Affordable care act: Predictive modeling challenges and opportunities for case management

Professional Case Management

Volumn 17, Issue 1, 2012, Pages 15-21

  Meek, Julie A ^a  

^a INDIANA UNIVERSITY   (United States)

Author keywords

Affordable Care Act; case management; future trends; predictive modeling

Indexed keywords

ACCOUNTABLE CARE ORGANIZATION; AGED; ARTICLE; CASE MANAGEMENT; CASE REPORT; HEALTH CARE POLICY; HUMAN; LEADERSHIP; LEGAL ASPECT; MALE; MEDICAL INFORMATICS; METHODOLOGY; NONBIOLOGICAL MODEL; NURSING INFORMATICS; ORGANIZATION; ORGANIZATION AND MANAGEMENT; THEORETICAL MODEL; UNITED STATES;

ACCOUNTABLE CARE ORGANIZATIONS; AGED, 80 AND OVER; CASE MANAGEMENT; HUMANS; LEADERSHIP; MALE; MEDICAL INFORMATICS; MODELS, ORGANIZATIONAL; MODELS, THEORETICAL; NURSING INFORMATICS; ORGANIZATIONAL CULTURE; PATIENT PROTECTION AND AFFORDABLE CARE ACT; UNITED STATES;

EID: 83155184568     PISSN: 15297764     EISSN: 15390675     Source Type: Journal    
DOI: 10.1097/NCM.0b013e318234e7dd     Document Type: Article

References (15)

1. Coleman, E. A., Mahoney, E., & Parry, C. (2005). Assessing the quality of preparation for post hospital care from the patient's perspective: The Care Transitions Measure. Medical Care, 43(3), 246-255. (Pubitemid 40353908)
2. Cousins, M. S. (2002). Predictive modeling for disease management risk stratifi cation. Disease Management, 5(3), 3-4.
3. Fisher, E. S., & Shor tell, S. M. (2010). Accountable care organizations: accountable for what, to whom, and how. JAMA, 304(15), 1715-1716.
4. Ghali, W. A., Hall, R. E., Rosen, A. K., Ash, A. S., & Moskow-itz, M. A. (1996). Searching for an improved comorbidity index for use with ICD-9-CM administrative data. Journal of Clinical Epidemiology, 49(3), 273-278. (Pubitemid 26149646)
5. Health Management Technology. (2011). Our experts cast their eyes toward the future of healthcare IT. Health Management Technology, 32(1), 1.
6. Iezzoni, L. I., Ash, A. S., Coffman, G. A., & Moskowitz, M. A. (1992). Predicting in-hospital mortality: A comparison of severity measurement approaches. Medical Care, 30(4), 347-359.
7. Institute of Medicine. (2010). The future of nursing: Leading change, advancing health. Washington DC: The National Academies Press.
8. Meek, J. A. (2003a). Predictive modeling and proactive care management: Part I. Lippincott's Case Management, 8(4), 170-174.
9. Meek, J. A. (2003b). Increasing return on investment potential in care management: Predictive modeling and proactive care management: Part II. Lippincott's Case Management, 8(5), 198-202.
10. Meek, J. A., & Citrin, R. S. (2005). Predictive modeling and its application to disease and case management. In D. L. Huber (Ed.), Disease management: A guide for case managers (pp. 21-31). St. Louis, MO: Elsevier Saunders Publishing.
11. Meek, J. A., Lyon, B. L., May, F. E., & Lynch, W. D. (2000). Targeting high utilizers: Predictive validity of a screening questionnaire. Disease Management & Health Outcomes, 8(4), 223-232.
12. Rosen, A. K., Ash, A. S., McNiff, K. J., & Moskowitz, M. A. (1995). The importance of severity of illness adjustment in predicting adverse outcomes in the Medicare population. Journal of Clinical Epidemiology, 48(5), 631-643.
13. The Care Transitions ProgramSM. (2011). Care Transitions Intervention®: Overview. Retrieved August 16, 2011, from http://www.caretransit ions.org/overview.asp
14. U.S. Department of Health and Human Services, National Institutes of Health. (2011a). Understanding the Affordable Care Act. Retrieved July 12, 2011, from http://www.healthcare.gov/law/about/index.html
15. U.S. Department of Health and Human Services, National Institutes of Health. (2011b). Electronic health records and meaningful use . Retrieved June 6, 2010, from http://healthit.hhs.gov/portal/server. pt?open=512&objID= 2996&mode=2