Effective Patient Teaching to Reduce Readmission Rates

Introduction

Chronic conditions such as diabetes and COPD account for the high 30-day readmission rates in US hospitals. The readmissions have implications for care quality and cost. However, evidence-based interventions have been shown to reduce up to 50% of potentially avoidable readmissions (Basu, Avila & Ricciardi, 2016). Patient education during hospitalization could impart self-care knowledge to reduce 30-day readmission rates. This paper reviews a primary study examining the effect of effective teaching using teach-back as an intervention to reduce patient readmission rates and improve medication adherence.

Research Question

The study examined the following main research question: Are there differences (a) between the usual care and intervention groups and (b) between the patient-centered intervention group and the intervention group that received motivational interviewing in medication adherence, hospital readmissions at 30 days after hospital discharge, patients’ perceptions of therapeutic alliance and confidence/importance for medication adherence?” (Hyrkas & Wiggins, 2014, p. 352)

Research Design

The study involved a prospective, longitudinal design. Data collection from non-randomized convenience samples was done for four months for the control arm and 19 months for the intervention arm (Hyrkas & Wiggins, 2014). Additional data were collected from a non-random sample nested in the treatment group that received motivational interviewing.

Sample/Population of the Study

A convenience sample was drawn from adult patients (study population) admitted to a 600-bed hospital in the Midwestern USA. The subjects were inpatients either in surgical or medical units for patients with chronic conditions. Inpatients in all the facility’s geriatric units participated in the study except one (Hyrkas & Wiggins, 2014). The sample size was 303 adult inpatients. Only adult patients (>18 years), recipients of treatment regimens, inpatients in the facility’s units, and literate English speakers were sampled. The ownership of a phone for a post-discharge follow-up was also a requirement for inclusion. Inpatients under new regimens, subjects in other clinical trials, and mentally ill patients were excluded from the study.

The sample size of 303 subjects was adequate. According to Aberson (2010), a “medium effect size” (α = 0.05 and Ӽ2 = 0.3) that takes into account a “10% dropout rate” would yield an appropriate sample size (p. 56). The researchers note that the 300 subjects could yield a medium effect size and cover for potential dropouts in this longitudinal study.

Data Collection Methods

Baseline data were collected for the two arms before the subjects were discharged. The subjects were required to return completed surveys to the study’s project manager. Telephone calls were used to collect follow-up data on medical adherence 2-3 days and 30 days after discharge. The project manager also collected post-discharge readmission data for 30 days through online notifications.

Four tools were used in data collection. The first set of instruments was the “Discharge Survey (DS) and Post-Discharge Survey (PDS)” (Hyrkas & Wiggins, 2014, p. 355). The DS captured the subjects’ data while the PDS recorded their medication adherence 3 days and 30 days after discharge. The other tools included the self-reported medication screening scale and Kim Alliance Scale (4-point Likert scale) for measuring the patient’s perceptions and patient-nurse relationships, respectively. A patient experience scale (7-point Likert scale) was used to measure the motivational interviewing outcomes for the nested treatment group.

Limitations

The study’s non-randomized design could have limited the variability of the sample subjects. Only English speaking inpatients in the facility were sampled into the control and intervention groups. Although this approach allowed for a comparison of the standard care and the intervention (standard care plus teach-back), the lack of subject variability may limit the generalisability of the study findings. Subsequent studies should use a random sample of inpatients from multiple hospitals to enhance the external validity of the findings.

The convenience sampling approach used also limited the study’s external validity. The sampling variance may not be a good estimate of variability at the population level for convenience samples. A simple random sampling technique would yield reliable data for estimating population parameters. Hyrkas and Wiggins (2014) reveal that the study continued beyond the scheduled timeline due to the failure to recruit the computed sample of 303. Only 97 subjects participated in the intervention arm, representing 24.3% of the expected sample (n = 205). Thus, the diminished sample size might cause Type II error. Future studies should recruit a larger sample to cater to potential dropout effects.

Findings

In this study, 10% of the intervention subjects were readmitted within 30 days after discharge. The study found that the difference in medication adherence and readmission rates between the two arms was not statistically significant (p = 0.001). However, there was a strong correlation between motivational interviewing and reduced readmission rate (β = – 1.55). The findings indicate that the teach-back method combined with motivational interviewing (MI) could lead to better post-discharge outcomes.

The answer to the study’s research question based on these findings is that there is no significant difference between standard care and treatment (teach-back) in terms of adherence and readmissions. However, teach-back coupled with motivational interviewing could lower readmission rates significantly. The approach reinforces the “patient’s perceptions of therapeutic alliance and confidence”, which enhances medication adherence, leading to fewer readmissions (Hyrkas & Wiggins, 2014, p. 357).

Summary of Article

The study compared medical compliance and readmissions in inpatients receiving standard care versus teach-back and teach-back coupled with motivational interviewing. It is grounded in the finding that patient-centered interventions lead to positive patient outcomes.

The study involved a convenient sample of 303 subjects (adult inpatients) with chronic conditions, including diabetes. Subsequently, 98 subjects received standard care (control group) while 205 received teach-back interventions (T1). A subset of the treatment group (n = 137) underwent a teach-back intervention conducted by trained clinicians while the remainder (n = 68) received teach-back plus MI (T2).

Post-discharge data collection was done at 3 days and 30 days after discharge using specific instruments. The study found no significant difference between the control group and T1 about regimen compliance and readmissions. However, the T2 group reported higher confidence in medical compliance than the control group. Furthermore, MI was found to lower readmission rates.

The findings show that the teach-back method could improve post-discharge patient outcomes as an adjunct to other patient-centered strategies. In this study, the technique is effective when combined with MI, which is essentially a counseling method. The evidence drawn from these findings is not strong enough to support the use of the teach-back method as a stand-alone intervention for reducing readmission rates.

A randomized controlled trial could give compelling (Level 1) evidence for the use of this intervention. Nevertheless, the technique could be useful in educating diabetic or COPD patients about medication dosage and side effects before being discharged. The rationale for this response is that the teach-back method may not guarantee that the patient will comply with the instructions, medications, or recommended dosage levels after leaving the hospital. Follow-up interventions may be required to bolster adherence and reduce 30-day readmissions.

References

Aberson, C.L. (2010). Applied Power Analysis for the Behavioral Sciences. New York, NY: Routledge.

Basu, J., Avila, R. & Ricciardi, R. (2016). Hospital Readmission Rates in U.S. States: Are Readmissions Higher Where More Patients with Multiple Chronic Conditions Cluster?. Health Service Research, 51(3), 1135-1151.

Hyrkas, K. & Wiggins, M. (2014). A Comparison of Usual Care, a Patient-centred Education Intervention and Motivational Interviewing to Improve Medication Adherence and Readmissions of Adults in an Acute-care Setting. Journal of Nursing Management, 22, 350–361. Web.

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