6 Keys to Accurate Healthcare Data Conversions
When switching to new systems, many healthcare facilities convert or archive patient and financial data to suit their specific needs. To maintain accuracy in data, legacy system data is put through many processes and checkpoints to maintain a comprehensive legal medical record. By thinking through the six topics outlined below and answering tough questions up front, your health system can drive high levels of accuracy, accountability and efficiency throughout your next healthcare data conversion project.
From the outset, it is important to clearly define the goal of your data conversion project, and how you will measure success. To ensure a smooth process, it is equally important to define deadlines, the roles and responsibilities of everyone involved, as well as establishing guidelines and expectations for communication. Having expectations and documentation, like a RACI chart, in place from the beginning empowers all team members by telling them what they should be doing when, and helps the team understand the necessary measures to take if and when a part of the project deviates from the course. Some helpful questions to ask up front are:
- Who is managing the overall project?
- Who owns each conversion process (systems, loads, quality assurance/testing, issue escalation)?
- Which team members have decision-making power, and which team members are responsible for execution
- What are the deliverables for the project, or what is the expected outcome?
- What key deadlines need to be hit to keep the project moving?
- Does the schedule allow for additional process design changes during the project?
Setting overall project expectations helps lay the groundwork for communication planning. Key stakeholders and decision-makers need to be involved during every step of the process to ensure the project is staying on track, which can require managing up and involving the right people at the right time. Keeping communication clear, concise and consistent is the best way to manage the expectations of everyone involved. When planning a communication strategy, consider the following:
- Who in the organization has a stake in the data conversion project, and how often do they need updates?
- Are the appropriate people being included in critical meetings?
- What level of detail needs to be discussed during multi-disciplinary meetings?
- What kind of issue log is being kept and who is responsible for maintaining the record?
Master Patient Indexes (MPI)
An accurate and complete master patient index (MPI) is critical to a healthcare organization’s success. Physicians and other healthcare providers need the most up-to-date records available in order to deliver the best patient outcomes. During data conversions, it is paramount that all disparate electronic medical record systems are integrated to create comprehensive patient records. In order for the master data to be operable across multiple systems, all data should be thoroughly analyzed to make sure it matches both the source and target system. When analyzing your MPI, address these questions:
- Does your MPI contain unmerged patients and visits, incorrect characters, name typos or mismatched identifiers?
- If so, what process is in place to mitigate issues before the new, consolidated MPI is populated?
- What is the primary source for data that all connected systems follow for medical record numbers and visit details?
- Will there be gaps that affect matching converted data to the record?
- When will MPI be processed throughout data conversion?
Deep knowledge of both source and target systems is necessary for an accurate and efficient data conversion project. Having system experts on hand can alleviate a lot of headaches throughout the process. System and project specifics should be thought through and well-documented before converting any data. For a baseline evaluation and comparison of your source and target systems, answer these questions:
- What data formats are used?
- What databases are being used to power your system, and how many facilities pull from each database?
- How much storage space is needed?
- How much time and money is willing to be spent on system experts?
- What challenges do the system specifics pose for the overall project?
- How will data validation and testing be handled?
- What processes will be directly impacted by changes to data systems, and how can the impacts be lessened?
Data integration can be complex, tedious and frustrating. However, most integration questions are about data formats and field mapping across systems to make sure all the elements line up. Having a solid plan and diligently analyzing source and target data up front will help alleviate integration issues. When putting together an integration plan, think about these questions:
- Which system is handling data for transfer?
- Are the source and target data formats compatible?
- If not, can the formats be made compatible through index files, data mapping or transformation?
- What resources are available to troubleshoot and assist in integration and solution design?
Validation & Testing
Once your data has been loaded, it needs to be validated and tested for accuracy and completeness. Validation and testing are two pivotal steps to evaluating the integrity of the data after the conversion and setting a standard of integrity moving forward. Both validation and testing require their own, unique strategies and special expertise from planning to execution. But as a starting point, consider these questions:
- What percentage of the data needs to be sampled, and should that sample include specialized cases?
- What types of visit data or documents need to be included in the sample?
- How will data evaluators be selected and trained prior to data validation and testing sessions?
- What is an acceptable error rate?
- What details need to be documented during testing in order to create a remediation plan for failed data?
Although answering these questions will get you started down the right path for your data, it is by no means a comprehensive guide to planning and executing a data conversion. The entire process requires collaborative thinking, technical expertise, patience, and experienced project leadership and management to keep things on the rails.
Worried about your next data conversion project? Let us help. At HCTec, we provide collaborative solutions for healthcare data conversions of all types. We also support legacy vendor systems before, during, and after new system implementations to free up internal resources for project work.