Discoveries and insights from implementing telehealth in a tele-acute unit: A retrospective study

Abstract

Objective: This study examines the impact of telehealth nursing interventions on length of stay (LOS) and ratio of LOS to risk-adjusted length of stay comparing tele-acute and traditional units.
Methods: Retrospective data from 6,999 patient visits at tele-acute and traditional hospital units between Q2 2020 and Q4 2022 were collected. Bivariate analysis and the Mann-Whitney U Test were used to determine statistical significance. Multivariate regression was conducted to analyze the factors affecting both LOS and the ratio.
Results: Regardless of the model, the findings suggest that LOS was greater in the traditional unit. In the LOS model, the stay was 7 hours and 39 minutes longer per admission in the traditional unit. In the risk-adjusted ratio model, the LOS was 5 hours and 14 minutes longer per admission than in the tele-acute unit.
Conclusions: This study contributes to a body of literature that is lacking in the use of telehealth nursing in the acute care setting. Our research offers new perspectives on how telehealth can affect operational measures like LOS and discharge times. This contribution is important as it broadens the scope of telehealth’s benefits beyond traditional remote care, highlighting its potential in fast-paced, acute care settings.

Keywords

Telemedicine / Telehealth / Tele-acute / Length of stay

ACKNOWLEDGEMENTS

The authors acknowledge the expert revisions suggested by the reviewers. those revisions helped to provide clarity to this study and resulted in an overall better manuscript.

AUTHORS CONTRIBUTIONS

SSF, EW, TS, AA and EEB originally conceptualized the project. AA analyzed data and wrote applicable parts of the paper. EEB and GO wrote the initial paper draft and managed edits and revisions of drafts. JB was responsible for data extraction. EW, WS, TS, and BK served as content experts. SSF was responsible for study oversight. All authors reviewed and approved all manuscript drafts.

FUNDING

The research is supported by the University of Alabama at Birmingham eMedicine Research Collaborative.

CONFLICTS OF INTEREST DISCLOSURE

The authors declare they have no conflicts of interest.

INFORMED CONSENT

Due to the retrospective nature of the research, informed consent was not collected.

ETHICS STATEMENT

This study was approved by the Institutional Review Board of The University of Alabama at Birmingham (No. IRB- 300008433) and was conducted per the ethical principles of the Declaration of Helsinki.

ETHICS APPROVAL

The Publication Ethics Committee of the Sciedu Press. The journal’s policies adhere to the Core Practices established by the Committee on Publication Ethics (COPE).

PROVENANCE AND PEER REVIEW

Not commissioned; externally double-blind peer reviewed.

DATA AVAILABILITY STATEMENT

Data utilized in this study is not publicly available due to privacy or ethical considerations. Data may be available upon request to the corresponding author.

DATA SHARING STATEMENT

No additional data are available.

OPEN ACCESS

This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).

COPYRIGHTS

Copyright for this article is retained by the author(s), with first publication rights granted to the journal.

References

[1] Snoswell CL, Taylor ML, Comans TA, et al. Determining if Telehealth Can Reduce Health System Costs: Scoping Review. J Med Internet Res. 2020; 22(10): e17298. PMid: 33074157. https://doi.org/10.2196/17298

[2] Kichloo A, Albosta M, Dettloff K, et al. Telemedicine, the current COVID-19 pandemic and the future: a narrative review and perspectives moving forward in the USA. Fam MedCommunity Health. 2020; 8(3).

[3] Hoppe KK, Williams M, Thomas N, et al. Telehealth with remote blood pressure monitoring for postpartum hypertension: a prospective single-cohort feasibility study. Pregnancy hypertension. 2019; 15: 1716.

[4] Langabeer JR, Gonzalez M, Alqusairi D, et al. Telehealth-enabled emergency medical services program reduces ambulance transport to urban emergency departments. Western Journal of Emergency Medicine. 2016; 17(6): 713.

[5] Gillespie SM, Shah MN, Wasserman EB, et al. Reducing emergency department utilization through engagement in telemedicine by senior living communities. Telemedicine and e-Health. 2016; 22(6): 489-96. PMid: 26741194. https://doi.org/10.1089/tmj.2015.0152

[6] O’Connor M, Asdornwised U, Dempsey ML, et al. Using telehealth to reduce all-cause 30-day hospital readmissions among heart failure patients receiving skilled home health services. Applied Clinical Informatics. 2016; 7(02): 238-47.

[7] Wakefield BJ, Holman JE, Ray A, et al. Outcomes of a home telehealth intervention for patients with heart failure. Journal of Telemedicine and Telecare. 2009; 15(1): 46-50. PMid: 19139220. https://doi.org/10.1258/jtt.2008.080701

[8] Cole J, Wilkins N, Moss M, et al. Impact of pharmacist involvement on Telehealth Transitional Care Management (TCM) for high medication risk patients. Pharmacy. 2019; 7(4): 158. PMid: 31775263. https://doi.org/10.3390/pharmacy7040158

[9] Wertheimer B, Jacobs RE, Bailey M, et al. Discharge before noon: an achievable hospital goal. J Hosp Med. 2014; 9(4): 210-4.

[10] Kane M, Weinacker A, Arthofer R, et al. A multidisciplinary initiative to increase inpatient discharges before noon. Journal of Nursing Administration. 2016; 46(12): 630-5. PMid: 27851703. https://doi.org/10.1097/NNA.0000000000000418

[11] Patel H, Yirdaw E, Yu A, et al. Improving Early Discharge Using a Team-Based Structure for Discharge Multidisciplinary Rounds. Prof Case Manag. 2019; 24(2): 83-9. PMid: 30688821. https://doi.org/10.1097/NCM.0000000000000318

[12] Feldman SS, Kennedy KC, Nafziger SM, et al. Critical Success Factors for Addressing Discharge Inefficiency at a Large Academic Medical Center: A Lean Six Sigma Approach. Journal of Nursing Care Quality. 2022; 37(2): 135-41.

[13] Micallef A, Buttigieg SC, Tomaselli G, et al. Defining delayed discharges of inpatients and their impact in acute hospital care: a scoping review. International Journal of Health Policy and Management. 2022; 11(2): 103.

[14] Rojas-García A, Turner S, Pizzo E, et al. Impact and experiences of delayed discharge: A mixed-studies systematic review. Health Expectations. 2018; 21(1): 41-56. PMid: 28898930. https://doi.org/10.1111/hex.12619

[15] Beck MJ, Okerblom D, Kumar A, et al. Lean intervention improves patient discharge times, improves emergency department throughput and reduces congestion. Hosp Pract (1995). 2016; 44(5): 252-9. PMid: 27791449. https://doi.org/10.1080/21548331.2016.1254559

[16] Orewa GN, Feldman SS, Hearld KR, et al. Using accountable care teams to improve timely discharge: a pilot study. Quality Management in Health Care. 2022; 31(1): 22-7. PMid: 34354033. https://doi.org/10.1097/QMH.0000000000000320.

[17] Zimmerman M, Benjamin I, Tirpak JW, D’Avanzato C. Patient satisfaction with partial hospital telehealth treatment during the COVID- 19 pandemic: Comparison to in-person treatment. Psychiatry Research. 2021; 301: 113966.

[18] Adams L, Lester S, Hoon E, et al. Patient satisfaction and acceptability with telehealth at specialist medical outpatient clinics during the COVID-19 pandemic in Australia. Internal Medicine Journal. 2021; 51(7): 1028-37. PMid: 34213046. https://doi.org/10.1111/imj.15205

[19] Haidar S, Vazquez R, Medic G. Impact of surgical complications on hospital costs and revenues: retrospective database study of Medicare claims. J Comp Eff Res. 2023; 12(7): e230080.

[20] Bentz JA, Brundisini F, MacDougall D. Perspectives and Experiences Regarding the Impacts of Emergency Department Overcrowding: A Rapid Qualitative Review. Canadian Journal of Health Technologies. 2023; 3(9).

[21] Shepperd S, Lannin NA, Clemson LM, et al. Discharge planning from hospital to home. Cochrane database of systematic reviews. 2013(1): CD000313.

[22] Khanna S, Sier D, Boyle J, et al. Discharge timeliness and its impact on hospital crowding and emergency department flow performance. Emerg Med Australas. 2016; 28(2): 164-70. PMid: 26845068. https://doi.org/10.1111/1742-6723.12543

[23] Kennedy K, Orewa G, Hall A, et al. From pandemic to endemic: A comparison of first, second, and third waves of COVID-19 for applicability in communicable disease management. Journal of Hospital Administration. 2022; 11(2): 1-7. https://doi.org/10.5430/jha.v11n2p1