The Quality of Surgical Care at a Newly-Started Healthcare Center and Its Objective Assessment by the Modified Jabalpur-Portsmouth Physiological and Operative Severity Score (J-POSSUM) in Northern India

Background Risk-adjusted mortality and morbidity provide more accurate and insightful data on the quality of care any healthcare system delivers. The Physiologic and Operative Severity Score for the Study of Mortality and Morbidity (POSSUM) and Portsmouth-POSSUM (P-POSSUM) calculate the risk for operative morbidity and mortality, which can help patients and their families make informed decisions about surgery, complications, and quality of care audits. The study aimed to assess existing surgical services objectively via the validated POSSUM equation in a developing tertiary health care institute. Methods The study was a hospital-based ambispective study at a newly started hospital in Northern India from February 2022 to February 2024 among patients aged 12-75 years. The study was conducted in two phases. The first phase involved a retrospective audit of patient records, validation/Correction of the POSSUM equation, and measures to improve the quality of patient care. The second phase determined the prediction of morbidity via the modified POSSUM equation and outcome assessment after implementation of patients' quality of care corrective measures. Morbidity was considered if any intraoperative and/or postoperative complications occurred within 30 days of the index operation. Exclusion criteria were severely immunocompromised patients, polytrauma patients, and patients with transfusion-related reactions. The surgical procedures were categorised according to the surgeon's convenience into four categories to compare the difficulties of surgical procedures. If a patient developed multiple complications, they were considered as one patient. Results The POSSUM and P-POSSUM equations for morbidity and mortality (n=217) in phase I showed the observed/expected ratio 3.42 (p=0.04) for patients categorised in the minor surgeries. So, Jabalpur-POSSUM (J-Possum) was recalculated by a correction factor of 0.619 for morbidity (predicted risk is <40%) and 0.257 (predicted risk is <10%). The J-POSSUM was plotted against morbidities to reassure predictive accuracy (p=0.00). Mean physiological and operative scores of phase II (n=470) patients were comparable with those of phase I (n=217) (p=0.11 and p=0.52). The number of patients having predicted risk of increased morbidity increased significantly in phase II (p=0.00), but complication rates decreased significantly from 69/214 (32.2%) to 71/470 (15.10%) (p=0.02). The predicted J-POSSUM equation suggested a significant decrease in intraoperative/ postoperative morbidities in phase II (p=0.00 and p=0.016), despite the increased number of patients having an increased predicted risk of morbidity in phase II (p=0.00). The expected increase in the number of patients at risk for mortality was enhanced on J-POSSUM (p=0.016). In phase I and II, mortality was 2/214 (0.09%) and 7/470 (1.5%), respectively. The P-POSSUM equation for mortality cannot be validated in the study population because of undersampling. Conclusion The author suggests the use of J-POSSUM as a validated benchmarking score in Indian settings to predict morbidities, especially in elective minor, intermediate, and major cases. Due to undersampling, the P-POSSUM equation for mortality could not be used in the current study.