Multidisciplinary Medication Therapy Management and Hospital Readmission in Patients Undergoing Maintenance Dialysis: A Retrospective Cohort Study

Original Investigation

Multidisciplinary Medication Therapy Management and Hospital Readmission in Patients Undergoing Maintenance Dialysis: A Retrospective Cohort Study Harold J. Manley, Gideon Aweh, Daniel E. Weiner, Huan Jiang, Dana C. Miskulin, Doug Johnson, and Eduardo K. Lacson Rationale & Objectives: Dialysis patients frequently experience medication-related problems. We studied the association of a multidisciplinary medication therapy management (MTM) with 30-day readmission rates. Study Design: Retrospective cohort study. Setting & Participants: Maintenance dialysis patients discharged home from acute-care hospitals between May 2016 and April 2017 who returned to End-Stage Renal Disease Seamless Care Organization dialysis clinics after discharge were eligible. Patients who were readmitted within 3 days, died, or entered hospice within 30 days were excluded.

and modality, marital status, home medications, frequent prior hospitalizations, length of stay, discharge diagnoses, hierarchical condition category, and facility standardized hospitalization rates. Propensity score matching was performed to examine the robustness of the associations in a comparison between the full- and no-MTM exposure groups on time to readmission.

Exposure: MTM consisting of nurse medication reconciliation, pharmacist medication review, and nephrologist oversight was categorized into 3 levels of intensity: no MTM, partial MTM (defined as an incomplete MTM process), or full MTM (defined as a complete MTM process).

Results: Among 1,452 discharges, 586 received no MTM, 704 received partial MTM, and 162 received full MTM; 30-day readmission rates were 29%, 19%, and 11%, respectively (P < 0.001). Compared with no MTM, discharges with full MTM had the lowest time-varying risk for readmission within 30 days (HR, 0.26; 95% CI, 0.15-0.45); discharges with partial MTM also had lower readmission risk (HR, 0.50; 95% CI, 0.37-0.68). In propensity score–matched sensitivity analysis, full MTM was associated with lower 30-day readmission risk (HR, 0.20; 95% CI, 0.06-0.69).

Outcome: The primary outcome was 30-day readmission.

Limitations: Reliance on observational data. Residual bias and confounding.

Analytical Approach: Time-varying Prentice, Williams, and Peterson total time hazards models explored associations between MTM and time to readmission after adjusting for age, race, sex, diabetes comorbidity, albumin level, vascular access type, kidney failure cause, dialysis vintage

Conclusions: MTM services following hospital discharge were associated with fewer 30-day readmissions in dialysis patients. Randomized controlled studies evaluating different MTM delivery models and cost-effectiveness in dialysis populations are warranted.

I

ndividuals treated with maintenance dialysis are medically complex with multiple comorbid conditions requiring on average 10 to 12 medications1-3 and experience nearly 2 hospitalizations per year, with 35% resulting in readmission.4 During care transitions,

Editorial, p. 7 medication changes are common; may cause patient confusion regarding which medications to continue, stop, or modify; and may not account for key issues such as medication dosing in dialysis. Structured medication reviews in dialysis patients on average identify 4 medication-related problems that medication therapy management (MTM) services can detect and resolve.5 Among older adults in the general population, 20% experience an adverse event after discharge, and 21%

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Complete author and article information provided before references. Correspondence to H.J. Manley (harold. [email protected]) Am J Kidney Dis. 76(1): 13-21. Published online March 12, 2020. doi: 10.1053/ j.ajkd.2019.12.002

© 2019 by the National Kidney Foundation, Inc.

of 30-day readmissions are medication related, of which 69% are preventable.6 Providing multidisciplinary MTM services involving pharmacists and nurses for discharge planning, medication reconciliation, and postdischarge telephone follow-up reduces rehospitalization.6,7 Similar impact data in the dialysis population are lacking. In the Centers for Medicare & Medicaid Services (CMS) Innovation Comprehensive End-Stage Renal Disease (ESRD) Care Model, ESRD Seamless Care Organizations (ESCOs) are incentivized to provide coordinated comprehensive care by making stakeholders responsible for hospitalization costs.8 ESCO quality measures include hospital readmission rates and medication reconciliation postdischarge.9 Dialysis Clinic, Inc (DCI)-affiliated ESCOs developed and implemented a multidisciplinary MTM intervention to reduce hospital readmission. We investigated our MTM program’s effect on 30-day readmission rates.

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Original Investigation Methods Study Design We conducted a retrospective observational study of all hospital discharges to home within DCI’s initial ESCOs (Music City, Metropolitan, and Palmetto Kidney Care Alliance), involving 27 dialysis clinics across 4 states (New Jersey, New York, Tennessee, and South Carolina). This study was conducted in adherence with the Declaration of Helsinki and considered exempt by the Western Institutional Review Board. MTM Process All patients discharged to home were eligible for MTM services. Patients were not asked if they wanted to participate because the MTM service was considered standard of care. The MTM process started with clinic nurses reconciling patient home medications through patient interview and comparison of medication lists among clinic records, discharge documents, and the patient’s pharmacy. The nurse then updated clinic electronic medical records and tasked a centralized pharmacist to conduct a medication review. The pharmacist evaluated the patient’s medication regimen for appropriateness and safety in the context of available clinic electronic medical record information (eg, medications, laboratory results, discharge documents, and progress notes). The pharmacist identified patient-specific potential medication-related problems and created a medication action plan with 3 sections: (1) specific recommendations with supporting evidence, (2) reconciled medication list, and (3) evaluation comments containing other necessary information for the care team. The medication action plan was provided to the patient’s nephrologist and nurse for review. The final MTM process step was the nephrologist signed and dated response to pharmacist recommendations. Nephrologist responses that modified patients’ medication regimens were considered physician orders. MTM Exposure Completion of each of the MTM process steps outlined causes a change in the MTM group assignment postdischarge (Fig 1). Initially, all discharges are assigned to the no-MTM group on date of discharge. On receipt of nurse medication reconciliation, the discharge is assigned to the partial-MTM group, remaining there even after the pharmacist creates and sends the medication action plan to the nephrologist. After the nephrologist reviews, signs, and returns the medication action plan, the discharge is assigned to the full-MTM group only if 100% of medications were reconciled by the nurse; otherwise, the discharge remained assigned to the partial-MTM group. Discharge assignment into the no-, partial-, or full-MTM groups was either the last MTM process step completed during the 30-day follow-up or the last process step accomplished at readmission. Patients who first received 14

MTM process steps 30 or more days after discharge were assigned to the no-MTM group. Pharmacists used an MTM software system (Assurance Pharmaceutical Care System; Genoa Healthcare, Inc) and classified potential medication-related problems as “adverse drug reaction,” “compliance” (ie, treatment adherence), “different drug needed,” “dosage too high,” “dosage too low,” “needs additional therapy,” or “unnecessary drug therapy” (Table S1). Each medication associated with a potential medication-related problem was classified according to Medi-Span schema (Wolters Kluwer Clinical Drug Information). Study Population Discharges to home were identified in Medicare Part A claims data. To account for patients with multiple discharges, “frequent” hospitalization was defined as 3 or more discharges in the previous 6 months before the first discharge within the study period. The MTM intervention study window was May 1, 2016, through April 30, 2017, with follow-up for events through May 31, 2017. Discharges were excluded if the patient died or entered hospice care within 30 days of discharge, hospital readmission occurred within 3 days, hospitalization was related to kidney transplantation surgery, the patient was designated transient, or the patient had missing data for dialysis modality and/or demographic information. Each discharge was considered a unique event. Individual patients experiencing more than 1 discharge during the study period had their respective demographic characteristics recorded at each discharge. Patient discharge characteristics included age, race, ethnicity, sex, kidney failure cause, dialysis start date and modality, marital status, vascular access type, diabetes comorbidity, serum albumin concentration, number of home medications at time of hospitalization, number of discharge diagnoses, hierarchical condition category (HCC) score, number of hospitalizations in prior 6 months, and facility standardized hospitalization rate. The HCC score incorporates demographic characteristics and diagnosis-based medical conditions documented in patient claims,10 and the HCC model assigns diagnoses into categories comprising conditions with comparable cost patterns. Higher categories are those with health care costs that are predicted to be greater, leading to higher risk scores. The CMS incorporates HCC score in risk-adjustment models to predict 30-day unplanned readmission in other populations.11 Patient HCC scores were calculated using diagnostic codes from ambulatory and inpatient claims data, and the look-back period included the prior 12 months before initial hospital discharge. Dichotomous indicators for each of the HCC’s 79 comorbid conditions were included in the models. The 2015 facility standardized hospitalization rate was obtained from the CMS Dialysis Facility Report 2017 data file.12 AJKD Vol 76 | Iss 1 | July 2020

Original Investigation The DCI electronic record captured all medication reconciliation events including details and date, with “home medications reconciled” indicating the proportion of home medications having reconciliation within 30 days of discharge. Hospitalization claims data were used to determine the number of diagnoses at discharge and length of stay, calculated as number of days between hospital admission and discharge dates. Statistical Analyses We used a time-varying Prentice, Williams, and Peterson total time (PWP-TT) model as our primary analysis to mitigate within-patient correlation at the patient level and minimize immortal time bias resulting from the median of 10 days needed to complete the MTM process.13 The timevarying PWP-TT model determined hazard ratios (HRs) and stratified each discharge in sequence so that the initial patient discharge HR can differ between sequential discharges. The model incorporated a robust covariance matrix estimator to account for within-patient correlation and facility correlation. The model was adjusted for the timeindependent (eg, diabetes comorbidity, kidney failure cause, sex, marital status, HCC score, and facility standardized hospitalization rate) and time-dependent variables (eg, age, dialysis vintage and modality, vascular access type, number of home medications, prior hospitalization history [frequent hospitalization defined as having ≥3 discharges in the previous 6 months], inpatient length of stay, albumin level, and number of diagnoses at discharge). The time-varying PWP-TT model incorporated the number of days within each step of the MTM process in the following manner: days within no-, partial-, and fullMTM interventions were assigned to each discharge (time zero), such that an individual counted as no MTM until the MTM process initiated (if applicable), as partial MTM following MTM initiation but before MTM completion, and as full MTM following MTM completion (if applicable). Patients who died before the end of follow-up were treated as censoring in all models. HRs and 95% confidence intervals (CIs) were calculated to assess the association between MTM and time to readmission within 30 days. If readmission did not occur, models censored patients at 30 days postdischarge. The noMTM group was the referent group in all analyses. Goodness-of-fit test was used to check PWP-TT model assumptions. In addition to the time-varying MTM status, there may exist unmeasured time-varying confounders, such as health status within 30 days postdischarge, that could affect MTM activities at various treatment levels (no, partial, or full MTM) and also affect readmission rates. Therefore, secondary analyses examined the robustness of the associations in a comparison that partially eliminated the residual confounding. A propensity score was calculated as the estimated probability from a logistic regression model of whether a discharge had full MTM or no AJKD Vol 76 | Iss 1 | July 2020

MTM. The following variables were used: age, dialysis vintage and modality, kidney failure cause, vascular access type, prior hospitalization history, albumin level, sex, marital status, and race. Without replacement, a 1:1 greedy-matching strategy by random order was used with a 0.1 caliper width based on propensity score and survival time between discharge and readmission for each full-MTM discharge. We analyzed matched pairs using stratified Cox proportional hazard models. In sensitivity analyses, we also investigated the association of MTM process implemented within 7 days, 7 to 15 days, or 15 days or later postdischarge with readmission. We used SAS, version 9.4 (SAS Institute Inc) to conduct all analyses. Results Between May 1, 2016, and April 30, 2017, there were 1,732 hospital discharges to home: 373 (51%) patients had 1 discharge; 181 (25%) had 2 discharges; 82 (11%) had 3 discharges, and 90 (12%) had 4 or more discharges. Of these, 1,452 (84%) discharges in 726 patients were included in the analyses. Discharges excluded were transient patients (n = 156; 9%), death occurring within 30 days (n = 43; 2%), readmission occurring within 3 days (n = 36; 2%), missing demographic information (n = 25, 1%), or missing dialysis modality information (n = 20; 1%). Three DCI ESCOs contributed 32.9%, 38.8%, and 28.2% of unique patients, respectively. Figure 1 depicts the cumulative percent of discharges within each MTM process step during 30 days after discharge. Overall, 866 (60%) discharges received some level of medication reconciliation. Pharmacist review was provided in 595 (41%) discharges and 492 (34%) had nephrologist review of pharmacist recommendation(s). Of the 866 discharges with some level of medication reconciliation, 409 (47%) discharges had 100% medications reconciled, 269 (31%) received pharmacist review, and 162 (19%) received both pharmacist medication review and nephrologist review of pharmacist recommendations within 30 days of discharge. The various combinations of MTM process steps and implementation timeliness resulted in provision of full or partial MTM in 162 (11%) and 704 (48%) of the 1,452 discharges, respectively. Among full-MTM discharges, defined as completion within 30 days after discharge, the mean time to complete the process was 12 ± 6 (standard deviation; median [interquartile range] of 10 [7]) days. Time to completion included 4 ± 3 (median, 3 [IQR, 3]) days for nurse medication reconciliation; 2 ± 3 (median, 1 [IQR, 3]) days for pharmacist medication review and sending of the medication action plan to nephrologists, and 6 ± 5 (median, 5 [IQR, 5]) days for nephrologist review, signing, and return of the medication action plan (Table S2). 15

Original Investigation 1600 No-MTM

1429

Partial*-MTM

Full†-MTM

1400

# Discharges

1200 1000 792

800

704

696 594

600

586

504

400 156

200 20 0

162

162

3

Day of discharge

≤10 days post discharge ≤20 days post discharge Days post discharge

≤30 days post discharge

Figure 1. Number of discharges in each medication therapy management (MTM) exposure level (no, partial, and full MTM) over time. *Includes 100% nurse medication reconciliation ± pharmacist recommendations to physician. yIncludes 100% nurse medication reconciliation + pharmacist recommendations to physician + physician review/approval of recommendations.

Patients were 64 ± 15 years old and 56% had diabetes (Tables 1 and S3). Patients experienced a mean of 2 discharges, each with a mean length of stay of 7 ± 6 days. The number and type of discharge diagnoses were similar among MTM groups at 30 days postdischarge (Table 1; Fig S1). Facility-level impact indicated that for every 0.1 greater facility standardized hospitalization rate, hospitalization rate was greater by 8% (HR, 1.08 [95% CI, 1.001.17]; Table S4). There were 5,466 potential medication-related problems identified. The top 3 potential medication-related problems identified were medication dosing issues (n = 1,697 [31%], comprising “dose too high” for 1,202 (22%) and “dose too low” for 495 (9%)); real or potential “adverse drug reaction” (n = 1,570; 29%); and “unnecessary drug therapy” (n = 928; 17%). Cardiovascular (n = 980; 18%), gastrointestinal (n = 825; 15%), analgesic (n = 635; 12%), and endocrine and metabolic drugs (n = 553; 10%) were the top 4 medication classes, accounting for 55% of pharmacist recommendations. Within each medication class, calcium channel blockers (n = 145), proton pump inhibitors (n = 149), insulins (n = 250), and salicylates (n = 165) were associated with most potential medication-related problems. Detailed information regarding potential medication-related problem definitions, frequency, and associated medications are provided in Tables S1, S5, and S6. There were 17 (11%), 135 (19%), and 170 (29%) 30day readmissions among full-, partial-, and no-MTM patients, respectively (P < 0.001). Of the 1,452 discharges, 16

there were 323 (22%) readmissions during the follow-up period and the majority (n = 28%) occurred 15 to 21 days postdischarge (Fig 2). Partial- and full-MTM services were associated with fewer readmissions within the 30-day time frame (Table 2). Full-MTM discharges had the lowest 30-day readmission risk (HR, 0.26; 95% CI, 0.15-0.45), while partial-MTM discharges also had lower 30-day readmission risk than those receiving no MTM (HR, 0.50; 95% CI. 0.37-0.68; Table 2). Within the partial-MTM group, 30day readmission rates for discharges that received medication reconciliation only (n = 333; 47%) and medication reconciliation and pharmacist review only (n = 371; 53%) were 17% and 21%, respectively (P = 0.09). In the secondary propensity score–matched analysis, 135 (83%) full-MTM discharges were matched to noMTM discharges; 27 full-MTM discharges were unable to be matched within decile restrictions. Full MTM was associated with lower 30-day readmission compared with no MTM (HR, 0.20; 95% CI, 0.06-0.69; Table 3). In further analysis, of the 492 discharges for which there were both pharmacist and nephrologist reviews after some degree (range, 12.5%-100%) of medication reconciliation, 282 (57%) discharges were matched to 282 no-MTM discharges; MTM was associated with lower 30-day readmission (HR, 0.29; 95% CI, 0.17-0.49; Table S7). Covariate balancing before and after propensity score matching are provided in Tables S8 to S11. In sensitivity analyses limited to discharges having intervention within 7 days and between 7 and 15 days, full MTM was associated with significantly lower risk for AJKD Vol 76 | Iss 1 | July 2020

Original Investigation Table 1. Patients Demographics at Discharge by MTM Group Intervention Group at 30 d Postdischarge Total no. of discharges Index onlya Index with readmissionb Discharge during follow-upc Demographic Age, y Female sex Race White Black Others Unknown Marital status Married Single Divorced/separated/widowed Unknown Kidney failure cause Diabetes Hypertension Other Unknown Dialysis vintage, mod Mean Median Hemodialysis as dialysis modality CVC as vascular access No. of discharge diagnoses Diabetes comorbidity Serum albumin, g/dL Frequent hospitalizationse No. of dischargesf Hierarchical condition category score Index hospitalization LOS, d Facility SHR

Overall 1,452 1,129 (78%) 309 (21%) 14 (1%)

No MTM 586 416 (71%) 166 (28%) 4 (1%)

Partial MTM 704 568 (81%) 126 (18%) 10 (1%)

Full MTM 162 145 (90%) 17 (11%) 0 (0%)

64 ± 15 46%

63 ± 15 44%

61 ± 15 55%

64 ± 14 42%

46% 43% 4% 8%

48% 40% 4% 8%

42% 48% 3% 7%

37% 55% 4% 4%

42% 24% 23% 11%

35% 23% 24% 18%

41% 26% 26% 7%

43% 22% 28% 7%

43% 21% 36% 0%

38% 19% 43% 1%

47% 22% 31% 0%

47% 25% 28% 0%

57 ± 52 48 [69] 89% 15% 6 [1] 56% 3.7 ± 0.5 4% 2 [2] 4 [3] 7 [6] 10 [2]

48 ± 49 34 [76] 90% 23% 6 [1] 54% 3.7 ± 0.5 7% 2 [1] 3 [2] 7 [6] 10 [2]

64 ± 53 54 [33] 89% 18% 6 [1] 67% 3.7 ± 0.4 8% 2 [1] 5 [3] 7 [5] 9 [2]

72 ± 57 58 [80] 95% 17% 6 [1] 59% 3.7 ± 0.4 4% 1 [1] 5 [3] 6 [4] 10 [2]

Note: Values for categorical variables given as count (percentage) or percentage; for continuous variables, as mean ± standard deviation or median [interquartile range]. Abbreviations and definitions: CVC, central venous catheter; LOS, length of stay; MTM, medication therapy management (full MTM consisted of 100% of medications reconciled postdischarge by nurse, pharmacist medication review, and physician review of pharmacist medication recommendations; partial MTM, <100% medication reconciliation postdischarge by nurse, possible pharmacist medication review, and possible physician review of pharmacist medication recommendations; patients could contribute multiple discharges and could appear in >1 MTM group); SHR, standardized hospitalization rate. a Discharges associated with index admission and did not have readmission during intervention period May 1, 2016, through April 30, 2017. b Discharges associated with readmission during intervention period May 1, 2016, through April 30, 2017. c Discharges during follow-up period through May 31, 2017. d Number of months between dialysis initiation date and index hospitalization date. e Three or more hospitalizations within past 6 months before participation. f Number of hospitalization discharges between May 1, 2016, through April 30, 2017, with follow-up for events through May 31, 2017.

30-day readmission (HRs of 0.29 [95% CI, 0.12-0.70] and 0.39 [95% CI, 0.21-0.73], respectively; Table S12). Association with 30-day readmission when full MTM provided after day 15 could not be determined because no patient in this group was readmitted within 30 days. Discussion Among dialysis patients receiving care in ESCO facilities, MTM services post–hospital discharge were associated with

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55% lower risk for 30-day readmission. Dialysis patients are frequently hospitalized and experience care transitions, putting them at risk for medication-related problems. Several studies suggest that MTM provided to dialysis patients can identify and resolve medication-related problems in ambulatory14-21 or currently hospitalized22,23 patients. Our results expand these data to patients recently discharged from the hospital, a period considered as high risk, and suggest that MTM programs can identify

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Original Investigation 40 No-MTM

Partial-MTM

Full-MTM

35

# Readmission

30

Excluded n=36

25 20

15 10 5 0 0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Days post discharge

Figure 2. Number of readmissions postdischarge by medication therapy management (MTM) group.

and address potential medication-related problems, with a subsequent reduction in rehospitalization. Dialysis patients may be discharged from the hospital with unresolved medication-related problems. In a 14week prospective observational study at a teaching hospital, a clinical pharmacist identified 161 medication-related problems in 30 dialysis patients experiencing 32 hospital admissions: 48% occurred at admission, 27% occurred during hospitalization, and 26% occurred at discharge.23 The association of discharge-related medication-related problems with readmission was not investigated. Our MTM program’s aim was to reduce the presumed risk associated with unresolved discharge-related medicationrelated problems through a structured multidisciplinary process when the patient returns to the clinic. In our population, we identified medication-related problems in 90% of discharges. Detailed information regarding

potential medication-related problem frequency and associated medications and some examples of pharmacist recommendations are provided in Tables 4, S5, and S6. Our experience is supported by prior small trials. One 2-year trial randomly assigned 104 hemodialysis patients to receive either MTM services or usual care.20 The MTM group received bimonthly medication review conducted in person by a clinical pharmacist, while the usual-care group received medication reviews conducted by nurses. Patients receiving MTM services had fewer hospitalizations (1.8 ± 2.4 vs 3.1 ± 3; P = 0.02) and nominally reduced lengths of stay (10 ± 15 vs 16 ± 16 days), though this latter finding was not statistically significant (P = 0.06). For patients with chronic kidney disease not requiring kidney replacement therapy, 1 randomized trial evaluated 90-day readmission rates after MTM in 138 patient discharges.24 The usual-care group had electronic

Table 2. Time-Varying PWP-TT Model for Readmission by MTM Status Intervention Group at 30 d Postdischarge No MTM Partial MTM Full MTM

HR (95% CI) N 586 704 162

Readmit Rate 29% 19% 11%

Unadjusted 1.00 (reference) 0.67 (0.51-0.89) 0.36 (0.21-0.61)

Adjusted 1.00 (reference) 0.50 (0.37-0.68) 0.26 (0.15-0.45)

Note: Full MTM consists of 100% of medications reconciled postdischarge by a nurse, pharmacist medication review, and physician review of pharmacist medication recommendations. Partial MTM consists of <100% medication reconciliation postdischarge by nurse, possible pharmacist medication review, and possible physician review of pharmacist medication recommendations. Patients could contribute multiple discharges. Models are adjusted for age, dialysis vintage and modality, diabetes comorbidity, number of home medications, kidney failure cause, prior hospitalization history (frequent hospitalization defined as having ≥3 discharges in the previous 6 months), inpatient length of stay, vascular access type, albumin level, sex, marital status, race, number of diagnoses at discharge, hierarchical condition category, and facility standardized hospitalization rate. Abbreviations: CI, confidence interval; HR, hazard ratio; MTM, medication therapy management; N, sample size; PWP, Prentice-Williams-Peterson total time.

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Original Investigation Table 3. Survival/Propensity Score Match Results for Readmission in Discharges Having 100% Medications Reconciled, Pharmacist Medication Recommendations for Physician Consideration, and Physician Reply Within 30 Days of Discharge Intervention Group at 30 d Postdischarge No MTM Full MTM

HR (95% CI) Readmit Rate 37% 19%

Unadjusted 1.00 (reference) 0.44 (0.26-0.73)

Unadjusted 1.00 (reference) 0.20 (0.06-0.69)

Note: n = 270 total; 135 each group. Full MTM consists of 100% of medications reconciled postdischarge by nurse, pharmacist medication review, and physician review of pharmacist medication recommendations; adjusted for age, dialysis vintage and modality, diabetes comorbidity, number of home medications, kidney failure cause, prior hospitalization history, inpatient length of stay, vascular access type, albumin level, sex, marital status, race, number of diagnoses at discharge, and facility standardized hospitalization rate. Abbreviations: CI, confidence interval; HR, hazard ratio; MTM, medication therapy management.

health record–derived medication lists and discharge prescriptions presented by a nurse, while the intervention group received usual care plus a single home visit 1 to 7 days postdischarge by a pharmacist to provide “MTM.” The intervention group had 263 medication-related issues identified during the home visit: 141 (53.6%) were discrepancy issues, 71 (27%) were medication adherence or access issues, and 51 (19.4%) were either adverse drug event, contraindicated medication, dosing issues, drug not needed, drug intolerance or additional follow up needed. There was no difference in readmission rates at 90 days. Differences in patient populations (non–kidney replacement therapy–requiring vs maintenance dialysis patients), sample size (1,452 vs 138 discharges), study design, and the different MTM interventions make comparisons very difficult if not impossible between these studies. There are potential biases affecting our results. Specifically, the higher readmission rate in the no-MTM group may reflect inclusion of a subset of patients who did not have the opportunity to receive MTM due to early readmissions. To mitigate within-patient correlation at the patient level and minimize immortal time bias resulting from the median of 10 days needed to complete the MTM

process, primary analyses used a time-varying PWP-TT model that first assigned patients to the no-MTM group before medication reconciliation was completed, then to the partial-MTM group until the medication action plan was reviewed by nephrologist or the 30-day threshold was reached, whichever came first, and only assigned patients to the full-MTM group when the entire process was completed within 30 days. Of note, within the partialMTM group, medication reconciliation alone compared with medication reconciliation and medication review was not significantly different, suggesting that full MTM including the physician action is important in avoiding 30day readmission. Our study has several limitations. First, our results are based on retrospective observational data and causality is not established. Second, this study includes varied time frames with which patients received their MTM intervention that can result in bias. As described, we mitigated immortal time bias by incorporating time to MTM completion within a time-varying PWP-TT model and performed sensitivity analyses investigating readmission association with MTM process implemented within 7 days, 7 to 15 days, or after 15 days and secondary analyses using propensity score matching. It is reassuring

Table 4. Examples of Postdischarge Medication-Related Issues and Corresponding Pharmacist Recommendations Medication-Related Problem Category Drug interaction

Medication(s) Implicated and Pharmacist Recommendation(s) Patient is concurrently prescribed sucralfate, calcium acetate, and doxycycline. Sucralfate and calcium acetate may diminish absorption of doxycycline. Counsel patient to take doxycycline as least 2 h before sucralfate and several hours after calcium acetate. Drug dose too high Patient is prescribed gabapentin, 300 mg, 3 times daily. The maximum recommended dose in patients requiring dialysis is 100-300 mg daily. Using higher dose can increase risk for gabapentin adverse effects such as dizziness, drowsiness, ataxia, fatigue, tremor, abnormal gait, abnormality in thinking, depression, amnesia, and nervousness. Consider decreasing gabapentin dose to 300 mg daily. Patient needs additional Patient is prescribed vancomycin for vascular access infection. Trough concentrations should be monitoring monitored to minimize toxicity, ensure efficacy, and reduce development of resistance. Please consider obtaining serum vancomycin concentrations before next dialysis session. Target a predialysis vancomycin concentration of 15-20 mg/L. Drug undesirable effect(s) Baclofen use is contraindicated in dialysis patients. Baclofen is eliminated primarily unchanged through possible the kidneys and cases of neurotoxicity due to accumulation have been described. In addition, there are potential additive adverse effects when used in combination with other agents, such as those that affect the CNS and cardiovascular medications. Baclofen can also affect conditions such as gastrointestinal/ motility/seizure disorders and psychiatric and respiratory disease, potentially exacerbating conditions. Please discontinue use of baclofen therapy. Abbreviation: CNS, central nervous system.

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Original Investigation that results remained robust using all these methodologies. Third, confounding by health status may be present due to the imperfect nature of the measurement of comorbid conditions at the time of discharge and the absence of information of postdischarge health status. It is possible that sicker patients are less likely to receive MTM and more likely to be readmitted. Although our sensitivity analysis somewhat addresses this issue, it does not eliminate the possibility of residual confounding. Fourth, cut points in some variables (eg, prior hospitalizations, number of home medications, or discharge diagnoses) and intrapatient and facility-level correlations may limit distinguishing features between groups. To account for this, the PWP-TT model adjusted for individual patient HCC score and facility standardized hospitalization rates. Fifth, although all discharges to home were eligible for the MTM, 586 (40%) discharges did not receive any component of MTM process. Potential reasons for this include late adoption of the MTM process, which was new and required progressive implementation based on capacity; the clinic may not have been aware of patient admission and discharge from hospital since the last dialysis treatment and therefore would not provide MTM; and the partial-MTM group included 233 discharges that had nurse medication reconciliation < 100%, pharmacist review, and nephrologist response. Sixth, our results may not be generalizable to the US dialysis population given that the ESCO infrastructure available for patient care exceeds that seen in many dialysis facilities. Of note, the 30-day readmission rate in our population was 29%, slightly lower than the national 30day readmission rate of 35%; this similar but slightly better readmission rate in our ESCO population suggests that these results are likely relevant to the broader US dialysis population and may provide important lessons for future dialysis care models. Finally, we observed that partial MTM was associated with a reduced readmission rate. As mentioned, the partial-MTM group included 233 discharges that completed the entire MTM process even though medication reconciliation was <100%. This resulted in attributing the discharge to the partial-MTM group and potentially contributed to lower readmission rates. Although pharmacist recommendations could not be implemented without physician approval, other nurse and nephrologist activities after discharge may contribute to readmission rates. Our ESCOs use an “all hands on deck” approach when patients return to the clinic after discharge, including the nurse interacting with the patient to inquire about necessary follow-up visits with other providers, conducting medication reconciliation, informing the nephrologist of the patient’s return to the clinic, and implementing any nephrologist orders to modify dialysis prescription, target weights, etc. These actions occur in parallel with MTM and likely provide benefits by detecting 20

problems and coordinating care beyond that to MTM. Unfortunately, we did not capture or measure these actions. Nonetheless, we found a “dose-response” effect whereby full MTM was associated with lower readmission rates compared with partial MTM, supporting the notion that MTM services provide additional marginal benefit. In conclusion, using a model of centralized clinical pharmacists with access to clinical data and documentation working in collaboration with local nurses and nephrologists to provide in-depth patient-specific medication reviews, our findings suggest a significant reduction in risk for 30-day readmission for patients receiving MTM. Randomized controlled studies evaluating different MTM delivery models and cost-effectiveness in dialysis populations are needed. Supplementary Material Supplementary File (PDF) Figure S1: Percent of index discharge diagnoses categories for no-, partial-, and full-MTM groups. Table S1: Definitions for potential medication-related problems identified. Table S2: Hospital discharges and MTM process timeline within each MTM group within ESCOs. Table S3: Patient demographics at discharge by ESCO location. Table S4: Unadjusted time-varying PWP-TT model hazard ratios for 30-day readmission. Table S5: Frequency of pharmacist recommendations by potential medication-related problem category. Table S6: Medications frequently associated with potential medication-related problems. Table S7: Survival/propensity score match results for readmission in discharges having any medications reconciled, pharmacist medication recommendations for physician consideration, and physician reply within 30 days of discharge. Table S8: Baseline characteristics at discharge in no- and full-MTM groups before propensity score matching. Table S9: Baseline characteristics at discharge in no- and full-MTM groups after propensity score matching. Table S10: Baseline characteristics at discharge in no- and complete process–MTM groups before propensity score matching. Table S11: Baseline characteristics at discharge in no- and complete process–MTM groups after propensity score matching. Table S12: Time-varying PWP-TT model for readmission where MTM intervention occurred within 7 or 7-15 days post-discharge.

Article Information Authors’ Full Names and Academic Degrees: Harold J. Manley, PharmD, Gideon Aweh, MS, Daniel E. Weiner, MD, MS, Huan Jiang, PhD, Dana C. Miskulin, MD, MS, Doug Johnson, MD, and Eduardo K. Lacson, MD, MPH. Authors’ Affiliations: Dialysis Clinic, Inc, Nashville, TN (HJM, GA, HJ, DJ, EKL); and Tufts Medical Center, Boston, MA (DEW, DCM, EKL). Address for Correspondence: Harold J. Manley, PharmD, Dialysis Clinic, Inc, 264 Washington Ave Ext, Albany, NY 12203. E-mail: [email protected] AJKD Vol 76 | Iss 1 | July 2020

Original Investigation Authors’ Contributions: Research idea and study design: HJM, GA, DEW, HJ, DCM, DJ, EKL; data acquisition: HJM, GA; data analysis/ interpretation: HJM, GA, DEW, HJ, DCM, EKL; supervision or mentorship: HJM, EKL. Each author contributed important intellectual content during manuscript drafting or revision, accepts personal accountability for the author’s own contributions, and agrees to ensure that questions pertaining to the accuracy or integrity of any portion of the work are appropriately investigated and resolved. Support: No support of any kind (eg, financial, writing, or administrative services) was obtained for this study. Financial Disclosures: The authors declare that they have no relevant financial conflict of interests. Acknowledgements: The authors acknowledge all the work of the ESCO’s nurse care coordinators, pharmacists, and nephrologists in the care of the patients. We would not be able to report the MTM program outcomes without their efforts. Disclaimer: The statements contained in this document are solely those of the authors and do not necessarily reflect the views or policies of CMS. The authors assume responsibility for the accuracy and completeness of the information contained in this article. Peer Review: Received July 31, 2019, as a submission to the expedited consideration track with 4 external peer reviews. Direct editorial input from a Statistics/Methods Editor, an Associate Editor, and the Editor-in-Chief. Accepted in revised form December 9, 2019. Further information on expedited consideration (AJKD Express) is available in the Information for Authors & Journal Policies.

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