Essay Example on Master Patient Index: Key to Accurate Patient Identification & Records

Introduction

A Master Patient Index (MPI), also described as a patient registry is an electronic database holding demographic information on patients receiving healthcare services (Zhao, 2018). As the MPI match and links an individual's identity based on a combination of information such as patient name, gender, address, among others, it plays a fundamental role in patient information integration. For instance, the MPI provides accurate identification of patients along with their health records since it maintains a central registry every patent alongside their demographics. Additionally, the MPI enables the update of information by eliminating duplicate registration entries for a specific patient through deterministic and probabilistic approached to match records. Within the patient information integration database, the MPI supports the provision of timely health records. The MPI creates a proper link between patients and clinical information that can be acquired at a particular time, such as information about facilities an individual has visited (Zhao, 2018).

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How Existing Differences in Data Formatting Will Impact Ability to Integrate Data with Information Systems

Correspondingly, the existing differences in data formatting could impact the ability to integrate data with information systems by affecting data cleansing, manual data entry, data conversion, and curation. Data curation is the integration of data collected from different sources. With the existing differences in the data formatting, this affects data curation, which involves annotation and presentation of the data to maintain value. Such difficulties negatively jeopardize the integration of data with information systems. In data conversion, having similar data sets makes it easier to convert data from one format to another. However, with the differences in the data formatting identified in Independence Medical Center, the differences will make it harder to integrate the data with information systems due to the data conversion complication.

Still, data cleansing will be affected since it might require manual cleanup, which has the potential of wrong entries. Due to the different dataset formats, this makes it difficult for automated data cleansing hence negatively affects the ability to integrate data with information systems with ease. The varying data formats in Independence Medical Center could change manual data entry since some information may not be compatible with internal data representation. Such issues deliver a significant impact on the ability to integrate the data with information systems.

Data Quality and Integration Issues Influencing the Foundation for Independence Medical Center's Database Architecture and Design

In its practices, Independence Medical Center applies three databases, Patient Billing Phys Database; Patient Billing Clinic Database; and Customers Clinic Database. The use of multiple databases poses a significant threat to the data integration and data quality for Independence Medical Center's database design and architecture due to loss of data integrity and gain complexities. For example, they could develop conflicting database roles for different users. Moreover, the various data entry methods in Independence Medical Center influence the database design and architecture since they define the type of datasets to be included in the central database. Also, the different data entry methods affect the dataset variables, which equally affect the foundation for Independence Medical Center's database design and architecture.

Data Integration Strategy Recommendation for Independence Medical Center

Since the significant challenges affect data integration in Independence Medical Center involve multiple databases, different data formats, and sources of information, the shared storage integration strategy would be appropriate. Often defined as data warehousing, this strategy involves standardized visualization of data by creating and storing a copy of acquired information. Data warehousing will help offer versatility in the EHR integration to provide value-based care (Arunachalam et al., 2016). Because of different data schema in Independence Medical Center, data warehousing will ensure ease in data acquisition, conversion, migration, data cleansing, normalization, and standardization. Also, data warehousing will ensure Master Patient Index to maintain data quality.

Conclusion

In conclusion, the best practices, methods, procedures, and policies for data integration include point to point communication, focusing on a service-oriented architecture and developing a proper enterprise service bus to ensure proper data flow. Also, the concept of microservices is relevant in data integration, along with real-time synchronization, to guarantee data quality. These practices enhance the ability to extract, transform, and load data, which is essential in data integration.

References

Arunachalam, S., Page, T., & Thorsteinsson, G. (2016). Healthcare Data Warehousing. i-Manager's Journal on Computer Science, 4(4), 1. http://search.proquest.com/openview/3edc1e12665404b2b68c63b1a2e672ed/1?pq-origsite=gscholar&cbl=2037358

Zhao, J. (2018). Identification of Master Patient Index (MPI) Record Challenges from Healthcare Professionals' Perspectives. Central Michigan University.