Qualidade do registro das informações dos nascidos vivos de risco no município de Maringá-Paraná, no ano de 2007
Bibliographic record
Abstract
The records produced routinely in numerous activities in the area of health are given that enable the transformation into information. The banks of data from the routine health services are used as a tool for the development of health policies, for planning and managing health services. Currently, the record is a criterion for evaluating the quality of the service where the quality of records are a reflection of the quality of care. The objective of this study was to assess the quality of information of the infants enrolled in the program for monitoring the high-risk newborns in Maringa-Parana in the various information systems in 2007. This is a crosssectional study with quantitative and analytical approach. Used as data sources SINASC, sheet Monitoring the Newborn Risk (Orange Card), Form A and C of the Information System of Primary Care and medical records of 23 Basic Health Units (UBS). Of the 4175 children born in the city of Maringa in 2007, 710 (17%) children were included in the monitoring program to high-risk newborns. Of these, we selected a random sample of 505 (71.12%) children, and 254 (50.29%) with low birth weight, 244 (48.31%) with prematurity, 142 (28.11%) children teenage mothers (<18 years), 50 (9.90%) with score ≤ 7 and 21 (4.15%) classified as congenital anomaly. It was observed that many of these children have more of a risk criterion. Of the total of the sheets were found 131 (25.9%) children, were located 128 (25.3%) children with Chips and C with respect to records, were located 359 (71.0%). The data were analyzed by Correspondence Analysis and Binary Ascending Hierarchical Classification where the basic health units were grouped into clusters. Correspondence analysis showed that the Orange Card, the variables with significant contributions were medical (3.6) in the UBS universe, City High and Guaiapó-Requião, nursing (2.2) in the UBS High City, Guaiapó-Requião Mall, Internorte, Quebec and Alvorada III, home visits (2.3) in UBS Mandacaru, pine, South Zone and at high inclusion in other programs (2.3) in UBS Mall, Internorte, Quebec, Alvorada III; The specs for the outstanding contributions indicate that the variable with the greatest significance is the referral to dentistry (4.0) Mall and the UBS (1.5) in UBS Pinheiros and Vila Esperança Universe; in Sheet C, the relevant contributions indicate that the variables with greatest significance was the chart registration form (7.0) in UBS Mall and other variables, monitoring ≤ 6 times the recorded (3.2) Mandacaru at UBS, for the records, the contributions combined with greater significance records were located (4.6) in UBS Acclimatization; records identified as high-risk NB (2.7) in UBS Parigot de Souza, S. Silvestre, Hope Town and Guaiapó-Requião; sheet located in Orange record (7.8) in UBS Parigot de Souza, Sao Silvestre, Vila Esperança, Guaiapó-Requião and Acclimatization; routing registered (1.8); hospital recorded (2.8) and immunization records (4.9) in UBS Mall, Falls, Industrial, strawberry, Ney Braga and universe. The quality of information in health records have a clear potential as a need for adequate health care and better organization of health services, to reclaim the basic principles of the SUS as a comprehensive care, with equity and universal access.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".