Bridging the impactibility gap in population health management: a systematic review

Identifying individuals with complex and long-term health-care needs using the Johns Hopkins Adjusted Clinical Groups System: A comparison of data from primary and specialist health care

AIMS

This study aimed to present the Johns Hopkins Adjusted Clinical Groups (ACG) System risk stratification profile of a total adult population of somatic health-care users when using data from either general practitioners (GPs) or hospital services and to compare the number and characteristics of individuals identified as having complex and long-term health-care needs in each data source.

METHODS

This was a registry-based study that included all adult residents (N=168,285) in four municipalities in Central Norway who received somatic health care during 2013. Risk profiles were generated using the ACG System based on age, sex and diagnoses registered by GPs or the local hospital. ACG output variables on number of chronic conditions, frailty and concurrent resource utilisation were chosen as indicators of complexity.

RESULTS

Nearly nine out of 10 (83.9%) of the population had been in contact with a GP, and 35.4% with the hospital. The mean number of diagnoses (3.0) was equal in both sources. A larger proportion of the population had higher risk scores in all variables except frailty when comparing hospital data to GP data. This was also found when comparing individuals identified as having complex and long-term health-care needs. A similar proportion of the population was found to have complex and long-term health-care needs (hospital 6.7%, GP 6.3%), but only one in five (21.5%) were identified in both data sets.

CONCLUSIONS

As data from GPs and hospitals identified mostly different individuals with complex and long-term health-care needs, combining data sources is likely to be the best option for identifying those most in need of special attention.

Exploration of understanding of impactibility analysis and application through workshops to inform model design for population health management policy: a qualitative assessment

OBJECTIVES

Assess understanding of impactibility modelling definitions, benefits, challenges and approaches.

DESIGN

Qualitative assessment.

SETTING

Two workshops were developed. Workshop 1 was to consider impactibility definitions and terminology through moderated open discussion, what the potential pros and cons might be, and what factors would be best to assess. In workshop 2, participants appraised five approaches to impactibility modelling identified in the literature.

PARTICIPANTS

National Health Service (NHS) analysts, policy-makers, academics and members of non-governmental think tank organisations identified through existing networks and via a general announcement on social media. Interested participants could enrol after signing informed consent.

OUTCOME MEASURES

Descriptive assessment of responses to gain understanding of the concept of impactibility (defining impactibility analysis), the benefits and challenges of using this type of modelling and most relevant approach to building an impactibility model for the NHS.

RESULTS

37 people attended 1 or 2 workshops in small groups (maximum 10 participants): 21 attended both workshops, 6 only workshop 1 and 10 only workshop 2. Discussions in workshop 1 illustrated that impactibility modelling is not clearly understood, with it generally being viewed as a cross-sectional way to identify patients rather than considering patients by iterative follow-up. Recurrent factors arising from workshop 2 were the shortage of benchmarks; incomplete access to/recording of primary care data and social factors (which were seen as important to understanding amenability to treatment); the need for outcome/action suggestions as well as providing the data and the risk of increasing healthcare inequality.

CONCLUSIONS

Understanding of impactibility modelling was poor among our workshop attendees, but it is an emerging concept for which few studies have been published. Implementation would require formal planning and training and should be performed by groups with expertise in the procurement and handling of the most relevant health-related real-world data.

Modifiable risk factors that may be addressed in routine care to prevent progression to and extension of multimorbidity in people with COPD: a systematic literature review

Chronic obstructive pulmonary disease (COPD) is a multisystem disease, and many patients have multiple conditions. We explored multimorbidity patterns that might inform intervention planning to reduce health-care costs while preserving quality of life for patients. Literature searches up to February 2022 revealed 4419 clinical observational and comparative studies of risk factors for multimorbidity in people with COPD, pulmonary emphysema, or chronic bronchitis at baseline. Of these, 29 met the inclusion criteria for this review. Eight studies were cluster and network analyses, five were regression analyses, and 17 (in 16 papers) were other studies of specific conditions, physical activity and treatment. People with COPD more frequently had multimorbidity and had up to ten times the number of disorders of those without COPD. Disease combinations prominently featured cardiovascular and metabolic diseases, asthma, musculoskeletal and psychiatric disorders. An important risk factor for multimorbidity was low socioeconomic status. One study showed that many patients were receiving multiple drugs and had increased risk of adverse events, and that 10% of medications prescribed were inappropriate. Many patients with COPD have mainly preventable or modifiable multimorbidity. A proactive multidisciplinary approach to prevention and management could reduce the burden of care.

Toward Adoption of Health Risk Assessment in Population-Based and Clinical Scenarios: Lessons From JADECARE

Introduction

Health risk assessment (HRA) strategies are cornerstone for health systems transformation toward value-based patient-centred care. However, steps for HRA adoption are undefined. This article analyses the process of transference of the Adjusted Morbidity Groups (AMG) algorithm from the Catalan Good Practice to the Marche region (IT) and to Viljandi Hospital (EE), within the JADECARE initiative (2020-2023).

Description

The implementation research approach involved a twelve-month pre-implementation period to assess feasibility and define the local action plans, followed by a sixteen-month implementation phase. During the two periods, a well-defined combination of experience-based co-design and quality improvement methodologies were applied.

Discussion

The evolution of the Catalan HRA strategy (2010-2023) illustrates its potential for health systems transformation, as well as its transferability. The main barriers and facilitators for HRA adoption were identified. The report proposes a set of key steps to facilitate site customized deployment of HRA contributing to define a roadmap to foster large-scale adoption across Europe.

Conclusions

Successful adoption of the AMG algorithm was achieved in the two sites confirming transferability. Marche identified the key requirements for a population-based HRA strategy, whereas Viljandi Hospital proved its potential for clinical use paving the way toward value-based healthcare strategies.

The incidence rate of planned and emergency physical health hospital admissions in people diagnosed with severe mental illness: a cohort study

BACKGROUND

People with severe mental illness (SMI) have more physical health conditions than the general population, resulting in higher rates of hospitalisations and mortality. In this study, we aimed to determine the rate of emergency and planned physical health hospitalisations in those with SMI, compared to matched comparators, and to investigate how these rates differ by SMI diagnosis.

METHODS

We used Clinical Practice Research DataLink Gold and Aurum databases to identify 20,668 patients in England diagnosed with SMI between January 2000 and March 2016, with linked hospital records in Hospital Episode Statistics. Patients were matched with up to four patients without SMI. Primary outcomes were emergency and planned physical health admissions. Avoidable (ambulatory care sensitive) admissions and emergency admissions for accidents, injuries and substance misuse were secondary outcomes. We performed negative binomial regression, adjusted for clinical and demographic variables, stratified by SMI diagnosis.

RESULTS

Emergency physical health (aIRR:2.33; 95% CI 2.22-2.46) and avoidable (aIRR:2.88; 95% CI 2.60-3.19) admissions were higher in patients with SMI than comparators. Emergency admission rates did not differ by SMI diagnosis. Planned physical health admissions were lower in schizophrenia (aIRR:0.80; 95% CI 0.72-0.90) and higher in bipolar disorder (aIRR:1.33; 95% CI 1.24-1.43). Accident, injury and substance misuse emergency admissions were particularly high in the year after SMI diagnosis (aIRR: 6.18; 95% CI 5.46-6.98).

CONCLUSION

We found twice the incidence of emergency physical health admissions in patients with SMI compared to those without SMI. Avoidable admissions were particularly elevated, suggesting interventions in community settings could reduce hospitalisations. Importantly, we found underutilisation of planned inpatient care in patients with schizophrenia. Interventions are required to ensure appropriate healthcare use, and optimal diagnosis and treatment of physical health conditions in people with SMI, to reduce the mortality gap due to physical illness.