D220 Task 1 EHRS Analysis Example

An Electronic Health Record System in a 25-Bed Critical Access Hospital: Purpose, Decisions, a Barrier, and the Systems Around It

Student Name

Leavitt School of Health, Western Governors University

D220: Information Technology in Nursing Practice, Task 1

Course Instructor

Month Day, Year

An Electronic Health Record System in a 25-Bed Critical Access Hospital: Purpose, Decisions, a Barrier, and the Systems Around It

Healthcare Setting and Electronic Health Record System

The setting is a composite 25-bed critical access hospital in a rural county, with a four-bed emergency department, a medical-surgical unit that also holds swing beds, a small laboratory and radiology service, and no on-site specialists. One physician or advanced practice provider covers the emergency department at night, and seriously ill patients are often transferred more than 90 miles to a tertiary center. The hospital uses MEDITECH Expanse as its electronic health record system (EHRS) for documentation, orders, results and medication administration across every department.

Purpose of the EHRS

In this setting the EHRS has three purposes. It is the single record of each patient's care, so a nurse on the medical unit can see what happened in the emergency department hours earlier. It is the channel for orders and results, so a provider covering several areas can order a test from one place and see the result as soon as it is verified. And it is the source of the data the hospital reports to state and federal programs, which matters for a small facility whose funding depends on accurate reporting. Nearly every United States hospital now has an EHRS, but critical access hospitals lag behind larger hospitals in using advanced functions such as analytics dashboards and patient engagement tools (Apathy et al., 2021). The purpose here is therefore practical and basic: one accurate record that a small team can rely on.

Nurses carry much of the responsibility for that accuracy. In a hospital this size the same nurse may admit a patient, give the first antibiotic dose, record the fall risk score and document the discharge teaching, so gaps in nursing documentation become gaps in the whole record. When the nurse records a vital sign late or in a free-text note instead of the flowsheet, the trend views and reports that other clinicians depend on no longer show it. For that reason the hospital's nurse educator reviews flowsheet completion each month and shares the results with each unit, treating documentation quality as part of patient safety rather than as clerical work.

Using the EHRS to Make a Patient Care Decision

At 0200 a 76-year-old composite patient admitted with pneumonia has a rising respiratory rate. The night nurse opens the vital signs flowsheet and sees the trend over the last eight hours: respiratory rate from 18 to 28, oxygen saturation from 95% to 90% on 2 liters, heart rate from 88 to 112, and a new temperature of 38.6 C. The same screen shows that a lactate drawn at admission was 1.8 mmol/L and that the last dose of ceftriaxone was given on time. Seeing the trend together, rather than as separate numbers, the nurse recognizes a patient who is getting worse, calls the provider with a structured report that quotes the values from the record, and receives orders for a repeat lactate, blood cultures and a chest radiograph.

The repeat lactate returns at 3.4 mmol/L. With the trend, the results and the medication record all in one place, the provider and nurse decide together that the patient needs a higher level of care than the hospital can provide, and the transfer process begins before the patient deteriorates further. The decision to escalate and transfer came from data the nurse entered and the EHRS displayed as a trend, which is the kind of decision support a small hospital depends on when no intensivist is in the building.

Barrier to Using the EHRS in This Setting

The main barrier is limited interoperability with the tertiary center, which uses a different vendor's system. When a patient is transferred, the receiving hospital often cannot open the critical access hospital's record directly, so nurses print or fax the medication record, recent results and progress notes, and the receiving team re-enters key information by hand. This creates delays, gaps and the risk of transcription errors at the moment a patient is most unstable. In a national sample of about 2,200 hospitals, those participating in a health information exchange organization engaged in more clinical information exchange than those that did not (Richwine et al., 2025), but a small hospital with two IT staff has limited capacity to build and maintain those connections.

The consequences reach the bedside. During the transfer in the example above, the receiving intensive care nurse would have to call back for the time of the last antibiotic dose and the trend of the lactate, while the sending nurse is already caring for other patients. Every item copied by hand is an item that can be copied wrong, and every phone call to clarify it takes a nurse away from a small unit with no one to cover.

Health Information System and Technology

The health information system examined here is the laboratory information system (LIS), which receives orders from the EHRS, manages specimens and analyzers in the hospital's small laboratory and sends verified results back into the patient's record. The technology is a tele-emergency cart: a mobile unit with a high-definition camera, speakers and a connection to an emergency physician group at a regional center, which the night provider can bring into the room for a live consultation.

How the Health Information System Supports Decision-Making

The LIS supports decisions by getting accurate results to the people who act on them quickly. In the pneumonia example, the repeat lactate was run on the hospital's analyzer, verified by the laboratory technologist and sent into the EHRS within 40 minutes, with a critical value flag that triggered a phone call to the nurse. Without an interface between the LIS and the EHRS, the result would have been printed and carried to the unit, adding time at night when one technologist covers the whole laboratory. The LIS also flags delta changes, such as a large jump in creatinine from the previous day, which prompts nurses to review fluid balance and medication doses before the next scheduled dose.

How the Technology Supports Decision-Making

The tele-emergency cart supports decisions about whether a patient must be transferred. Across six tele-emergency networks serving 65 rural hospitals, about one in five tele-emergency encounters met criteria for an averted transfer, and each averted transfer saved an estimated $2,673 in transport costs (Ward et al., 2021). In this setting the remote physician can examine the patient, review the EHRS on a shared screen and help the local provider decide whether the patient can safely stay, which keeps patients close to their families when transfer is not needed and sends them sooner when it is. For nurses, the consultation clarifies the plan and the monitoring expected overnight.

Conclusion

In a small rural hospital, the EHRS, the laboratory information system and tele-emergency technology work together to give a thin night team the information it needs to make safe decisions. The EHRS turns separate numbers into a visible trend, the LIS delivers results quickly with the right flags, and the tele-emergency cart brings specialist judgment to the bedside. The weak point is the record's poor movement to the tertiary center, which is where the next investment in interoperability should go.

References

Apathy, N. C., Holmgren, A. J., & Adler-Milstein, J. (2021). A decade post-HITECH: Critical access hospitals have electronic health records but struggle to keep up with other advanced functions. Journal of the American Medical Informatics Association, 28(9), 1947-1954. https://doi.org/10.1093/jamia/ocab102

Richwine, C., Strawley, C., Chang, W., & Everson, J. (2025). Assessing the value of health information exchange organizations to hospital interoperability. Health Affairs Scholar, 3(7), qxaf133. https://doi.org/10.1093/haschl/qxaf133

Ward, M. M., Carter, K. D., Ullrich, F., Merchant, K. A. S., Natafgi, N., Zhu, X., Weigel, P., Heppner, S., & Mohr, N. M. (2021). Averted transfers in rural emergency departments using telemedicine: Rates and costs across six networks. Telemedicine and e-Health, 27(5), 481-487. https://doi.org/10.1089/tmj.2020.0080