Healthcare IT is ever-changing and Perficient is on the forefront of this change, guiding the industry and those we serve toward a brighter future. We partner with healthcare companies to help people live their lives to their fullest potential today, using best practices and cost saving technologies and processes.
As we look to the future of Healthcare Information Systems, the effectiveness of an organization is measured by four areas; the heart of who we are and do is all about the integration, accuracy, consistency and timeliness of health information.
Healthcare organizations are among the most complex forms of human organization ever attempted to be managed, making transformation a daunting task. Despite the challenges associated with change, organizations need to evolve into a data-driven outcomes improvement organization.
They aggregate tremendous amounts of data – they need to figure out how to use it to drive innovation, boost the quality of care outcomes, and cut costs.
Data Integration Challenges
Besides members and providers, as well as internal/external business partners and vendors, there are a multitude state and federal regulatory/compliance agencies that insist on having our information on a near real-time manner in order to perform their own functions and services. These integration requirements needs are constantly changing.
As an EDI Integration Specialist, I have seen many organizations struggle to constantly keep up with the business needs of their trading partners, state and federal agencies. Often, as our trading partners analyze the information we have sent them, they discover missing data or inconsistencies.
This requires a tedious and painful iterative remediation process to get the missing data, and results in resending massive amounts of historical data or correcting/retro-adjudicating claims. Adjusting and recouping claim payments is always painful for all entities involved, especially providers, with possible penalties or sanctions.
In the last few years, I have worked with several clients on getting their claims information loaded into their state’s All Payer Claims Databases (APCDB) and CMS to get their health claims reimbursed. We struggled to get the complete data set loaded successfully, and to meet the rigorous quality assurance standards.
It required several attempts working with their legacy systems to get the necessary data into the correct format. It required a great deal of coordination, testing and validation. Each state has a different submission format and data requirements, not necessarily an 837 EDI format, including one state that had a 220+ field delimited record format (Rhode Island).
We spent a great amount of time in compliance validation, and each submission required a manual effort. We constantly had to monitor each submission’s file acceptance status, handling original and adjusted claims differently using the previously accepted claim ID. If files were not submitted accurately and on a timely manner, there were significant fines imposed.
Several times we discovered that even though the files were successfully accepted, there were still missing information which need to be resubmitted. To be honest, it was a logistical nightmare.
As we design and develop data integrations, APIs and extracts, we often ‘shortcut’ to deliver data due to competing priorities, quickened project delivery schedules or limited development/testing staff. This leads to not giving our full attention to the complete requirements of the client/trading partners.
Companion guides and documentation are vague and say ‘send if known’, realizing several years later that these ‘shortcuts’ will be found out and possibly leading to penalties and corrective action plans. Sometimes legacy system and technical limitations lead to not having the complete record set that is required.
Limitations of electronic health record (EHR) system combined with variable levels of expertise in outcomes improvement impede the health system’s ability to transform.
In many healthcare organizations, information technology (IT) teams—including data architects and data analysts—and quality and clinical teams work in silos. IT provides the technologies, designs and delivers reports, without a clear understanding of the needs of the quality and clinical teams.
This can sometimes turn into a finger pointing exercise. Quality and clinical teams claim IT is not delivering the data they need to succeed, while IT insists that others are not clearly articulating what they need. It takes clear-eyed analysis to see that the teams are failing to work together to prioritize their outcomes improvement initiatives and drive sustainable outcomes.
How Can Health Care/System Redesign Be Put Into Action?
At Perficient, we can provide a comprehensive picture of your organization’s information needs and provide you with a path to implementing complex system redesigns and simplify integrations. Putting health care redesign into action can be done in the following four general phases:
1. Getting started. The most important part of building a skyscraper is looking at the requirements, developing a blueprint and building a robust foundation. The first phase involves devising a strategic plan and assembling a leadership team to focus on quality improvement efforts. The team should include senior leaders, clinical champions (clinicians who promote the redesign), and administrative leaders. We need to develop a long-term strategy that sunsets legacy systems, consolidates business functions, build synergies between departments and aggregates data into a central repository. High-level needs assessments are performed, scope is defined to limit effort, and a change management process is created to assist in project management. A business governance committee determines what and when business decisions are implemented. Technical/architectural review committee approves the overall design and data governance of systems, interfaces and integrations of enterprise systems.
2. Review the complete electronic dataset. That includes building a corporate data dictionary (including pricing/benefits, membership, providers, claims, utilization, brokers, authorizations/referrals, reference data and code sets, etc.) and set priorities for improvement. The second phase involves gathering data to help inform the priorities for improvement. Once data requirements are gathered, performance measures such as NCQA/HEDIS that represent the major clinical, business, satisfaction, and operations goals for the practice can be identified. Corporate reporting and process needs are critical at this phase to look to ensure compliance and meeting internal and external customers’ requirements. The creation of dashboards and user reports that are easy to manage provide the right information at the right time can make the difference of cost savings and effective management throughout the organization. Using these dashboards allow users to keep an eye on the overall health and utilization of the services that they provide to their members.
One of the most helpful EDI integration practices I have found is to perform a source to target gap analysis between core claims/membership systems, my inbound/outbound EDI staging database, and the EDIFEC/GENTRAN mapping logic which translates the data to the outbound and from the inbound x12 EDI 837 Claims and 834 Membership enrollment files. This document also identifies any transformations, conversions or lookups that are needed from propriety values to HIPAA Standard values. By looking at every EDI Loop/Segment/Element and mapping it all the way through, I was able to identity data fields that were not being sent or being sent incorrectly. I give this mapping document as part of my technical specification documents to my EDI developers, which I customize for specific trading partners while I was reviewing the vendor’s companion guides.
3. Redesign care and business systems. The third phase involves organizing the care team around their roles, responsibilities, and workflows. The care team offers ideas for improvement and evaluates the effects of changes made. Determining how an enterprise integrates and uses often disparate systems is critical to determine timely, complete and accurate data/process flow. The design, creation and use of APIs and messaging technologies assist in getting information extracted, transformed and loaded (ETL) is critical, especially if information is to be used real-time web-based portals. Evaluation of easy to use yet robust batch process ETL tools, such as Informatica, become the cornerstone of any data integration project. Healthcare organization relay upon reporting tools to evaluate, investigate and reconcile information, especially with their financial and clinical systems. Imaging, workflow management and correspondence generation systems are used to create and manage the communications.
4. Continuously improve performance and maintain changes. The fourth phase includes ongoing review of clinical and financial integration outcomes and making adjustments for continued improvement. As we are looking to the future, we need to look at the IT architecture and its ability to expand with the ever-changing technology and needed capability models. Perficient is a preferred partner with IBM, Oracle and Microsoft with extensive experience for digital and cloud based implementations. Using these technologies gives our clients the ability to expand their systems, application servers to be spun up on demand based on need and growth, allow for failover, allow for redundancy, distributed and global databases to be employed, virtualization of software and upgrades be made while being transparent to the end users.
Perficient’s health information technology (IT) initiative for the integration of health information technology (IT) and care management includes a variety of electronic methods that are used to manage information about people’s health and health care, for both individual patients and groups of patients. The use of health IT can improve the quality of care, even as it makes health care more cost-effective.
Bringing in an Analytics/Reporting Platform
Implementing an enterprise data warehouse (EDW) or a data lake/analytic platform (DLAP) results in the standardization of terminology and measures across the organization and provides the ability to easily visualize performance. These critical steps allow for the collection and analysis of information organization-wide.
The EDW/DLAP aggregates data from a wide variety of sources, including clinical, financial, supply chain, patient satisfaction, and other operational data sources (ODS) and data marts.
It provides broad access to data across platforms, including the CEO and other operational leaders, department heads, clinicians, and front line leaders. When faced with a problem or question that requires information, clinicians and leaders don’t have to request a report and wait days or weeks for data analysts to build it.
The analytics platform provides clinicians and leaders the ability to visualize data in near-real time, and to explore the problem and population of interest. This direct access increases the speed and scale with which we achieve improvement. Obtaining data required to understand current performance no longer takes weeks or even months.
Application simplification takes the confusion as to the consistency and the accuracy of data within an organization. Per member/Per Month (PMPM) reporting is delivered in a standard format throughout, regardless of line of business.
The analytics platform delivers performance data used to inform organizational and clinician decision-making, evaluate the effectiveness of performance improvement initiatives, and increasingly, predict which patients are at greatest risk for an adverse outcome, enabling clinicians to mobilize resources around the patient to prevent this occurrence.
An analytics platform is incredibly powerful and provides employees and customers with the ability to easily visualize its performance, setting the stage for data-driven outcomes improvement. However, healthcare providers and payers know that tools and technology alone don’t lead to improvement.
To be effective, clinicians, IT, and Quality Assurance have to partner together to identify best practices and design systems to adopt them by building the practices into everyday workflows. Picking the right reporting and analytical tool and platform is critical to the success of the integration project.
Big data tools such Hadoop/HIVE/HUE and cloud technologies are used to bring together various data source together into a unified platform for the end-user.
Roadmap to Transformation
Perficient provides a full service IT roadmap to transform your healthcare organization and achieve both an increased personalization of care via the same path: digital transformation in healthcare. New health system technology, such as moving beyond basic EMR (Electronic Medical Record) infrastructure to full patient-focused CRM (Customer Relationship Management) solutions, has enabled healthcare organizations to integrate extended care teams, enhance patient satisfaction and improve the efficiency of care.
We connect human insight with digital capabilities in order to transform the consumer experience and deliver significant business value.
For more information on how Perficient can help you with your Healthcare IT integration and analytical needs, please see https://www.perficient.com/industries/healthcare/strategy-and-advisory-service
