Meaningful Differences in Meaningful Use

After Adoption, Organizational Differences Still Predict Electronic Health Record Utilization

The Institute of Medicine’s report To err is human (Kohn & Corrigan 1999) estimated that  98,000 patients die each year from preventable medical errors. More recently, at a congressional hearing on the subject, Ashish Jha, MD, professor at Harvard School of Public Health suggested that this number is “clearly” a large underestimate of the toll brought by preventable medical errors (McCann, 2014; James, 2013).

“98,000 patients die each year from preventable medical errors… a large underestimate.”

A growing body of research suggests that well designed IT systems and electronic health records (EHR) have the potential to reduce medical errors and streamline delivery. Using data of IT-enabled productivity gains in other industries, some estimate that HIT could reduce annual health care spending by $346-$813 billion. A particular EHR function, computerized physician order entry, allows physicians to make prescriptions through the hospital’s EHR system and has the potential to eliminate as many as 200,000 adverse drug events each year by reducing human errors and harmful drug interactions (Hillestad et al, 2005).

“HIT could reduce annual healthcare spending by $346-$813 billion... [And] eliminate as many as 200,000 adverse drug events.”

Given these projections and others, the Center for Medicare and Medicaid (CMS) has developed the EHR Incentive Program, which reimburses eligible professionals and hospitals for adopting and utilizing authorized EHR systems. More than 545,000 professionals and hospitals are actively registered in the program as of August 2015, which has given out more than $30 billion in payments (CMS, 2016). This significant public investment has clearly motivated providers to implement EHR within their organizations.

“CMS has given out more than $30 billion in payments. This significant public investment has certainly motivated providers to implement EHR.”

In 2014, 3 out of 4 (76%) of hospitals had adopted at least a Basic EHR system. This represents an increase of 27% from 2013 and an eight-fold increase since 2008 (Charles et al 2015). Research on HIT adoption up to and following the incentive program has focused almost entirely on whether or not an EHR system exists in a hospital. This may have been proper in a time period where many hospitals did not adopt EHR but in our present state (largely thanks to the incentive program) most hospitals have EHR systems.

In 2014, 3 out of 4 (76%) hospitals had adopted at least a Basic EHR system. This represents an increase of 27% from 2013 and an eight-fold increase since 2008.

My research used the EHR incentive program’s performance metrics to study utilization levels instead of adoption. Whereas adoption is measured as a yes or no response, utilization level through these performance metrics is measured as the percent of cases in which an EHR function could be used for which the EHR function was actually used. For example; if a hospital makes 100,000 prescriptions a year and only used the EHR’s computerized provider order entry function to make 25,000 orders, the utilization level for that function would be 25%.

Factors supporting the utilization of EHR as described above are less understood. It should not be taken for granted that the predictors of adoption are the same predictors of utilization. My research describes variations in the utilization of EHR functions among acute-care hospitals enrolled in the EHR Incentive program and explores correlations between their organizational characteristics and performance on utilization metrics. It is important to understand EHR utilization because its benefits can only be realized by utilization and not simply by adoption.

From my analyses it turns out that simply adopting EHR doesn’t guarantee utilization, and not all predictors of adoption are predictors of utilization.

• Teaching status and system membership are correlated with greater utilization. 
• Larger size and for-profit status are correlated with less utilization. 
• Clinician workload is not correlated with utilization but the presence of contractual relationships is correlated with utilization. 
• Furthermore, tighter physician contractual relationships are correlated with greater utilization of most EHR functions.

It turns out that simply adopting doesn’t guarantee utilization and not all predictors of EHR adoption are predictors of EHR utilization.

We infer from the results and existing theory that although larger hospitals have the resources to adopt EHR they are slower to change clinical processes for its utilization. For-profit hospitals may respond to incentive payments but may like-wise have difficulty prioritizing process change. Supporting the process-change concept is evidence that hospitals with contractual relationships with physicians, i.e. greater clinical alignment perform better for those functions requiring process change. Methodologically, this research supports the use of utilization level as a more useful measure of EHR adoption.

Overall, these results suggest that it is important to consider factors impacting process change in general and in the delivery of healthcare in particular. 

I will be presenting my findings in more detail at the 2016 AcademyHealth Annual Research Meeting. You can find me speaking at the Healthcare Organization and Delivery session of the Health IT interest group and at the poster-session for Healthcare Organizational Behavior and Management.

By: Rekar K. Taymour, MS Candidate, Health Services Research, University of Michigan School of Public Health, Department of Health Management and Policy

References

Kohn, L. T., Corrigan, J. M., & Molla, S. (1999). To Err Is Human. Medicine, 126(November), 312. http://doi.org/10.1017/S095026880100509X

McCann, E. (2014). Death by medical mistake at record high. Healthcare IT News. Retrieved from http://www.healthcareitnews.com/news/death-medical-mistake-record-high

James, J. T. (2013). A new, evidence-based estimate of patient harms associated with hospital care. Journal of Patient Safety, 9(3), 122–8. http://doi.org/10.1097/PTS.0b013e3182948a69

Hillestad, R., Bigelow, J., Bower, A., Girosi, F., Meili, R., Scoville, R., et al. (2005). Can electronic medical record systems transform healthcare? Potential health benefits, savings, and costs. Health Affairs, 24(5), 1103—1117.

CMS 2016, Centers for Medicare & Medicaid Services, EHR Incentive Programs, Data and Program Reports, https://www.cms.gov/Regulations-and-guidance/legislation/EHRIncentivePrograms/DataAndReports.html

Charles, D., Gabriel, M., Searcy, T., Carolina, N., & Carolina, S. (2015). Adoption of Electronic Health Record Systems among U . S . Non - Federal Acute Care Hospitals : 2008 -2014 

The Health Information Technology for Economic and Clinical Health ( HITECH ) Act of 2009 directed the Office of the National Coordinator for Health, 4(23), 2008–2014.