The work focused on Hospital Clínic de Barcelona, a predominantly adult tertiary hospital with limited pediatric services. Because notification rules in Spain and Catalonia include both communicable and some noncommunicable conditions, the investigators included every notifiable-disease episode reported at the hospital during the three-month period, rather than selecting diseases in advance. The sample covered 25 conditions grouped into 10 categories, including sexually transmitted infections, mosquito-borne diseases, respiratory infections, hepatitis, zoonoses and asthma. Of the analyzed episodes, 173 involved males, 110 females and one person whose sex was recorded as unknown. Median age was 42 years, with an interquartile range of 25 years. One episode with no information in the clinical record was excluded from subsequent analyses, leaving 283 for assessment by healthcare setting and document type.

Sexually transmitted diseases formed the largest notified group, accounting for 73 episodes, or 25.8%. Most notifications originated in the outpatient clinic, which accounted for 145 episodes, or 51.2%; 96, or 33.9%, came from the emergency room and 42, or 14.8%, from hospital care. Medical doctors reviewed whether sufficient information was available on the reporting date to justify notification under Catalonia’s public health criteria. They classified 210 episodes, representing 74.2%, as adequately suspected and 73, or 25.8%, as inadequate. The investigators also calculated the interval between the first appearance of suspicion in the electronic health record and the actual report.

Among the adequately notified episodes for which relevant records could be identified, 170 were subsequently confirmed as having the reported condition. Thirty-three episodes, equal to 15% of the adequately notified group, had been reported before suspicion was recorded in the electronic health record and were excluded from the delay calculation. Among the remaining 177 episodes, the median delay was zero days and the interquartile range was three days. Sixty-two percent were reported on the same day that the first suspicion appeared, but 10% were reported more than two weeks later. The authors said explanations for reports preceding the electronic record, such as telephone calls or internal messages, remained hypotheses because the original notification source had not been registered.

The leading cause of inadequate reporting was the treatment of a chronic condition as a new reportable event, which explained 34.2% of the 73 inadequate notifications. References to a disease in a patient’s medical history accounted for 26.0%, while disease-related language whose clinical context did not support current suspicion accounted for 23.3%. A further 12.3% lacked supporting information, and 4.1% involved a mismatch between the disease reported and the condition suggested by the available records. Importantly, 83% of inadequate notifications contained at least one term from the disease-specific thesaurus. The results therefore show that the mere presence of a disease word or clinical concept is not enough to establish that an episode warrants notification.

Manual review of six types of electronic health record documents revealed where suspicion-related terms were most likely to appear. When the corresponding document was available, investigators found such terms in 93.0% of hospital discharge notes, 89.0% of unreleased clinical drafts, 84.7% of emergency-room discharge notes, 78.7% of clinical course reports, 63.3% of microbiology reports and 45.4% of laboratory reports. These percentages describe the content of available documents, however, and do not mean that every document type was equally accessible across episodes. Availability differed substantially by healthcare setting and disease group, making the importance of a source depend on where and how a patient was being treated.

The pattern changed markedly across care environments. In emergency-room episodes, emergency-room discharge notes contained suspicion-related information in 85.4% of cases, while unreleased clinical drafts did so in 83.8%. Clinical course reports were less frequent in that setting, and hospital discharge notes and microbiology reports were often unavailable. For hospitalized patients, clinical course reports contained relevant information in every episode in which they were assessed, with additional contributions from hospital discharge notes and unreleased drafts. Outpatient records had a different profile: clinical course reports contained relevant terms in 96.8% of episodes, and laboratory and microbiology reports also contributed, whereas the three other document types were not frequently available. These differences argue against a surveillance tool based on one fixed electronic record source.

Disease group also altered the contribution of each document. Clinical course reports were the most consistently available source, appearing in more than 80% of episodes in every disease group; when available, they contained suspicion-related terms in 81.2% of episodes. Unreleased clinical drafts were present in more than half the episodes of six disease groups and contained relevant terms in 94.8% of those available documents. Emergency-room discharge notes were representative for asthma, exanthematous viral diseases and mumps, and heatstroke, while hospital discharge notes were representative only for respiratory infectious diseases. Microbiology reports were available in at least half the episodes of six groups and contained relevant terms in 81.1% of available reports. Their contribution was particularly prominent for exanthematous viral diseases and mumps, foodborne and waterborne diseases, mosquito-borne diseases, and sexually transmitted infections.

The authors say the findings point toward a future system that selects document sources according to disease and care pathway, maps variations in language to standardized clinical concepts, and interprets those concepts in context rather than treating them as isolated keywords. A system would need to distinguish active suspicion from chronic disease, past history, negation and contextual mentions that do not support notification. The analysis was performed on raw clinical documentation, retaining abbreviations, misspellings, typographical errors, idiomatic expressions and colloquialisms; investigators manually identified and then standardized concepts for classification. A future system would also need expert review in a human-in-the-loop workflow, particularly because the study found overnotification as well as delays.

This work does not demonstrate that natural language processing or large language models can improve disease surveillance. No automated system was tested, and the researchers could not calculate the sensitivity, specificity or diagnostic performance of a future pipeline. The analysis included only episodes that had already been notified, rather than independently identifying cases that escaped reporting, and it did not include prior notification records needed to verify repeated reports. Its three-month summer sample may underrepresent conditions with different seasonal patterns, while the single hospital setting limits generalizability. Future research would need larger and more representative datasets, automated testing on unprocessed text, and direct measurement of accuracy and reporting time. Even with those limitations, the study offers a concrete starting point: the documents most likely to contain early signals, the conditions that generate false alerts, and the clinical pathways any future surveillance tool would have to understand.

Subject of Research: Evaluation of notifiable-disease reporting and clinical documents for future NLP-assisted hospital surveillance

Article Title: Setting the basis for a natural language processing tool to improve the reporting of notifiable diseases: a descriptive study

Article References: Cano-Escobar, C., Barón-Miras, L. E., Gualda-Gea, J. J., Frid, S., & Bertran, M. J. (2026). Setting the basis for a natural language processing tool to improve the reporting of notifiable diseases: a descriptive study. Frontiers in Digital Health, 8, Article 1882377. https://doi.org/10.3389/fdgth.2026.1882377

Image Credits: AI Generated

DOI: 10.3389/fdgth.2026.1882377

Keywords: natural language processing, notifiable diseases, public health surveillance, electronic health records, clinical informatics, disease reporting, hospital epidemiology, text mining, Barcelona, Setting, basis, natural

The study was conducted through a German Federal Ministry for the Environment pilot project commissioned by the Federal Agency for Nature Conservation. It applies a national life-satisfaction model to the “visual amenity services” of urban ecosystems, defined in the UN System of Environmental-Economic Accounting as ecosystem contributions to local living conditions through sensory benefits, especially those provided by seeing natural features. The analysis considers only publicly accessible green space near residences. It estimates a hypothetical price for access, allowing the benefits of nearby green to be compared with alternative uses of urban land.

Its empirical foundation is a life-satisfaction analysis by Krekel and colleagues based on approximately 42,000 records from Germany’s Socio-Economic Panel for 2000–2012. Respondents rated their life satisfaction on a scale from 0 to 10, while the analysis also considered age, gender, marital status, health, education and income. The proportion of publicly accessible green space within a one-kilometre radius of each respondent’s home was included in a multicriteria regression. The estimated increase in life satisfaction associated with more green space was compared with the income increase associated with the same reported improvement, yielding an estimated marginal willingness to pay for an additional hectare.

The researchers distinguish the study’s life-satisfaction method from hedonic pricing analysis, which derives preferences for amenities from property-price differences. A comparison of two German studies using the same general one-kilometre green-space indicator found that hedonic estimates were only about one thirty-eighth to one one-hundred-and-twenty-fourth of the life-satisfaction estimates. A market-simulation model suggested that features of real-estate markets—including incomplete information, high transaction costs, short-term constraints on supply and equity preferences—may cause property prices to capture only part of green space’s association with life satisfaction. The present study therefore uses the Life Satisfaction Method, classified within the accounting framework as a simulated exchange-value approach.

For the national extrapolation, the researchers replaced the 2006 European Urban Atlas data used in the original analysis with the ATKIS Basis-DLM geodata in the IOER Monitor version. This dataset covers all of Germany rather than only its most urbanised regions and can use more precise cadastral information in settlements. The green-space measure includes woody vegetation, woodland, meadow and pasture, parks and other publicly accessible green space, sports, leisure and recreation areas, and cemeteries. This broader definition includes forests and agricultural grassland near settlements that were absent from the earlier Urban Atlas category. Population distribution came from the 2011 census, represented in 100-by-100-metre grid cells containing more than three residents, while the 2012 version of the land data was selected to keep the spatial inputs close in time to the life-satisfaction and census data.

Because both the land database and green-space definition had changed, the original marginal-utility function required adjustment before national extrapolation. The researchers first transformed it linearly to accommodate the higher average green-space supply per person produced by ATKIS data and the additional land classes. They then calibrated it so that an Urban Atlas calculation using the original function and an ATKIS calculation using the adjusted function produced the same total monetary value for the same area. This required reducing the slope of the fitted function. The valid nationwide monetary results come from a two-by-two-kilometre grid analysis; monetary results from a previously published, more detailed 100-by-100-metre analysis were found to be incorrect.

The model reports two different monetary concepts. Accounting-compatible exchange value is the simulated price of an additional, or “last,” unit of green space multiplied by the total area available to a household. Welfare value is the area under the marginal-utility curve and represents the total benefit of all nearby green space. Under normal market conditions, welfare value exceeds exchange value. Where green-space supply exceeds the point at which households are no longer willing to pay for an additional unit, exchange value is zero even though individual welfare value is at its maximum. Such places are generally on urban fringes or outside urban areas, where lower population numbers make the aggregate benefit smaller than in densely settled districts. A separate scarcity indicator multiplies the simulated marginal price by the number of households to show where an additional unit of green could have the greatest aggregate social significance.

In the highest-density cells, the estimated €783,838 per hectare per year corresponds to a one-time present value of €2,613 per square metre when calculated for an indefinite period at a 3% discount rate. Halving the discount rate to 1.5% doubles that one-time value. For comparison, average expenditure for land ready for construction in German cities with more than 500,000 inhabitants was just under €700 per square metre in 2016, the reference year for the monetary estimates. Even the present value of particularly expensive park construction and maintenance, calculated from information used by the earlier study, was about €680 per square metre. In the lowest-density cells, which contain 40% of the population, the green-space estimate averages just under €12 per square metre. This is below the €56 average 2016 sales value of building plots in municipalities with fewer than 2,000 inhabitants and the cited €78 present value for particularly low-cost green provision.

Intermediate-density cells, containing the remaining 30% of the population, have a mean green-space value of approximately €486 per square metre. Depending on the density class, this estimate is partly above and partly below the combined benchmark of €294 per square metre for building land in cities with 200,000–500,000 inhabitants and €379 per square metre for the cited construction and maintenance costs of parks. The researchers therefore conclude that, within the model’s assumptions, the amenity value of green space can exceed both development value and the costs of providing green in many locations. The estimates do not show that every city will capture a fiscal return: they measure household welfare through a simulated exchange value rather than municipal income.

Several limitations constrain how the national results can be used. The model uses an average marginal-utility function, making the monetary estimates income-neutral and potentially underrepresenting low-income neighbourhoods, where limited access to private gardens or fewer resources for recreational travel may increase the need for public green space. It also does not capture the value of large green spaces as local identity markers or establish minimum provision for every resident. Private gardens, urban and roadside trees, and qualitative features such as the condition and character of green space were excluded. Because health was already included in the original life-satisfaction regression, part of the measured association may reflect recreation, air filtration or local climate regulation rather than visual amenity alone; the study could not quantify those overlaps. The “sorted preferences” correction, which accounts for the possibility that people who value green more strongly choose to live where it is more abundant, remains uncertain because its proposed upper and lower limits are relatively far apart. Site-specific planning would additionally require current land-use dynamics, neighbourhood-level land prices and more detailed information on investment and maintenance costs.

Subject of Research: National modeling of urban green-space amenity values and their potential relevance to municipal planning in Germany.

Article Title: Setting priorities for greening cities with monetary accounting values for amenity services of urban green

Article References: Ekinci, B., Grunewald, K., Meier, S., Schwarz, S., Schweppe-Kraft, B., & Syrbe, R.-U. (2022). Setting priorities for greening cities with monetary accounting values for amenity services of urban green. One Ecosystem, 7, Article e89705. https://doi.org/10.3897/oneeco.7.e89705

Image Credits: AI Generated

DOI: 10.3897/oneeco.7.e89705

Keywords: urban green space, ecosystem accounting, life satisfaction, amenity services, Germany, municipal planning, welfare economics, land valuation, public green space, Setting, priorities, greening