121
Views
0
CrossRef citations to date
0
Altmetric
Research Articles

Empirical analysis of the impact of collaborative care in internal medicine: Applications to length of stay, readmissions, and discharge planning

, , ORCID Icon &

References

  • Agency for Healthcare Research and Quality. (2017). Strategy 4: Care transitions from hospital to home: IDEAL discharge planning, December 2017, http://www.ahrq.gov/professionals/systems/hospital/engagingfamilies/strategy4/index.html.
  • Agresti, A. (2019). An introduction to categorical data analysis (3rd ed.). Wiley.
  • Anderson, G. F., & Steinberg, E. P. (1985). Predicting hospital readmissions in the Medicare population. Inquiry, 22(3), 251–258.
  • Angus, D. C., Linde-Zwirble, W. T., Sirio, C. A., Rotondi, A. J., Chelluri, L., Newbold, R. C., Lave, J. R., & Pinsky, M. R. (1996). The effect of managed care on ICU length of stay: Implications for Medicare. Journal of the American Medical Association, 276(13), 1075–1082.
  • Awad, A., Bader–El–Den, M., & McNicholas, J. (2017). Patient length of stay and mortality prediction: A survey. Health Services Management Research, 30(2), 105–120. https://doi.org/10.1177/0951484817696212
  • Barnes, S., Hamrock, E., Toerper, M., Siddiqui, S., & Levin, S. (2016). Real-time prediction of inpatient length of stay for discharge prioritization. Journal of the American Medical Informatics Association: JAMIA, 23(e1), e2–e10. https://doi.org/10.1093/jamia/ocv106
  • Bertsimas, D., Pauphilet, J., Stevens, J., & Tandon, M. (2022). Predicting inpatient flow at a major hospital using interpretable analytics. Manufacturing & Service Operations Management, 24(6), 2809–2824. https://doi.org/10.1287/msom.2021.0971
  • Breusch, T. S., & Pagan, A. R. (1979). A simple test for heteroscedasticity and random coefficient variation. Econometrica, 47(5), 1287. https://doi.org/10.2307/1911963
  • Centers for Medicare and Medicaid Services. (2016). FY2016-IPPS-final-rule-tables @. www.cms.gov, https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Acute-Inpatient-Files-for-Download-Items/FY2016-Final-Rule-Correction-Notice-Files.
  • Centers for Medicare and Medicaid Services. (2021a). Hospital readmission reduction program (HRRP), 01 December 2021, https://www.cms.gov/medicare/quality-initiatives-patient-assessment-instruments/value-based-programs/hrrp/hospital-readmission-reduction-program.html.
  • Centers for Medicare and Medicaid Services. (2021b). Clarification of patient discharge status codes and hospital transfer policies, 05 May 2021, https://www.hhs.gov/guidance/document/clarification-patient-discharge-status-codes-and-hospital-transfer-policies.
  • Delgado, M. K., Liu, V., Pines, J. M., Kipnis, P., Gardner, M. N., & Escobar, G. J. (2013). Risk factors for unplanned transfer to intensive care within 24 hours of admission from the emergency department in an integrated health system. Journal of Hospital Medicine, 8(1), 13–19. https://doi.org/10.1002/jhm.1979
  • DeVoe, J. (2015). When knowing more about a patient enables us to do less. JAMA Internal Medicine, 175(10), 1605–1606. https://doi.org/10.1001/jamainternmed.2015.4219
  • Donze, J., Aujesky, D., Williams, D., & Schnipper, J. L. (2013). Potentially avoidable 30-day hospital readmissions in medical patients: Derivation and validation of a prediction model. JAMA Internal Medicine, 173(8), 632–638. https://doi.org/10.1001/jamainternmed.2013.3023
  • Gonzalo, J. D., Wolpaw, D. R., Lehman, E., & Chuang, C. H. (2014). Patient-centered interprofessional collaborative care: Factors associated with bedside interprofessional rounds. Journal of General Internal Medicine, 29(7), 1040–1047. https://doi.org/10.1007/s11606-014-2817-x
  • Goodwin, J. S., Lin, Y. L., Singh, S., & Kuo, Y. F. (2013). Variation in length of stay and outcomes among hospitalized patients attributable to hospitals and hospitalists. Journal of General Internal Medicine, 28(3), 370–376. https://doi.org/10.1007/s11606-012-2255-6
  • Goroll, A. H., & Hunt, D. P. (2015). Bridging the hospitalist - Primary care divide through collaborative care. New England Journal of Medicine, 372(4), 308–309. https://doi.org/10.1056/NEJMp1411416
  • Greene, W. H. (2018). Econometric analysis (8th ed.). Pearson.
  • Hasan, O., Meltzer, D. O., Shaykevich, S. A., Bell, C. M., Kaboli, P. J., Auerbach, A. D., Wetterneck, T. B., Arora, V. M., Zhang, J., & Schnipper, J. L. (2010). Hospital readmission in general medicine patients: A prediction model. Journal of General Internal Medicine, 25(3), 211–219. https://doi.org/10.1007/s11606-009-1196-1
  • Hastie, T., Qian, J., & Tay, K. (2021). An Introduction to glmnet, 01 November 2021, https://web.stanford.edu/∼hastie/glmnet/glmnet_alpha.html.
  • Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning (2nd ed.). Springer.
  • Herzke, C. A., Michtalik, H., Durkin, N., Finkelstein, J., Deutschendorf, A., Miller, A., Leung, C., & Brotman, D. J. (2018). A method for attributing patient-level metrics to rotating providers in an inpatient setting. Journal of Hospital Medicine, 13(7), 470–475. https://doi.org/10.12788/jhm.2897
  • Hoerl, A. E., & Kennard, R. W. (1970). Ridge regression: Biased estimation for nonorthogonal problems. Technometrics, 12(1), 55–67. https://doi.org/10.1080/00401706.1970.10488634
  • Hurvich, C. M., & Tsai, C. L. (1990). The impact of model selection on inference in linear regression. American Statistician, 44(3), 214–217. https://doi.org/10.2307/2685338
  • Jaeker, J. A. B., & Tucker, A. L. (2017). Past the point of speeding up: The negative effects of workload saturation on efficiency and patient severity. Management Science, 63(4), 1042–1062. https://doi.org/10.1287/mnsc.2015.2387
  • James, G., Witten, D., Hastie, T., & Tibshirani, R. (2021). An introduction to statistical learning with applications in R (2nd ed.). Springer.
  • Knaus, W. A., Wagner, D. P., Zimmerman, J. E., & Draper, E. A. (1993). Variations in mortality and length of stay in intensive care units. Annals of Internal Medicine, 118(10), 753–761. https://doi.org/10.7326/0003-4819-118-10-199305150-00001
  • Koenker, R. (1981). A note on studentizing a test for heteroscedasticity. Journal of Econometrics, 17(1), 107–112. https://doi.org/10.1016/0304-4076(81)90062-2
  • Lin, C. J., Cheng, S. J., Shih, S. C., Chu, C. H., & Tjung, J. J. (2012). Discharge planning. International Journal of Gerontology, 6(4), 237–240. https://doi.org/10.1016/j.ijge.2012.05.001
  • MacKinnon, J. G., & White, H. (1985). Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties. Journal of Econometrics, 29(3), 305–325. https://doi.org/10.1016/0304-4076(85)90158-7
  • Marshall, A., Vasilakis, C., & El-Darzi, E. (2005). Length of stay-based patient flow models: Recent developments and future directions. Health Care Management Science, 8(3), 213–220. https://doi.org/10.1007/s10729-005-2012-z
  • Mor, V., & Besdine, R. W. (2011). Policy options to improve discharge planning and reduce rehospitalization. JAMA - Journal of the American Medical Association, 305(3), 302–303. https://doi.org/10.1001/jama.2010.2006
  • Pereira, S., Foley, N., Salter, K., McClure, J. A., Meyer, M., Brown, J., Speechley, M., & Teasell, R. (2014). Discharge destination of individuals with severe stroke undergoing rehabilitation: A predictive model. Disability and Rehabilitation, 36(9), 727–731. https://doi.org/10.3109/09638288.2014.902510
  • Peterson, M. C. (2009). A systematic review of outcomes and quality measures in adult patients cared for by hospitalists vs. nonhospitalists. Mayo Clinic Proceedings, 84(3), 248–254. https://doi.org/10.4065/84.3.248
  • Shulan, M., Gao, K., & Moore, C. D. (2013). Predicting 30-day all-cause hospital readmissions. Health Care Management Science, 16(2), 167–175. https://doi.org/10.1007/s10729-013-9220-8
  • Southern, W., Berger, W., Bellin, E., Hailpern, S., & Arnsten, J. (2007). Hospitalist care and length of stay in patients requiring complex discharge planning and close clinical monitoring. Archives of Internal Medicine, 167(17), 1869–1874. https://doi.org/10.1001/archinte.167.17.1869
  • Tibshirani, R. (1996). Regression shrinkage and selection via the Lasso. Journal of the Royal Statistical Society Series B, 58(1), 267–288. https://doi.org/10.1111/j.2517-6161.1996.tb02080.x
  • Williams, S., Bottle, A., & Aylin, P. (. (2005). Length of hospital stay and subsequent emergency readmission. BMJ (Clinical Research ed.), 331(7513), 371. https://doi.org/10.1136/bmj.331.7513.371
  • Zapatero, A., Barba, R., Marco, J., Hinojosa, J., Plaza, S., Losa, J. E., & Canora, J. (2012). Predictive model of readmission to internal medicine wards. European Journal of Internal Medicine, 23(5), 451–456. https://doi.org/10.1016/j.ejim.2012.01.005
  • Zou, H., & Hastie, T. (2005). Addendum: Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society Series B: Statistical Methodology, 67(5), 768–768. Erratum: Regularization and variable selection via the elastic net (Journal of the Royal Statistical Society. Series B: Statistical Methodology (2005) 67 (301-320)). https://doi.org/10.1111/j.1467-9868.2005.00527.x

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.