Abstract Background and Aims For many years, dialysis data have been manually registered and transferred to the patients’ electronic health records by dialysis staff. However, manual documentation can be associated with poor data completeness, delayed recognition of inadequate dialysis prescriptions, and high staff workload. We studied the effect of introducing a new integrated, digitalized haemodialysis surveillance system, the Treatment Guidance System (TGS), on staff workload and time saving in clinics from a large multi-national dialysis provider. To measure the effect of introducing the new TGS system on staff workload and time saving. Method This was a prospective, observational multicenter study conducted between November 2021 and January 2023 in five countries: Saudi Arabia, Spain, Portugal, UK, and Kazakhstan. Inclusion criteria were clinics with adequate digital infrastructure, introducing the TGS. Only staff without prior experience with TGS were included in this study. Staff workload was determined using the NASA Task Load Index (TLS) at three timepoints: 1: two weeks prior to introduction of the TGS, 2: one month after introduction of the TGS, and 3: three months after introduction of the TGS. Time saving was determined by observation of the time used for dialysis data documentation by an independent person at timepoints 1 and 3. Differences in staff workload were determined by Friedman's two-way analysis of variance by ranks with Bonferroni correction for multiple tests, while time saving was determined by Wilcox signed rank test. Results In total, 223 participants from 20 clinics were included in the study, 56% were female, age distribution was 32.1% <30 years, 58.8% 30-49 years, and 9.1% ≥50 years, and dialysis experience was 17.5% ≤2 years, 27.9% 2-5 years, 33.3% 5-10 years, and 21.2% >10 years. The staff adaptability to the introduction of TGS at their workplace and the workload perception improved significantly over all domains of the NASA TLS (Table 1). While most domains improved by approximately 50%, median physical demand improved by more than 60% (Table 1). There was some variation of the observed time used for documentation between different countries, however, the observed time decreased in all countries from median (25-75%) 9:35 (5:36-14:41) minutes at timepoint 1 to 5:22 (2:05-9:22) minutes at timepoint 3 (p < 0.001). The largest saving was noted in the United Kingdom (14:06 (11:01-18:25) to 5:17 (4:56-5:45) minutes), while the smallest saving was noted in Kazakhstan, where only 3 individuals were observed (3:37 to 3:08). Conclusion Introduction of the novel, digitalized, integrated real-time dialysis documentation system TGS greatly reduced staff workload and time spent with documentation of dialysis treatments. Digitalization and automation of haemodialysis treatment has the potential to improve dialysis treatment, which will be further elucidated by the analysis of data quality and completeness in the current study.
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May 31, 2024
Taha Abbasi-Hashemi + 3
Open Access