Improving Patient Matching: Using Healthcare IT and Data Strategy to Create a Single Patient View
Patient matching is one of the biggest challenges facing healthcare today and is critical to effective health information exchange (HIE) and population health. The challenge starts with getting it right within a healthcare organization first. This four part blog series explores effective and enduring approaches to patient matching that providers can take internally to ensure their short and long term clinical success, financial stability, and, ultimately, their survival.
In this blog, "Part 1: Risks and History," I will discuss the risks of patient matching inaccuracies and the history behind it which will shed light on our path for a solution.
What are the Risks?
The risks of patching matching inaccuracies are both clinical and financial. The clinical impact is manifested as inadequate, ineffective or inappropriate care and results in readmissions, privacy violations and low quality short and long term wellness. Financially, patient matching failures result in billing errors that delay payments and increase customer frustration and dissatisfaction, and regulatory and compliance failures that can result in fines or reduced reimbursement funds.
A November 15, 2013 report by Kaiser Health News in collaboration with NPR reported that "Medicare penalizes nearly 1,500 hospitals for poor quality scores.” The article noted “Medicare has raised payment rates to 1,231 hospitals based on two-dozen quality measurements, including surveys of patient satisfaction and—for the first time—death rates. Another 1,451 hospitals are being paid less for each Medicare patient they treat.”
Patient matching is a complex process and the complexity grows the more patients utilize healthcare—an inevitability. As patients move through their pathways of care, their journey will ultimately take them beyond their first provider and that is where the patient matching challenge begins. Moving from that first provider to the second, the third and so on increases the complexity of matching patients and their records across healthcare organizations and increases the potentiality of associated clinical and financial costs (figure 1). Understanding where it all started and the current state of patient data within a single healthcare organization will shed light on effective solutions.
How did we get here?
Today’s patient matching dilemma began in 1999 as a result of federal appropriations legislation. That statute was a by-product of the Health Insurance Portability and Accountability Act (HIPAA) and Congress’ response to public outcry for privacy protection. It effectively denies funding for Health and Human Services (HHS) to create a “unique health identifier for an individual (except in an individual's capacity as an employer or a health care provider).” The result: while HIPAA facilitates the sharing of patient information between healthcare providers, the 1999 legislation handcuffs how providers match that information since they cannot use patient-specific unique identification information—something like a national patient id number.
Since patient data cannot be cross referenced or synchronized across organizations using a unique identifier, providers must resort to alternative methods. These include the use of technology and complex algorithms. Two standards include deterministic matching, sometimes referred to as exact match logic, and probabilistic matching which is a process that ascertains the probability that records match through the use of statistical analysis. Unfortunately, both approaches are not 100% accurate and that is a significant problem.
In an effort to help improve patient matching across healthcare organizations The Office of National Coordinator for Health Information Technology (ONC) announced on September 11, 2013 by Lee Stevens, Policy Director, State HIE Program, the launch of a “Patient Matching Initiative.”
"As part of our ongoing effort to improve patient matching across disparate systems, we are beginning a collaborative project to help identify the common denominators and best practices being used by private sector health care delivery systems and Federal agencies. By identifying and recommending standardization of the basic attributes most commonly used for patient matching, we are looking to improve patient safety, care coordination and efficiency."
We must be aware that these patient identity challenges are applicable to HIE between organizations due to privacy concerns and are not applicable to patient data management within the healthcare organization. There are no restrictions on providers creating their own unique identifier for use internally in their own organization.
This brings us to the next installment in this blog series where I will discuss the current state of patient data management in healthcare organizations and why it contributes to patient matching complexity. The blog will also introduce approaches to overcome patient identity and data management challenges within healthcare organizations to facilitate better HIE and population health.
Kaiser Health News in collaboration with NPR
- Medicare Penalizes Nearly 1,500 Hospitals For Poor Quality Scores, http://www.npr.org/blogs/health/2013/11/15/245254951/medicare-penalizes-...
- Nearly 1,500 Hospitals Penalized Under Medicare Program Rating Quality, http://www.kaiserhealthnews.org/stories/2013/november/14/value-based-pur...
- Interactive Chart: Bonuses And Penalties For U.S. Hospitals, http://www.kaiserhealthnews.org/Stories/2013/November/14/value-based-pur...
10 Section 516, Title V, Omnibus Consolidated and Emergency Supplemental Appropriations for FY 1999, H.R. 4328 (P.L. 105-277), October 21, 1998. http://www.gpo.gov/fdsys/pkg/PLAW-105publ277/html/PLAW-105publ277.htm
"Sec. 516. None of the funds made available in this Act may be used to promulgate or adopt any final standard under section 1173(b) of the Social Security Act (42 U.S.C. 1320d-2(b)) providing for, or providing for the assignment of, a unique health identifier for an individual (except in an individual's capacity as an employer or a health care provider), until legislation is enacted specifically approving the standard."
ONC Launches Patient Matching Initiative, September 11, 2013, Lee Stevens, Policy Director, State HIE Program, http://www.healthit.gov/buzz-blog/health-innovation/onc-launches-patient-matching-initiative/