N538 Module 6 assignment: quality and meaningful use paper on an electronic clinical quality measure, a full sample

From the Discharge Medication List to a Reported Rate: The Safe Use of Opioids Measure as an Informatics Problem

Student Name

Master of Science in Nursing Program, Aspen University

N538: Advanced Health Care Informatics

Instructor Name

Month Day, Year

From the Discharge Medication List to a Reported Rate: The Safe Use of Opioids Measure as an Informatics Problem

Meaningful use began in 2011 as a federal program that paid hospitals and clinicians to adopt certified electronic health records and use them in specified ways. Its successor for hospitals, the Medicare Promoting Interoperability program, still ties payment to how the EHR is used, and one of its requirements is the electronic reporting of clinical quality measures calculated directly from EHR data. That shift changes the nurse's relationship to quality. When a measure is calculated by software from structured fields, what is documented, and where, becomes the quality result.

This paper follows one electronic clinical quality measure, Safe Use of Opioids: Concurrent Prescribing, from the clinical problem it addresses to the data elements it uses, the ways those data can mislead, and the documentation and workflow changes that would improve both the care and the reported rate at a composite 280-bed hospital.

The Clinical Problem Behind the Measure

Opioids and benzodiazepines both depress breathing, and together they raise the risk of overdose. In claims data for 315,428 privately insured adults who filled an opioid prescription between 2001 and 2013, Sun et al. (2017) found that the share of opioid users who also used a benzodiazepine rose from 9% to 17%. Concurrent use was associated with a higher risk of an emergency visit or admission for opioid overdose, and the authors estimated that, if the association were causal, eliminating concurrent use could cut that risk in the population by about 15%.

Clinical guidance followed the evidence. The 2022 federal guideline on opioid prescribing for pain advises clinicians to use particular caution when prescribing opioids and benzodiazepines together and to weigh whether the benefits outweigh the risks of combining them (Dowell et al., 2022). A hospital discharge is a natural checkpoint for that caution, because patients often leave with new prescriptions added to the medications they already took at home.

How the Measure Is Built

The measure (Centers for Medicare & Medicaid Services [CMS], 2024) reports the proportion of inpatient hospitalizations for adults in which the patient is prescribed, or continued on, two or more opioids, or an opioid and a benzodiazepine, at discharge. The denominator is hospitalizations of patients 18 and older who leave with an opioid or benzodiazepine on the discharge medication list. The numerator is the subset with the concurrent combination. Exclusions remove patients for whom concurrent prescribing may be appropriate, among them patients with cancer and those receiving palliative or hospice care. A lower rate is better.

Every element is drawn from structured EHR data. The discharge medications come from the reconciled discharge medication list, the diagnoses that exclude a patient come from coded problem and encounter diagnoses, and palliative or hospice care must appear as a coded order, encounter or intervention. Nothing a clinician writes in a free-text note is read. For the composite hospital, which reported a rate of 14% last year, that fact is the starting point of the analysis: some of those hospitalizations reflect real concurrent prescribing, and some reflect data that did not say what the clinicians knew.

Where Electronic Measures Go Wrong

Electronic measures promise complete, timely data without manual chart review, but their accuracy depends on documentation. An early review of the literature by Chan et al. (2010) concluded that EHR-based quality measures were limited by missing and inconsistently recorded data, and that the validity of a measure could differ markedly from one data element to the next. More recent evidence shows the same pattern at scale. Comparing electronic and manually abstracted results for two perinatal measures across U.S. hospitals, Schmaltz et al. (2022) found near-perfect agreement for exclusive breast milk feeding but poor agreement on the numerator for elective delivery, largely because the electronic data failed to capture gestational age, active labor and the conditions that justify an early delivery.

The lesson transfers directly. An electronic measure is as accurate as its least reliable data element. For the opioid measure at the composite hospital, a quality review of 40 numerator cases identified three kinds of error. In several, a home benzodiazepine the patient had stopped during the admission stayed on the discharge list because reconciliation carried it forward. In others, a patient receiving palliative care had no coded palliative order, only a consult note, so the exclusion never fired. In a few, two opioid entries were a scheduled dose and an as-needed dose of the same drug that the prescriber had meant as one regimen. Only the remaining cases represented deliberate concurrent prescribing.

What Nursing Documentation and Workflow Can Change

Three changes follow from the review, and nurses are central to two of them. First, medication reconciliation at discharge should require an explicit decision on every home medication, continue, change or stop, rather than defaulting to continue. Nurses often perform the discharge teaching that reveals a medication the patient no longer takes, and a structured field for the nurse to flag a discrepancy to the prescriber would catch stopped benzodiazepines before the list is finalized.

Second, palliative and hospice care should be captured as coded data at the time the decision is made. When the palliative team or the admitting clinician documents goals of care, an order or a coded encounter should accompany the note, so the exclusion reflects reality. Nurses who coordinate goals-of-care conversations can prompt that step. Third, when an opioid and a benzodiazepine are both on the discharge list for a patient who is not excluded, the EHR should display an interruptive advisory to the prescriber with the option to reduce, taper or document a reason, and to prescribe naloxone. That advisory changes care, not only the rate.

Evaluating the Result

The hospital should track the reported measure rate quarterly and, alongside it, the three error types from the case review, re-audited on a sample of 40 numerator cases each quarter. If the rate falls because documentation errors disappear while deliberate concurrent prescribing is unchanged, the data have become more truthful but care has not changed, and the advisory's effect needs attention. A realistic first-year target is a rate below 9% with fewer than one in ten audited numerator cases caused by documentation error. Naloxone prescribing for patients who remain on both drugs is a useful balancing measure, since the goal is safer prescribing rather than a lower number for its own sake.

Conclusion

Meaningful use and its successor programs made quality reporting an informatics task. The Safe Use of Opioids measure addresses a real risk, and because it is calculated entirely from structured EHR data, its result depends on reconciliation decisions, coded exclusions and the design of prescribing advice at discharge. Nurses influence each of these. When the informatics nurse treats the measure as a data pipeline to be understood and improved, the hospital gains both a more accurate number and fewer patients who go home with a dangerous combination they did not need.

References

Centers for Medicare & Medicaid Services. (2024). Safe use of opioids: Concurrent prescribing (CMS506) [Electronic clinical quality measure specification]. eCQI Resource Center. https://ecqi.healthit.gov/ecqm/eh/2024/cms0506v6

Chan, K. S., Fowles, J. B., & Weiner, J. P. (2010). Electronic health records and the reliability and validity of quality measures: A review of the literature. Medical Care Research and Review, 67(5), 503-527. https://doi.org/10.1177/1077558709359007

Dowell, D., Ragan, K. R., Jones, C. M., Baldwin, G. T., & Chou, R. (2022). CDC clinical practice guideline for prescribing opioids for pain: United States, 2022. MMWR Recommendations and Reports, 71(3), 1-95. https://doi.org/10.15585/mmwr.rr7103a1

Schmaltz, S., Vaughn, J., & Elliott, T. (2022). Comparison of electronic versus manual abstraction for 2 standardized perinatal care measures. Journal of the American Medical Informatics Association, 29(5), 789-797. https://doi.org/10.1093/jamia/ocab276

Sun, E. C., Dixit, A., Humphreys, K., Darnall, B. D., Baker, L. C., & Mackey, S. (2017). Association between concurrent use of prescription opioids and benzodiazepines and overdose: Retrospective analysis. BMJ, 356, Article j760. https://doi.org/10.1136/bmj.j760