The development of an HIV-specific complexity rating scale

Abstract

As treatment for HIV improves, an ageing population is experiencing comorbidity which often leads to complex clinical presentations requiring an interdisciplinary care approach. This study sought to quantify clinician assessment of the level of clinical complexity, through the development of a rating scale for people living with HIV (PLHIV), to improve client care through an interdisciplinary care model. An existing alcohol and other drug complexity rating scale was selected and modified for use with PLHIV. HIV-specific items were included through consultation with an interdisciplinary team. A risk-prediction model was developed and validated using clinician ratings of clients attending The Albion Centre, a tertiary HIV clinic in Sydney, Australia, resulting in the development of the Clinical Complexity Rating Scale for HIV (CCRS-HIV). Multivariable logistic regression models identified eight characteristics based on clinician assessment of complexity in PLHIV: financial instability, social isolation, problematic crystal methamphetamine use, mental illness and/or other problematic substance use, cognitive/neurological impairment, polypharmacy, current hepatitis C infection and/or cancer, and other physical health comorbidity. A weighted risk-prediction model was developed and validated. The final model accurately predicted 85% of complex clients, with a sensitivity of 80% and specificity of 91%. This study developed an HIV-specific clinician-rated complexity scale. Further investigations are required to validate the CCRS-HIV with broader HIV populations. This simple complexity screening tool is a promising adjunct to clinical assessment to identify clients with complex physical and psychosocial needs who may benefit from interdisciplinary care interventions and allocation of resources.

The Role of Comorbidity on Retention in HIV Care

“…Scores are weighted, acknowledging that variables do not all have the same degree of impact on functioning. During validation, the screening tool was shown to accurately predict 85% of complex clients, with a sensitivity of 80% and specificity of 91% [ 13 ]. Examples of decision-making when scoring the tool include “Does financial instability impact the person’s current functioning?”, or “Does the presence of other physical health comorbidity impact the person’s current functioning?”.…”

“…Examples of decision-making when scoring the tool include “Does financial instability impact the person’s current functioning?”, or “Does the presence of other physical health comorbidity impact the person’s current functioning?”. In the validation study, those with a total score of 0–29 were considered in the ‘low’ complexity range, those with a total score of 30–39 in the ‘medium’ complexity range, and those with a score of 40 or greater in the ‘high’ complexity range [ 13 ]. Scores were then summed in both domains.…”

“…Given the retrospective design of the study, only routinely collected variables were reviewed, including age and sex. All clients attending Albion for medical HIV care had been assessed by their treating AMO for medical and/or psychosocial comorbid presentations, using the Clinical Complexity Rating Scale for HIV [CCRS-HIV; [13]]. This 8-item tool has been validated to screen for complex medical and/ or psychosocial comorbidity.…”

“…The profile and frequency of comorbidity identified by clinicians using the CCRS-HIV [13] are presented in Table 2. The majority (71.6%) of the sample were classified in the 'low' complexity range (with 42.4% not scoring on any variable), 7.7% in the 'medium' range, and a further 20.7% in the 'high' range.…”

“…These authors noted that, although psychosocial comorbidities were often central in determining the schedule and frequency of follow-up visits, this data is not consistently captured in medical records and therefore could not be included in their algorithm [ 12 ]. A third study developed a brief risk-prediction screening tool of clinician-assessed physical and psychosocial comorbidity and clinical complexity for people living with HIV in Sydney, Australia [ 13 ]. Such research highlights a way to capture the characteristics of those at risk of sub-optimal appointment adherence in a standardized manner.…”