Practical Steps: Interprofessional Learning in Hospitals

Interprofessional learning in hospitals is the structured and informal process by which nurses, physiotherapists, and other clinicians learn with, from, and about each other to improve collaboration and patient care. Hospital managers, clinical educators, and applied researchers need concrete, research-backed steps to identify how workplace conditions help or hinder IPL and to measure IPL outcomes. The primary keyword for this post is interprofessional learning in hospitals, and the payoff is practical guidance: use thematic, frequency, and cross-segment qualitative analysis to convert interviews, ward observations, and meeting notes into prioritized, organization-specific interventions. The rest of this post refracts the scoping review by Åhlund et al. in PLOS One through the lens of AI-enabled qualitative research methods so teams can detect facilitators and barriers and track progress over time.

Key Takeaways

The short answer: the PLOS One scoping review shows that interprofessional learning in hospitals succeeds when organizational structures enable regular interaction, inclusive team cultures exist, and leadership supports collaboration, and those conditions are measurable with qualitative methods, according to Åhlund et al. in PLOS One.

Åhlund et al. in PLOS One published the review on August 7, 2026 and included 11 empirical studies after screening 1, 973 titles and abstracts in a systematic search completed in July 2026.
According to PLOS One, 10 out of 11 included studies used qualitative interviews (91%) and the samples in the included studies ranged from 18 to 333 participants, providing diverse clinician and student perspectives.
According to PLOS One, facilitators clustered as: socialization/familiarization (reported in 6 studies), positive team climate (5 studies), and conducive organizational structures (10 studies).
According to PLOS One, barriers clustered as: limited structural prerequisites (5 studies), constrained interprofessional interactions (4 studies), and non-conducive workplace culture (5 studies).

What happened and how the PLOS One review worked

This section explains who did the review, what they searched for, and how they summarized the evidence so you can apply the same measures locally.

Åhlund et al. in PLOS One registered a protocol on OSF and searched PubMed, CINAHL, and Scopus from inception to July 2026, which the authors report in their Methods.

Åhlund et al. in PLOS One reported that the database searches initially returned 2, 206 records, that 1, 973 unique titles and abstracts were screened after duplicates were removed, that 33 full texts were reviewed, and that 11 empirical peer-reviewed articles met inclusion criteria.

Åhlund et al. in PLOS One reported that the included studies were published between 2009 and 2022 and that the most common study design among the included articles was qualitative interviews (10 of 11 studies, 91%), with field observations present in 5 studies (46%) and surveys in 3 studies (27%).

Åhlund et al. in PLOS One coded facilitators and barriers into themes through collaborative charting and narrative synthesis, which produced three facilitator themes and three barrier themes that hospitals can operationalize as measurable constructs.

Findings Snapshot

Date / Source	Metric	Value (from PLOS One)	Implication for hospital teams
August 7, 2026 / PLOS One	Studies included	11 empirical articles	Modest evidence base, suitable for qualitative program evaluation
July 2026 / PLOS One	Records screened	1, 973 titles and abstracts	Comprehensive search supports transferability of themes
2009–2022 / PLOS One	Study years	All included studies published between 2009 and 2022	Trends may predate telehealth and pandemic-driven team changes; re-evaluate locally
PLOS One synthesis	Most common methods	Interviews (10/11, 91%), observations (5/11, 46%), surveys (3/11, 27%)	Combine interviews and observations when auditing IPL locally
PLOS One thematic result	Top facilitator theme	Conducive organizational structures (reported in 10 studies)	Leadership and scheduling are high-leverage intervention points

Implications for clinical educators and hospital researchers

How should clinical educators prioritize changes?

Prioritize organizational structures and leadership support first, because PLOS One found conducive organizational structures in 10 of the 11 included studies and the authors highlight leadership as pivotal.

Design interventions that create regular shared planning time, co-located spaces, and supervisor-led interprofessional activities, because PLOS One identifies shared physical spaces and clinical supervisors as concrete enablers of IPL.

What measures should researchers collect in ward-level IPL audits?

Measure both process and perception: collect documented joint assessments/rounds, frequency of interprofessional meetings, and staff reports of team climate, because PLOS One shows that socialization, team climate, and organizational structures are distinct actionable themes.

Combine qualitative interviews, short surveys, and structured observations, because PLOS One reports that 91% of included studies used interviews and 46% used observations, making mixed qualitative methods a validated approach.

How urgent is addressing IPL for patient safety?

Address IPL as a medium-term patient safety priority, because Åhlund et al. in PLOS One link IPL to sustained team knowledge and cite broader evidence that interprofessional collaboration is associated with improved safety outcomes.

Make cultural and structural changes resilient to staff turnover, because PLOS One explicitly recommends organizational structures that preserve IPL despite changing staff.

How Evidano Helps

Problem: Unstructured qualitative data makes IPL hard to measure → Solution: rapid thematic analysis

Evidano is an AI-powered qualitative data analysis platform that helps researchers analyze interviews, open-ended surveys, and documents.

Evidano extracts themes, quotes, and frequency counts from interview transcripts and observation notes, which matches the PLOS One recommendation to use interviews and observations to identify facilitators and barriers.

Evidano's thematic coding and hierarchical code maps let you operationalize the PLOS One themes (socialization, team climate, organizational structure) into codebooks that clinical teams can reuse across wards, and you can learn more on the Evidano features page.

Problem: Time-consuming transcription and PII handling → Solution: secure speech-to-text

Evidano's transcription tools accelerate conversion of ward interviews and learning reflections into searchable text, which addresses PLOS One's finding that interviews are the dominant data source in IPL studies.

Evidano's transcription supports custom dictionaries for clinical terms and PII redaction so that clinical researchers can comply with local privacy rules while coding transcripts, see Evidano speech-to-text.

Problem: Hard to compare subgroups (nurses vs physiotherapists) → Solution: cross-segment analysis

Evidano performs cross-segment analyses so you can compare themes, sentiment, and quote frequency between nurses and physiotherapists, aligning with the PLOS One focus on both professions being represented in included studies.

Evidano's co-occurrence networks and exportable codebooks let educators quantify how often 'joint rounds', 'shadowing', or 'shared space' appear in each subgroup, producing the kind of evidence hospital leaders need to act on PLOS One findings.

FAQ: interprofessional learning in hospitals

What is interprofessional learning in hospitals?

Interprofessional learning in hospitals is when clinicians from different professions learn with, from, and about one another to improve collaboration and patient care, as defined and discussed by Åhlund et al. in PLOS One.

The PLOS One review frames IPL as workplace learning that occurs through socialization, joint clinical activities, and organizational practices that make interaction possible.

Which organizational changes most reliably support IPL?

Make it possible for teams to meet regularly, co-locate staff, and empower leaders to schedule joint planning, because PLOS One reports conducive organizational structures in 10 of 11 studies as a top facilitator.

Operationalize these changes by tracking meeting frequency, shared rounds, and supervisor-facilitated interprofessional activities using qualitative logs and short process metrics.

How can I measure IPL improvement over time with limited resources?

Use a repeatable qualitative protocol: brief semi-structured interviews, short ward observations, and a 5-question climate survey, because PLOS One indicates that interviews plus observations capture the core themes effectively.

Apply AI-enabled coding to speed analysis and extract verbatim quotes that illustrate change, then track theme frequency and co-occurrence across months.

Can AI tools bias qualitative interpretations of IPL?

AI tools can introduce bias if codebooks and dictionaries are not validated by domain experts, so always combine automated coding with human review, as best practice endorsed in qualitative research methods and consistent with the transparency aims of the PLOS One review.

Evidano supports custom codebooks and manual overrides so teams retain interpretive authority while using automation to scale synthesis.

Conclusion & Next Steps

The PLOS One scoping review by Åhlund et al. shows that interprofessional learning in hospitals depends mainly on actionable organizational structures, team climate, and everyday socialization opportunities.

Hospitals and clinical educators should audit current practices using interviews, observations, and short surveys, and then convert those data into prioritized interventions such as regular joint planning, co-located spaces, and supervisor-led IPL activities, following the themes reported in PLOS One.

For teams that want to accelerate analysis, Evidano can extract themes, quotes, and cross-segment comparisons from your interviews and observations and produce visualizations and exportable codebooks to guide implementation; learn more on the Evidano features page.

If you want to pilot an AI-enabled qualitative audit of IPL on one ward, Try Evidano for free.

Topics

interprofessional learning in hospitals
interprofessional learning
IPL in clinical practice
qualitative analysis of IPL

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Practical Steps: Interprofessional Learning in Hospitals

Key Takeaways

What happened and how the PLOS One review worked

Findings Snapshot

Implications for clinical educators and hospital researchers

How should clinical educators prioritize changes?

What measures should researchers collect in ward-level IPL audits?

How urgent is addressing IPL for patient safety?

How Evidano Helps

Problem: Unstructured qualitative data makes IPL hard to measure → Solution: rapid thematic analysis

Problem: Time-consuming transcription and PII handling → Solution: secure speech-to-text

Problem: Hard to compare subgroups (nurses vs physiotherapists) → Solution: cross-segment analysis

FAQ: interprofessional learning in hospitals

What is interprofessional learning in hospitals?

Which organizational changes most reliably support IPL?

How can I measure IPL improvement over time with limited resources?

Can AI tools bias qualitative interpretations of IPL?

Conclusion & Next Steps

Topics

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