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How EHR Data Integration, Integrity Hold Back Effective EHR Use

Improving EHR data integration and integrity can optimize patient health outcomes and save healthcare organizations money.

EHR Data Integration is imperative for effective EHR use.

Source: Thinkstock

By Kate Monica

- Regulatory pressures have motivated nearly all healthcare organizations across care settings to engage in EHR use. However, problems with EHR data integration and data integrity still bar some hospitals and health systems from getting the most value out of clinical EHR use for the benefit of improved patient health outcomes and organization savings.

Integrating different types of data into EHR systems and health data exchange can help healthcare organizations get more out of their EHR systems, while firm health data governance policies can improve EHR data integrity.

EHR Data Integration

Integrating a wide variety of data types into EHRs can offer providers a more comprehensive view of patient health for better-informed clinical decision-making. 

Most systems currently offer providers access to patient demographic information, medical histories, allergy and medication lists, lab test results, and other kinds of information through patient EHRs. However, social determinants of health data are still largely absent from clinical data.  

The Centers for Disease Control and Prevention (CDC) define social determinants of health as the conditions of the places where people live, learn, work, and play that affect an individual’s level of health risks. Unstable housing, low income, unsafe neighborhoods, and substandard education can exacerbate many health risks and negatively affect outcomes.

READ MORE: EHR Use, Administrative Burden Accelerating Physician Burnout

Past evidence has shown the value of integrating social determinants of health data into patient EHRs. One 2017 study in the Journal of the American Board of Family Medicine (JABFM) found standardizing social determinants of health data collection and presentation in EHR systems can improve patient and population health outcomes in community health centers.

Researchers working with Oregon Community Health Information Network (OCHIN) developed ways to optimize social determinants of health data collection, present the data in EHR systems, and integrate the data into physician workflows.

Ultimately, researchers found documenting a patient’s social determinants of health data in EHRs may allow care teams to leverage the information for more comprehensive, accurate patient care delivery and care coordination.

“Systematically documenting patients' SDH data in EHRs could help care teams incorporate this information into patient care, for example, by facilitating referrals to community resources to address identified needs,” they wrote. “This could be especially useful in ‘safety net’ community health centers, whose patients have higher health risks than the general US population.”

While researchers have found evidence to support the theoretical value of social determinants of health data integration, few healthcare organizations have realized the benefits of utilizing this kind of information in patient EHRs.

READ MORE: EHR Use-Related Malpractice Claims Increased Over Past Decade

A joint pilot project by Methodist Healthcare Ministries of South Texas and the state’s health information exchange (HIE) — HASA — will soon put research into practice by linking social determinants of health data to EHRs.

Methodist Healthcare Ministries awarded HASA a $175,000 grant to expand its services to include social determinants of health data. HASA will integrate this data into its clinical data repository through a cloud-based app.

The program will give physicians a more holistic view of patient health that includes clinical, social, and behavioral risks. With the addition of social determinants of health data, care teams will have the necessary information to connect patients with community services capable of reducing the need for emergency visits.

If successful, the program could reduce the cost of emergency services for the community and improve health outcomes for patient populations particularly affected by social or behavioral conditions that augment certain health risks.  

Integrating a wider variety of data types in health data exchange could also help to improve patient health outcomes.

EHR Data Integration in Health Data Exchange

READ MORE: EHR Use, CPOE System Use Common at Majority of US Hospitals

Health data exchange and interoperability have improved in recent years as a result of health IT innovation and stakeholder collaboration. However, a lack of image data integration as a result of limited information exchange prevents imaging from having a more significant effect on efficient clinical decision-making.

A recent American Journal of Managed Care (AJMC) study showed diagnostic EHR data sharing between different health systems was associated with higher patient mortality scores for patients with heart failure. Meanwhile, data sharing between providers within the same health system was associated with lower patient mortality rates and improved health outcomes.

Researchers reasoned data sharing between different health systems may be ineffective in part because few healthcare organizations have integrated image data into patient EHRs or exchange. For example, exchange of radiology reports may be limited by a lack of radiology images in patient health records.

“This may partially account for the differential between sharing with providers within and outside of systems because physicians within the system may be able to access the source images through other means when necessary,” wrote researchers. “Hospitals that solve the communication challenges associated with EHR data may be able to significantly reduce patient readmissions and mortality.”

Improving image data integration in EHRs and health data exchange may improve diagnostic data sharing between health systems. With more complete EHR data, providers can deliver more accurate care to lower mortality rates and improve patient health outcomes.

Healthcare organizations can further improve care accuracy by optimizing health data integrity.

EHR Data Integrity

While EHR data integration can increase the amount of information available to providers, ensuring a high level of data integrity is necessary to enabling effective patient care.

According to AHIMA, “data integrity means that data should be complete, accurate, consistent, and up-to-date.”

Integrating inaccurate or outdated data in EHRs provides little value to providers. One recent AJMC study found EHR problem lists are particularly lacking in data integrity and are not accurate enough for risk adjustment.

EHR problem lists comprise patient diagnoses entered into EHR systems by clinicians during patient visits. Outpatient health records often rely on EHR problem lists to identify conditions. However, these lists are not updated on a consistent basis. Researchers noted EHR problem lists are only occasionally updated by administrative or clinical staff.

Furthermore, these lists are largely inaccurate.

“Future diagnoses are also collected cumulatively without expiration dates for time-limited or rule-out diagnoses, and some problem lists are truncated to the most current issues, which can unintentionally omit major chronic diagnoses,” wrote researchers.

As a result of the poor data integrity of EHR problem lists, EHR problem list-based comorbidity assessments had poor sensitivity for identifying major comorbidities.

“Despite interest in capitalizing on readily available problem list data in the EHR for purposes of risk adjustment, our findings suggest that these data should be validated prior to application to performance assessment,” wrote researchers. “The sensitivity of the VA problem list for identifying common major comorbidities was poor, ranging from 1 percent to 46 percent, compared with manual free-text note abstraction.”

The inaccuracy of EHR problem lists in identifying major comorbidities for risk adjustment could have negative financial consequences for physicians as the healthcare industry transitions to value-based care. Physicians and physician groups in accountable care organizations (ACOs) must report certain quality measures to CMS to earn incentive payments.

“Absent a valid method of adjustment for comorbidity, it is not possible to confidently distinguish between physicians or groups who provide poor care and those who disproportionately see patients with greater disease burden,” stated researchers.

“Because measures of quality of care are now being tied to compensation in programs like value-based purchasing, the stakes are higher and the consequences of errors in performance assessment are much more substantial,” they added.

In order to effectively utilize EHR problem lists for risk adjustment, healthcare organizations would need to improve their health data governance policies.

Improving health data governance strategies can boost data integrity and improve the quality and accuracy of EHR data for a variety of uses. With strong health data integrity and diverse EHR data integration, healthcare organizations can equip providers with more complete patient information for optimal care delivery. 

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