Case-Mix products
Enara APR
This is the data analytics solution developed by Sigesa for the management and analysis of hospital case-mix, designed to facilitate decision-making based on objective and comparable information. It enables the analysis and monitoring of healthcare activity, based on the Solventum™ APR-GRD patient grouping system.
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Enara CAL
A solution designed to calculate standardised, validated and internationally recognised healthcare quality indicators (AHRQ). It enables hospitals to analyse the quality of care and patient safety in a straightforward manner.
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Enara MLS
Machine learning models developed by Sigesa that enable the creation of benchmarks, as well as the performance of predictive analytics on indicators and the simulation of case scenarios.
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Enara CRG
A data analytics solution developed by Sigesa for analysing population health, calculating and analysing population-level risk adjustment indicators, and analysing and managing patients with chronic conditions based on the Solventum™ CRG (Clinical Risk Groups) population stratification algorithm.
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Enara Emergency Room
A solution developed by Sigesa that enables the standardisation, validation and analysis of activity in the A&E department, presenting relevant indicators regarding activity, treatment and waiting times, triage, return visits, coding quality, etc.
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Enara Outpatient
A solution that enables the standardisation, validation and analysis of outpatient department activity.
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SmartView AE
A solution specifically designed for department heads and specialist doctors. It provides a summary of the data gathered by the various solutions on the Enara platform.
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SmartView Manager
A solution designed for senior management at the hospital, available on mobile devices. It provides summarised information that allows users to quickly and easily gain an overview of the hospital’s current situation.
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TeamCoder
A versatile, adaptable and highly customisable expert coding solution. It is designed by and for coders, and includes a range of tools to streamline and optimise the coding process.
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Alcor GRD
A data analytics solution developed by Sigesa for the management and analysis of hospital case-mix, designed to facilitate decision-making based on objective and comparable information. It enables the analysis and monitoring of healthcare activity, based on the Solventum™ IR-GRD patient grouping system.
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Alcor CAL
A solution designed to calculate standardised, validated and internationally recognised healthcare quality indicators (AHRQ). It enables hospitals to analyse the quality of care and patient safety in a straightforward manner.
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Alcor CCI
Calculate the GRD at any stage of the patient’s care pathway and save the coding so that the patient and the GRD associated with that time period can be tracked over time.
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Alcor POB
A data analytics solution developed by Sigesa for analysing population health, calculating and analysing population-level risk adjustment indicators, and analysing and managing patients with chronic conditions based on the Solventum™ CRG (Clinical Risk Groups) population stratification algorithm.
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Solventum™ APR-DRG (All Patient Refined)
A patient classification system that enables the most detailed hospital case data to be grouped, providing information on the severity of the illness, the patient’s risk of mortality and the impact on the cost of the service.
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Solventum™ IR-DRG (International Refined)
Patient Classification System covering all hospital activities, including outpatient services (A&E, day hospital, outpatient clinics, etc.).
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Solventum™ MS-DRG
The MS software assigns a GRD to each patient based on data from hospital discharge records. It is particularly useful for calculating certain AHRQ (Agency for Healthcare Research and Quality) indicators.
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Solventum™ CRG (Clinical Risk Groups)
A population-based patient classification system that utilises all clinical data on patients and links this to their medical history and demographic characteristics in order to assign each individual to a group adjusted for their health status and severity level.
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