master patient index
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2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
J Lintz

Abstract Background A Master Patient Index (MPI) system is essentially a database that is built into an Electronic Health Record (EHR) system to maintain a unique identifier for each patient seen at the organizational or enterprise level. The current study is to identify the gaps between the revenue cycle and patient information functionalities used in Electronic Health Records (EHRs) in collecting and reporting patient information. Additional focus was on perceptions of healthcare professionals who are familiar with MPI systems on the impact of these gaps of ensuring maximum reimbursements and adequacy of services provided. The study also sought to glean their perceptions vis-a-vis key challenges in the EHRs that affect organizational workflow. Methods A semi-structured questionnaire was used to collect information from healthcare professionals responsible for the MPI. The population studied is healthcare organizations using EPIC as the Electronic Health Records (EHRs). Results This study confirmed systems gaps between EPIC and other downstream systems used by the healthcare organizations to process patient information, as well as the extent of patient matching challenges that healthcare professionals have encountered in the MPI. These challenges include varying methods of matching patient data; lack of data standardization; absence of policies and procedures; frequently changing demographic data; multiple required data points needed for record matching; and default and null values in key-identifying fields. Conclusions The study offered evidence found in the literature that implies that duplicate records continue to plague healthcare organizations. Widespread technological interoperability insufficiency among healthcare facilities points to future challenges for federal policy makers as they seek to promote interoperability programs to demonstrate meaningful use of certified electronic health record technology (CEHRT). Key messages The study confirmed that despite a low level of duplication in the MPI, the organizations have lost revenue during the last 6 months. Duplicate records in the EHR systems has led to downstream problems in the revenue cycle, including denials and insurance takebacks that impact hospital revenue cycle efficiency.


2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Raffaella Vaccaroli ◽  
Frédéric Markus ◽  
Samuel Danhardt ◽  
Heiko Zimmermann ◽  
Francois Wisniewski ◽  
...  

2019 ◽  
Vol 8 (2) ◽  
pp. 83
Author(s):  
Lori Thorell ◽  
JosephDal Molin ◽  
Justin Fyfe ◽  
San Hone ◽  
SuMyat Lwin

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Jacob Krive ◽  
Annamarie Hendrickx ◽  
Terri Godar

Population health relies on tracking patients through a continuum of care with patient records from disparate sources. An assumption is made that all patient records are connected. The reality is: they are not. Disconnected records negatively impact results: from individual patient care management through population health's predictive analytics. An enterprise master patient index (EMPI) system can be employed to connect all patient records, but it requires comprehensive tuning to maximize the number of connected records. This presentation describes how one large healthcare integrated delivery network tuned their EMPI system to maximize the number of connected patient records across all sources.


2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Stacey Hoferka ◽  
Ivan Handle ◽  
Steven Linthicum ◽  
Dejan Jovanov ◽  
William Trick ◽  
...  

In support of Meaningful Use public health reporting, health departments are expanding their capacity to receive electronic health data. The Illinois Department of Health is working with the Illinois Health Information Exchange to build services and applications to improve the quality and utility of surveillance data. The Master Patient Index is an innovative component of the technology that will integrate public health data across surveillance systems. This presentation will cover the application of the MPI to ambulatory syndromic surveillance as well as other surveillance systems and highlight potential use cases.


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