Validation of a Reduced Set of High-Performance Triggers for Identifying Patient Safety Incidents with Harm in Primary Care: TriggerPrim Project.

OBJECTIVE: The aim of the study was to construct and validate a reduced set of high-performance triggers for identifying adverse events (AEs) via electronic medical records (EMRs) review in primary care (PC). METHODS: This was a cross-sectional descriptive study for validating a diagnostic test. The study included all 262 PC centers of Madrid region (Spain). Patients were older than 18 years who attended their PC center over the last quarter of 2018. The randomized sample was n = 1797. Main measurements were as follows: ( a ) presence of each of 19 specific computer-identified triggers in the EMR and ( b ) occurrence of an AE. To collect data, EMR review was conducted by 3 doctor-nurse teams. Triggers with statistically significant odds ratios for identifying AEs were selected for the final set after adjusting for age and sex using logistic regression. RESULTS: The sensitivity (SS) and specificity (SP) for the selected triggers were: ≥3 appointments in a week at the PC center (SS = 32.3% [95% confidence interval {CI}, 22.8%-41.8%]; SP = 92.8% [95% CI, 91.6%-94.0%]); hospital admission (SS = 19.4% [95% CI, 11.4%-27.4%]; SP = 97.2% [95% CI, 96.4%-98.0%]); hospital emergency department visit (SS = 31.2% [95% CI, 21.8%-40.6%]; SP = 90.8% [95% CI, 89.4%-92.2%]); major opioids prescription (SS = 2.2% [95% CI, 0.0%-5.2%]; SP = 99.8% [95% CI, 99.6%-100%]); and chronic benzodiazepine treatment in patients 75 years or older (SS = 14.0% [95% CI, 6.9%-21.1%]; SP = 95.5% [95% CI, 94.5%-96.5%]).The following values were obtained in the validation of this trigger set (the occurrence of at least one of these triggers in the EMR): SS = 60.2% (95% CI, 50.2%-70.1%), SP = 80.8% (95% CI, 78.8%-82.6%), positive predictive value = 14.6% (95% CI, 11.0%-18.1%), negative predictive value = 97.4% (95% CI, 96.5%-98.2%), positive likelihood ratio = 3.13 (95% CI, 2.3-4.2), and negative likelihood ratio = 0.49 (95% CI, 0.3-0.7). CONCLUSIONS: The set containing the 5 selected triggers almost triples the efficiency of EMR review in detecting AEs. This suggests that this set is easily implementable and of great utility in risk-management practice.

Is primary care a patient-safe setting? Prevalence, severity, nature, and causes of adverse events: numerous and mostly avoidable.

Knowing the frequency and characteristics of adverse events (AEs) is key to implementing actions that can prevent their occurrence. However, reporting systems are insufficient for this purpose and epidemiological studies are also required. Currently, the reviewing of clinical records is the gold standard method for knowing the frequency and characteristics of AEs. Research on AEs in a primary care setting has been limited and primarily focuses on specific types of events (medication errors, etc.) or patients. Large studies that search for any kind of AE in all patients are scarce. This study aimed to estimate the prevalence of AEs in the primary care setting and their characteristics. SETTING: all 262 primary health-care centres in the Madrid region (Spain) during the last quarter of 2018. DESIGN: cross-sectional descriptive study. Eligible population: subjects over 18 years of age who attended medical consultation over the last year (N = 2 743 719); a randomized sample stratified by age. MAIN OUTCOMES: age, sex, occurrence of an AE, number of consultations in the study period, avoidability, severity, place of occurrence, type of event, and contributory factors. The clinical records were reviewed by three teams, each composed of one doctor and one nurse trained and with expertise in patient safety. The SPSS software package (version 26) was used for the statistical analyses. The evaluators reviewed 1797 clinical records. The prevalence of AEs over the study period was 5.0% [95% confidence interval (CI): 4.0%‒6.0%], with higher values in women (5.7%; 95% CI: 4.6%‒6.8%;P = 0.10) and patients over 75 years of age (10.3%; 95% CI: 8.9%‒11.7%; P < 0.001). The overall occurrence per hundred consultations was estimated to be 1.58% (95% CI: 1.28%‒1.94%). Of the detected AEs, 71.3% (95% CI: 62.1%‒80.5%) were avoidable. Additionally, 60.6% (95% CI: 50.7%‒70.5%) were categorized as mild, 31.9% (95% CI: 22.4%‒41.4%) as moderate, and 7.4% (95% CI: 2.1%‒12.7%) as severe. Primary care was the occurrence setting in 76.6% (95% CI: 68.0%‒85.2%) of cases. The overall incidence of AEs related to medication was 53.2% (95% CI: 50.9%‒55.5%). The most frequent types of AEs were prescription errors (28.7%; 95% CI: 19.5%‒37.9%), followed by drug administration errors by patients (17.0%; 95% CI: 9.4%‒24.6%), and clinical assessment errors (11.7%; 95% CI: 5.2%‒18.2%). The most common contributory factors were those related to the patient (80.6%; 95% CI: 71.1%‒90.1%) and tasks (59.7%; 95% CI: 48.0%‒71.4%). A high prevalence of AEs (1 in 66 consultations) was observed, which was slightly higher than that reported in similar studies. About 3 out of 4 such events were considered to be avoidable and 1 out of 13 was severe. Prescription errors, drug administration errors by patients, and clinical assessment errors were the most frequent types of AEs. Graphical Abstract.

Establishing Technical Values for Nursing Diagnoses in Primary Healthcare.

PURPOSE: To establish technical values for nursing diagnoses in primary healthcare with which to weight the delivery of care based on criteria of complexity and relevance. METHODS: A three-phase cross-sectional descriptive study: (1) establishing and weighting of the assessment criteria of technical values, (2) scoring of the assessment criteria per diagnosis, and (3) assigning technical values. FINDINGS: Diagnoses were ordered on the scoring scale obtained and a technical value of 1 to 4 was assigned according to their quartile. CONCLUSIONS: Having a technical value for each nursing diagnosis helps to measure the diversity and complexity of care. IMPLICATIONS FOR NURSING PRACTICE: Technical values may contribute to improving nursing management indicators, as they incorporate a quantitative view into the assessment process.

OBJETIVO: Definir un valor técnico para los diagnósticos enfermeros en Atención Primaria que permita ponderar la prestación de cuidados en base a criterios de complejidad y relevancia. MÉTODOS: Estudio descriptivo transversal realizado en 3 fases: 1) definición y ponderación de los criterios de valoración del valor técnico, 2) puntuación de los criterios de valoración por diagnóstico, 3) asignación del valor técnico. RESULTADOS: Se ordenaron los diagnósticos en la escala de puntuación obtenida y se asignó un valor técnico del 1 al 4 en función del cuartil. CONCLUSIONES: Disponer de un valor técnico de cada diagnóstico enfermero permite dimensionar la diversidad y la complejidad de los cuidados. IMPLICACIONES: El valor técnico puede contribuir a mejorar los indicadores de gestión de servicios enfermeros al añadir una visión cuantitativa al proceso evaluativo. PALABRAS CLAVE: diagnóstico de enfermería; terminología normalizada de enfermería; Atención Primaria de salud; indicadores de calidad de la atención de salud; indicadores de gestión.

Effectiveness of an educational group intervention in primary healthcare for continued exclusive breast-feeding: PROLACT study.

BACKGROUND: The World Health Organization leads a global strategy to promote the initiation and maintenance of breast-feeding. Existing literature shows that education and supportive interventions, both for breast-feeding mothers as well as for healthcare professionals, can increase the proportion of women that use exclusive breast-feeding, however, more evidence is needed on the effectiveness of group interventions. METHODS: This study involves a community-based cluster randomised trial conducted at Primary Healthcare Centres in the Community of Madrid (Spain). The project aims to evaluate the effectiveness of an educational group intervention performed by primary healthcare professionals in increasing the proportion of mother-infant pairs using exclusive breastfeeding at six months compared to routine practice. The number of patients required will be 432 (216 in each arm). All mother-infant pairs using exclusive breastfeeding that seek care or information at healthcare centres will be included, as long as the infant is not older than four weeks, and the mother has used exclusive breastfeeding in the last 24 h and who gives consent to participate. The main response variable is mother-infant pairs using exclusive breast-feeding at six months. Main effectiveness will be analysed by comparing the proportion of mother-infant pairs using exclusive breast-feeding at six months between the intervention group and the control group. All statistical tests will be performed with intention-to-treat. The estimation will be adjusted using an explanatory logistic regression model. A survival analysis will be used to compare the two groups using the log-rank test to assess the effect of the intervention on the duration of breastfeeding. The control of potential confounding variables will be performed through the construction of Cox regression models. DISCUSSION: We must implement strategies with scientific evidence to improve the percentage of exclusive breast-feeding at six months in our environment as established by the WHO. Group education is an instrument used by professionals in Primary Care that favours the acquisition of skills and modification of already-acquired behaviour, all making it a potential method of choice to improve rates of exclusive breast-feeding in this period. TRIAL REGISTRATION: The trial was registered with ClinicalTrials.gov under code number NCT01869920 (Date of registration: June 3, 2013).

Influencia de los factores sociodemográficos, laborales y profesionales de enfermería en la percepción del entorno de la práctica en atención primaria / Influence of socio-demographic, labour and professional factors on nursing perception concerning practice environment in Primary Health Care

Objetivo: Analizar la percepción de los profesionales enfermeros de atención primaria de Madrid sobre el entorno en el que realizan su práctica, también relacionada con los factores sociodemográficos, laborales y profesionales. Diseño: Estudio observacional analítico transversal. Participantes y contexto: 475 enfermeros de Atención Primaria de Madrid (áreas 6 y 9, en 2010). Mediciones principales: Percepción del entorno de la práctica, a través del cuestionario Practice Environment Scale of the Nursing Work Index (PES-NWI); edad; sexo; años de experiencia profesional; categoría; área de salud; contratación y nivel académico. Resultados: Se estudiaron 331 sujetos (tasa de respuesta: 69,7%). La puntuación bruta para el PES-NWI fue: 81,04 [IC 95%: 79,18-82,91]. El factor mejor valorado fue «Apoyo de los gestores» (2,9 [IC 95%: 2,8-3]) y el peor, «Adecuación de la plantilla» (2,3 [IC 95%: 2,2-2,4]). En el modelo de regresión (variable dependiente: puntuación bruta del PES-NWI), ajustado por edad, sexo, situación laboral, permanecieron con una p≤0,05, la categoría profesional (coeficiente B =6,586) y los años de ejercicio profesional en el centro (coeficiente B = 2,139, para tiempo de 0a 2 años; coeficiente B = 7,482, para tiempo de 3-10 años; coeficiente B = 7,867, para tiempo de más de 20 años).Conclusiones: Las enfermeras con cargo de responsabilidad y aquellas que tienen mayor formación tienen una mejor percepción de su entorno de práctica. Conocer los factores del entorno de la práctica es un elemento clave para la organización sanitaria con el fin de optimizar la provisión de cuidados, y mejorar los resultados en salud (AU)

Aim: To analyze the perception of nursing professionals of the Madrid Primary Health Care environment in which they practice, as well as its relationship with socio-demographic, work-related and professional factors. Design: Cross-sectional, analytical, observational study. Participants and context: Questionnaire sent to a total of 475 nurses in Primary Health Care in Madrid (former Health Care Areas 6 and 9), in 2010. Main measurements: Perception of the practice environment using the Practice Environment Scale of the Nursing Work Index (PES-NWI) questionnaire, as well as; age; sex; years of professional experience; professional category; Health Care Area; employment status and education level. Results: There was a response rate of 69.7% (331). The raw score for the PES-NWI was: 81.04 [95%CI: 79.18–82.91]. The factor with the highest score was “Support from Managers” (2.9 [95%CI: 2.8–3]) and the lowest “Workforce adequacy” (2.3 [95%CI: 2.2–2.4]). In the regression model (dependent variable: raw score in PES-NWI), adjusted by age, sex, employment status, professional category (coefficient B = 6.586), and years worked at the centre (coefficient B = 2.139, for a time of 0–2 years; coefficient B = 7.482, for 3–10 years; coefficient B = 7.867, for over 20 years) remained at p ≤ 0.05. Conclusions: The support provided by nurse managers is the most highly valued factor in this practice environment, while workforce adequacy is perceived as the lowest. Nurses in posts of responsibility and those possessing a higher degree of training perceive their practice environment more favourably. Knowledge of the factors in the practice environment is a key element for health care organizations to optimize provision of care and to improve health care results (AU)

Influence of socio-demographic, labour and professional factors on nursing perception concerning practice environment in Primary Health Care.

AIM: To analyze the perception of nursing professionals of the Madrid Primary Health Care environment in which they practice, as well as its relationship with socio-demographic, work-related and professional factors. DESIGN: Cross-sectional, analytical, observational study. PARTICIPANTS AND CONTEXT: Questionnaire sent to a total of 475 nurses in Primary Health Care in Madrid (former Health Care Areas 6 and 9), in 2010. MAIN MEASUREMENTS: Perception of the practice environment using the Practice Environment Scale of the Nursing Work Index (PES-NWI) questionnaire, as well as; age; sex; years of professional experience; professional category; Health Care Area; employment status and education level. RESULTS: There was a response rate of 69.7% (331). The raw score for the PES-NWI was: 81.04 [95%CI: 79.18-82.91]. The factor with the highest score was "Support from Managers" (2.9 [95%CI: 2.8-3]) and the lowest "Workforce adequacy" (2.3 [95%CI: 2.2-2.4]). In the regression model (dependent variable: raw score in PES-NWI), adjusted by age, sex, employment status, professional category (coefficient B=6.586), and years worked at the centre (coefficient B=2.139, for a time of 0-2 years; coefficient B=7.482, for 3-10 years; coefficient B=7.867, for over 20 years) remained at p≤0.05. CONCLUSIONS: The support provided by nurse managers is the most highly valued factor in this practice environment, while workforce adequacy is perceived as the lowest. Nurses in posts of responsibility and those possessing a higher degree of training perceive their practice environment more favourably. Knowledge of the factors in the practice environment is a key element for health care organizations to optimize provision of care and to improve health care results.