Adverse drug events in elderly patients receiving home health services following hospital discharge

OBJECTIVE

To assess incidence, healthcare consequences, and identify risk factors for adverse drug events (ADEs) in elderly patients receiving home health services during the month following hospital discharge.

METHOD

This was a prospective cohort study of three home health agencies in Madison, Wisconsin, and its surrounding area. The sample consisted of 256 participants aged > or =65 years who were hospitalized for medical illness, received home nursing after discharge, and completed the one-month interview. The main outcome measure was self-reported ADEs (possible, probable, or definite) during the month following hospital discharge.

RESULTS

Incidence of ADEs was 20%. Fifty-two participants (20.3%) reported 64 ADEs: 23 possible, 37 probable, and four definite. The most common ADEs involved the gastrointestinal tract (31.3%) and the central nervous system (31.3%). Of 53 ADEs reported to providers, 59% of the drugs were discontinued or altered. One ADE resulted in hospitalization. In logistic regression, female gender (OR = 2.26; 95% CI 1.06 to 4.77) and the interaction between number of new medications and cognition were significantly associated with ADEs. The risk of an event increased with the number of new medications at discharge; however, risk was elevated primarily for participants with lower cognition.

CONCLUSIONS

ADEs were common during the month following hospital discharge, were more frequent in women, and often resulted in medication changes. Individuals at particular risk were those with lower cognition who were discharged with several new medications.

The medical cost of undiagnosed sleep apnea

Obstructive sleep apnea is an under-diagnosed, but common disorder with serious adverse consequences. Cost data from the year prior to the diagnosis of sleep-disordered breathing in a consecutive series of 238 cases were used to estimate the potential medical cost of undiagnosed sleep apnea and to determine the relationship between the severity of sleep-disordered breathing and the magnitude of medical costs. Among cases, mean annual medical cost prior to diagnosis was $2720 versus $1384 for age and gender matched controls (p<0.01). Regression analysis showed that the reciprocal of the apnea hypopnea index among cases was significantly related to log-transformed annual medical costs after adjusting for age, gender, and body mass index (p<0.05). We conclude that patients with undiagnosed sleep apnea had considerably higher medical costs than age and sex matched individuals and that the severity of sleep-disordered breathing was associated with the magnitude of medical costs. Using available data on the prevalence of undiagnosed moderate to severe sleep apnea in middle-aged adults, we estimate that untreated sleep apnea may cause $3.4 billion in additional medical costs in the U.S. Whether medical cost savings occur with treatment of sleep apnea remains to be determined.

Modeling risk using generalized linear models

Traditionally, linear regression has been the technique of choice for predicting medical risk. This paper presents a new approach to modeling the second part of two-part models utilizing extensions of the generalized linear model. The primary method of estimation for this model is maximum likelihood. This method as well as the generalizations quasi-likelihood and extended quasi-likelihood are discussed. An example using medical expense data from Washington State employees is used to illustrate the methods. The model includes demographic variables as well as an Ambulatory. Care Group variable to account for prior health status.