By Laurie A. Rinehart-Thompson, JD, RHIA, CHP, FAHIMA

Health information management (HIM) education sets the stage for a variety of career trajectories that provide nearly limitless professional opportunities. As members of educational cohorts, HIM baccalaureate-degree students can confidently surmise that, although all of them will graduate armed with the same degree in HIM, their work settings and roles will be as diverse as the number of students in the cohort.

With the HIM profession’s origins in the hospital, the hospital setting remains restrictively deemed the “traditional” environment. However, there are myriad departments and opportunities within hospitals for which the HIM skill set is well suited. For example, licensure and accreditation, information systems, data analytics, revenue and reimbursement, quality improvement, privacy and compliance, and, of course, HIM. Within these areas, job titles can include licensing and accreditation specialist, systems analyst, project manager, data analytics specialist, revenue and reimbursement analyst, quality data manager, compliance analyst, business system analyst, and EMPI data analyst, among others.

In addition to the many opportunities a hospital or other healthcare provider affords HIM graduates, a unique benefit of this profession—contrasted with direct-care health professions—is the opportunity to immediately pursue career paths in the non-provider realm, such as electronic health record (EHR) software developers; technology-enabled healthcare providers; healthcare benefits technology companies; healthcare technology companies delivering cloud-based software in the areas of financial planning, analytics, and performance; software platforms that deliver artificial intelligence (AI) solutions and communications, workflow, and information management software; consulting companies; government agencies; and law firms. Job titles can include implementation specialist; project manager; sales development and operations specialist; client systems analyst; billing operations associate; application analyst; and data integration consultant.

While HIM programs strive to meet the needs of all students, regardless of where they ultimately work, the ever-present question is: What are the essential skills that new and relatively new HIM professionals deem critical to their success?

To answer these questions, I emailed HIM professionals from New England to California and locations in between and asked them if they would informally answer some open-ended questions in hopes that they would share their professional experiences, as well as the knowledge and skills required for their success. Understanding what these professionals have found they need to be successful—in terms of technical skills and soft/professional skills—is instructive in helping educators build a curriculum that advances their needs. The young professionals that provided feedback all had fewer than four years of post-graduate experience, including those who graduated in the past year.

What emerged from their experiences and collective insights was a snapshot that, while not unexpected, gave greater clarity about the essential elements for success among HIM professionals engaged in the business of healthcare.

Technical Skills and Tools

Technical skills and proficiency with multiple technology-based tools are imperative. There are technical tools that all workforce members should be able familiar with and proficient in using—regardless of the setting they work in. The technical skill set required of HIM professionals working for hospitals and other healthcare providers is not vastly different from that required in other settings. While this is reflected in part by the fact that HIM professionals work in diverse roles within a hospital, it should also cause us to question any assertion that “traditional” HIM careers are less technically rigorous.

Proficiency with spreadsheets, databases, and EHR software frameworks and navigation is crucial for HIM professionals, whether they work in a hospital or other type of setting. Whether they use these tools as end users, support staff, or in a vendor capacity, they should be well versed in implementation and troubleshooting.

Other technical skills include knowledge of commonly used computer terminology; understanding of the basic structure of computers and servers; the ability to ask intuitive questions; data mining, analysis, and presentation; an understanding of the basic language and structure of HL7 messages; and knowing what specific information to look for in interface messages. For HIM professionals involved in clinical information system design: development and implementation, and an understanding of current and new applications and software is integral to the success of clinical operations.

Excel and SQL/SSMS were the most frequently cited technological tools used, followed closely by Tableau, Power BI, Epic, and other EHRs including legacy EHR systems, Outlook, and Microsoft Office Suite (with an emphasis on PowerPoint and Access). Other tools included Zoom and Microsoft Teams, Google Drive, computer assisted coding (CAC) software, Microsoft Visual Studio, Crystal Reports, REDCap, Smartsheet, Compliance360, Service Now, OnBase, Jira, Workday, SaaS, Zendesk, Salesforce, Definitive Healthcare, Outreach io, and customized software developed by and for the individual employers.

What does the future hold, and what technical skills and tools do HIM professionals expect they will eventually need to learn or become more proficient in? This, of course, depends on their roles. However, professionals employed both within the healthcare provider realm and outside of it stated that the ability to write programming language and to work with software such as R, RStudio, Python, and SAS for data analysis is expected to become more prevalent. The ability to perform advanced SQL scripting and a more sophisticated understanding of cloud computing and AI are also important as they continue to consume a larger portion of the healthcare space. Those who are not already using Tableau, Power BI, or other reporting tools expect usage and mastery to become more necessary and, eventually, an employer expectation.

Professional and Soft Skills

Several themes emerged from the feedback I received from HIM professionals from diverse professional experiences. Customer service skills were mentioned frequently. This came up in expected areas such as consulting, but it also was apparent in areas such as hospital information systems, where the definition of “customer” can encompass a variety of stakeholders. Working HIM professionals also emphasized time management and prioritization, stress management, organization, ability to multitask, attention to detail, critical thinking, problem solving, troubleshooting, and the ability to take action following fast-paced conversations.

Communication, while a known important soft skill, is multifaceted. It includes public speaking and strong presentation skills, as well as unstructured and spontaneous speaking during business conversations, projecting confidence, and making sure that one’s voice is heard at the table. It further includes setting agendas and preparing meeting materials that provide clarity to others, and finessing written communications so the end product is both professional and personable.

Less apparent, perhaps, is having difficult but essential conversations, and admitting when one doesn’t know the answer but promises to find it—and the ability to follow through on that promise.

Also stressed were personal characteristics—of which many are hallmarks of emotional intelligence—such as positivity, motivation, curiosity, adaptability, openness to learning new things, understanding others’ work preferences, developing a thick skin so as not to take negative feedback personally, and empathy.

All of the characteristics highlighted are well recognized as necessary in order to work well with others. What was noted, however, was, as remote communication became more prevalent pre-pandemic and has burgeoned out of necessity during the pandemic, soft skills will need to be finessed to meet the expanded remote working environment that will certainly continue to exist post-pandemic.

Understanding the Healthcare System

We must be careful not to underestimate the value to HIM graduates of entering the workforce with a solid understanding of the healthcare system. New graduates are hired from many disciplines and for many reasons, including the aforementioned technical skills and soft skills. However, HIM graduates have an advantage over new graduates with degrees in non-health-related disciplines or generalized health studies who, although hired for their critical thinking skills, come into their positions lacking the important context of a generalized knowledge of the healthcare system as well as more specific industry concepts.

It was reported, by those working for healthcare providers and non-providers alike, that an understanding of certain healthcare topics is more difficult if one hasn’t learned about them in an educational setting. That can include lack of familiarity with health record content, HIM-related vocabulary and health terminology—such as knowing what an ambulatory patient is; the difference between Medicare and Medicaid; and the basic concept and structure of an HL7 message. All can be difficult for those without a focused healthcare/HIM education. Knowledge of these concepts and industry knowledge, in contrast, allow HIM professionals to keep pace with conversations that those without an HIM background cannot.

It’s All About the Data

Data management has always been a central component of the HIM profession. However, the profession has made a profound shift from not only managing data, but also understanding types of healthcare data and utilizing specific data elements in order to make significant contributions to business decision-making. The HIM professionals I heard from concluded that the ability to harness and appropriately use data cannot be overvalued. To be successful, HIM professionals also must understand the vast amount and different types of health data, how quickly they are created and exchanged, their degree of accuracy, and their value.¹

Large databases that enable data aggregation help with decision making, but optimizing these databases through appropriate use and reporting requires skill and training. HIM professionals must have a keen understanding of how data are gathered, structured, categorized, and manipulated, and then must be able convert raw data into meaningful information to identify trends and translate those trends into deliverables for key stakeholders. In other words, what story is that data telling? Or, as one HIM professional aptly stated: “What is the ‘so what?’”

It is only with a sophisticated knowledge about data that their significance can be discerned and, subsequently, insightful decisions can be made. Just as data elements within the primary source—the medical record—are the building blocks for individualized patient care, so too are aggregated data elements the building blocks for important purposes such as improved health outcomes, strategic planning, and successful public health initiatives.

Notes

1. Ishwarappa and J. Anuradha. “A Brief Introduction on BigData 5Vs Characteristics and Hadoop Technology.” Procedia Computer Science. 2015. https://doi.org/10.1016/j.procs.2015.04.188.

Laurie A. Rinehart-Thompson (laurie.rinehart-thompson@osumc.edu) is a professor and the program director of the health information management and systems program at The Ohio State University.

By Lauren Riplinger, JD

The overall cost of healthcare is top of many Americans’ minds these days. According to a March 2021 Gallup poll, 80 percent of respondents worry about the availability and affordability of healthcare a “great deal” or a “fair amount.”¹

Today, most Americans have coverage through their employer or a public program, such as Medicare or Medicaid. However, in 2019, 28.9 million individuals were uninsured. At the same time, healthcare costs have continued to increase. Much of this cost has been passed along to individuals in the form of higher premiums, deductibles, and other forms of cost sharing.

As the cost of care rises, policymakers have increasingly focused on the need for greater transparency in healthcare prices and health plan coverage.

In 2009, the Affordable Care Act introduced the industry’s first requirement for hospitals to make available their list of standard charges for items and services. More recently, under federal rules issues by the Trump administration, the Centers for Medicare and Medicaid Services (CMS) required hospitals to publish the price of 300 health services that can be scheduled in advance. These prices must also be made available in a “machine-readable file” on the hospital’s website. The intention of this rule is to enhance the ability of individuals to make more informed decisions based on costs.

Additionally, policymakers have focused on how technology may be leveraged to help individuals better understand healthcare prices. Both the CMS Patient Access and Interoperability Rule and the ONC Cures Act Final Rule encourage the adoption of application programming interfaces (APIs) and modern technical standards that could support the development of highly customized pricing tools for consumers.

To ensure that the health information (HI) perspective is a part of these discussions, AHIMA’s Board of Directors recently approved a public policy statement on affordability. In approving the statement, the board affirmed its belief that “AHIMA supports the use of public policy to ensure that individuals have all the information they need to make informed choices about their healthcare. This includes both access to their personal health information and actionable information about the cost of their healthcare.”

The public policy statement identifies five key recommendations for policymakers to support the ability of individuals to make informed decisions about their healthcare:

1. Support individuals in accessing both their personal health information and actionable information about the costs of their healthcare.
2. Support the development of accurate, useful, real-time tools to inform individuals of their healthcare costs.
3. Find equitable solutions to prevent “surprise billing” for consumers.
4. Maintain the privacy and security of health information, including when it is shared with third parties.
5. Support education for consumers, regardless of their financial situation, on how to understand their health plan coverage and ask for the information they need to make informed decisions.

In developing this public policy statement, AHIMA brought together a member work group to understand key considerations associated with improving individuals’ access to their personal health information and actionable information about the costs of their care. This included discussions around the key challenges associated with providing individuals with information to support affordability, such as changes in health plan coverage and billing rules and the barriers associated with individuals understanding their out-of-pocket costs.

Policy discussions around affordability are expected to continue in the current Congress and the Biden administration. Initial results related to implementation of the CMS Price Transparency Rule have found that: current price estimates provided by hospitals do not always allow for accurate comparison, price estimates change over a short period of time, pricing information provided in machine-readable files is not complete, and at times, pricing information is hard to access or comprehend.²  At the end of last year as part of the Omnibus Appropriations and Emergency Coronavirus Relief Act, Congress also included The No Surprises Act, which seeks to protect consumers from surprise billing in certain circumstances. Regulatory work will need to be done to implement these provisions. As these debates continue in Congress and within the federal agencies, AHIMA stands ready to lend its perspective and expertise to the conversation.

Work Group members

• Terri Eichelmann, MBA, RHIA, Director, Enterprise Coding and HIM Technology Support, BJC HealthCare (Board member)
• Judy Kelly, RHIA, CPHI, CHDA, CCS-P, CCS, Senior Director, Health Information Management, Rochester Regional Health
• Lou Ann Schraffenberger, MBA, RHIA, CCS, CCS-P, CPC, FAHIMA, Former Manager of Clinical Data, Advocate Health Care
• Charniece Martin, MBA, RHIA, CCS, CCS-P, Healthcare Coding Analyst, American Medical Association
• Jennifer Goins, MHA, RHIA, Managing Consultant, BKD Health Care Performance Advisory Services
• Anny Yuen, RHIA, CDIP, CCS, CCDS, Consultant/Principal, AP Consulting Associates, LLC
• Laura Pait, RHIA, CDIP, CCS, Director, Strategic Realization and Implementation, Enjoin
• Mary Stanfill, MBI, RHIA, CCS, CCS-P, FAHIMA, Vice President Consulting Services, United Audit Systems, Inc.

Notes

1. Gallup. “In Depth: Topics A to Z, Healthcare System.” https://news.gallup.com/poll/4708/Healthcare-System.aspx.
2. Kurani, Nisha, Giorlando Ramirez, Julie Hudman, Cynthia Cox and Rabah Kamal. “Early results from federal price transparency rule show difficultly in estimating the cost of care.” Peterson-KFF Health System Tracker. April 9, 2021. https://bit.ly/3293PJO.

Lauren Riplinger (lauren.riplinger@ahima.org) is vice president of policy and government affairs at AHIMA.

By Ellen S. Karl, MBA, RHIA, CHDA, FAHIMA

In today’s healthcare arena, the requirements for educated professionals have increased dramatically. However, the field of health information management (HIM) has not kept pace. In my current role as an educator, I attempted to promote my adjunct faculty, but I found it difficult to do so because the HIM terminal degree remains at a baccalaureate-degree level.

In many other fields, both within healthcare and external to HIM, the doctorate is considered to be the terminal degree. Many moons ago when I launched my career in HIM, my colleagues in the physical therapy and pharmacy fields were also baccalaureate-prepared. We were all equals—all department directors in a given hospital. But professionals in these fields (and their associations or state departments of health) wanted more. Pretty soon, doctorate degrees were required for pharmacists and physical therapists who are required to have a PharmD and a DPT, respectively. In HIM, however, the push to earn advanced degrees stagnated at the bachelor’s-degree level.

Personally, the decision to continue my own education beyond a bachelor’s degree was to bolster my opportunities. Senior-level HIM positions in the large, urban, multi-hospital systems usually require master’s-prepared HIM professionals to fulfill their leadership teams. When I transitioned to academia after working in acute care for 25 years, a new white paper, “Vision 2016: A Blueprint for Quality Education in Health Information Management,” had been written by a committee of educators (the AHIMA Education Strategies Committee) on the importance of HIM members moving their education to the next level. That was in 2007. In 2016, “Vision 2016” morphed into “Reality 2016,” and here we still are with the terminal degree being the bachelor’s degree.

I do believe that today there are a larger number of masters- and doctorate-prepared HIM professionals than when these papers were written. Some of this has to do with educational offerings. Do we have enough universities offering a master’s in HIM so that we can elevate the terminal degree to the master’s? Not yet. There are only a few CAHIIM-accredited master’s degree programs, with several in the pipeline. For me at the time, I sought out an MBA with a concentration in health administration since there weren’t any HIM master’s programs when I was looking for one. In order to elevate the profession, we need the expectation to be that the master’s in HIM is the terminal degree. But until we have enough people with that degree and enough colleges offering the degree, we cannot move the ball forward.

There is an imperative in today’s healthcare world for the skills necessary for higher-level positions in HIM. In my HIM program at City University of New York (CUNY), we have a full course for students in database management and project management. Sometimes students ask, “Why do we need these courses?” If HIM professionals are to remain relevant in this healthcare environment, we need to evolve, adapt, and change. You don’t need to be a database manager or a full-time project manager, but you need to know these skills so that your expertise can be relied upon. Picking up specialty credentials can also help your career trajectory, such as the Certified Health Data Analyst (CHDA) or Certified in Healthcare Privacy and Security (CHPS) credentials.

In my younger professional days, I was asked to create my capital budget for the HIM department. I decided to put anything and everything that I thought I needed into that budget. There was something new and innovative called an optical disc player that could store copies of medical record documents. I had a hard time procuring prices to include in my budget, but I did include it. It did not get funded, but I was trying hard to be forward thinking and pushing myself and the organization to look down that future road.

Have you looked down the road at your own career? Have you pushed yourself to the next academic level? Education is a key marker to help you get to where you want to go. You just need to get started. Today.

Ellen S. Karl (ellen.karl@cuny.edu) is the academic director for health information management and health services administration programs at CUNY School of Professional Studies.

Social determinants of health (SDOH) are the socioeconomic factors that impact a person’s health. Examples include food insufficiency, limited access to healthcare, social isolation, and unemployment. SDOH have been shown to have a far greater impact on a patient’s health outcomes than either the clinical care provided or genetic factors.¹ Healthcare providers and payers are directing significant attention towards SDOH to improve healthcare quality and reduce costs. HIM professionals need to ensure that SDOH information is being captured to support these initiatives, including improving ICD-10-CM coding for SDOH.

Increased Focus on Social Determinants of Health

An increase in value-based purchasing and at-risk payment models has contributed to a greater interested in improving the health of populations being managed.² Healthcare providers and payers recognize that significant improvements in healthcare cannot be achieved until SDOH are addressed. Many key stakeholders in the healthcare industry have signaled the need to collect, measure, and analyze SDOH.

CMS has developed the following strategies to account for social risks in Medicare’s value-based purchasing program:³

• To measure and report quality for beneficiaries with social risk factors
• Set high, fair quality standards for all beneficiaries
• Reward and support better outcomes for beneficiaries with social risk factors

The Core Quality Measures Collaborative, which is housed at the National Quality Forum, has identified disparities of SDOH as a priority area for quality measure development.⁴ Healthy People 2030, a data-driven set of national objectives to improve the health and well-being of Americans over the next decade, has a strong focus on SDOH.⁵ The Office of the National Coordinator for Health IT (ONC) has included support of federal-directed plans that address SDOH in its strategic plan.⁶ SDOH concepts are also increasingly being used in risk adjustment models to better assess patient outcomes.

Current State of SDOH Documentation and ICD-10-CM Coding

The increased interest in SDOH has led to an expansion in documentation and ICD-10-CM code assignment of SDOH issues. However, SDOH are still not routinely or systematically collected. One study found that only 24 percent of hospitals and 16 percent of physician practices screen for common SDOH. A 2017 survey of hospitals found that while 88 percent of hospitals do screen patients for SDOH, only 62 percent reported systematic or consistent screening of their patient population. Larger healthcare organizations and providers that treat disadvantaged patient populations reported higher screening rates for SDOH. Additionally, standardized terminology is not always used when documenting SDOH.^7,8

An analysis of the CMS Chronic Condition Data Warehouse indicates that the five most reported ICD-10-CM SDOH-related Z codes are:⁹

• Z59.0, Homelessness
• Z60.2, Problems related to living alone
• Z63.0, Problems in relationship with spouse or partner
• Z63.4, Disappearance and death of family member
• Z65.8, Other specified problems related to psychosocial circumstances

Updates to the ICD-10-CM Official Coding Guideline I.B.14, Documentation by Clinicians Other Than the Patient’s Provider, has made assigning SDOH-related Z codes easier. These updates allow for the use of health record documentation from clinicians involved in the care of the patient who are not the patient’s provider since the information represents social information rather than medical diagnoses. Additionally, patient self-reported documentation may be used to assign SDOH-related codes as long as the patient information is signed-off by and incorporated into the health record by either a clinician or provider. The AHA 4^th Quarter 2019 issue of Coding Clinic further clarified that the ICD-10-CM official coding guidelines do not provide a definition for the term “clinicians.” However, for SDOH-related coding, documentation that meets requirements for inclusion in a facility’s health record based on regulatory or accreditation requirements or internal hospital policies may be used.

Current ICD-10-CM codes for SDOH are not sufficient to capture the wide range of SDOH domains and in some circumstances existing codes are not specific enough to reflect different aspects/severity of a domain. For example, there is no code to adequately report transportation difficulties. Furthermore, code Z59.4, Lack of adequate food and safe drinking water, is too broad and is used to capture multiple SDOH concepts. The Gravity Project, an initiative which convenes stakeholders in a collaborative process to develop consensus-based standards to facilitate SDOH data capture and exchange, is addressing these gaps in the ICD-10-CM classification system. The Gravity project will be submitting a request for new codes to the ICD-10-CM Coordination and Maintenance Committee to allow for better capture of various SDOH domains.¹⁰

Internal Coding Guidelines

ICD-10-CM code assignment for SDOH is increasing. Many healthcare facilities are developing internal guidelines to facilitate coding and to support organizational efforts to address SDOH. Examples of internal guidelines include:

• In accordance with the AHA 4^th Quarter 2019 issue of Coding Clinic, identifying the categories of clinicians, such as, community health workers, social workers and case managers whose health record documentation may be used for SDOH code assignment.
• Identifying documentation that would justify the assignment of an SDOH-related ICD-10-CM code. For example, documentation of “Tent City” resident or “Lives in vehicle” would justify the reporting of code Z59.0, Homelessness. Code Z56.6, Other physical and mental strain related to work, is to be assigned for documentation of patient being furloughed, underemployed, or reporting reduced work hours.
• Reporting SDOH-related codes on readmission records to support the healthcare organization’s readmission reduction program.
• Requiring the reporting of SDOH-related codes on all well child visits to meet a state Medicaid requirement that this information be included on the claim.
• Requiring that SDOH-related ICD-10-CM codes be reported in the top 25 diagnosis fields to ensure that the information is included on claims submitted to payers.

Steps to Improve ICD-10-CM Code Assignment for SDOH at Your Facility

Efforts to improve coding for SDOH must start with an assessment of the organization’s SDOH-information needs and the current state of SDOH documentation. Ideally, a multi-disciplinary team comprised of healthcare providers, (including population health specialists, clinicians representing the staff that document the non-medical SDOH information), coding and CDI professionals and information technology staff responsible for EHR development should be convened. Given the resources available that can be dedicated to improve the coding for SDOH, organizations may opt to start with a pilot focusing on a single SDOH domain such as food insecurity or homelessness.

Some concrete steps that HIM professionals can take to improve the ICD-10-CM coding of SDOH include:

• Generate reports to determine which SDOH codes are being assigned. Review a sampling of records to assess the types of cases and documentation for which the codes were assigned.
• Meet with clinicians that document SDOH concepts to determine the best health record sources to capture this information.
• Develop internal coding guidelines to identify the categories of clinicians (e.g. community health worker, case manager) from whom documentation can be used for code assignment and the likely location of this information in the health record.
• Ensure that CDI and coding staff have access to and are aware of all the locations in the EHR where SDOH information may be documented.
• Educate CDI and coding staff on the importance of SDOH code assignment.
• Educate providers and clinicians on the importance of consistently documenting SDOH information.
• Work with staff responsible for computer assisted coding products to create logic for the review of SDOH documentation and generation of suggested ICD-10-CM codes.
• Monitor for improvement (increased reporting) of SDOH code assignment by patient type, diagnosis, provider and SDOH domain.
• Conduct audits on the quality of SDOH documentation and ICD-10-CM coding accuracy. Provide feedback, as needed. For example, if needed, request EHR templates be developed to support more complete capture of SDOH information.

As providers, health systems, and payers continue to address SDOH, the ability to analyze patient outcomes and assess the effectiveness of various initiatives will be essential. HIM professionals must act now to be able to support these goals to improve health outcomes and reduce costs.

Notes

1. Schroeder, Steven A. “We Can Do Better — Improving the Health of the American People .” New England Journal of Medicine 1221-1228: 2007.
2. Deloitte Center for Health Solutions. “Social Determinants of Health: How Are Hospitals and Health Systems Investing in and Addressing Social Needs?” 2017. https://www2.deloitte.com/content/dam/Deloitte/us/Documents/life-sciences-health-care/us-lshc-addressing-social-determinants-of-health.pdf.
3. US Department of Health & Human Services’ Office of the Assistant Secretary for Planning and Evaluation. “Social Risk Factors and Performance in Medicare’s Value-Based Purchasing Program.” 2020. https://aspe.hhs.gov/system/files/pdf/263676/Second-IMPACT-SES-Report-to-Congress.pdf.
4. The Core Quality Measures Collaborative. 2020. “Analysis of Measurement Gap Areas and Measure Alignment.” http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=94324.
5. US Department of Health and Human Services’ Office of Disease Prevention and Health Promotion. Social Determinants of Health. Accessed December 6 2020. https://health.gov/healthypeople/objectives-and-data/social-determinants-health.
6. Office of the National Coordinator for Health IT. “Federal Health IT Strategic Plan 2015-2020.” 2015. https://www.healthit.gov/sites/default/files/9-5-federalhealthitstratplanfinal_0.pdf.
7. Fraze, Taressa K. et al. “Prevalence of Screening for Food Insecurity, Housing Instability, Utility Needs, Transportation Needs, and Interpersonal Violence by US Physician Practices and Hospitals.” Journal of the American Medical Association Network Open 2 (9): 2019. doi:doi:10.1001/jamanetworkopen.2019.11514.
8. US Department of Health and Human Services’ Office of the Assistant Secretary for Planning and Evaluation, ibid.
9. Centers for Medicare and Medicaid Services’ Office of Minority Health. “Z Codes Utilization among Medicare Fee-for-Service (FFS) Beneficiaries in 2017.” 2020. https://www.cms.gov/files/document/cms-omh-january2020-zcode-data-highlightpdf.pdf.
10. The Gravity Project. “Announcements.” November 2020. https://confluence.hl7.org/display/GRAV/The+Gravity+Project#TheGravityProject-Announcements.

Margaret M. Foley is associate professor at Temple University.

The challenge for today’s health information management (HIM) professionals is to think beyond the task at hand, to see the big picture of how their performance and expertise impacts the whole organization.

Information is the currency of today’s healthcare ecosystem. The ability to gather, analyze, distribute, and apply data is essential for optimal patient care and the health of the organization. HIM professionals are data’s most critical gatekeepers, ensuring optimal accuracy, structure, and security.

However, hospitals and health systems have traditionally been siloed and fragmented organizations. Healthcare professionals focus on their sphere of influence to the exclusion of other areas, which often results in inefficiencies or a lack of harmonization among all departments in an organization.

How do the strengths of a clinical professional complement the strengths of an HIM professional or a revenue cycle team member, creating a stronger team than any one of them could create on their own?

Lessons from The Wizard of Oz

The Oz Principal, a book written by Roger Connors, Tom Smith, and Craig Hickman, proposed the idea that each of us is already equipped with what we need to obtain higher results for our organizations.

In the 1939 film The Wizard of Oz, Dorothy and her band of friends take the yellow brick road to the city of the eponymous wizard, who they believe is the answer to all their problems.

Powerless on their own, together our band of heroes brought out the best in themselves and each other, able to take charge of their own actions and destinies.

Taking this a step further and incorporating these ideas into the HIM world, let’s discuss how leaders can bring their employees to a place where they have the capacity to work for change and self-empowerment.

Courage of the Lion: Identify the Problem

Before any positive change can be implemented, one must first identify that there is a problem.

Many HIM employees feel that their job is to complete the few functions they were hired for and not ask questions. However, most of these professionals are often in the position to identify a problem first before the situation snowballs out of control.

Do the HIM professionals in your organization feel that they can approach management with problems and feel like they are being heard? Or have they been made to feel that solving problems is the sole purview of management?

It is important for leaders to help the employee feel a sense of ownership for even the most routine of tasks and to be quick to identify problems. Like the Cowardly Lion from the movie, sometimes employees just need to be reminded to open their eyes and speak up when they see an issue or process that could be improved.

Heart of the Tin Man: Own the Problem

It is one thing for HIM professionals to notice a problem, and another to accept when they have played a part in the situation.

In The Oz Principal, the authors state, “Only by accepting full ownership of all past and present behavior that has contributed to current circumstances can you hope to improve your future situation.”

Often, employees feel they must do all they can to cover mistakes and place any blame elsewhere. Managers should work to help employees feel safe to speak up when an error comes from something they did or did not do.

Wisdom of the Scarecrow: Brainstorm for Solutions

Once the HIM employee has identified an issue, it is important for them to feel that their observations and/or experiences make them a perfect member of the team to search for solutions.

Including front-line employees on special committees and providing a safe place for them to express their concerns or ideas will go far in the search for solutions and in the personal development of the employee. Employees should be allowed to be part of the solution whenever possible. Team building and problem-solving can develop creativity and self-esteem within the employees once they feel they are included, and that they are important to the group’s success.

Ruby Slippers: Advancing Change for the Organization

What many people overlook in the story of Dorothy in The Wizard of Oz is that she could have changed her situation at any time by using the magical ruby slippers she took at the beginning of the film.

Our employees come to us from many work backgrounds and with a multitude of talents and ideas. While ongoing education is always a good thing, managers would do well not to overlook even the most unconventional skills their employees possess. Leadership and problem-solving can come in many forms—not just in formalized HIM education and credentials. Managers can work with their employees to develop those skills for best use within the organization.

The Question Behind the Question

Many organizations operate under the mentality of doing just enough to get by and not take risks. This limited thinking is passed down throughout the organization to the front-line employees.

Wise managers should seek to both receive and provide feedback, and to work hard to free people who have locked themselves in a victim mentality. Quality leaders risk their own comfort and security by searching beyond symptoms to discover the core problems that spring from a lack of employee accountability. It is critical to remember that they must always provide a model for those with whom they work or associate.

In his book Personal Accountability, John G. Miller describes the idea of “the question behind the question” (QBQ): “It takes some effort to push aside the junk questions—those that are focused outwardly—and ask [QBQ]. This is more difficult to ask than the original question because it’s the accountable question, the one that explores what I could have done to prevent the problem or what I can do in the future.”

A QBQ is a way for management to reframe our interactions from victim thinking to higher levels of personal accountability. Effective questions such as “What can I do?” or “How can I contribute?” will lead us to doing what is not natural for most of us—living a life of personal accountability.

Over the Rainbow

The Oz Principal summarizes this difficult topic in this way, “Remember, only when you assume full accountability for your thoughts, feelings, actions, and results can you direct your own destiny; otherwise, someone or something else will.”

HIM management can encourage employees to climb out of the victim cycle to benefit from what we have learned regarding the courage to look for improvements, owning their part in the process, working for change, and using skills they already possess.

References

Connors, R., T. Smith, and C. Hickman. The Oz Principal: Getting Results through Individual and Organization Accountability. Prentice Hall Press: 1994.

Miller, John G. Personal Accountability: Power and Practical Ideas for You and Your Organization. Denver Press: 1988.

Betty Gossell (Betty.Gossell@BSWHealth.org) is a coding auditor and part of the coding education program at Baylor Scott & White. She has 30 years of coding, auditing, and HIM management experience in a variety of settings.

By Jason Brantley, SVP and General Manager

When was the last time you entered your bank to get a monthly statement? In today’s digital world, credit card companies, mortgage lenders, and a variety of other entities conduct most business electronically. Even many brick-and-mortar stores provide a digital receipt. Most consumers love this. They don’t need to worry about misplacing or retrieving paper documents because it’s all just one click away on their mobile device. Why should release of information (ROI) be any different? It isn’t, and in the next couple of years (or sooner), it won’t be.

The question is, will your organization be ready?

While change can be daunting, the good news is that shifting to digital ROI isn’t the big, scary endeavor it might have been in the past. Now, organizations can access cost-effective technology that makes it easy and secure to release protected health information digitally—all while making sure the right information reaches the right requester at the right time.

Meeting patients’ demands

If there’s anything that banking and other industries have taught us, it’s this: In the not-too-distant future, digital ROI won’t be a choice. It will be ‘the default’ option simply because that’s what an overwhelming majority of requesters—particularly patients—will want. Interestingly, two-thirds of patients are likely to switch to a new health system if their expectations are not met, according to a recent Accenture survey. If organizations want to attract, retain, and continually engage patients, digital ROI is one way to do it.

Digital ROI can also be one of many ways organizations can move the needle on patient experience and subsequently boost their bottom line. Research has shown that hospitals with higher patient experience ratings perform better financially. Accenture found that organizations that improve the patient experience could potentially increase their revenue by 5%-10% pre-COVID levels within 12 months.

Being able to request and retrieve information electronically likely plays an important role in patient outcomes as well. For example, when patients can access their information more easily, they may be more likely to follow through with referrals to specialists, take medications as prescribed, and more.

Digital ROI is also critical during the COVID-19 pandemic. Many organizations have already prohibited in-person requests, choosing instead to direct patients to the patient portal. ROI specialists working remotely can oversee, validate, and fulfill these requests. These organizations may opt to continue this process post-COVID simply because it frees up physical space within the organization for other revenue-generating opportunities.

The need for digital ROI may be intensified by a federal push for interoperability and patient access. As information blocking becomes applicable, providers will continue to innovate in increasing access to health data and patients may welcome and adopt these innovations. It’s a natural evolution for which organizations must be prepared.

Getting started with digital ROI

Not sure where to start when it comes to transforming your ROI processes?

The first step may be to simply overcome myths within the organization that could prevent moving forward with more technology-enabled ROI processes. Consider the following three myths and how ROI processes have advanced to overcome them.

Myth #1: Digital ROI requires a big ‘IT lift.’

Not true. Application program interfaces (API), the technology that makes it seamless to push information from one system to another, are commonly offered by reputable ROI vendors. Is your vendor one of them? With a few hours of dedicated IT time, organizations can have a significant positive impact on patient and requester satisfaction by releasing information digitally from multiple EHRs with minimal effort.

Myth #2: Protected health information isn’t secure with digital ROI.

Not true. Today’s sophisticated technology often requires multiple forms of authentication, including a photo ID, a HIPAA-compliant electronic signature, and confirmation of other personal details to authenticate their identity. To access the records, recipients receive a PIN that’s sent in a separate email, ensuring security on the front and backends. In fact, digital ROI can secure protected health information more than paper-based processes.

Myth #3: Organizations compromise quality with digital ROI.

Not true. It all goes back to that long-standing fear that organizations will release too much information, not enough information, or the wrong information when they go digital—that they can’t rely on natural language processing (NLP) and artificial intelligence (AI) to maintain quality and fulfill requests accurately.

Using advanced NLP and AI simply aids the human ROI specialist— it does not replace the role entirely. This is exactly what happened with computer-assisted coding (CAC). CAC enhanced coding and enabled skilled coders to be even more effective. In fact, using NLP and AI enables ROI specialists to quickly validate straightforward requests so they can spend more time focusing on complex requests that require deep patient interaction, phone calls to the requester or other steps to validate. These technologies elevate these individuals so they can add more value in the ROI process.

In conclusion

All organizations should be thinking about digital ROI regardless of whether their process is in-house, outsourced, or a combination of the two. If the process is outsourced, what is your vendor doing to support digital transformation while also maintaining quality? Reputable vendors can deploy technology to maximize efficiency and speed in processing requests in less time with the increased quality, so patients and other requesters receive the records more quickly.

The principles of ROI (i.e., getting the right information to the right person at the right time) don’t change. Digital ROI simply makes it easier for organizations to achieve these objectives.

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Mid-revenue cycle leakage remains difficult for health systems to manage due to competing priorities, a lack of clinical knowledge, and a scarcity of appropriate software solutions. But there are options, and one of the most compelling strategies is to implement a thorough retrospective review process.

This whitepaper will explore:

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There is no question that the COVID-19 pandemic played a catalytic role in the use of telehealth in 2020. A recent survey by Rock Health and Stanford Medicine found an increased use of live video telehealth, with 43 percent of respondents reporting that they had a video visit (compared to 32 percent in 2019).

Much of the increased use of telehealth in the US has been the result of steps taken by the Centers for Medicare and Medicaid Services (CMS) to expand telehealth services for Medicare beneficiaries. At the same time, the US Department of Health and Human Services’ Office for Civil Rights took steps to exercise its enforcement authority and waive penalties against providers from HIPAA violations who in good faith used applications that allow for video chats during the public health emergency.

One year since the start of the pandemic, the question isn’t “will telehealth go away?” but rather “how do we ensure its eventuality?”

Ongoing debate about the future of telehealth is currently happening in the halls of Congress, within federal agencies, and in state legislatures as much of the fate of telehealth in the US is contingent upon policymakers at the state and federal level.

To ensure the health information (HI) perspective is a part of these discussions, AHIMA’s Board of Directors recently approved a public policy statement on telehealth and remote patient monitoring.

By approving this statement, the board affirmed its belief that “AHIMA supports the use of public policy and other tools to expand access to care, reduce costs, and improve convenience for patients by using telehealth and remote patient monitoring technologies and that HI professionals have considerable knowledge and relevant experience to contribute in developing public policy that seeks to expand telehealth while ensuring the continuity of accurate, timely, and trusted health information.”

The public policy statement identifies seven considerations for policymakers to expand the use of telehealth:

1. Promote patient and provider choice. Policy must ensure that patients and providers are not arbitrarily limited by geography or modality when receiving or offering telehealth services. Policy must also ensure that patients have access to telehealth services anywhere, including at home. Additionally, policy must encourage all technologies and/or modes of telehealth, provided the technology is safe, effective, appropriate, secure, interoperable, and can be integrated into a provider’s clinical workflow.
2. Ensure parity between telehealth services and in-person services. Policy must treat remote services no differently than services provided to patients in-person in terms of the scope of services that can be provided. Policy must also ensure that reimbursement of telehealth services is commensurate with the expense of providing such services, including investment in technology related to telehealth services. Additionally, policy must ensure equivalent documentation requirements, coding and billing rules/guidelines, and quality measures are consistently applied across all payers for telehealth services.
3. Invest in telehealth infrastructure, including broadband internet access in rural and underserved communities (in both urban and rural areas) that have limited access to affordable and adequate connectivity, hampering their ability to deploy telehealth solutions.
4. Prioritize privacy and security. Efforts to expand the use of telehealth requires consideration of appropriate privacy and security policies, including consent management and limits on the collection, use and disclosure of health information to that which is minimally necessary to the specific transaction in question. This also includes consideration of identity management and data storage and retention practices. Additionally, policy must consider the implementation of appropriate and consistent security safeguards for telehealth platforms, such as authentication and data encryption.
5. Facilitate the delivery of healthcare services across state lines. Policy barriers that deter patients from seeking treatment across state lines using telehealth services may lead to fragmented or delayed care. Policy must encourage interstate licensure compacts and other licensure portability policies that enable clinicians to deliver care across state lines using telehealth services.
6. Address disparities in the use and willingness to use telehealth and remote patient monitoring technologies. Telehealth offers the potential to improve access to care and address disparities in underserved communities. However, evidence suggests that inequities exist in accessing telehealth services on the basis of age, gender, race/ethnicity, language, geography, and income.^1,2 To avoid increasing disparities, policy must identify and mitigate the underlying reasons why some groups have lower levels of use of telehealth services.
7. Promote program integrity. At the same time that public policy expands access to telehealth, it must also ensure appropriate guardrails and oversight are in place to prevent opportunities for fraud and abuse, including new approaches that monitor and audit unusual billing behaviors related to telehealth.

To develop this statement, AHIMA brought together an AHIMA member work group on telehealth not only to better understand the opportunities and challenges of expanding telehealth but to ensure that the principles were reflective of the operational realities of today.

Federal lawmakers will continue to grapple with questions over the future of telehealth this year. Most recently, the US House Energy and Commerce Committee held a hearing about the future of telehealth—the first of many anticipated hearings about this topic. Congress’ Medicare advisory panel (MedPAC) also recently called for a one- to two- year extension of existing telehealth expansion to gather more evidence about the impact of telehealth on access, quality, and costs to help inform more permanent changes. While the fate of some of these discussions is still unclear, AHIMA and its members will bring their expertise to the table as these debates continue.

Work Group Members

• Brenda K. Beckham, RHIA, executive director of HIM, Baptist Health (board member)
• Lesley Clack, ScD, CPH, assistant professor and MHA program coordinator, health policy and management, University of Georgia
• Penny Crow, MS, RHIA, SHRM-SCP, principal/compliance officer, Brittain-Kalish Group, LLC
• Jennifer Garvin, PhD, MBA, RHIA, CTR, CPHQ, CCS, FAHIMA, division director and associate professor, the Ohio State University College of Medicine
• Faith McNicholas, RHIT, CPC, CPCD, PCS, CDC, manager, coding and reimbursement, advocacy and policy, American Academy of Dermatology
• Jeanne Solberg, MA, RHIA, FAHIMA, health information consultant
• Sarah Throop, CCS-P, coding quality expert, Indiana University Health

Notes

1. Eberly, Lauren A., Sameed Ahmed M. Khatana, Ashwin S. Nathan, et al. “Telemedicine Outpatient Cardiovascular Care During the COVID-19 Pandemic.” Circulation. June 2020. https://www.ahajournals.org/doi/10.1161/CIRCULATIONAHA.120.048185.
2. Eberly, Lauren A., Kallan, Michael J., Julien, Howard M., et al. “Patient Characteristics Associated With Telemedicine Access for Primary and Specialty Ambulatory Care During the COVID-19 Pandemic.” JAMA Network Open. December 29, 2020. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2774488.

Lauren Riplinger (lauren.riplinger@ahima.org) is vice president of policy and government affairs at AHIMA.

[Editor’s Note: This paper was originally published in the Winter 2020 issue of Perspectives in Health Information Management. It is been reproduced in its entirety here, with the authors’ permission.]

Abstract

Northeast Alabama Regional Medical Center (RMC) in Anniston, Alabama purchased a smaller hospital in 2017. Staff at the two hospitals were tasked with merging the two Electronic Medical Record (EMR) systems into one unified system. From the outset, there were two systems with different medical record number specifications and patient identification systems as well as two different patient name parameters. The merging of these records and systems meant dealing with different vendor EMR systems and ancillary systems to produce a single unified record within RMC’s EMR and the document imaging system that housed the legal medical record for each patient.

This case study describes the process and procedures of merging the patient records from both hospitals to create one Enterprise Master Patient Index (EMPI); and the collaboration between the Health Information Management and Information Technology departments to accomplish this goal.  It also reviews the impact and challenges related to the system’s development, as well as lessons learned while completing the project.

Keywords: medical records systems, computerized/organization & administration, patient identification systems/standards, duplicated medical records

Introduction

Healthcare delivery has changed and increased in pace especially in the past three decades to include merging and acquisition of other healthcare organizations.¹ Mergers and acquisitions benefits integration of care, decreases duplication of clinical services, fosters clinical standardization to reduce cost for operating expenses and improves overall quality.^{2, 3} As more hospital systems purchase external clinics, physician practices and hospitals, the goal should be to have all operations using one medical record system to ensure quality of care is consistent among all providers and information is accessible by all entities within the system serving the patient. Patient identification and duplicated medical records are always challenges and are major issues to be resolved when merging medical record systems.

The challenges in hospital mergers and acquisitions involve multiple functions of the facilities, health information technology being one of the most challenging components.⁴ Other impacted areas, such as financial and accounting systems, purchasing and supply systems, pharmacy, radiology, laboratory and human resources systems require active reconciliation.^4,5 Healthcare informatics is the field of information science concerned with the management of all traits of health data and information through the application of computers and computer technologies.  Increased technology, such as advanced Enterprise Master Patient Index (EMPI), algorithms, radio frequency identification and smart cards, are major tools in solving duplicate medical records and patient identification matching issues.^{6, 7} Because of the current culture of mergers in the overall health care system, it is highly likely that a Health Information Management (HIM) Director or Manager, will be required to be responsible for making decisions on how to accomplish a unified medical record and an EMPI.⁶  A strong, collaborative and capable leadership team is the key for a project to be successful in merging and implementation of a new system within healthcare organizations.⁸

This case study describes the collaborative efforts between HIM and Information Technology (IT) as a very specialized team, their accomplishment of creating an Enterprise Medical Record System, the processes of the system’s development and steps involved in the merging process. It also reviews the impact and challenges related to the system’s development. Lastly, several lessons learned and recommendations for merging medical record systems and the alliance of HIM and IT collaboration works are discussed.

Methods

Project Scope

The purchasing hospital, Northeast Alabama Regional Medical Center (RMC)⁹ serves a five-county area as the region’s leading healthcare provider in northeast Alabama. The hospital that was purchased (Purchased Hospital) is in the same city as RMC. Statistically about 90% of the local physicians are on staff at both hospitals. The purchase was intended to align the delivery of healthcare in the region and reduce waste and duplication of limited healthcare resources.

As part of the acquisition, RMC was required to disconnect the Purchased Hospital from its legacy Electronic Medical Record (EMR) within 14 months of the purchase date. Dozens of systems had to be migrated in the 14-month timeframe, with the largest and most complex of these being the EMR and storage system for the legal medical record. RMC’s EMR is Allscripts Paragon, a single integrated system that allows both physicians and clinical staff to document, order and review patient information. The EMR transfers the data into OneContent, a Hyland Product, which is the document imaging storage system where the legal medical record is located. The Purchased Hospital’s EMR was a group of systems proprietary to the previous owner that provided the EMR functions for physicians and nurses. The Purchased Hospital used McKesson’s Horizon Patient Folder (HPF), an earlier software version of OneContent, for the document imaging storage system. RMC’s challenge was to convert and implement Paragon (and other key systems) at the Purchased Hospital for all EMR activities such as clinical functions, billing, General Ledger (GL)/Accounts Payable (AP), charge master and materials management.

RMC had decreased the clinical paper documentation to 30% since implementation in 2013 and only uses paper documentation in some outpatient areas. One goal would be to standardize the documents and continue decreasing paper at both hospitals. This was a large adjustment to the Purchased Hospital’s processes which would require RMC to educate and train all clinical disciplines how to document in Paragon. Since 90% of the physicians were using Paragon at RMC, the responsibility for physicians only included training 10% of the medical staff.

There was a total of 709,528 medical records in both systems with a potential 50% to 60% overlap which meant the patient had been at both facilities. This data was provided by an algorithm report that RMC contracted a vendor to provide RMC.  The first algorithm report showed that we would need to create an estimated 60,000 new medical record numbers for patients that were not in the RMC’s Master Patient Index (MPI). The goal was to decrease that by matching more of the patients by investigating each case to ensure the patient truly was not in RMC’s MPI. RMC’s Paragon had a total 482,528 medical records with a potential duplication rate of less than 2%. The medical record numbers were 6-digits (123456) and the account numbers were 10-digits (1234567890). The Purchased Hospital had 227,000 medical records with an 8% potential duplication rate. The medical record number was a 10-digits number which had 4 leading zeros (0000123456) and the account numbers had 7-digits (1234567). Table 1 illustrates the basic comparison of characteristics of medical record systems from RMC and the Purchased Hospital.

Project Goals

The primary goals of the project include:

1. Assess the feasibility, compatibility of the systems, and determine the scope of the project.
2. Design an electronic system that would merge and store all the medical records and administrative data from both hospitals.
3. Identify all potential duplicates in medical records, and upon verification, merge in the hospital information system.
4. Develop a team to ensure that any downstream systems that operate using a medical record as identification are updated or changed at the same time.
5. To create a new medical record number with all the patient’s visits from the Purchased Hospital’s system into RMC Paragon and OneContent. An example would include radiology films must match your EMPI.
6. Migrate all patient medical record documents stored in HPF into OneContent under the correct patient medical record number.

Definitions

• Person: Any individual contained within the Paragon database. A person can be a patient, physician, employee, guarantor, etc.
• Patient: A person within the Paragon database who has been registered for at least one visit. All patients are persons within Paragon, but not all persons are patients.
• Potential Duplicate: A patient identified as having two or more medical record numbers.

Project Phases and Timelines

This project consisted of three phases. It started from Phase I Analysis and Design in May 2017 and ended in Phase III Go Live in July 2018 (see Table 2).

Results

Project Procedures

In order to carry on the merging of duplicated records, a three-step process should be followed: identification, verification, and merging.

Step 1: Identification

1. Identification of potential duplicates is ascertained through daily monitoring of the Possible Duplicate Persons report housed in the Paragon Medical Records Reports Module and communication from hospital personnel who identify potential duplicates through the course of their job duties.
2. Printing the Possible Duplicate Persons report. Research the entries to confirm whether valid duplicate medical record numbers exist (see Figure 1).
3. Notifications regarding potential duplicates that are received via the Medical Record Number Correction form, e-mail, telephone call, etc. will be processed according to this policy and procedure.

Step 2: Verification

1. In order for the potential duplicates to be considered a 100% match all the following criteria MUST match:

a.) Date of Birth

b.) Social Security Number

c.) First Name

d.) Last Name

2. Access Abstract Maintenance in Paragon Medical Records to verify the information. Compare the print outs. If all items listed in #1 match for both persons, the merge process can begin. Otherwise, continue verification process.
3. Verify Social Security Number at OneSource. If social security verification determines person is not a duplicate, stop here and do not merge (see Figure 2).
4. Verify insurance using Paragon Patient Management and OneSource. Determine patient’s insurance type through Paragon Patient Management. Use OneContent to compare information such as insurance cards, signatures. Global documents will include information such as insurance cards, and driver’s license which can be used to verify patient’s identity (see Figure 3).

Step 3: Merging

Merging has two conditions:

a.) Merging when all medical record numbers are attached to a visit;

b.) Merging when one or more medical record numbers are not attached to a visit.

1. When determining which medical record number to retain, check to see if any of the medical record numbers have an active account. The merge cannot be completed until the account(s) have been discharged and are no longer active. Typically, the medical record number with the most visits will be retained. If the medical record numbers being merged have an equal number of visits, retain the medical record number with the most recent account.
2. After determining which medical number will be retained, review the demographic sheet print out and ensure the following data elements match the medical record number with the most current visit. The elements in bold must match for Paragon to allow the merge.

a.) Date of birth

b.) Sex

c.) Race

d.) Social Security number (enter 9 zeros for all medical records not being retained)

e.) Ethnicity

f.) Marital status

g.) Religion

h.) Preferred language

i.) Privacy note date

j.) Advance directive

The Key Tasks and Accomplishments in Each Phase

Phase I. Analysis and Design (May 2017-September 2017)

1. Assigned leadership responsibilities to the Director of Health Information Services (HIS) from RMC (with 33 years’ experience in HIM) to work with Chief Information Officer (CIO) (with 25 years hospital IT experience and system implementation) to have oversight for the project. Due to the nature of the project, it required both HIM and IT skill sets to accomplish this major project.
2. After assessing the systems at both hospitals, the team decided on the best approach to combine the disparate data sets. EMPI teams were formed to compare and review the data for accuracy for the overlay patients, duplicate patients and the patients that had not been to RMC. This team would determine which patients would need to be assigned a new medical record number. To correct each duplicate record, it was estimated that the length of time to take 38 minutes per record. Each person on the team could potentially fix 10 to 15 records per day.
3. Conducted an investigation to determine if new medical records would need to be created for all 60,000 patients. The investigation was needed due to discrepancies in the data fields such as different last names, dates of birth, unknown sex and social security numbers being off by one digit. It was estimated to take approximately 1 to 2 hours to complete the needed investigation work per patient record. This estimate included the time it took to switch and compare data between two systems. This goal was critical to patient safety to ensure a complete medical record was being implemented. Contracted with one HIM vendor to assist in doing the investigations for three months due to of the amount of time it would take to investigate each case.
4. Analyzed how the mapping would occur for the documents, bar codes and images from the Purchased Hospital’s HPF system into RMC’s OneContent system. The team made the decision to use RMC’s naming convention since RMC was the larger database and was built with more complicated workflows. An example of naming conventions would include a document name in the Legacy System such as Consent for Treatment and in OneContent that document name would be listed as Adm Consent Treatment. The team had to ensure that all documents would be stored properly for the legal medical record. Table 3 illustrates examples of documentation names.
5. Created an EMPI in Paragon and OneContent. Both hospitals would require training on how to locate the patient and medical record. Screen shots were developed for purpose of training the staff.
6. Set-up a messaging system to alert when there is a change in medical record numbers to downstream systems, such as laboratory radiology, cardiology, Tumor Registry and the patient portal, where the EMPI in the systems could be updated immediately.
7. Mapped financial data, such as patient types, payer codes, insurance, financial class and account types.
8. Developed training manuals and procedures by both HIM and IT teams. For protection of patient safety and data integrity, every staff member is responsible in following the procedures.

Phase Two: Action Steps (October 2017-July 2018)

1. Established a subset of EMPI data including medical record number, Social Security number, last name, first name, middle name, DOB, address, age and sometimes maiden name from both hospital systems. Determined which data subset contained the latest demographic data for each patient. These data subsets were used with a scripting tool to verify the data comparisons to the first algorithm report.
2. Merged all confirmed duplicate medical records in the live systems. The goal was to decrease the number of duplicate medical records before the systems Go Live.
3. Identified if a patient needed a new medical record number in RMC’s EMPI or if we needed to merge the patient’s medical records between the two hospitals. These reports were worked and saved weekly.
4. Weekly reports were run by Paragon and OneContent representatives to measure how many patients were left to match. The patients’ data were updated in the test system weekly and would be pulled from test into the live system on July 30, 2018.
5. Created a medical record process for new patients being registered in the hospital to allow automatically and systematically assigned medical record numbers.
6. Tested the amount of time it would take to move the medical records numbers, account numbers and documents with the images from the Purchased Hospital into Paragon and OneContent. These tests assisted with estimation of the required downtime during the Go Live conversion.
7. Determined how incorporating the Purchased Hospital into one system would affect the patient portals with an immediate HL7 feed at both facilities.
8. Consolidated statistical data or reports for financial, quality, state or federal reporting by multiple teams including Administration, IT and HIM. Formatted documentation forms with barcodes. Tested the amount of time that it took to move the actual document images. Mapped patient index files that required by Centers for Medicare and Medicaid Services (CMS) and The Joint Commission (TJC) to be permanent from both hospitals.
9. Provided screen shots to identify and teach all the staff on both campuses on the EMPI and how the new set-up will look.
10. Evaluated medical records from both hospitals for matching the Purchased Hospital’s 10-digit registration system. Many tests were required as this feature caused the hospital to have false data on the patient algorithm reports. Many of the 60,000 were actual one to one matches once the data was reviewed for 11-character names such as Christopher.
11. Matched EMPI number and medical record number in Paragon and OneContent. The team verified admission and discharge dates and times were correct for RMC and the Purchased Hospital.
12. Set-up Go Live date and time as July 30, 2018, at 7:00 am. All systems at Purchased Hospital were taken offline on July 27, 2018 at 5:00 a.m. and would begin manual downtime processes. Registration tracked all patients that were in-house at downtime and any other patients that were treated at the hospitals.
13. Uploaded verified data into the live system starting around 11:00 p.m. on July 29, 2018. During this time, IT pulled new reports and sent this to the team to analyze the data to ensure the data was uploaded correctly in the live system.

Phase III. Go Live (July 30, 2018)

1. Activated entire hospital system. All systems were brought on-line at 7:00 a.m. The EMPI team continued to verify the data and documents had uploaded correctly in the live systems. The Business office registered all the patients that had presented to the Purchased Hospital from July 27, 2018, 7:00 a.m. until Go Live on July 30, 2018 at 7:00 a.m.
2. A swat team of IT and clinical staff was maintained at the Purchased Hospital to support all hospital staff after Go Live. This team was stationed there for several weeks to ensure quick assistance and issue resolution.
3. Monitored all patient census coming into the system during the downtime.
4. Monitored and tested for any type of errors that may have been loaded in all systems for one month after Go Live. For example, patient portal reports were built to ensure that the correct patient’s information was automatically being sent to the portal.
5. Assigned one employee to report the census and another to work on any new duplicate medical records created after Go Live for both facilities from Paragon.

Discussion

When approaching a project such as this one it is essential to have an effective leadership team from both HIM and IT for a successful project.  The MPI is the foundation base for all EMRs and it is critical that the information is accurate.  Our key points on lessons learned and recommendations during the conversion include involve the right staff, clean up MPI, know the workflows, consolidate systems, interface to automate, and source of truth.

Involve the Right Staff

Involve all the key players from both facilities.  It is very important to ensure all key areas are represented while planning and working through the conversion process.  This should include not only HIM and IT but areas such as registration, scheduling and the business office.  These areas work with the patient accounts daily with very different functions that involve data being represented in the EMPI and patient accounts. Be prepared to commit to weekly or bi-weekly communication either by conference calls or video between all members. It is believed that this communication saved the hospital from many issues on the constant updating of data and meeting the goals.

Clean Up that EMPI

If your IT system has the ability to run an analytical report on both the current and the newly purchased systems this must be your first step. If not, we suggest purchasing an algorithm report. That will be your base to determine the amount of time needed and what type of work will need to be performed. Do as much cleanup work on the EMPI as possible before you begin to merge any data.  The more time spent identifying duplicate persons, missing data elements and cleansing data the better.  In our situation we had a large percentage of overlapping patients that had accounts at both hospitals.  This proved to be very challenging and required a lot of manual data verification to ensure the right accounts would be merged, and new accounts created when necessary.

Know the Workflows

It is critical to understand the workflows and the culture of the other organization.  This is a lesson we learned quickly.  While a workflow may work fine at one facility it may need to be tweaked to work just a little differently at the other facility.  Standardizing workflows and processes should be a goal but be flexible when needed.  Look at all options and possibilities.  Keeping in mind the way you are currently performing a process may not actually be the most efficient way to start with.  Just because it’s always been done that way does not mean it’s the right or best way.

Consolidate Systems

Consolidate systems when possible, as it is much easier to manage and support.  This holds true for not just clinical applications but any system being used at both facilities.  During our conversion the goal was to ensure both hospitals were using the same systems both clinical and non-clinical across the board.  This helps with staff orientation, training and when staff may float between hospitals. A good example of this is the policies and procedures that are attached to your workflows or documentation.

Interface to Automate

Interface to eliminate manual processes.  Interfaces are the backbone of healthcare applications allowing different systems to pass information back and forth.  Interfaces can save hundreds of man hours and ensure data is available in real-time.  Ensure you have a robust Interface Engine in place that can handle the multiple interface loads as well as being able to customize interfaces as needed.  And always remember a standard admission, discharge, transfer (ADT) interface is never “standard”.

Source of Truth

With so many different computer systems sharing data within a healthcare environment, it is critical that there be a single source of truth (SSOT) for EMPI data.  This SSOT is the master key to all EMPI related data.  All downstream systems will receive data from the SSOT provider, and that data should be considered golden.  Any and all changes to EMPI data should be made at the SSOT point.

Conclusion

Patient matching continues to be a challenge for hospitals and health information exchanges. This situation increases the hospital expenses and endangers the integrity of the patient medical records. A solution to ensure that patient data can be matched correctly is needed whether that is a national unique patient identification or allowing the private sector to help solve the problem. With increased technology and informatics, patient identification and matching issues can be resolved effectively and efficiently. This must be one of our nation’s priorities. A collaborative team between HIM and IT and a strong leadership are the key for a successful project in merging medical record systems.

Acknowledgment

The authors would like to thank everyone that worked with the team so closely in making this project such a success! Likewise, much appreciation also goes to the IT and HIM Departments along with the vendors, Allscripts and Hyland.

Donna Crew, RHIA (dcrew@rmccares.org) is Director of HIS/Privacy Officer, the Health Care Authority of the City of Anniston, Anniston, AL.

Pete Furlow (pfurlow@rmccares.org) is Chief Information Officer, the Health Care Authority of the City of Anniston, Anniston, AL.

Shannon H. Houser, PhD, MPH, RHIA, FAHIMA (shouser@uab.edu) is Professor, Department of Health Services Administration, the University of Alabama at Birmingham, Birmingham, AL.

References

1. Beaulieu ND, Dafny LS, Landon BE, Dalton JB, Kuye I, McWilliams JM. Changes in Quality of Care after Hospital Mergers and Acquisitions. The New England Journal of Medicine. 2020;382:51-9. DOI: 10.1056/NEJMsa1901383
2. Schmitt M. Do hospital mergers reduce costs?”Journal of Health Economics. 2017;52:74-94. https://doi.org/10.1016/j.jhealeco.2017.01.007
3. Noether MS. Hospital Merger Benefits: Views from Hospital Leaders and Econometric Analysis. Charles River Associates. 2017. Available at http://www.crai.com/sites/default/files/publications/Hospital-Merger-Full-Report-_FINAL-1.pdf
4. Lohrkea FT, Frownfelter-Lohrkea C, Ketchen DJ Jr. The role of information technology systems in the performance of mergers and acquisitions. Business Horizons. 2016;59(1):7-12. https://doi.org/10.1016/j.bushor.2015.09.006
5. Minich-Pourshadi K. Challenges in Hospital Mergers and Acquisitions. Health Leaders Intelligence. 2010. Available at http://content.hcpro.com/pdf/content/259008.pdf
6. Harris S, Houser SH. Double Trouble—Using Health Informatics to Tackle Duplicate Medical Record Issues. Journal of AHIMA. 2018;89(8): 20–23.
7. Steininger K, Kempinger B, Schiffer S, Pomberger G. A Process Model for IT Migrations in the Context of a Hospital Merger – Results From an Austrian Case Study. Studies of Health Technology Informatics. 2016;223:182-90.
8. Walker AR. “Case Study: Leading Change across Two Sites: Introduction of a New Documentation System.” Nursing Leadership. 2006;19(4): 34-40. doi:10.12927/cjnl.2006.18598
9. Reference: RMC Health System. “About Us.” Available at https://rmccares.org/about/

Table 1. Basic Comparisons of Medical Record Systems between RMC and the Purchased Hospital

Table 2. Phases and Timelines

Table 3. Examples of Document Names in Legacy System and OneContent

Figure 1. Screen Shot of Identification Procedure

Figure 2. Screen Shot of Verification Procedure

Figure 3. Screen Shot of Verification Procedure

According to the Centers for Disease Control and Prevention (CDC), electronic case reporting (eCR) is the “automated generation and transmission of case reports from an electronic health record (EHR) to public health agencies for review and action. eCR makes disease reporting from healthcare providers to public health faster and easier.”¹

Reporting of cases or diseases provides an understanding of occurrences and trends that assists with public health planning efforts, resource allocation, and policymaking. Typically, case reporting, which is required by law to report to state and local public health entities regarding specific diseases and conditions, has been conducted via paper-based methods. Paper-based methods cause several challenges in public health’s ability to report timely data that supports their efforts in conducting regular surveillance to help prevent, investigate, report, and control disease outbreaks.

Passage of the Health Information Technology for Economic and Clinical Health Act (HITECH Act), enacted under the American Recovery and Reinvestment Act of 2009 (ARRA), served as a catalyst for adopting, implementing, and using health information technologies (health IT) and transitioning away from paper-based reporting to a more advanced process of eCR. The Centers for Medicare and Medicaid Services (CMS) Meaningful Use EHR Incentive Program issued a final rule in 2015 for Stage 3 that added eCR as a new public health measure.

Enacting this law created unprecedented opportunities for public health agencies and facilitated a much-needed push toward electronic reporting. However, the ability for public health agencies to receive electronic reporting information was still nascent and progress was slow in this area.  Without laying the framework through policy levers and making eCR a requirement, public health agencies have been slow to adopt as the infrastructure and funding make this a lower priority.

Despite these challenges, EHRs and other health IT solutions have advanced stakeholders’ ability to collect, analyze, and report on required public health surveillance efforts. As these technologies have matured since HITECH, health information exchanges (HIEs) and other case reporting systems have emerged to support eCR and have become more widely adopted. eCR provides several benefits over paper-based reporting, such as:

• Reduces response time by automatically submitting required case reporting to designated public health agencies
• Reduces manual entry, faxing, and phone calls
• Complies with reporting requirements for the Promoting Interoperability Program (formerly meaningful use) for implementing eCR
• Complies with HIPAA and state reporting laws
• Monitors the spread of reportable conditions such as COVID-19

Although eCR provides many benefits to stakeholders as they transition away from paper-based reporting, public heath reporting systems remain fragmented and siloed. This has created significant challenges, and with the onset of COVID-19, it has exposed limitations within the United States’ public health surveillance system in a significant way where timeliness, completeness, and accuracy of data is critical in the pandemic’s response efforts.

Congressional Efforts Supporting COVID-19 Response

To support public health agencies and their ability to report data in response to COVID-19, Congress has taken several steps. The Coronavirus Aid, Relief, and Economic Security Act (CARES Act) that was signed into law in March 2020 provided a $2.2 trillion economic stimulus, which included $500 million for the CDC to support “public health data surveillance and analytics infrastructure modernization.”² In supplemental appropriations for COVID-19, the CDC has received $7.5 billion and $10.25 billion in grants for testing and other public health purposes (including surveillance). Additional funding may be transferred to the CDC from other US Department of Health & Human Services (HHS) accounts and used by the agency for surveillance purposes.

Lab Reporting Requirements

The CARES Act requires that every clinical laboratory that performs or analyzes tests—which are intended to detect or diagnose possible cases of COVID-19—to report the results to HHS. The reporting period and format of the data submission is at the discretion of the HHS secretary until the end of the COVID-19 Public Health Emergency declaration or any extension that has been granted.

Congressional Reports

The Paycheck Protection Program and Health Care Enhancement Act (PPPHCEA), enacted in April 2020, required analyses and reporting of COVID-19 data by HHS. Congress required no later than 21 days after enactment, and every 30 days until the end of COVID-19 PHSA, HHS was required to report on testing, cases, hospitalizations, and death, which also included de-identified demographic data and other relevant factors. Congress also expected HHS to report on, no later than 180 days after enactment, the number of positive diagnosis, hospitalizations, and deaths as a result of COVID-19 and any other factors.

eCR Now

As COVID-19 emerged and persisted across the country (and the world), it became clear that a solution was needed quickly to address the rapidly spreading disease. Relying on the currently mostly paper-based and inconsistent infrastructure was insufficient to provide a rapid response to the evolving health crisis.

Despite policy and funding efforts within Promoting Interoperability, eCR was in the early deployment stages and existed only in a limited number of sites led by the CDC, the Council of State and Territorial Epidemiologists, and the Association of Public Health Laboratories (APHL) when COVID-19 was first identified.

Seeing an urgent need to address the rapidly developing public health crisis, the eCR team developed a strategy, termed eCR Now, for immediate deployment. eCR Now provides the identifiable clinical patient data as required to state and local public health agencies that are needed to support outbreak management and action.

According to John W. Loonsk, MD, FACMI Adjunct Associate Professor, Johns Hopkins Bloomberg School of Public Health, Consulting Chief Medical Informatics Officer, Association of Public Health Laboratories since the beginning of COVID-19 more than 6,900 facilities have reported on COVID-19 through eCR.

eCR supports three different approaches toward reporting COVID-19 cases:

Element 1: A cohort based COVID-19 rapid eCR implementations for sites that have eCR-enabled EHRs. This approach leverages the FHIR trigger code distribution service that allows users to stay current with codes (ICD-10, LOINC, SNOMED) as they change. Confirmed cases reported to public health agencies are not required to submit data via manual entry and reporting, thus reducing the burden on providers and public health.

Element 2: eCR Now FHIR SMART App (as shown in Figure 1) is a solution supporting EHRs that are non-eCR enabled to ramp up quickly for reporting purposes. This app connects the COVID-19 eCR to existing infrastructure and automatically reports triggering and trigger codes, electronic initial case reporting (eICR), reportability response sorting, etc., through the APHL Informatics Messaging Services (AIMS) shared services infrastructure. Different implementation models are provided to support different options, such as local or cloud hosting, SMART on FHIR or through a system application launch. Figure 1 demonstrates the infrastructure of eCR Now and how the app is integrated into the current reporting workflow.³

Figure 1: eCR Infrastructure

Element 3: A nationwide eCR trust framework for eHealth Exchange, Carequality, CommonWell members, and those entities that connect with them to support the onboarding process. Participants that currently conduct eCR are not required to develop new legal agreements for their participation.

CDC’s Data Modernization Initiative

At the urging of key stakeholders and support from the CDC director and Congress, in 2014 the CDC began its journey toward a modernized surveillance strategy that allows the agency to move toward anticipating threats rather than reacting to them. The plan highlighted three goals: 1) enhance the workforce; 2) accelerate the use of emerging tools and approaches to improve the availability of quality and timely surveillance data; and 3) demonstrate early successes through four crosscutting surveillance system initiatives (mortality reporting, case reporting, electronic laboratory reporting, and syndromic surveillance) to improve public health surveillance outcomes. Since then, the CDC made progress in its modernization efforts and had begun to pilot new systems for data sharing between public health departments and healthcare organizations in real time through the Digital Bridge initiative. In fiscal year 2020, Congress provided its first specific appropriations ($50 million) to the CDC for “Public Health Data Surveillance/IT Systems Modernization.” In previous years, the CDC’s modernization efforts were funded through other budget line items.

By the time the pandemic arrived, public health reporting was still reliant on siloed, manual, and paper-based processes to exchange or report data. Meeting the volume and velocity of reporting needs for COVID-19 overwhelmed public health data systems and their infrastructure, which created challenges for reporting. The CARES Act provided the CDC with $500 million for data surveillance and analytical infrastructure that will boost its efforts in modernizing public health data and reporting initiatives for immediate COVID-19 needs and for the long-term. With this funding, the CDC expects to:

• Leverage data for surveillance, detection, and improving jurisdictions’ situational awareness to allow localized, targeted responses and decision-making using more real-time data to respond to outbreaks like COVID-19.
• Expand the electronic exchange and integration of information between public health and healthcare, including electronic health records, which is essential for timely, accurate, and accessible disease surveillance.
• Support for public health’s data science, informatics, and IT workforce; expanding core data, informatics, and IT capacity; advancing interoperable systems and tools; strengthening and expanding collaboration.⁴

The CDC has expanded its automated reporting for COVID-19 test results from laboratories to health departments and the CDC, with 46 jurisdiction having converted to electronic systems as of October 16, 2020.⁵ New investments in fiscal year 2020 through CARES Act supplemental funding enabled the CDC to begin strengthening the public health data and surveillance infrastructure of the US through the launch of the agency wide Public Health Data Modernization Initiative (DMI).

The CDC is also collaborating with the eCR Now initiative to implement eCR that will enable data exchange between public health agencies and healthcare providers. Finally, as the Office of the National Coordinator for Health IT (ONC) is preparing its interoperability rules for EHRs in 2022, the CDC is working with the agency to support its attempts at public health data modernization.

COVID-19 has demonstrated the need for a strong public health infrastructure that is capable of electronically collecting and reporting on data to federal, state, local, and tribal communities. It has also brought to light the challenges of getting the right information to the right people at the right time when needed most.

Once health emergencies occur, especially public health emergencies the size and scope of COVID-19, you may believe that is not the time to advance programs in their nascent stages such as eCR Now or the CDC DMI, but it is exactly that time when our focus is on public health data reporting from a policy, planning, financial, and resource perspective when it is needed most.   

Notes

1. Centers for Disease Control and Prevention (CDC). “eCR Now: COVID-19 Electronic Case Reporting.” cdc.gov/coronavirus/2019-ncov/php/electronic-case-reporting.html
2. Congressional Research Service. “Tracking COVID-19: U.S. Public Health Surveillance and Data.” November 20, 2020.
3. Electronic Case Reporting. eCR General Information. https://ecr.aimsplatform.org/general/ecr-now-covid-19-fhir-app-challenge.
4. Centers for Disease Control and Prevention (CDC). “CDC Public Health Data Modernization.” cdc.gov/budget/documents/fy2021/fy2021-PHDM-factsheet.pdf.
5. Congressional Research Service.

Taking the Pulse of the Nation’s Social and Mental Wellness

Wanting to acquire information and understand the impact on economic and mental health of American households as a result of COVID-19, the National Center for Health Statistics partnered with the US Census Bureau and several other agencies to develop an experimental data system called the “Household Pulse Survey.”

The program consists of three phases, with phase one focusing on employment status, food security, housing, access to healthcare, educational disruption, and physical and mental health. The data collected will help to uncover what people are experiencing during the pandemic.

Because this initiative is a first of its kind, the federal statisticians are keeping an eye on the quality of the data to ensure data that is reported remains high.

Author’s Note: This citation belongs to the Household Pulse Survey. “Novel COVID-19 survey takes nation’s social, mental ‘Pulse.”

Allison Viola (aviola@guidehouse.com) is director at Guidehouse.