Standardizing the digital frontier: A Nordic survey of remote patient management practice patterns and variations in peritoneal dialysis care

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Welcome to AudioScholar. Today we're covering Standardizing the digital frontier: A Nordic survey of remote patient management practice patterns and variations in peritoneal dialysis care, by Dai and colleagues, published in Peritoneal Dialysis International: Journal of the International Society for Peritoneal Dialysis.

Remote patient management in automated peritoneal dialysis gives clinical teams near real-time access to ultrafiltration volumes, alarms, blood pressure and weight. The authors cite a cluster-randomized trial linking it to lower mortality and fewer hospitalizations. They argue that real-world use remains inconsistent, with no consensus on how often data should be reviewed or how teams should act on it. This study set out to map how Nordic clinicians actually use these platforms and where standardization could help.

This was a cross-sectional survey of nephrologists and renal nurses at peritoneal dialysis clinics in Sweden, Denmark, Norway and Finland. It used a thirteen-item questionnaire on the Sharesource platform, which is made by the study's funder, Vantive. The survey went to 192 clinicians across 85 clinics. Sixty clinicians responded, covering 49 clinics. Nurses made up about three in five respondents. The primary aim was descriptive: to characterize current practice and identify opportunities for standardization. Most analyses were frequencies, with some comparisons between nurses and physicians.

Almost everyone saw the value of these platforms. Over ninety percent of respondents said remote monitoring helps catch ultrafiltration or catheter problems early, and no respondent said it does not. Yet fewer than half of respondents reported a standardized protocol at their clinic. About a third reported no protocol, and a fifth were unsure whether one existed. Protocol availability also varied by country, from about a quarter of Swedish respondents to roughly three quarters of Norwegian respondents.

The sharpest finding was the split between professions. Nearly two thirds of nurses reviewed treatment data at least twice a week. No physician reported reviewing it that often. Roughly four in five physicians looked at the data only during routine clinic visits or not at all, and close to two in five physicians never reviewed it. Despite this, about two thirds of respondents rated a standardized protocol as very or extremely important. Nearly two thirds of respondents were open to joining a work group on optimizing its use.

The authors list several limitations. First, they note the modest sample and purposive sampling, which excluded centres with fewer than five patients or no involvement with remote monitoring. That may introduce selection bias, so the picture may not apply to smaller or less digitally experienced units. Second, the questionnaire was built for this study and was not formally validated or pilot tested. Without established reliability, readers cannot be sure each question measured what it intended. Third, the authors note a response rate of about thirty-one percent. In a survey on technology use, clinicians who skip the survey may differ systematically from those who answer. Finally, they state the study was not powered to examine how program size, staffing or workflow relate to adoption.

Before we close, where the authors go from here. They call for larger, adequately powered multicentre studies with broader sampling. These studies should examine the organizational, cultural and resource-related factors behind adoption. The authors also call for a collaborative effort to build protocol-driven pathways with continuous training. Peritoneal dialysis program leads, and nurses and nephrologists designing remote monitoring workflows, will want the full paper and its supplementary country data in hand.

That's your AudioScholar summary. The full transcript and reference are on the episode page. Until next time.

This is an automated summary generated by artificial intelligence, which can make mistakes. Always review the original source materials.