In general, results were characterised by high heterogeneity between the analysed hospitals in all categories. Especially general surveillance organisation, access to digital data sources and software configuration varied not only between hospitals of different care levels, but also between hospitals in the same care level. Table 1 shows a tabular summary of the interview statements in each category.

Table 1 Summary of the interview statementsParticipants’ background (occupation and type of hospital)

Eight individuals from seven different hospitals or hospital networks were interviewed.

All interviewees were physicians or nurses who had received special training in infection prevention and control (IPC). They were employed in hospitals across the entire range of care levels: Four of the interviewees worked at a university hospital (care level III). One person worked at a contract hospital, two interviewees were in charge of several hospitals within a hospital network of care levels I and II. Another person worked for a hospital providing specialised care (care level II).

Current general surveillance organisation

All participants reported that most surveillance at their sites was either based on or at least partially based on the criteria of the Krankenhaus-Infektions-Surveillance System (Hospital-Infection-Surveillance System) “KISS” of the German national reference centre for surveillance of nosocomial infections (NRZ) [16]. The choice of modules differed between all locations, but most commonly focused on high-risk areas: apart from legally required surveillance for multi-drug resistant organisms, modules for intensive care units (ITS-KISS) and surgical site infection (SSI)-surveillance (OP-KISS) were mentioned most frequently. Some participants used the definition provided in the modules but did not transfer surveillance data to the NRZ.

Most interviewees confirmed the pre-assumption that surveillance was in large parts still dominated by manual, labour-intensive tasks - even when supported by specialised software. Especially in hospitals of lower care-levels, surveillance was often not digitalised at all but still paper-based. In addition, in-house solutions which were, for example, based on excel spreadsheets, were still frequently used. Contrarily, the surveillance process in more digitalised hospitals was often impaired by a multitude of subsystems where data for surveillance purposes could be sourced in combination with a lack of data integration in a centralised surveillance system.

The group of persons entrusted with collecting data, that was required for surveillance (depending on availability digital structured data, digital unstructured data or paper based documents), varied between and within hospitals. In most cases, either IPC nurses or clinicians in the wards conducted data collection. Hospitals of the care levels I and II were more often outsourcing data collection directly to the wards. In contrast, IPC nurses usually carried out data collection in tertiary care hospitals. Physicians with special training in infection control usually took up a more supervisorial role and the evaluation of cases.

Most time consuming steps during the surveillance process

The statements on most time consuming steps varied with the level of digitalisation in the participants’ hospitals. Especially personnel in less digitalised hospitals reported the frequent need for further inquiries with clinicians on the wards. Information required for the surveillance activities was oftentimes not digitally registered and accessible by IPC professionals but rather available paper-based on the respective wards.

Collection of data used for surveillance purposes from different sources was deemed especially time-consuming. This presented an issue regardless of the level of digitalisation: in hospitals with less digital data sources, participants needed to physically gather or look up documents at the sites they needed to conduct surveillance. In more digitalised hospitals, data was spread throughout different subsystems.

The actual review of the collected data and identification of cases was deemed very time consuming as well. This was in large parts accomplished by manual chart review (either in a HIS or paper based). No automatic or semi-automatic systems for identification or preselection of cases or any other surveillance purposes was routinely utilised in clinical practice.

Data availability/Access to digital data sources

The combination of HIS, LIS, PDMS and (if available) electronic surveillance systems varied between all hospitals. No two hospitals shared the same combination of software systems. Most, but not all, interviewees had access to digital patient- related data. Not all hospitals had implemented electronic medical records, yet. In addition, PDMS usually differed between normal wards and intensive care units within the same hospitals.

HIS and PDMS software that were already implemented and mentioned during the interviews were: SAP® i.s.h.med® (Oracle Cerner Corporation, North Kansas City, Missouri, United States), Orbis (Dedalus Healthcare Group AG, Bonn, Germany), medico® (CompuGroup Medical SE & Co. KGaA, Koblenz, Germany), Soarian® (CompuGroup Medical SE & Co. KGaA, Koblenz, Germany), MEONA (Mesalvo GmbH, Freiburg, Germany), Dräger ICM (Drägerwerk AG & Co. KGaA, Lübeck, Germany) and COPRA (COPRA System GmbH, Berlin, Germany).

Problems with data integration were a recurring pattern in all care and digitalisation levels.

Inconsistent documentation and registration practices, even inside the same software solution, further complicated data collection. IPC professionals had to extract data from different (free- text) fields or documents inside the respective HIS, LIS and PDMS systems. Relevant information for surveillance purposes was sometimes buried between different diagnoses in free-text fields or unstructured physician’s letters.

While the majority of interviewees had access to some sort of digital microbiological data, access ways and data quality differed between locations. Employees of university clinics (care level III) with own affiliated laboratories could usually access structured data directly from the LIS or via specialised software for infection control (with an interface to the LIS).

Employees in non-university hospitals without own laboratories faced additional challenges as they received data they then had to integrate from multiple different external laboratories (and therefore laboratory information systems). Access to external laboratory data was sometimes only possible via unstructured PDF-documents.

Software specifically for infection control (including intentions and impediments for implementation of software specifically for infection control)

In many of the hospitals in this study software solutions specifically for surveillance are already in place. The most frequently utilised software mentioned by the interviewees was HyBASE (epiNET GmbH, Bochum, Germany). In two locations the future implementation of infection control software by the manufacturer of the respectively used hospital information system was planned but not yet implemented (IPSS (CompuGroup Medical SE & Co. KGaA, Koblenz, Germany), Orbis infection management (Dedalus Healthcare Group AG, Bonn, Germany)). One location neither had software implemented nor planned to implement any in the next five years. The participants mentioned a number of reasons that currently delay or impede the implementation of new surveillance software: Half of the participants mentioned financial reasons for an impediment of the implementation of specialised software for infection control. This was followed by a lack of personnel to implement and maintenance the software (three participants). Other reasons mentioned were: lack of quality of the offered solutions (three participants), lack of trust in data quality, possible breakdown risk, lack of support or understanding of infection control issues of the local IT-department.

Where specific software is already used to aid infection control, experiences and perceived usefulness for clinical practice spanned from very useful to unusable. While some interviewees reported that they use the software on a daily basis (despite an initial high learning curve) and had them integrated in their workflows others stated the software had been purchased and installed but could not be properly utilised because of interoperability issues or lack of maintenance. Apart from access-databases or excel spreadsheets only commercial solutions were implemented.

Outside of research projects, neither fully automatic software nor solutions utilising artificial intelligence have currently been implemented in clinical routine in any of the locations that took part in this study.

Future suggestions for improvement

The healthcare workers openly expressed the need for different kinds of improvements during the interviews in connection with automation and software for their surveillance activities:

When software was already available at their location, but not properly functioning, these participants wished for a properly functioning surveillance solution that is maintained adequately.

Interview partners mostly reported problems with interfaces to either the HIS (incomplete import of data from the HIS and operation- management software) or missing interfaces for the import of laboratory data.

Where software was already implemented, some participants also wished for an extension of the current functionality (e.g. acquisition of additional modules).

In contrast, in locations without software specifically for infection prevention participants rather obviously wished for the implementation of a software solution that merges the diverse data systems into one comprehensive surveillance platform. Another functionality the interviewees were looking for were alert systems, which alerted them of clusters or infections.