The fragmentation of hospital use among a cohort of high utilizers: Implications for emerging care coordination strategies for patients with multiple chronic conditions

Medical Care

Volumn 52, Issue 3 SUPPL. 2, 2014, Pages

  Hempstead, Katherine ^a,b   DeLia, Derek ^b   Cantor, Joel C ^b   Nguyen, Tuan ^b,c,d   Brenner, Jeffrey ^e  

^a ROBERT WOOD JOHNSON FOUNDATION   (United States)

^b Rutgers University   (United States)

^c RUTGERS UNIVERSITY   (United States)

^d UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^e Camden Coalition of Healthcare Providers   (United States)

Author keywords

Accountable Care Organizations; Care coordination; Delivery reform; High utilizers; Multiple chronic conditions

Indexed keywords

ADULT; CHRONIC DISEASE; COHORT STUDIES; COMORBIDITY; FEMALE; HOSPITALIZATION; HUMANS; LENGTH OF STAY; MALE; MIDDLE AGED; NEW JERSEY; OUTCOME ASSESSMENT (HEALTH CARE); POISSON DISTRIBUTION; QUALITY ASSURANCE, HEALTH CARE; REGRESSION ANALYSIS; RETROSPECTIVE STUDIES; YOUNG ADULT;

EID: 84894482008     PISSN: 00257079     EISSN: 15371948     Source Type: Journal    
DOI: 10.1097/MLR.0000000000000049     Document Type: Article

References (22)

1. Emanuel EJ. Where are the health care cost savings? JAMA. 2012;307:39-40
2. Cohen S, Yu W. The concentration and persistence in the level of health expenditures over time: Estimates for the US population 2008-2009. Statistical Brief #354, January 2012, Agency for Healthcare Research and Quality, Rockville, MD. Available at: http://www.meps.ahrq.gov/mepsweb/data-files/publications/ st354/stat354.pdf. Accessed November 12, 2013
3. Bush H. Tackling the high cost of chronic diseases. Hosp Health Netw. 2012;October:34-40
4. Bush H. Caring for the costliest. Hosp Health Netw. 2012;86:25-29
5. Feigenbaum P, Neuwirth E, Trowbridge L, et al. Factors contributing to all-cause 30- day readmissions: a structured case series across 18hospitals. Med Care. 2012;50:599- 605
6. Jencks SF, Williams MV, Coleman EA. Rehospitalization among patients in the Medicare fee-for-service program. N Engl J Med. 2009; 360:1418-1428
7. IMS Institute for Healthcare Informatics. Healthcare spending among privately insured individual under age 65, February 2012. Available at: http://www.imshealth.com. Accessed November 12, 2013
8. Raven M, Carrier ER, Lee J, et al. Substance use treatment barriers for patients with frequent hospital admissions. J Subst Abuse Treat. 2010;38:22-30
9. Walley AY, Paasche-Orlow M, Lee E, et al. Acute care hospital utilization among medical inpatients discharged with a substance use disorder diagnosis. J Addict Med. 2012;6:50-56
10. Lewis VA, Larson BK, McClurg AB, et al. The promise and peril of accountable care for vulnerable populations: a framework for overcoming obstacles. Health Aff. 2012;31:1777-1785
11. US Census Bureau; 2010 Census Summary File 1; "Profile of General Population and Housing Characteristics," using American FactFinder. Available at: http://factfinder2.census.gov, http://www.census.gov/hhes/www/ cpstables/032012/health/toc.htm. Accessed November 12, 2013
12. Dartmouth Atlas, Hospital Care Intensity Index, by state. Available at http://www.dartmouthatlas.org/data/table. Accessed January 19, 2013
13. Campbell KM. The Link King: Record Linkage and Consolidation Software v6.4. Available at: http://www.the-link-king.com. Accessed November 12, 2013
14. Chronic Condition Indicator (CCI) for ICD-9 CM. H-CUP. Available at: http://www.hcup-us.ahrq.gov/toolssoftware/chronic/chronic.jsp. Accessed November 12, 2013
15. Agency for Healthcare Research and Quality. HCUP Comorbidity Software. Healthcare Cost and Utilization Project (HCUP). Rockville, MD: Agency for Healthcare Research and Quality; 2012. Available at: http://www.hcup- us.ahrq.gov/toolssoftware/comorbidity/comorbidity.jsp.Accessed November 12, 2013
16. Elixhauser A, Steiner C, Harris DR, et al. Comorbidity measures for use with administrative data. Med Care. 1998;36:8-27 (Pubitemid 128456396)
17. Southern DA, Quan H, Ghali WA. Comparison of the elixhauser and Charlson/Deyo methods of comorbidity measurement in administrative data. Med Care. 2004;42:355- 360
18. Li B, Evans D, Faris P, et al. Risk adjustment performance of charlson and elixhauser comorbidities in ICD-9 and ICD-10 administrative databases. BMC Health Serv Res. 2008;8:12. PMCID:PMC2267188
19. Scherer FM, Ross D. Industrial Market Structure and Economic Performance. 3rd Ed. Boston, MA: Houghton Mifflin; 1990
20. Guangyong Z. A modified poisson regression approach to prospective studies with binary data. Am J Epi. 2004;159:702-706
21. Colin CA, Trivedi PK. Regression Analysis of Count Data, Vol. 30. Cambridge University Press; 1998
22. New Jersey Department of Health. NJDDCS version 2 data dictionary, version 12.4. October 1, 2012. Available at: http://www.state.nj.us/health/ healthcarequality/ub/before08/NJDDCS-datadictionary-v12.4.pdf. Accessed November 12, 2013