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Published in: BMC Health Services Research 1/2012

Open Access 01-12-2012 | Research article

Use of routine hospital morbidity data together with weight and height of patients to predict in-hospital complications following total joint replacement

Published in: BMC Health Services Research | Issue 1/2012

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Abstract

Background

Routinely collected data such as hospital morbidity data (HMD) are increasingly used in studying clinical outcomes among patients undergoing total joint replacement (TJR). These data are readily available and cover large populations. However, since these data were not originally collected for the purpose of health research, a rigorous assessment of their quality is required. We assessed the accuracy of the diagnosis of obesity in HMD and evaluated whether the augmentation of HMD with actual weight and height of patients could improve their ability to predict major in-hospital complications following total joint replacement in men.

Methods

The electronic records of 857 participants in the Health In Men Study (HIMS) who had had TJR were linked with Western Australia HMD. HMD-recorded diagnosis of obesity was validated using the actual weight and height obtained from HIMS. In-hospital major complications were modelled using multivariable logistic regressions that either included the actual weight and height or HMD-recorded obesity. Model discrimination was calculated using area under ROC curve.

Results

The HMD failed to detect 70% of the obese patients. Only 64 patients (7.5%) were recorded in HMD as obese although 216 (25%) were obese [BMI: ≥30kg/m2] (sensitivity: 0.2, positive predictive value: 0.7). Overall, 174 patients (20%) developed an in-hospital major complication which was significantly higher in the overweight and obese comparing with patients with normal weight. HMD-recorded obesity was not independently associated with major complications, whereas a dose–response relationship between weight and these complications was observed (P=0.004). Using the actual weight and height of the participants instead of HMD-recorded diagnosis of obesity improved model discrimination by 9%, with areas under ROC curve of: 0.69, 95% CI: 0.64-0.73 for the model with HMD-recorded obesity compared with 0.75, 95% CI: 0.70-0.79 for the model with actual weight and height, P<0.001.

Conclusion

Body weight is an important risk factor for in-hospital complications in patients undergoing TJR. HMD systems do not include weight and height as variables whose recording is mandatory. Augmenting HMD with patients’ weight and height may improve prediction of major complications following TJR. Our study suggests making these variables mandatory in any hospital morbidity data system.
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Literature
1.
go back to reference Aylin P, Bottle A, Majeed A: Use of administrative data or clinical databases as predictors of risk of death in hospital: comparison of models. BMJ. 2007, 334: 1014-1015. 10.1136/bmj.39211.453275.80.CrossRef Aylin P, Bottle A, Majeed A: Use of administrative data or clinical databases as predictors of risk of death in hospital: comparison of models. BMJ. 2007, 334: 1014-1015. 10.1136/bmj.39211.453275.80.CrossRef
2.
go back to reference Scott I, Youlden D, Coory M: Are diagnosis specific outcome indicators based on administrative data useful in assessing quality of hospital care?. Qual Saf Health Care. 2004, 13: 32-39. 10.1136/qshc.2002.003996.CrossRefPubMedPubMedCentral Scott I, Youlden D, Coory M: Are diagnosis specific outcome indicators based on administrative data useful in assessing quality of hospital care?. Qual Saf Health Care. 2004, 13: 32-39. 10.1136/qshc.2002.003996.CrossRefPubMedPubMedCentral
3.
go back to reference Mnatzaganian G, Ryan P, Norman PE, Davidson DC, Hiller JE: Length of stay in hospital and all-cause readmission following elective total joint replacement in elderly men. Orthop Res Rev. 2012, 4: 43-51.CrossRef Mnatzaganian G, Ryan P, Norman PE, Davidson DC, Hiller JE: Length of stay in hospital and all-cause readmission following elective total joint replacement in elderly men. Orthop Res Rev. 2012, 4: 43-51.CrossRef
4.
go back to reference Romano PS, Schembri ME, Rainwater JA: Can administrative data be used to ascertain clinically significant postoperative complications?. Am J Med Qual. 2002, 17: 145-154. 10.1177/106286060201700404.CrossRefPubMed Romano PS, Schembri ME, Rainwater JA: Can administrative data be used to ascertain clinically significant postoperative complications?. Am J Med Qual. 2002, 17: 145-154. 10.1177/106286060201700404.CrossRefPubMed
5.
go back to reference Fisher ES, Whaley FS, Krushat WM, Malenka DJ, Fleming C, Baron JA, Hsia DC: The accuracy of Medicare’s hospital claims data: progress has been made, but problems remain. Am J Public Health. 1992, 82: 243-248. 10.2105/AJPH.82.2.243.CrossRefPubMedPubMedCentral Fisher ES, Whaley FS, Krushat WM, Malenka DJ, Fleming C, Baron JA, Hsia DC: The accuracy of Medicare’s hospital claims data: progress has been made, but problems remain. Am J Public Health. 1992, 82: 243-248. 10.2105/AJPH.82.2.243.CrossRefPubMedPubMedCentral
6.
go back to reference Jollis JG, Ancukiewicz M, DeLong ER, Pryor DB, Muhlbaier LH, Mark DB: Discordance of databases designed for claims payment versus clinical information systems. Implications for outcomes research. Ann Intern Med. 1993, 119: 844-850.CrossRefPubMed Jollis JG, Ancukiewicz M, DeLong ER, Pryor DB, Muhlbaier LH, Mark DB: Discordance of databases designed for claims payment versus clinical information systems. Implications for outcomes research. Ann Intern Med. 1993, 119: 844-850.CrossRefPubMed
7.
go back to reference Iezzoni LI, Foley SM, Daley J, Hughes J, Fisher ES, Heeren T: Comorbidities, complications, and coding bias. Does the number of diagnosis codes matter in predicting in-hospital mortality?. JAMA. 1992, 267: 2197-2203. 10.1001/jama.1992.03480160055034.CrossRefPubMed Iezzoni LI, Foley SM, Daley J, Hughes J, Fisher ES, Heeren T: Comorbidities, complications, and coding bias. Does the number of diagnosis codes matter in predicting in-hospital mortality?. JAMA. 1992, 267: 2197-2203. 10.1001/jama.1992.03480160055034.CrossRefPubMed
8.
go back to reference Jencks SF, Williams DK, Kay TL: Assessing hospital-associated deaths from discharge data. The role of length of stay and comorbidities. JAMA. 1988, 260: 2240-2246. 10.1001/jama.1988.03410150088036.CrossRefPubMed Jencks SF, Williams DK, Kay TL: Assessing hospital-associated deaths from discharge data. The role of length of stay and comorbidities. JAMA. 1988, 260: 2240-2246. 10.1001/jama.1988.03410150088036.CrossRefPubMed
9.
go back to reference Mnatzaganian G, Ryan P, Norman PE, Hiller JE: Accuracy of hospital morbidity data and the performance of comorbidity scores as predictors of mortality. J Clin Epidemiol. 2012, 65: 107-115. 10.1016/j.jclinepi.2011.03.014.CrossRefPubMed Mnatzaganian G, Ryan P, Norman PE, Hiller JE: Accuracy of hospital morbidity data and the performance of comorbidity scores as predictors of mortality. J Clin Epidemiol. 2012, 65: 107-115. 10.1016/j.jclinepi.2011.03.014.CrossRefPubMed
10.
go back to reference Quan H, Parsons GA, Ghali WA: Validity of information on comorbidity derived from ICD-9-CCM administrative data. Med Care. 2001, 40: 675-685.CrossRef Quan H, Parsons GA, Ghali WA: Validity of information on comorbidity derived from ICD-9-CCM administrative data. Med Care. 2001, 40: 675-685.CrossRef
11.
go back to reference Pine M, Jordan HS, Elixhauser A, Fry DE, Hoaglin DC, Jones B, Meimban R, Warner D, Gonzales J: Enhancement of claims data to improve risk adjustment of hospital mortality. JAMA. 2007, 297: 71-76. 10.1001/jama.297.1.71.CrossRefPubMed Pine M, Jordan HS, Elixhauser A, Fry DE, Hoaglin DC, Jones B, Meimban R, Warner D, Gonzales J: Enhancement of claims data to improve risk adjustment of hospital mortality. JAMA. 2007, 297: 71-76. 10.1001/jama.297.1.71.CrossRefPubMed
12.
go back to reference Kurtz S, Ong K, Lau E, Mowat F, Halpern M: Projections of primary and revision hip and knee arthroplasty in the United States from 2005 to 2030. J Bone Joint Surg Am. 2007, 89: 780-785. 10.2106/JBJS.F.00222.CrossRefPubMed Kurtz S, Ong K, Lau E, Mowat F, Halpern M: Projections of primary and revision hip and knee arthroplasty in the United States from 2005 to 2030. J Bone Joint Surg Am. 2007, 89: 780-785. 10.2106/JBJS.F.00222.CrossRefPubMed
13.
go back to reference Birrell F, Johnell O, Silman A: Projecting the need for hip replacement over the next three decades: influence of changing demography and threshold for surgery. Ann Rheum Dis. 1999, 58: 569-572. 10.1136/ard.58.9.569.CrossRefPubMedPubMedCentral Birrell F, Johnell O, Silman A: Projecting the need for hip replacement over the next three decades: influence of changing demography and threshold for surgery. Ann Rheum Dis. 1999, 58: 569-572. 10.1136/ard.58.9.569.CrossRefPubMedPubMedCentral
14.
go back to reference Talmo CT, Robbins CE, Bono JV: Total joint replacement in the elderly patient. Clin Geriatr Med. 2010, 26: 517-529. 10.1016/j.cger.2010.04.002.CrossRefPubMed Talmo CT, Robbins CE, Bono JV: Total joint replacement in the elderly patient. Clin Geriatr Med. 2010, 26: 517-529. 10.1016/j.cger.2010.04.002.CrossRefPubMed
15.
go back to reference Mahomed NN, Barrett JA, Katz JN, Phillips CB, Losina E, Lew RA, Guadagnoli E, Harris WH, Poss R, Baron JA: Rates and outcomes of primary and revision total hip replacement in the United States medicare population. J Bone Joint Surg Am. 2003, 85-A: 27-32.PubMed Mahomed NN, Barrett JA, Katz JN, Phillips CB, Losina E, Lew RA, Guadagnoli E, Harris WH, Poss R, Baron JA: Rates and outcomes of primary and revision total hip replacement in the United States medicare population. J Bone Joint Surg Am. 2003, 85-A: 27-32.PubMed
16.
go back to reference SooHoo NF, Lieberman JR, Ko CY, Zingmond DS: Factors predicting complication rates following total knee replacement. J Bone Joint Surg Am. 2006, 88: 480-485. 10.2106/JBJS.E.00629.CrossRefPubMed SooHoo NF, Lieberman JR, Ko CY, Zingmond DS: Factors predicting complication rates following total knee replacement. J Bone Joint Surg Am. 2006, 88: 480-485. 10.2106/JBJS.E.00629.CrossRefPubMed
17.
go back to reference Sadr Azodi O, Bellocco R, Eriksson K, Adami J: The impact of tobacco use and body mass index on the length of stay in hospital and the risk of post-operative complications among patients undergoing total hip replacement. J Bone Joint Surg Br. 2006, 88: 1316-1320. 10.1302/0301-620X.88B10.17957.CrossRefPubMed Sadr Azodi O, Bellocco R, Eriksson K, Adami J: The impact of tobacco use and body mass index on the length of stay in hospital and the risk of post-operative complications among patients undergoing total hip replacement. J Bone Joint Surg Br. 2006, 88: 1316-1320. 10.1302/0301-620X.88B10.17957.CrossRefPubMed
18.
go back to reference Mnatzaganian G, Ryan P, Norman PE, Davidson DC, Hiller JE: Total joint replacement in men: old age, obesity and in-hospital complications. ANZ J Surg. 2012, 10.1111/j.1445-2197.2012.06227.x. Mnatzaganian G, Ryan P, Norman PE, Davidson DC, Hiller JE: Total joint replacement in men: old age, obesity and in-hospital complications. ANZ J Surg. 2012, 10.1111/j.1445-2197.2012.06227.x.
19.
go back to reference Katz JN, Wright EA, Baron JA, Corbett KL, Nti AA, Malchau H, Wright J, Losina E: Predictive value of Medicare claims data for identifying revision of index hip replacement was modest. J Clin Epidemiol. 2011, 64: 543-546. 10.1016/j.jclinepi.2010.05.005.CrossRefPubMed Katz JN, Wright EA, Baron JA, Corbett KL, Nti AA, Malchau H, Wright J, Losina E: Predictive value of Medicare claims data for identifying revision of index hip replacement was modest. J Clin Epidemiol. 2011, 64: 543-546. 10.1016/j.jclinepi.2010.05.005.CrossRefPubMed
20.
go back to reference Norman PE, Flicker L, Almeida OP, Hankey GJ, Hyde Z, Jamrozik K: Cohort Profile: The Health In Men Study (HIMS). Int J Epidemiol. 2009, 38: 48-52.CrossRefPubMed Norman PE, Flicker L, Almeida OP, Hankey GJ, Hyde Z, Jamrozik K: Cohort Profile: The Health In Men Study (HIMS). Int J Epidemiol. 2009, 38: 48-52.CrossRefPubMed
21.
go back to reference Mnatzaganian G, Ryan P, Norman PE, Davidson DC, Hiller JE: Smoking, body weight, physical exercise, and risk of lower limb total joint replacement in a population-based cohort of men. Arthritis Rheum. 2011, 63: 2523-2530. 10.1002/art.30400.CrossRefPubMed Mnatzaganian G, Ryan P, Norman PE, Davidson DC, Hiller JE: Smoking, body weight, physical exercise, and risk of lower limb total joint replacement in a population-based cohort of men. Arthritis Rheum. 2011, 63: 2523-2530. 10.1002/art.30400.CrossRefPubMed
22.
go back to reference Holman CD, Bass AJ, Rouse IL, Hobbs MS: Population-based linkage of health records in Western Australia: development of a health services research linked database. Aust N Z J Public Health. 1999, 23: 453-459. 10.1111/j.1467-842X.1999.tb01297.x.CrossRefPubMed Holman CD, Bass AJ, Rouse IL, Hobbs MS: Population-based linkage of health records in Western Australia: development of a health services research linked database. Aust N Z J Public Health. 1999, 23: 453-459. 10.1111/j.1467-842X.1999.tb01297.x.CrossRefPubMed
23.
go back to reference Parvizi J, Mui A, Purtill JJ, Sharkey PF, Hozack WJ, Rothman RH: Total joint arthroplasty: When do fatal or near-fatal complications occur?. J Bone Joint Surg Am. 2007, 89: 27-32. 10.2106/JBJS.E.01443.CrossRefPubMed Parvizi J, Mui A, Purtill JJ, Sharkey PF, Hozack WJ, Rothman RH: Total joint arthroplasty: When do fatal or near-fatal complications occur?. J Bone Joint Surg Am. 2007, 89: 27-32. 10.2106/JBJS.E.01443.CrossRefPubMed
24.
go back to reference Deyo RA, Cherkin DC, Ciol MA: Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992, 45: 613-619. 10.1016/0895-4356(92)90133-8.CrossRefPubMed Deyo RA, Cherkin DC, Ciol MA: Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992, 45: 613-619. 10.1016/0895-4356(92)90133-8.CrossRefPubMed
25.
go back to reference Australian Bureau of Statistics (ABS): Cat. No. 2039.0. 1996 Census of Population and Housing: Socioeconomic Indexes for Areas. 1998, Canberra: AusInfo Australian Bureau of Statistics (ABS): Cat. No. 2039.0. 1996 Census of Population and Housing: Socioeconomic Indexes for Areas. 1998, Canberra: AusInfo
26.
go back to reference 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: 373-383. 10.1016/0021-9681(87)90171-8.CrossRefPubMed 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: 373-383. 10.1016/0021-9681(87)90171-8.CrossRefPubMed
27.
go back to reference Pine M, Norusis M, Jones B, Rosenthal GE: Predictions of hospital mortality rates: a comparison of data sources. Ann Intern Med. 1997, 126: 347-354.CrossRefPubMed Pine M, Norusis M, Jones B, Rosenthal GE: Predictions of hospital mortality rates: a comparison of data sources. Ann Intern Med. 1997, 126: 347-354.CrossRefPubMed
28.
go back to reference Geraci JM, Johnson ML, Gordon HS, Petersen NJ, Shroyer AL, Grover FL, Wray NP: Mortality after cardiac bypass surgery: prediction from administrative versus clinical data. Med Care. 2005, 43: 149-158. 10.1097/00005650-200502000-00008.CrossRefPubMed Geraci JM, Johnson ML, Gordon HS, Petersen NJ, Shroyer AL, Grover FL, Wray NP: Mortality after cardiac bypass surgery: prediction from administrative versus clinical data. Med Care. 2005, 43: 149-158. 10.1097/00005650-200502000-00008.CrossRefPubMed
29.
go back to reference Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, Flegal KM: Prevalence of overweight and obesity among US children, adolescents, and adults, 1999–2002. JAMA. 2004, 291: 2847-50. 10.1001/jama.291.23.2847.CrossRefPubMed Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, Flegal KM: Prevalence of overweight and obesity among US children, adolescents, and adults, 1999–2002. JAMA. 2004, 291: 2847-50. 10.1001/jama.291.23.2847.CrossRefPubMed
30.
go back to reference Naessens JM, Brennan MD, Boberg CJ, Amadio PC, Karver PJ, Podratz RO: Acquired conditions: an improvement to hospital discharge abstracts. Qual Assur Health Care. 1991, 3: 257-62.CrossRefPubMed Naessens JM, Brennan MD, Boberg CJ, Amadio PC, Karver PJ, Podratz RO: Acquired conditions: an improvement to hospital discharge abstracts. Qual Assur Health Care. 1991, 3: 257-62.CrossRefPubMed
31.
go back to reference Freebody S: Implementation of a nutritional assessment tool for patients undergoing surgery. J Orthop Nurs. 1998, 2: 25-31. 10.1016/S1361-3111(98)80007-1.CrossRef Freebody S: Implementation of a nutritional assessment tool for patients undergoing surgery. J Orthop Nurs. 1998, 2: 25-31. 10.1016/S1361-3111(98)80007-1.CrossRef
Metadata
Title
Use of routine hospital morbidity data together with weight and height of patients to predict in-hospital complications following total joint replacement
Publication date
01-12-2012
Published in
BMC Health Services Research / Issue 1/2012
Electronic ISSN: 1472-6963
DOI
https://doi.org/10.1186/1472-6963-12-380

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