Economic Impact Analysis of Hospital Readmission Rate and Service Quality Using Machine Learning

bailek, Alexandra (2018): Economic Impact Analysis of Hospital Readmission Rate and Service Quality Using Machine Learning. Published in:

Abstract

The hospital readmission rate has been proposed as an important outcome indicator computable from routine statistics. The purpose of this research is to investigate the Economic Impact of service in hospitals and integrated delivery networks in the United States based on the readmission rates as the target variable. The data set includes information from 130 hospitals and integrated delivery networks in the United States from 1999 to 2008 to investigate significance of different factors in readmission rate. The dataset contains 101,766 patients’ encounters and 50 variables. The 30-day readmission rate is considered as an indicator of the quality of the health providers and is used as target variable in this project. Preliminary data analysis shows that age, admission type, discharge disposition etc. is correlated to the readmission rate and will be incorporated for further data analysis. Data analysis are performed on the diabetic patient dataset to develop a classification model to predict the likelihood for a discharged patient to be readmitted within 30 days. KNN, Naive Bayes and Logistic Regression algorithm were used to classify data and KNN appears to be the best approach to develop the model. Hospitalisations and drug prescriptions accounted for 50% and 20% of total readmission expenditure, respectively. Long term nursing home care after hospital admission cost an additional £46.4 million. With the ability to identify those patients who are more likely to be readmitted within 30 days, we can deploy the hospital resources more economically affordable while improving services. Based on the results it can be concluded that the direct cost of readmission rate for hospitals rose to £459 million in 2000 and nursing home costs rose to £111 million. Also, it can be perceived that a reduced length of hospital stay was associated with increased readmission rates for jaundice and dehydration.

• Item Type: MPRA Paper
• Language: English
• Keywords: Predictive Modeling, Re-admission, Simulation, Healthcare Service, Classification Modeling, Health care Quality Indicator
• Subjects: A - General Economics and Teaching > A1 - General Economics; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C11 - Bayesian Analysis: General; C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C55 - Large Data Sets: Modeling and Analysis

References

Hofer, T. P., & Hayward, R. A. (1995, March). Can Early Re-Admission Rates Accurately Detect Poor-Quality Hospitals? Journal Storage (JSTOR), 33(3), 234-245. Retrieved April 13, 2017, from http://www.jstor.org/stable/3766825

Strack, B., DeShazo, J. P., Gennings, C., Olmo, J. L., Ventura, S., Cios, K. J., & Clore, J. N. (2014, April 3). Impact of HbA1c Measurement on Hospital Readmission Rates: Analysis of 70,000 Clinical Database Patient Records. BioMed Research International, 1-11. doi:https://www.hindawi.com/journals/bmri/2014/781670/

Rontal R, Kiess MJ, DesHarais S, Reutter K. Applications for risk-adjusted outcome measures. Qual Assur Health Care 1991; 3:243.

Brook RH, Lohr KN. Monitoring quality of care in the Medicare program. JAMA 1987; 258:313.

Holloway JJ, Thomas JW. Factors influencing readmission risk: implications for quality monitoring. Health Care Financ Rev 1989; 11:19.

Sisk JE, Dougherty DM, Ehrenhaft PM, Ruby G, Mitchner BA. Assessing information for consumers on the quality of medical care. Inquiry 1990; 27:263.

Pallarito K. Expert sees quality of care becoming important factor in hospital credit ratings. Modern Healthcare 1990; 20:48

Perry L. Michigan Blues plan initiates bonuses penalties ties tied to standards of quality. Modern Healthcare 1989;19:58.

M. A. Zaman, Bicubic L 1 Spline Fits for 3D Data Approximation (Master's thesis), 2018.

Moraga, R., & Rabiei Hosseinabad, E. (2017). A System Dynamics Approach in Air Pollution Mitigation of Metropolitan Areas with Sustainable Development Perspective: A Case Study of Mexico City. Journal of Applied Environmental and Biological Sciences, 164-174.

Hosseinabad E. R., Moraga R. J. (2017). Air Pollution Mitigation in Metropolitans Using System Dynamics Approach, Institute of Industrial and Systems Engineers (IISE), pp.638-643, Retrieved from http://www.sustainableengineer.org/air-pollution-mitigation-in-metropolitans-using-system-dynamics-approach/.

Feili, H. R., Ahmadian, P., & Rabiei Hosseinabad, E. (2014). Life Cycle Assessment Of Municipal Solid Waste Systems To Prioritize And Compare Their Methods With Multi-Criteria Decision Making. The Open Access Journal of Resistive Economics (OAJRE), 39.

Feldstein, M. S. (1971). Hospital cost inflation: A study of nonprofit price dynamics. The American Economic Review, 61(5), 853-872.

Zaman, M. A. U., Parmer, A. B., & Naghdi, S. (2018). Design of Experiments on Grass Growth in Controlled Environment.