Comparison of McKesson and cerner Electronic Health Records

Senior (College 4th year) ・Healthcare&Medicine ・APA ・7 Sources

The purpose of healthcare information system is to capture, manage, store and transmit healthcare related information of individuals or the organizational activities that work in a health sector. Electronic health records (EHRs) are electronic systems that store individuals health records in place of hardcopy papers, according to Health information technology. This paper, therefore, compares McKesson and Cerner EHR vendors in the United States.


McKesson was established in 1833 as a seller and importer of botanical drugs thus being one of the oldest companies that have operated in the United States (Zieger, 2016). Currently, the company has two divisions in health IT systems and pharmaceuticals. In 2013, the company collected a revenue worth $122.5 billion placing it at the helm of the list of top health IT companies regarding revenue as per Healthcare Informatics (Zieger, 2017). Its clients comprise of the MedWest Healthcare Systems in N.C., Clyde, St. Mark's Medical Center in LaGrange, Texas, Oconee Medical Center in Seneca, S.C, and Twin County Regional Healthcare in Galax, Va. Moreover, McKesson designed Paragon and EHR without other set design features, interface requirements or, without fixed length fields, thus enabling EHR to fit and meet the needs of healthcare (Zieger, 2016).


The company was founded in 1979 by its CEO Neal Patterson. In 2013, Cerner recorded more than $2.67 billion (Zieger, 2016). It is the largest independent healthcare IT Company in the world and based in Kansas City, Mo. Its clients include Indiana University Health in Indianapolis, Pittsburgh-based UPMC, and Memorial Hermann Health System in Houston, Phoenix-based Banner Health, and Adventist Health System in Altamonte Springs, Fla. Also, 37 of its clients have reached the HIMSS Analytics stage 7.

Regardless of the company facing lawsuits in regards to EHR lawsuits, it scores highly in the independent user satisfaction surveys. In 2013, the company had to pay Medical Center in Minot, N.D., $106 million to resolve the allegation that the software they sold to them did not meet its functionality requirements as expected (Zieger, 2017). Also, Girard (Kan.) Medical Center, in 2012, sued the company for failing to complete HER. Besides the challenges, Cerner acquired several companies which include: Clairvia, a workforce management software vendor in 2011; Anasazi Software behavioral health technology vendor in 2012; and PureWellness, a population health and patient engagement software vendor in 2013 (Zieger, 2017).

Moreover, Zieger (2016) argues that the company has entered several partnerships in its efforts to be a leader in the field of health IT. It partnered with Children's National Health System in Washington, D.C., in September 2013. As a result, it developed the nation's first IT devoted research institute. Also, in December 2013, the company partnered with Claritas Genomics with the aim of developing a next generation's scalable laboratory solution for molecular diagnostics (Zieger, 2016). The aim was to increase the use of personalized medicine all over the healthcare industry. Furthermore, in October 2013, Cerner partnered with, Salt Lake City-based Intermountain Healthcare to implement Cerner software in its 185 ambulatory clinics and 22 hospitals.

According to Reddy & Reddy (2014), EHRs are designed to give doctors easy access to individuals' health information via a database that allows access to information even when an individual's doctor's office remains closed.  Other than data collected in healthcare's provider's office, EHRs includes comprehensive patient's history. They are designed to share and contain patients' information from healthcare providers lined to patients. Also, data in EHR can be created, manage, and consult anted by staff and authorized personnel across various health organizations (Weaver et al., 2016). 

Regarding patient data mobility, EHRs enables movement of patient health records from within them to other hospitals, healthcare providers, specialists, nursing home, and across states. Moreover, when looking at data integrity, EHRs have customized documentation applications that allow for the use of smart phrases and templates that assist with documentation. However, if not used appropriately, fraudulent activity may arise. However, to overcome the fraudulent activities, established policies and procedures put in place like auditing must ensure compliant billing (Dugani et al., 2017). 

Most importantly, is important to note that EMPI is created and accessed via EHR systems. However, irregularities may arise as a result of the difference in vendors thus resulting in reduced ability to reduce health information exchange (HIE) (In Weaver et al., 2016). Therefore, it is important to maintain consistency between EMPI and EHR systems to maintain consistency between them. Consequently, experts in health information technology in the United States argue that to solve the problem industry, or government-driven patient identification system can solve the problem. Eventually, it will lead to a national EMPI. Patient's data typically stored in the EMPI of healthcare organizations they are registered in as it is with EHRs of the specialists or ambulatory providers they see (Institute of Medicine, 2014).

Furthermore, EHRs are not the only healthcare systems they contain EMPI. Computerized physician order entry, radiology information systems, and lab systems also generate unique patient identifiers that EMPI can be contained. Therefore, a vendor can sell EMPI as stand-alone, or packaged in other products to healthcare organizations (Dugani et al., 2017). Because EMPI store information in a similar format, they can be used as a source of exchange of healthcare information amongst healthcare facilities. Health information exchange is therefore dependable in accountable care organizations (ACO) setting since they reduce ACO's workload. The arrangement makes EMPI as an important factor that helps health data analytics in the management of population health.  

Comparison between the vendors of Electronic Health Records(EHR)

The two main vendors that have been discussed in this category are the McKesson and the Cerner companies. Both are very competitive but the weight of competition is the one that brings up the difference. Firstly, McKesson is the older than Cerner because it was started in the year 1833 while the latter was started in 1979 by Neal Patterson who is the CEO. In the year 2013, McKesson was among the three companies that could expand their market share while Cerner company collected a high revenue worth $ 2.67 billion but was not lucky to be listed in the top three. The target of McKesson is small and retail users while Cerner vendor, has a very big market with several companies and has also been able to enter into several partnerships making the company a leader in the IT department. The designation of McKesson made it easy to fit the needs of healthcare records whereas Cerner experienced some challenges before stability like receiving complaints from their clients about software failure. A good example was Medical Centre in Minot that was paid $ 106 million to settle the allegations.  Cerner is the most-used certified health IT vendor as reported by hospitals compared to McKesson. By July 2016, 1,029 hospitals were reported to be using Cerner software.


In conclusion, EHR is a more beneficial system compared to the paperwork system. EHR enables track of data over time and monitors how certain patient parameters like blood pressure readings and vaccinations are measured. Moreover, EHR makes it easy for the identification of patients who are due for screening visits and above all improve the quality of health services provided (Tilley & Rosenblatt, 2017). The two companies, McKesson and Cerner, are dedicated to offering effective EHR services to all their clients.


Dugani, S. V., Dixit, S., & 2017 International Conference on Innovative Mechanisms for Industry Applications (ICIMIA). (February 01, 2017). Physiotherapy data analysis of big data in healthcare applications. 506-511.

In Weaver, C. A., In Ball, M. J., In Kim, G. R., & In Kiel, J. M. (2016). Healthcare information management systems: Cases, strategies, and solutions.

Institute of Medicine (U.S.). (2014). Capturing social and behavioral domains in electronic health records: Phase 1.

Reddy, N., & Reddy, G. (2014). Study of cloud computing in healthcare industry. International Journal of Science and Engineering Research, 4(9), 68-71 

Tilley, S., & Rosenblatt, H. (2017). Systems analysis and design, eleventh edition. Boston, MA: Cengage Learning.

Zieger, A. (May 16, 2017). Researcher Puts Epic In Third Place For EMR Market Share., 2017-5.

Zieger, A. (October 04, 2016). Integrating With EMR Vendors Remains Difficult, But This Must Change., 2016-10.

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