Fear of the COVID-19 and medical liability. Insights from a series of 130 consecutives medico-legal claims evaluated in a single institution during SARS-CoV-2-related pandemic

2.1 Sampling and classification of medico-legal cases

We evaluated claims for medical liability from March 2019–January 2020 and March 2020–January 2021 regardless of whether the assessment was requested by the Public Prosecutor or by Law Firms. The cases for which an evaluation was requested and in which a deviation from guidelines was detected were considered. A simple claim is not necessarily synonymous with the existence of a legally relevant fault. According to a number of Insurance Italian reports, 22.7% to 50.1% of cases do not lead to compensation [15, 16, 17, 18].

The cases were categorized according to the type of deviation from the ideal conduct identified. The term ‘error in surgical technique’ (Group A) implies cases with a technical error during the interventions.

The ‘error in therapeutic diagnostic management’ (Group B) means any deviation from the clinical management of patients prescribed by guideline algorithms. Nosocomial infections were also considered in this group.

The ‘delay’ group (Group C) means a longer time required than indicated in the guidelines for transfer to hospital, for the evaluation of the onset of symptoms, for the treatment of the underlying pathology compared to what is required by the guidelines, and/or by the good clinical practices. This group included only cases to be treated in emergency or urgency in which the outcome of the disease was time-dependent (acute myocardial infarcts, aortic dissection, strangulation-strangulation of intestinal hernia, cerebral hemorrhage, stroke, acute appendicitis, acute abdomen). Conversely, diagnostic delays that did not require emergency-urgency treatment (diagnosis of neoplastic pathology) were counted among generic treatment errors.

Finally, ‘lack of supervision’ (Group D) implies cases in which the subjects required continuous support from the caregivers—due to lack of physical or mental autonomy (bedridden patients, elderly patients with cognitive problems, psychiatric patients, patients who are not independent in the activities of daily life)—and a lack of support was the cause of the damage.

2.2 General analysis

In our main analysis, we compared the categories of error not influenced by the measures taken during the COVID emergency (Group A and Group B) with those for which the restrictive measures for prevention of COVID-19 may have played a role in the error (Group C and Group D).

2.3 Sub-analysis of the groups

Group C was distinguished from cases in which the delay in accessing the hospital or in the surgical evaluation or in carrying out the intervention was due to the patient’s conditions and not COVID-19. For example, the patient required stabilization or those that had a delay with respect to what is foreseen in the guidelines due to organizational-structural problems (unavailability of means of transport, health personnel, surgical rooms within the structure).

In the group examined (cases between March 2020 and January 2021), after a careful check of the clinical documentation in the records, we considered delays attributable to COVID-19 those in which there was a concrete application of the guidelines for prevention from SARS-CoV-2 that resulted in a longer times due to COVID-specific changes in protocol. Group D was compared with the control group based on the causes that led to a request for evaluation.

2.4 Statistical analysis

Data analysis was performed by Statistical Package for Social Science (SPSS version 21.0). Numerical variables were summarized as mean $\pm$ standard deviation (SD) for parametric data, and nominal data were summarized as percentage. The normality of the data used the Shapiro-Wilk test and Lilliefors test. If data were normally distributed, then parametric statistical tests were used; otherwise nonparametric tests were used.

Cases were subdivided according to the categories. The data were analyzed via a $\chi$${}^2$ test. Other specific statistical tests are described as they are encountered in the article. p-values less than 0.05 were considered significant.

3.1 Sample description

There were 159 cases from March 2019–January 2020 with 71 females (44.64%) and 88 males (55.36%); all were Caucasian. The mean age was 60.24 years [range 1–98; DS 15.6]. As for the categories, 61 cases (38.4%) were attributable to a surgical error. The other 63 cases (39.6%) were attributable to diagnostic or therapeutic errors/nosocomial infections. Twenty cases (12.6%) were attributable to a delay in treatment (diseases for which the outcome was time-dependent such as myocardial infarctions, aortic dissections, hemorrhages, etc.). The other 15 cases (9.4%) were attributed to a problem in patient care (especially falls in hospital or injuries caused by patients entrusted to the hospital who had left the hospital without the knowledge of the healthcare workers).

There were 130 cases from March 2020–January 2021 with 57 (43.85%) women and 73 (56.15%) men all of Caucasian race and average age of 59.2 years [range 1–102; DS 16.52]. Surgical errors were reported in 45 cases (34.6%). Forty cases (30.8%) had diagnostic, therapeutic, or nosocomial origin pathologies (surprisingly no cases of COVID-19). In 25 (19.2%) cases, the request for evaluation was based on a delay in treatment or access to the hospital. In the remaining 20 cases (15.4%), the requests for evaluation were based on a patient care problems (Fig. 1).

Fig. 1.Sample under examination and control sample divided according to the causes that led to the evaluation for any professional liability.

3.2 Results of general analysis

The cases attributable to groups A + B were compared with those attributable to those C + D. The analysis used a $\chi$${}^2$ test with tolerated error fixed at 5% ($\alpha$ = 0.05).

The test results showed a significantly significant increase from March 2020 to January 2021 for groups C and D versus the reference period (March 2019–January 2020). The $\chi$${}^2$ test was 5.67. The p-value was 0.11 (significant at p $<$ 0.05) (Table 1).

3.3 Temporal distribution of cases

The distribution of cases was uniform over time: March–May, June–September, and October–January. There was a decrease in the absolute number of Groups A and B complaints and a simultaneous increase in the absolute number of complaints for cases in groups C and D mainly in phase I of the pandemic in Italy (hard lockdown). The absolute number of complaints in the subsequent phases (June-September and October-January) is consistent with what occurred in the control group (Fig. 2).

Fig. 2.Chronological distribution in the different phases of the year. Cases in 2019–2020 (A) divided according to time intervals corresponding in 2020–2021 (B) to the tight lockdown period (March–May), decrease in restrictions (June–September), and return to moderate restrictions (October–January).

3.4 Focus on Groups C and D

The data showed differences in group C (delay in diagnosing and performing surgical interventions with respect to the time frame indicated in the guidelines) and group D (injuries due to a lack of care). For group C analysis, we performed a first-level analysis on the 25 cases of the study group and on the 20 cases of the control group distinguishing between cases in which the delay was due to the conditions of the patient and those in which it was due to organizational or structural problems.

Of the 25 cases, in 12 (48%) cases the delay was due to the need for stabilization of the patient following a decompensation that made them not transportable (polytrauma after road accident, need to support vital functions on site). In two (8%) cases, the event occurred in centers distant from a hospital able to guarantee a surgical/therapeutic intervention ($>$ 1.5 h). In two (8.0%) cases, due to the lack of specificity of the symptoms, the patients were referred to specialist cardiological care and died at home due to AMI and intestinal perforation. In nine (36%) cases, there was a delay with respect to the reference timing, and the course of time-dependent diseases was directly influenced by the implementation of the protocols necessary to prevent the spread of the COVID-19 pandemic. In particular, five of these (55.56%) cases led to the activation of the protocol with delayed diagnosis of the underlying pathology: aortic dissection, two cases of AMI, strangulated inguinal hernia, acute appendicitis. These subjects had hyperpyrexia, which required a SARS-Cov-2 testing after triage according COVID-19 guidelines.

In one (11.11%) case (bacterial pneumonia), the presence of dyspnea meant that the COVID-19 protocol was activated, but a medical vehicle arrived on site three hours after the first call and the patient died during transport to the hospital. (The medical vehicles were engaged in other aid and the volunteers did not have the PPE equipment necessary to transport the patient). In another (11.11%) case, the lack of operating rooms due to the need to sanitize the environment led to a two-day delay of an operation for abdominal aortic aneurysms of an already hospitalized patient. During this period, there was a sudden precipitation of symptoms leading to death. In two cases (22.22%), the nearest hospital was a COVID-19 center, and the patients were referred to another center after a pre-triage from which non-specific signs emerged (epigastric pain and non-specific abdominal pain which later turned out to be a fissured aortic aneurysm MI).

Out of the nine cases examined, the delay in the treatment of pathologies in which the outcome is time-dependent led to death. In one (appendicitis) the patient came to the attention of a surgeon more than 48 hours after the onset of symptoms and a laparoscopic intervention was required. Of the 20 patients in the control group, 15 cases (75%) had delay due to poor stability of the patient for polytrauma (8 cases) or for different medical conditions. These situations made the patients non-transportable prior to stabilization.

In three (15%) cases, the patient suffering from atypical symptoms (in one case characterized by abdominal pain and headache in others) was sent home pending specialist examinations. In two (10%) cases, the delay was due to the coordination between rescues or to the distance of the hospital structure capable of managing a specific type of pathology (Fig. 3).

Fig. 3.Group C (delay) sub-analysis. (A) Data from March 2019–January 2020. (B) Data from March 2020–January 2021. In red triage errors influenced by COVID-19 related measures. In blue triage errors not influenced by COVID-19 related measures.

With regards to assessments requested for alleged “care shortages”, the absolute number of requests regarding falls in hospital (nine cases) remained unchanged even if the patient denounced them for this cause there was a decrease in terms of percentage (64% vs. 45%). There was a slight decrease for injuries in non-autonomous patients who went around the wards [five (29%) vs. two (10)]. On the other hand, there was a slight increase in complaints for patients who died in the facilities without direct assistance from health personnel [one (7%) vs. two (10%)]. Unlike in 2019, there was one (5%) complaint for a patient who committed suicide in the health facility and six (30%) requests for evaluation for patients in whom pressure ulcers developed (Fig. 4).

Fig. 4.Group D (assistance) sub-analysis. (A) Data from March 2019 to January 2020. (B) Data for the interval March 2020 to January 2021.