Introduction to Ranking Models - Text Mining Techniques for Healthcare Provider Quality Determination - page 32

Monami, M., Lambertucci, L., Lamanna, C., Lotti, E., Marsili, A., & Masotti, G. (2007). Are comorbidity
indices useful in predicting all-cause mortality in Type 2 diabetic patients? Comparison between Charlson
index and disease count. Aging Clinical and Experimental Research , 19 (6), 492-496.
Moran, J. L., Bristow, P., Solomon, P. J., George, C., & Hart, G. K. (2008). Mortality and length-of-stay
outcomes, 1993-2003, in the binational Australian and New Zealand intensive care adult patient database.
Critical Care Medicine , 36 (1), 46-61.
Nattinger, A. B., Laud, P. W., & Rut Bajorunaite, R. A. S., Jean L Freeman. (2004). An algorithm for the
use of Medicare claims data to identify women with incident breast cancer. Health Services Research,
39 (6 (part 1)), 1733-1749.
Norton, E. C., Garfinkel, S. A., McQuay, L. J., Heck, D. A., Wright, J. G., Dittus, R., & Lubitz, R. M.
(1998). The effect of hospital volume on the in-hospital complication rate in knee replacement patients.
Health Services Research , 33 (5), 1191-1210.
O'Connell, R., & Lim, L. (2000). Utility of the Charlson comorbidity index computed from routinely
collected hospital discharge diagnosis codes. Methods of Information in Medicine , 39 (1), 7-11.
O'Leary, J., Keeler, E. B., Damberg, C., & Kerr, E. A. (1998). An Overview of Risk Adjustment. In
Health Information Systems: Design Issues and Analytic Applications (pp. 1-37). Santa Monica, CA:
Rand Corporation.
Odueyungbo, A., Browne, D., Akhtar-Danesh, N., & Thabane, L. (2008). Comparison of generalized
estimating equations and quadratic inference functions using data from the Nationalo Longitudinal Survey
of Children and Youth (NLSCY) database. BMC Medical Research Methodology , 8 (28), 1-10.
Raaijmakers, R., Noordam, C., Karagiannis, C., Gregory, G., Hertel, J., & Sipila, N. (2008). Response
to growth hormone treatment and final height in Noonan syndrom in a large cohort of patients in the
KIGS database. Journal of Pediatric Endocrinology & Metabolism , 21 (3), 267-273.
Reilly, J. J., Chin, B., Berkowitz, J., Weedon, J., & Avitable, M. (2003). Use of a state-wide administrative
database in assessing a regional trauma system: the New York City experience. Journal of the American
College of Surgeons , 198 , 509-518.
Rochon, P., Katz, J., Morrow, L., McGlinchey-Berroth, R., Ahlquist, M., & Sarkarati, M. (1996). Co-
morbid illness is associated with survival and length of hospital stay in patients with chronic disability.
A prospective comparison of three comorbidity indices. Medical Care , 34 (11), 1093-1100.
Rosen, A. K., Reid, R., Broemeling, A.-M., & Rakovski, C. C. (2003). Applying a Risk-Adjustment
Framework to Primary Care: Can We Improve on Existing Measures? Annals of Family Medicine , 1 ,
44-51.
Sabate, J. (1999). Nut consumption, vegetarian diets, ischemic heart disease risk, and all-cause mor-
tality: evidence from epidemiologic studies. The American Journal of Clinical Nutrition , 70 (Suppl),
500S-503S.
Schlenker, R. E., Powell, M. C., & Goodrich, G. K. (2005). Initial Home Health Outcomes Under Pro-
spective Payment. Health Services Research , 40 (1), 177-193.