Mortality Benefits of Antibiotic Computerised Decision Support System: Modifying Effects of Age

Angela L P Chow, David C Lye, Onyebuchi A Arah, Angela L P Chow, David C Lye, Onyebuchi A Arah

Abstract

Antibiotic computerised decision support systems (CDSSs) are shown to improve antibiotic prescribing, but evidence of beneficial patient outcomes is limited. We conducted a prospective cohort study in a 1500-bed tertiary-care hospital in Singapore, to evaluate the effectiveness of the hospital's antibiotic CDSS on patients' clinical outcomes, and the modification of these effects by patient factors. To account for clustering, we used multilevel logistic regression models. One-quarter of 1886 eligible inpatients received CDSS-recommended antibiotics. Receipt of antibiotics according to CDSS's recommendations seemed to halve mortality risk of patients (OR 0.54, 95% CI 0.26-1.10, P = 0.09). Patients aged ≤65 years had greater mortality benefit (OR 0.45, 95% CI 0.20-1.00, P = 0.05) than patients that were older than 65 (OR 1.28, 95% CI 0.91-1.82, P = 0.16). No effect was observed on incidence of Clostridium difficile (OR 1.02, 95% CI 0.34-3.01), and multidrug-resistant organism (OR 1.06, 95% CI 0.42-2.71) infections. No increase in infection-related readmission (OR 1.16, 95% CI 0.48-2.79) was found in survivors. Receipt of CDSS-recommended antibiotics reduced mortality risk in patients aged 65 years or younger and did not increase the risk in older patients. Physicians should be informed of the benefits to increase their acceptance of CDSS recommendations.

Figures

Figure 1. Joint effects of age and…
Figure 1. Joint effects of age and receipt of ARUSC recommendations on 30-day all-cause mortality risk.

References

    1. Jacob J. T. & Gaynes R. P. Emerging trends in antibiotic use in US hospitals: quality, quantification and stewardship. Expert Rev. Anti Infect. Ther. 8, 893–902 (2010).
    1. Davey P. et al. Interventions to improve antibiotic prescribing practices for hospital inpatients. Cochrane Database Syst. Rev. 4, CD003543 (2013).
    1. Polk R. E., Fox C., Mahoney A., Letcavage J. & MacDougall C. Measurement of Adult Antibacterial Drug Use in 130 US Hospitals: Comparison of Defined Daily Dose and Days of Therapy. Clin. Infect. Dis. 44, 664–670 (2007).
    1. Ohl C. A. & Luther V. P. Antimicrobial stewardship for inpatient facilities. J. Hosp. Med. 6, S4–S15 (2011).
    1. World Health Organization, WHO Global Strategy for Containment of Antimicrobial Resistance. (2001) (Date of access: 22/05/2015).
    1. Livermore D. M. Minimising antibiotic resistance. Lancet Infect. Dis. 5, 450–459 (2005).
    1. Van de Sande-Bruinsma N. et al. Antimicrobial Drug Use and Resistance in Europe. Emerg. Infect. Dis. 14, 1722–1730 (2008).
    1. World Health Organization, Antimicrobial resistance: global report on surveillance 2014. (2014) (Date of access: 22/05/2015).
    1. Tamma P. D. & Cosgrove S. E. Antimicrobial stewardship. Infect. Dis. Clin. North Am. 25, 245–260 (2011).
    1. Teng C. B. et al. Guidelines for antimicrobial stewardship training and practice. Ann. Acad. Med. Singapore 41, 29–34 (2012).
    1. Duane T. M. et al. Surgeons do not listen: evaluation of compliance with antimicrobial stewardship program recommendations. Am. Surg. 79, 1269–1272 (2013).
    1. Evans R. S. et al. A computer-assisted management program for antibiotics and other antiinfective agents. N. Engl. J. Med. 338, 232–238 (1998).
    1. Paul M. et al. Improving empirical antibiotic treatment using TREAT, a computerized decision support system: cluster randomized trial. J. Antimicrob. Chemother. 58, 1238–1245 (2006).
    1. Thursky K. A. et al. Reduction of Broad-Spectrum Antibiotic Use with Computerized Decision Support in an Intensive Care Unit. Int. J. Qual. Health Care 18, 224–231 (2006).
    1. Steurbaut K. et al. COSARA: Integrated Service Platform for Infection Surveillance and Antibiotic Management in the ICU. J. Med. Syst. 36, 3765–3775 (2012).
    1. Ng T. M. et al. An interactive, point-of-care, computerised antibiotic prescription decision support system and quality of antibiotic prescription in the management of complicated urinary tract infection. J. Glob. Antimicrob. Resist. 2, 127–128 (2014).
    1. Zaidi S. T. R. & Marriott J. L. Barriers and Facilitators to Adoption of a Web-based Antibiotic Decision Support System. South. Med Rev. 5, 42–50 (2012).
    1. Sintchenko V., Coiera E. & Gilbert G. L. Decision support systems for antibiotic prescribing. Curr. Opin. Infect. Dis. 21, 573–579 (2008).
    1. Fijn R., Chow M.-C., Schuur P. M. H., De Jong-Van den Berg L. T. W. & Brouwers J. R. B. J. Multicentre evaluation of prescribing concurrence with anti-infective guidelines: epidemiological assessment of indicators. Pharmacoepidemiol. Drug Saf. 11, 361–372 (2002).
    1. Menéndez R. et al. Compliance with guidelines-recommended processes in pneumonia: impact of health status and initial signs. PloS One 7, e37570 (2012).
    1. Evans R. S., Classen D. C., Pestotnik S. L., Lundsgaarde H. P. & Burke J. P. Improving Empiric Antibiotic Selection Using Computer Decision Support. Arch. Intern. Med. 154, 878–884 (1994).
    1. Jr J. E. M. Antimicrobial Stewardship—the State of the Art in 2011: Focus on Outcome and Methods. Infect. Control Hosp. Epidemiol. 33, 331–337 (2012).
    1. Chow A. L., Lye D. C. & Arah O. A. Patient and physician predictors of patient receipt of therapies recommended by a computerized decision support system when initially prescribed broad-spectrum antibiotics: a cohort study. J. Am. Med. Inform. Assoc. ocv120 (2015), doi: 10.1093/jamia/ocv120.
    1. Fridkin S. et al. Vital signs: improving antibiotic use among hospitalized patients. MMWR Morb. Mortal. Wkly. Rep. 63, 194–200 (2014).
    1. McDonald L. C. et al. Recommendations for surveillance of Clostridium difficile-associated disease. Infect. Control Hosp. Epidemiol. Off. J. Soc. Hosp. Epidemiol. Am. 28, 140–145 (2007).
    1. Paterson D. L. & Doi Y. A step closer to extreme drug resistance (XDR) in gram-negative bacilli. Clin. Infect. Dis. Off. Publ. Infect. Dis. Soc. Am. 45, 1179–1181 (2007).
    1. Charlson M. E., Pompei P., Ales K. L. & MacKenzie C. R. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J. Chronic Dis. 40, 373–383 (1987).
    1. Quan H. et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med. Care 43, 1130–1139 (2005).
    1. Mol P. G. M. et al. Limited effect of patient and disease characteristics on compliance with hospital antimicrobial guidelines. Eur. J. Clin. Pharmacol. 62, 297–305 (2006).
    1. Snijders T. A. B. & Bosker R. J. Multilevel Analysis. An Introduction to Basic and Advanced Multilevel Modeling. (SAGE Publications, 2012).
    1. Rubin D. B. Estimating causal effects from large data sets using propensity scores. Ann. Intern. Med. 127, 757–763 (1997).
    1. Braitman L. E. & Rosenbaum P. R. Rare outcomes, common treatments: analytic strategies using propensity scores. Ann. Intern. Med. 137, 693–695 (2002).
    1. Cole S. R., Chu H. & Greenland S. Multiple-imputation for measurement-error correction. Int. J. Epidemiol. 35, 1074–1081 (2006).
    1. McGregor J. C. et al. Impact of a Computerized Clinical Decision Support System on Reducing Inappropriate Antimicrobial Use A Randomized Controlled Trial. J. Am. Med. Inform. Assoc. 13, 378–384 (2006).
    1. Sintchenko V., Iredell J. R., Gilbert G. L. & Coiera E. Handheld computer-based decision support reduces patient length of stay and antibiotic prescribing in critical care. J. Am. Med. Inform. Assoc. JAMIA 12, 398–402 (2005).
    1. Nachtigall I. et al. Long-term effect of computer-assisted decision support for antibiotic treatment in critically ill patients: a prospective ‘before/after’ cohort study. BMJ Open 4, e005370 (2014).
    1. Tafelski S. et al. Computer-assisted Decision Support for Changing Practice in Severe Sepsis and Septic Shock. J. Int. Med. Res. 38, 1605–1616 (2010).
    1. Chow A., Lye D. C. B. & Arah O. A. Psychosocial determinants of physicians’ acceptance of recommendations by antibiotic computerised decision support systems: A mixed methods study. Int. J. Antimicrob. Agents 45, 295–304 (2015).
    1. Leibovici L., Kariv G. & Paul M. Long-term survival in patients included in a randomized controlled trial of TREAT, a decision support system for antibiotic treatment. J. Antimicrob. Chemother. 68, 2664–2666 (2013).
    1. Shebl N. A., Franklin B. D. & Barber N. Clinical decision support systems and antibiotic use. Pharm. World Sci. PWS 29, 342–349 (2007).
    1. Carling P., Fung T., Ann Killion R., Terrin N. & Barza M. Favorable Impact of a Multidisciplinary Antibiotic Management Program Conducted During 7 Years. Infect. Control Hosp. Epidemiol. 24, 699–706 (2003).

Source: PubMed

Sponsoren und Mitarbeiter

Krankheiten

Drogeninterventionen

3
Abonnieren