Colleen M. Renier

Maximizing medication therapy management services through a referral initiative.

PURPOSE The implementation and effects of an initiative to refer patients to receive medication therapy management (MTM) services after hospital discharge are described. METHODS A check box to order an MTM appointment was added to the discharge medication order form printed for hospitalized patients in an integrated health system. Hospitalists were informed about MTM services and encouraged to refer hospitalized patients to the service who were at risk for adverse drug events or medication nonadherence. A retrospective case series review was conducted to evaluate documented MTM encounters, comparing the number of patients seen at the MTM practice for hospital follow-up during the four months before and after the initiatives implementation. Secondary endpoints included revenue generated by MTM encounters and the percentage of patients with documented drug therapy problems due to medication nonadherence. RESULTS A total of 313 encounters were included in the analysis (142 preimplementation and 171 postimplementation). The percentage of MTM hospital follow-up encounters significantly increased from the preimplementation period to the post-implementation period, from 30.28% (n = 43) to 63.74% (n = 109) (p < 0.001). After the referral initiative was implemented, MTM hospital follow-up encounters were more likely to reveal medication nonadherence, compared with regular office visits (odds ratio, 2.1; 95% confidence interval, 1.01-4.34; p = 0.039). CONCLUSION The implementation of an initiative to refer hospitalized patients to an MTM service in an integrated health system increased the percentage of recently discharged patients seen in an MTM practice; patients seen postimplementation were more likely to be nonadherent to their medication regimen.

Development and validation of a survey to assess patient-perceived medication knowledge and confidence in medication use.

Background and Purpose: The primary objective of this study is to establish the validity and reliability of a perceived medication knowledge and confidence survey instrument (Okere–Renier Survey). Methods: Two-stage psychometric analyses were conducted to assess reliability (Cronbach’s α >.70) of the associated knowledge scale. To evaluate the construct validity, exploratory and confirmatory factor analyses were performed. Results: Exploratory factor analysis (EFA) revealed three subscale measures and confirmatory factor analysis (CFA) indicated an acceptable fit to the data (goodness-of-fit index [GFI = 0.962], adjusted goodness-of-fit index [AGFI = 0.919], root mean square residual [RMR = 0.065], root mean square error of approximation [RMSEA] = 0.073). A high internal consistency with Cronbach’s α of .833 and .744 were observed in study Stages 1 and 2, respectively. Conclusions: The Okere–Renier Survey is a reliable instrument for predicting patient-perceived level of medication knowledge and confidence.

Predictors of Hospital Length of Stay and Readmissions in Ischemic Stroke Patients and the Impact of Inpatient Medication Management

OBJECTIVE This study was designed to evaluate predictors of hospital length of stay (LOS) and readmissions among nonsurgical ischemic stroke patient, and the impact of inpatient medication management. METHODS This retrospective cohort study includes adult patients (≥18 years) hospitalized with a diagnosis of nonsurgical ischemic stroke from November 2007 to March 2013. In November 2011, an inpatient medication management model was implemented in the stroke unit. At the end of the study period, patients were matched before and after implementation of the inpatient medication management model (non-PHC [pharmacist-hospitalist collaborative] and PHC, respectively) to evaluate change in outcomes. The primary outcome of the study is an evaluation of predictive factors affecting LOS and readmissions. Additionally, changes in LOS and all-cause readmission at 30, 60, and 90 days when compared between PHC and non-PHC were evaluated. FINDINGS A total of 151 PHC patients were matched to 248 non-PHC patients. There was no difference in LOS between the PHC and non-PHC patients (mean adjusted difference -.14; P = .66). Similar finding was observed for readmissions (P > .05). Insurance type was a significant predictor of LOS, with Medicare patients having an extended LOS compared to patients with private insurance (mean difference -1.00; P = .005). Patients taking statins and patients aged less than 80 years had a lower 30-day readmission rate compared to nonstatin users and patients aged 80 years or older, respectively (P < .05). CONCLUSIONS Insurance type and severity of illness are important predictors of LOS, whereas readmissions are mostly influenced by age and statin use.

Comparison of a pharmacist–hospitalist collaborative model of inpatient care with multidisciplinary rounds in achieving quality measures

PURPOSE Results of a study of hospitalization outcomes with the use of a pharmacist-hospitalist collaborative (PHC) model of care as an alternative to multidisciplinary rounds (MDR) are reported. METHODS In a retrospective matched-cohort study, data on more than 2000 adults discharged from two medical units of a community teaching hospital were analyzed to compare selected outcomes before and after the units augmented traditional hospitalist care (usual care) with either MDR or a PHC care model emphasizing pharmacist involvement in case review and medication management. The study cohorts were matched for primary diagnosis, severity of illness, and other variables. The outcomes were mean length of stay (LOS) and rates of all-cause readmission during designated preintervention and intervention periods. RESULTS Among patients admitted to the unit that implemented the PHC care model, those admitted during the preintervention period had a longer mean LOS than matched intervention-phase patients: 5.5 days (95% confidence interval [CI], 5.0-6.0 days) versus 4.7 days (95% CI, 4.2-5.3 days); p = 0.002. Patients admitted to the MDR unit during the preintervention period also had a significantly longer mean LOS than those in the matched intervention-phase cohort. There were no significant between-group differences in all-cause readmissions. CONCLUSION Systematic implementation of either the PHC or the MDR model of care was associated with a decreased mean hospital LOS relative to LOS values with usual care only. No significant differences in readmissions at 30, 60, and 90 days were attributable to implementation of the PHC or the MDR model.

Effects of Statins on Hospital Length of Stay and All-Cause Readmissions Among Hospitalized Patients With a Primary Diagnosis of Sepsis.

Background: There is little information on the impact of statins on hospital length of stay (LOS) or readmission among patients with sepsis. Objective: The objective of this study is to evaluate the association between statin use and LOS and all-cause readmissions among sepsis patients hospitalized in the medical unit. Methods: The design was a retrospective propensity score–matched study of adult patients with a primary diagnosis of sepsis from 2007 to 2013. Information was extracted from the electronic health record. Sepsis patients were identified using ICD-9CM codes. Propensity scores estimated the probability that a patient would be on statins, and patients who were on statins were then matched with those who were not, within ±0.05. Additional greedy matching criteria were organ dysfunction (yes/no) and all patient refined diagnosis-related group (APR-DRG) medical/surgical. The primary outcome was LOS, and the secondary outcomes were all-cause readmission at 30, 60, and 90 days, adjusted for age, sex, modified Deyo-Charlson comorbidity index, APR-DRG severity of illness (SOI), and APR-DRG medical/surgical, as appropriate. Results: Patients taking statins had a shorter LOS than patients not taking statins, 8.7 ± 3.7 and 10.3 ± 2.7 days, respectively (P value = 0.018). There was no significant difference (P> 0.05) in all cause readmissions between statin and nonstatin patients. Presence of comorbidities and SOI were significant factors for 60- and 90-day readmissions. Conclusions: The use of statins among patients admitted with primary sepsis in the medical unit was associated with shorter length of hospital stay. However, it did not affect frequency of readmissions.

Differences in breast tissue oxygenation following radiotherapy

Tissue perfusion and oxygenation changes following radiotherapy may result from and/or contribute to the toxicity of treatment. Breast tissue oxygenation levels were determined in the treated and non-treated breast 1 year after radiotherapy for breast conserving treatment. Transcutaneous oxygenation varied between subjects in both treated and non-treated breast. Subjects without diabetes mellitus (n=16) had an average oxygenation level of 64.8 ± 19.9mmHg in the irradiated breast and an average of 72.3 ± 18.1mmHg (p=0.018) at the corresponding location in the control breast. Patients with diabetes (n=4) showed a different oxygenation pattern, with lower oxygenation levels in control tissue and no decrease in the irradiated breast. This study suggests oxygenation levels in normal tissues vary between patients and may respond differently after radiotherapy.

CC4-04: An Application of Doubly Robust Estimation

Background/Aims Observational data often has treatment exposure confounded with baseline covariates. Doubly robust estimation utilizes both a regression model and an additional model for the exposure, often the propensity score, to estimate the causal effect of an exposure on an outcome. Methods In a study designed to evaluate change in hemoglobin (Hb) with use of angiotensin-converting enzyme inhibitors (ACEI) or angiotensin receptor blockers (ARB), in a primary care patient population, we found that receiving ARB vs. ACEI was associated with several of the baseline covariates. These baseline covariates, Hb, treatment start date, chronic kidney disease, congestive heart failure, diabetes mellitus, hypertension, sex, and age, initially thought to be informative in estimating follow-up (F/U) Hb, were chosen a priori. No medical explanation for the differential ordering of ACEI and ARB based on the level of these covariates was identified, so the treatment effect of ARB relative to ACEI is considered to be truly confounded. We therefore adopted the doubly robust semiparametric efficient estimator of Robins et al. (1994) in a causal analysis of the treatment effect of ARB vs. ACEI on F/U Hgb. The method produces an estimate of the treatment effect by simultaneously incorporating the propensity of a subject to receive ACEI or ARB, given their levels of covariates, and the effects of the covariates upon the response of interest, F/U Hb. It is doubly robust in the sense that it produces an unbiased estimate of the treatment effect if either the outcome or propensity model is correct. A complete-case ANCOVA was conducted to estimate the treatment effect. Results We found the estimated F/U Hb and bootstrap bias-corrected accelerated (BCa) 95% confidence interval (CI) of ACEI and ARB to be 14.31 (14.21, 14.42) gm/dL and 14.48 (14.33, 14.62) gm/dL, respectively. The causal effect of ARB relative to ACEI and associated BCa CI is estimated to be 0.17 (0.00, 0.31) gm/dL (p = 0.0310). Discussion The use of doubly robust estimation documented a significant difference between the effects of ACEI and ARB on F/U Hb, despite the association of several of the baseline covariates with the differential ordering of these drugs.