Using present-on-admission coding to improve exclusion rules for quality metrics: The case of failure-to-rescue

Medical Care

Volumn 51, Issue 8, 2013, Pages 722-730

  Needleman, Jack ^a,b   Buerhaus, Peter I ^c   Vanderboom, Catherine ^d   Harris, Marcelline ^e  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

^d MAYO CLINIC   (United States)

^e UNIVERSITY OF MICHIGAN   (United States)

Author keywords

failure to rescue; mortality rates; outcomes research; patient safety indicators; quality of care

Indexed keywords

ARTICLE; CODING; CONTROLLED STUDY; GOLD STANDARD; HOSPITAL ADMISSION; HOSPITAL DISCHARGE; HUMAN; MORTALITY; NURSING STAFF; PREDICTION; PRIORITY JOURNAL; REGISTERED NURSE; RESCUE PERSONNEL; RISK; SENSITIVITY AND SPECIFICITY; UNITED STATES; UNIVERSITY HOSPITAL;

HOSPITAL BED CAPACITY; HOSPITAL MORTALITY; HUMANS; INSURANCE CLAIM REVIEW; INTERNATIONAL CLASSIFICATION OF DISEASES; NURSING STAFF, HOSPITAL; PATIENT ADMISSION; QUALITY INDICATORS, HEALTH CARE; QUALITY OF HEALTH CARE; RISK ADJUSTMENT; UNITED STATES; UNITED STATES AGENCY FOR HEALTHCARE RESEARCH AND QUALITY;

EID: 84880748701     PISSN: 00257079     EISSN: 15371948     Source Type: Journal    
DOI: 10.1097/MLR.0b013e31829808de     Document Type: Article

References (26)

1. Silber JH, Williams SV, Krakauer H, et al. Hospital and patient characteristics associated with death after surgery. A study of adverse occurrence and failure to rescue. Med Care. 1992;30:615-629.
2. Silber JH, Rosenbaum PR, Schwartz JS, et al. Evaluation of the complication rate as a measure of quality of care in coronary-artery bypass graft-surgery. JAMA. 1995;274:317-323.
3. Silber JH, Rosenbaum PR, Ross RN. Comparing the contributions of groups of predictors-which outcomes vary with hospital rather than patient characteristics. J Am Stat Assoc. 1995;90:7-18.
4. Silber JH, Rosenbaum PR, Williams SV, et al. The relationship between choice of outcome measure and hospital rank in general surgical procedures: implications for quality assessment. Int J Qual Health Care. 1997;9:193-200.
5. Silber JH, Romano PS, Rosen AK, et al. Failure-to-rescue: comparing definitions to measure quality of care. Med Care. 2007;45:918-925.
6. Needleman J, Buerhaus P, Mattke S, et al. Nurse-staffing levels and quality of care in hospitals. N Engl J Med. 2002;346:1415-1422.
7. Needleman J, Buerhaus PI. Failure-to-rescue: comparing definitions to measure quality of care. Med Care. 2007;45:913-915.
8. Iezzoni LI, Daley J, Foley SM, et al. Screening Quality of Care Using Administrative Data. Rockville, MD: Agency for Health Care Policy and Research; 1992.
9. Iezzoni LI, Daley J, Heeren T, et al. Using administrative data to screen hospitals for high complication rates. Inquiry. 1994;31:40-55.
10. Iezzoni LI, Daley J, Heeren T, et al. Identifying complications of care using administrative data. Med Care. 1994;32:700-715.
11. Ball J, Elixhauser A, Johantgen M, et al. HCUP Quality Indicators, Methods, Version 1.1: Outcome, Utilization, and Access Measures for Quality Improvement. Rockville, MD: Agency for Health Care Policy and Research; 1998.
12. 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.
13. McDonald KM, Davies SM, Geppert J, et al. Why rescue the administrative data version of the "failure to rescue" quality indicator. Med Care. 2007;45:277-279.
14. Moriarty JP, Finnie DM, Johnson MG, et al. Do pre-existing complications affect the failure to rescue quality measures? Qual Saf Health Care. 2010;19:65-68.
15. Ballentine NH. Coding and documentation: Medicare severity diagnosis- related groups and present-on-admission documentation. J Hosp Med. 2009;4:124-130.
16. Hughes JS, Averill RF, Goldfield NI, et al. Identifying potentially preventable complications using a present on admission indicator. Health Care Finance Rev. 2006;27:63-82.
17. Pine M, Fry DE, Jones B, et al. Screening algorithms to assess the accuracy of present-on-admission coding. Perspect Health Inf Manag. 2009;6:2.
18. Houchens RL, Elixhauser A, Romano PS. How often are potential patient safety events present on admission? Jt Comm J Qual Patient Saf.. 2008;34:154-163.
19. Leibson CL, Needleman J, Buerhaus P, et al. Identifying in-hospital venous thromboembolism (VTE): a comparison of claims-based approaches with the Rochester Epidemiology Project VTE cohort. Med Care. 2008;46:127-132.
20. Agency for Healthcare Research and Quality. Patient safety indicators download, AHRQ quality indicators. 2007. Available at: http://www. qualityindicators.ahrq.gov/Modules/psi-resources.aspx. Accessed March 10, 2009.
21. Agency for Healthcare Research and Quality. Patient Safety Indicators: technical specifications, AHRQ quality indicators. 2007. Available at: http://www.qualityindicators.ahrq.gov/Downloads/Modules/PSI/V31/ psi-technical-specs-v31.pdf. Accessed February 15, 2013.
22. Needleman J, Buerhaus P, Mattke S, et al. Nurse Staffing and Patient Outcomes in Hospitals. Boston, MA: Harvard School of Public Health; 2001.
23. Harless DW, Mark BA. Addressing measurement error bias in nurse staffing research. Health Serv Res. 2006;41:2006-2024.
24. Spetz J. The effects of managed care and prospective payment on the demand for hospital nurses: evidence from California. Health Serv Res. 1999;34:993-1010.
25. Agency for Healthcare Research and Quality. Patient safety indicators overview. 2011. Available at: http://www.qualityindicators.ahrq.gov/Modules/psi- overview.aspx. Accessed March 17, 2012.
26. Elixhauser A, Steiner C, Harris DR, et al. Comorbidity measures for use with administrative data. Med Care. 1998;36:8-27. Initiative