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

Abstract

ObjectivesAssess whether impactibility modelling is being used to refine risk stratification for preventive health interventions.DesignSystematic review.SettingPrimary and secondary healthcare populations.PapersArticles published from 2010 to 2020 on the use or implementation of impactibility modelling in population health management, reported with the terms ‘intervenability’, ‘amenability’, and ‘propensity to succeed’ (PTS) and associated with the themes ‘care sensitivity’, ‘characteristic responders’, ‘needs gap’, ‘case finding’, ‘patient selection’ and ‘risk stratification’.InterventionsQualitative synthesis to identify themes for approaches to impactibility modelling.ResultsOf 1244 records identified, 20 were eligible for inclusion. Identified themes were ‘health conditions amenable to care’ (n=6), ‘PTS modelling’ (n=8) and ‘comparison or combination with clinical judgement’ (n=6). For the theme ‘health conditions amenable to care’, changes in practice did not reduce admissions, particularly for ambulatory care sensitive conditions, and sometimes increased them, with implementation noted as a possible issue. For ‘PTS modelling’, high costs and needs did not necessarily equate to high impactibility and targeting a larger number of individuals with disorders associated with lower costs had more potential. PTS modelling seemed to improve accuracy in care planning, estimation of cost savings, engagement and/or care quality. The ‘comparison or combination with clinical judgement’ theme suggested that models can reach reasonable to good discriminatory power to detect impactable patients. For instance, a model used to identify patients appropriate for proactive multimorbid care management showed good concordance with physicians (c-statistic 0.75). Another model employing electronic health record scores reached 65% concordance with nurse and physician decisions when referring elderly hospitalised patients to a readmission prevention programme. However, healthcare professionals consider much wider information that might improve or impede the likelihood of treatment impact, suggesting that complementary use of models might be optimum.ConclusionsThe efficiency and equity of targeted preventive care guided by risk stratification could be augmented and personalised by impactibility modelling.

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

“…Moreover, the momentum propitiated by the continuous progress in digital technologies for data capture and management, artificial intelligence and the advances in medical sciences are shaping novel and stimulating scenarios for health promotion and care and positioning predictive medicine at the forefront [7][8][9]. Despite the promising potential of HRA, there is a noticeable gap between its benefits and its current application, attributed to several limitations, including the utilisation of suboptimal risk assessment tools, the insufficient engagement of health professionals, the application of ineffective or inexistent deployment strategies, and unresolved ethical and regulatory issues [10,11].…”

A Critical Review of Global Digital Divide and the Role of Technology in Healthcare

“…The various groups within a population can be classified based on nationality, race, cultural variations, city /village/town of residence, or geography of the location [14]. Apps that connect you instantaneously to a doctor as per your need, software that allows the making and maintaining of electronic patient case records, facilitating access for both patients and physicians, android applications that allow you to monitor your vitals and provide timely tips to manage your lifestyle, and many more such up and coming software or electronic programs form the umbrella of population health tools [15].…”

“…Population health management (PHM) implies (quality-care-cost) triple objectives of cutting down per capita health expenditure, enriching the health & well-being of the populace, and enhancing every individual's experience of healthcare [15]. To bring these objectives to fruition, population health management involves bettering access to healthcare for all and fortifying uniform availability of disease screening/ preventive services, and spurring positive behavioral changes [16].…”

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

“…Predicting which people with COPD will go on to develop or experience extension of multimorbidity and planning how to intervene to address modifiable risk factors could help to reduce costs and preserve quality of life for patients. This systematic literature review was performed as part of the groundwork for development of an impactibility model 17 and had the objective of exploring the breadth of relevant information in the literature. In this paper, we discuss which modifiable risk factors are most reported in people with COPD and might be possible to address in routine care to prevent progression to or extension of multimorbidity in people with an existing COPD diagnosis.…”