The impact of hospital-based post-discharge pharmacist medication review on patient clinical outcomes: A systematic review

Background

Clinical pharmacists have been shown to identify and resolve medication related problems post-discharge, however the impact on patient clinical outcomes is unclear.

Aims

To undertake a systematic review to identify, critically appraise and present the evidence on post-discharge hospital clinics that provide clinical pharmacist medication review; report the patient clinical outcomes measured; and describe the activities of the clinical pharmacist.

Methods

Published studies evaluating a patient clinical outcome following a post-discharge hospital clinic pharmacy service were included. All studies needed a comparative design (intervention vs control or comparator). Pubmed, Embase, CINAHL, PsycnINFO, Web of Science, IPA and APAIS-Health databases were searched to identify studies. The type of clinic and the clinical pharmacist activities were linked to patient clinical outcomes.

Results

Fifty-seven studies were included in the final analysis, 14 randomised controlled trials and 43 non-randomised studies. Three key clinic types were identified: post-discharge pharmacist review alone, inpatient care plus post-discharge review and post-discharge collaborative clinics. The three main outcome metrics identified were hospital readmission and/or representation, adverse events and improved disease state metrics. There was often a mix of these outcomes reported as primary and secondary outcomes. High heterogeneity of interventions and clinical pharmacist activities reported meant it was difficult to link clinical pharmacist activities with the outcomes reported.

Conclusions

A post-discharge clinic pharmacist may improve patient clinical outcomes such as hospital readmission and representation rates. Future research needs to provide a clearer description of the clinical pharmacist activities provided in both arms of comparative studies.

The Effect of the Drug-Related Problems Prevention Bundle on Early Readmissions in Patients From the Emergency Department: A Randomized Clinical Trial

BACKGROUND

Drug-related problems (DRPs) are prevalent and avoidable disease that patients experience due to drug use or nonuse. However, secondary prevention policies have not yet been systematized.

OBJECTIVE

To assess the clinical impact of a secondary prevention bundle for DRPs in patients who visited the emergency department (ED) for medicine-related problems.

METHODS

A single-center randomized clinical trial was conducted from August 28, 2019, to January 28, 2021, with 1-month follow-up. We included 769 adult patients who visited ED with a DRP associated with cardiovascular, alimentary tract, and metabolic system medications. For the intervention group, a DRP prevention bundle, consisting of a combined strategy initiated in the ED was applied. Patients in the control group received standard pharmaceutical care. Intervention was evaluated in terms of 30-day hospital readmission due to any cause.

RESULTS

Final analysis included 769 patients, of which 68 (8.8%) were readmitted within 30 days (control group, 40 of 386 [cumulative incidence: 10.4%]; intervention group, 28 of 383 [cumulative incidence, 7.3%]). After adjustment of the model for chronic heart failure, there was a lower incidence of hospital readmission among patients in the intervention group compared with those in the control group, odds ratio: 0.59 [95% confidence interval: 0.37-0.97]; number needed to treat (NNT) = 32. No significant differences in other outcomes were observed.

CONCLUSION AND RELEVANCE

In this clinical trial, DRP prevention bundle in adjusted analysis decreased the rate of 30-day hospital readmission for any cause in patients who visited ED for a DRP.

TRIAL REGISTRATION

ClinicalTrials.gov (Identifier: NCT03607097).

SPUR: A Patient-Reported Medication Adherence Model as a Predictor of Admission and Early Readmission in Patients Living with Type 2 Diabetes

PURPOSE

Poor medication adherence (MA) is linked to an increased likelihood of hospital admission. Early interventions to address MA may reduce this risk and associated health-care costs. This study aimed to evaluate a holistic Patient Reported Outcome Measure (PROM) of MA, known as SPUR, as a predictor of general admission and early readmission in patients living with Type 2 Diabetes.

PATIENTS AND METHODS

An observational study design was used to assess data collected over a 12-month period including 6-month retrospective and 6-month prospective monitoring of the number of admissions and early readmissions (admissions occurring within 30 days of discharge) across the cohort. Patients (n = 200) were recruited from a large South London NHS Trust. Covariates of interest included: age, ethnicity, gender, level of education, income, the number of medicines and medical conditions, and a Covid-19 diagnosis. A Poisson or negative binomial model was employed for count outcomes, with the exponentiated coefficient indicating incident ratios (IR) [95% CI]. For binary outcomes (Coefficient, [95% CI]), a logistic regression model was developed.

RESULTS

Higher SPUR scores (increased adherence) were significantly associated with a lower number of admissions (IR = 0.98, [0.96, 1.00]). The number of medical conditions (IR = 1.07, [1.01, 1.13]), age ≥80 years (IR = 5.18, [1.01, 26.55]), a positive Covid-19 diagnosis during follow-up (IR = 1.83, [1.11, 3.02]) and GCSE education (IR = 2.11, [1.15,3.87]) were factors associated with a greater risk of admission. When modelled as a binary variable, only the SPUR score (-0.051, [-0.094, -0.007]) was significantly predictive of an early readmission, with patients reporting higher SPUR scores being less likely to experience an early readmission.

CONCLUSION

Higher levels of MA, as determined by SPUR, were significantly associated with a lower risk of general admissions and early readmissions among patients living with Type 2 Diabetes.

Accuracy of the Simplified HOSPITAL Score to Predict Nonelective Readmission in a Brazilian Tertiary Care Public Teaching Hospital

BACKGROUND AND OBJECTIVES

Predictive models to identify patients at high risk of readmission have gained the attention of health care teams, which have focused the strategies to reduce unnecessary readmissions on the "at-risk" patients. The HOSPITAL score includes 7 predictor variables with a C-statistic of 0.70 or more when applied to international datasets. Its simplified version retains a C-statistic at around the same level, but only incipient external validation has been attempted to date. The primary objective of this study was to evaluate the prognostic accuracy of the simplified HOSPITAL score to predict nonelective hospital readmissions in a tertiary care public teaching hospital in Brazil.

METHODS

We used a retrospective cohort that included all patients discharged from the internal medicine service of a Brazilian tertiary care public teaching hospital in 2018. We excluded patients who died before index discharge, were transferred to another institution, left against medical advice, or were readmitted electively. We calculated the simplified HOSPITAL score for each admission, and admissions were divided into low (0-4 points) or high risk (≥ 5 points) of nonelective 30-day readmission. We estimated accuracy, area under the receiver operating characteristic curve (AUC), and observed/expected (O/E) readmission ratio; the latter using the mid-P exact test with Miettinen's modification at a 95% confidence interval (CI). A P value < .05 was considered significant.

RESULTS

A total of 4472 hospital discharges were analyzed during the study period after application of the exclusion criteria. The nonelective 30-day readmission rate was 14.0% (n = 625). Of all patients discharged, 3173 (71.0%) were considered to be at low risk and 1299 (29.0%) at high risk of readmission according to the simplified HOSPITAL score. The AUC was 0.68 (95% CI: 0.66-0.71; P < .001). The nonelective 30-day readmission rate was 9.2% in the low-risk group (expected: 9.2%; O/E: 1.0 [95% CI: 0.89-1.12]) and 25.7% in the high-risk group (expected: 27.2%; O/E: 0.95 [95% CI: 0.85-1.05]) ( P < .001). At a cut-off of 5 points, the score had a sensitivity of 53.4%, specificity of 74.9%, positive predictive value of 25.7%, and negative predictive value (NPV) of 90.8%.

CONCLUSIONS

The parameters of the score were almost identical to the original study, with better applicability to exclude low-risk patients given its high NPV. Additional adjustments are still needed for better applicability in daily clinical practice.

Implementation of the Patient Counselling Service at the Cancer Hospital in Radom, Poland

Background: Non-adherence occurs in various groups of patients, including those with chronic diseases. One strategy to increase adherence among oncological patients is to individualise treatment and expand pharmaceutical care. Pharmaceutical labels that remind patients how they should take their medications are of great importance in this respect. Objective: The main objective of this study was to evaluate medication adherence in oncological patients, and to gather their opinions on the individual medication labelling system as an element of effective treatment. Methods: The study was conducted in 2021 among 82 patients of the oncological department of the Centre of Oncology in Radom. The research tool was a questionnaire consisting of personal data and two parts relating to the patient's disease and the medication labelling system. Results: Nearly half of the respondents reported that they forget to take medications and how they should take them. These problems increased with the age of the patient and the number of administered medications. Of the respondents, 89% stated that the labels with dosing information are helpful. Over 67% agreed that these labels should be affixed to all medications. Nearly 90% of the respondents believed the labels should be available in all pharmacies. Conclusions: Non-adherence is a common phenomenon among oncological patients. Pharmacists providing a labelling service for medicinal products can play a significant role in reducing this phenomenon.

Assessing the impact of adding pharmacist management services to an existing discharge planning program on 30-day readmissions

BACKGROUND

Although hospital readmission rates are declining nationally, avoidable readmissions remain a public health concern. Effective readmission interventions are multifaceted and include discharge planning and transition-of-care coordination. Clinical pharmacists are effective contributors to these processes, bringing expertise to discharge counseling, medication reconciliation, medication adherence, and postdischarge follow-up counseling.

OBJECTIVE

We evaluated the impact of adding health plan clinical pharmacy management services to an existing discharge program on all-cause readmissions and postdischarge primary physician visits.

METHOD

Pharmacy management services by health plan clinical pharmacists of a large regional integrated delivery system were added to an existing optimal discharge planning (ODP) program. Criteria for eligibility for these pharmacists' services included patients who prescribed a new maintenance medication after discharge, received a therapeutic substitution, had a previous discharge within 30 days, or were taking a high-risk medication. A retrospective, observational analysis of a subgroup of patients, who received the pharmacy management services as part of ODP, was performed using a difference-in-difference model, by comparing propensity-matched discharges from February 22, 2016, to January 31, 2017 (preprogram implementation) with discharges from February 22, 2017, to January 31, 2018 (implementation period), to estimate changes in 30-day readmission rates and postdischarge primary physician visits.

RESULTS

A total of 111 of the propensity matched received the pharmacy management services; of these, 73% (ODP) versus 64% (non-ODP) were ≥ 58 years, 60% were females, and 62% (ODP) versus 52% (non-ODP) were Medicare beneficiaries. There was a 16.7% (P = 0.022) statistically significant reduction in combined inpatient and observation 30-day readmissions and a 19.7% increase in 5-day postdischarge follow-up physician visits (P = 0.037) for the subgroup who also received the pharmacy management services.

CONCLUSION

Addition of pharmacist management services to an existing hospital discharge program for select at-risk patients was associated with reduced inpatient and observation 30-day readmissions.

Stakeholder impact on the implementation of integrated care: Opportunities to consider for patient-centered outcomes research

Nearly half of Americans live with chronic disease. Many have multiple chronic conditions that often present as a combination of physical and mental health conditions. Aligning stakeholder-driven, patient-centered outcomes research with population health strategies such as innovative ways to deliver care management can reduce the burden of multiple chronic conditions. In addition, successfully creating meaningful, inclusive research requires actively engaging stakeholders throughout the lifecycle of a study. This study integrates stakeholder engagement, using a large health plan in western Pennsylvania, to conduct a randomized controlled trial. Three care management strategies, High-Touch, High-Tech, and Usual Care, are compared for effectiveness among members with multiple chronic conditions. Care strategies are delivered via the Community Team, a multidisciplinary community-based team, offering in-person (High-Touch) and digital (High-Tech) care management in 14 counties across Pennsylvania. Participants are followed for 12months, with repeated measurements of self-reported health status and activation in care, while tracking administrative measurements of primary and specialty health service utilization. Quality of life, care satisfaction, engagement in care, and service utilization will be compared using generalized mixed models. Additionally, semi-structured interviews are conducted for both participants and care managers over the course of the study to evaluate feasibility. This manuscript presents implementation strategies, while noting that the implementation of patient-centered outcomes research in a real-world setting requires rapid evaluation, redesign of workflow, and tailored approaches for success.

Hospital Readmission and Mortality in a Brazilian Tertiary Public Hospital

BACKGROUND AND OBJECTIVES

Data on mortality associated with hospital readmission are imprecise and highly variable. This study aimed to describe the rate of nonelective 30-day readmission and associated hospital mortality of patients discharged from the Internal Medicine Unit of a Brazilian tertiary public hospital.

METHODS

This retrospective cohort study included all patients discharged from the Internal Medicine Unit of our institution between September and November 2017 who were nonelectively readmitted within 30 days.

RESULTS

A total of 1047 hospital discharges were analyzed. The rate of nonelective 30-day readmission was 13.7%. Of these, 41 (28.5%) were early readmissions (0-7 days) and 103 (71.5%) were late readmissions (8-30 days). The hospital mortality rate during readmission was 27.8%, being significantly higher during early readmissions (41.5% vs 22.3%; P = .035). Early (as compared with late) readmission was associated with mortality during readmission (relative risk [RR] 1.95; 95% confidence interval, 1.18-3.22; P = .002), regardless of age and Charlson comorbidity index.

CONCLUSION

The Readmission rate was 13.7%, with an associated mortality of 27.8%. Early readmission was an independent predictor of mortality (RR 1.95) in relation to late readmission. Larger studies are needed to better identify this group of patients with an aim to adopt preventive measures.

Evaluating provider acceptance of pharmacist interventions in the Discharge Companion Program and its association with readmission reduction

OBJECTIVE

To evaluate provider acceptance of pharmacist interventions within the Discharge Companion Program (DCP) and its association with hospital readmissions.

METHODS

This retrospective record review included patients referred to the DCP between January and October 2018. DCP pharmacists' interventions were assessed for provider acceptance on follow-up consultation or readmission. A chi-square test assessed the association between provider acceptance, communication modality, and technology used. A logistic regression model assessed the association between readmission risk and variables of interest. An a priori alpha level of 0.05 was used.

RESULTS

Of the 197 patients referred to the DCP, 102 met inclusion criteria. DCP pharmacists made a total of 271 interventions; 185 (68.7%) required provider action. The most common intervention type was medication addition or discontinuation (n = 74, 40%); the communication mode was between DCP nurses and primary care provider offices or skilled nursing facilities (n = 56, 54.9%); and the preferred technology was the telephone (n = 58, 56.9%). Provider acceptance rate was 30.8% (n = 57) of actionable interventions, although it was not significantly associated with 30-day readmission reductions (P = 0.833) and did not differ significantly when interventions were communicated to other health care professionals (P = 0.53). The specific intervention communication mode (i.e., telephone, facsimile, or both) of pharmacist interventions did not significantly affect provider acceptance (P = 0.133). The overall readmission rate was 22.5% (n = 23), and the only significant predictor of 30-day readmission was the number of comorbidities (odds ratio 1.28 [95% CI 1.03-1.58], P = 0.024).

CONCLUSION

Provider acceptance of pharmacists' interventions did not significantly affect 30-day readmission rates, regardless of communication mode (telephone or facsimile) or technology used. However, the DCP successfully identified numerous medication-related problems. Further study is warranted regarding provider acceptance of pharmacist recommendations on 30-day readmission reduction.