Risk of Hospitalization Due to Medication Nonadherence Identified Through EMRs of Patients With Psychosis

Data were collected from records created between May 1, 2013, and April 30, 2015. Patients included in the study were enrolled in the clinics as of April 30, 2015; were age 13 or older; and had a diagnosis of a primary psychotic disorder. Participants provided informed consent in a procedure approved by the Johns Hopkins University School of Medicine Institutional Review Board. Patients were excluded if they had a diagnosis of intellectual disability and were therefore unable to provide informed consent.

The study included patients from two clinics that focus on patients with psychosis at a major university hospital with a centralized EMR. All patients in these clinics had been assigned a psychiatrist and a master’s-level therapist. Diagnoses were made by the patients’ psychiatrist through a formal clinical interview using DSM-IV-TR criteria. Therapists provided demographic information (sex, race-ethnicity, and age). Records were reviewed by one of the authors (CA) to assess all other variables. Hospital discharge summaries and therapists’ intake notes were used to determine duration of illness and number of hospitalizations prior to the observation period. Treatment in the clinic preceded EMR implementation (May 1, 2013) for 23 patients (31%) in the final sample of 75. In these cases, paper charts were reviewed to obtain hospitalization history. Monthly variables (LAI antipsychotic use, psychiatric rehabilitation program attendance, substance use, and medication nonadherence) were assessed exclusively with data from EMRs.

Hospitalizations of clinic patients were recorded beginning in May 2013 for patients enrolled in the clinic prior to EMR implementation and 30 days after enrollment for patients initiating treatment after this date. The 30-day lapse accounted for patients who were enrolled during an acute phase of illness and thus rapidly hospitalized without significant treatment in one of the clinics. Data on medication nonadherence and substance use were collected for each patient from his or her therapist’s first appointment note of each month. Therapists’ notes include fields for medication adherence and substance use, which are assessed at every visit. For the purpose of data collection, when the response in these fields was not “yes” or “no” (for example, “questionable”), “nonadherent” was assumed for medication adherence, and “yes” was assumed for substance use.

The free text of the appointment note was also reviewed for further mention of medication nonadherence and substance use. For patients who had an appointment only with a physician in a given month, the physician’s note was reviewed in lieu of the therapist’s note. For patients using LAI antipsychotics who had neither a therapist’s note nor a physician’s note of medication adherence, notes from injection appointments were reviewed to determine whether patients were adherent to medication injections. Medical records were also searched for the presence of notes from psychiatric rehabilitation program staff to indicate program attendance. Data were not collected for months in which patients did not attend any appointments, including months during which they were hospitalized continuously.

We analyzed whether medication nonadherence, substance use, participation in psychiatric rehabilitation, and LAI medication use in any given month were associated with the risk of hospitalization in the subsequent month by using generalized estimating equations (GEEs) with logarithmic link and binomial distribution of residuals—that is, relative risk regression. GEEs correct for the repeated measures of multiple months per individual. In addition to the unadjusted models, multivariable models adjusted for the number of prior hospitalizations and time since onset of illness.

Ninety-eight patients were enrolled in the clinic as of April 30, 2015, and were thus potentially eligible for participation in the study. Of these, 75 (77%) consented to participate, ten (10%) refused, two (2%) had not been enrolled in the clinic for over 30 days, two (2%) had diagnoses of intellectual disability, two (2%) were judged by their clinicians to be too symptomatic to consent, three (3%) did not have a primary psychotic disorder, and four (4%) were not asked to consent for other reasons at their clinicians’ discretion.

The ages of the 75 participants ranged from 13.6 to 59.0 (mean±SD=29.1±11.9), and 80% (N=60) were male. Most patients were African American (N=44, 59%), followed by non-Hispanic white (N=22, 29%), Asian (N=3, 4%), Hawaiian/Pacific Islander (N=1, 1%), and multiracial (N=2, 3%); three (4%) did not identify as one of these categories. Diagnoses included schizophrenia (N=42, 56%), schizoaffective disorder (N=17, 23%), psychotic disorder not otherwise specified (N=7, 9%), affective disorder with psychotic features (N=6, 8%), and other psychotic disorders (N=3, 4%).

The 75 patients contributed 1,118 months of observation, with a mean length of observation of 14±8 months. In collecting data on medication adherence and substance use, a physician’s note was used for five of the 1,118 months; therapists’ notes were used for all other months. Of 19 instances of LAI nonadherence, 15 (79%) were due to missed injections—that is, injections that were received seven or more days after they were due. In the other four instances (21%), injections were received six or fewer days after they were due and were thus considered late. During the observation period, 19 of the 75 patients (25%) were hospitalized (33 hospitalizations). Hospitalization was not significantly associated with psychiatric rehabilitation program attendance, substance use, or LAI antipsychotic use in the preceding month. However, medication nonadherence was associated with increased risk of hospitalization in the following month (adjusted relative risk=7.19) (Table 1).

Our data confirm previous findings that medication nonadherence is a major factor in the risk of hospitalization for patients with psychotic disorders. Assessing medication nonadherence, however, remains a difficult task. Our results show that assessment and recording of medication adherence by using EMRs is feasible and clinically useful for detecting changes in risk of future hospitalization, despite evidence that physicians tend to overestimate adherence (12).

A strength of our study—with important implications for application of our findings—was that the vast majority of adherence data were gathered by therapists and that this information was collected at every therapy appointment, which prevented missing data. Patients may be more willing to reveal medication nonadherence to nonphysician providers (13), and in many settings, therapists see patients more frequently than do psychiatrists or other prescribers. Although we make no claim that we completely captured all instances of nonadherence, an additional strength of our study is that assessment of adherence was within the scope of routine practice. In addition, we used a standard EMR system that can be employed in any type of clinic, although our clinics are affiliated with a large medical institution. Furthermore, even though nonadherence was strongly associated with hospitalization, it is possible that other, more proximal factors resulted in both nonadherence and subsequent hospitalization. Nevertheless, EMR recording of medication nonadherence may alert the provider to an elevated risk of hospitalization. In addition, because patients were not randomly assigned to participation in a psychiatric rehabilitation program or to LAI medication use, this study could not examine the utility of these measures in preventing hospitalization.

The widespread implementation of EMR systems provides an opportunity to improve clinical practice and facilitate research. Our results demonstrate that EMR data may be used for research designed to answer questions of direct clinical relevance to a specific patient population or in a single clinic of modest size. Our results also suggest the utility of EMRs in achieving the goal of personalized psychiatric treatment, in this case by automated tracking of medication nonadherence to identify patients at risk of hospitalization. Patients thus identified may be appropriate targets for more intensive outpatient care, with specific attention to changes that may improve adherence.

Currently, assessment of medication adherence by using EMR data primarily focuses on the relationship between electronic prescriptions and subsequent filling of prescriptions—the medication possession ratio (14). This methodology does not capture missed doses, a shortcoming that may be particularly problematic in studies of patients with psychotic disorders, compared with studies of patients with other chronic conditions. Collection of EMR medication adherence data from provider notes could supplement and enhance pharmacy data, improve outcomes, and reduce costs significantly in this patient population.

The authors thank Constantine Lyketsos, M.D., M.H.S., and the Department of Psychiatry and Behavioral Sciences at Johns Hopkins University School of Medicine for their support of this report.