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Focal Areas for Improving Patient Matching in Provider Settings

Having updated EHR systems with established methods of exchange and a national strategy for stronger patient matching will greatly benefit healthcare.

patient matching ehr patient data

Source: Thinkstock

By Elizabeth Snell

- Accurate patient identification is a critical aspect of healthcare, especially as healthcare organizations are implementing new EHRs and connecting to HIEs in the push toward nationwide interoperability. Patient matching issues can occur with EHR use, and can be detrimental to patient safety and create administrative errors within organizations.

A 2018 Imprivata survey found that 42 percent of CIOs said patient matching was a top focus area, while approximately one-quarter said it was not currently a main priority but that it should be.

Thirty-eight percent of respondents admitted they did not know the percentage of external (between institutions) mismatched patient records that would impact their respective organizations. Eighteen percent said they did not know the percentage of mismatched patient records within their institution.

Additionally, 17 percent of CIOs said a patient matching error led to patient harm at their institution.

Outdated systems, duplicate medical records, human errors, and miscommunication can all contribute to patient identification errors, stated Imprivata Chief Medical Officer Dr. Sean Kelly.

READ MORE: How an Alaska HIE is Improving its Patient EHR Matching Strategy

Healthcare organizations can work on overcoming patient matching issues by ensuring they have an established method within their organization for identifying patients and a current EHR system. Additionally, a federal set of standards can also benefit the industry. Finally, working toward healthcare interoperability can also push organizations into establishing a stronger patient identification process.

Patient matching and healthcare interoperability

Healthcare organizations across the nation are working toward improved interoperability, and a stronger patient matching process could also be greatly beneficial in achieving that goal.

A strong set of federal standards or requirements for how healthcare organizations must gather and share demographics would definitely help in the interoperability process, Colorado Regional Health Information Organization (CORHIO) CEO Morgan Honea previously told EHRIntelligence.com.

“In Colorado we’ve got a really strong infrastructure and a foundation built in the [All Payer Claims Database] and the health information exchanges, and the healthcare delivery system in general,” he explained.

“We have one of the highest rates of EHR adoption through the meaningful use program. Generally, there’s just this really strong foundation of digital health built here,” Honea added. “That’s not necessarily the case everywhere, but it really depends on where you are on the spectrum of interoperability and where you go next in terms of what your needs are in this realm.”

READ MORE: 4 Key Areas to Watch in Healthcare Interoperability

CORHIO recently opted to integrate Verato technology into its enterprise master patient index (EMPI) technology. Honea said the HIE wanted to incorporate more types of health data into the CORHIO network.

“Verato’s MPI was incredibly appealing to us because we are right now working very closely with the state and other partners to go beyond traditional health information exchange and start to work on a more social determinant longitudinal record,” Honea said. “It will include folks with housing insecurities, food insecurities, and transportation challenges.”

Finding ways to include benefit management systems and eligibility information can also help CORHIO grow its “concentric circles out of folks who are working with common patients,” he explained. Some of those organizations may not be using traditional systems that are typically seen in healthcare EMRs.

The new patient matching option will allow CORHIO to match patients when it may not have been able to have certain essential data elements for demographics coming out of an EHR.

“In the traditional sense of health information exchange, patient safety and privacy are the two primary drivers for the need to match patients effectively,” Honea stated. “You certainly don’t want to be treated for someone else’s record and you certainly don’t want your record being viewed as someone else’s.”

Establish standard practices within the organization

READ MORE: Focusing on Patient Care to Fuel Healthcare Interoperability

Another area that could impact patient matching strategies is healthcare organizations ensuring that there is a standardized approach within their daily operations.

A lack of data standardization, specifically within the Master Patient Index (MPI) record process can lead to discrepancies in duplicate medical records, according to a 2018 study published in AHIMA’s Perspectives in Health Information Management.

The researchers interviewed five HIM professionals at Primary Care Clinic of North Texas, finding five top challenges facing those types of employees.

Overlaid records and inconsistent methods for collecting changing patient demographic data hindered their organizational workflow, the HIM professionals said.

Data standardization, patient provided information, multiple demographic data points, key identifying fields, and MPI challenges that hinder organizational workflow were all key challenges.

“Clinical managers need to work together to reengineer and standardize the MPI record process by developing an extensive, organization-wide MPI record cleaning project, focusing especially on areas in which duplicate patient record discrepancies are often due to a blank entry or a default entry in one of the key identifying fields,” Parker University Health Information Management Program Director Joe Lintz, MS, RHIA explained.

Organizations can work on overcoming these issues by focusing on better collection of data on errors, Lintz said. Additionally, standardizing the approaches to patient identification across all points of registration in the healthcare system will help create a holistic plan to address challenges.

“The results of the study provided the organization leaders a foundational framework to develop a comprehensive strategic plan of action to address the challenges proactively,” Lintz wrote.

Having a national strategy on patient matching strategies

A national patient identifier (NPI) has previously been suggested as a way to solve certain patient matching issues. However, the process has been filled with its own obstacles.

The College of Healthcare Information Management Executives (CHIME) suspended its National Patient ID Challenge Initiative toward the end of 2017, following approximately two years of work.

The $1 million competition was first announced in January 2016, urging health IT innovators to develop a solution for ensuring 100 percent accuracy in patient EHR matching.

“Though we’ve made great progress and moved the industry forward in many ways through the Challenge, we ultimately did not achieve the results we sought to this complex problem,” CHIME stated when it announced the end of the initiative. “We have consequently decided the best course for addressing this patient safety hazard is to redirect our attention and resources to another strategy.”

In December 2017 though, ONC partnered with the Capability Maturity Model Integration (CMMI) Institute to create the Patient Demographic Data Quality (PDDQ) framework. Open to the public, the framework aims to help healthcare organizations reduce patient matching errors.

Duplicative testing will also be reduced with the framework, as well as incorrect treatments or diagnoses, and billing errors. 

“The ONC Community of Practice analyzed available frameworks and selected the CMMI Institute’s Data Management Maturity (DMM) model as the baseline for developing the PDDQ framework of best practices,” said ONC Director of State and Interoperability Policy Lee Stevens. “The DMM’s fact-based approach and built-in path for capability growth is aligned with the healthcare industry’s need for a comprehensive standard.”

Thirty-three healthcare stakeholder groups wrote to Congress in May 2018, stressing the need for clarification on the unique patient identifier to better enable patient matching. Specifically, the House and Senate FY19 Labor, Health and Human Services, and Education and Related Agencies (Labor-HHS) Appropriations Bills must include language that will end patient safety issues that arise from patient matching.

“Accurately identifying patients and matching them to their data is essential to coordination of care and is a requirement for health system transformation and the continuation of our substantial progress towards nationwide interoperability, a goal of the landmark 21st Century Cures Act,” the letter read.

There are multiple barriers preventing a smooth patient matching process, but a national strategy could help organizations of all sizes approach the issues together and ensure patients receive proper care.



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