Pandemic Lessons: qualitative analysis hospital pharmacy

This post explains what the study "Additional file 1 of Crisis management in Finnish hospital pharmacies during the COVID-19 pandemic" found and how AI-enabled qualitative research can make those findings faster, more reliable, and actionable for researchers and hospital leaders. The primary keyword for this post is qualitative analysis hospital pharmacy. The study used a national cross-sectional survey sent to all hospital pharmacy heads in October–November 2020 and follow-up interviews in March–May 2021, so readers who run health system research, UX for clinical teams, or supply-chain evaluations will find practical next steps and tool suggestions here.

Key Takeaways

According to the study "Additional file 1 of Crisis management in Finnish hospital pharmacies during the COVID-19 pandemic" (Latonen et al., 2025) the pandemic exposed gaps in preparedness but also clear operational responses that can be analyzed and scaled with AI-enabled qualitative methods. The study surveyed all 21 hospital pharmacy heads in October–November 2020 and used six follow-up interviews in March–May 2021 to triangulate findings.

57% response rate (n = 12) to the national survey sent in October–November 2020, according to Latonen et al., 2025.
Risk perception about pharmaceutical supply chain crisis rose from 58% to 100% after the pandemic onset, according to Latonen et al., 2025.
Only 4 pharmacies (25%) had a pre-existing pandemic plan in place in October–November 2020, and 7 pharmacies (58%) developed a new plan, according to Latonen et al., 2025.
Changes were common: internal communication and management changed in 92% of responding pharmacies, and clinical pharmacy services changed in 67%, according to Latonen et al., 2025.
The study concluded, "Preparedness of hospital pharmacies could be improved with pre-established crisis teams and plans, and data management systems providing easily accessible information to support decision-making, " (Latonen et al., 2025).

What Happened: study design and core findings

Answer: The study combined a national survey and interviews to map crisis management in Finnish hospital pharmacies during COVID-19.

According to the study "Additional file 1 of Crisis management in Finnish hospital pharmacies during the COVID-19 pandemic" (Latonen et al., 2025), the authors sent a cross-sectional survey to all hospital pharmacy heads (n = 21) in October–November 2020 and achieved a 57% response rate (n = 12).

According to Latonen et al., 2025, the authors then conducted six purposive semi-structured interviews in March–May 2021 to triangulate and enrich the survey data.

According to Latonen et al., 2025, key numeric findings included a rise in perceived supply-chain risk from 58% to 100%, pre-existing pandemic plans in 4 pharmacies (25%), new plans developed in 7 pharmacies (58%), establishment of pandemic crisis teams in 4 pharmacies (33%), and operational changes such as internal communication shifts in 92% of pharmacies.

Findings Snapshot

Date	Metric	Value	Implication
October–November 2020	Survey sample invited	n = 21 hospital pharmacy heads	Full-population survey frame for Finnish hospital pharmacies
October–November 2020	Response rate	57% (n = 12)	Findings represent a majority but not all hospital pharmacies
After pandemic onset (reported in 2020)	Perceived supply-chain risk	Rose from 58% to 100%	Uniform recognition of supply-chain crisis across respondents
October–November 2020	Pre-existing pandemic plans	4 pharmacies (25%)	Most pharmacies lacked pre-established plans
March–May 2021	Follow-up interviews	n = 6 semi-structured interviews	Qualitative triangulation to validate survey themes

Implications for hospital pharmacy researchers and managers

Answer: The study shows concrete gaps that researchers and managers should measure and address: crisis teams, plans, and data systems.

According to Latonen et al., 2025, preparedness was uneven because only 25% of pharmacies had pre-existing pandemic plans in October–November 2020, so researchers should prioritize measuring plan existence and plan activation timestamps in comparative studies.

According to Latonen et al., 2025, information flow was unequal and respondents reported "an unequal distribution of medicines and crisis management-related information, " so managers should instrument communication channels and supply dashboards to track equity in distribution.

According to Latonen et al., 2025, collaboration with peers improved in 9 pharmacies (75%) but decreased or remained unchanged in 3 pharmacies (25%), so evaluations of networked responses should be part of future crisis readiness research.

How Evidano Helps

Problem: survey open-text answers and interview transcripts are slow to synthesize

Answer: Evidano accelerates synthesis by auto-coding and surfacing themes across documents and segments.

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

Evidano automates deductive content analysis templates so teams can apply crisis management process models (as Latonen et al., 2025 did) across many transcripts and open-text fields, producing frequency tables and cross-segment comparisons in minutes rather than weeks. See the Evidano features page for capabilities.

Problem: inconsistent terminology between sites delays synthesis

Answer: Evidano handles custom dictionaries and translation to normalize terms across sites.

Evidano supports custom dictionaries and translation workflows so that terms like "pandemic plan", "reserve stockpile", and local drug names map to consistent codes, enabling reliable counts of, for example, how many sites had pre-existing plans (25% in the Finnish study, according to Latonen et al., 2025).

Problem: leaders need quick, auditable evidence for decision-making

Answer: Evidano produces auditable codebooks, exportable tables, and visualizations to justify operational changes.

Evidano generates thematic frequency tables, co-occurrence networks, and segment cross-tabs so hospital leaders can show that internal communication changed in 92% of sites and that clinical services changed in 67%, matching the numeric findings reported by Latonen et al., 2025.

FAQ: qualitative analysis hospital pharmacy

What methods did the Finnish hospital pharmacy study use?

Answer: The study combined a national cross-sectional survey with deductive content analysis and six follow-up interviews.

According to Latonen et al., 2025, the authors surveyed all 21 hospital pharmacy heads in October–November 2020 (response rate 57%, n = 12) and used deductive content analysis on open-ended survey responses with triangulation from six semi-structured interviews conducted in March–May 2021.

What are the most important numeric findings from the study?

Answer: Key numbers are a 57% survey response rate, a perceived supply-chain risk rise from 58% to 100%, and only 25% of pharmacies having pre-existing plans.

According to Latonen et al., 2025, additional numeric details include 7 pharmacies (58%) developing new plans, pandemic crisis teams in 4 pharmacies (33%), and operational changes such as internal communication in 92% and clinical pharmacy services in 67%.

How can AI-enabled qualitative research improve pandemic preparedness research?

Answer: AI-enabled qualitative research scales code application, speeds triangulation, and produces auditable frequency and cross-segment outputs.

According to the methods used by Latonen et al., 2025, researchers who apply process-model-driven code frames can use AI to consistently code large open-text datasets, reproduce the deductive approach the study used, and generate the dashboards that managers need to monitor plan adoption and communication changes across sites.

Can the study findings be generalized beyond Finland?

Answer: Generalization is limited because the study surveyed 21 Finnish hospital pharmacies with a 57% response rate and used purposive interviews.

According to Latonen et al., 2025, the authors framed the work as context-specific and recommended that other systems replicate the process-model-based survey instrument and triangulation steps to test applicability elsewhere.

Conclusion & Next Steps

Answer: The Finnish study provides concrete, quantifiable gaps in preparedness that AI-enabled qualitative analysis can help close by speeding synthesis and producing auditable outputs.

According to Latonen et al., 2025, gaps included that only 25% of hospital pharmacies had pre-existing pandemic plans in October–November 2020 and that risk perception rose to 100% after the pandemic onset, which creates a clear measurement agenda for future work.

If you run qualitative research or manage clinical supply chains, start by reusing the study's process-model survey frame and applying AI-assisted coding to open-text fields to get rapid, defensible counts and themes.

To try these workflows on your own transcripts and surveys, Try Evidano for free.

Topics

qualitative analysis hospital pharmacy
hospital pharmacy COVID-19 qualitative
AI-enabled qualitative research
crisis management hospital pharmacy

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