JMIR Publications

ABSTRACT

Background:

The social determinants of health, understood as the circumstances in which people are born, grow up, work, live, age, including the healthcare system, can be more influential on people's health than medical or lifestyle choices. Despite having demonstrated their strong relationship on people's health, there is a deficit of registration in the computerised medical history of patients and primary care plays a key role. The recording of social determinants of health in the electronic medical record is coded and recorded through non-clinical diagnoses or Z-coded diagnoses. In this study we rely on the Z-coding of the Statistical Classification of Diseases and Related Health Problems of the World Health Organization. With the aim of improving people's health, this study aims to increase the recording of Z-coding in the patient's computerised medical record and thus to adapt the treatment.

Objective:

To develop and evaluate the effectiveness of a mixed intervention (face-to-face-digital) aimed at improving the quantity and quality of the records of the social determinants of health in computerised medical records at primary care clinics.

Methods:

An intervention consisting of face-to-face and virtual training was provided to the health professionals who participated in the study. The aim of the intervention was to increase the recording of 5 social determinants. The choice of the 5 social determinants of health was made taking into account usability, benefit and existing social determinants terminology. A checklist was provided as a tool to facilitate the coding of the social determinants of health in the patient's computerised medical record. This checklist was designed by 3 professionals belonging to different disciplines and with experience in primary care. It was subsequently integrated as part of the usual multidisciplinary clinical workflow in primary care practices. A total of 176 primary care professionals were analyzed, of which 39 professionals belonged to the intervention group and 137 to the control group

Results:

After 6 months from the implementation of the intervention, we compared the number of records of 5 social determinants of health and observed a significant increase in the median number of diagnoses before and after the intervention (p=<.001). There was also an increase in the diversity of selected social determinants. Using the linear regression model, the significant mean increase in the experimental group with respect to the control group was estimated with a coefficient of 8.18 (95% CI: 5.11;11.26)

Conclusions:

The described intervention is an effective tool for Z-diagnosis coding designed by a multidisciplinary team. The results have shown that this tool is ideal to be incorporated into the workflow of primary care practices. The effectiveness of its usability and the description of the intervention described here should be generalizable to any health care setting Clinical Trial: NCT04151056