Int J Qual Health Care-2001-Rubin-469-74

On the other hand implementing process measures can

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: ed into routine clinical data collection also provide a constant educational reminder to clinicians about the correct process, and eliminate duplicative data collection for quality assessment. On the other hand, implementing process measures can be difficult because they require constant updating as the science of medicine advances. Joint efforts among providers, professional societies, and external government or payer agencies 3. Donabedian A. Evaluating quality of medical care. Millbank Q 1996; 44: 166–206. 4. Lohr KN, Schroeder SA. A strategy for quality assurance in Medicare. N Engl J Med 1990; 322: 1161–1171. 5. Palmer RH, Miller MR. Methodologic challenges in developing and implementing measures of quality of child health care. Ambul Pediatr 2001; 1: 39–52. 6. Palmer RH. Using health outcomes data to compare plans, networks, and providers. Int J Qual Health Care 1998; 10: 477–483. 8. Berwick DM, Wald DL. Hospital leaders’ opinions of the HCFA mortality data. J Am Med Assoc 1990; 263: 247–249. 9. Jollis JG, Romano PS. Pennsylvania’s focus on heart attack— grading the scorecard. N Engl J Med 1998; 338: 983–987. 10. Hannan EL, Kilburn H, Racz M, Shields E, Chassin MR. Improving the outcomes of coronary artery bypass graft mortality in New York State. J Am Med Assoc 1995; 273: 209–213. 11. Green J, Wintfeld N. Report cards on cardiac surgeons; assessing New York State’s approach. N Engl J Med 1995; 332: 1229–1232. 12. Rainwater JA, Romano PS, Antonius DM. The California Hospital Outcomes Project: How useful is California’s report card for quality improvement? Jt Comm J Qual Improv 1998; 24: 31–39. 13. National Committee on Quality Assurance, USA: http:// www.ncqa.org. Note: website address at time of printing. 14. Jencks SF, Cuerdon T, Burwen DR et al. Quality of medical 473 H. R. Rubin et al. care delivered to Medicare beneficiaries: A profile at state and national levels. J Am Med Assoc 2000; 284: 1670–1676. 15. Rosenthal GE, Hammar PJ, Way LE et al. Using hospital performance data in quality improvement: The Cleveland Health Quality Choice experience. Jt Comm J Qual Improv 1998; 24: 347–360. 16. The Leapfrog Group, USA: http://www.leapfroggroup.com. Note: website address at time of printing. 19. Angus DC, Clermont G, Kramer DJ et al. Short-term and long-term outcome prediction with the Acute Physiologic and Chronic Health Evaluation II system after orthotopic liver transplantation. Crit Care Med 2000; 28: 150–156. 20. Clermont G, Angus DC, Dirusso SM et al. Predicting hospital mortality for patients in the intensive care unit: A comparison of artificial neural networks with logistic regression models. Crit Care Med 2001; 29: 291–296. 17. Pronovost PJ, Jenckes M, Dorman T et al. Organizational characteristics of intensive care units related to outcomes of abdominal aortic surgery. J Am Med Assoc 1999; 281: 1310–1317. 18. McGlynn EA. Choosing and evaluating clinical performance measures. Jt Comm J Qual Improv 1998; 24: 470–479. 474 Accepted for publication 28 September 2001...
View Full Document

This document was uploaded on 03/09/2014 for the course ACC 301 at HELP University.

Ask a homework question - tutors are online