Healthcare Data Governance Software to Unify Data for Decision-Making

Data governance software is used by huge academic medical centers that have hundreds of beds and serve millions of outpatient visits and tens of thousands of inpatient admissions annually. Healthcare systems admit the process of turning into analytics-driven industries, which makes data the most valuable asset yet the most challenging in management.

Healthcare organizations strive to grow into advanced analytics organizations that can handle huge volumes of data and apply predictive analytics to achieve the best outcomes. Data governance software allows medical systems to standardize data, assign responsibilities, and develop a multi-year roadmap to guarantee sustainable data quality and accessibility. In this post, healthtech experts from the Belitsoft software development company share their ideas about the benefits, features, and areas of application of healthcare analytics.

Applying relevant analytics allows healthcare organizations to easily transform to value-based care, as they have timely access to reliable data sets. For healthcare providers, there should be a single source of trustworthy information that is collected from disparate sources and can be used by multiple experts for various purposes. This goal is achieved by both technological solutions and solid frameworks for data management. Besides analytics, it is the governing body that sets procedures and execution plans to keep the data safe, accessible, usable, and credible.

Challenges of Academic Healthcare Centers on the Way to Advanced Analytics Organization

Data governance software and analytics applications help providers to deal with a bunch of tasks. The challenges that those organizations want to solve can be divided into three groups:

Challenges with data gathering

Integrating data from numerous internal applications and systems, such as inpatient and ambulatory electronic health records (EHRs), lab data and pharmacy systems, and enterprise resource planning (ERP) systems.
Collecting data from external sources, such as affiliated providers' EHRs, payers systems, third-party laboratories and pharmacies, and benchmarking sources.
Time-consuming processes of manual collection, acquisition, and data validation.
Insufficient time left for data examination and search for improvement opportunities.

Challenges with data quality

Necessity for a comprehensive data clean-up driven by inaccuracies and missing information caused by various data sources.
Conflicting data, such as different length of stay (LOS) measures in various reports, caused by disagreements in timing or variations in data type definitions.
Absence of standardized terms and definitions.
Lack of proper data governance practices to validate the accuracy of existing analytic outputs, such as dashboards, scorecards, etc.

Challenges with data usage

Absence of an efficient solution to streamline data processing instead of increased staffing.
Necessity to develop a single source of data for clinical and operational end-users, and other people engaged while taking into account their different levels of training and expertise.
Data gaps and breakdowns in the process of reporting key metrics as a result of implementing new systems, such as modernized revenue cycle systems.
Difficulties with providing relevant decision-makers with the right data.
Absence of users’ trust in the data, as a result of inaccurate, conflicting, or missed information.

Features of the Analytics Applications to Address the Data Governance Challenges

Data governance software and related analytics applications help healthcare organizations effectively manage their data and guarantee that it is clear, reliable, accessible, and safe for users. Here are the features such apps perform:

Automation of the data-gathering procedures.
Providing accurate data for decision-making processes on time.
Appropriate data availability to proper users.
Focusing on determining and applying improvements rather than just data reporting.
Assuring data quality with the help of standardization, process engineering, and developing and tracking of the data quality measures.
Integrating applications that facilitate data engagement and informed decision-making, such as data glossaries, training resources, metadata databases, and near real-time access to reliable data sets.
Allowing for data access to clinical and operational users per their needs.
Monitoring the usage of the enterprise data warehouse (EDW), such as achieved optimizations, decreased reliances on non-enterprise data solutions, and assessing the apps effectiveness to ensure stakeholders are utilizing the developed business intelligence (BI) solutions.

Organizational Measures for Smooth Analytics Implementation

Implementing data governance software and additional analytics requires healthcare organizations to handle a range of tasks, such as data stewardship, quality issues, and availability opportunities. Those tasks demand the active participation of the senior leaders and correlation of the data governance with real clinical and operational processes to achieve the necessary level of engagement. The formation of the data governance committee inside healthcare systems helps to achieve the best results. The leaders of healthcare organizations are responsible for providing relevant technological, clinical, and operational expertise to form the committee.

The data governance committee sanctioned by senior healthcare leaders should be given executive authority to manage data, business intelligence, and information assets. However, it should be clear that the committee does not own data, it makes the utilization of the data easy for generating proper decisions. The purpose of the IT experts is to bring high-quality data into the hands of relevant end users. Those users are mostly clinical and operational decision-makers who work on improving care.

The data governance committee unites clinical, executive, and healthcare technology partners to jointly develop and optimize information assets so that they can serve the organization’s goals and target achievement. The governance also covers the determination of the sources of truth, record systems, distribution of appropriate roles and responsibilities, standards of the information delivery, and certified enterprise reports and dashboards. Besides, the committee deals with data security and access rights.

The committee can be divided into several groups and teams, each of which has particular responsibilities:

The Executive Group deals with vision and develops strategies for improvement actions.
The Advisory Group works with tactics and solves data quality issues, sets priorities, and organizes working groups.
Working groups include subject matter experts who operate in specific domains that the group is formed to study.
The Support Team unites chairs, facilitators, and knowledge managers who deal with technologies and improve clinical and operational processes.

Data management cannot be given a low priority. End-users should operate high-quality data in their routine to drive progress and sustainability. Leaders within the committee should possess both the technological and social skills required for excellent customer service to be able to build rapport with clinical and administrative executives.

Benefits of Healthcare Data Governance Software

Healthcare networks that have already implemented relevant healthcare analytics report the following improvements in their data management processes:

Transforming from a fragmented business intelligence landscape to a more unified enterprise approach with embedded advanced BI architecture, essential for managing large data volumes and utilizing predictive analytics.
Development of the long-term roadmap for business intelligence and data governance.
Increased number of standardized data definitions approvals during a year.
Enabling end-users to productively possess and manage their information demands.
Significantly increased rates of the key clinical and operational executives' participation in data governance meetings.
Training end-users to enhance their analytical skills and encourage them for better performance.
Building trust in data and the spread of responsible data management among end-users due to quality fixes and improvements.
Engagement of the clinical and executive staff in data governance across the system and developing a data-driven mentality among the staff of healthcare networks.

How Can a Reliable Healthcare Software Development Company Help?

Healthcare software development companies, such as Belitsoft, provide outsourced services for building powerful data operating systems. They can also integrate required analytics applications into the ecosystem of healthcare data analytics companies.

Healthtech companies develop integrated data platforms that allow for collecting, storing, processing, and analyzing large volumes of data from such sources as electronic medical records, clinic management systems, laboratory systems, financial systems, etc. Those platforms offer the following possibilities:

Automate data processing workflows (cleansing, standardization, and normalization).
Configure scalable data warehouses.
Set up and implement analytical tools for creating dashboards, reports, and data visualizations.
Ensure a high level of data security and compliance with healthcare regulations such as HIPAA.
Integrate machine learning and AI into analytics.

Healthtech companies also help build special analytical applications to implement data governance software with the following features:

Gathering data from various sources into a single repository, such as an enterprise data warehouse (EDW).
Automated data extraction and reporting.
Data modeling on the basis of common vocabulary and data definitions.
Data governance dashboard to monitor and manage such metrics as the quantity of identified data owners, documented processes, and saved dollars or prevented costs.

If you are looking for competent assistance in data analytics, data infrastructure, data platforms, HL7 interfaces, workflow engineering, and development within the cloud (AWS, Azure, Google Cloud), hybrid, or on-premises environments, the healthcare software development company Belitsoft can serve these needs.