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Infusing Data Analytics into Healthcare

By: David Whitton, General Manager of Kodak Alaris - Eastern Cluster (Middle East, Africa, East Europe, Turkey & Russia)

Healthcare providers in the Middle East that leverage data driven from clinical and business analytics are discovering new opportunities to lower costs, provide better care for patients and establish health programmes. The on-going challenge, however, is in being able to effectively compile all forms of structured and unstructured health data into an analytics database.

Though clinical and business analytics can lead to dramatic improvements in patient care and business operations, it can be challenging to extract comprehensive information from healthcare data in unstructured formats such as email, faxes, text messages and paper, which can limit analytical outcome accuracy and usability. Forward-thinking organizations are using data classification, extraction and management software to free unstructured data that was formerly trapped, in order to realize a 360-degree patient view from all existing health data.  

As health data continues to increase in volume, variety and importance, organizations looking toward the future are implementing new strategies for collection, grouping and analysis. Smarter data can help healthcare providers integrate and identify correlations between previously inaccessible data, available in real or near-real time.

Benefits of Leveraging Health Analytics

New methods of applying clinical and business analytics give healthcare practices a holistic view of patient care and health trends. These analytics allow healthcare providers to move from basing business and patient care decisions on hindsight toward making decisions based on insight and foresight. Having access to health analytics has the following benefits:  

1. Help care providers identify health trends and risks.  

Clinical analysis allows healthcare practices to generate reports based on aggregated data at individual and group levels in order to identify illness trends, proactively treat patients and offer focused preventative wellness programs or advice. Real-time analytics can help predict disease outbreaks, enabling preventative measures such as offering vaccinations for illnesses like the flu and pneumonia, which traditionally have high costs of treatment. These measures not only reduce costs for the business and for patients, but they can also improve the overall health of the community.

Clinical analysis helps reduce hospital readmissions by helping clinicians provide comprehensive, proactive care and discharge at the right time. It can highlight complications that are commonly linked to primary illnesses so healthcare providers know what symptoms to watch for. This early warning can help care providers treat patients at the first sign of an exacerbated or secondary illness, and avoid readmissions reimbursement penalties. Clinical analysis also helps healthcare facilities allocate staff and device resources in real time in order to eliminate bottlenecks, reduce patient waiting times and provide optimal patient care and coverage. These proactive steps contribute to improved patient satisfaction and outcomes.

2. Allow care providers to see if treatments are effective. 

Clinical analysis allows healthcare providers to monitor the effect of treatments over time with individuals or groups. This real-time data can help clinicians change an ineffective or sub-effective course of treatment earlier in the patient care cycle, in contrast to the traditional “watch and wait” scenario. By changing a course of treatment earlier, healthcare providers can head off secondary disease, provide a structured, reassuring course of treatment, and improve the treatment effects for the patient and the overall success rate of the practice.

3. Enable decision making based on foresight. 

In the past, administrators and clinicians had to make the best decisions they could base on personal experience or data manually aggregated from databases and spreadsheets. Making decisions based on spreadsheets introduces unnecessary risk because spreadsheets are notoriously error-prone and labour intensive. Data management software is exponentially faster, more powerful and more reliable than manual legacy tools such as Excel, which were originally designed for finance.

For healthcare providers, this real- or near-real-time data analysis can improve patient care and quality of life because it is based on data gathered from silos across the entire practice, and is free of human intervention (therefore reducing error). Clinical and business analytics allow administrators and care providers to make decisions based on data offering supported foresight instead of guesses. Rich data and analytics give decision makers the ability to actually affect future results with a reasonable degree of confidence in the outcome. 

In conclusion, new health data analysis tools provide expanded opportunities for healthcare providers to streamline operations, improve patient care and outcomes, and reduce costs for the practice and the patient.

By leveraging advanced information management technology, healthcare providers can capture, classify and present aggregated data formerly trapped in structured and unstructured data formats. Once managed, this data can be used for business and clinical analysis that benefits the business, patients and population. By gathering critical data trapped in silos and systems across the business and practice, applying predictive analysis and making results available, clinicians, administrators, key decision makers and healthcare practices can lower costs for the organization and improve quality of life for everyone.

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