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Evidence-Based Decision Making 6: Administrative Databases as Secondary Data Source for Epidemiologic and Health Service Research

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Clinical Epidemiology

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2249))

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Abstract

Health-care systems require reliable information on which to base health-care planning and make decisions, as well as to evaluate their policy impact. Administrative data, predominantly captured for non-research purposes, provide important information about health services use, expenditures, and clinical outcomes and may be used to assess quality of care. With increased digitalization and accessibility of administrative databases, this data is more readily available for health service research purposes, aiding evidence-based decision making. This chapter discusses the utility of administrative data for population-based studies of health and health care.

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References

  1. Iezzoni LI (1997) Assessing quality using administrative data. Ann Intern Med 127:666–674

    Article  CAS  PubMed  Google Scholar 

  2. Cowper DC, Hynes DM, Kubal JD, Murphy PA (1999) Using administrative databases for outcomes research: select examples from VA health services research and development. J Med Syst 23:249–259

    Article  CAS  PubMed  Google Scholar 

  3. Fantini M, Cisbani L, Manzoli L, Vertrees J, Lorenzoni L (2003) On the use of administrative databases to support planning activities the case of the evaluation of neonatal case-mix in the emilia–romagna region using drg and apr–drg classification systems. Eur J Pub Health 13:138–145

    Article  CAS  Google Scholar 

  4. Malenka DJ, McLerran D, Roos N, Fisher ES, Wennberg JE (1994) Using administrative data to describe casemix: a comparison with the medical record. J Clin Epidemiol 47:1027–1032

    Article  CAS  PubMed  Google Scholar 

  5. Ray WA (1997) Policy and program analysis using administrative databases. Ann Intern Med 127:712–718

    Article  CAS  PubMed  Google Scholar 

  6. Virnig BA, McBean M (2001) Administrative data for public health surveillance and planning. Annu Rev Pub Health 22:213–230

    Article  CAS  Google Scholar 

  7. Tricco AC, Pham B, Rawson NS (2008) Manitoba and Saskatchewan administrative health care utilization databases are used differently to answer epidemiologic research questions. J Clin Epidemiol 61:192–197

    Article  PubMed  Google Scholar 

  8. Rucker D, Hemmelgarn BR, Lin M, Manns BJ, Klarenbach SW, Ayyalasomayajula B et al (2011) Quality of care and mortality are worse in chronic kidney disease patients living in remote areas. Kidney Int 79:210–217

    Article  PubMed  Google Scholar 

  9. Wiebe N, Klarenbach SW, Chui B, Ayyalasomayajula B, Hemmelgarn BR, Jindal K et al (2012) Adding specialized clinics for remote-dwellers with chronic kidney disease: a cost-utility analysis. Clin J Am Soc Nephrol 7:24–34

    Article  PubMed  Google Scholar 

  10. Suissa S, Primer GE (2007) Administrative health databases in observational studies of drug effects—advantages and disadvantages. Nat Clin Pract Rheumatol 3:725–732

    Article  CAS  PubMed  Google Scholar 

  11. Kokotailo RA, Hill MD (2005) Coding of stroke and stroke risk factors using international classification of diseases, revisions 9 and 10. Stroke 36:1776–1781

    Article  PubMed  Google Scholar 

  12. Peter CA, Paul AD, Jack VT (2002) A multicenter study of the coding accuracy of hospital discharge administrative data for patients admitted to cardiac care units in Ontario. Am Heart J 144:290–296

    Article  Google Scholar 

  13. Ronksley PE, Tonelli M, Quan H, Manns BJ, James MT, Clement FM et al (2012) Validating a case definition for chronic kidney disease using administrative data. Nephrol Dial Transplant 27:1826–1831

    Article  CAS  PubMed  Google Scholar 

  14. Grimes DA (2010) Epidemiologic research using administrative databases: garbage in, garbage out. Obstet Gynecol 116:1018–1019

    Article  PubMed  Google Scholar 

  15. Iezzoni L, Foley S, Daley J, Hughes J, Fisher E, Heeren T (1991) Comorbidities, complications, and coding bias. Does the number of diagnosis codes matter in predicting in-hospital mortality? J Am Med Assoc 267:2197–2203

    Article  Google Scholar 

  16. Jollis JG, Ancukiewicz M, DeLong ER, Pryor DB, Muhlbaier LH, Mark DB (1993) Discordance of databases designed for claims payment versus clinical information systems: implications for outcomes research. Ann Intern Med 119:844–850

    Article  CAS  PubMed  Google Scholar 

  17. Hux JE, Ivis F, Flintoft V, Bica A (2002) Diabetes in Ontario: determination of prevalence and incidence using a validated administrative data algorithm. Diab Care 25:512–516

    Article  Google Scholar 

  18. Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi J-C et al (2005) Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 43:1130–1139

    Article  PubMed  Google Scholar 

  19. Clement FM, James MT, Chin R, Klarenbach SW, Manns BJ, Quinn RR et al (2011) Validation of a case definition to define chronic dialysis using outpatient administrative data. BMC Med Res Methodol 11:25

    Article  PubMed  PubMed Central  Google Scholar 

  20. Jones SS, Adams JL, Schneider EC, Ringel JS, McGlynn EA (2010) Electronic health record adoption and quality improvement in us hospitals. Am J Manag Care 16:SP64–SP71

    PubMed  Google Scholar 

  21. Lillard LA, Farmer MM (1997) Linking medicare and national survey data. Ann Intern Med 127:691–695

    Article  CAS  PubMed  Google Scholar 

  22. Interdisciplinary Chronic Disease Collaboration (2008) The research to health policy cycle: a tool for better management of chronic noncommunicable diseases. J Nephrol 21:621–631

    Google Scholar 

  23. Black N (2001) Evidence based policy: proceed with care. Br Med J 323:275

    Article  CAS  Google Scholar 

  24. Wennberg J, Gittelsohn A (1973) Small area variations in health care delivery a population-based health information system can guide planning and regulatory decision-making. Science 182:1102–1108

    Article  CAS  PubMed  Google Scholar 

  25. Relman AS (1988) Assessment and accountability: the third revolution in medical care. N Engl J Med 319:1220

    Article  CAS  PubMed  Google Scholar 

  26. Roper WL, Winkenwerder W, Hackbarth GM, Krakauer H (1988) Effectiveness in health care. An initiative to evaluate and improve medical practice. N Engl J Med 319:1197

    Article  CAS  PubMed  Google Scholar 

  27. Gabriel S, Crowson C, O’Fallon W (1995) Costs of osteoarthritis: estimates from a geographically defined population. J Rheumatol Suppl 43:23–25

    CAS  PubMed  Google Scholar 

  28. Clancy CM, Eisenberg JM (1997) Outcomes research at the agency for health care policy and research. Dis Man Clin Outcomes 1:72–80

    Article  Google Scholar 

  29. Lave JR, Pashos CL, AndersonN G, Brailer D, Bubolz T, Conrad D et al (1994) Costing medical care: Using medicare administrative data. Med Care 32:JS77–JS89

    Article  CAS  PubMed  Google Scholar 

  30. Mitchell JB, Bubolz T, Paul JE, Pashos CL, Escarce JJ, Muhlbaier LH et al (1994) Using medicare claims for outcomes research. Med Care 32:JS38–JS51

    Article  CAS  PubMed  Google Scholar 

  31. Institute of Medicine Committee on Quality of Health in America (2001) Crossing the quality chasm: a new health system for the 21st century. National Academies Press, Washington, DC, pp 1–337

    Google Scholar 

  32. Canadian Institute for Health Information (2004) Health Care in Canada. CIHI, Ottawa

    Google Scholar 

  33. The Bristol Royal Infirmary Inquiry: The report of the public inquiry into children’s heart surgery at the Bristol Royal Infirmary 1984–1995. London, UK. 2001

    Google Scholar 

  34. National Health and Hospitals Reform Commission Australia (2009) A healthier future for all Australians final report. Canberra, ACT: Dept. Of Health and Ageing

    Google Scholar 

  35. Winglee M, Valliant R, Scheuren F (2005) A case study in record linkage. Survey Method 31:3–11

    Google Scholar 

  36. Black N, Barker M, Payne M (2004) Cross sectional survey of multicentre clinical databases in the United Kingdom. Br Med J 328:1478

    Article  Google Scholar 

  37. Evans S, Bohensky M, Cameron P, McNeil J (2011) A survey of Australian clinical registries: can quality of care be measured? Intern Med J 41:42–48

    Article  CAS  PubMed  Google Scholar 

  38. Holman CAJ, Bass AJ, Rouse IL, Hobbs MS (1999) Population-based linkage of health records in Western Australia: development of a health services research linked database. Aust N Z J Pub Health 23:453–459

    Article  CAS  Google Scholar 

  39. Chamberlayne R, Green B, Barer ML, Hertzman C, Lawrence WJ, Sheps SB (1997) Creating a population-based linked health database: a new resource for health services research. Can J Pub Health 89:270–273

    Article  Google Scholar 

  40. Hemmelgarn BR, Clement F, Manns BJ, Klarenbach S, James MT, Ravani P et al (2009) Overview of the Alberta kidney disease network. BMC Nephrol 10:30

    Article  PubMed  PubMed Central  Google Scholar 

  41. Acheson E, Evans J (1964) The Oxford record linkage study: a review of the method with some preliminary results. Proc R Soc Med 57:269

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Kendrick S, Clarke J (1993) The Scottish record linkage system. Health Bull (Edinb) 51:72–79

    CAS  Google Scholar 

  43. Conley J, Tonelli M, Quan H, Manns BJ, Palacios-Derflingher L, Bresee LC et al (2012) Association between gfr, proteinuria, and adverse outcomes among White, Chinese, and South Asian individuals in Canada. Am J Kid Dis 59:390–399

    Article  PubMed  Google Scholar 

  44. Samuel SM, Palacios-Derflingher L, Tonelli M, Manns B, Crowshoe L, Ahmed SB et al (2014) Association between first nations ethnicity and progression to kidney failure by presence and severity of albuminuria. Can Med Assoc J 186(2):E86–E94

    Article  Google Scholar 

  45. Deved V, Jette N, Quan H, Tonelli M, Manns B, Soo A et al (2013) Quality of care for first nations and non-first nations people with diabetes. Clin J Am Soc Nephrol 8:1188–1194

    Article  PubMed  PubMed Central  Google Scholar 

  46. Ayyalasomayajula B, Wiebe N, Hemmelgarn BR, Bello A, Manns B, Klarenbach S et al (2011) A novel technique to optimize facility locations of new nephrology services for remote areas. Clin J Am Soc Nephrol 6:2157–2164

    Article  PubMed  PubMed Central  Google Scholar 

  47. Faruque LI, Ayyalasomayajula B, Pelletier R, Klarenbach S, Hemmelgarn BR, Tonelli M (2012) Spatial analysis to locate new clinics for diabetic kidney patients in the underserved communities in Alberta. Neph Dial Transplant 27:4102–4109

    Article  Google Scholar 

  48. Schorr M, Hemmelgarn BR, Tonelli M, Soo A, Manns BJ, Bresee LC (2013) Assessment of serum creatinine and kidney function among incident metformin users. Can J Diabetes 37:226–230

    Article  PubMed  Google Scholar 

  49. Turin TC, Tonelli M, Manns BJ, Ravani P, Ahmed SB, Hemmelgarn BR (2012) Chronic kidney disease and life expectancy. Nephrol Dial Transplant 27:3182–3186

    Article  CAS  PubMed  Google Scholar 

  50. Turin TC, Tonelli M, Manns BJ, Ahmed SB, Ravani P, James M et al (2012) Lifetime risk of ERSD. J Am Soc Nephrol 23:1569–1578

    Article  PubMed  PubMed Central  Google Scholar 

  51. Hemmelgarn BR, James MT, Manns BJ, O’Hare AM, Muntner P, Ravani P et al (2012) Rates of treated and untreated kidney failure in older vs younger adults. J Am Med Assoc 307:2507–2515

    Article  CAS  Google Scholar 

  52. McBrien KA, Manns BJ, Chui B, Klarenbach SW, Rabi D, Ravani P et al (2012) Health care costs in people with diabetes and their association with glycemic control and kidney function. Diab Care 36:1172–1180

    Article  Google Scholar 

  53. Hemmelgarn BR, Manns BJ, Lloyd A, James MT, Klarenbach S, Quinn RR et al (2010) Relation between kidney function, proteinuria, and adverse outcomes. J Am Med Assoc 303:423–429

    Article  CAS  Google Scholar 

  54. Raghupathi W (2010) Data mining in health care. In: Kudyba S (ed) Healthcare informatics: improving efficiency and productivity. Taylor and Francis, Boca Raton, FL, pp 211–223

    Chapter  Google Scholar 

  55. Lynch C (2008) Big data: how do your data grow? Nature 455:28

    Article  CAS  PubMed  Google Scholar 

  56. Kankanhalli A, Hahn J, Tan S, Gao G (2016) Big data and analytics in healthcare: introduction to the special section. Inf Syst Front 18:233–235

    Article  Google Scholar 

  57. Belle A, Thiagarajan R, Soroushmehr SM, Navidi F, Beard DA, Najarian K (2015) Big data analytics in healthcare. Biomed Res Int 2015(370):194

    Google Scholar 

  58. Gandomi A, Haider M (2015) Beyond the hype: big data concepts, methods, and analytics. Internat J Info Man 35:137–144

    Article  Google Scholar 

  59. Bello A, Hemmelgarn B, Manns B, Tonelli M (2012) Use of administrative databases for health-care planning in ckd. Nephrol Dial Transpl 27:iii12–iii18

    Google Scholar 

  60. Shurraw S, Hemmelgarn B, Lin M, Majumdar SR, Klarenbach S, Manns B et al (2011) Association between glycemic control and adverse outcomes in people with diabetes mellitus and chronic kidney disease: a population-based cohort study. Arch Intern Med 171:1920–1927

    Article  PubMed  Google Scholar 

  61. Turin TC, James M, Ravani P, Tonelli M, Manns BJ, Quinn R et al (2013) Proteinuria and rate of change in kidney function in a community-based population. J Am Soc Nephrol 24:1661–1667

    Article  PubMed  PubMed Central  Google Scholar 

  62. Alexander RT, Hemmelgarn BR, Wiebe N, Bello A, Samuel S, Klarenbach SW et al (2013) Kidney stones and cardiovascular events: a cohort study. Clin J Am Soc Nephrol 9:506–512

    Article  PubMed  PubMed Central  Google Scholar 

  63. Tonelli M, Muntner P, Lloyd A, Manns BJ, James MT, Klarenbach S et al (2011) Using proteinuria and estimated glomerular filtration rate to classify risk in patients with chronic kidney disease: a cohort study. Ann Intern Med 154:12–21

    Article  PubMed  Google Scholar 

  64. Chou SH, Tonelli M, Bradley JS, Gourishankar S, Hemmelgarn BR (2006) Quality of care among aboriginal hemodialysis patients. Clin J Am Soc Nephrol 1:58–63

    Article  PubMed  Google Scholar 

  65. Tonelli M, Manns B, Culleton B, Klarenbach S, Hemmelgarn B, Wiebe N et al (2007) Association between proximity to the attending nephrologist and mortality among patients receiving hemodialysis. Can Med Assoc J 177:1039–1044

    Article  Google Scholar 

  66. Ronksley PE, Ravani P, Sanmartin C, Quan H, Manns B, Tonelli M et al (2013) Patterns of engagement with the health care system and risk of subsequent hospitalization amongst patients with diabetes. BMC Health Serv Res 13:399

    Article  PubMed  PubMed Central  Google Scholar 

  67. James MT, Quan H, Tonelli M, Manns BJ, Faris P, Laupland KB et al (2009) CKD and risk of hospitalization and death with pneumonia. Am J Kid Dis 54:24–32

    Article  PubMed  Google Scholar 

  68. Manns B, Hemmelgarn B, Tonelli M, Au F, Chiasson TC, Dong J et al (2010) Population based screening for chronic kidney disease: cost effectiveness study. Br Med J 341:c5869

    Article  Google Scholar 

  69. Hemmelgarn BR, Zhang J, Manns BJ, James MT, Quinn RR, Ravani P et al (2001) Nephrology visits and health care resource use before and after reporting estimated glomerular filtration rate. J Am Med Assoc 303:1151–1158

    Article  Google Scholar 

  70. Manns BJ, Tonelli M, Zhang J, Campbell DJ, Sargious P, Ayyalasomayajula B et al (2012) Enrolment in primary care networks: impact on outcomes and processes of care for patients with diabetes. Can Med Assoc J 184:E144–E152

    Article  Google Scholar 

  71. Hemmelgarn BR, Manns BJ, Straus S, Naugler C, Holroyd-Leduc J, Braun TC et al (2012) Knowledge translation for nephrologists: strategies for improving the identification of patients with proteinuria. J Nephrol 25:933–943

    Article  PubMed  Google Scholar 

  72. Wick JP, Turin TC, Faris PD, MacRae JM, Weaver RG, Tonelli M et al (2017) A clinical risk prediction tool for 6-month mortality after dialysis initiation among older adults. Am J Kid Dis 69:568–575

    Article  PubMed  Google Scholar 

  73. James MT, Pannu N, Hemmelgarn BR, Austin PC, Tan Z, McArthur E et al (2017) Derivation and external validation of prediction models for advanced chronic kidney disease following acute kidney injury. J Am Med Assoc 318:1787–1797

    Article  Google Scholar 

  74. Turin TC, Coresh J, Tonelli M, Stevens PE, de Jong PE, Farmer CKT et al (2012) One-year change in kidney function is associated with an increased mortality risk. Am J Nephrol 36:41–49

    Article  PubMed  Google Scholar 

  75. Turin TC, Coresh J, Tonelli M, Stevens PE, de Jong PE, Farmer CK et al (2012) Short-term change in kidney function and risk of end-stage renal disease. Nephrol Dial Transplant 27:3835–3843

    Article  CAS  PubMed  Google Scholar 

  76. Turin TC, Coresh J, Tonelli M, Stevens PE, de Jong PE, Farmer CK et al (2013) Change in the estimated glomerular filtration rate over time and risk of all-cause mortality. Kidney Int 83:684–691

    Article  CAS  PubMed  Google Scholar 

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Chowdhury, T.T., Hemmelgarn, B.R. (2021). Evidence-Based Decision Making 6: Administrative Databases as Secondary Data Source for Epidemiologic and Health Service Research. In: Parfrey, P.S., Barrett, B.J. (eds) Clinical Epidemiology. Methods in Molecular Biology, vol 2249. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1138-8_26

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  • DOI: https://doi.org/10.1007/978-1-0716-1138-8_26

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