BACKGROUND: Evidence regarding the effect of psychosocial factors on hospital readmission in the setting of hemodialysis is limited. We examined whether social worker-assessed factors were associated with 30-day readmission among prevalent hemodialysis patients. METHODS: Data on 14 factors were extracted from the first available psychosocial assessment performed by social workers at three metropolitan Atlanta dialysis centers. Index admissions (first admission preceded by ≥30 days without a previous hospital discharge) were identified in the period 2/1/10-12/31/14, using linked national administrative hospitalization data. Readmission was defined as any admission within 30 days after index discharge. Associations of each of the psychosocial factors with readmission were assessed using multivariable logistic regression with adjustment for patient and index admission characteristics. RESULTS: Among 719 patients with index admissions, 22.1% were readmitted within 30 days. No psychosocial factors were statistically significantly associated with readmission risk. However, history of substance abuse vs. none was associated with a 29% higher risk of 30-day readmission [OR: 1.29, 95% CI: 0.75-2.23], whereas depression/anxiety was associated with 20% lower risk [OR: 0.80, 95% CI: 0.47-1.36]. Patients who were never married and those who were divorced, or widowed had 38 and 17% higher risk of 30-day readmission, respectively, than those who were married [OR: 1.38, 95% CI: 0.84-2.72; OR: 1.17, 95% CI: 0.73-1.90]. CONCLUSIONS: Results suggest that psychosocial issues may be associated with risk of 30-day readmission among dialysis patients. Despite the limitations of lack of generalizability and potential misclassification due to patient self-report of psychosocial factors to social workers, further study is warranted to determine whether addressing these factors through targeted interventions could potentially reduce readmissions among hemodialysis patients.

BACKGROUND: Readmission within 30 days of hospital discharge is common and costly among end-stage renal disease (ESRD) patients. Little is known about long-term outcomes after readmission. We estimated the association between hospital admissions and readmissions in the first year of dialysis and outcomes in the second year. METHODS: Data on incident dialysis patients with Medicare coverage were obtained from the United States Renal Data System (USRDS). Readmission patterns were summarized as no admissions in the first year of dialysis (Admit-), at least one admission but no readmissions within 30 days (Admit+/Readmit-), and admissions with at least one readmission within 30 days (Admit+/Readmit+).We used Cox proportional hazards models to estimate the association between readmission pattern and mortality, hospitalization, and kidney transplantation, accounting for demographic and clinical covariates. RESULTS: Among the 128,593 Medicare ESRD patients included in the study, 18.5% were Admit+/Readmit+, 30.5% were Admit+/Readmit-, and 51.0% were Admit-. Readmit+/Admit+ patients had substantially higher long-term risk of mortality (HR = 3.32 (95% CI, 3.21-3.44)), hospitalization (HR = 4.46 (95% CI, 4.36-4.56)), and lower likelihood of kidney transplantation (HR = 0.52 (95% CI, 0.44-0.62)) compared to Admit- patients; these associations were stronger than those among Admit+/Readmit- patients. CONCLUSIONS: Patients with readmissions in the first year of dialysis were at substantially higher risk of poor outcomes than either patients who had no admissions or patients who had hospital admissions but no readmissions. Identifying strategies to both prevent readmission and mitigate risk among patients who had a readmission may improve outcomes among this substantial, high-risk group of ESRD patients.

BACKGROUND: U.S. hospitals and dialysis centers are penalized for 30-day hospital readmissions of dialysis patients, despite little infrastructure to facilitate care transitions between these settings. We are developing a third-party web-based information exchange platform, DialysisConnect, to enable clinicians to view and exchange information about dialysis patients during admission, hospitalization, and discharge. This health information technology solution could serve as a flexible and relatively affordable solution for dialysis facilities and hospitals across the nation who are seeking to serve as true partners in the improved care of dialysis patients. The purpose of this study was to evaluate the perceived coherence of DialysisConnect to key clinical stakeholders, to prepare messaging for implementation. METHODS: As part of a hybrid effectiveness-implementation study guided by Normalization Process Theory, we collected data on stakeholder perceptions of continuity of care for patients receiving maintenance dialysis and a DialysisConnect prototype before completing development and piloting the system. We conducted four focus groups with stakeholders from one academic hospital and associated dialysis centers [hospitalists (n = 5), hospital staff (social workers, nurses, pharmacists; n = 9), nephrologists (n = 7), and dialysis clinic staff (social workers, nurses; n = 10)]. Transcriptions were analyzed thematically within each component of the construct of coherence (differentiation, communal specification, individual specification, and internalization). RESULTS: Participants differentiated DialysisConnect from usual care variously as an information dashboard, a quick-exchange communication channel, and improved discharge information delivery; some could not differentiate it in terms of workflow. The purpose of DialysisConnect (communal specification) was viewed as fully coherent only for communicating outside of the same healthcare system. Current system workarounds were acknowledged as deterrents for practice change. All groups delegated DialysisConnect tasks (individual specification) to personnel besides themselves. Partial internalization of DialysisConnect was achieved only by dialysis clinic staff, based on experience with similar technology. CONCLUSIONS: Implementing DialysisConnect for clinical users in both settings will require presenting a composite picture of current communication processes from all stakeholder groups to correct single-group misunderstandings, as well as providing data about care transitions communication beyond the local context to ease resistance to practice change.

BACKGROUND: Both dialysis facilities and hospitals are accountable for 30-day hospital readmissions among U.S. hemodialysis patients. We examined the association of post-hospitalization processes of care at hemodialysis facilities with pulmonary edema-related and other readmissions. METHODS: In a retrospective cohort comprised of electronic medical record (EMR) data linked with national registry data, we identified unique patient index admissions (n = 1056; 2/1/10-7/31/15) that were followed by ≥3 in-center hemodialysis sessions within 10 days, among patients treated at 19 Southeastern dialysis facilities. Indicators of processes of care were defined as present vs. absent in the dialysis facility EMR. Readmissions were defined as admissions within 30 days of the index discharge; pulmonary edema-related vs. other readmissions defined by discharge codes for pulmonary edema, fluid overload, and/or congestive heart failure. Multinomial logistic regression to estimate odds ratios (ORs) for pulmonary edema-related and other vs. no readmissions. RESULTS: Overall, 17.7% of patients were readmitted, and 8.0% had pulmonary edema-related readmissions (44.9% of all readmissions). Documentation of the index admission (OR = 2.03, 95% CI 1.07-3.85), congestive heart failure (OR = 1.87, 95% CI 1.07-3.27), and home medications stopped (OR = 1.81, 95% CI 1.08-3.05) or changed (OR = 1.69, 95% CI 1.06-2.70) in the EMR post-hospitalization were all associated with higher risk of pulmonary edema-related vs. no readmission; lower post-dialysis weight (by ≥0.5 kg) after vs. before hospitalization was associated with 40% lower risk (OR = 0.60, 95% CI 0.37-0.96). CONCLUSIONS: Our results suggest that some interventions performed at the dialysis facility in the post-hospitalization period may be associated with reduced readmission risk, while others may provide a potential existing means of identifying patients at higher risk for readmissions, to whom such interventions could be efficiently targeted.

RATIONALE & OBJECTIVE: Suboptimal care coordination between dialysis facilities and hospitals is an important driver of 30-day hospital readmissions among patients receiving dialysis. We examined whether the introduction of web-based communications platform (DialysisConnect) was associated with reduced hospital readmissions. STUDY DESIGN: Pilot pre-post study. SETTING & PARTICIPANTS: A total of 4,994 index admissions at a single hospital (representing 2,419 patients receiving dialysis) during the study period (January 1, 2019-May 31, 2021). INTERVENTION: DialysisConnect was available to providers at the hospital and 4 affiliated dialysis facilities (=intervention facilities) during the pilot period (November 1, 2020-May 31, 2021). OUTCOMES: The primary outcome was 30-day readmission; secondary outcomes included 30-day emergency department visits and observation stays. Interrupted time series and linear models with generalized estimating equations were used to assess pilot versus prepilot differences in outcomes; difference-in-difference analyses were performed to compare these differences between intervention versus control facilities. Sensitivity analyses included a third, prepilot/COVID-19 period (March 1, 2020-October 31, 2020). RESULTS: There was no statistically significant difference in the monthly trends in the 30-day readmissions pilot versus prepilot periods (-0.60 vs -0.13, P = 0.85) for intervention facility admissions; the difference-in-difference estimate was also not statistically significant (0.54 percentage points, P = 0.83). Similar analyses including the prepilot/COVID-19 period showed that, despite a substantial drop in admissions at the start of the pandemic, there were no statistically significant differences across the 3 periods. The age-, sex-, race-, and comorbid condition-adjusted, absolute pilot versus prepilot difference in readmissions rate was 1.8% (-3.7% to 7.3%); similar results were found for other outcomes. LIMITATIONS: Potential loss to follow-up and pandemic effects. CONCLUSIONS: In this pilot, the introduction of DialysisConnect was not associated with reduced hospital readmissions. Tailored care coordination solutions should be further explored in future, multisite studies to improve the communications gap between dialysis facilities and hospitals.

BACKGROUND: We piloted a web-based, provider-driven mobile app (DialysisConnect) to fill the communication and care coordination gap between hospitals and dialysis facilities. OBJECTIVE: This study aimed to describe the development and pilot implementation of DialysisConnect. METHODS: DialysisConnect was developed iteratively with focus group and user testing feedback and was made available to 120 potential users at 1 hospital (hospitalists, advanced practice providers [APPs], and care coordinators) and 4 affiliated dialysis facilities (nephrologists, APPs, nurses and nurse managers, social workers, and administrative personnel) before the start of the pilot (November 1, 2020, to May 31, 2021). Midpilot and end-of-pilot web-based surveys of potential users were also conducted. Descriptive statistics were used to describe system use patterns, ratings of multiple satisfaction items (1=not at all; 3=to a great extent), and provider-selected motivators of and barriers to using DialysisConnect. RESULTS: The pilot version of DialysisConnect included clinical information that was automatically uploaded from dialysis facilities, forms for entering critical admission and discharge information, and a direct communication channel. Although physicians comprised most of the potential users of DialysisConnect, APPs and dialysis nurses were the most active users. Activities were unevenly distributed; for example, 1 hospital-based APP recorded most of the admissions (280/309, 90.6%) among patients treated at the pilot dialysis facilities. End-of-pilot ratings of DialysisConnect were generally higher for users versus nonusers (eg, I can see the potential value of DialysisConnect for my work with dialysis patients: mean 2.8, SD 0.4, vs mean 2.3, SD 0.6; P=.02). Providers most commonly selected reduced time and energy spent gathering information as a motivator (11/26, 42%) and a lack of time to use the system as a barrier (8/26, 31%) at the end of the pilot. CONCLUSIONS: This pilot study found that APPs and nurses were most likely to engage with the system. Survey participants generally viewed the system favorably while identifying substantial barriers to its use. These results inform how best to motivate providers to use this system and similar systems and inform future pragmatic research in care coordination among this and other populations.