Duplicate Patient EHR's Costs Hospitals $1950 per Inpatient Stay

April 10, 2018 - Duplicate patient EHRs cost hospitals an average of $1,950 per patient per inpatient stay, according to a 2018 Black Book survey about the use and value of enterprise master patient index (EMPI) solutions.

Black Book researchers surveyed 1,392 health IT managers about patient identification processes from the third quarter (Q3) of 2017 to the first quarter (Q1) of 2018. Problems were found surrounding patient EHR matching and that it has a significant effect on hospital spending and patient safety.

Respondents included hospital executives, clinicians, IT specialists, and health IT implementation project participants.

For the full article:

https://ehrintelligence.com/news/duplicate-patient-ehrs-cost-hospitals-1950-per-inpatient-stay

Forbes:

The Best Solutions to Health Care's $6 billion Patient Matching Problem

Faster, more accurate record matching through machine learning

Machine learning is the study of computer algorithms that automatically improve with experience. Using machine learning, a computer program can discover rules from data and can refine those rules as more data becomes available. In most cases, computers can discern these rules far better and faster than humans.

For the full article:

https://www.forbes.com/sites/forbestechcouncil/2018/12/04/the-best-solutions-to-health-cares-6-billion-patient-matching-problem/#290b1e729695

PEW Research Center:

Enhanced Patient Matching Is Critical to Achieving Full Promise of Digitial Health Records

Patient matching helps address interoperability by determining whether records—both those held within a single facility and those in different health care organizations—correctly refer to a specific individual. Unfortunately, patient matching rates vary widely, with health care facilities failing to link records for the same patient as often as half the time. Deficiencies in matching patients to their records can lead to safety problems: For example, if an allergy listed in one record is not documented in another, or if records for two different individuals are incorrectly merged, patient harm can occur. In a 2012 survey conducted by the College of Healthcare Information Management Executives (CHIME), 1 in 5 hospital chief information officers indicated that patients had been harmed in the previous year due to mismatches.

Failures to effectively match patients can also be costly, leading to repeat tests and delays in care. In an extreme example, the care for an 11-month-old twin was documented in her sister’s record, resulting in the failure of the health system to recoup $43,000 in costs from the insurer.

Inadequate patient matching has generated interest among federal policymakers. The 21st Century Cures Act— signed into law in 2016—requires the Government Accountability Office to examine steps taken by the federal government and the private sector to reduce matching errors. In the same law, Congress also required the Office of the National Coordinator for Health Information Technology (ONC, the federal agency that oversees EHRs) to develop a policy to support the exchange of information on a nationwide scale. In implementing the policy, known as the Trusted Exchange Framework and Common Agreement (TEFCA), ONC has proposed creating a series of health information networks and an independent organization to govern them. Success of the effort relies on adequate patient matching.

For the full article:

https://www.pewtrusts.org/en/research-and-analysis/reports/2018/10/02/enhanced-patient-matching-critical-to-achieving-full-promise-of-digital-health-records

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