Skip to main content
Download PDF

Caring for high-need patients

BMC Health Services Research volume 23, Article number: 1289 (2023) Cite this article

Abstract

Objective

We aimed to explore the construct of “high need” and identify common need domains among high-need patients, their care professionals, and healthcare organizations; and to describe the interventions that health care systems use to address these needs, including exploring the potential unintended consequences of interventions.

Methods

We conducted a modified Delphi panel informed by an environmental scan. Expert stakeholders included patients, interdisciplinary healthcare practitioners (physicians, social workers, peer navigators), implementation scientists, and policy makers. The environmental scan used a rapid literature review and semi-structured interviews with key informants who provide healthcare for high-need patients. We convened a day-long virtual panel meeting, preceded and followed by online surveys to establish consensus.

Results

The environmental scan identified 46 systematic reviews on high-need patients, 19 empirical studies documenting needs, 14 intervention taxonomies, and 9 studies providing construct validity for the concept “high need.” Panelists explored the construct and terminology and established that individual patients’ needs are unique, but areas of commonality exist across all high-need patients. Panelists agreed on 11 domains describing patient (e.g., social circumstances), 5 care professional (e.g., communication), and 8 organizational (e.g., staffing arrangements) needs. Panelists developed a taxonomy of interventions with 15 categories (e.g., care navigation, care coordination, identification and monitoring) directed at patients, care professionals, or the organization. The project identified potentially unintended consequences of interventions for high-need patients, including high costs incurred for patients, increased time and effort for care professionals, and identification of needs without resources to respond appropriately.

Conclusions

Care for high-need patients requires a thoughtful approach; differentiating need domains provides multiple entry points for interventions directed at patients, care professionals, and organizations. Implementation efforts should consider outlined intended and unintended downstream effects on patients, care professionals, and organizations.

Peer Review reports

Introduction

High-need patients present challenges to healthcare delivery organizations due to their heterogeneity [1], complexity from multimorbidity or social circumstances, [2, 3] frequent healthcare utilization, [4] and need for higher levels of assistance [5]. These challenges exist at the patient (e.g., poor functional health), healthcare care professionals (e.g., limited training), and the healthcare organization (e.g., resources) level [6].

Many interventions addressing high-need patients have aimed to improve health and health care, to enhance experiences with healthcare, to decrease utilization, and ultimately, to decrease healthcare cost; but there are few clear solutions [7]. Health care systems that seek to improve healthcare delivery for high-need patients may benefit from a greater understanding of the concept of high-need as well as approaches that have been described in literature, including effects on the patients, their care professionals, and the health care organizations.

In this study, we combined an environmental scan with a stakeholder panel to understand the breadth of interventions that have been implemented for high-need patients in healthcare organizations. The environmental scan included insights from key informants and published literature. We engaged stakeholders in a modified Delphi panel process with the following objectives: (1) To explore the construct of “high need” and to identify common needs among high-need patients, their healthcare professionals, and healthcare organizations; and (2) to describe the interventions that health care professionals and health care systems use to address these needs, including exploring potential unintended consequences of the healthcare interventions. We aimed to develop a framework of needs and interventions that can be employed by health systems aiming to improve care for their most vulnerable patients.

Materials and methods

A detailed workplan guided a one-year research process. An environmental scan consisted of a synthesis of published literature and key informant interviews. The results of this environmental scan informed an expert stakeholder panel. The University of Southern California Institutional Review board determined the study to be exempt.

Environmental scan

Environmental scan sources included interviews with key informants and a review of published literature.

Key informant interviews

We selected key informants to provide information potentially not yet available in the published research literature: An experienced social worker from the VA healthcare system; the evidence review team working on the Agency for Healthcare Research and Quality evidence report on high utilizers; [7] an emergency medicine physician in downtown Los Angeles who serves complex patients in underserved communities; and team members on an intensive case management demonstration program from the VA healthcare system team. Key informants provided written and verbal input. Verbal input was obtained in one-hour semi-structured phone interviews. We grouped responses by the definition of “high need,” the content of patient and health care professional needs, intervention types and unintended consequences, issues not fully recognized in research and policy, and available tools (Appendix Table 1).

In addition, we reviewed transcripts of qualitative interviews that were collected through a multi-site intensive case management pilot in primary care to improve care for high-need patients [8]. Appendix Table 2 documents quotes from health care professionals and are thematically organized by categories of needs: social determinants of health; substance use disorder, with or without co-occurring mental health issues; mental health; physical health; multimorbidity or medical complexity; chronic condition or disease management; patient or healthcare professional education; reliable access to healthcare professionals and services; patient or caregiver-clinician and team member relationships; trust; lifestyle change; changed outlook; difficulties in the home; improvements needed in the home environment; challenges navigating VHA care/services; and communication and care coordination. This in-depth analysis informed the stakeholder groups as well as topics that need to be explored further in the literature and panel discussions.

Literature review

The literature review identified systematic reviews that addressed complex patients and empirical investigations aiming to determine the needs of complex primary care patients. We followed rapid literature review methodology and searched the research databases PubMed, CINHAL, and the Web of Science. Searches were designed and executed by an experienced librarian specializing in evidence reviews. Because standard nomenclature for high-need research does not exist, the complex concepts had to be translated into a comprehensive search strategy (see online appendix). In addition, we mined the references of relevant reviews. Two literature reviewers screened the search output, and all publications deemed potentially relevant by at least one reviewer were obtained as full text. The full-text publications were screened against transparent pre-specified eligibility criteria, and the inclusion and exclusion decisions were recorded together with the reasons for exclusion. Eligibility criteria included systematic reviews, empirical studies describing needs, studies validating the construct, intervention taxonomies, and tool collections; full details are provided in the appendix.

Literature searches identified 2,582 citations. Of these, 195 publications were obtained as full text, and 78 were included. The flow diagram (Appendix Fig. 1) provides an overview of the identified literature and reasons for exclusion for excluded studies.

Fig. 1
figure 1

Need domains of high-needs patients, their healthcare professionals, and care organizations

Note: Bolded domains were rated as essential, domains rated as important are also shown (not bolded)

Full size image

Stakeholder panel

We recruited a stakeholder panel representing diverse viewpoints. The panel recruiting process followed a structured, two-step approach: identifying key stakeholders by using a patient-centered framework, [9] followed by finding individuals who could represent the stakeholder group. The 12 panelists (see appendix) included patients, physicians and nurses experienced in the care of high-need patients, policy makers, social worker, peer navigator, and content experts in improvement and implementation science, all of whom were associated with large integrated healthcare delivery systems. The panelists also had clinical experience in four key areas for this patient population: mental health, homelessness, older adults, and addiction.

Data collection

The consensus-finding process consisted of a pre- and post-panel online survey and a day-long virtual panel meeting with presentations and moderated discussions. Panelists were provided with the results of the environmental scan prior to completing the pre-panel survey. Our modified Delphi panel process adhered to principles of consensus methods for medical and health services research: anonymity (private ranking or voting to avoid dominance issues in the group), iteration (multiple rounds to allow individuals to change their opinions after discussions), controlled feedback (feedback of the group response after each rating round), and statistical group response (provision of summary measures of the group response) [10].

The pre-panel survey was divided into sections addressing procedures, terminology, and measurement or operationalization. Panelists were asked about guidance for high-need patients, how the organization defined high need, and how high-need patients were identified in their local organization. Panelists rated characteristics of high-need patients in order to establish a shared understanding of the concept. The survey assessed whether crosscutting recommendations regarding high-need patients are possible, given the heterogeneity of this patient group. Panelists rated 22 different statements regarding the generalizability of tools and recommendation (e.g., “as interventions may need to be uniquely targeted to individual patients, generic recommendations may not be possible.”) The survey asked panelists for a description of the needs of high-need patients and to rate components of need based on suggestions identified in the literature. In addition, about it targeted needs of primary care professionals caring for high-need patients that go beyond the routine strains of the care environment (e.g., clinician burnout is not specific to high-need patients). In addition, the survey elicited needs of the healthcare organizations caring for high-need patients. The survey asked respondents about unintended consequences of interventions for high-need patients that might affect patients, healthcare professionals, or healthcare organizations. Finally, panelists were given an opportunity to identify issues not sufficiently covered in research or existing policy, examples of successful approaches for high-need patients, information on interventions that have been implemented to address high-need patients in panelists’ local organizations, and helpful tools for high-need patients.

The one-day expert panel meeting focused on approaches for high-need patients. The panel meeting had been planned as an in-person meeting, following a standard procedure, [11,12,13,14,15] but had to be converted to an online virtual meeting due to the COVID-19 pandemic. The research team presented the results of the pre-panel survey. Panelists discussed the ratings, focusing primarily on areas of disagreement. Following an approach used for RAND appropriateness panels, no attempt was made to force the panel to consensus [16]. Instead, the process was designed to distinguish between discrepant ratings due to true disagreement (i.e., actual differences in opinion) and misunderstandings (i.e., interpretation differences that can be resolved). In addition to the 12 panelists, several observers were present. Observers were advised to not interrupt the discussions during the panel meeting, and they did not complete the pre-or post-panel survey nor did they vote during the panel meetings. Observers made valuable contributions using the chat function during the panel meeting by providing examples or additional discussion points.

After the meeting, a post-panel survey was sent to panelists to consolidate findings. The survey included pre-panel items that had been discussed during the panel meeting and new items generated in panel discussions. Specifically, the post-panel survey was completed after the meeting to avoid group pressure and groupthink, ensuring independent ratings.

All items were rated on a scale from 1 to 5, where five represented the highest level of importance or relevance, or essential. We analyzed the central tendency, dispersion in ratings, the mode, and the proportion of panelists judging the item to be essential. To determine disagreement, we used a standard deviation value of greater than one and situations where a small number of panelists (up to 30%) identified the item as essential while others did not rate the item as particularly important. Any item that had a mean value equal or above 3.5 across all panelists was considered important, values equal or above 4.5 essential.

Results

The following describes results regarding the concept of high-need patients, domains of needs, and intervention characteristics.

High need concept and terminology

The content of the key informant interviews is documented in detail (Appendix Table 1). All key informants indicated that there is no universally accepted definition of high-need patients, that research and policy often focus on specific patient populations (e.g., potentially preventable high use of healthcare), and that high need can mean unique circumstances for individual patients.

The evidence table (Appendix Table 3) summarizes the 46 identified research syntheses presented to the panelists [17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62]. The publications spanned over a decade (the earliest identified review searched the literature in 2006), but a third of the summaries were published in 2018 and 2019. Reviews described the populations most often as patients with multi-morbidity and complex patients. Others addressed research in high-need, high-cost populations; patients with multiple health and social care needs; high-need and high-risk patients; chronic diseases and complex healthcare needs; older participants with several chronic conditions; and patients with mental and physical multimorbidity. Reviews also operationalized the specific population of high-need patients differently, such as multimorbidity (e.g., defined as two or medical diagnoses or multiple chronic conditions), and noted that definitions and measurement vary across studies included in a review [43].

Seven reviews provided construct validity for the concept of high need by describing predictors useful to identify these patients [38, 41, 42, 54, 57,58,59]. Predictors included prior healthcare utilization, older age, number of diseases, and combination of chronic disease and biopsychosocial factors. In addition, we identified nine primary studies that provided construct, content, or predictive validity for individual predictors or the construct high utilizers [3, 5, 63,64,65,66,67,68,69]. Notably, a Medicare Expenditure Panel Survey study demonstrated that a definition of high needs as three or more chronic diseases and a functional limitation in ability to care for themselves or perform routine daily tasks was associated with more emergency department visits, visits with doctor or home health care, higher spending, and persistent high-cost [64]. A study using a medical complexity definition (2 + complex conditions, 6 + chronic conditions, any acute or post-acute health services utilization, indicators of frailty, and any functional impairment in activities of daily living or mobility) reported higher mortality and hospitalization rates compared to other beneficiaries [63]. Other studies documented distinct patient subgroups in latent class analyses with or without machine learning support [5, 65, 66, 69]. The evidence table (Appendix Table 4) documents the results in detail. Across all identified reviews, a recurring theme was the lack of consensus on defining and measuring high need. Issues not fully recognized in existing research sparked discussions regarding the lack of consensus on how high-need should be defined across key informants. Considerations for policy included assessing and addressing the patient’s context (e.g., food insecurity) and looking outside the healthcare system (e.g., community care providing additional resources for patients).

In preparation of the stakeholder panel meeting, panelists responded to the suggested terminology to establish a shared understanding for the population of interest. Panelists identified the term ‘high utilizers (referring to services)’ as particularly useful to describe high-need patients (mean 4.45, SD 0.66, mode 5, 55% endorsed the term as essential). All ratings are shown in Appendix Table 7 and Appendix Fig. 2 displays the number of times each term was rated as essential. Finally, when presented with 11 statements addressing the uniqueness of high-need patients, stakeholders agreed the most with the statement “Patients’ needs are unique but there are some areas of commonality for high need patients,” but none of the statements were rated as essential by all stakeholders (Appendix Table 8).

Need domains relevant to the care of high-need patients

The project differentiated needs of patients, their healthcare professionals, and those of healthcare organizations caring for high-need patients.

Asking key informants about the needs of complex patients led to rich discussion about how generalizable these needs were across patients. Key informants identified social determinants that complicate care for high-need patients (e.g., homelessness) and noted a tendency to medicalize social or basic human needs (e.g., need for food and shelter) in healthcare. Furthermore, informants expressed a need for culturally competent tools (e.g., for patient engagement and health literacy) in different languages and noted that existing tools supporting clinical practice are often not specific to complex patients. The quotes in Appendix Table 2 provide insights into concrete needs expressed by personnel caring for high-need patients. The quotes highlight patient needs and the struggles that high-need patients experience in navigating a complex care environment, in addition to medical complexity.

Of the identified research syntheses identified in preparation of the stakeholder panel, only seven addressed the needs of patients [24, 29, 31, 39, 47, 49, 60]. Themes identified across studies were dealing with the physical and emotional impact of multi-morbidity, the importance of self-care, time needed to arrange medical appointments, and information needs regarding side effects and interaction of medications or conflicting advice across different conditions. Three syntheses addressed healthcare professional needs, mainly focusing on care coordination issues, such as shared care across specialists and primary care physicians, and fragmentation of care [32, 50, 60].

Our searches also identified 19 primary research publications assessing the needs of complex patients, their healthcare professionals, or both (Appendix Table 5) [70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88]. Half of these addressed patients and or healthcare professionals in the US; other countries included Canada, Sweden, Australia, and UK, and three studies were conducted across multiple countries. Most studies conducted interviews and asked about healthcare needs of high-need patients and their healthcare professionals and some studies were large-scale surveys. Of these, 12 publications referred to chronic or longstanding conditions, [70, 72, 73, 75, 76, 78, 80,81,82,83,84, 86] eight to multiple medical conditions, [70, 74,75,76, 82, 83, 86, 87] five to healthcare use, [72, 77, 79, 80, 84] four to frailty or functional limitations, [70, 82, 83, 86] and three to costs. [72, 85, 88] The evidence table in the appendix documents the elicited patient needs documented in the literature. Across 14 identified studies, responses ranged from concrete needs such as the need for simpler prescription refills, to a general need for better coordinated care [70, 72, 73, 75,76,77, 79, 80, 82,83,84,85,86, 88]. Seven studies reported on healthcare professional needs, such as the need for more time with patients and communication with other healthcare professionals for care coordination [71, 74, 75, 78, 80, 81, 87].

Needs of patients, healthcare professionals, and organizations, informed by the literature findings, were a major focus of the stakeholder panel. Panelists had rated needs identified in the literature individually in preparation of the panel meeting. The stakeholder panel discussions focused on disagreements identified in the pre-panel survey and newly nominated need domains suggested by individual panelists in the pre-panel survey. Rating results for all items are shown in Appendix Table 9. All domains confirmed as important or essential in the post-panel survey are shown in Fig. 1 as bolded.

Panelists identified 11 distinct aspects relevant to patient needs. The highest rated domain was social circumstances, such as housing instability. Other domains identified as essential were the interpersonal domain (e.g., whether the patient is supported by family members), medical complexity, organizational navigation (e.g., knowledge where to get help), cognitive (e.g., understanding the care sequence steps), functional (e.g., missing important appointments), behavioral (e.g., following recommendations) health, care access, and trust in healthcare professionals and the care organization. Additional important areas included psychiatric complexity and psychosocial aspects (e.g., successful interactions with healthcare professionals and direct environment).

With respect to needs related to healthcare professionals, panelists identified communication (e.g., healthcare professionals engaging other healthcare professionals to coordinate care), an interdisciplinary team to provide care, time needed for high-need patients, and professional skills (e.g., being able to address the care complexity) as essential. In addition, professional knowledge about care and the system (e.g., being familiar with resources and personnel patients should be connected with) was rated as important across all stakeholders.

The highest rated domains for organizations caring for high-need patients included staffing arrangements (e.g., care in multidisciplinary teams), collaboration within and outside the healthcare system, and the care approach and culture in the organization (e.g., whether the organization takes a holistic care approach). Other domains judged as important were technology (e.g., information technology support), finances (supporting care for high-need patients), investment in the workforce such as training in complex patient care, existing expertise in the organization (e.g., social worker is part of the team or easily accessible to the care team), and measurement capabilities (e.g., being able to identify and flag high-need patients).

Interventions for high-need patients

Results regarding interventions focus on intervention types and unintended consequences.

Taxonomy of interventions

Key informants disagreed on whether interventions for high-need patients are disease-specific or implementable across conditions. Key informants suggested that in practice, interventions may need to be tailored to individuals to address the specific and unique needs of individual patients. Furthermore, informants indicated that coordination between emergency and other departments and between social and healthcare organizations is critical to address patients’ needs due to a strong interdependence (e.g., a local housing initiative may empty the emergency room with emergency departments functioning as cities’ shelter systems or modern almshouses [89]).

Half (23/46) of the research syntheses identified in preparation of the panel summarized interventions for high-need patients. While some described specific interventions (mobile health apps, self-management, case management, care coordination, shared decision making, health education), others targeted broader approaches, such as the chronic care model or interdisciplinary care approaches [17,18,19,20,21,22,23, 27, 29, 30, 33, 36, 37, 43, 46, 48, 49, 51,52,53, 55, 56, 60] We also identified publications providing a taxonomy of interventions aimed at high-need patients, i.e., proposing systems to differentiate intervention types (see Appendix Table 6) [18, 20, 23, 27, 33, 36, 46, 51, 53, 88, 90,91,92,93] Taxonomies were often based on a literature review, but publications varied in scope and categorization approaches (e.g., focusing on distinct aspects such as patient goals, characteristics of successful programs, or intervention components across multi-faceted interventions). A comprehensive review identified 15 interventions, including interdisciplinary primary care, models that supplement primary care, transitional care approaches, models of acute care in patients’ homes, nurse-physician teams for residents of nursing homes, and models of comprehensive care in hospitals [20].

When presented with interventions identified in the environmental scan, stakeholders endorsed 15 suggested categories as either essential or as important for a taxonomy, as depicted in the tree diagram in Fig. 2. The 15 intervention categories include interventions directed primarily at the patient, with interventions addressing social support of patients, practical support necessary to receive care (e.g., transportation), interventions potentially reducing the need for care (e.g., food bank), and care navigation rated as essential. Intervention at the healthcare professional level classified as important are also shown in Fig. 2; none was endorsed as essential across panelists. Organizational interventions rated as essential were processes for identification and tracking of high-need patients, care coordination strategies, changing procedures to accommodate for high-need patients, and structural changes such as implementing protocols for frequent contact scheduling and monitoring.

Fig. 2
figure 2

Intervention Categories

Note: Size of the bar is proportionate to the number of times chosen as essential, a black frame indicates a mean rating of essential

Full size image

Unintended consequences of interventions

As part of the environmental scan, the key informants highlighted potential unintended consequences for patients (e.g., the need to “game the system”) and healthcare professionals (e.g., coordinating care is an additional task for healthcare professionals that are already stretched to their limits) that they had encountered in their own work with high-need patients.

Identifying unintended consequences of organizational interventions is critical to fully understanding the impacts of interventions, but none of the research syntheses identified in the literature review described unintended or negative effects of the evaluated interventions.

The stakeholder panel resulted in rich discussions about unintended consequences of interventions implemented in healthcare organizations. The pre-panel survey had elicited several potential consequences of interventions for patients, healthcare professionals, and healthcare organizations proposed by individual panelists that were discussed in detail at the panel meeting. Table 1 shows the final ratings from the post-panel survey, ordered by the central tendency magnitude.

Table 1 Potential unintended consequences of interventions for high-need patients
Full size table

While none of the identified possible unintended consequences were seen as an essential aspect of care, panelists identified 12 potential consequences of interventions as important (see top half of Table 1). Of these, several would affect patients directly, such as high costs incurred for patients (e.g., through co-payment or needed resources) and fragmented care due to a new caregiver or program. Others would primarily impact healthcare professionals (e.g., increased workload, more care coordination demands) and the healthcare system (e.g., interventions may be unsustainable).

Discussion

This project comprised of an environmental scan and stakeholder panel. The environmental scan explored the concept of high need further with key informants and provided an overview of the published research base on high-need patients. The stakeholder panel used modified Delphi methodology to determine domains of need in this population and healthcare professionals and organizations caring for them and to determine characteristics of interventions for high-need patients, their healthcare professionals, and healthcare organizations caring for high-need patients.

Stakeholders reviewed conceptual frameworks and terminology of high need and established that individual patients’ needs are unique but all high-need patients share some common features. As documented in multiple research publications, the lack of consensus on terminology hinders research and policy [2, 5, 43, 94,95,96]. Panelists agreed that healthcare utilization is a key characteristic of high-need patients; however, focus on utilization and spending is problematic as intense use is often temporary [97]. In recent years, researchers have started to collate existing measures to identify high-need patients, [41, 44] to assess multi-morbidity, [25, 26, 34, 61] and to document treatment preferences and results. [40, 45, 98] In addition, recommendations for treatment of multimorbidity, [50] a collection of conceptual models of patient complexity, [62] and research agendas to support patients with multiple conditions [95, 99] have been published recently, which may advance research and policy for high-need patients more broadly.

Panelists agreed on domains describing patient, healthcare professionals, and care organization needs. The findings recognized the complexity of the identified needs and established that eleven different domains should be differentiated for patients (e.g., needs routed in social circumstances such as homelessness versus needs routed in the medical complexity of diagnoses, such as possible drug interactions resulting from polymedication). Similarly, there are five different healthcare professional needs that should be addressed through interventions and resource support (e.g., communication needs and skills versus having access to an interdisciplinary team). Organizational need domains are also diverse and offer multiple entry points for organizational changes (e.g., the need to make staffing arrangements including adjusted panel sizes versus the need for collaboration within and outside the healthcare system) as indicated in the eight identified domains. The diversity in needs highlights the necessity to explore areas beyond the simple operationalization of counting the number of chronic conditions to describe high-need patients or defining patient complexity as morbidity alone [62, 96]. It highlights the multi-level and multi-component approach that is needed to care for high-need patients.

Our taxonomy of interventions was informed by published intervention categorizations as well as panel discussions. The taxonomy includes 15 types of interventions and reflects the diversity of approaches to support high-need patients. Not all interventions are directed at patients (e.g., providing practical support promoting access to care), as some approaches may also target healthcare professionals (e.g., changing clinician behavior) or implement organizational changes (e.g., introducing mechanisms to identify high-need patients). Our literature review identified over 20 published evidence syntheses summarizing the effects of interventions for high-need patients–all providing information on different interventions, components, or approaches–highlighting the diversity of this field. In addition to and independently from patients, healthcare professionals also benefit from support, and structural interventions can benefit patients, professionals, and organizations [100,101,102,103,104,105,106].

Our project also addressed potential unintended consequences of interventions for high-need patients. The panelists agreed that the top unintended consequences to consider include costs incurred for patients, unsustainable interventions, screening for needs without resources to respond appropriately, increased time and effort for healthcare professionals, and straining organizational capacity. Some of the unintended consequences may be mitigated with careful planning or may be avoided altogether, for example, through effective care coordination. However, our study shows that interventions should be addressed from a systems approach that measures effects from different perspectives, including patients, healthcare professionals, and organizations. In addition, many interventions for high-need patients are complex, with multi-components, which in itself poses evaluation challenges, reinforcing the need for careful measurement of effects [27].

Our study has several strengths and weaknesses. We identified a large number of relevant scientific publications and explored the concept of high need with key informants to thoroughly prepare for the stakeholder panel. We followed established methodology and incorporated diverse perspectives from relevant stakeholders. However, it should be noted that we used rapid review methodology rather than conducting full systematic reviews for the topics of interest, and thus may have missed relevant publications. Despite a framework-guided approach, the panelists are selected representatives of stakeholder groups and do not necessarily cover the universe of opinions. The limited number of panelists enabled meaningful group discussions and consensus finding, consistent with the RAND/UCLA Appropriateness Method and allowed elicitation of diverse opinions while also allowing consensus to emerge [14, 16]. It should be noted that the panel did not include family or other non-professional care givers; future research should pay particular attention to this important group. In addition, multiple panelists had a VA Health System affiliation and future research should determine whether and which needs do not generalize to other healthcare systems that care for high-need patients.

We demonstrated, in a multi-faceted, evidence-based and expert-informed research project, that care for high-need patients requires a thoughtful approach. Differentiating need domains provides multiple entry points for interventions directed at patients, healthcare professionals, and organizations. Intervention evaluations should consider the intended and unintended effects downstream effects on all stakeholders; most importantly high-need patients, their healthcare professionals, and the healthcare organization caring for this population.

Data Availability

All data generated or analyzed during this study are included in this manuscript and its supplementary information files in de-identified format.

References

  1. Khullar D, Kaushal R. Precision health for high-need, high-cost patients. Am J Manag Care. 2018;24(9):396–8.

    PubMed  Google Scholar 

  2. Valderas JM, Starfield B, Sibbald B, Salisbury C, Roland M. Defining comorbidity: implications for understanding health and health services. Ann Fam Med. 2009;7(4):357–63.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Schickedanz A, Sharp A, Hu YR, Shah NR, Adams JL, Francis D, Rogers A. Impact of Social Needs Navigation on utilization among high utilizers in a large Integrated Health System: a quasi-experimental study. J Gen Intern Med. 2019;34(11):2382–9.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Hochman M, Asch SM. Disruptive models in primary care: caring for High-Needs, high-cost populations. J Gen Intern Med. 2017;32(4):392–7.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Buja A, Claus M, Perin L, Rivera M, Corti MC, Avossa F, Schievano E, Rigon S, Toffanin R, Baldo V, et al. Multimorbidity patterns in high-need, high-cost elderly patients. PLoS ONE. 2018;13(12):e0208875.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Turner-Stokes L, Bavikatte G, Williams H, Bill A, Sephton K. Cost-efficiency of specialist hyperacute in-patient rehabilitation services for medically unstable patients with complex rehabilitation needs: a prospective cohort analysis. BMJ Open. 2016;6(9):e012112.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Agency for Healthcare Research and Quality. Management of High-Need, high-cost patients: a Realist and systematic Review Research Protocol. Volume 4. In. Rockville, MD: Agency for Healthcare Research and Quality Effective Health Care Program; 2019.

    Google Scholar 

  8. Chang ET, Raja PV, Stockdale SE, Katz ML, Zulman DM, Eng JA, Hedrick KH, Jackson JL, Pathak N, Watts B, et al. What are the key elements for implementing intensive primary care? A multisite Veterans Health Administration case study. Healthc (Amst). 2018;6(4):231–7.

    Article  PubMed  Google Scholar 

  9. Concannon TW, Fuster M, Saunders T, Patel K, Wong JB, Leslie LK, Lau J. A systematic review of stakeholder engagement in comparative effectiveness and patient-centered outcomes research. J Gen Intern Med. 2014;29(12):1692–701.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Jones J, Hunter D. Consensus methods for medical and health services research. BMJ. 1995;311(7001):376–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Hempel S, Shekelle PG, Liu JL, Sherwood Danz M, Foy R, Lim YW, Motala A, Rubenstein LV. Development of the Quality Improvement Minimum Quality Criteria Set (QI-MQCS): a tool for critical appraisal of quality improvement intervention publications. BMJ Qual Saf. 2015;24(12):796–804.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Shekelle PG, Pronovost PJ, Wachter RM, Taylor SL, Dy SM, Foy R, Hempel S, McDonald KM, Ovretveit J, Rubenstein LV, et al. Advancing the science of patient safety. Ann Intern Med. 2011;154(10):693–6.

    Article  PubMed  Google Scholar 

  13. Rubenstein L, Khodyakov D, Hempel S, Danz M, Salem-Schatz S, Foy R, O’Neill S, Dalal S, Shekelle P. How can we recognize continuous quality improvement? Int J Qual Health Care. 2014;26(1):6–15.

    Article  PubMed  Google Scholar 

  14. Hempel S, Miake-Lye I, Brega AG, Buckhold F 3rd, Hassell S, Nowalk MP, Rubenstein L, Schreiber K, Spector WD, Kilbourne AM, et al. Quality improvement toolkits: recommendations for development. Am J Med Qual. 2019;34(6):538–44.

  15. Rubenstein L, Hempel S, Danz M, Rose D, Stockdale S, Curtis I, Kirsh S. Eight Priorities for Improving Primary Care Access Management in Healthcare organizations: results of a modified Delphi Stakeholder Panel. J Gen Intern Med. 2020;35(2):523–30.

    Article  PubMed  Google Scholar 

  16. Fitch K, Bernstein SJ, Aguilar MD, Burnand B, LaCalle JR, Lazaro P, van het Loo M, McDonnell J, Vader J, Kahan JP. The RAND/UCLA Appropriateness Method user’s Manual. Santa Monica, CA: RAND Corporation; 2001.

    Google Scholar 

  17. Baker JM, Grant RW, Gopalan A. A systematic review of care management interventions targeting multimorbidity and high care utilization. BMC Health Serv Res. 2018;18(1):65.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Bleich SN, Sherrod C, Chiang A, Boyd C, Wolff J, DuGoff E, Salzberg C, Anderson K, Leff B, Anderson G. Systematic review of Programs Treating High-need and high-cost people with multiple chronic Diseases or disabilities in the United States, 2008–2014. Prev Chronic Dis. 2015;12:E197.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Boehmer KR, Abu Dabrh AM, Gionfriddo MR, Erwin P, Montori VM. Does the chronic care model meet the emerging needs of people living with multimorbidity? A systematic review and thematic synthesis. PLoS ONE. 2018;13(2):e0190852.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Boult C, Green AF, Boult LB, Pacala JT, Snyder C, Leff B. Successful models of comprehensive care for older adults with chronic conditions: evidence for the Institute of Medicine’s retooling for an aging America report. J Am Geriatr Soc. 2009;57(12):2328–37.

    Article  PubMed  Google Scholar 

  21. Bunn F, Goodman C, Russell B, Wilson P, Manthorpe J, Rait G, Hodkinson I, Durand MA. Supporting shared decision making for older people with multiple health and social care needs: a realist synthesis. BMC Geriatr. 2018;18(1):165.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Butterworth JE, Hays R, McDonagh ST, Richards SH, Bower P, Campbell J. Interventions for involving older patients with multi-morbidity in decision-making during primary care consultations. Cochrane Database Syst Rev 2019, 2019(10).

  23. Coller RJ, Nelson BB, Sklansky DJ, Saenz AA, Klitzner TS, Lerner CF, Chung PJ. Preventing hospitalizations in children with medical complexity: a systematic review. Pediatrics. 2014;134(6):e1628–1647.

    Article  PubMed  Google Scholar 

  24. Coventry PA, Small N, Panagioti M, Adeyemi I, Bee P. Living with complexity; marshalling resources: a systematic review and qualitative meta-synthesis of lived experience of mental and physical multimorbidity. BMC Fam Pract. 2015;16:171.

    Article  PubMed  PubMed Central  Google Scholar 

  25. De Groot V, Beckerman H, Lankhorst GJ, Bouter LM. How to measure comorbidity: a critical review of available methods. J Clin Epidemiol. 2003;56:221–9.

    Article  PubMed  Google Scholar 

  26. Diederichs C, Berger K, Bartels DB. The measurement of multiple chronic Diseases-A systematic review on existing Multimorbidity indices. Journals of Gerontology Series a-Biological Sciences and Medical Sciences. 2011;66(3):301–11.

    Article  PubMed  Google Scholar 

  27. Edwards ST, Peterson K, Chan B, Anderson J, Helfand M. Effectiveness of Intensive Primary Care interventions: a systematic review. J Gen Intern Med. 2017;32(12):1377–86.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Fraccaro P, Arguello Casteleiro M, Ainsworth J, Buchan I. Adoption of clinical decision support in multimorbidity: a systematic review. JMIR Med Inform. 2015;3(1):e4.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Gobeil-Lavoie AP, Chouinard MC, Danish A, Hudon C. Characteristics of self-management among patients with complex health needs: a thematic analysis review. BMJ Open. 2019;9(5):e028344.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Haroun D, Smits F, van Etten-Jamaludin F, Schene A, van Weert H, Ter Riet G. The effects of interventions on quality of life, morbidity and consultation frequency in frequent attenders in primary care: a systematic review. Eur J Gen Pract. 2016;22(2):71–82.

    Article  PubMed  Google Scholar 

  31. Hohmann NS, McDaniel CC, Mason SW, Cheung WY, Williams MS, Salvador C, Graves EK, Camp CN, Chou C. Patient perspectives on primary care and oncology care coordination in the context of multiple chronic conditions: a systematic review. Res Social Adm Pharm 2019.

  32. Hohmann NS, McDaniel CC, Mason SW, Cheung WY, Williams MS, Salvador C, Graves EK, Camp CN, Chou CH. Healthcare providers’ perspectives on care coordination for adults with cancer and multiple chronic conditions: a systematic review. J Pharm Health Serv Res.

  33. Hudon C, Chouinard MC, Pluye P, El Sherif R, Bush PL, Rihoux B, Poitras ME, Lambert M, Zomahoun HTV, Legare F. Characteristics of Case Management in Primary Care Associated with positive outcomes for frequent users of Health Care: a systematic review. Ann Fam Med. 2019;17(5):448–58.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Huntley AL, Johnson R, Purdy S, Valderas JM, Salisbury C. Measures of multimorbidity and morbidity burden for use in primary care and community settings: a systematic review and guide. Ann Fam Med. 2012;10(2):134–41.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Johnston MC, Crilly M, Black C, Prescott GJ, Mercer SW. Defining and measuring multimorbidity: a systematic review of systematic reviews. Eur J Public Health. 2019;29(1):182–9.

    Article  PubMed  Google Scholar 

  36. Kastner M, Cardoso R, Lai Y, Treister V, Hamid JS, Hayden L, Wong G, Ivers NM, Liu B, Marr S, et al. Effectiveness of interventions for managing multiple high-burden chronic Diseases in older adults: a systematic review and meta-analysis. CMAJ. 2018;190(34):E1004–e1012.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Latour CH, van der Windt DA, de Jonge P, Riphagen II, de Vos R, Huyse FJ, Stalman WA. Nurse-led case management for ambulatory complex patients in general health care: a systematic review. J Psychosom Res. 2007;62(3):385–95.

    Article  PubMed  Google Scholar 

  38. Le Reste JY, Nabbe P, Manceau B, Lygidakis C, Doerr C, Lingner H, Czachowski S, Munoz M, Argyriadou S, Claveria A, et al. The European General Practice Research Network presents a comprehensive definition of multimorbidity in family medicine and long term care, following a systematic review of relevant literature. J Am Med Dir Assoc. 2013;14(5):319–25.

    Article  PubMed  Google Scholar 

  39. Liddy C, Blazkho V, Mill K. Challenges of self-management when living with multiple chronic conditions systematic review of the qualitative literature. Can Fam Physician. 2014;60(12):1123–33.

    PubMed  PubMed Central  Google Scholar 

  40. Mangin D, Stephen G, Bismah V, Risdon C. Making patient values visible in healthcare: a systematic review of tools to assess patient treatment priorities and preferences in the context of multimorbidity. BMJ Open. 2016;6(6):e010903.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Marcoux V, Chouinard MC, Diadiou F, Dufour I, Hudon C. Screening tools to identify patients with complex health needs at risk of high use of health care services: a scoping review. PLoS ONE. 2017;12(11):e0188663.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, Meinow B, Fratiglioni L. Aging with multimorbidity: a systematic review of the literature. Ageing Res Rev. 2011;10(4):430–9.

    Article  PubMed  Google Scholar 

  43. Moe J, Kirkland SW, Rawe E, Ospina MB, Vandermeer B, Campbell S, Rowe BH. Effectiveness of interventions to decrease Emergency Department visits by adult frequent users: a systematic review. Acad Emerg Med. 2017;24(1):40–52.

    Article  PubMed  Google Scholar 

  44. Ng SK, Tawiah R, Sawyer M, Scuffham P. Patterns of multimorbid health conditions: a systematic review of analytical methods and comparison analysis. Int J Epidemiol. 2018;47(5):1687–704.

    Article  PubMed  Google Scholar 

  45. Pillay M, Dennis S, Harris MF. Quality of care measures in multimorbidity. Aust Fam Physician. 2014;43(3):132–6.

    PubMed  Google Scholar 

  46. Poitras ME, Maltais ME, Bestard-Denomme L, Stewart M, Fortin M. What are the effective elements in patient-centered and multimorbidity care? A scoping review. BMC Health Serv Res. 2018;18(1):446.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Rosbach M, Andersen JS. Patient-experienced burden of treatment in patients with multimorbidity - A systematic review of qualitative data. PLoS ONE 2017, 12(6).

  48. Sasseville M, Chouinard M-C, Fortin M. Patient-reported outcomes in multimorbidity intervention research: a scoping review. Int J Nurs Stud. 2018;77:145–53.

    Article  PubMed  Google Scholar 

  49. Singh K, Drouin K, Newmark LP, Filkins M, Silvers E, Bain PA, Zulman DM, Lee JH, Rozenblum R, Pabo E, et al. Patient-facing mobile apps to treat High-Need, high-cost populations: a scoping review. JMIR Mhealth Uhealth. 2016;4(4):e136.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Sinnott C, Mercer SW, Payne RA, Duerden M, Bradley CP, Byrne M. Improving medication management in multimorbidity: development of the MultimorbiditY COllaborative medication review and DEcision making (MY COMRADE) intervention using the Behaviour Change Wheel. Implement Sci. 2015;10:132.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Smith SM, Soubhi H, Fortin M, Hudon C, O’Dowd T. Managing patients with multimorbidity: systematic review of interventions in primary care and community settings. BMJ. 2012;345:e5205.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Smits FT, Wittkampf KA, Schene AH, Bindels PJ, Van Weert HC. Interventions on frequent attenders in primary care. A systematic literature review. Scand J Prim Health Care. 2008;26(2):111–6.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Soril LJ, Leggett LE, Lorenzetti DL, Noseworthy TW, Clement FM. Reducing frequent visits to the emergency department: a systematic review of interventions. PLoS ONE. 2015;10(4):e0123660.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Soril LJ, Leggett LE, Lorenzetti DL, Noseworthy TW, Clement FM. Characteristics of frequent users of the emergency department in the general adult population: a systematic review of international healthcare systems. Health Policy. 2016;120(5):452–61.

    Article  PubMed  Google Scholar 

  55. Stokes J, Panagioti M, Alam R, Checkland K, Cheraghi-Sohi S, Bower P. Effectiveness of Case Management for ‘At Risk’ Patients in Primary Care: A Systematic Review and Meta-Analysis. PLoS ONE 2015, 10(7).

  56. Vermunt N, Harmsen M, Westert GP, Olde Rikkert MGM, Faber MJ. Collaborative goal setting with elderly patients with chronic Disease or multimorbidity: a systematic review. BMC Geriatr. 2017;17(1):167.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Violan C, Foguet-Boreu Q, Flores-Mateo G, Salisbury C, Blom J, Freitag M, Glynn L, Muth C, Valderas JM. Prevalence, determinants and patterns of multimorbidity in primary care: a systematic review of observational studies. PLoS ONE. 2014;9(7):e102149.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Welzel FD, Stein J, Hajek A, Konig HH, Riedel-Heller SG. Frequent attenders in late life in primary care: a systematic review of European studies. BMC Fam Pract. 2017;18(1):104.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Willadsen TG, Bebe A, Koster-Rasmussen R, Jarbol DE, Guassora AD, Waldorff FB, Reventlow S, Olivarius Nde F. The role of Diseases, risk factors and symptoms in the definition of multimorbidity - a systematic review. Scand J Prim Health Care. 2016;34(2):112–21.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Yardley S, Cottrell E, Rees E, Protheroe J. Modelling successful primary care for multimorbidity: a realist synthesis of successes and failures in concurrent learning and healthcare delivery. BMC Fam Pract. 2015;16:23.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Yurkovich M, Avina-Zubieta JA, Thomas J, Gorenchtein M, Lacaille D. A systematic review identifies valid comorbidity indices derived from administrative health data. J Clin Epidemiol. 2015;68(1):3–14.

    Article  PubMed  Google Scholar 

  62. Zullig LL, Whitson HE, Hastings SN, Beadles C, Kravchenko J, Akushevich I, Maciejewski ML. A systematic review of conceptual frameworks of Medical Complexity and New Model Development. J Gen Intern Med. 2016;31(3):329–37.

    Article  PubMed  Google Scholar 

  63. Belanger E, Silver B, Meyers DJ, Rahman M, Kumar A, Kosar C, Mor V. A retrospective study of Administrative Data to identify high-need Medicare beneficiaries at risk of dying and being hospitalized. J Gen Intern Med. 2019;34(3):405–11.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Hayes SL, Salzberg CA, McCarthy D, Radley DC, Abrams MK, Shah T, Anderson GF. High-Need, high-cost patients: who are they and how do they use Health Care? A Population-based comparison of demographics, Health Care Use, and expenditures. Issue Brief (Commonw Fund). 2016;26:1–14.

    PubMed  Google Scholar 

  65. Matzer F, Wisiak UV, Graninger M, Sollner W, Stilling HP, Glawischnig-Goschnik M, Lueger A, Fazekas C. Biopsychosocial health care needs at the emergency room: challenge of complexity. PLoS ONE. 2012;7(8):e41775.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Nuti SV, Doupe P, Villanueva B, Scarpa J, Bruzelius E, Baum A. Characterizing subgroups of High-Need, high-cost patients based on their clinical conditions: a machine learning-based analysis of Medicaid Claims Data. J Gen Intern Med. 2019;34(8):1406–8.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Price-Haywood EG, Petersen H, Burton J, Harden-Barrios J, Adubato M, Roberts M, Markward N. Outpatient complex Case Management: Health System-tailored risk stratification taxonomy to identify High-Cost, high-need patients. J Gen Intern Med. 2018;33(11):1921–7.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Sarnak DO, Ryan J. How high-need patients experiences the Health Care System in Nine Countries. Issue Brief (Commonw Fund). 2016;1:1–14.

    PubMed  Google Scholar 

  69. Smeets RGM, Elissen AMJ, Kroese M, Hameleers N, Ruwaard D. Identifying subgroups of high-need, high-cost, chronically ill patients in primary care: a latent class analysis. PLoS ONE. 2020;15(1):e0228103.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Bhattacharyya O, Mossman K, Gustafsson L, Schneider EC. Using human-centered design to build a Digital Health Advisor for patients with Complex needs: Persona and Prototype Development. J Med Internet Res. 2019;21(5):e10318.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Bridges J, Hughes J, Farrington N, Richardson A. Cancer treatment decision-making processes for older patients with complex needs: a qualitative study. BMJ Open. 2015;5(12):e009674.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Das LT, Abramson EL, Kaushal R. High-Need, High-Cost Patients Offer Solutions for Improving Their Care and Reducing Costs. NEJM Catal 2019, 2019.

  73. Goodridge D, Bandara T, Marciniuk D, Hutchinson S, Crossman L, Kachur B, Higgins D, Bennett A. Promoting chronic Disease management in persons with complex social needs: a qualitative descriptive study. Chron Respir Dis. 2019;16:1479973119832025.

    Article  PubMed  PubMed Central  Google Scholar 

  74. Kuluski K, Ho JW, Hans PK, Nelson M. Community Care for people with Complex Care needs: bridging the gap between Health and Social Care. Int J Integr Care. 2017;17(4):2.

    Article  PubMed  PubMed Central  Google Scholar 

  75. Larsson LG, Back-Pettersson S, Kylen S, Marklund B, Carlstrom E. Primary care managers’ perceptions of their capability in providing care planning to patients with complex needs. Health Policy. 2017;121(1):58–65.

    Article  PubMed  Google Scholar 

  76. Maneze D, Dennis S, Chen HY, Taggart J, Vagholkar S, Bunker J, Liaw ST. Multidisciplinary care: experience of patients with complex needs. Aust J Prim Health. 2014;20(1):20–6.

    Article  PubMed  Google Scholar 

  77. Mautner DB, Pang H, Brenner JC, Shea JA, Gross KS, Frasso R, Cannuscio CC. Generating hypotheses about care needs of high utilizers: lessons from patient interviews. Popul Health Manag. 2013;16(Suppl 1):26–33.

    Article  Google Scholar 

  78. Osborn R, Moulds D, Schneider EC, Doty MM, Squires D, Sarnak DO. Primary Care Physicians in Ten Countries Report challenges Caring for patients with Complex Health needs. Health Aff (Millwood). 2015;34(12):2104–12.

    Article  PubMed  Google Scholar 

  79. Parkerson GR Jr., Bell HS, Albright JB, Krause K. A telephone needs assessment for potential high utilizers. Fam Med. 2001;33(6):466–72.

    PubMed  Google Scholar 

  80. Poitras ME, Hudon C, Godbout I, Bujold M, Pluye P, Vaillancourt VT, Debarges B, Poirier A, Prevost K, Spence C et al. Decisional needs assessment of patients with complex care needs in primary care. J Eval Clin Pract 2019.

  81. Pratt LR. Long-term conditions 5: meeting the needs of highly complex patients. Br J Community Nurs. 2006;11(6):234–5.

    Article  PubMed  Google Scholar 

  82. Ryan J, Abrams MK, Doty MM, Shah T, Schneider EC. How high-need patients Experience Health Care in the United States. Findings from the 2016 Commonwealth Fund Survey of High-need patients. Issue Brief (Commonw Fund). 2016;43:1–20.

    PubMed  Google Scholar 

  83. Salzberg CA, Hayes SL, McCarthy D, Radley DC, Abrams MK, Shah T, Anderson GF. Health System performance for the high-need patient: a look at Access to Care and Patient Care experiences. Issue Brief (Commonw Fund). 2016;27:1–12.

    PubMed  Google Scholar 

  84. Schoen C, Osborn R, Squires D, Doty M, Pierson R, Applebaum S. New 2011 survey of patients with complex care needs in eleven countries finds that care is often poorly coordinated. Health Aff (Millwood). 2011;30(12):2437–48.

    Article  PubMed  Google Scholar 

  85. Soto Mas F, Iriart C, Pedroncelli R, Binder DS, Qualls CR, Price B. Impact of Health Care and Socioeconomic needs on Health Care utilization and Disease Management: the University of New Mexico Hospital Care one program. Popul Health Manag. 2019;22(2):113–9.

    Article  PubMed  PubMed Central  Google Scholar 

  86. Steele Gray C, Miller D, Kuluski K, Cott C. Tying eHealth Tools to Patient needs: exploring the Use of eHealth for Community-Dwelling patients with Complex Chronic Disease and Disability. JMIR Res Protoc. 2014;3(4):e67.

    Article  PubMed  PubMed Central  Google Scholar 

  87. Whitebird RR, Solberg LI, Crain AL, Rossom RC, Beck A, Neely C, Dreskin M, Coleman KJ. Clinician burnout and satisfaction with resources in caring for complex patients. Gen Hosp Psychiatry. 2017;44:91–5.

    Article  PubMed  Google Scholar 

  88. Zulman DM, Ezeji-Okoye SC, Shaw JG, Hummel DL, Holloway KS, Smither SF, Breland JY, Chardos JF, Kirsh S, Kahn JS, et al. Partnered research in healthcare delivery redesign for high-need, high-cost patients: development and feasibility of an Intensive Management patient-aligned Care Team (ImPACT). J Gen Intern Med. 2014;29(Suppl 4):861–9.

    Article  PubMed  PubMed Central  Google Scholar 

  89. Malone RE. Whither the almshouse? Overutilization and the role of the emergency department. J Health Polit Policy Law. 1998;23(5):795–832.

    Article  CAS  PubMed  Google Scholar 

  90. Anderson GF, Ballreich J, Bleich S, Boyd C, DuGoff E, Leff B, Salzburg C, Wolff J. Attributes common to programs that successfully treat high-need, high-cost individuals. Am J Manag Care. 2015;21(11):e597–600.

    PubMed  Google Scholar 

  91. Hong CS, Siegel AL, Ferris TG. Caring for high-need, high-cost patients: what makes for a successful care management program? Issue Brief (Commonw Fund). 2014;19:1–19.

    PubMed  Google Scholar 

  92. Long P, Abrams MK, Milstein A, et al. Effective care for high-need patients: opportunities for improving outcomes, Value, and Health. Washington, DC: National Academy of Medicine; 2017.

    Book  Google Scholar 

  93. McCarthy D, Ryan J, Klein S. Models of Care for High-Need, high-cost patients: an evidence synthesis. Issue Brief (Commonw Fund). 2015;31:1–19.

    PubMed  Google Scholar 

  94. Grembowski D, Schaefer J, Johnson KE, Fischer H, Moore SL, Tai-Seale M, Ricciardi R, Fraser JR, Miller D, LeRoy L, et al. A conceptual model of the role of complexity in the care of patients with multiple chronic conditions. Med Care. 2014;52(Suppl 3):7–S14.

    Article  Google Scholar 

  95. Le Reste JY, Nabbe P, Lingner H, Kasuba Lazic D, Assenova R, Munoz M, Sowinska A, Lygidakis C, Doerr C, Czachowski S, et al. What research agenda could be generated from the European General Practice Research Network concept of Multimorbidity in Family Practice? BMC Fam Pract. 2015;16:125.

    Article  PubMed  PubMed Central  Google Scholar 

  96. Webster F, Rice K, Bhattacharyya O, Katz J, Oosenbrug E, Upshur R. The mismeasurement of complexity: provider narratives of patients with complex needs in primary care settings. Int J Equity Health. 2019;18(1):107.

    Article  PubMed  PubMed Central  Google Scholar 

  97. Johnson TL, Rinehart DJ, Durfee J, Brewer D, Batal H, Blum J, Oronce CI, Melinkovich P, Gabow P. For many patients who use large amounts of health care services, the need is intense yet temporary. Health Aff (Millwood). 2015;34(8):1312–9.

    Article  PubMed  Google Scholar 

  98. Smith SM, Wallace E, Salisbury C, Sasseville M, Bayliss E, Fortin M. A Core Outcome Set for Multimorbidity Research (COSmm). Ann Fam Med. 2018;16(2):132–8.

    Article  PubMed  PubMed Central  Google Scholar 

  99. Bierman AS, Wang J, O’Malley PG, Moss DK. Transforming care for people with multiple chronic conditions: Agency for Healthcare Research and Quality’s research agenda. Health Serv Res. 2021;56(Suppl 1):973–9.

    Article  PubMed  PubMed Central  Google Scholar 

  100. Berry-Millett R, Bodenheimer TS. Care management of patients with complex health care needs. Synth Proj Res Synth Rep 2009(19).

  101. Capobianco E, Lio P. Comorbidity: a multidimensional approach. Trends Mol Med. 2013;19(9):515–21.

    Article  PubMed  Google Scholar 

  102. Cristofalo M, Boutain D, Schraufnagel TJ, Bumgardner K, Zatzick D, Roy-Byrne PP. Unmet need for mental health and addictions care in urban community health clinics: frontline provider accounts. Psychiatr Serv. 2009;60(4):505–11.

    Article  PubMed  Google Scholar 

  103. Gardner AL, Weppner WG, Willis J, Bernotski J. PACT ICU Model: Interprofessional Case Conferences for High-Risk/High-Need Patients. Fed Pract 2018, 35(12):34–41.

  104. Safford MM, Allison JJ, Kiefe CI. Patient complexity: more than comorbidity. The vector model of complexity. J Gen Intern Med. 2007;22(Suppl 3):382–90.

    Article  PubMed  PubMed Central  Google Scholar 

  105. Sampalli T, Dickson R, Hayden J, Edwards L, Salunkhe A. Meeting the needs of a complex population: a functional health- and patient-centered approach to managing multimorbidity. J Comorb. 2016;6(2):76–84.

    Article  PubMed  PubMed Central  Google Scholar 

  106. Yedidia MJ. Competencies for engaging high-needs patients in primary care. Healthc (Amst). 2018;6(2):122–7.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We thank the key informants Nancy Berkmann, Todd Schneberk, Ulyana Shramovyat, and team members of the VA PACT Intensive Management demonstration program for critical insights. We thank the esteemed panelists Varis Green, Robert Carr, Nadereh Pourat, Robert Friedman, Donna Zulman, Bowen Chung, and Laura-Mae Baldwin for supporting this work. We would like to thank Alicia Bergman, Emily Wong, Ken Wells, Michelle Wong, and Marian Katz for their valuable contributions to the key informant information and panel discussions, and Jennifer Dinalo for help with the literature searches.

Funding

The work was funded by the Department of Veterans Affairs. The views and opinions of authors expressed in this manuscript do not necessarily state or reflect those of the Department of Veterans Affairs or the United States Government.

Author information

Authors and Affiliations

  1. Southern California Evidence Review Center, University of Southern California, Los Angeles, USA

    Susanne Hempel, Maria Bolshakova, Gina Thompson, Aneesa Motala & Ben Dennis

  2. Gehr Family Center for Health Systems Science and Innovation, University of Southern California, Los Angeles, CA, USA

    Michael Hochman

  3. VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA

    Elvira Jimenez, David A. Ganz, Sonya Gabrielian & Evelyn Chang

  4. VA Portland Health Care System, Portland, OR, USA

    Samuel Edwards

  5. Los Angeles County Department of Mental Health, Los Angeles, CA, USA

    James Zenner

Authors
  1. Susanne Hempel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maria Bolshakova
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michael Hochman
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Elvira Jimenez
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Gina Thompson
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Aneesa Motala
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. David A. Ganz
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Sonya Gabrielian
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Samuel Edwards
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. James Zenner
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Ben Dennis
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Evelyn Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

SH drafted the manuscript; EJ, DG, SG, SE, JZ, BD provided data; SH, EC, MB, MH, GT, AM prepared analyses, table and figures; SH and EC drafted the manuscript; all authors edited and approved the final manuscript.

Corresponding author

Correspondence to Susanne Hempel.

Ethics declarations

Ethics approval and consent to participate

The University of Southern California Institutional Review Board determined the study to be exempt (ID #HS-20-00106, 5/19/2020) from 45 to 46 according to § 46.104(d) as category (2) and authorized the PI to conduct the research. Informed consent was not required given the exempt status, but key informants gave oral informed consent before the interviews and panelists gave written informed consent before participating in the expert panel. All methods were carried out in accordance with relevant guidelines and regulations and have been performed in accordance with the Declaration of Helsinki.

Consent to publish

Not applicable.

Conflict of interest

The authors have no competing interests as defined by BMC, or other interests that might be perceived to influence the results and/or discussion reported in this paper.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hempel, S., Bolshakova, M., Hochman, M. et al. Caring for high-need patients. BMC Health Serv Res 23, 1289 (2023). https://doi.org/10.1186/s12913-023-10236-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12913-023-10236-w

Keywords

BMC Health Services Research

ISSN: 1472-6963

Contact us