Dataset Information

Perceptions of Risk Stratification Workflows in Primary Care.

ABSTRACT: Risk stratification (RS) in primary care is frequently used by policy-makers, payers, and health systems; the process requires risk assessment for adverse health outcomes across a population to assign patients into risk tiers and allow care management (CM) resources to be targeted effectively. Our objective was to understand the approach to and perception of RS in primary care practices. An online survey was developed, tested, and administered to 148 representatives of 37 primary care practices engaged in RS varying in size, location and ownership. The survey assessed practices' approach to, perception of, and confidence in RS, and its effect on subsequent CM activities. We examined psychometric properties of the survey to determine validity and conducted chi-square analyses to determine the association between practice characteristics and confidence and agreement with risk scores. The survey yielded a 68% response rate (100 respondents). Overall, participants felt moderately confident in their risk scores (range 41-53.8%), and moderately to highly confident in their subsequent CM workflows (range 46-68%). Respondents from small and independent practices were more likely to have higher confidence and agreement with their RS approaches and scores (p < 0.01). Confidence levels were highest, however, when practices incorporated human review into their RS processes (p < 0.05). This trend was not affected by respondents' professional roles. Additional work from a broad mixed-methods effort will add to our understanding of RS implementation processes and outcomes.

SUBMITTER: Ross RL

PROVIDER: S-EPMC5746712 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Perceptions of Risk Stratification Workflows in Primary Care.

Ross Rachel L RL Sachdeva Bhavaya B Wagner Jesse J Ramsey Katrina K Dorr David A DA

Healthcare (Basel, Switzerland) 20171021 4

Risk stratification (RS) in primary care is frequently used by policy-makers, payers, and health systems; the process requires risk assessment for adverse health outcomes across a population to assign patients into risk tiers and allow care management (CM) resources to be targeted effectively. Our objective was to understand the approach to and perception of RS in primary care practices. An online survey was developed, tested, and administered to 148 representatives of 37 primary care practices ...[more]

PMID: 29065454

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Project description:BackgroundA prospective Population Risk Stratification (PRS) tool was first introduced in the public Basque Health Service in 2011, at the level of its several Primary Care (PC) practices. This paper aims at exploring the new tool's implementation process, as experienced by its potential adopters/users, ie. PC clinicians (doctors and nurses). Findings could help guide future PRS implementation strategies.MethodsThree focus groups exploring clinicians' opinions and experiences related to the PRS tool and its implementation in their daily practice were conducted. A purposive sample of 12 General Practitioners and 11 PC nurses participated in the groups. Discussions were digitally recorded, transcribed verbatim and analysed by two independent researchers using thematic analysis based on Graham et al.'s Knowledge Translation Theory.ResultsExploring PC clinicians' experience with the new PRS tool, allowed us to identify certain elements working as barriers and facilitators in its implementation process. This series of closely interrelated elements, which emerged as relevant in building up the complex implementation process of the new tool, as experienced by the clinicians, can be grouped into four domains: 1) clinicians' characteristics as potential adopters, 2) clinicians' perceptions of their practice settings where PRS is to implemented, 3) clinicians' perceptions of the tool, and 4) the implementation strategy used by the PRS promoter.ConclusionsLessons from the implementation process under study point at the need to frame the implementation of a new PRS tool within a wider strategy encouraging PC clinicians to orientate their daily practice towards a population health approach. The PRS tool could also improve the perceived utility by its potential adopters, by bringing it closer to the clinicians' needs and practice, and allowing it to become context-sensitive. This would require clinicians being involved from the earliest phases of conceptualisation, design and implementation of the new tool, and mounting efforts to improve communication between clinicians and tool promoters.Graham et al.'s Knowledge Translation Theory proved a suitable framework to explore the implementation process of a new PRS tool in the public Basque Health Service's PC practice, and hence to identify implementation barriers and facilitators as experienced by the clinicians.

Project description:BackgroundDespite several countrywide attempts to strengthen and standardise the primary healthcare (PHC) system, Greece is still lacking a sustainable, policy-based model of integrated services. The aim of our study was to identify operational integration levels through existing patient care pathways and to recommend an alternative PHC model for optimum integration.MethodsThe study was part of a large state-funded project, which included 22 randomly selected PHC units located across two health regions of Greece. Dimensions of operational integration in PHC were selected based on the work of Kringos and colleagues. A five-point Likert-type scale, coupled with an algorithm, was used to capture and transform theoretical framework features into measurable attributes. PHC services were grouped under the main categories of chronic care, urgent/acute care, preventive care, and home care. A web-based platform was used to assess patient pathways, evaluate integration levels and propose improvement actions. Analysis relied on a comparison of actual pathways versus optimal, the latter ones having been identified through literature review.ResultsOverall integration varied among units. The majority (57%) of units corresponded to a basic level. Integration by type of PHC service ranged as follows: basic (86%) or poor (14%) for chronic care units, poor (78%) or basic (22%) for urgent/acute care units, basic (50%) for preventive care units, and partial or basic (50%) for home care units. The actual pathways across all four categories of PHC services differed from those captured in the optimum integration model. Certain similarities were observed in the operational flows between chronic care management and urgent/acute care management. Such similarities were present at the highest level of abstraction, but also in common steps along the operational flows.ConclusionsExisting patient care pathways were mapped and analysed, and recommendations for an optimum integration PHC model were made. The developed web platform, based on a strong theoretical framework, can serve as a robust integration evaluation tool. This could be a first step towards restructuring and improving PHC services within a financially restrained environment.

Project description:Background and aimsIn our current healthcare situation, burden on healthcare services is increasing, with higher costs and increased utilization. Structured population health management has been developed as an approach to balance quality with increasing costs. This approach identifies sub-populations with comparable health risks, to tailor interventions for those that will benefit the most. Worldwide, the use of routine healthcare data extracted from electronic health registries for risk stratification approaches is increasing. Different risk stratification tools are used on different levels of the healthcare continuum. In this systematic literature review, we aimed to explore which tools are used in primary healthcare settings and assess their performance.MethodsWe performed a systematic literature review of studies applying risk stratification tools with health outcomes in primary care populations. Studies in Organisation for Economic Co-operation and Development countries published in English-language journals were included. Search engines were utilized with keywords, for example, "primary care," "risk stratification," and "model." Risk stratification tools were compared based on different measures: area under the curve (AUC) and C-statistics for dichotomous outcomes and R 2 for continuous outcomes.ResultsThe search provided 4718 articles. Specific election criteria such as primary care populations, generic health utilization outcomes, and routinely collected data sources identified 61 articles, reporting on 31 different models. The three most frequently applied models were the Adjusted Clinical Groups (ACG, n = 23), the Charlson Comorbidity Index (CCI, n = 19), and the Hierarchical Condition Categories (HCC, n = 7). Most AUC and C-statistic values were above 0.7, with ACG showing slightly improved scores compared with the CCI and HCC (typically between 0.6 and 0.7).ConclusionBased on statistical performance, the validity of the ACG was the highest, followed by the CCI and the HCC. The ACG also appeared to be the most flexible, with the use of different international coding systems and measuring a wider variety of health outcomes.

Project description:BackgroundPatients with complex health care needs may suffer adverse outcomes from fragmented and delayed care, reducing well-being and increasing health care costs. Health reform efforts, especially those in primary care, attempt to mitigate risk of adverse outcomes by better targeting resources to those most in need. However, predicting who is susceptible to adverse outcomes, such as unplanned hospitalizations, ED visits, or other potentially avoidable expenditures, can be difficult, and providing intensive levels of resources to all patients is neither wanted nor efficient. Our objective was to understand if primary care teams can predict patient risk better than standard risk scores.MethodsSix primary care practices risk stratified their entire patient population over a 2-year period, and worked to mitigate risk for those at high risk through care management and coordination. Individual patient risk scores created by the practices were collected and compared to a common risk score (Hierarchical Condition Categories) in their ability to predict future expenditures, ED visits, and hospitalizations. Accuracy of predictions, sensitivity, positive predictive values (PPV), and c-statistics were calculated for each risk scoring type. Analyses were stratified by whether the practice used intuition alone, an algorithm alone, or adjudicated an algorithmic risk score.ResultsIn all, 40,342 patients were risk stratified. Practice scores had 38.6% agreement with HCC scores on identification of high-risk patients. For the 3,381 patients with reliable outcomes data, accuracy was high (0.71-0.88) but sensitivity and PPV were low (0.16-0.40). Practice-created scores had 0.02-0.14 lower sensitivity, specificity and PPV compared to HCC in prediction of outcomes. Practices using adjudication had, on average, .16 higher sensitivity.ConclusionsPractices using simple risk stratification techniques had slightly worse accuracy in predicting common outcomes than HCC, but adjudication improved prediction.

Project description:Insomnia is a widespread issue among United States adults and rates of insomnia among veterans are even higher than the general population. Prior research examining primary care provider (PCP) perspectives on insomnia treatment found that: sleep hygiene and pharmacotherapy are the primary treatments offered; PCPs tend to focus on perceived causes of insomnia rather than the insomnia itself; and neither patients nor providers are satisfied with insomnia treatment options. Although insomnia complaints are typically first reported to primary care providers, little research has focused on perspectives regarding insomnia treatment among PCPs working in the largest integrated health care system in the United States-the Veterans Affairs (VA) health care system. This study was conducted to examine VA PCP perceptions of the availability of insomnia treatments, identify specific strategies offered by PCPs, and examine perceptions regarding the importance of treating insomnia and the role of comorbid conditions.A survey was conducted within the VA health care system. Primary care providers completed surveys electronically.A high percentage of veterans (modal response = 20% to 39%) seen in VA primary care settings report an insomnia complaint to their provider. Almost half of respondents do not consistently document insomnia in the medical record (46% endorsed "sometimes," "rarely," or "never"). PCPs routinely advise sleep hygiene recommendations for insomnia (ie, avoid stimulants before bedtime [84.3%], and keep the bedroom environment quiet and dark and comfortable [68.6%]) and many are uncertain if cognitive behavioral therapy for insomnia is available at their facility (43.1%).Findings point to the need for systems-level changes within health care systems, including the adoption of evidence-based clinical practice standards for insomnia and PCP education about the processes that maintain insomnia.A commentary on this article appears in this issue on page 937.

Dataset Information

Perceptions of Risk Stratification Workflows in Primary Care.

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Perceptions of Risk Stratification Workflows in Primary Care.

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