Diane M. Dewar, PhD University at Albany, State University of New York Jean-Paul Hafner, MD, MPH Stratton VA Medical Cen

1. Survival Analysis of Patients Undergoing Mechanical Ventilation with Tracheostomy in New York State 1992-1996: Does Managed Care Influence Outcome for DRG 483? Diane M. Dewar, PhD University at Albany, State University of New York Jean-Paul Hafner, MD, MPH Stratton VA Medical Center and University at Albany, State University of New York

2. Critical Care Services’ Impact on Health Care Expenditures • Critical care has a significant impact on health care expenditures in the United States • 1-1.5% of gross domestic product • 7-8% of total health care expenditures nationwide • 20-34% of all hospital expenditures • 50% of critical care expenditures are allocated to patients with prolonged mechanical ventilation • only 10% of critical care unit patients have prolonged mechanical ventilation

3. High Costs of Mechanical Ventilation • Nationwide costs for mechanical ventilation in 1999 were in the range of $45 billion • Ventilator dependent patients have costs that are 8-9 times those of medical-surgical floor patients • Growth in utilization of mechanical ventilation is due to increased use among elderly with chronic conditions • leads to the question whether differential utilization of resources and outcomes are age-specific or due to delivery system changes

4. How does Delivery System Changes Affect Health Outcomes? • Managed care delivery is associated with lower levels of critical care resource utilization than traditional delivery and financing • Results are mixed whether reduction is due to financial incentives of managed care organization or severity of illness • Which delivery system, managed care or traditional delivery and financing, is more efficient in utilizing these critical care resources?

5. Study Goals • Study investigates the impact of managed care on hospital survival for critically ill patients requiring mechanically ventilation who are discharged under DRG 483 in New York State during 1992-1996. • Research Questions: • Are improved survival rates among managed care patients due to self-selection or the elimination of ineffective care in the inpatient setting? • Do delivery system changes or clinical characteristics have a greater influence over the health outcomes for this subpopulation?

6. Data Sources • Hospital Characteristics from the Bureau of Health Economics, NYS Department of Health • Teaching status, number of beds, location • State-wide analysis uses New York Statewide Planning and Research Cooperative System (SPARCS) data base for 1992-1996 under all-payer system • Demographic, clinical, discharge disposition and payor data collected for population of 1,456 patients managed care adults and 32,337 non-managed care adults aged 19-95 discharged under from hospitals under DRG 483, “tracheostomy except for mouth, larynx and pharynx disorder”

7. Sample Frame Exclusions • Sample does not include patients: • With pre-existing tracheostomy • Who were over 95 years of age due to small numbers • With hospital stay over 90 days • Biologically implausible that events occurring at the time of tracheostomy would have longer-lasting effects • Discharged after 1996 • No confounding from affects from competitive reimbursement regime under the NY Health Care Reform Act enacted in 1997.

8. Preliminary Statistical Analyses • All conditions and procedures that were present in more than 3.5% of patients were examined with bivariate analysis (2 x 2 contingency tables) to test for an association with mortality • Where possible, similar diagnostic codes were grouped together for the final analysis • Comorbid conditions and procedures associated with a 1.5 times greater risk of mortality than the general subpopulation were obtained from ICD-9 codes (principal and secondary) • Preliminary inpatient survival assessments using Kaplan-Meier curves • Allowed for assessment of proportionality of hazards prior to entry in a multivariate Cox Proportional Hazards Model (PH)

9. --------Preliminary Statistical Analyses • : • age: linear, quadratic and cubic forms • demographics: dummy variables for race, gender, location • clinical risk factors: dummy variables for high frequency and high mortality diagnoses. Disorders of fluid, electrolyte, and acid-based balance, other bacterial pneumonia, pneumonia, organism unspecified, and pleurisy • admission type: dummy variable for emergency, urgent admission • payer classes: dummy variables for payment source (i.e., selfpay, various insurance combinations) • MCO: dummy variable for managed care participation, % MCO in hospital of discharge • HCRA: dummy variable competitive regime enactment • Length of stay • Teaching: teaching status of hospital of discharge

10. Profile of DRG 483 and DRG 475 Hospital Survivors in 1995-1999 in New York State • DRG 483 survivors are more likely to be male, have more elective admissions, and have long hospital stays averaging 63 days. • DRG 475 survivors are more likely to be female, Hispanic, have more emergency admissions, and have moderate hospital stays of 17 days • No statistically significant differences between DRG 483 and DRG 475 survivors in managed care coverage and commercial/self-insurance class, upstate location, and most frequent age range of 36-50

12. Profile of Survivors in DRG 483 and DRG 475 Pre- and Post-NYS Health Care Reform Enactment of 1996 • Pre-HCRA enactment • DRG 483 survivors are equally likely to be MCO and non-MCOs, with 30% of survivors discharged to SNFs • DRG 475 survivors are more likely to be in MCO, with 16% of survivors discharged to SNFs • Post-HCRA enactment • DRG 483 survivors are more likely to be in MCO, with 44% of survivors discharged to SNFs • The greatest proportion of survivors occurs in 1999 • Regardless of MCO status, more survivors are seen post-HCRA • DRG 475 survivors are more likely to be in non-MCO, with 25% of survivors discharged to SNFs • The greatest proportion of survivors occurs in 1997-1999

15. Skilled Nursing Facility Discharge Rates for DRG 483 and DRG 475 by Year

16. Competitive Hospital Reimbursements and Payer Status are Major Determinants of Hospital Survival for DRG 483 • Increased likelihood of survival seen for: • Competitive reimbursement regime • MCO discharges under HCRA • Decreased likelihood of survival seen for: • Medicare payment • Non-elective admissions • Statistically significant predictors but do not contribute to increased risk of survival: • MCO status • Hospital teaching status • Length of stay

17. Competitive Hospital Reimbursements and Payer Status are Major Determinants of Discharges to Skilled Nursing Facilities for DRG483 • Results of two-stage probit model predicting likelihood of SNF discharges for survivors: • Significant increases in likelihood of SNF discharges for: • Competitive reimbursement regime • Medicaid payment • NYC location • Statistically significant predictors but do not contribute to increased risk of discharge location: • MCO status • Length of stay • Est. survival likelihood

18. Clinical Factors are Major Determinants of Hospital Survival for DRG 475 • Increased likelihood of survival seen for: • Non-elective admissions • Chronic airway obstruction • Decreased likelihood of survival seen for: • Most other high-risk diagnose • Statistically significant predictors but do not contribute to increased risk of survival: • Competitive reimbursement regime • MCO status • Hospital teaching status • Length of stay

19. Competitive Hospital Regime and Payer Status are Major Determinants of Discharges to Skilled Nursing Facilities for DRG 475 Survivors • Results of two-stage probit estimation predicting likelihood of SNF discharges for survivors: • Increases in SNF discharges seen for: • Competitive reimbursement regime • Medicaid payment • Hospital volume • Most high-risk diagnoses • Statistically significant predictors but do not contribute to increased risk of discharge location: • MCO status • Length of stay • Est. survival prob.

20. Discussion • Models fit the data well and indicate that competitive hospital market leads to increased shifting to other venues of care for high-cost critical care patients • State-level administrative data can provide indication of impact of system changes on management of patients • Limitations include: • Lack of information concerning specific changes in reimbursement rates by payer under competition • Lack of information concerning intervention by case management and social work to facilitate discharge planning • Unclear what proportion of discharges to other venues are clinically appropriate or due to cost pressures

21. Clinical Excellence must be Combined with Cost Control • Managed care does not uniquely impact the likelihood of survival nor skilled nursing facility discharges for survivors among DRG 483 and DRG 475 discharges • No unique evidence that managed care preferentially selects patients nor favorably manages discharges on the state-level • Competitive reimbursement regime under HCRA of 1996 indicates trends of increased hospital survival and increased cost-shifting to skilled nursing facilities for survivors among both DRGs • Differential reimbursements under Medicare for hospital and skilled nursing facilities may lead to increased discharges for LTC settings under competition • Critical care services delivered to older persons with chronic illness are facing greater scrutiny but clinical outcomes also need to be considered • more emphasis should be placed on multidisciplinary management teams