HINF 500 Week 1 Informatics as a Strategic Tool for the Health Administrator Example

Timestamps Nobody Read: How a Community Hospital's Administrator Turned Electronic Record Data Into a Strategy for Emergency Department Boarding

[Student Name]

University of Phoenix

HINF/500: Informatics for Health Administration

Week 1 Assignment

[Instructor Name]

[Date]

The hospital, its data and the administrator's decisions are composites written for a model paper; national findings and research come from the sources listed.

Three weeks into her job as vice president of operations at a composite 310-bed community hospital, the new executive sat in a meeting where the chief medical officer and the chief financial officer argued about whether to build a 24-bed addition. The emergency department was holding admitted patients for hours, and the medical officer said the hospital simply had too few beds. The vice president, who had just started a Master of Health Administration, asked what the data showed. No one knew. This paper explains informatics as a strategic tool and follows how she answered the question.

What Informatics Is

Health informatics is the use of data, information and technology to support decisions and improve care, operations and health. It differs from information technology, which provides the systems. A useful way to think about informatics is as a ladder: data are raw facts, such as the time a bed was requested; information is data organized to answer a question, such as the median wait for a bed; knowledge is understanding why the wait is long; and wisdom is choosing the right response. Administrators work at every step of that ladder, even when analysts do the extraction.

How Records Became Electronic

Not long ago, most of this data sat on paper. A national survey published in 2009 reported that just 1.5% of hospitals responding had electronic records running in every clinical unit, while 7.6% more had a basic system in at least one unit, with cost the most cited barrier (Jha et al., 2009). Later that year, the federal economic stimulus law set aside billions of dollars to reward hospitals and physicians that installed certified record systems and showed they were using them in defined ways, with payment penalties for those that did not. Adoption rose rapidly, and today nearly every hospital records care electronically. The result is a vast store of timestamps, orders and results that most organizations use far below its potential.

Sourcing the Data

The vice president asked the hospital's data analyst for every inpatient admission from the emergency department in the past year, with the times of the admission decision, the bed request, bed assignment, the patient's departure from the department and the discharge time of the patient who had last occupied the assigned bed. The electronic record held all of these. The extract covered 14,200 admissions.

Checking the Data

Before analyzing, the analyst checked quality. About 4% of records had missing or impossible times, such as a departure before a bed request, usually from late documentation. These were excluded. The analyst also compared a sample of 50 records with nurses' notes and found the timestamps accurate within 15 minutes in 46 cases.

What the Data Showed

The median time from admission decision to departure from the emergency department was 5 hours and 10 minutes, and 18% of admitted patients waited more than 12 hours. But bed occupancy at midnight averaged 86%, not full. The problem was timing: 62% of discharges occurred after 2 p.m., while admissions from the emergency department peaked from late morning into the early evening. Beds existed but emptied too late in the day.

Why It Matters

Long boarding carries real risk. In a study of 41,256 admissions from an emergency department, hospital mortality rose from 2.5% for patients boarded under 2 hours to 4.5% for those boarded 12 hours or more, and length of stay also increased, even after adjustment for illness (Singer et al., 2011). The data turned a construction debate into a question about what time of day patients go home.

From Information to Strategy

The analysis changed the decision. Rather than a $19 million bed addition, the vice president proposed a strategy to move discharges earlier. Evidence suggested it was achievable: an academic medical center that set a discharge-before-noon goal, with daily planning, early rounding on patients ready to leave and a discharge lounge, saw early discharges climb to 38% of the total from 11% at baseline, moved the average discharge time 91 minutes earlier and reduced length of stay relative to expected, without a significant change in readmissions (Wertheimer et al., 2014).

The Plan

The plan includes a daily bed huddle at 8:30 a.m. using a live capacity dashboard, identification the evening before of patients likely to leave the next day, early pharmacy and transport scheduling for those patients and a staffed discharge lounge that frees each bed while the departing patient's family is on the way.

Measuring Success

The dashboard will track the share of discharges before noon, median boarding time, the share of patients boarding more than 12 hours, length of stay and 30-day readmissions. Results will be reviewed weekly by the operations team and monthly by executives.

Why the Bed Addition Looked Right

The bed addition was not a foolish idea. Anyone walking through the emergency department at 6 p.m. saw admitted patients on stretchers in hallways, and the inpatient units reported that they were full. Both observations were accurate at that hour. What neither side could see without data was the daily cycle: beds that were full in the evening had been occupied by patients who were medically ready to leave that morning but did not go until afternoon because of late rounds, waits for medications and rides and discharge paperwork completed at the end of the day. Only timestamps across a year of admissions revealed that pattern.

The People Behind the Data

Informatics also depends on people. The analyst who built the extract knew which fields nurses actually used and which were left blank. The nurse managers explained why beds sat clean but unassigned for an hour after a patient left. The hospitalists described why discharge orders were written after noon. The vice president learned that data rarely speak for themselves; the analysis became persuasive only when the people who created the data helped interpret it.

Limits of the Data

The data cannot show everything. Timestamps record when a nurse clicked, not always when an event happened. The data do not capture why a discharge was late, which requires talking with physicians and nurses. And the analysis covers one year; seasonal influenza surges may change the picture.

Informatics as Strategy

The boarding example shows why informatics belongs in strategy, not only in the information technology department. The same records support decisions on staffing, service lines, quality and contracts. Administrators who know what data exist, how reliable they are and what questions to ask can make better decisions about capital, operations and care.

Conclusion

The hospital already held the answer to its boarding problem in timestamps nobody had read. Informatics, turning those data into information, knowledge and a decision, redirected a $19 million construction debate toward a strategy for earlier discharges supported by research. That is the administrator's use of informatics: not buying technology, but asking the right question of the data the organization already has.

References

Jha, A. K., DesRoches, C. M., Campbell, E. G., Donelan, K., Rao, S. R., Ferris, T. G., Shields, A., Rosenbaum, S., & Blumenthal, D. (2009). Use of electronic health records in U.S. hospitals. New England Journal of Medicine, 360(16), 1628-1638. https://doi.org/10.1056/NEJMsa0900592

Singer, A. J., Thode, H. C., Jr., Viccellio, P., & Pines, J. M. (2011). The association between length of emergency department boarding and mortality. Academic Emergency Medicine, 18(12), 1324-1329. https://doi.org/10.1111/j.1553-2712.2011.01236.x

Wertheimer, B., Jacobs, R. E. A., Bailey, M., Holstein, S., Chatfield, S., Ohta, B., Horrocks, A., & Hochman, K. (2014). Discharge before noon: An achievable hospital goal. Journal of Hospital Medicine, 9(4), 210-214. https://doi.org/10.1002/jhm.2154