Ronald Lagoe^1*, Mark Murphy², Shelly Littau¹

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¹ Hospital Executive Council, Syracuse, NY, USA.
² St. Joseph’s Hospital Health Center, Syracuse, NY, USA.
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Abstract: Hospital admission/discharges rates are generating increased attention from health care providers and payors. This study focused on evaluation of inpatient hospital admission/discharge rates for Syracuse and other New York State metropolitan areas during 2014 and 2015. It provided comparative information concerning this subject and suggested how this approach to analysis of hospital utilization could be carried out using publicly available data. The study data demonstrated that hospital admission/discharge rates per 1000 population increased with patient age in all of these areas. The study data suggested that differences in hospital admission/discharge rates among the New York State metropolitan areas were generally consistent between 2014 and 2015. Utica and New York City produced the highest rates. Rochester and Albany produced the lowest rates. Utilization rates for Syracuse were considerably lower than for Utica and New York City and slightly higher than for Rochester and Albany. This analysis demonstrated that most of the differences between aggregate rates for Syracuse and Rochester were produced by elderly patients, especially those aged 75 years and over. The analysis demonstrated that most of these differences in admission rates for the elderly were produced by adult medicine patients aged 75 years and over. Most of these differences were generated by patients with respiratory, digestive, and orthopedic disorders. Additional data suggested that the highest readmission rates for adult medicine and adult surgery were produced by patients aged 75 years and over.

Keywords: Hospitals, Hospitalization, Hospital Admissions

Cite this paper: Lagoe, R. , Murphy, M. and Littau, S. (2016) Evaluating Hospital Admission/Discharge Rates at the Community Level. International Journal of Clinical Medicine, 7, 608-619. doi: 10.4236/ijcm.2016.79067.

References

[1]   Dentzler, S. (2011) Urgent Measures for an Old Problem. Health Affairs, 30, 1626.
http://dx.doi.org/10.1377/hlthaff.2011.0961

[2]   Friedman, B., De La Mare, J., Andrews, R. and McKenzie, D.H. (2002) Practical Options for Estimating the Costs of Hospital Stays. Journal of Health Care Finance, 291, 1-12.

[3]   Cushing, W.T. (2004) Extra Hospital Days Can Cost You Plenty. Medical Economics, 81, 83.

[4]   Chassin, M.R., Brook, R.H., Park, R.E., Kessey, J., Fink, A., Kahn, K., Merrick, N. and Solomon, D.H. (1986) Variations in the Use of Medical and Surgical Services by the Medicaid Population. New England Journal of Medicine, 315, 285-290.
http://dx.doi.org/10.1056/NEJM198601303140505

[5]   Tedeschi, P.I., Wolfe, R.A. and Griffith, J.R. (1990) Micro Area Variation in Hospital Use. Health Services Research, 24, 729-740.

[6]   Knickman, J.R. and Foltz, A.M. (1985) A Statistical Analysis of Reasons for East West Differences in Hospital Use. Inquiry, 22, 45-58.

[7]   Barr, P. (2015) Three Practical Approaches to Population Health. Hospitals and Health Networks, 89, 22-27.

[8]   Toone, K. and Muhlstein, D. (2015) MACRA: Quality Incentives, Provider Considerations, and the Path Forward. Leavitt Partners, New York.

[9]   Skinner, J., Chandra, A., Goodman, D. and Fisher, E.S. (2009) The Elusive Connection between Health Care Spending and Quality. Health Affairs, 28, 1256-1258.
http://dx.doi.org/10.1377/hlthaff.28.1.w119

[10]   Weil, A.R. (2015) Hospital Costs and Quality. Health Affairs, 34, 1263.
http://dx.doi.org/10.1377/hlthaff.2015.0786

[11]   Rau, J. (2012) Medicare to Penalize 2211 Hospitals for Excess Readmissions. Kaiser Health News.

[12]   Goldfield, N.I., McCullough, E.C., Hughes, J.S., Tang, A.M., Eastman, B., Rawlins, L.K. and Averill, R.F. (2009) Identifying Potentially Preventable Readmissions. Health Care Financing Review, 30, 75-92.

[13]   Fuller, R.L.; McCullough, E.C., Bao, M.Z. and Averill, R.F. (2009) Estimating the Costs of Potentially Preventable Hospital Acquired Complications. Health Care Financing Review, 30, 17-32.

[14]   Evans, M. (2012) The Early Returns on Accountable Care. Modern Healthcare, 42, S1-S5.

[15]   Fisher, E.E., Shortell, S.M., Kriendler, S.A., Van Citters, A.D. and Larson, B.K. (2012) A Framework for Evaluating the Formation and Implementation of Accountable Care Organizations. Health Affairs, 31, 2368-2378.
http://dx.doi.org/10.1377/hlthaff.2012.0544

[16]   Burke, G.C. and Brundage, S.C. (2016) Performance of New York’s Accountable Care Organizations in Year 2 of the Medicare Shared Savings Program. United Hospital Fund, New York.

[17]   Barkholz, D. (2016) Under Construction: Risk-Based Reimbursement. Modern Healthcare, 46, 14-18.

[18]   Lagoe, R., Pasinski, T., Kronenberg, P., Quinn, T., Schaengold, P. (2006) Linking Health Services at the Community Level. Canada Healthcare Quarterly, 9, 60-65.
http://dx.doi.org/10.12927/hcq..18229

[19]   3M Health Information Systems (1998) All Patient Refined Diagnosis Related Groups (APR-DRGs). 3M Health Information Systems, Wallingford.