Reducing Hospital Readmission Risk Using Predictive Analytics

Published Online:https://doi.org/10.1287/inte.2022.0086

References

  • Andritsos DA, Tang CS (2018) Incentive programs for reducing readmissions when patient care is co-produced. Production Oper. Management 27(6):999–1020.Google Scholar
  • Artetxe A, Beristain A, Graña M (2018) Predictive models for hospital readmission risk: A systematic review of methods. Comput. Methods Programs Biomed. 164:49–64.Google Scholar
  • Auerbach A, Kripalani S, Vasilevskis E (2016) Preventability and causes of readmissions in a national cohort of general medicine patients. JAMA Intern. Med. 176(4):484–493.Google Scholar
  • Benchoff B, Arai Yano C, Newman A (2017) Kaiser Permanente Oakland medical center optimizes the operating room block schedule for New Hospital. Interfaces 47(3):214–229.LinkGoogle Scholar
  • Brock J, Mitchell J, Irby K (2013) Association between quality improvement for care transitions in communities and rehospitalizations among Medicare beneficiaries. JAMA 309(4):381–391.Google Scholar
  • Bumblauskas D, Igou A, Kalghatgi S, Wetzel C (2022) Public policy and broader applications for the use of text analytics during pandemics. INFORMS J. Appl. Analytics 52(6):568–581.LinkGoogle Scholar
  • Cheng G, Gao SY, Yuan Y, Zhang C, Zheng Z (2022) On the test accuracy and effective control of the COVID-19 pandemic: A case study in Singapore. Informs J. Appl. Analytics 52(6):524–538.LinkGoogle Scholar
  • Dharmarajan K, Hseih AF, Lin Z (2013) Diagnosis and timing of 30-day readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia. JAMA 309(4):355–363.Google Scholar
  • Donze J, Aujesky D, Williams D, Schnipper J (2013) Potentially avoidable 30-day hospital readmissions in medical patients. JAMA Intern. Med. 173(8):632–638.Google Scholar
  • Futoma J, Morris J, Lucas J (2017) A comparison of models for predicting early hospital readmissions. J. Biomed. Informatics 64:17–29.Google Scholar
  • Gouglas D, Hoyt K, Peacocke E, Kaloudis A, Ottersen T, Rottingen J (2019) Setting strategic objectives for the Coalition for Epidemic Preparedness Innovations: An exploratory decision analysis process. INFORMS J. Appl. Analytics 49(6):430–446.LinkGoogle Scholar
  • Harrell F (2015) Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis (Springer, New York).Google Scholar
  • Heins J, Schoenfelder J, Heider S, Heller AR, Brunner JO (2022) A scalable forecasting framework to predict COVID-19 hospital bed occupancy. INFORMS J. Appl. Analytics 52(6):508–523.LinkGoogle Scholar
  • Jamei M, Nisnevich A, Wetchler E, Sudat S, Liu E (2017) Predicting all-cause risk of 30-day hospital readmission using artificial neural networks. PLoS One 12(7):e0181173.Google Scholar
  • Kaparthi S, Bumblauskas D (2020) Designing predictive maintenance systems using decision tree-based machine learning techniques. Internat. J. Qual. Reliab. Management 37(4):659–686.Google Scholar
  • Lee EK, Atallah HY, Wright MD, Post ET, Thomas C IV, Wu DT, Haley LL Jr (2015) Transforming hospital emergency department workflow and patient care. Interfaces 45(1):58–82.LinkGoogle Scholar
  • Lee EK, Helder I, Nakaya Yuan F, Querec TD, Burel G, Pietz FH, Benecke BA, Pulendran B (2016) Machine learning for predicting vaccine immunogenicity. Interfaces 46(5):368–390.LinkGoogle Scholar
  • Litjens G, Kooi T, Bejnordi BE, Setio AAA, Ciompi F, Ghafoorian M, van der Laak JAWM, van Ginneken B, Sanchez CI (2017) A survey on deep learning in medical image analysis. Med. Image Anal. 42:60–88.Google Scholar
  • McCarthy D, Johnson MB, Audet A-M (2013) Recasting readmissions by placing the hospital role in a community context. JAMA 309(4):351–352.Google Scholar
  • Meddings J, Reichert H, Smith SN, Iwashyna TJ, Langa KM, Hofer TP, McMahon LF (2016) The impact of disability and social determinants of health on condition-specific readmissions beyond Medicare risk adjustments: A cohort study. J. Gen. Intern. Med. 32(1):71–80.Google Scholar
  • Miotto R, Wang F, Wang S, Jiang X, Dudley JT (2017) Deep learning for healthcare: Review, opportunities, and challenges. Brief. Bioinform. 19(6):1236–1246.Google Scholar
  • Morgan DJ, Bame B, Zimand P, Dooley P, Thom KA, Harris AD, Bentaen S, et al. (2019) Assessment of machine learning vs standard prediction rules for predicting hospital readmissions. JAMA Netw. Open. 2(3):e190348.Google Scholar
  • Queenan C, Cameron K, Snell A, Smalley J, Joglekar N (2019) Patient heals thyself: Reducing hospital readmissions with Technology Enabled continuity of care and patient activation. Production Oper. Management 28(11):2841–2853.Google Scholar
  • Rodriguez F, Scheinker D, Harrington RA (2018) Promise and perils of big data and artificial intelligence in clinical medicine and biomedical research. Circ. Res. 123(12):1282–1284.Google Scholar
  • Scheinker D, Brandeau ML (2020) Implementing analytics projects in a hospital: Successes, failures, and opportunities. Interfaces 50(3):176–189.Google Scholar
  • Senot C (2019) Continuity of care and risk of readmission: An investigation into the healthcare journey of heart failure patients. Production Oper. Management 28(8):2008–2030.Google Scholar
  • Smalley HK, Keskinocak P, Vats A (2015) Physician scheduling for continuity: An application in pediatric intensive care. Interfaces 45(2):133–148.LinkGoogle Scholar
  • van de Kracht T, Heragu SS (2020) Lessons from modeling and running the world’s largest drive-through mass vaccination clinic. INFORMS J. Appl. Analytics 51(2):91–105.Google Scholar
  • van Walraven C, Dhalla IA, Bell C, Etchells E, Stiell IG, Zarnke K, Austin PC, Forster AJ (2010) Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community. CMAJ 182(6):551–557.Google Scholar
  • Vashi AA, Fox JP, Carr BG, D’Onofrio G, Pines JM, Ross JS, Gross CP (2013) Use of hospital-based acute care among patients recently discharged from the hospital. JAMA 309(4):364–371.Google Scholar
  • Wang H, Robinson R, Johnson C, Zenarosa N, Jayswal R, Keithley J, Delaney K (2014) Using the LACE index to predict hospital readmissions in congestive heart failure patients. BMC Cardiovasc. Disord. 14:97.Google Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.