Maximising the value of hospital administrative datasets

Australian Health Review

Volumn 34, Issue 2, 2010, Pages 216-223

  Nadathur, Shyamala G ^a  

^a MONASH UNIVERSITY   (Australia)

Author keywords

Access; Administrative data; And evaluation; Casemix; Data collection; Health care quality; Health services administration; Health services research; Hospital administration; Hospital information systems; Information management; Information storage and retrieval; Morbidity; Mortality; Patient care

Indexed keywords

EID: 77952803494     PISSN: 01565788     EISSN: 14498944     Source Type: Journal    
DOI: 10.1071/AH09801     Document Type: Article

References (65)

1. McLoughlin V, Leatherman S. Quality or financing: what drives design of the health care system? Qual Saf Health Care 2003; 12(2): 136-142 [Comparative study] doi:10.1136/qhc.12.2.136
2. McGlynn EA, Damberg CL, Kerr EA, Brook RH. Health information systems: Design issues and analytical applications. RAND: Santa Monica, CA, USA; 1998.
3. Duckett SJ. Casemix funding for acute hospital inpatient services in Australia. Med J Aust 1998; 169(Suppl): S17-21.
4. Coory M, Youlden D, Baker P. Interpretation of hospital-specific outcome measures based on routine data. Aust Health Rev 2002; 25(4): 69-72. doi:10.1071/AH020069
5. McNair P, Duckett S. Funding Victoria's public hospitals: The Casemix policy of 2000-2001. Aust Health Rev 2002; 25(1): 72-98. doi:10.1071/ AH020072
6. VDH. Victoria - Public Hospitals & Mental Health Services policy and funding guidelines 2008-2009. Melbourne, Australia: Funding, Health and Information Policy Branch, Victorian Department of Health (VDH); 2009. Available at http://www.health.vic.gov.au/pfg/ [verified 21 April 2009].
7. VDH. Victoria - Public hospitals and mental health services policy and funding guidelines 2008-2009 - General conditions of funding. Melbourne, Australia: Victorian Department of Health (VDH); 2007.
8. AIHW. A guide to data development. Canberra, ACT, Australia: Australian Institute of Health and Welfare (AIHW), Canberra, Australia; 2007.
9. NEHTA. National e-health standards development: A management framework. National E-Health Transition Authority (NEHTA); 2006. pp. 1-26.
10. AIHW. Data Standards. Canberra, Australia: Australian Institute of Health and Welfare (AIHW), Canberra, Australia; 2008. Available at http://www.aihw.gov.au/datadevelopment/index.cfm [verified January 2009].
11. VDH. Improving Information Practices in Victorian Department of Human Services. Department of Health (VDH), Melbourne, Victoria, Australia; 2001. pp. 1-40.
12. Heslop L, Gardner B, Diers D, Poh BC. Using clinical data for nursing research and management in health services. Contemp Nurse 2004; 17(1-2): 8-18. [Review]
13. Landrum L, Weinrich S. Readmission data for outcomes measurement: identifying and strengthening the empirical base. Qual Manag Health Care 2006; 15(2): 83-95. [Review]
14. Holcomb J. The role of administrative data in measurement and reporting of quality of hospital care. Tex Med 2000; 96(10): 48-52. [Review]
15. Ansari MZ, Ackland MJ, Jolley DJ, Carson N, McDonald IG. Interhospital comparison of mortality rates. Int J Qual Health Care 1999; 11(1): 29-35. doi:10.1093/intqhc/11.1.29 (Pubitemid 29100341)
16. Ghali WA, Hall RE, Ash AS, Rosen AK, Moskowitz MA. Evaluation of complication rates after coronary artery bypass surgery using administrative data. Methods Inf Med 1998; 37(2): 192-200.
17. Heslop L, Gardner B, Athan D, Diers D, Taylor C. Researching hospital patient data to enhance operational management. Health Inf Manag 2004; 32(1): 13-16
18. Hargreaves J. Reporting of adverse events in routinely collected data sets in Australia. Canberra, Australia: Australian Institute of Health and Welfare (AIHW), Canberra, Australia (Health Division Working Paper No. 3); 2001.
19. Carroll R, McLean J, Walsh M. Reporting hospital adverse events using the Alfred Hospital's morbidity data. Aust Health Rev 2003; 26(2): 100-105 doi:10.1071/AH030100
20. Ehsani JP, Jackson T, Duckett SJ. The incidence and cost of adverse events in Victorian hospitals 2003-2004. Med J Aust 2006; 184(11): 551-555
21. Quan H, Parsons GA, Ghali WA. Validity of information on comorbidity derived from ICD-9-CCM administrative data. Med Care 2002; 40(8): 675-685 doi:10.1097/00005650-200208000-00007
22. Roos NP, Roos LL, Mossey J, Havens B. Using Administrative Data to predict important health outcomes entry to hospital, nursing home, and death. Med Care 1988; 26(3): 221-39. doi:10.1097/00005650- 198803000-198900001
23. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992; 45(6): 613-619 doi:10.1016/0895-4356(92)90133-8
24. Diers D, Bozzo J. Using administrative data for practice and management. Nurs Econ 1999; 17(4): 233-237
25. Diers D, Pelletier D. Seeding information management capacity to support operational management in hospitals. Aust Health Rev 2001; 24(2): 74-82. doi:10.1071/AH010074
26. Pelletier D, Diers D. Developing data for practice and management: an Australian educational initiative. Comput Inform Nurs 2004; 22(4): 197-202. doi:10.1097/00024665-200407000-00006
27. Agrawal R, Johnson C. Securing electronic health records without impeding the flow of information. Int J Med Inf 2007; 76(5-6): 471-479 [Review] doi:10.1016/j.ijmedinf.2006.09.015
28. Nadathur SG. Bayesian networks in the health domain. In: Ali S, Xiang Y, editors. Dynamic and Advanced Data Mining for Progressing Technological Development. Hershey, PA, USA: IGI Global Publication; 2009. pp. 342-376
29. NHMRC. National Ethics Application Form (NEAF). Canberra, Australia: National Health & Medical Research Council (NHMRC), Canberra, Australia; 2009. Available at https://www.neaf.gov.au/ default.aspx [verified June 2009].
30. VDH. Multi-site research. Melbourne, Australia: Victorian Department of Health (VDH); 2009. Available at http://www.health.vic.gov.au/ ethics/multi/index.htm [verified June 2009].
31. Iezzoni LI.How much are we willing to pay for information about quality of care? Ann Intern Med 1997; 126(5): 391-3. [Comment Editorial; Erratum: Ann Intern Med 1997; 126(7): 588]
32. Iezzoni LI. How much are we willing to pay for information about quality? Ann Intern Med 1997; 126(9): 746. [Letter]
33. Allen DE, Bockenhauer B, Egan C, Kinnaird LS. Relating outcomes to excellent nursing practice. J Nurs Adm 2006; 36(3): 140-147 [Review] doi:10.1097/00005110-200603000-00008
34. Institute of Medicine, Committee on Enhancing Federal Healthcare Quality Program, Corrigan J, Eden J, Smith BM. Leadership by example: coordinating government roles in improving health care quality. Washington, DC: National Academies Press; 2003.
35. VDH. Proposals for revisions to Victorian Emergency Minimum Dataset (VEMD) for 1 July 2005. Victorian Department of Health (VDH), Melbourne, Victoria, Australia; 2004. pp. 1-8.
36. Nadathur SG. Recorded categories of non-principal diagnoses in Victorian public hospital transient ischaemic attack and stroke admissions. Health Information Management Journal 2008; 37(3): 33-44.
37. Best WR, Khuri SF, Phelan M, Hur K, Henderson WG, Demakis JG, Daley J. Identifying patient preoperative risk factors and postoperative adverse events in administrative databases: results from the Department of Veterans Affairs National Surgical Quality Improvement Program. J Am Coll Surg 2002; 194(3): 257-266 doi:10.1016/S1072-7515(01) 01183-8
38. Schwamm L, Reeves MJ, Frankel M. Designing a sustainable national registry for stroke quality improvement. Am J Prev Med 2006; 31(6, Suppl 2): S251-7. doi:10.1016/j.amepre.2006.08.013 (Pubitemid 44914116)
39. Chassin MR, Galvin RW.The urgent need to improve health care quality. Institute of Medicine National Roundtable on Health Care Quality.JAMA 1998; 280(11): 1000-1005 [Review] doi:10.1001/jama.280.11.1000
40. GlanceLG,DickAW,OslerTM,MukamelDB.Does date stampingICD- 9-CM codes increase the value of clinical information in administrative data? Health Serv Res 2006; 41(1): 231-251 doi:10.1111/j.1475- 6773.2005.00419.x
41. DoHA. Casemix Classifications. Canberra, Australia: Commonwealth Department of Health and Aging (DoHA); 2009. Available at http:// www.health.gov.au/internet/main/publishing.nsf/Content/ Classificationshub.htm [verified 29 May 2009].
42. NCCH. The International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Australian Modification (ICD-10-AM) - 3rd Edition. Sydney: National Centre for Classification in Health (NCCH); 2002.
43. Roberts RF, Innes KC, Walker SM. Introducing ICD-10-AM in Australian hospitals. Med J Aust 1998; 169(Suppl): S32-5.
44. Nadathur SG, Groom A. Coding and DRG relationships in stroke and transient ischaemic attack (TIA). Health Information Management Journal 2006; 35(1): 38-44.
45. Shapiro MF, Park RE, Keesey J, Brook RH. The effect of alternative case-mix adjustments on mortality differences between municipal and voluntary hospitals in New York City. Health Serv Res 1994; 29(1): 95-112.
46. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987; 40(5): 373-83. doi:10.1016/0021- 9681(87)90171-90178
47. Polanczyk CA, Rohde LE, Philbin EA, Di Salvo TG. A new Casemix adjustment index for hospital mortality among patients with congestive heart failure. Med Care 1998; 36(10): 1489-99. doi:10.1097/00005650- 199810000-199900007
48. D'Hoore W, Bouckaert A, Tilquin C. Practical considerations on the use of the Charlson Comorbidity Index with administrative data bases. J Clin Epidemiol 1996; 49(12): 1429-1433 doi:10.1016/S0895-4356(96) 00271-5
49. Chaudhry S, Jin L, Meltzer D. Use of a self-report-generated Charlson Comorbidity Index for predicting mortality. Med Care 2005; 43(6): 607-615 doi:10.1097/01.mlr.0000163658.65008.ec (Pubitemid 40847298)
50. Ghali WA, Hall RE, Rosen AK, Ash AS, Moskowitz MA. Searching for an improved clinical comorbidity index for use with ICD-9-CM administrative data. J Clin Epidemiol 1996; 49(3): 273-8. doi:10.1016/ 0895-4356(95)00564-571
51. Needham DM, Scales DC, Laupacis A, Pronovost PJ. A systematic review of the Charlson comorbidity index using Canadian administrative databases: A perspective on risk adjustment in critical care research. J Crit Care 2005; 20(1): 12-19 doi:10.1016/j.jcrc.2004.09.007 (Pubitemid 40602219)
52. Schneeweiss S, Maclure M, Schneeweiss S, Maclure M. Use of comorbidity scores for control of confounding in studies using administrative databases. Int J Epidemiol 2000; 29(5): 891-898 [Review] doi:10.1093/ije/29.5.891
53. Klabunde CN, Potosky AL, Legler JM, Warren JL. Development of a comorbidity index using physician claims data. J Clin Epidemiol 2000; 53(12): 1258-1267 doi:10.1016/S0895-4356(00)00256-0 (Pubitemid 32007842)
54. Romano PS, Roos LL, Jollis JG, Romano PS, Roos LL, Jollis JG. Further evidence concerning the use of a clinical comorbidity index for use with ICD-9-CM administrative data: Differing perspectives. J Clin Epidemiol 1993; 46(10): 1085-1090 doi:10.1016/0895-4356(93) 90106-B
55. Romano PS, Roos LL, Jollis JG. Variance and Dissent Presentation: Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. J Clin Epidemiol 1993; 46(10): 1075-1079 doi:10.1016/0895-4356(93)90103-8 (Pubitemid 23302074)
56. Roos LL, Menec V, Currie RJ. Policy analysis in an information-rich environment. Soc Sci Med 2004; 58(11): 2231-2241 doi:10.1016/ j.socscimed.2003.08.008
57. Williams TA, Dobb GJ, Finn JC, Knuiman M, Lee KY, Geelhoed E, et al. Data linkage enables evaluation of long-term survival after intensive care. Anaesth Intensive Care 2006; 34(3): 307-315
58. Stone CA, Ramsden CA, Howard JA, Roberts M, Halliday JH. From data linkage to policy and back again: A preliminary report on the linkage of neonatal data in Victoria. Symposium on Health Data Linkage: Its value for Australian health policy development and policy relevant research; 2002, March 20-21 Sydney, NSW, Australia. Public Health Information Development Unit (PHIDU), Adelaide University; 2002. pp. 209-211
59. Sundararajan V, Henderson TM, Ackland M, Marshall R. Linkage of the Victorian Admitted Episodes Dataset. Symposium on Health Data Linkage: Its value for Australian health policy development and policy relevant research; 2002, March 20-21; Sydney, NSW, Australia. Public Health Information Development Unit (PHIDU), Adelaide University; 2002. pp. 212-215
60. Karmel R, Rosman D. Linkage of health and aged care service events: comparing linkage and event selection methods. BMC Health Serv Res 2008; 8: 149. doi:10.1186/1472-6963-8-149
61. Robinson JR,YoungTK, RoosLL, Gelskey DE. Estimating the burden of disease: Comparing administrative data and self-reports. Med Care 1997; 35(9): 932-947 doi:10.1097/00005650-199709000-00006
62. Semmens JB, Platell C, Threlfall TJ, Holman CD. A population-based study of the incidence, mortality and outcomes in patients following surgery for colorectal cancer in Western Australia. Aust N Z J Surg 2000; 70(1): 11-18 doi:10.1046/j.1440-1622.2000.01734.x (Pubitemid 30104109)
63. NEHTA. Action plan for adoption success: The response to the independent review of NEHTA. National E-Health Transition Authority (NEHTA); 2007. pp. 1-10.
64. Andriessen DG. Stuff or love? How metaphors direct our efforts to manage knowledge in organisations. Knowledge Management Research and Practice 2008; 6: 5-12. doi:10.1057/palgrave.kmrp.8500169
65. van Gool K, Lancsar E, Viney R, Hall J, Haywood P. Diagnosis and prognosis of Australia's health information for evidence-based policy. J Health Serv Res Policy 2002; 7(Suppl 1): 40-5. doi:10.1258/ 135581902320176368 (Pubitemid 34760625)