# Assessing the Impact of Patient Characteristics on Genetic Clinical Pathways: A Regression Approach
## 3 Results
### Identification of Clinical Pathways  
In Table 1, we report the main motivations, i.e., the diagnostic questions, reported by the clinicians at the time of referral. The list includes pathologies (e.g., genetic, cytogenetic,  
Figure 1: The influence of individual characteristics on care complexity and clinical pathway length.  
chromosomal) and exposures (e.g., radiation, drugs, infection) that might impact the health of the fetus.  
The first step for the modeling was to assign each patient to a motivation, i.e., the diagnostic question, because, according to Evidence-Based Medicine (EBM) guidelines, assignment to a specific diagnostic treatment protocol should depend on this [22; 23].  
In Table 2, the number of motivations recorded for the 2119 patients is reported. We observe that the majority of patients (1866) present only one motivation, but a substantial number (253) present two or more entry motivations. It is evident that in the case of patients with only one motivation, the allocation of patients to the specific protocol was completed automatically by the information in the database. For the others, with double motivation or multiple motivations, the association to the pathway was made with the support of the medical doctors of the operating units involved.  
As a result, it was possible to agree on some general allocation rules (Table 3). This was, however, only possible for 210 patients. The other 43 were considered to be special cases and had to be assigned one by one.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Motivation** & **Description of the Motivation for the Diagnosis** \\ \hline
1 & Gene pathology in the family \\
2 & Chromosomal pathology in the family \\
3 & Multifactorial/heterogeneous pathology in the family \\
4 & Undefined or other pathology in the family \\
5 & Fetal ultrasound pathology \\
6 & Cytogenetic fetal pathology \\
7 & Fetal screening \\
8 & Maternal exposure to radiation \\
9 & Maternal exposure to drugs \\
10 & Maternal environmental exposure \\
11 & Maternal infection exposure \\
12 & Consanguinity \\
13 & Maternal age (EMA)—Chorionic villi \\
14 & Maternal age (EMA)—Amniotic fluid \\
15 & Non-specific indication \\ \hline \hline \end{tabular}
\end{table}
Table 1: List and description of the motivations for clinical investigation.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Motivations Assigned to Patients** & **Number of Patients** \\ \hline One motivation & 1866 \\ Two motivations & 239 \\ Three motivations & 13 \\ Four motivations & 1 \\ \hline Total & 2119 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Distribution of the number of motivations assigned to patients.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Motivations Assigned to Patients** & **Number of Patients** \\ \hline One motivation & 1866 \\ Two motivations & 239 \\ Three motivations & 13 \\ Four motivations & 1 \\ \hline Total & 2119 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Rules for assigning patients to a motivation group.  
Subsequently, considering the diagnostic-therapeutic protocols prescribed by medical practice for different cases, again on the recommendation of the medical doctors, it was possible to aggregate the different groups of motivations, thus arriving at the definition of 16 clinical pathways that identify homogeneous groups of patients in terms of the type of services to be provided (Table 4).  
The most consistent flows are those corresponding to Motivations 13 and 14, referred to overall as type-A pathways, corresponding to the Maternal Age (EMA) motivation. Type-B pathways are those corresponding to single or multiple motivations identified using rules (the 210 cases reported in Table 3), and type C refers to the 43 individually assigned patients.