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Digital health and inpatient palliative care: a cohort-controlled study
  1. Baldev Malkit Singh1,2,
  2. Nisha Kumari-Dewat3,
  3. Adam Ryder4,
  4. Emma Parry5,6,
  5. Vijay Klaire7,
  6. Dawn Matthews8,
  7. Gemma Bennion8,
  8. Hannah Jennens8,
  9. Benoit M E Ritzenthaler8,
  10. Sophie Rayner9,
  11. Jean Shears4,
  12. Kamran Ahmed10,
  13. Mona Sidhu11,
  14. Ananth Viswanath12 and
  15. Kate Warren7,13
  1. 1 Institute of Digital Health, Royal Wolverhampton Hospitals NHS Trust, Wolverhampton, UK
  2. 2 Research Institute for Health Sciences, University of Wolverhampton, Wolverhampton, UK
  3. 3 Community Nursing, Royal Wolverhampton Hospitals NHS Trust, Wolverhampton, UK
  4. 4 Departmenet of Medicine, Royal Wolverhampton Hospitals NHS Trust, Wolverhampton, UK
  5. 5 Academic Unit of Primary Care, Institute of Digital Health, Royal Wolverhampton Hospitals NHS Trust, Wolverhampton, UK
  6. 6 School of Medicine, Keele University, Keele, UK
  7. 7 Digital Innovation Unit, Institute of Digital Health, Royal Wolverhampton Hospitals NHS Trust, Wolverhampton, UK
  8. 8 Department of Palliative Medicine, Royal Wolverhampton Hospitals NHS Trust, Wolverhampton, UK
  9. 9 Department of Palliative Medicine, Derriford Hospital, Plymouth, UK
  10. 10 Pennfields Medical Centre, Wolverhampton, UK
  11. 11 Lea Road Medical Practice, Wolverhampton, UK
  12. 12 Department of Diabetes and Endocrinology, Royal Wolverhampton Hospitals NHS Trust, Wolverhampton, UK
  13. 13 Department of Public Health, Wolverhampton City Council, Wolverhampton, UK
  1. Correspondence to Dr Baldev Malkit Singh, Institute of Digital Health, Royal Wolverhampton Hospitals NHS Trust, Wolverhampton WV10 0QP, UK; baldev.singh{at}nhs.net

Abstract

Objectives End of life has unacceptable levels of hospital admission and death. We aimed to determine the association of a novel digital specific system (Proactive Risk-Based and Data-Driven Assessment of Patients at the End of Life, PRADA) to modify such events.

Methods A cohort-controlled study of those discharged alive, who died within 90 days of discharge, comparing PRADA (n=114) with standard care (n=3730).

Results At 90 days, the PRADA group were more likely to die (78.9% vs 46.2%, p<0.001), had a shorter time to death (58±90 vs 178±186 days, p<0.001) but readmission (20.2% vs 37.9%, p<0.001) or death in hospital (4.4% vs 28.9%, p<0.001) was lower with reduced risk for a combined 90-day outcome of postdischarge non-elective admission or hospital death (OR 0.45, 95% CI 0.27–0.74, p<0.001). Tightening criteria with 1:1 matching (n=83 vs 83) showed persistent significant findings in PRADA contact with markedly reduced adverse events (OR 0.15, 95% CI 0.02–0.96, p<0.05).

Conclusions Being seen in hospital by a specialist palliative care team using the PRADA tool was associated with significantly improved postdischarge outcomes pertaining to those destined to die after discharge.

  • Service evaluation
  • Hospital care
  • Advance Care Planning
  • Clinical decisions
  • Methodological research
  • Prognosis

https://doi.org/10.1136/spcare-2023-004474

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    Footnotes

    • Contributors Principal and accountable author: BMS; authors NK-D, AR, DM, EP. Data accrual, integration and quality: VK. Statistical analysis: BMS. Manuscript development: all authors. Medical ethics: AR. PRADA system development and pilot: BMER, GB, HJ, KW, JS, SR, MS, KA, AV.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; internally peer reviewed.