A method for analyzing inpatient care variability through physicians' orders

Status quo of pain-related patient reported outcomes and perioperative pain management in 10 415 patients from 10 countries: analysis of registry data

BACKGROUND

Postoperative pain is common at the global level, despite considerable attempts for improvement, reflecting the complexity of offering effective pain relief. In this study, clinicians from Mexico, China, and eight European countries evaluated perioperative pain practices and patient-reported outcomes (PROs) in their hospitals as a basis for carrying out quality improvement (QI) projects in each country.

METHODS

PAIN OUT, an international perioperative pain registry, provided standardized methodology for assessing management and multi-dimensional PROs on the first postoperative day, in patients undergoing orthopedic, general surgery, obstetric & gynecology or urological procedures.

RESULTS

Between 2017-2019, data obtained from 10,415 adult patients in 105 wards, qualified for analysis. At the ward level: 50% (median) of patients reported worst pain intensities ≥7/10 NRS, 25% spent ≥50% of the time in severe pain and 20-34% reported severe ratings for pain-related functional and emotional interference. Demographic variables, country and surgical discipline explained a small proportion of the variation in the PROs, leaving about 88% unexplained. Most treatment processes varied considerably between wards. Ward effects accounted for about 7% and 32% of variation in PROs and treatment processes, respectively.

CONCLUSIONS

This comprehensive evaluation demonstrates that many patients in this international cohort reported poor pain-related PROs on the first postoperative day. PROs and treatments varied greatly. Most of the variance of the PROs could not be explained. The findings served as a basis for devising and implementing QI programs in participating hospitals.

Methods and measures to quantify ICU patient heterogeneity

Patients in intensive care units are heterogeneous and the daily prediction of their days to discharge (DTD) a complex task that practitioners and computers are not always able to solve satisfactorily. In order to make more precise DTD predictors, it is necessary to have tools for the analysis of the heterogeneity of the patients. Unfortunately, the number of publications in this field is almost non-existent. In order to alleviate this lack of tools, we propose four methods and their corresponding measures to quantify the heterogeneity of intensive patients in the process of determining the DTD. These new methods and measures have been tested with patients admitted over four years to a tertiary hospital in Spain. The results deepen the understanding of the intensive patient and can serve as a basis for the construction of better DTD predictors.