Clinical evaluation of the national hospital-acquired complication programme.

BACKGROUND: The national hospital-acquired complication programme captures complications arising from patient-related and hospital-related factors, but the proportion of the two is unclear. AIM: Health services are encouraged to evaluate data from the national hospital-acquired complications (HAC) programme and identify strategies to mitigate them. METHODS: A retrospective chart review compared HAC extracted from administrative data. The setting was a 430-bed university-affiliated metropolitan hospital. Records from 260 participants with, and 462 without, reported HAC from 2619 multi-day stay adults were reviewed. The main outcome measures were prevalence and positive predictive value (PPV) of HAC methodology. RESULTS: No errors of HAC coding or classification were identified. Four hundred and twenty-three HAC events were reported in 260 records; most commonly delirium (n = 57; 13.4%), pneumonia (n = 46; 10.9%), blood stream infection (n = 39; 9.2%), hypoglycaemia (n = 33; 7.8%) and cardiac arrhythmias (n = 33; 7.8%). One hundred and eight (25.5%) 'HAC' events in 69 separations (95% confidence interval (CI) = 2.05-3.33 per 100 separations) were false positive, and 43 of 462 (95% CI = 6.72-12.22 per 100 separations) were false negative. Prevalence of total (reported plus missing) HAC was 16.06 (95% CI = 14.02-19.52), reported HAC was 9.93 (95% CI = 8.76-11.21), potentially preventable HAC was 1.68 (95% CI = 1.22-2.26) and healthcare errors was 0.31 (95% CI = 0.13-1.30) per 100 separations. PPV of HAC for true clinical events was 0.74 (0.68-0.79), preventable events 0.18 (0.13-0.23) and healthcare error 0.03 (0.01-0.06). CONCLUSIONS: Prevalence of HAC events was higher than expected, but PPV for healthcare errors was low, suggesting provision of care is a less common cause of HAC events than patient factors. HAC may be an indicator of hospital admission complexity rather than HAC.

Post-intensive care syndrome: Screening and management in primary care.

BACKGROUND: Post-intensive care syndrome (PICS) affects as many as 50% of intensive care unit (ICU) survivors, and symptoms can persist for months to years. When psychological symptoms are experienced by patients' loved ones, this is termed PICS-family (PICS-F). Patients with these syndromes represent a frequently underrecognised and suboptimally managed cohort. OBJECTIVE: The aim of this article is to outline the key aspects of screening and primary care management, providing an evidence-based framework for general practitioners (GPs). DISCUSSION: PICS screening is not well defined. The breadth of symptoms, along with the absence of a national consensus, renders in-depth assessment a significant undertaking. Community management relies on a coordinated effort from the whole multidisciplinary team, spearheaded by the GP, and focuses on three key areas: 'information and education', 'assessment and therapy' and 'personal support'. Collaboration between key stakeholders is needed to improve outcomes in this hitherto underrecognised patient population.

Post-intensive care syndrome: A crash course for general practice.

BACKGROUND: Post-intensive care syndrome (PICS) refers to a constellation of cognitive, psychiatric and physical symptoms experienced by patients during and following a period of critical illness. As many as 50% of intensive care unit (ICU) survivors are affected, and symptoms can persist for months to years. When psychological symptoms are experienced by patients' loved ones, this is termed PICS-family (PICS-F). OBJECTIVE: The aim of this article is to summarise the key facets of PICS and PICS-F with a focus on incidence and pathophysiology.  DISCUSSION: The amalgam of symptoms in PICS has a profound impact on the quality of life of affected ICU survivors. The number of patients with PICS is expected to rise considerably as a result of the COVID-19 pandemic. Primary care practitioners are ideally situated to assist in early diagnosis and treatment.