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Top 10 Health IT and Analytics Considerations for Effective and Efficient Care Management

Posted by Matthew Smith on May 23, 2016 1:55:44 PM

The demand for meaningful and actionable data in healthcare has never been as prevalent as it is today. While most healthcare organizations are utilizing some form of health information technology (“health IT”) platforms to capture clinical documentation, system integration and broad spectrum analytic capabilities offered by these platforms are very underdeveloped. As pay-for-value becomes the standard for healthcare service reimbursement, organizations are beginning to realize the importance of establishing more efficient and effective care management processes that are supported by robust health IT systems and analytics frameworks. Below are 10 key health IT and analytic considerations to enable an effective care management program.

  1. Data Governance. Data is the crux of healthcare improvement. It is critical to establish a data governance council consisting of an interdisciplinary team that is responsible for developing a set of processes that serve as a quality control mechanism for handling information. These mechanisms define lines of responsibility and establish methods to foster the accessibility, completeness, and integrity of data. Strong data governance that can validate the accuracy of the data is critical to instill trust among clinicians. The absence of a data governance structure exposes the risk of clinicians contesting the accuracy and usefulness of the performance information produced by the data, thereby reducing its value to continuous improvement initiatives.
  2. Health IT Strategy. An organization must develop a health IT and analytics strategy to determine the types of health IT necessary to support the clinical and operational processes of the organization. The most essential component in the development of a successful health IT strategy is to gain consensus from all affected stakeholders. Attempting to implement a strategy without the buy-in from the affected stakeholders will be extremely difficult, if not impossible, because clinicians will not support the efforts and may challenge the types of health IT implemented.
  3. Systems and Technology Framework. The systems and technology framework of healthcare organizations is very complex. Organizations must inventory the various systems and develop a blueprint to guide system selection, technical and functional builds, consistent standards, and information output. All of these aspects affect clinical operations, and the implications must be considered and risks mitigated. Neglecting this activity will have serious implications on system integration and data aggregation efforts.
  4. System Integration and Solution Architecture. Healthcare organizations have various technology systems and platforms that were typically implemented at a point in time to serve a specific business need without extensive thought or planning given to system integration. The result of this approach is that these systems are not designed to “speak to each other”. Organizations must build an enterprise architectural approach that allows platform integration of multiple disparate systems, supports system interoperability, and establishes a centralized master data management structure.
  5. Solutions Search and Selection. Commonly, a systems and technology inventory reveals gaps in the framework, and the organization must embark on a search and selection process to identify a system to fulfill the need(s). It is important to establish a systematic approach to IT system selection so that the evaluation of the systems is comparative. More important, the organization must enlist the help of an interdisciplinary team to evaluate and score the systems based on a pre-defined list of functionality and standards. The process must be executed very methodically, starting with defining the system requirements, developing the evaluation criteria, training the evaluation team, conducting the system demonstrations, reviewing test cases, and selecting the system of choice. In addition, the organization must establish an enterprise approach to system search and selection, which can help minimize ad hoc purchases that can conflict with the overall integration strategy.
  6. Workflow Redesign. Clinical workflow redesign is integral with any health IT solution implementation. Before even embarking on system selection, an organization must first understand the clinical workflow. This will provide insight to the existing processes and protocols and enable the organization to select a technology solution that will best support clinical operations by incorporating solution sets that promote workflow redesign around functional roles, care model redesign, clinical decision support, and clinical protocols. Failure to consider the clinical implications when selecting a system will lead to an underutilized system and decrease efficiencies.
  7. Clinical Health IT Optimization. Clinical care optimization is critical to maximize the value of the health IT system. Health IT systems are rarely used to their fullest potential. This underutilization can have negative impacts on many facets of a healthcare organization, including patient safety, quality of care, clinical performance, staff satisfaction, and revenue capture. The organization can improve the functional use of systems and applications through utilization evaluation, reeducation of clinical documentation requirements, and system functionality retraining for clinical staff. Failure to optimize clinical health IT systems leaves the organization vulnerable and at risk for poor coordination of care, fragmented communication, performance penalties, staff turnover, and decreased revenue.
  8. Integrated Analytics and Reporting Strategy. An integrated analytics strategy is imperative to establish a streamlined approach to developing, managing, updating, and reporting performance measures. Many organizations are faced with various regulatory, accreditation, and quality program reporting requirements. Typically, report writers will build ad hoc reports according to the specifications requested, but report reviews reveal that many of these reports include the same metrics. Organizations must catalogue the performance measures contained in all reports. This accounting should include the details of the measure (e.g., numerator and denominator), discreet data needed to calculate the measure, the source system for the data, the purpose of the measure, the report measure owner (both requester and developer), the user(s) of the information, and the user  status (internal or external). This will help the organization to delineate the various reports, identify duplications, and establish consistency across the clinical analytics and reporting requirements.
  9. Clinical Informatics and Analytics. In line with the analytics and reporting strategy, an organization must define an approach and process to ensure that solution capabilities enable the collection of discreet clinical data that supports the development of reliable, action-oriented reports. An important component to developing a sound clinical informatics and analytics process is having an interdisciplinary team composed of IT, clinical, and report analyst representatives. This team composition will ensure that the information needed from the clinical team is addressed, the technical team can build it, and that it is structured so that analysts can easily generate the necessary reports.
  10. Actionable Data Analytics. Once the type of information that is needed for analytical reports is determined and the process by which this information will be captured is defined, an organization needs to determine the most effective way to present the information, to whom the information should be provided, and how frequently in a timely manner. Most important is designing reports that present data in a usable, action-oriented, and meaningful way. The way in which data is presented can make the difference between impactful care management and quality improvement results and futile care coordination efforts.

Topics: HIT, Health IT, Data Analytics, Workflow Redesign, Data Governance

Three Keys to Improved Medical Practice Workflow Redesign

Posted by Matthew Smith on Apr 28, 2015 3:25:00 PM

New consumer-oriented service delivery sites such as retail clinics and virtual visits are popping up to fill voids in access to care. In order to successfully compete in the future, medical groups must evaluate the way they currently operate with a critical focus on managing patient access through the promotion of consumer-oriented services and efficient workflows. One way of competing in this new market is to increase access without adding locations or providers by improving the efficiency of existing locations and providers. Redesigned workflows place the patient at the center of the care model, with the goal of improving patient engagement and access to care. This results in a better patient experience and improved clinical outcomes at reduced cost.

1. Identify Care Model and Care Team

One of the key attributes in workflow redesign is to identify the care model and care team needed to ensure that providers and staff are practicing at the top of their license or skill set. This might mean transferring work from providers to clinical staff or from clinical staff to front office staff. It also entails identifying the most valuable use of all staff time. This may be achieved through effective use of technology while engaging patients through the use of patient portals, email, text messaging, and home monitoring.

2. Utilize Process Flow Mapping

Another attribute is to utilize process flow mapping to create a picture of the current-state workflows and identify areas of potential waste or bottlenecks. Once current-state workflows are mapped, utilize a team of providers and staff to create a vision for the future (or ideal state). Work as a team to eliminate as much waste as possible to move towards the future state. Establish performance targets for the ideal state and measure baseline performance to gauge progress. Conduct cycle time studies as part of the redesign effort as an effective measure of wait time (value-added vs. non-value added time). Test the redesign efforts and compare results to established targets and continue to modify until goals are achieved.

3. Optimize Technology to Meet Clinical Care Needs

Finally, ensure providers and staff are effectively trained on the practice management (“PM”) and electronic health record (“EHR”) systems and that the technology is fully optimized to meet clinical care needs. Spend time shadowing providers to evaluate how the system is used in practice and what changes can be easily made to better accommodate workflows. Make sure a local resource may be contacted with questions or advice as well as dedicated site-specific subject matter experts (“SMEs”) for immediate troubleshooting. Create a continuous learning environment, through the use of webinars, on-site educational sessions, and shadowing to increase provider/staff adoption of the technology, and reduce rework or general frustration due to a lack of training or appropriate optimization of the system.

Workflow redesign efforts, if successfully implemented, can significantly decrease non-value added time by allowing for increased time with patients and increased access to care. Improving operational efficiencies and optimizing electronic systems also increases provider and staff satisfaction thereby supporting a patient-centered environment.

Medical Practice Workflow Redesign, The Camden Group,

Topics: EHR, Care Model, Workflow Redesign, Medical Practice Workflow Redesign, Care Team

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