A methodological approach for register-based evaluation of cost and outcomes in health care

References

• Wray NP, Ashton CM, Kuykendall DH, Hollingsworth JC. Using administrative databases to evaluate the quality of medical care: A conceptual framework. Soc Sci Med. 1995;40:1707–15.
   PubMedGoogle Scholar
• de Pouvourville G, Minvielle É. Measuring the quality of hospital care: The state of the art. What information should be made available to the public? Measuring Up: Improving Health System Performance in OECD Countries Paris: Organisation for Economic Co-operation and Development; 2002. 251–75.
   Google Scholar
• Iezzoni LI. Reinvigorating the quality improvement incentives of hospital prospective payment. Med Care. 2009;47: 269–71.
   PubMedGoogle Scholar
• Terris DD, Aron DC. Attribution and causality in health-care performance measurement. Smith PC, Mossialos E, Papanicolas I, Leatherman S. Performance Measurement for Health System Improvement: Experiences, Challenges, and Prospects. Cambridge: Cambridge University Press; 2009. 311–38.
   Google Scholar
• Gissler M, Haukka J. Finnish health and social welfare registers in epidemiological research. Norsk Epidemiologi. 2004;14:113–20.
   Google Scholar
• Haukka J, Suvisaari J, Tuulio-Henriksson A, Lonnqvist J. High concordance between self-reported medication and official prescription database information. Eur J Clin Pharmacol. 2007;63:1069–74.
   PubMed Web of Science ®Google Scholar
• Rikala M, Hartikainen S, Sulkava R, Korhonen MJ. Validity of the Finnish Prescription Register for measuring psychotropic drug exposures among elderly finns: a population-based intervention study. Drugs Aging 2010;27: 337–49.
   PubMed Web of Science ®Google Scholar
• Lahti RA, Penttila A. The validity of death certificates: routine validation of death certification and its effects on mortality statistics. Forensic Sci Int. 2001;115:15–32.
   PubMed Web of Science ®Google Scholar
• Gissler M, Shelley J. Quality of data on subsequent events in a routine Medical Birth Register. Med Inform Internet Med. 2002;271:33–8.
   Google Scholar
• Jämsen E, Huotari K, Huhtala H, Nevalainen J, Konttinen YT. Low rate of infected knee replacements in a nationwide series – is it an underestimate? Acta Orthop. 2009;802: 205–12.
   Google Scholar
• Pajunen P, Koukkunen H, Ketonen M, Jerkkola T, Immonen-Raiha P, Karja-Koskenkari P, . The validity of the Finnish Hospital Discharge Register and Causes of Death Register data on coronary heart disease. Eur J Cardiovasc Prev Rehabil. 2005;12:132–7.
   PubMed Web of Science ®Google Scholar
• Tolonen H, Salomaa V, Torppa J, Sivenius J, Immonen-Raiha P, Lehtonen A, . The validation of the Finnish Hospital Discharge Register and Causes of Death Register data on stroke diagnoses. Eur J Cardiovasc Prev Rehabil. 2007;14: 380–5.
   PubMedGoogle Scholar
• Sund R, Nurmi-Luthje I, Luthje P, Tanninen S, Narinen A, Keskimaki I. Comparing properties of audit data and routinely collected register data in case of performance assessment of hip fracture treatment in Finland. Methods Inf Med. 2007;46:558–66.
   PubMed Web of Science ®Google Scholar
• Pihlajamaa J, Suvisaari J, Henriksson M, Heila H, Karjalainen E, Koskela J, . The validity of schizophrenia diagnosis in the Finnish Hospital Discharge Register: findings from a 10-year birth cohort sample. Nord J Psychiatry. 2008;62:198–203.
   PubMed Web of Science ®Google Scholar
• Sund R. Methodological perspectives for register-based health system performance assessment – Developing a hip fracture monitoring system in Finland. Helsinki: Stakes, 2008. Research Report. 174.
   Google Scholar
• Jacobzone S. Introduction to the ageing-related diseases project. A Disease-based Comparison of Health Systems Paris: Organisation for Economic Co-operation and Development; 2003. 11–26.
   Google Scholar
• Solon JA, Feeney JJ, Jones SH, Rigg RD, Sheps CG. Delineating episodes of medical care. Am J Pub Health. 1967;57:401–8.
   PubMed Web of Science ®Google Scholar
• Rosen AK, Mayer-Oakes A. Episodes of care: theoretical frameworks versus current operational realities. Jt Comm J Qual Improv. 1999;25:111–28.
   PubMedGoogle Scholar
• Sund R. Utilisation of administrative registers using scientific knowledge discovery. Intel Data Analysis. 2003;7: 501–19.
   Google Scholar
• Rosen AAB, Cutler DM. Challenges in building disease-based national health accounts. Med Care. 2009;47 (supplement):S7–S13.
   PubMedGoogle Scholar
• Hujanen T. Terveydenhuollon yksikkökustannukset Suomessa vuonna 2001. Stakes, Aiheita 1, 2003 [in Finnish].
   Google Scholar
• Sund R, Juntunen M, Lüthje P, Huusko T, Häkkinen U. Monitoring the performance of hip fracture treatment in Finland. Ann Med. 2011;43:S39–46.
   PubMed Web of Science ®Google Scholar
• Häkkinen U, Hartikainen J, Juntunen M, Peltola M, Tierala I. Analysing current trends in care of acute myocardial infarction using PERFECT data. Ann Med. 2011;43:S14–21.
   PubMed Web of Science ®Google Scholar
• de Groot V, Beckerman H, Lankhorst GJ, Bouter LM. How to measure comorbidity: a critical review of available methods. J Clin Epidemiol. 2003;56:221–9.
   PubMed Web of Science ®Google Scholar
• Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi JC, . Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005;43:1130–9.
   PubMed Web of Science ®Google Scholar
• Holman CD, Preen DB, Baynham NJ, Finn JC, Semmens JB. A multipurpose comorbidity scoring system performed better than the Charlson index. J Clin Epidemiol. 2005;58:1006–14.
   PubMedGoogle Scholar
• Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36:8–27.
   PubMed Web of Science ®Google Scholar
• Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chron Dis. 1987;40: 373–83.
   PubMedGoogle Scholar
• Maio V, Yuen E, Rabinowitz C, Louis D, Jimbo M, Donatini A, . Using pharmacy data to identify those with chronic conditions in Emilia Romagna, Italy. J Health Serv Res Policy. Policy 2005;10:232–8.
   PubMedGoogle Scholar
• Lamers LM, van Vliet RC. The Pharmacy-based Cost Group model: validating and adjusting the classification of medications for chronic conditions to the Dutch situation. Health Policy. 2004;68:113–21.
   PubMed Web of Science ®Google Scholar
• Naughton C, Bennett K, Feely J. Prevalence of chronic disease in the elderly based on a national pharmacy claims database. Age Ageing. 2006;35:633–6.
   PubMed Web of Science ®Google Scholar
• Drösler S, Romano P, Wei L. Health care quality indicators project: Patient safety indicators report 2009. Directorate For Employment, Labour And Social Affairs Health Committee. Paris: OECD, 2009;47.
   Google Scholar
• DeLong EER, Peterson ED, DeLong DM, Muhlbaier LH, Hackett S, Mark DB. Comparing risk-adjustment methods for provider profiling. Stat Med. 1997;16:2645–64.
   PubMed Web of Science ®Google Scholar
• Iezzoni LI. Risk Adjustment for Measuring Healthcare Outcomes. 3rd. Chigago: Health Administration Press; 2003.
   Google Scholar
• Newhouse JP, McClellan M. Econometrics in outcomes research: the use of instrumental variables. Annu Rev Public Health. 1998;19:17–34.
   PubMed Web of Science ®Google Scholar
• Rubin DB. Estimating causal effects from large data sets using propensity scores. Ann. Intern. Med. 1997;127:757–63.
   PubMed Web of Science ®Google Scholar
• Brand DA, Quam L, Leatherman S. Medical practice profiling: concepts and caveats. Med Care Res Rev. 1995;52: 223–51.
   PubMedGoogle Scholar
• Goldstein H, Spiegelhalter DJ. League tables and their limitations: statistical issues in comparisons of institutional performance. J Royal Stat Soc: Series A (Statistics in Society) 1996;159:385–443.
   Web of Science ®Google Scholar
• Christiansen CL, Morris CN. Improving the statistical approach to health care provider profiling. Ann Intern Med. 1997;127:764–8.
   PubMed Web of Science ®Google Scholar
• Normand ST, Glickman ME, Gatsonis CA. Statistical methods for profiling providers of medical care: issues and applications. J Am Stat Assoc. 1997;92:803–14.
   Web of Science ®Google Scholar
• DeLong ER, Peterson ED, DeLong DM, Muhlbaier LH, Hackett S, Mark DB. Comparing risk-adjustment methods for provider profiling. Stat Med. 1997;16:2645–64.
   PubMed Web of Science ®Google Scholar
• Burgess JF Jr, Christiansen CL, Michalak SE, Morris CN. Medical profiling: improving standards and risk adjustments using hierarchical models. J Health Econ. 2000;19: 291–309.
   PubMed Web of Science ®Google Scholar
• Ohlssen DI, Sharples LD, Spiegelhalter DJ. A hierarchical modelling framework for identifying unusual performance in health care providers. J Royal Stat Soc: Series A (Statistics in Society) 2007;170:865–90.
   Web of Science ®Google Scholar
• Howley PP, Gibberd R. Using hierarchical models to analyse clinical indicators: a comparison of the gamma-Poisson and beta-binomial models. Int J Qual Health Care. 2003;15:319–29.
   PubMedGoogle Scholar
• Marshall EC, Spiegelhalter DJ. Institutional performance. Leyland A, Goldstein H. Multilevel Modelling of Health Statistics Chichester: John Wiley & Sons; 2001. 127–42.
   Google Scholar
• Ash AS, Shwartz M, Peköz EA. Comparing outcomes across providers. Iezzoni LI. Risk adjustment for measuring health care outcomes. 3rd. Chicago: Health Administration Press; 2003. 297–333.
   Google Scholar
• Keskimäki I, Aro S. Accuracy of data on diagnoses, procedures and accidents in the Finnish Hospital Discharge Register. Int J Health Sci. 1991;2:15–21.
   Google Scholar
• Juntunen M, Sund R, Peltola M, Häkkinen U. Potilasrakenteen erojen huomioon ottaminen erikoissairaanhoidon vaikuttavuuden rekisteritutkimuksessa. Sosiaalilääk Aikak. 2008;45:258–72.
   Google Scholar