November 29 - December 2, 2020
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HIMSS-Elsevier Digital Healthcare Awards

HIMSS-Elsevier Digital Healthcare AwardsThe HIMSS-Elsevier Digital Healthcare Awards aim to identify and recognise organisations across the globe that effectively use information and technology to successfully improve quality of health and care as well as patient safety.

The Middle Eastern edition will take place virtually as part of the HIMSS & Health 2.0 Digital Health Conference on Sunday 29th November 2020 where HIMSS and Elsevier will jointly be announcing this year's award winners. These Awards are open to all hospitals and healthcare providers based in the Middle East.

This year, the HIMSS-Elsevier Awards team are seeking to recognise professionals in two categories:

Outstanding ICT Achievement Award

  • To recognize outstanding achievement in harnessing ICT to provide significant improvement to patient care and safety.
  • The ICT solution adopted may not be new but it has been effectively used by the awarded hospitals to significantly improve patient care and outcome and/or address major challenges faced by the hospitals.
  • Other limiting factors like the hospital financial background, the niche community that the hospital is serving, the long-standing problem that the target population is facing et cetera will also be taken into consideration.

Outstanding ICT Innovations Award

  • To recognize the most innovative, creative and "out-of-the-box" ICT solutions used to improve patient care and safety.
  • Innovation can be in the form of leveraging on existing technology to come up with new and creative usage of ICT to significantly enhance patient care and outcome OR developing a ground-breaking technology that leads the way in ICT adoption.

Submissions are closed. All projects were submitted by Q1 / 2020 and they are not reflecting any outstanding achievements and innovation that may have happened during the COVID-19 outbreak.

We are delighted to announce the finalists!

Outstanding ICT Achievement

Description and goals

The "Stroke Golden Hour" is an IT-driven system developed to improve the treatment outcomes for patients with acute ischemic stroke (AIS). Stroke patients have a greater chance of surviving and avoiding long-term brain damage if they receive treatment within the first hour from the onset symptoms. One of the critical components is the door-to-needle time (DTN) – the time between the presentation of the patient at the hospital to receiving intravenous thrombolysis (IVT), a standard therapy in eligible patients with AIS. The solution focuses on workflow improvements to enhance efficiency in coordination of administrative tasks and patient evaluation.

Measures

Ministry of Health & Prevention's goal was to achieve high clinical processes' automation and tasks optimisation following evidence-based guidelines regarding patients with AIS. It covers the entire patient journey and harmonises services at different points of care, from Emergency Medical Services (EMS) to the Emergency Department (ED). Developers established a new methodology by integrating the EMS system with pre-alert stroke notification into Electronic Medical Record (EMR), deploying automated clinical rules to order laboratory tests and medical imaging services (CT). This approach enables real-time information flow within the EMR, including the thrombolysis checklist, auto-calculation of the required dosage, as well as appropriate prompts, alerts and stroke reporting system to monitor clinical outcomes.

Results

  • A reduction in door-to-needle time (DTN) from an average of 94.2 minutes to 52.76 minutes across all MOHAP facilities;
  • The utilisation of clinical analytics, clinical decision support and evidence-based medicine to reduce the morbidity and mortality resulting from stroke;
  • Improving and standardising the treatment of patients with acute ischemic stroke to enhance treatment outcomes;
  • Elimination of administrative bottlenecks to minimise time losses related to patient admission;
  • Development of digital care coordination architecture to control the full stroke patient's journey.

Description and goals

Analyses carried out by NGHA showed a significant waste of financial resources related to imaging diagnostics, estimated at millions of Saudi riyals. After an in-depth analysis, it was found that in most referrals, there were no evidence-based indications to perform the examination. Unnecessary tests generated high diagnostics costs. The NGHA decided to implement precise patient classification's guidelines for diagnostic imaging. The main objective was to reduce the costs of medical imaging services by introducing evidence-based approaches recommended by the European Society of Radiology and the American College of Radiology.

Measures

To reduce financial losses due to unnecessary medical imaging, web service-based clinical decision support system (CDSS) was developed and integrated with existing Electronic Medical Record. From the beginning of the project, CEOs, CMOs were engaged in the design and implementation. It helped to strengthen the acceptance of the solution and boost the change management process. In the first stage, communication was focused on the leaders selected within the organisations (bottom-up approach). In the future, the system will be implemented in other healthcare settings and sites of the NGHA.

Results

  • Deployment of imaging referral guidelines based on best practices and user-friendly scoring system;
  • Enhancement of decision-making by primary healthcare providers through better access to reliable, up-to-date knowledge;
  • Standardisation of quality of care in all NGHA facilities;
  • Large scale deployment of guidelines in a result of effective communication with end-users and engagement of the healthcare facilities' CEO;
  • The optimisation of medical imaging related costs and improvement of the patient experience.

Description and goals

Amid the increased patients fall incidents, Royal Commission Health Services Program (RCHSP) decided to automate the manual fall risk assessment. The hospital digitalised two scales used in clinical practice to calculate the patient's likelihood of falling: Morse Fall Scale (for adults) and The Humpty Dumpty Falls Scale (for children). Both scales have been built into patient digital flowsheets, allowing automatic score calculations and decision-support. The system also suggests preventive measures recommended for different risk levels and thus improves patient safety.

Measures

Digitisation of the fall risk assessment process began with the retrospective audit that revealed staff compliance issues regarding manual fall risk assessment. The RCHSP informatics team and the HIS vendor implemented a new tool, integrated within the Hospital Information System. The fall risk assessment scales are now a part of a 24/7 care plan. The challenge was to achieve the broad acceptance of new assessment procedures, minimalise the time required to calculate the risk and translate output data into action. Automatic score calculations and decision-support features provide a risk level of each patient. Pop-up messages and alerts support relevant, evidence-based fall prevention measures.

Results

  • Simplified identification of patients at risk of falling;
  • Improved patient safety and higher convenience of fall risk calculation by staff due to automated calculations and decision-support features;
  • Staff compliance with fall risk assessment documentation reached almost 100%;
  • Successful implementation due to engaging management and the hospital's staff in the early stages of system design and development;
  • Integration of scales within the existing information system to improve data exchange and workflow management.

Outstanding ICT Innovation

Description and goals

Ministry of Health & Prevention aimed to deploy a universal and automated newborn hearing screening in all MOHAP maternity hospitals. A re-designed system, which has been integrated with the existing Electronic Medical Record (EHR), enables to coordinate the testing procedures and facilitate data flow in order to detect hearing impairments within the first month of child's life and take appropriate clinical measures. The "Newborn Hearing Screening" IT-driven solution was designed and implemented in-house as a result of cooperation between IT experts and clinicians, under the umbrella of "Informatics driven clinical excellence."

Measures

Early detection and relevant medical interventions are crucial to minimising the impact of hearing loss on a child's development. The new AI-based system registers children born in the hospitals, stratifies risk following the identified factors, navigates through complex workflows, generates referral for ENT (Ear, Nose, Throat) reviews in case of hearing loss symptoms, assigns appropriate ICD-10 code in the baby's digital chart. Members of the care team are reported automatically about screening results. Clinical decision support features have been developed to streamline the process to reduce cognitive load on physicians and nurses.

Results

  • All UAE newborns will receive appropriate testing towards hearing loss, counselling, and treatment to avoid physical and mental disabilities and reduce mortality;
  • Simplification and automation of the workflows and screening process;
  • Coordination of care over children through the access to full data on the Electronic Medical Record;
  • The standardisation of newborn care and population screenings programs in all MOHAB hospitals;
  • High (93%) workflow compliance achieved within the first few months.

Description and goals

Ministry of Health & Prevention of the United Arab Emirates conducted a study to examine the feasibility of expanding an existing automated outpatient pharmacy across the other seven facilities. The study bases on the outcomes gathered over the 12 months from the automated outpatient pharmacy located in Fujairah Hospital and conventionally-managed outpatient pharmacy in Al Qassimi Hospital. Both quantitative and qualitative indicators have been monitored to validate whether the robotic pharmacies are to bring improvements.

Measures

The goal of the study was to review if automation in pharmacies can improve patient satisfaction and generate savings in local healthcare settings. The rising number of outpatient visits and shortages of healthcare professionals demand better use of human resources and automation of repetitive, simple tasks. The evaluation included indicators like the number of served patients, prescriptions and line items filled, completeness of dispensed orders, filling time and "overtimes". As a result, success factors of deploying automated pharmacies have been identified. The study highlights the added value achieved by improving patient experience and the redeployment of human resources.

Results

  • A potential annual saving related to the replacement of traditional pharmacy workflows was estimated at 490.900 AED;
  • Various improvements were observed regarding, i.e. average time from prescription order to dispensing, expired inventory, inventory stock levels, a turnaround of unused or uncollected medications into circulation etc.;
  • Automated pharmacies' efficiency depends on the integration of CPOE, EMAR, EMR and the automatic dispensing system software to ensure fluent resupply;
  • Average installation of automation pharmacy can potentially enhance performance allowing to redeploy seven full-time-employees to high-value tasks;
  • The test installations and study enabled to develop guidelines regarding the automation of outpatient pharmacies.

Description and goals

Royal Commission Health (RCH), as the first hospital in the Kingdom of Saudi Arabia, implemented an integrated chatbot Wateen to optimise the patient's journey and improve communication with patients. RCH adapted and customised ready-to-use system to the local settings, developed new functions and integrated the tool within the hospital information system (HIS) by applying the chatbot's API. Users can book and modify appointments, check ER waiting times, request medical forms etc. Due to the outbreak of COVID-19 pandemic, the hospital also released Wateen Coronavirus Chatbot to update communities on the novel virus.

Measures

The challenge was to build a chatbot that is easy to manage for all patients. Using Natural Language Processing, Wateen Chatbot recognises keywords in sentences entered by the user (in Arabic and English) and responds automatically. AI-driven functions detect incorrect words and undefined questions, match them with the database, and guides the user to receive the information needed. By integration with WhatsApp, the tool is broadly accessible and responds to patients requests in real-time. Compatibility with HIS facilitates the acquisition of critical data.

Results

  • Chatbot fosters communication with the patients, automates administrative tasks to reduce the overall burden on staff;
  • Due to its flexible architecture, it can be implemented in other healthcare facilities;
  • The hospital can monitor the patient's journey and the patient's experience to improve the quality of care;
  • y using a standardised system, integration via API and customisation, the full integration was completed within one month;
  • It allows to reduce human errors, increase patients' satisfaction, optimise patient care and patient journey, improve management in the ER and patients flow, introduce new services.

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