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Bringing Life-Saving Medical Technology to Africa

Support READS Africa

Our Hospital System (READS) helps deliver safer, faster, and better quality care to save lives.

Since 2016 Tapa Healthcare have donated their READS technology to a hospital in Kitovu, Uganda, to bring a level of patient safety and care that has not been available before. We are extremely gratified and encouraged that this innovation has helped improve care and clinical outcomes, and will help save many lives in the future.

"READS helps provide better care and saves lives" Dr Martin Opio, Kampala, Uganda."

Hospitals in Africa have only $20 to spend per patient, yet have approximately twice as many severely ill patients as in the developed world, and these patients are three times more likely to die.

In low resource regions like Africa it is not possible for them to buy systems, devices and medicines which is why we need your help. We wish to donate and support READS to three Ugandan hospitals and we hope that you will support our cause by helping us raise $65,000. If we exceed this amount we will continue to identify other hospitals in Uganda, Kenya, Tanzania, and Rwanda to donate and support a READS system.

"We have loved this system...the patients love it so much, they know when they come for treatment that they are followed up very well." - Sister Christine, Kitovu Hospital

Support more patients

Improve Care & outcomes

Save lives

The Solution - READS Patient Safety System

Tapa Healthcare has a CE Marked Class I Medical Device which has been used in hospitals across the UK, Ireland, Europe, and Africa, which tackles the biggest causes of preventable deaths in hospitals. READS is a Patient Safety system that assesses illness severity, anticipates patient deterioration, and prompts actions to save the patient.

  • Patient-centric workflows

    Provides automated Clinical Intelligence to inform Clinical Decision Making

  • Electronic Observation System

    64 clinical data points; patient vital signs, symptoms, behaviours, and background are captured and calculated in under 60 seconds.

  • Rapid Response System

    Fits in Doctors and Nurse’s pockets, for rapid communication and alerting.

  • smart, fast, efficient

    Helps save time and lives by replacing inefficient manual work with rapid automated processes

  • ALCOA Compliant Medical Records

    A portable mobile platform that requires minimal IT infrastructure.

  • medical-analytics

    Over 20 customisable quality management protocols, actions or best practice recommendations inform the user of each individual patient's risks and needs.

READS Patient Dasbhoard
READS Workflow Management
READS Electronic Charting

READS uses this information to help clinicians more quickly identify, treat or prevent:
  • Sepsis (which kills 8,000,000 people per year, with Africa having the highest ratio)
  • Stroke, Acute Kidney Injury, and other volatile conditions
  • Undiagnosed chronic conditions
  • And much more...

We need your support to further develop, implement and donate bespoke hospital technology that will help save lives in Africa. Every penny raised will go to supporting this project; developing new algorithms and software, to buying relevant hardware, installing servers, medical supplies and the process of identifying and implementing READS into new hospitals across Africa (initially expanding within Uganda).

The Science and Impact

Tapa Healthcare has over 18 years experience in producing and validating patient deterioration algorithms, with independent core studies across four continents, spanning 8,000,000+ research data points. Furthermore an earlier READS prototype has been active in Kitovu hospital, Uganda for over 18 months, the results of which have fuelled the desire to further invest in tailored African healthcare solutions and to save lives with innovative technology.

Global Knowledge Leaders

Tapa is supported by renowned doctors and experts within the sphere of predictive health analytics and acute medicine, the following key opinion leaders are part of the Clinical Advisory Group, and they have a direct influence over research, innovation and delivery:

  • Dr John Kellett - Co-Founder and Chief Medical Officer of Tapa Healthcare
  • Dr Martin Opio - Medical Superintendent, International Hospital Kampala, Uganda
  • Dr Mikkel Brabrand - Clinical Associate Professor, Institute if Regional Health Research, University of Southern Denmark
  • Dr Chris Subbe - Consultant in Acute, Respiratory and Intensive Care Medicine at the Ysbyty Gwynedd, Bangor, Wales UK
  • Prof. Wendelin Schramm, Professor for health economics and health care management at Heilbronn University, Germany

Research Data Points
Independent Case Studies Across the World
Years of Global Clinical Research

Clinical Studies, Research, and Validation

  • Cummings MJ, Wamala JF, Bakamutumaho B and Davis JL. Vital signs: the first step in prevention and management of critical illness in resource‑limited settings. Intensive Care Med 2016;42:1519–1520 2.
  • Kruisselbrink R, Kwizera A, Crowther M et al. Modified Early Warning Score (MEWS) identifies critical illness among ward patients in a resource restricted setting in Kampala, Uganda: a prospective observational study. PLoS One 2016;11:e0151408. doi:10.1371/journal.pone.0151408 3.
  • Asiimwe SB, Abdallah A, Ssekitoleko S. A simple prognostic index based on admission vital signs data among patients with sepsis in a resource-limited setting. Crit Care 2015;19:86 4. Riviello ED, Pisani L, Schultz MJ. What’s new in ARDS: ARDS also exists in resourceconstrained settings. Intensive Care Med 2016;42:794–796. doi:10.1007/s00134-016-4308-5 5.
  • Asiimwe SB, Okello S, Moore CC. Frequency of vital signs monitoring and its association with mortality among adults with severe sepsis admitted to a general medical ward in Uganda. PLoS One 2014;9:e89879. doi:10.1371/journal.pone.0089879 6.
  • Opio MO, Nansubuga G., Kellett J. Validation of the VitalPACTM Early Warning Score (ViEWS) in acutely ill medical patients attending a resource-poor hospital in sub-Saharan Africa. Resuscitation 2013;84:743-746. 7.
  • OpioMO, Nansubuga G., Kellett J, In-hospital mortality of acutely ill medical patients admitted to a resource poor hospital in sub-Saharan Africa and to a Canadian Regional Hospital compared using the abbreviated VitalPAC™ Early Warning Score Eur J Intern Med 2014;25:142-146. 8.
  • Opio M.O., Nansubuga G., Kellett J., Clifford M., Murray A. Performance of TOTAL, in medical patients attending a resource-poor hospital in sub-Saharan Africa and a small Irish rural hospital. Acute Medicine 2013;12:135-140 9.
  • Wheeler I., Price C., Sitch A., Banda P., Kellett J., Nyirenda M., Rylance J. Early warning scores generated in developed healthcare settings are not sufficient at predicting early mortality in Blantyre, Malawi: a prospective cohort study. PlosOne 2013;8(3): e59830. doi:10.1371/journal.pone.0059830 10.
  • Nabayigga B, Kellett J, Brabrand M, Opio MO. The mortality of acutely ill medical patients for up to 60 days after admission to a resource poor hospital in sub-Saharan Africa compared with patients of similar illness severity admitted to a Danish Regional Teaching Hospital — An exploratory observational study. European Journal of Internal Medicine 2016;27: 24–30 4 11.
  • Nabayigga B, Kellett J, Opio MO. The alertness, gait and mortality of severely ill patients at two months after admission to a resource poor sub-Saharan hospital—Why is post-discharge surveillance not routine everywhere? European Journal of Internal Medicine 2016;28:25–31 12.
  • Moore CC, Hazard R, Saulters KJ, et al. Derivation and validation of a universal vital assessment (UVA) score: a tool for predicting mortality in adult hospitalised patients in subSaharan Africa. BMJ Glob Health 2017;2:e000344. doi:10.1136/ bmjgh-2017-000344 13.
  • Opio MO, Namujwiga T, Nakitende I, Kellett J, Brabrand M. on behalf of the Kitovu Hospital Study Group The prediction of in-hospital mortality by mid-upper arm circumference: a prospective observational study of the association between mid-upper arm circumference and the outcome of acutely ill medical patients admitted to a resource poor hospital in subSaharan Africa. Clinical Medicine – in press 14.
  • Cummings MJ, Goldberg E, Mwaka S, Kabajaasi O, Vittinghoff E, Cattamanchi A, Katamba A, Kenya-Mugisha N, Jacob ST, andDavis JL. A complex intervention to improve implementation of World Health Organization guidelines for diagnosis of severe illness in low-income settings: a quasi-experimental study from Uganda. Implementation Science 2017;12:126 15.
  • Baker T, Schell CO, Lugazia E, Blixt J, Mulungu M, Castegren M, et al. Vital Signs Directed Therapy: Improving Care in an Intensive Care Unit in a Low-Income Country. PLoS ONE 2015;10(12): e0144801. doi:10.1371/journal.pone.0144801

Visit to see a further 60 published, peer-reviewed white papers, journals and clinical study reports.

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Donation Link: Indiegogo/projects/TapaHealthCare

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