Measuring the incidence of hospital-acquired complications and their effect on length of stay using CHADx

Medical Journal of Australia

Volumn 199, Issue 8, 2013, Pages 543-547

  Trentino, Kevin M ^a   Swain, Stuart G ^a   Burrows, Sally A ^b   Sprivulis, Peter C ^c   Daly, Frank F S ^a  

^a WA Department of Health   (Australia)

^b UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

^c UNIVERSITY OF WESTERN AUSTRALIA   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; ARTICLE; AUTOMATION; CARDIOVASCULAR DISEASE; CLASSIFICATION OF HOSPITAL ACQUIRED DIAGNOSES; COMPLICATION; CONTROLLED STUDY; CROSS-SECTIONAL STUDY; FEMALE; HOSPITAL ACQUIRED COMPLICATION; HOSPITAL MANAGEMENT; HOSPITAL PATIENT; HUMAN; IATROGENIC DISEASE; INCIDENCE; LABOR COMPLICATION; LENGTH OF STAY; MAJOR CLINICAL STUDY; MALE; OUTCOME ASSESSMENT; PATIENT SAFETY; RETROSPECTIVE STUDY;

ADULT; AGED; CROSS-SECTIONAL STUDIES; DIAGNOSIS-RELATED GROUPS; FEMALE; HUMANS; IATROGENIC DISEASE; INCIDENCE; INTERNATIONAL CLASSIFICATION OF DISEASES; LENGTH OF STAY; MALE; MIDDLE AGED; RETROSPECTIVE STUDIES; RISK FACTORS; SEX FACTORS;

EID: 84886068122     PISSN: 0025729X     EISSN: 13265377     Source Type: Journal    
DOI: 10.5694/mja12.11640     Document Type: Article

References (24)

1. Jackson TJ, Michel JL, Roberts RF, et al. A classification of hospital-acquired diagnoses for use with routine hospital data. Med J Aust 2009; 191: 544-548
2. Australian Commission on Safety and Quality in Health Care. Classification of Hospital Acquired Diagnoses (CHADx). http://www.safetyandquality.gov.au/wpcontent/ uploads/2010/01/35566-CHADx.pdf (accessed Dec 2010).
3. Rivard PE, Luther SL, Christiansen CL, et al. Using patient safety indicators to estimate the impact of potential adverse events on outcomes. Med Care Res Rev 2008; 65: 67-87
4. Carey K, Stefos T. Measuring the cost of hospital adverse patient safety events. Health Econ 2011; 20: 1417-1430
5. Shreve J, Van Den Bos J, Gray T, et al. The economic measurement of medical errors. Schaumburg, Ill: Society of Actuaries, 2010. http://www.soa.org/research/researchprojects/ health/research-econ-measurement.aspx (accessed Oct 2013).
6. Van Den Bos J, Rustagi K, Gray T, et al. The $17.1 billion problem: the annual cost of measurable medical errors. Health Aff (Millwood) 2011; 30: 596-603
7. Jackson T, Nghiem HS, Rowell DS, et al. Marginal costs of hospital acquired conditions: information for priority-setting for patient safety programmes and research. J Health Serv Res Policy 2011; 16: 141-146
8. Classen DC, Pestotnik SL, Evans RS, et al. Adverse drug events in hospitalized patients. Excess length of stay, extra costs, and attributable mortality. JAMA 1997; 277: 301-306
9. Herwaldt LA, Cullen JJ, Scholz D, et al. A prospective study of outcomes, healthcare resource utilization, and costs associated with postoperative nosocomial infections. Infect Control Hosp Epidemiol 2006; 27: 1291-1298
10. Dimick JB, Chen SL, Taheri PA, et al. Hospital costs associated with surgical complications: a report from the private-sector National Surgical Quality Improvement Program. J Am Coll Surg 2004; 199: 531-537
11. Swain S, Trentino K. Developing an abstract model for implementing the CHADx classification system. http://www.safetyandquality.gov.au/our-work/informationstrategy/ health-information-standards/classification-of-hospital-acquireddiagnoses-chadx (accessed Feb 2013).
12. Michel JL, Cheng D, Jackson TJ. Comparing the coding of complications in Queensland and Victorian admitted patient data. Aust Health Rev 2011; 35: 245-252
13. Sundararajan V, Henderson TM, Perry C, et al. New ICD-10 version of the Charlson comorbidity index predicted in-hospital mortality. J Clin Epidemiol 2004; 57: 1288-1294
14. Ehsani JP, Jackson T, Duckett SJ. The incidence and cost of adverse events in Victorian hospitals 2003-04. Med J Aust 2006; 184: 551-555
15. Layde PM, Meurer LN, Guse C, et al. Medical injury identification using hospital discharge data. In: Henricksen K, Battles JB, Marks E, Lewin DI, editors. Advances in patient safety: from research to implementation. Volume 2: Concepts and methodology. Rockville, Md: Agency for Healthcare Research and Quality, 2005: 119-132
16. Zhan C, Miller MR. Excess length of stay, charges, and mortality attributable to medical injuries during hospitalization. JAMA 2003; 290: 1868-1874
17. Browning RM, Trentino K, Nathan EA, Hashemi N; Western Australian Patient Blood Management Program. Preoperative anaemia is common in patients undergoing major gynaecological surgery and is associated with a fivefold increased risk of transfusion. Aust N Z J Obstet Gynaecol 2012; 52: 455-459
18. Meurer JR, Meurer LN, Grube J, et al. Combining performance feedback and evidence-based educational resources. In: Henricksen K, Battles JB, Marks E, Lewin DI, editors. Advances in patient safety: from research to implementation. Volume 4: Programs, tools, and products. Rockville, Md: Agency for Healthcare Research and Quality, 2005: 237-252
19. Centers for Medicare and Medicaid Services. Hospital-acquired conditions (HAC) in acute inpatient prospective payment system (IPPS) hospitals [fact sheet]. Baltimore, Md: CMS, 2012. https://www.cms.gov/HospitalAcqCond/downloads/ HACFactsheet.pdf (accessed Oct 2013).
20. Independent Hospital Pricing Authority. Literature review: efficiency, international best practice in ABF and future payment reform. http://www.ihpa.gov.au/internet/ihpa/publishing.nsf/Content/future-payment-reform (accessed Feb 2013).
21. Performance Unit, South Metropolitan Health Service. Patient blood management program: reducing anaemia, transfusions and length of stay for knee patients. 2012. https://www.healthroundtable.org/News.aspx (accessed Feb 2013).
22. O'Leary KJ, Devisetty VK, Patel AR, et al. Comparison of traditional trigger tool to data warehouse based screening for identifying hospital adverse events. BMJ Qual Saf 2013; 22: 130-138
23. Stevenson KB, Khan Y, Dickman J, et al. Administrative coding data, compared with CDC/NHSN criteria, are poor indicators of health care-associated infections. Am J Infect Control 2008; 36: 155-164
24. Weingart SN, Iezzoni LI, Davis RB, et al. Use of administrative data to find substandard care: validation of the complications screening program. Med Care 2000; 38: 796-806.