Abstract
When hospital capacity is near census, either due to limits on the number of physical or staffed beds, delays in patients’ discharge can result in domino effects of congestion for the emergency department, the intensive care units, the postanesthesia care unit, and the operating room. Hospital administrators often promote increasing the percentage of patients discharged before noon as mitigation. However, benchmark data from multiple hospitals are lacking. We studied the time of weekday inpatient discharges from all 202 acute care hospitals in the state of Florida between 2010 and 2018 using publicly available data. Statewide, the average length of stay (4.63 days) did not change, but hospital discharges increased 6.1%. There was no change over years in the percentage of patients discharged before 12 noon (13.0% ± 0.28% standard error [SE]) or before 3 PM (42.2% ± 0.25% SE). For every year, the median hour of patient discharge was 3 PM. Only 9 of the 202 hospitals (4.5%) reliably achieved a morning weekday discharge rate ≥ 20.0%. Only 19 hospitals (9.4%) in the state reliably achieved a ≥ 50.0% weekday discharge rate before 3 PM. Hospital administrators seeking to achieve earlier patient discharges can use our provided data as realistic benchmarks to guide efforts. Alternatively, administrators could plan based on a model that beds will not be reliably available for new patients until late in the afternoon and apply other well-developed operational strategies to address bottlenecks affecting the internal transfer of patients within the hospital.
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Notes
PubMed search on August 26, 2019: ((“patient discharge”[MeSH Terms] AND (“bed capacity”[TIAB] OR “hospital capacity”[TIAB] OR “hospital discharge time”[TIAB])) OR ((“bed occupancy”[MeSH Terms] OR “hospital bed capacity”[MeSH Terms]) AND “crowding”[MeSH Terms])) OR (discharge before home) returned 329 articles. Examination of the abstracts identified 16 studies relevant to efforts to improve the timeliness of hospital discharge for inpatients, which were then read.
There were 210 unique acute care hospitals in 2006 and 219 in 2018, a net increase of 4.3%. The number of licensed beds increased by 3.1%, from 57,144 to 58,939. During this interval, the resident population in Florida increased by 17.7%, from 18.09 to 21.30 million [26].
This value matches with the South Atlantic portion of the 2016 National Inpatient Sample mean length of stay for short-term acute care hospitals of 4.7 days (30). This subset includes data from Delaware, Maryland, the District of Columbia, Virginia, West Virginia, North and South Carolina, Georgia, and Florida. The nearly identical vales for mean length of stay demonstrates congruent validity of our analyzed dataset.
References
Lucas, R., Farley, H., Twanmoh, J., Urumov, A., Olsen, N., Evans, B., and Kabiri, H., Emergency department patient flow: the influence of hospital census variables on emergency department length of stay. Acad. Emerg. Med. 16(7):597–602, 2009.
Johnson, D. W., Schmidt, U. H., Bittner, E. A., Christensen, B., Levi, R., and Pino, R. M., Delay of transfer from the intensive care unit: a prospective observational study of incidence, causes, and financial impact. Crit. Care 17:R128, 2013.
Zollinger, T. W., Saywell, Jr., R. M., Smith, C. P., Highland, D., Pfeiffer, B., and Kelton, G. M., Delays in patient transfer: Postanesthesia care nursing. Nurs. Econ. 17:283–290, 1999.
Cowie, B., and Corcoran, P., Postanesthesia care unit discharge delay for nonclinical reasons. J. Perianesth. Nurs. 27(6):393–398, 2012.
Kravet, S. J., Levine, R. B., Rubin, H. R., and Wright, S. M., Discharging patients earlier in the day: A concept worth evaluating. Health Care Manag. (Frederick) 26:142–146, 2007.
Hesselink, G., Zegers, M., Vernooij-Dassen, M. et al., Improving patient discharge and reducing hospital readmissions by using Intervention Mapping. BMC Health Serv. Res. 14:389, 2014.
Hsu, C. M., Liang, L. L., Chang, Y. T., and Juang, W. C., Emergency department overcrowding: Quality improvement in a Taiwan medical center. J. Formos. Med. Assoc. 118:186–193, 2019.
Kerr, J., Maitland, H., Bell, C., White, J., and Hunter, A., Daily dynamic discharge - a whole system solution to ED crowding. Emerg. Med. J. 34(12):A875–A876, 2017.
El-Eid, G. R., Kaddoum, R., Tamim, H., and Hitti, E. A., Improving hospital discharge time: a successful implementation of Six Sigma methodology. Medicine (Baltimore) 94:e633, 2015.
McGowan, J. E., Truwit, J. D., Cipriano, P., Howell, R. E., VanBree, M., Garson, Jr., A., and Hanks, J. B., Operating room efficiency and hospital capacity: Factors affecting operating room use during maximum hospital census. J. Am. Coll. Surg. 204:865–871, 2007.
Wertheimer, B., Jacobs, R. E. A., Bailey, M., Holstein, S., Chatfield, S., Ohta, B., Horrocks, A., and Hochman, K., Discharge before noon. J. Hosp. Med. 9:210–214, 2014.
Patel, H., Yirdaw, E., Yu, A., Slater, L., Perica, K., Pierce, R. G., Amaro, C., and Jones, C. D., Improving early discharge using a team-based structure for discharge multidisciplinary rounds. Prof. Case Manag. 24:83–89, 2019.
Lyons, J., McCaulley, L., Maronian, N., and Hardacre, J. M., A targeted initiative to discharge surgical patients earlier in the day is associated with decreased length of stay and improved hospital throughput. Am. J. Surg. 217:419–422, 2019.
Molla, M., Warren, D. S., Stewart, S. L., Stocking, J., Johl, H., and Sinigayan, V., A lean six sigma quality improvement project improves timeliness of discharge from the hospital. Jt .Comm. J. Qual. Patient Saf. 44:401–412, 2018.
Kane, M., Rohatgi, N., Heidenreich, P., Thakur, A., Winget, M., Shum, K., Hereford, J., Shieh, L., Lew, T., Horn, J., Chi, J., Weinacker, A., Seay-Morrison, T., and Ahuja, N., Lean-based redesign of multidisciplinary rounds on general medicine service. J. Hosp. Med. 13(7):482–485, 2018.
Artenstein, A. W., Rathlev, N. K., Neal, D., Townsend, V., Vemula, M., Goldlust, S., Schmidt, J., and Visintainer, P., Decreasing emergency department walkout rate and boarding hours by improving inpatient length of stay. West J. Emerg. Med. 18:982–992, 2017.
Patel, H., Morduchowicz, S., and Mourad, M., Using a systematic framework of interventions to improve early discharges. Jt. Comm. J. Qual. Patient Saf. 43:189–196, 2017.
Kane, M., Weinacker, A., Arthofer, R., Seay-Morrison, T., Elfman, W., Ramirez, M., Ahuja, N., Pickham, D., Hereford, J., and Welton, M., A multidisciplinary initiative to increase inpatient discharges before noon. J. Nurs. Adm. 46:630–635, 2016.
Mustafa, A., and Mahgoub, S., Understanding and overcoming barriers to timely discharge from the pediatric units. BMJ Qual. Improv. Rep. 5. eCollection, 2016.
Beck, M. J., and Gosik, K., Redesigning an inpatient pediatric service using Lean to improve throughput efficiency. J. Hosp. Med. 10(4):220–227, 2015.
Hernandez, N., John, D., and Mitchell, J., A reimagined discharge lounge as a way to an efficient discharge process. BMJ Qual. Improv. Rep. 31:3, 2014. https://doi.org/10.1136/bmjquality.u204930.w2080. eCollection.
Glasgow, J. M., Davies, M. L., and Kaboli, P. J., Findings from a national improvement collaborative: are improvements sustained? BMJ Qual. Saf. 21:663–669, 2012.
Agency for Health Care Administration. Order Data/Data Dictionary. https://www.floridahealthfinder.gov/Researchers/OrderData/order-data.aspx Accessed August 26, 2019.
Agency for Health Care Administration. AHCA Patient Data Submission Guide. https://ahca.myflorida.com/SCHS/DataCollection/docs/DataGuideUpdate010818.pdf Accessed October 31, 2019.
Starnes, J. R., Wanderer, J. P., and Ehrenfeld, J. M., Metadata from data: Identifying holidays from anesthesia data. J. Med. Syst. 39:44, 2015.
Duffin E. Resident population in Florida 1960-2018. https://www.statista.com/statistics/206109/resident-population-in-florida/ Accessed November 1, 2019.
Centers for Medicare and Medicaid Services. CMS navigator glossary of terms. https://www.cms.gov/Research-Statistics-Data-and-Systems/Research/ResearchGenInfo/Downloads/DataNav_Glossary_Alpha.pdf Accessed August 13, Accessed August 13,2019.
Dexter, F., Dutton, R. P., Kordylewski, H., and Epstein, R. H., Anesthesia workload nationally during regular workdays and weekends. Anesth. Analg. 121:1600–1603, 2015.
Dexter, F., Epstein, R. H., and Rodriguez, L. I., Throughout the United States, pediatric patients undergoing ambulatory surgery enter the operating room and are discharged earlier in the day than are adults. Perioper. Care Oper. Room Manag. 16:100076, 2019. https://doi.org/10.1016/j.pcorm.2019.100076.
Agency for Healthcare Research and Quality. Surgeries in hospital-based ambulatory surgery and hospital inpatient settings, 2014 https://hcup-us.ahrq.gov/reports/statbriefs/sb223-Ambulatory-Inpatient-Surgeries-2014.jsp Accessed September 3, 2019.
Schreyer, K. E., and Martin, R., The economics of an admissions holding unit. West J. Emerg. Med. 18:553–558, 2017.
Ziser, A., Alkobi, M., Markovits, R., and Rozenberg, B., The postanaesthesia care unit as a temporary admission location due to intensive care and ward overflow. Br. J. Anaesth. 88:577–579, 2002.
Marcon, E., Kharraja, S., Smolski, N., Luquet, B., and Viale, J. P., Determining the number of beds in the postanesthesia care unit: a computer simulation flow approach. Anesth. Analg. 96:1415–1423, 2003.
Epstein, R. H., Dexter, F., and Traub, R. D., Statistical power analysis to estimate how many months of data are required to identify PACU staffing to minimize delays in admission from ORs. J. Perianesth. Nurs. 17(2):84–88, 2002.
Dexter, F., Epstein, R. H., Marcon, E., and de Matta, R., Strategies to reduce delays in admission into a postanesthesia care unit from operating rooms. J. Perianesth. Nurs. 20(2):92–102, 2005.
Prin, M., and Wunsch, H., The role of stepdown beds in hospital care. Am. J. Respir. Crit. Care Med. 190:1210–1216, 2014.
Agency for Healthcare Research and Quality. Overview of U.S. hospital stays in 2016: Variation by geographic region. https://www.hcup-us.ahrq.gov/reports/statbriefs/sb246-Geographic-Variation-Hospital-Stays.jsp Accessed August 13, 2019.
Shine, D., Discharge before noon: An urban legend. Am. J. Med. 128:445–446, 2015.
Salehi, L., Phalpher, P., Valani, R., Wan, A., Herman, J., and Mercuri, M., Time of transfer of admitted patients from the ED: A contributor to ED boarding in high-volume community hospitals. Healthc. Q. 21:48–53, 2019.
Ehrenfeld, J. M., Dexter, F., Rothman, B. S., Minton, B. S., Johnson, D., Sandberg, W. S., and Epstein, R. H., Lack of utility of a decision support system to mitigate delays in admission from the operating room to the postanesthesia care unit. Anesth. Analg. 117:1444–1452, 2013.
Dexter, F., Traub, R. D., and Penning, D. H., Statistical analysis by Monte-Carlo simulation of the impact of administrative and medical delays in discharge from the postanesthesia care unit on total patient care hours. Anesth. Analg. 92:1222–1225, 2001.
Dexter, F., Epstein, R. H., and Penning, D. H., Statistical analysis of postanesthesia care unit staffing at a surgical suite with frequent delays in admission from the operating room – A case study. Anesth. Analg. 92(4):947–949, 2001.
Dexter, F., Wachtel, R. E., and Epstein, R. H., Impact of average patient acuity on staffing of the phase I PACU. J. Perianesth. Nurs. 21(5):303–310, 2006.
Schoenmeyr, T., Dunn, P. F., Gamarnik, D., Levi, R., Berger, D. L., Daily, B. J., Levine, W. C., and Sandberg, W. S., A model for understanding the impacts of demand and capacity on waiting time to enter a congested recovery room. Anesthesiology 110:1293–1304, 2009.
Agency for Healthcare Research and Quality.Central Distributor SID: Availability of Data Elements by Year. https://www.hcup-us.ahrq.gov/db/state/siddist/siddist_ddeavailbyyear.jsp Accessed September 1, 2019.
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Richard H. Epstein helped design the study, obtain the data, analyze the data, and write the manuscript. Franklin Dexter helped design the study, analyze the data, and write the manuscript. Christian Diez helped write the manuscript.
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Epstein, R.H., Dexter, F. & Diez, C. The Distributions of Weekday Discharge Times at Acute Care Hospitals in the State of Florida were Static from 2010 to 2018. J Med Syst 44, 47 (2020). https://doi.org/10.1007/s10916-019-1496-x
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DOI: https://doi.org/10.1007/s10916-019-1496-x