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Implementation of a Digitally Enabled Care Pathway (Part 1): Impact on Clinical Outcomes and Associated Health Care Costs.
Connell, Alistair; Raine, Rosalind; Martin, Peter; Barbosa, Estela Capelas; Morris, Stephen; Nightingale, Claire; Sadeghi-Alavijeh, Omid; King, Dominic; Karthikesalingam, Alan; Hughes, Cían; Back, Trevor; Ayoub, Kareem; Suleyman, Mustafa; Jones, Gareth; Cross, Jennifer; Stanley, Sarah; Emerson, Mary; Merrick, Charles; Rees, Geraint; Montgomery, Hugh; Laing, Christopher.
Afiliación
  • Connell A; Centre for Human Health and Performance, University College London, London, United Kingdom.
  • Raine R; DeepMind Health, London, United Kingdom.
  • Martin P; Department of Applied Health Research, University College London, London, United Kingdom.
  • Barbosa EC; Department of Applied Health Research, University College London, London, United Kingdom.
  • Morris S; Department of Applied Health Research, University College London, London, United Kingdom.
  • Nightingale C; Department of Applied Health Research, University College London, London, United Kingdom.
  • Sadeghi-Alavijeh O; Department of Applied Health Research, University College London, London, United Kingdom.
  • King D; Population Health Research Institute, St George's, University of London, London, United Kingdom.
  • Karthikesalingam A; Royal Free London NHS Foundation Trust, London, United Kingdom.
  • Hughes C; DeepMind Health, London, United Kingdom.
  • Back T; DeepMind Health, London, United Kingdom.
  • Ayoub K; DeepMind Health, London, United Kingdom.
  • Suleyman M; DeepMind Health, London, United Kingdom.
  • Jones G; DeepMind Health, London, United Kingdom.
  • Cross J; DeepMind Health, London, United Kingdom.
  • Stanley S; Royal Free London NHS Foundation Trust, London, United Kingdom.
  • Emerson M; Royal Free London NHS Foundation Trust, London, United Kingdom.
  • Merrick C; Royal Free London NHS Foundation Trust, London, United Kingdom.
  • Rees G; Royal Free London NHS Foundation Trust, London, United Kingdom.
  • Montgomery H; Royal Free London NHS Foundation Trust, London, United Kingdom.
  • Laing C; Faculty of Life Sciences, University College London, London, United Kingdom.
J Med Internet Res ; 21(7): e13147, 2019 07 15.
Article en En | MEDLINE | ID: mdl-31368447
BACKGROUND: The development of acute kidney injury (AKI) in hospitalized patients is associated with adverse outcomes and increased health care costs. Simple automated e-alerts indicating its presence do not appear to improve outcomes, perhaps because of a lack of explicitly defined integration with a clinical response. OBJECTIVE: We sought to test this hypothesis by evaluating the impact of a digitally enabled intervention on clinical outcomes and health care costs associated with AKI in hospitalized patients. METHODS: We developed a care pathway comprising automated AKI detection, mobile clinician notification, in-app triage, and a protocolized specialist clinical response. We evaluated its impact by comparing data from pre- and postimplementation phases (May 2016 to January 2017 and May to September 2017, respectively) at the intervention site and another site not receiving the intervention. Clinical outcomes were analyzed using segmented regression analysis. The primary outcome was recovery of renal function to ≤120% of baseline by hospital discharge. Secondary clinical outcomes were mortality within 30 days of alert, progression of AKI stage, transfer to renal/intensive care units, hospital re-admission within 30 days of discharge, dependence on renal replacement therapy 30 days after discharge, and hospital-wide cardiac arrest rate. Time taken for specialist review of AKI alerts was measured. Impact on health care costs as defined by Patient-Level Information and Costing System data was evaluated using difference-in-differences (DID) analysis. RESULTS: The median time to AKI alert review by a specialist was 14.0 min (interquartile range 1.0-60.0 min). There was no impact on the primary outcome (estimated odds ratio [OR] 1.00, 95% CI 0.58-1.71; P=.99). Although the hospital-wide cardiac arrest rate fell significantly at the intervention site (OR 0.55, 95% CI 0.38-0.76; P<.001), DID analysis with the comparator site was not significant (OR 1.13, 95% CI 0.63-1.99; P=.69). There was no impact on other secondary clinical outcomes. Mean health care costs per patient were reduced by £2123 (95% CI -£4024 to -£222; P=.03), not including costs of providing the technology. CONCLUSIONS: The digitally enabled clinical intervention to detect and treat AKI in hospitalized patients reduced health care costs and possibly reduced cardiac arrest rates. Its impact on other clinical outcomes and identification of the active components of the pathway requires clarification through evaluation across multiple sites.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Telemedicina / Atención a la Salud Tipo de estudio: Guideline / Health_economic_evaluation / Risk_factors_studies Límite: Female / Humans / Male Idioma: En Revista: J Med Internet Res Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Telemedicina / Atención a la Salud Tipo de estudio: Guideline / Health_economic_evaluation / Risk_factors_studies Límite: Female / Humans / Male Idioma: En Revista: J Med Internet Res Asunto de la revista: INFORMATICA MEDICA Año: 2019 Tipo del documento: Article País de afiliación: Reino Unido