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Post-pandemic patient safety: have the characteristics of incidents with harm changed? Comparative observational study in primary care via review of medical records with a trigger tool

BMC Primary Care volume 25, Article number: 392 (2024) Cite this article

Abstract

Background

The COVID-19 pandemic generated or accelerated healthcare changes, some of which persist thereafter (e.g., healthcare reorganisation, remote consultation). Such changes entail novel risks for patient safety.

Methods

Aim

To compare the characteristics of patient safety incidents with harm (PSIH) in primary care before the pandemic and at present.

Design and setting

Cross-sectional, comparative, observational study conducted within the entire Primary Care Service of the Madrid region with observations at two time points (2018 and 2021/2022).

Participants

Patients > 18 years of age with at least one consultation in the previous year. The necessary sample size was established at N1 = 2,000 for the first time point and N2 = 2,700 for the second. Sampling was performed by simple randomisation for the first group and by clusters followed by simple randomisation for the second.

Main measurements

Age, gender, presence of PSIH in the medical record, and characteristics of the PSIH, specifically avoidability, severity, place of occurrence, nature, and contributory factors. Triggers validated in primary care were employed to screen the patients’ medical records and those containing any trigger were reviewed by three nurse-physician teams who underwent previous training.

Analysis

Comparative analysis using Fisher’s exact test.

Results

A total of 63 PSIHs and 25 PSIHs were found for the first and second samples, respectively. The comparison of the characteristics of PSIH before the pandemic and currently was: avoidable 62% vs. 52% (p = 0.47), mild 51% vs. 48% (p = 0.57), in the primary care setting 73% vs. 64% (p = 0.47), respectively. Although no statistically significant differences were observed globally in the nature of the incidents (p = 0.13), statistically significant differences were found for diagnostic errors, with pre-pandemic rates of 6% vs. 20% at present (p < 0.05). Finally, no significant differences were found in the contributory factors.

Conclusions

No differences were found in the avoidability, severity, place of occurrence, or contributory factors of PSIHs before the pandemic and currently. In terms of the nature of these incidents, the outcomes revealed an increase in diagnostic errors (excluding diagnostic tests), which could be attributed to a greater frequency of remote consultations and a decrease in the longitudinality of care resulting from the shortage of professionals.

Peer Review reports

Background

The COVID-19 pandemic generated, hastened, or accelerated new healthcare tools and models to address the challenge it posed to medical attention [1, 2]. Some of these changes have been reversed after the pandemic as medical attention has returned to “normality”. Nevertheless, other changes are likely to persist as they continue to make sense beyond the pandemic context. These include the reorganisation of care resulting from the disruption of routine care and the scarcity of resources [3] as well as non-face-to-face care and telemedicine, especially via telephone consultation [4,5,6].

The newly adopted tools and care models entail novel risks for patient safety, as is often the case with changes. The deterioration of patient safety during the pandemic has been described [7, 8], particularly concerning risks and patient safety incidents associated with changes in the provision of healthcare under those circumstances [1, 9,10,11,12,13,14]: medication errors (prescription and administering), diagnostic and medication errors associated with telemedicine, diagnostic errors and delays associated with the disruption of routine care and the reorganisation of care provision, etc. Such risks have been described both in the hospital and primary care (PC) settings. However, no global studies have been identified in PC on patient safety incidents related to the new healthcare tools and models that remain at present, after the end of the COVID-19 pandemic.

The question posed in this research, which gives title to this publication, is whether the characteristics of patient safety incidents with harm (PSIHs) have undergone a global change due to these modifications in the PC delivery model (namely, whether they are different at present from what they were before the pandemic). The change in the global characteristics of PSIHs has been described in several studies [15, 16]. However, these focus on the “during the pandemic” period and not the “post-pandemic”. Moreover, these are studies on reporting systems, even if underreporting is well known [17] and furtherly accentuated during the pandemic [15, 16]. For this reason, this study aimed to address the research question using the method of reviewing medical records (MRs), which can be considered the gold standard [18, 19] despite presenting certain limitations [18, 19].

The low prevalence of PSIHs in PC [20,21,22], estimated at 1–3 PSIHs per 100 MRs reviewed, reduces the performance of MR review in detecting these occurrences and has therefore limited its use in this setting. Nevertheless, one of the three main applications of trigger tools [23, 24] is precisely to circumvent this limitation: by conducting a previous screening of MRs and selecting only those that contain a trigger for subsequent review [25], the probability of identifying a PSIH also increases, hence optimising the process of MR review. The other two main applications of trigger tools are the so-called “learning model”, aimed at searching for PSIHs for learning and improvement purposes, and its predictive use to identify high-risk patients and trigger alerts [26]. Very few studies on trigger validation in PC [27, 28] can be found. One of them, conducted by the present authors, constructed a set of five high-performance triggers elicited from electronic MRs (TriggerPrim®: >3 appointments/week, hospitalisation, emergency room visit, benzodiazepines prescription, and opioids prescription) [28] that multiplied by three times the probability of finding an PSIH in the MR, with a negative predictive value of 98%.

Methods

The aim of this study was to compare the characteristics of PSIHs in PC before the pandemic and at present, specifically avoidability, severity, place of occurrence, nature, and contributory factors. This was accomplished using the MR review method with the support of a trigger tool.

A cross-sectional, comparative, observational study was conducted with observations at two cut-off points via MR review facilitated by a trigger tool, in all the 264 primary healthcare centres of the Madrid region (Spain). These centres serve a population exceeding six and a half million people and are staffed by approximately 4,000 family physicians, 1,500 paediatricians, and 3,500 nurses.

The first cut-off was set between October 1 and December 31, 2018, while the second section included two segments, one between October 1 and December 31, 2022 and another between January 1 and March 31, 2023.

This study is part of the TriggerPrim® project that has been funded by the Instituto de Salud Carlos III (ISCIII) and co-funded by the European Union (ref. PI20/01012). It was approved by the Ethics Committee for Research of the Hospital de la Princesa in Madrid (ref. CP 10/19) and by the Central Commission for Research of the PC Management within the Madrid Health Service (ref. 04/20).

Participants

The eligible population were patients over 18 years of age with an active MR at the end of each cut-off point, who had attended the primary healthcare centre for consultation over the previous year (N1 = 2,743,719 and N2 = 2,995,721 MRs).

To calculate the sample size, an estimation was made of the required number of PSIHs to be identified for comparing their characteristics and detecting percentage differences of 10% in any given characteristic reaching percentage values of 20%, with confidence levels set at 95% (95%CI) and a statistical power of 80%. Based on a frequency of PSIH estimated at 5% in previous studies [20,21,22] and considering 20% of potential losses to follow-up, the necessary size was calculated to be 4,700 patients. By convenience, the sample was distributed into N1 = 2,000 and N2 = 2,700 patients for the first and second groups, respectively.

The patients were selected by simple randomisation for the first cut-off whereas for the second one, first an opportunistic cluster sampling of nine PC healthcare centres was performed that was subsequently followed by simple randomisation of the eligible population from these centres.

Outcome variables and data collection

The sociodemographic characteristics of the patients were recorded (age and gender) as well as the characteristics of the PSIH whenever present, namely avoidability, severity, place of occurrence, nature, and contributory factors.

The electronic MRs of both samples were screened using the trigger tool methodology [24] via a set of five previously validated triggers (TriggerPrim®: >3 appointments/week, hospitalisation, emergency room visit, benzodiazepines prescription, and opioids prescription) [28] that increased the probability of finding a PSIH. Of note, PSIH was defined according to the definition by the WHO [29] as an “event or circumstance that caused unnecessary harm to a patient”. Each MR containing at least one trigger was classified as TriggerPrim®+ and selected for subsequent manual review in search for the presence of any PSIH. The outcome variables were obtained from these MRs. The six-point scale of the APEAS study [21] was employed to determine the degree of certainty (1 = minimum certainty, 6 = maximum certainty), and a score of ≥ 2 points was considered to be indicative of the presence of a PSIH.

The following information about the identified PSIHs was recorded: (a) avoidability (yes/no), using a different six-point scale from the APEAS study [21] that indicates the degree of certainty about the avoidability of occurrence of the PSIH (1 = minimum certainty, 6 = maximum certainty), where ≥ 4 points deemed the PSIH as avoidable ; (b) severity, which classified the PSIH in accordance with the classification by the National Health Service [30] as mild (required extra observation or minor treatment), moderate (caused short-term harm requiring subsequent treatment or procedure, including brief hospital admission), and severe (caused long-term/permanent harm or death); (c) place of occurrence, namely in the PC setting (PC healthcare centre, patient’s home, healthcare handover) or other (hospital, socio-health centre); (d) nature of the PSIH based on a modified classification of the Incidents Reporting System of the Madrid region (CISEMadrid) which classifies them into drug administration errors by the patient, prescription errors, follow-up and care errors, errors in therapeutic procedures, errors in diagnostic tests, diagnostic errors, and others; (e) in the case of avoidable PSIHs, contributory factors classified into the categories established by the National Patient Safety Agency [31], where each group of factors were treated as a dichotomous variable (present/absent).

The fieldwork corresponding to the MR review of the first sample (last trimester of 2018) was finally delayed until 2021 due to the lengthy process for obtaining MR access authorisations, automatised extraction of triggers, hiring of human resources, and the COVID-19 pandemic.

Three physicians and three nurses, all expert clinicians in patient safety, reviewed the MRs identified as TriggerPrim®+. They additionally received 25 h of theoretical and practical training on the trigger tool methodology and were provided with a procedures manual. For the first sample (pre-pandemic), three physician-nurse teams reviewed the MRs so that each team functioned as a single observer. The degree of inter-observer agreement between the three teams of reviewers yielded a Fleiss kappa-value of 0.512 (CI95%:0.508–0.516), which indicates moderate agreement. For the second sample, each of the former reviewers partnered with new ones to form six new nurse-physician teams. The new reviewers were also clinicians expert in patient safety. They received 5 h of theoretical training in group and several hours of practical training, each with their expert partner. The research team and the expert reviewers from the patient safety units conducted the enrollment. Since each pair included one expert reviewer, the degree of inter-observer agreement was assumed to be along the lines of previous estimations.

Each physician-nurse pair functioned as a single observer and each MR was reviewed by a single physician-nurse team.

Data analysis

For each of the two study groups, a descriptive analysis of the characteristics of the PSIHs (avoidability, severity, place of occurrence, nature, and contributory factors) was performed based on the distribution of frequencies with the corresponding 95%CI. A comparative analysis was performed of the frequency distribution for each of the aforementioned characteristics pre-pandemic and currently using the chi-squared test as a hypothesis comparison test or Fisher’s exact test when the former could not be applied (> 20% of expected values < 5).

The SPSS Version 26.0 statistical package software was used for the statistical analyses.

Results

A total of N1 = 1,797 MRs were reviewed for the first sample (pre-pandemic) and N2 = 2,713 MRs were reviewed for the second (present-day). Losses to follow-up from sampling (2018) until the fieldwork (2021) amounted to 203 MRs for the first sample. Figure 1 shows the flowchart of the study. The electronic screening of records using the trigger tool methodology identified 387 MRs TriggerPrim®+ (namely, containing at least one trigger in the validated set) in the first group and 446 MRs in the second one. The review of these MRs detected 63 and 25 PSIHs in the first and second samples, respectively.

Fig. 1
figure 1

Flowchart of the study

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The sociodemographic characteristics of patients with PSIH were similar between both samples (Table 1).

Table 1 Characteristics of patients with PSIH before the pandemic and at present
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Table 2 shows the distribution of the characteristics of PSIHs. No statistically significant differences were found in avoidability before the pandemic and present-day, with figures of 62% and 52%, respectively (p = 0.47). Similarly, the differences in the distribution of mild, moderate, and severe PSIH before the pandemic and at present were not statistically significant. The most frequent place of occurrence was the PC setting, with 73% of the cases before the pandemic and 64% at present and no statistically significant differences in its distribution (p = 0.47). In terms of the nature of the PSIH, although the overall distribution did not show statistically significant differences, there was a notable increase in the percentage of PSIH due to diagnostic errors (Fig. 2), with figures of 6.3% before the pandemic and 20.0% at present, a change that reached statistical significance in isolated comparison (p = 0.05) (Table 2).

Table 2 Distribution of the characteristics of PSIH before the pandemic and at present
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Fig. 2
figure 2

Nature of patient safety incidents with harm before the pandemic and at present

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Finally, the percentage of avoidable PSIHs in which a contributory factor was present was similar before the pandemic and at present for all the evaluated types of factors, with no significant differences between them (Table 3). The most frequent of such factors were those related to patient characteristics.

Table 3 Contributory factors to preventable PSIH before the pandemic and at present
Full size table

Discussion

The appearance of new risks after the COVID-19 pandemic appears to be a reasonable assumption. Such risks could be related to changes in PC care models that persist at present, such as greater frequency of remote consultations, different procedures to access healthcare, or an accentuated shortage of professionals, among others. However, despite these changes, the characteristics of the PSIH were overall similar to those before the pandemic, except for a significant increase in diagnostic errors.

The overall post-pandemic prevalence (25 PSIH in 446 MR reviewed: 5.6%) was comparable to that described in similar studies in the PC setting [20, 22, 27]. Although apparently low, this figure translates into a high volume of harmed patients when applied to the total PC population (potentially exceeding 5 million patients annually in a country like Spain).

Avoidability was not found to differ from present times, with figures of 50–60% of avoidable PSIHs, which is along the lines of the outcomes in other studies [20,21,22, 32]. Continuing with the previous example, in a country like Spain, approximately 3 million patients would suffer avoidable harm. Few clinical interventions have the potential to impact on this many individuals.

Severity remained also similar to that before the pandemic, with about half the PSIHs classified as mild in both samples, which is consistent with findings in comparable studies [20]. This implies that one in 50 patients will experience moderate or severe harm in PC over a three-month period, a figure that challenges the perception of PC as a low-risk environment.

No changes were observed in terms of the place of occurrence of the PSIH, with 65–75% of them happening in the PC setting.

Although no publications were found that compare PSIHs between the pre-pandemic and current times, some studies have compared PSIHs before and during the pandemic. These are based on incident reporting systems [15, 16] and did not report the severity of PSIH to have worsened during the pandemic, which is in agreement with the findings of the present research.

Although the distribution by nature of the PSIH showed changes, globally these were not statistically significant. Only a significant increase in diagnostic errors was found (excluding diagnostic tests that were in a separate category). The frequency of diagnostic errors was already high before the pandemic, as reported in other studies [20,21,22]. However, these types of PSIH are frequently underreported in reporting systems [15, 16], suggesting that MR review is a complementary method essential for their detection.

One of the aforementioned studies also reported a greater number of diagnostic error reports during the pandemic [15]. The factors that could explain such an increase have been described [1,2,3,4,5,6, 10, 13, 14]: disruption of routine care, shortage of resources, care reorganisation, overload, remote care, technological tools, or losses to follow-up. Many of these factors are no longer present after healthcare reverted to “normality”. However, at least two of the relevant changes in the model of care have persisted after the pandemic: the more frequent use of non-face-to-face consultations and the shortage of professionals, especially physicians, which forces a reorganisation of care. The present study interprets that this rise in diagnostic errors can be attributed to two main factors: on the one hand, the elevated risk associated with non-face-to-face consultations, which has already been reported [12, 33,34,35], and on the other hand the loss of longitudinality of care due to the shortage of professionals. The provision of care for a particular process by different professionals at different consultations could increase the risk of diagnostic errors. The relevance of this finding in PC is further emphasised when considering that diagnostic errors have traditionally been under-researched [36] and, moreover, they are under-reported [15, 16].

Finally, the contributory factors to PSIHs also did not show differences before the pandemic and at present. The most frequent factors were those related to the characteristics of patients, which is in agreement with other research [21, 22, 37].

Among the most important strengths of this study is the employed methodology of MR review. Although research on PSIH based on reporting systems is more common because of its simplicity, underreporting is well known [17, 18] and therefore the outcomes may not reflect the reality of PSIH, not only in terms of frequency but also of their distribution. For example, the reporting of diagnostic errors is rare in PC [16] and yet it is very frequently found in epidemiological studies [21, 22]. Another strength is the use of a trigger tool, which allows enhancing the process of MR review with a validated method [24, 28]. The sample size and the regional, multi-centric setting are also strengths of the study, as well as the expertise of the main reviewers.

The two main limitations of the study are the difference in the sampling method for the two groups and the losses to follow-up in the first one. The variance in the sampling method (simple randomisation for the first sample and by clusters for the second one) could potentially introduce a bias if the characteristics of the PSIHs at the primary healthcare centres selected for the present-day sample differed from those of the overall study population. However, a comparison was made between two subsamples of centres from both study sections that did not reveal differences between them, which suggests a low probability that the centres served different study populations. The other limitation was the losses to follow-up in the first sample, which reached 10.4%. This was due to restrictions on access to the MR of these patients given the time elapsed between the formerly established cut-off in 2018 and the actual fieldwork in 2021. Almost 60% of the losses were due to transfers of residence outside the region of Madrid, a reason not directly related to the occurrence of an event, which suggests a low probability of significant bias for this reason.

Although the inter-rater reliability might seem suboptimal (kappa-value of 0.512), achieving high inter-observer agreement in the identification of adverse events by MR review has been described to be challenging, particularly when assessing avoidability [38], as in this study. Previous MR review studies have found kappa-values in the range of 0.3‒0.6 for avoidable PSIH [39,40,41]. Furthermore, the aforementioned studies focused on medication errors within specific populations, which enhances concordance. In contrast, the present study sought to identify all types of PSIH (not only standardised PSIH, such as medication incidents) in all types of patients (not limited to those at high-risk of suffering incidents). Nevertheless, the concordance level attained in this study was at the upper end of the reported range. Although concordance was only measured at the beginning of the study, weekly consensus meetings and a continuous online communication channel between the teams were established during the fieldwork in order to further improve it. Each team presented the cases in which uncertainties had arisen and a criterion was defined by all the teams that resolved doubts and served to address other similar cases. The agreed criteria were then uniformly applied, and even MRs that had already been evaluated were revisited and reclassified if necessary. More than 5% of the AE’s were reclassified following these meetings. Although concordance was not recalculated at the end of the study, it is highly likely that concordance improved throughout it as a result.

The results of this study appear to indicate that the new forms of care provision, mainly consisting of an increased frequency of remote consultation and the reorganisation of care due to the scarcity of resources, could be related to a higher frequency of diagnostic errors. Consequently, one implication for the practise of the study is the implementation of safe non-face-to-face care procedures with “don’t miss” diagnoses and “red flag” symptoms [42] with the objective of reducing diagnostic errors. On the other hand, efforts could be made when reorganising medical attention to maintain the longitudinality of care, at least throughout individual processes and in vulnerable and/or complex patients. Furthermore, the implementation of barriers such as alert systems for missed diagnostic opportunities could also lower this risk. As for the implications for research, further studies are desirable to confirm this increase in diagnostic errors and to investigate both the relevant factors that and the impact of barriers that can potentially be implemented.

Conclusions

No differences were found in the avoidability, severity, place of occurrence, or contributory factors of PSIHs before the pandemic and at present. In terms of the nature of the PSIH, an increase in diagnostic errors (excluding diagnostic tests) was observed, which could be related to a greater frequency of remote care and to the loss of longitudinality of care resulting from a shortage of professionals.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable requestThe data that support the findings of this study will be available from electronic clinical record system of Madrid region, AP-MADRID, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. However, each new project based on these data must be previously submitted to CEICA for approval. However, data are available from the authors upon reasonable request and with permission of the project’s principal investigator.

Abbreviations

PC:

Primary care

PSIH:

Patient Safety Incident with Harm

MR:

Medical record

CI:

Confidence interval

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Acknowledgements

We would like to thank Mercedes Drake Canela, Elena Bartolomé Benito and María José Toribio Vicente who participated in the study design, and Angela Bravo Navajón, M. Carmen Álvarez Pérez , Olga Nieto García, Concepción Zafra Urango, Purificación Peñasco Iglesias , Ana Sánchez Sempere , Maria Hernandez de Luna, Pilar Rapp Fernández, Mª José Castillo Lizárraga, Jose Ignacio Aza Pascual-salcedo and Laura Carvajal González who participated in the EMRs reviewing.We are grateful to Teresa Sanz Cuesta and Isabel del Cura González from the Research Unit of the Primary Care Management from the Madrid Health Service (SERMAS) who supported and oriented the research team in all phases of the project and who are statistical experts and have evaluated statistics repoted.

Jorge de Vicente Guijarro, Lina Marcela Parra Ramírez, Cristina Paniagua Alcaraz, Marcos Alonso García, Moisés David Espejo Mambie, César Pérez Romero, Marta González Touya, Belén Luna Porta, and Blanca Andreu Ivorra have collaborated in some aspects of the study design, fieldwork, or drafting of the manuscript.

Finally, we would like to thank Primary Care Management for providing the necessary human resources.

AUTHOR’S GROUP “RESEARCH TEAM TRIGGERPRIM®”:

• María Luisa, Alcázar González1

• Aurora, Barberá Martín1

• Dolores, Conejos Míquel1

• Asunción, Cañada Dorado1

• Dolores, Martínez Patiño1

• Marta, Castelo Jurado1

Funding

This work was supported by the Health Institute Carlos III (Instituto de Salud Carlos III-ISCIII) and co-funded by the European Union [grant number PI20/01012].

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Authors and Affiliations

  1. Primary Care Management (Gerencia Asistencial de Atención Primaria) Madrid Health Service (SERMAS), C/ San Martín de Porres 6, 5ª planta, Madrid, 28035, Spain

    Gerardo Garzón González, Tamara Alonso Safont, Oscar Aguado Arroyo, Cristina Villanueva Sanz, Arancha Luaces Gayán, Esther Zamarrón Fraile, Juan José Jurado Balbuena & Inmaculada Mediavilla Herrera

Authors
  1. Gerardo Garzón González
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  2. Tamara Alonso Safont
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  3. Oscar Aguado Arroyo
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  4. Cristina Villanueva Sanz
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  5. Arancha Luaces Gayán
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  6. Esther Zamarrón Fraile
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  7. Juan José Jurado Balbuena
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  8. Inmaculada Mediavilla Herrera
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Consortia

Research Team “TriggerPrim®”

  • María Luisa Alcázar González
  • , Aurora Barberá Martín
  • , Dolores Conejos Míquel
  • , Asunción Cañada Dorado
  • , Dolores Martínez Patiño
  •  & Marta Castelo Jurado

Contributions

Gerardo Garzón González (GGG), Tamara Alonso Safont (TAS), Inmaculada Mediavilla Herrera (IMH) and Research Team “TriggerPrim® (RTT) contributed to the study design. Esther Zamarrón Fraile (EZF), Arancha Luaces Gayán (ALG), Cristina Villanueva Sanz (CVS), Oscar Aguado Arroyo (OAA), Juan José Jurado Balbuena (JJJB) reviewed the EMRs. TAS performed the electronic data extraction and access to EMR. GGG, TAS and RTT conducted the training. IMH participated in achieving resources. GGG performed the data analysis. All authors drafted the initial version of the manuscript and all authors reviewed and agreed to its final version.

Corresponding author

Correspondence to Gerardo Garzón González.

Ethics declarations

Ethics approval and consent to participate

This study was carried on in accordance with the Declaration of Helsinki and it was approved by the Research Ethics Committee of Hospital de la Princesa (Comité de Ética de Investigación del Hospital de la Princesa) (Madrid) (grant number CP 10/19) and the Central Committee for Research of the Primary Care Management from the Madrid Health Service (Comisión Central de Investigación de la Gerencia de AP del Servicio Madrileño de Salud) (grant number 04/20).

Statement on consent to participate. Data patients were anonymous so consent wasn’t needed.

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Not applicable.

Competing interests

The authors declare no competing interests.

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Garzón González, G., Alonso Safont, T., Aguado Arroyo, O. et al. Post-pandemic patient safety: have the characteristics of incidents with harm changed? Comparative observational study in primary care via review of medical records with a trigger tool. BMC Prim. Care 25, 392 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12875-024-02639-3

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Keywords

BMC Primary Care

ISSN: 2731-4553

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