Your privacy, your choice

We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and social media.

By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some third parties are outside of the European Economic Area, with varying standards of data protection.

See our privacy policy for more information on the use of your personal data.

for further information and to change your choices.

Skip to main content

Identifying factors influencing emerging innovations in hospital discharge decision making in response to system stress: a qualitative study

Abstract

Background

The purpose of this qualitative study was to identify emergent rehabilitation innovations and clinician perceptions influencing their implementation and outcomes related to hospital discharge decision-making during the Coronavirus 2019 pandemic.

Methods

Rehabilitation clinicians were recruited from the Veterans Affairs Health Care System and participated in individual semi-structured interviews guided by the integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework. Data were analyzed using a rapid qualitative, deductive team-based approach informed by directed content analysis.

Results

Twenty-three rehabilitation clinicians representing physical (N = 11) and occupational therapy (N = 12) participated in the study. Three primary themes were generated: (1) Innovation: emerging innovations in discharge processes included perceived increases in team collaboration, shifts in caseload prioritization, and alternative options for post-acute care. (2) Recipients: innovations emerged as approaches to communicating discharge recommendations changed (in-person to virtual) and strong patient/family preferences to discharge to the home challenged collaborative goal setting; and (3) Context: the ability of rehabilitation clinicians to innovate and the form of innovations were influenced by the broader hospital system, interdisciplinary team dynamics, and policy fluctuations. Innovations described by participants included (1) use of technological modalities for interdisciplinary collaboration, (2) expansion of telehealth modalities to deliver care in the home, (3) changes in acute care case prioritization, and (4) alternative options for discharge directly to home.

Conclusions

Our findings reinforce that rehabilitation clinicians developed innovative strategies to quickly adapt to multiple systems-level factors that were changing in the face of the COVID-19 pandemic. Future research is needed to assess the impact of innovations, remediate unintended consequences, and evaluate the implementation of promising innovations to respond to emerging healthcare delivery needs more rapidly.

Peer Review reports

Background

Rehabilitation clinicians’ discharge recommendations are one of the strongest predictors of hospital readmissions and other adverse events [1,2,3]. After COVID-19, discharge decision-making fundamentally changed as patients sought to avoid post-acute care facilities by discharging to home. Furthermore, the ability to provide necessary care in the home was hampered by ongoing, COVID-19 exacerbated industry challenges including an undervalued workforce and insufficient staffing [4,5,6,7]. Yet, we do not have a deeper understanding of how rehabilitation clinicians innovate during their discharge decision making processes in the face of external pressures to the health care system. This information has the potential to generate hypotheses to test changes to models of transitional care and inform measurement of unintended consequences (e.g., costly rehospitalizations or multiple, unnecessary transitions in care).

Given the rapid and evolving nature of the COVID-19 pandemic and post-pandemic procedures, a Learning Health System (LHS) approach is needed to study how pandemic-induced changes influenced the emergence of innovation in rehabilitation clinicians’ approaches and recommendations for hospital discharge. The LHS approach encourages continual learning between clinical practice and research through a bi-directional cycle of data to knowledge, knowledge to practice, and practice to data [8,9,10]. Learning Health Systems use rapid cycle methods that integrate data and real-world experiences to iteratively evaluate clinical practices and models of care [11,12,13,14,15]. The Veterans Health Administration (VHA) is the largest integrated health system in the United States and has communicated a vision to adopt LHS approaches into all aspects of research, clinical care, education, and emergency preparedness to optimize care and outcomes for over 9 million veterans served [12, 13, 16]. Thus, we wanted to explore VHA rehabilitation clinicians’ perceptions of hospital discharge decision making and transitions of care to identify emerging innovations that could inform future work evaluating the impact of promising innovations and spread or scale-up.

The continuous learning cycle supported through a LHS lens allows us to translate our approach to identifying and exploring emerging innovations—across a variety of clinical disciplines, settings, and systems–closer to real-time, thus allowing for more rapid and informed responses to system stressors. The COVID-19 pandemic is but one example of an external pressure and innovations in discharge decision-making are likely to occur again, particularly in the face of technological advances and possible post-pandemic reforms in healthcare. With our current focus on hospital discharge, understanding organic innovation is a critical element to move forward with research and quality improvement initiatives to ensure safe, cost-effective, and patient-centered care transitions during the pandemic and beyond. Therefore, the aim of this qualitative study was to identify emergent rehabilitation innovations and clinician perceptions influencing their implementation and outcomes related to hospital discharge decision-making during the COVID-19 pandemic. Our study’s overarching focus was on the data to knowledge aspect of LHS, by which we used qualitative approaches to identify emerging innovations and perceptions of best practices in hospital discharge recommendations and transitions of care. Results were rapidly disseminated to key leadership to inform future evidence and implementation of knowledge to practice.

Methods

Study design

We used a qualitative study design guided by the integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) conceptual framework [17, 18]. The i-PARIHS model has been adapted previously to address complex implementation science research questions, thus we adapted i-PARIHS to identify organic innovations (e.g., practice, intervention, approach) around discharge decision making (data to knowledge) rather than to evaluate implementation of a specific intervention (knowledge to practice). While i-PARIHS considers facilitation a central component to aligning the innovation, recipients, and context for successful implementation, instead, we examined the interactions among the potential clinical innovations, recipients involved, and contextual factors. Using i-PARIHS in this way provides the foundation for facilitation to be used when considering implementation of emerging innovations that occur in response to system stressors. In i-PARIHS innovation is traditionally defined as the intervention characteristics, including the complexity of the intervention, relative advantage compared to current practice or another intervention, usability, and evidence to support the intervention (e.g., research-based evidence, clinical experience, and patient preferences). In this study, innovation consisted of practices or approaches that organically emerged during the COVID-19 pandemic to manage hospital discharge decision-making and processes [17, 18]. The i-PARIHS construct recipients includes characteristics of the people who are affected by the innovation including patients and care partners [17, 18]. Context includes aspects internal to the organizational setting including leadership support, culture, organizational priorities, evaluation and feedback processes, and learning networks. Context also includes aspects external to the organization, such as policy drivers and priorities, incentives and mandates, and inter-organizational networks [17, 18].

Participants

We used convenience sampling to recruit occupational therapists (OTs), occupational therapist assistants (OTAs), physical therapists (PTs), and physical therapist assistants (PTAs) who spend at least 25% of their time providing acute or post-acute care service in the Veterans Affairs (VA) Health Care System. An initial recruitment letter was sent out to rehabilitation clinicians in the Minneapolis VA Health Care System (MVAHCS), where co-authors have a relationship with clinical leadership. We then used a snowball technique [19, 20] to supplement our recruitment efforts by expanding beyond the MVAHCS to other VAs. Informed consent was obtained prior to data collection, which included an overview of the purpose of the study, risks and benefits to participating, confidentiality, and the voluntary nature of the study.

Data collection

Qualitative data were collected from rehabilitation clinicians using 30–60 min semi-structured interviews conducted between May 2022 and August 2022. Interviews were conducted virtually. Interview participants self-reported descriptive characteristics that included discipline and years of practice. Union rules prohibited collection of any other demographic information (e.g., sex, race/ethnicity, age, highest degree earned). The interview guide (Table 1) was developed through an iterative, team-based approach and informed by expert input from key informants at the MVAHCS (two of whom participated in the interviews), a review of relevant literature [21,22,23], and the i-PARIHS framework [17, 18]. Semi-structured interview procedures included a welcome, introduction, study purpose, interview goals, and a statement of confidentiality. The goal of the interview was for rehabilitation clinicians to provide detailed descriptions of their discharge decision making process and perceptions of the patient’s transition from hospital to home, which could then be further analyzed within the i-PARIHS framework. VA union rules prohibited recording and transcribing qualitative interviews with the rehabilitation clinicians participating in this study. To ensure trustworthiness of data, interviews were documented using extensive field notes by trained research members [24]. During the interviews, two members of the research team were present to document the interviews through extensive field notes. These two members of the research team met immediately after the interview to collaboratively review the field notes, revise notes for accuracy of participant comments, and document immediate impressions. To further reduce risk of bias, we also conducted member checking [19, 20] as described below in the section titled Reflexivity and rigor.

Table 1 Semi-structured interview guide

Data analysis

We used a rapid qualitative, deductive team-based approach [25, 26] informed by directed content analysis [27, 28]. Aligned with the LHS approach [8], a rapid qualitative approach [25, 26] was employed as the healthcare system continues to have evolving processes post-pandemic and the insights gathered are timely and pertinent. Insights were disseminated to key leadership throughout the data analysis process to provide immediate value to the MVAHCS, such as influencing the content and utility of research in this area as well as by informing decision making in real-time regarding potential resource needs and promising approaches that could be scaled quickly to address ongoing system capacity challenges. Directed content analysis uses a predefined framework (in this case i-PARIHS [17, 18]) to guide data collection, analysis, and interpretation [28].

We used the constructs outlined in i-PARIHS (recipients, context, and innovation) to guide deductive themes and were also open to emergent themes. For analysis, we compiled extensive field notes into a matrix for analysis (Microsoft Excel). The rows consisted of participants and columns represented the pre-identified categories mapped to the interview guide questions. Once all data was organized for each participant, the data was transferred to a word document (Microsoft Word) where repetitive data were removed. Three members of the research team (AMG, MJM and JPW) met bi-weekly to iteratively discuss and analyze the accruing data by deductively categorizing the raw data into predefined themes by timepoint (pre-pandemic versus COVID-19 era) and discussing the potential for emerging themes or the need to collapse themes. During this time, the team also identified representative field note excerpts for emergent themes. This team-based approach to coding allowed a less arduous, yet still rigorous, approach to ensuring data dependability and trustworthiness compared to calculating inter-rater reliability [29]. Finally, the multi-disciplinary research team met bi-weekly to discuss resulting themes and how they compared or contrasted across timepoints. Saturation was defined by the absence of new and emerging themes within the data [30].

Reflexivity and rigor

This qualitative study followed the consolidated criteria for reporting qualitative research checklist (COREQ) to ensure the rigor of the study design, conduct, and interpretation of findings [31]. Prior to conducting any interviews, researchers (HJH, AMG, NB) were extensively trained by co-author JPW—including completing practice interviews–to ensure consistency with qualitative interview processes. All members of the research team involved in the interview process received extensive training by co-author JPW on documenting field notes using practice interviews and corroborated notes for accuracy [24]. We also used a team-based approach to open coding to create inter-coder consensus [29]. As a form of member checking, we discussed a draft table of results with three participants to ensure trustworthiness of our rapid qualitative analysis of findings [19, 20, 32]. During this member check, participants provided feedback on near completed qualitative findings, voiced agreement or disagreement, as well as provided additional context for our findings. These data were then used to finalize our qualitative results.

Role of funding source

The funders played no role in the design, conduct, of reporting of this study.

Results

We collected data from 23 rehabilitation clinicians (PT/PTA: 11; OT: 12) across 10 VHA facilities. No OTAs were recruited. The mean number of years working as a rehabilitation clinician was 13.7 (SD = 6.4; range 5–24 years) with the mean number of years working in the VHA system at 11.3 (SD = 6.7; range 1–23 years). For each of the i-PARIHS constructs, we identified primary themes emerging from the qualitative data. The primary themes described emergent innovations and factors that influence the emergence of these innovations (context and recipients). The primary theme for innovation was “evolving processes.” The primary theme for recipients was “patient & care partner needs.” The primary theme for context was “system & personnel needs”. Table 2 outlines exemplar excerpts from our field notes.

Table 2 i-PARIHS constructs and emergent themes by pre-pandemic and COVID-19 era time frames with exemplar field note summaries

Innovation: evolving processes

The innovation construct of i-PARIHS was portrayed by the primary theme of evolving processes that emerged with the onset of the COVID-19 pandemic. Participants described different approaches to hospital discharge decision making pre-pandemic versus the COVID-19 era, with noted innovations occurring because of contextual and recipient factors arising from the COVID-19 era. Emergent, nested sub-themes included interdisciplinary collaboration; prioritization of workflow and caseloads; and reducing readmission risk. Innovations described by participants included (1) use of technological modalities for interdisciplinary communication and collaboration regarding discharge decision making, (2) expansion of telehealth modalities to deliver care to patients in the post-acute period that influenced where patients could safely discharge, (3) changes in acute care case prioritization, and (4) alternative options for discharge directly to home.

Interdisciplinary collaboration

Pre-pandemic, participants described the complex decision-making process that requires a high level of clinical reasoning to sift through the interaction between a patient’s individual (e.g., falls risk, cognition, health literacy), social (e.g., caregiver support), and environmental (e.g., home environment, transportation) factors. Interdisciplinary collaboration was stated as a key component to making discharge recommendations. During the COVID-19 era, most participants talked about challenges with communication between interdisciplinary team members due to limited in-person interactions. As a result, participants talked about innovations in improved inter- and intra-disciplinary communication and collaboration through the expanded capacity of virtual communication platforms (e.g., Microsoft Teams, virtual care platform) that were newly implemented in the federal system. For example, one participant explained that despite limited face-to-face interactions, chat and calling features on a secure network allowed for faster response time and virtual hand-offs. The absence of family or care partners to confirm or provide accurate information to inform discharge process and decisions was a significant challenge to meeting patient and family needs. As a result, during the COVID-era most participants described innovations related to enhanced interdisciplinary team coordination (formal and informal) that occurred to make sure everyone was on the same page in terms of what information is provided (by patients, family, or care partners) and how it impacts the discharge decision. Participants spoke about how the pandemic-accelerated expansion of virtual care options allowed clinicians to make discharge decisions that would ensure patients would receive the necessary follow-up care and support services. Participants described the continuity of care that could be provided by the VA when VA physical and occupational therapists could provide virtual care to veterans in their home following hospitalization.

Prioritization of workflow & caseloads

Pre-pandemic, most participants described workflows where patients with imminent hospital discharges were prioritized to receive visits or services versus those awaiting placement and needing a sub-acute level of care. After high-priority cases were seen, participants talked about how their built-in workflows allowed for follow-up to capture the natural progression of recovery and potential changes in functional status that could influence updates to discharge recommendations. Participants spoke about how follow-up allowed for reassessment of the patient’s progress and function to determine what level of sub-acute rehabilitation care may (or may not) be needed and the most appropriate discharge location. For patients where a discharge directly to home was considered, participants indicated caregiver presence was crucial along with the willingness to complete home physical or occupational therapy to maximize function and ability to complete activities of daily living.

During the COVID-19 era, some participants spoke about innovations related to earlier discharge planning and decision-making for more complex patients for whom discharge placement would be difficult. They acknowledged that patients with difficult placements were not a new challenge, but the pandemic has made such placements and the increased hospital lengths of stay more visible in an era where hospital stays may be longer due to limited or unavailable post-acute resources. When discussing the COVID-19 era, participants described adjusting the frequency of services per week in two scenarios. The first scenario was a sub-acute model of care where they were providing treatment 5 days per week to patients who would be going home, and pre-pandemic would have discharged to sub-acute care. For example, participants described pre-pandemic plans of care for patients waiting for sub-acute care as 1–3 days per week. In the second scenario, participants described decreasing plans of care (visits per week) in patients waiting for sub-acute care to get to more acute patients.

Reducing readmission risk

Pre-pandemic, most participants talked about the default recommendation being sub-acute rehabilitation to ensure the patient’s overall daily function was maximized prior to return home. Some participants indicated that multiple hospitalizations or recent readmissions signaled a need for further conversation with the patient and interdisciplinary team to reflect on what worked and did not work in the previous discharge plan. Participants spoke about the need for care partner support and willingness to complete home rehabilitation as an essential component of discharge making when considering a safe discharge to home.

Many participants noted a shift during the COVID-19 era towards more discharge recommendations to home with supports and services. This shift has varied throughout the pandemic due to restrictions in rehabilitation facilities being lifted and the availability of vaccines. For example, some participants described maintenance of this type of mindset to promote aging in place, while also indicating that other members of their team have slipped back to the previous default of discharge to sub-acute rehabilitation. Some participants indicated their discharge decision-making included more “thinking outside the box.” Participants described a wider array of discharge options that balanced tensions and strains of the pandemic on health and social supports. For example, one participant talked about how pre-pandemic the discharge recommendations were limited to 3–4 options (home, home with home health rehabilitation, sub-acute rehabilitation, and acute rehabilitation unit). Now in the COVID-19 era, the participant indicated more rehabilitation recommendation options were created to innovatively expand safe discharge options for home (e.g., home with durable medical equipment, home with skilled or unskilled care). However, some participants noted that patients may “fall through the cracks” due to the lack of follow-up to ensure equipment was received, home services and supports were started in a timely manner, and rehabilitation was initiated.

During the pandemic, participants indicated teleworking allowed time to reach out to patient’s following hospital or post-acute discharge to ensure equipment and home services were in place and assess whether the patient or care partner had additional questions. One participant noted that during the COVID-19 era, supply chain issues for durable medical equipment (e.g., standard wheelchair, lifts) have led to creative solutions to ensure patients have what they need as an alternative “bridge” to the equipment for safe discharge home. For example, rehabilitation clinicians leveraged equipment that might be available in satellite clinics to ensure patients were able to get critical needs, such as a walker or crutches, before discharging home. Another example was increased communication and collaboration with family—outside of the primary care partner—on a plan to safely assist in the home until lift equipment arrived.

Recipients: patient & care partner needs

The recipients construct of i-PARIHS was encapsulated by the primary theme of patient and care partner needs. This theme relates to the receipt of and potential participation in hospital discharge decision-making by patients and their care partners. Two nested sub-themes, representing differing approaches to meeting the diverse, modifiable (or not), and potentially independent needs of patients and care partners included planning and communication and the complex nature of needs.

Planning & communication

Pre-pandemic, interviewees said they relied on in-person communication with care partners to understand a patient’s social support system including care partner availability, safety concerns, and additional services already in place. For instance, some participants spoke about in-person communication with care partners allowing for discussion of their preferences for and confidence in providing recommended care to the patient following hospital discharge. Participants then integrated this information with the patient’s functional ability and environmental factors to formulate a safe discharge recommendation that met both patient and care partner needs. Pre-pandemic, participants described communicating typical recommendations for sub-acute rehabilitation stay (e.g., skilled nursing facility) following hospitalization to patients and care partners to allow increased time for the interdisciplinary team, patient, and family to adequately plan for appropriate and safe discharge. During the COVID-19 era, participants maintained that communication with care partners remained an essential component of care despite difficulty communicating and providing hands-on training with care partners due to visitor restrictions. As such, communication with family or care partner occurred via phone or video which participants indicated may lead to miscommunications and misunderstanding of a patient’s current level of function and corresponding needs. A few participants talked about how the family needed to see the patient’s challenges in-person to fully understand what the patient’s needs would be at hospital discharge by comparing to his or her prior level of function. Additionally, visitor restrictions made hands-on training and subsequent planning for safe discharge challenging. One participant described providing care partner training over the phone and indicated it was ineffective because the clinician was unable to model the training (e.g., where to stand, how the clinician might assist with verbal cues, home set-up modifications).

Complex nature of needs

Pre-pandemic, participants described the active engagement of patients and care partners in collaborative goal setting to support autonomy in both the patient’s ultimate decision to go with or against discharge recommendations and the potential need for a higher level of care after hospital discharge (e.g., memory care or long-term care placement). In some complex situations, patient autonomy was influenced by insurance coverage or environmental needs. For example, one participant described an instance where a patient’s discharge options were limited due to experiencing homelessness, leading to an unsafe environment. When talking about the COVID-19 era, participants indicated that patient preferences to discharge home meant reliance on home health care and services that were experiencing staffing shortages. Participants suggested such staff shortages meant patient may have unmet needs prior to hospitalization that persist following discharge with added gaps in care and services to meet any new needs arising from recent hospitalization.

Context: system & personnel needs

The context construct of i-PARIHS was captured by the primary theme of system and personnel needs. This theme relates to the environment in which the health care system and rehabilitation clinicians operated in to make and enact discharge planning and decisions. Participants described different contextual factors influencing hospital discharge decision making pre-pandemic versus the COVID-19 era, thus emergent sub-themes included system influence on clinician practice, the team role of rehabilitation clinicians, and pandemic-related fluctuations in practices, processes, and policies. Practices, processes, and policies generated in response to the pandemic emerged as a subtheme that was unique to the COVID-19 era.

System influence on clinician practice

Pre-pandemic, participants cited pressure to discharge patients to the next level of sub-acute care for rehabilitation to increase the time needed to plan for a safe discharge home. Participants talked about documentation as being essential to justifying rehabilitation clinicians’ decisions surrounding appropriateness for further rehabilitation (acute or sub-acute), the need for additional services, and recommendations to ensure the safest discharge possible. During the COVID-19 era—specifically in the initial stages of the pandemic–some participants indicated they were operating under the assumption that patients need to discharge home, even in cases where they would have recommended short term rehabilitation for the same patient in a pre-pandemic scenario. This perceived pressure to discharge to home during the COVID-19 era created tension as clinicians grappled with the current state of post-acute care. For example, one clinician explained that staffing shortages impacted home health care quality and timeliness, resulting in limited options for discharge.

Team role of rehabilitation clinicians

Some participants felt that members of the rehabilitation team were often the last ones invited to join in the discharge planning and decision-making process. These last-minute requests for assessment often left rehabilitation clinicians scrambling to set up home safety evaluations and care partner training. In some cases, participants felt their recommendations were the only thing keeping a patient from discharging to situation that was unsafe or where needs were not going to be met and readmission to the hospital was inevitable. For example, one participant explained that they were the “last defense” when advocating for a patient they deemed as not ready to discharge to home due to limited awareness for safety with transfers. The clinician explained that they worked with the family to provide training on transfers and evaluating assistive devices prior to discharge. Participants described delivering continuing education to interdisciplinary clinicians to address late involvement of rehabilitation clinicians and promote early and appropriate involvement of the rehabilitation team. Participants described their pre-pandemic role as primarily acute care assessment. During the COVID-19 era, some participants talked about a shift from their pre-pandemic assessment role to a sub-acute model of care—termed “Rehab in Place.” “Rehab in Place” was described as daily treatment while hospitalized with a discharge goal directed at home. Some participants reported that this shift created tension in work roles as workflow (e.g., triaging) and resources (e.g., staffing to provide treatments 6 to 7 days per week) needed to change to adequately support such a paradigm shift. Participants talked about how the COVID-19 pandemic initially made discharge to rehabilitation facilities difficult due to outbreaks and patient/family fears of contracting the virus at a communal facility. According to some participants, these difficult placements led to longer hospitalizations and adjustments to plans of care (i.e., frequency of acute services) provided by rehabilitation clinicians. As a result of these longer hospitalizations, some clinicians perceived elevated scrutiny from higher levels of leadership to either “Rehab in Place” with a higher frequency of services or develop alternative options for discharge.

Pandemic-related fluctuations in practices, processes, and policies

During the COVID-19 era, participants reported high stress and emotional burden due to various communication breakdowns regarding visitor policies, personal protective equipment policies, outbreak status, and changing public health recommendations. For example, one participant explained that they were tired and stressed due to the disconnect between management, leadership, and clinicians as the policies changed frequently and different plans were communicated from various leadership. While these changes in practice, processes, and policies have evolved with the pandemic, some participants felt rehabilitation teams were "not given the chance to breathe” and adjust to contextual changes in acute care delivery. Some participants spoke about the changes to workflow and resources as sources of tension between clinicians and organizational leadership.

Discussion

This qualitative study found factors that influenced the emergence of innovation in hospital discharge decision-making during the COVID-19 era, thereby informing the data to knowledge aspect of LHS. Factors at the recipient and contextual level brought forth innovation to hospital discharge decision making. Emerging innovations, as perceived and described by rehabilitation clinicians, included interdisciplinary acute team collaboration, shifts in caseload prioritization, and alternative options for post-acute care. Our study adds to the literature by depicting a health care system’s response and emerging innovation in discharge decision making that fostered creative solutions to existing, new, and evolving issues with hospital discharge during the COVID-19 era.

We identified similar challenges during the COVID-19 era as those described by other qualitative studies [33, 34] including reports of reduced communication between clinicians and care partners, a focus on decreasing hospital lengths of stay, patients opting to go home rather than sub-acute rehabilitation, and ongoing stress and emotional burden with ever changing policies/practices. Our findings are also consistent with experiences of other healthcare professionals during the pandemic [35, 36]. Other qualitative studies of frontline providers during the pandemic described positive experiences that emerged from the challenges such as feeling part of something bigger than themselves and being valued as healthcare professionals [36, 37]. These experiences align with our findings of innovation in the midst of a systemic stressor. Importantly, the COVID-19 pandemic has drastically transformed health care, particularly with the accelerated integration of technology into care delivery [38, 39]. Thus, the current study has relevance in the post-pandemic world as we grapple with the many healthcare issues unmasked by the pandemic and seize the opportunity to leverage this momentum for healthcare transformation to reshape our approaches to care and care delivery. Our study found that innovations during the hospital discharge decision making is evolving as the pandemic persists and some changes were perceived as positive by rehabilitation clinicians.

Rehabilitation clinicians perceived many of the innovations in response to external stressors (pandemic) as having potential positive or negative impacts on patient outcomes. These findings highlight the need for future research to evaluate the impact of the following perceived innovations identified by participants to determine the patient, clinician, and system-level outcomes: increased ease of team collaboration due to virtual options, changes in caseload prioritization in the hospital setting, increased consideration of transitions of care directly to the home, and the increased availability and accessibility of virtual care in the home. Many of these innovations align with prioritization of aging in place” which is known to have many benefits from patients [40, 41]. It may be that clinicians and systems saw firsthand the benefits of aging in place and perceived the risks of discharging home were not as high as previously assumed. Identification and evaluation of unintended consequences that are not deliberate or foreseen are needed to fully understand the impact innovations can have on multiple outcomes [42]. For example, a shift toward a “Rehab in Place” model of care may have implications for staffing structures and patient perceptions of care. There is also a need to recognize the toll of the pandemic on rehabilitation clinicians’ mental health and collective trauma from providing care during the pandemic [43]. Staff stress and burnout—despite innovations—is a necessary factor to consider when potentially redefining the role of rehabilitation clinicians in the hospital setting.

Our findings also highlight the importance of implementation frameworks—such as i-PARIHS—in identifying factors that hinder or facilitate innovations that improve health service delivery and patient outcomes. We applied the i-PARIHS framework in a novel way to identify organic clinical innovation developed during hospital discharge decisions when the system was stressed by the COVID-19 pandemic. While i-PARIHS is traditionally used to identify barriers and facilitators to implementation of a specified innovation, we used the framework to identify emerging innovations in response to the pandemic. Additionally, we used i-PARIHS to understand and describe the underlying context and recipient factors that potentially drove these innovations. Such an application of i-PARIHS allows future research to consider alternative approaches to evaluating emerging innovations that have the potential to translate knowledge into practice. Breton and colleagues utilized a similar approach, although not with i-PARIHS, to qualitatively examine how the pandemic modified the organization and processes of primary care and how those were implemented for continuous quality improvement [44]. Identifying and understanding these factors can inform future studies along the research continuum from effectiveness to implementation trials.

Our study’s strength is that it provides insight into evolving recipient and contextual factors that fostered innovation and contributes to the data to knowledge part of a LHS cycle. With a LHS lens, we applied the i-PARIHS framework in a novel way to identify organic clinical innovation developed during hospital discharge decisions when the system was stressed (in this case by the COVID-19 pandemic). The application of this method transcends disciplines, settings, communities, and systems as the need to iteratively evaluate and continuously learn is crucial to healthcare transformation and the overall vision of optimizing patient and population outcomes.

Limitations

A few limitations of this study should be noted. First, the participants were recruited from and provided care in the VA health care system and, thus, the results may not be immediately transferrable to other non-VA health care systems. The COVID-19 pandemic created a natural experiment where all health care systems were stressed and, thus, responses to such stress may be similar across systems. In addition, we choose the VA given its vision to implement LHS principles and the infrastructure it is creating to support this vision. Second, due to union stipulations we were unable to record interviews or collect demographic data on participants other than disciplines and years of clinical experience. To address this, we used member checking to ensure we accurately captured the data. In terms of demographic data, the American Physical Therapy Association’s most recent data to date on members (2016–2017) indicates a majority identify as female, white, non-Hispanic with most having at or above a doctorate level terminal degree [45].

Conclusions

Understanding the experiences of rehabilitation clinicians providing care and engaging in hospital discharge decisions prior to the pandemic and during the COVID-19 era is essential to informing real-time resource needs and promising approaches that can be adapted, implemented, evaluated, and scaled quickly in response to system stressors. Importantly, the information gathered by this qualitative study provides foundational data for future research and LHS efforts focused on improving transitions from the hospital to the next level care. The experiences captured by rehabilitation clinicians suggest responses to the ongoing pandemic and future, unforeseen stressors can be innovative and potentially a positive change to the current status quo.

Data availability

The datasets generated and/or analyzed during the current study are not publicly available to minimize identification of participants but may be available from the corresponding author on reasonable request.

Abbreviations

VA:

Veteran Affairs

VHA:

Veteran Health Administration

LHS:

Learning Healthy System

i-PARIHS:

integrated Promoting Action on Research Implementation in Health Services

OT:

Occupational Therapist

OTA:

Occupational Therapist Assistant

PT:

Physical Therapist

PTA:

Physical Therapist Assistant

MVAHCS:

Minneapolis Veteran Affairs Health Care System

References

  1. Smith BA, Fields CJ, Fernandez N. Physical therapists make accurate and appropriate discharge recommendations for patients who are acutely ill. Phys Ther. 2010;90(5):693–703. https://doi.org/10.2522/PTJ.20090164.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Wright JR, Koch-Hanes T, Cortney C, et al. Planning for Safe Hospital Discharge by identifying patients likely to fall after discharge. Phys Ther. 2022;102(2). https://doi.org/10.1093/PTJ/PZAB264.

  3. Kadivar Z, English A, Marx BD. Understanding the relationship between physical therapist participation in Interdisciplinary rounds and Hospital Readmission Rates: preliminary study. Phys Ther. 2016;96(11):1705–13. https://doi.org/10.2522/PTJ.20150243.

    Article  PubMed  Google Scholar 

  4. Gustavson AM, Toonstra A, Johnson JK, Ensrud KE. Reframing Hospital to Home Discharge from should we? To how can we? COVID-19 and Beyond. J Am Geriatr Soc. 2021;69(3):608–9. https://doi.org/10.1111/JGS.17036.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Donker T, Bürkin Bsc FM, Wolkewitz Phd M et al. Navigating hospitals safely through the COVID-19 epidemic tide: predicting case load for adjusting bed capacity. Infect Control Hosp Epidemiol. https://doi.org/10.1017/ice.2020.464.

  6. Franzosa E, Wyte-Lake T, Tsui E, Reckrey J, Sterling MR. Essential but excluded: building disaster preparedness capacity for Home Health Care Workers and Home Care agencies. J Am Med Dir Assoc. 2022;23(12). https://doi.org/10.1016/J.JAMDA.2022.09.012.

  7. Cornell PY, Magid KH, Corneau E, Haverhals LM, Levy C. Decline in Veterans’ admissions to nursing homes during COVID-19: fewer beds, more fear, and finding Alternative Care settings. J Am Med Dir Assoc. https://doi.org/10.1016/j.jamda.2022.12.021. Published online 2023.

  8. Kilbourne AM, Evans E, Atkins D. Learning health systems: driving real-world impact in mental health and substance use disorder research. FASEB BioAdvances. 2021;3(8):626. https://doi.org/10.1096/FBA.2020-00124.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Guise JM, Savitz LA, Friedman CP. Mind the gap: putting evidence into practice in the era of Learning Health systems. J Gen Intern Med. 2018;33(12):2237–9. https://doi.org/10.1007/S11606-018-4633-1.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Friedman CP, Rubin JC, Sullivan KJ. Toward an Information Infrastructure for Global Health Improvement. Yearb Med Inform. 2017;26(1):16–23. https://doi.org/10.15265/IY-2017-004.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Olsen L, Aisner D, McGinnis JM. The Learning Healthcare System: Workshop Summary. Natl Academy Pr; 2007.

    Google Scholar 

  12. Kilbourne AM, Schmidt J, Edmunds M, Vega R, Bowersox N, Atkins D. How the VA is training the Next-Generation workforce for learning health systems. Learn Health Syst. 2022;6(4):e10333. https://doi.org/10.1002/LRH2.10333.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Atkins D, Kilbourne AM, Shulkin D. Moving from Discovery to system-wide change: the role of Research in a Learning Health Care System: experience from three decades of Health Systems Research in the Veterans Health Administration. Annu Rev Public Health. 2017;38:467–87. https://doi.org/10.1146/ANNUREV-PUBLHEALTH-031816-044255.

    Article  PubMed  Google Scholar 

  14. Gustavson AM. A learning health system approach to long COVID Care. Fed Practitioner. 2022;39(7). https://doi.org/10.12788/FP.0288.

  15. Romanelli RJ, Azar KMJ, Sudat S, Hung D, Frosch DL, Pressman AR. Learning health system in crisis: lessons from the COVID-19 pandemic. Mayo Clin Proc Innovations Qual Outcomes. 2021;5(1):171–6. https://doi.org/10.1016/J.MAYOCPIQO.2020.10.004.

    Article  Google Scholar 

  16. Kilbourne AM, Jones PL, Atkins D. Accelerating implementation of research in Learning Health systems: lessons learned from VA Health Services Research and NCATS Clinical Science Translation Award programs. J Clin Translational Sci. 2020;4(3):195–200. https://doi.org/10.1017/CTS.2020.25.

    Article  Google Scholar 

  17. Kitson AL, Rycroft-Malone J, Harvey G, McCormack B, Seers K, Titchen A. Evaluating the successful implementation of evidence into practice using the PARiHS framework: theoretical and practical challenges. Implement Sci. 2008;3(1). https://doi.org/10.1186/1748-5908-3-1.

  18. Harvey G, Kitson A. PARIHS revisited: from heuristic to integrated framework for the successful implementation of knowledge into practice. Implement Science: IS. 2016;11(1). https://doi.org/10.1186/S13012-016-0398-2.

  19. Creswell JW, Poth CN. Qualitative inquiry & research design: choosing among five approaches. 4th ed. Thousand Oaks: Sage Publicatons Inc.; 2016. p. 1–646. Published online 2017.

  20. Miles MB, Huberman AM. In: Miles MB, Huberman AM, editors. An expanded sourcebook: qualitative data analysis (2nd Edition). 2nd ed. Sage Publications; 1994. p. 1–354.

    Google Scholar 

  21. Holland DE, Bowles KH. Standardized discharge planning assessments: impact on patient outcomes. J Nurs Care Qual. 2012;27(3):200–8. https://doi.org/10.1097/NCQ.0B013E31824EBC59.

    Article  PubMed  Google Scholar 

  22. Bowles KH, Foust JB, Naylor MD. Hospital discharge referral decision making: a multidisciplinary perspective. Appl Nurs Res. 2003;16(3):134–43. https://doi.org/10.1016/S0897-1897(03)00048-X.

    Article  PubMed  Google Scholar 

  23. Strategy 4: Care Transitions From Hospital to Home: IDEAL Discharge Planning | Agency for Healthcare Research and Quality. https://www.ahrq.gov/patient-safety/patients-families/engagingfamilies/strategy4/index.html. Accessed 27 Dec 2021.

  24. Rutakumwa R, Mugisha JO, Bernays S, et al. Conducting in-depth interviews with and without voice recorders: a comparative analysis. Qualitative Res. 2020;20(5):565–81. https://doi.org/10.1177/1468794119884806.

    Article  Google Scholar 

  25. Johnson GA, Vindrola-Padros C. Rapid qualitative research methods during complex health emergencies: a systematic review of the literature. Soc Sci Med. 2017;189:63–75. https://doi.org/10.1016/J.SOCSCIMED.2017.07.029.

    Article  PubMed  Google Scholar 

  26. Beebe J. Rapid qualitative inquiry: a field guide to team-based assessment. 2014.

    Google Scholar 

  27. Braun V, Clarke V. Using thematic analysis in psychology. Qualitative Res Psychol. 2006;3(2):77–101. https://doi.org/10.1191/1478088706QP063OA.

    Article  Google Scholar 

  28. Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15(9):1277–88. https://doi.org/10.1177/1049732305276687.

    Article  PubMed  Google Scholar 

  29. Cascio MA, Lee E, Vaudrin N, Freedman DA. A Team-based Approach to open coding: considerations for creating Intercoder Consensus. Field Methods. 2019;31(2):116–30. https://doi.org/10.1177/1525822X19838237.

    Article  Google Scholar 

  30. Saunders B, Sim J, Kingstone T, et al. Saturation in qualitative research: exploring its conceptualization and operationalization. Qual Quant. 2018;52(4):1893. https://doi.org/10.1007/S11135-017-0574-8.

    Article  PubMed  Google Scholar 

  31. Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health care: J Int Soc Qual Health Care. 2007;19(6):349–57. https://doi.org/10.1093/INTQHC/MZM042.

    Article  Google Scholar 

  32. Birt L, Scott S, Cavers D, Campbell C, Walter F. Member checking: a tool to enhance trustworthiness or merely a nod to validation? Qual Health Res. 2016;26(13):1802–11. https://doi.org/10.1177/1049732316654870.

    Article  PubMed  Google Scholar 

  33. Burgdorf JG, Wolff JL, Chase JA, Arbaje AI. Barriers and facilitators to family caregiver training during home health care: a multisite qualitative analysis. J Am Geriatr Soc. 2022;70(5):1325–35. https://doi.org/10.1111/JGS.17762.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Van Oorsouw R, Oerlemans A, Klooster E, et al. A sense of being needed: a phenomenological analysis of Hospital-based Rehabilitation Professionals’ experiences during the COVID-19 pandemic. Phys Ther. https://doi.org/10.1093/PTJ/PZAC052. Published online May 5, 2022.

  35. Billings J, Ching BCF, Gkofa V, Greene T, Bloomfield M. Experiences of frontline healthcare workers and their views about support during COVID-19 and previous pandemics: a systematic review and qualitative meta-synthesis. BMC Health Serv Res. 2021;21(1). https://doi.org/10.1186/S12913-021-06917-Z.

  36. Dagyaran I, Risom SS, Berg SK, et al. Like soldiers on the front - a qualitative study understanding the frontline healthcare professionals’ experience of treating and caring for patients with COVID-19. BMC Health Serv Res. 2021;21(1). https://doi.org/10.1186/S12913-021-06637-4.

  37. Gerada C. Clare Gerada: some good must come out of covid-19. BMJ (Clinical Res ed). 2020;369. https://doi.org/10.1136/BMJ.M2043.

  38. Ndwabe H, Basu A, Mohammed J. Post pandemic analysis on comprehensive utilization of telehealth and telemedicine. Clin eHealth. 2024;7:5–14. https://doi.org/10.1016/j.ceh.2023.12.002.

    Article  Google Scholar 

  39. Blandford A, Wesson J, Amalberti R, AlHazme R, Allwihan R. Opportunities and challenges for telehealth within, and beyond, a pandemic. Lancet Glob Health. 2020;8(11):e1364–5. https://doi.org/10.1016/S2214-109X(20)30362-4.

    Article  PubMed  PubMed Central  Google Scholar 

  40. ACTIVE AGEING. A POLICY FRAMEWORK Active Ageing.

  41. Gustavson AM, Vincenzo J, Miller MJ, et al. Equitable implementation of innovations to promote successful aging in place. J Am Geriatr Soc. 2023;71(2). https://doi.org/10.1111/JGS.18177.

  42. Kirk MA, Moore JE, Wiltsey Stirman S, Birken SA. Towards a comprehensive model for understanding adaptations’ impact: the model for adaptation design and impact (MADI). Implement Sci. 2020;15(1):1–15. https://doi.org/10.1186/S13012-020-01021-Y/FIGURES/3.

    Article  Google Scholar 

  43. Linzer M, Jin JO, Shah P, et al. Trends in clinician burnout with associated mitigating and aggravating factors during the COVID-19 pandemic. JAMA Health Forum. 2022;3(11):E224163. https://doi.org/10.1001/JAMAHEALTHFORUM.2022.4163.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Breton M, Marshall EG, Deslauriers V, et al. COVID-19 - an opportunity to improve access to primary care through organizational innovations? A qualitative multiple case study in Quebec and Nova Scotia (Canada). BMC Health Serv Res. 2022;22(1). https://doi.org/10.1186/S12913-022-08140-W.

  45. Physical Therapy Workforce Data | APTA. https://www.apta.org/your-career/careers-in-physical-therapy/workforce-data. Accessed 2 Feb 2023.

Download references

Acknowledgements

We thank the participants for their time and willingness to share their lived experience. We thank Marie Kenny and Hope Salameh for their assistance in taking field notes during qualitative interviews. We thank Drs. Jennifer Stevens-Lapsley, Kenneth A. Taylor, Laura Swink, Jason Sharpe, Alison Cogan, and Megan Gately for their assistance in expanding recruitment.

Funding

This work was funded by the Minneapolis Veterans Affairs Center of Innovation, Center for Care Delivery and Outcomes Research (CIN 13–406) Pilot Grant. This work was partially funded by the Agency for Healthcare Research and Quality (AHRQ) and Patient-Centered Outcomes Research Institute (PCORI), grant K12HS026379. Dr. Miller is supported by the National Institutes of Health (KL2TR001870). The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States Government, AHRQ, PCORI, or Minnesota Learning Health System Mentored Career Development Program (MN-LHS).

Author information

Authors and Affiliations

Authors

Contributions

JPW provided training on qualitative interviewing techniques. Interviews were conducted by authors AMG, NB, and HJH. Data was analyzed and themes were developed by AMG, MJM, JPW, and EMH. The manuscript was drafted by AMG and critically reviewed by REB. All authors reviewed the manuscript and suggested revisions prior to submission.

Corresponding author

Correspondence to Allison M. Gustavson.

Ethics declarations

Ethics approval and consent to participate

This study involves human participants. As such, all methods were carried out in accordance with relevant guidelines and regulations outlined in the Declaration of Helsinki. This research study received ethical approval by the Minneapolis Veterans Affairs Health Care System’s Institutional Review Board (#1652969) and obtained informed consent from all participants. No minors were recruited or enrolled for participation. Personally identifiable information has been removed to ensure participant privacy.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

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

Supplementary Information

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/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gustavson, A.M., Miller, M.J., Boening, N. et al. Identifying factors influencing emerging innovations in hospital discharge decision making in response to system stress: a qualitative study. BMC Health Serv Res 24, 1293 (2024). https://doi.org/10.1186/s12913-024-11784-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12913-024-11784-5

Keywords