN, Ripley BD. Modern Applied Statistics With S. 4th ed. New York, NY: Springer; 2002.
21. Bates D, Maechler M. lme4: Linear mixed-effects models using S4 classes. R package version 0.999375-31, 2009.
22. Leisch F. Sweave: dynamic generation of statistical reports using literate data analysis. In: Härdle W, Rönz B, eds. Compstat 2002 - Proceedings in Computational Statistics. Heidelberg, Germany: Physica Verlag; 2002:575-580.
23. Pronovost P, Needham D, Berenholtz S, et al. An intervention to decrease catheter-related bloodstream infections in the ICU. N Engl J Med. 2006;355(26):2725-2732.