https://orcid.org/0009-0002-8078-8186
Figures
Abstract
Background
Hospital pre-discharge interventions are becoming one of the leading strategies to promote early discharge. For older adult patients, it remains unclear what these interventions are and how they affect discharge outcomes.
Objective
This scoping review categorizes pre-discharge interventions promoting early acute care hospital discharging or total hospital length of stay reductions among older adults, synthesizes contextual factors (e.g., cost, staffing) driving implementation, and assesses the perceived intervention’s impact.
Design
The review followed the five states of the Arksey and O’Malley framework and the PRISMA-ScR extension. The PubMed, Embase, and Scopus databases were searched from 1983 to 2020 for pre-discharge interventions designed or adapted to discharge older adults earlier in their stay from acute care hospitals. Potentially relevant articles were screened against eligibility criteria. Findings were extracted and collated in data charting forms followed by brief thematic analyses.
Results
The search yielded 5,455 articles of which 91 articles were included. Eight pre-discharge intervention categories were identified: clinical management, diagnostic/risk assessment tools, staffing enhancements, drug administration, length of stay protocols, nutrition planning, and communication improvements. Leading motivations for intervention implementation included the nationwide drive to reduce care costs and hospitals’ need to increase hospital profitability, improve quality of care, or optimize resource utilization. Discharge outcomes reported included hospitalization costs, readmission rates, mortality rates, resource utilization rates and costs, and length of stay. Mixed results were found regarding the effectiveness of early discharge interventions on discharge outcomes based on expressed author sentiment.
Conclusions
The drive for pre-discharge interventions that reduce older adult hospital stays and associated costs continues to stem primarily from economic and governmental policies. Follow-up studies may be required to emphasize patient perspectives and care trajectories to avoid unintentional costly and health-deteriorating consequences.
Citation: Garcia E, Hass ZJ (2025) Characterizing pre-discharge interventions to reduce length of stay for older adults: A scoping review. PLoS ONE 20(2): e0318233. https://doi.org/10.1371/journal.pone.0318233
Editor: Vineet Gupta, University of California San Diego, UNITED STATES OF AMERICA
Received: August 3, 2024; Accepted: January 14, 2025; Published: February 10, 2025
Copyright: © 2025 Garcia, Hass. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: EG received a National Science Foundation (NSF) Graduate Research Fellowships Program (GRFP) fellowship. The website is https://nsfgrfp.org/applicants/statements/#:~:text=The%20maximum%20length%20of%20the,is%20three%20(3)%20pages.&text=The%20Graduate%20Research%20Plan%2 0Statement,Intellectual%20Merit%20and%20Broader%20Impacts. The NSF GRFP fellowship did not play a role in the study design, data collection nor any preparation of the manuscript. EG also received a Purdue Doctoral Fellowship whose website is https://education.purdue.edu/graduate-students/graduate-funding/fellowshipsscholarships/ but there is no grant number available. The Purdue Doctoral Fellowship also did not play any role in the study design, data collection nor analysis nor preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
The 1983 establishment of the Prospective Payment System (PPS) by the Centers for Medicare and Medicaid Services (CMS) spurred a nationwide effort to promote cost-efficient hospital management to curb rapidly increasing care costs [1–7]. Hospitals became motivated to discharge patients sooner, nearing the lower length of stay (LOS) range permitted by PPS, to reduce resource utilization and maximize revenue [8–14]. PPS offered hospitals a fixed price for diagnosis-related care, enabling hospitals to generate net revenue from hospitalizations with lower care costs than the PPS reimbursed for [15].
Within the first three years of the PPS, average national hospital LOS decreased by 25%. For older adults undergoing surgical procedures the mean LOS decrease from 21.9 days to 12.6 days [9, 11, 16]. Hospitals also increased patient referrals to post-acute care services from 38% to 60%, shifting recovery care locations to nursing homes and other settings. This improved bed turn-over rates, optimized hospital resource usage, and secured shorter patient stay rewards from some insurance payers, enabling another source of hospital revenue [8, 13, 14, 16, 17].
However, the financial incentive to decrease unnecessary care services may cause hospitals to choose the least expensive or minimal number of care procedures, raising concerns over reduced patient care quality. Retrospective studies identified that older adult inpatients have suffered a significantly higher rate of poor care quality correlating to LOS reductions, suggesting that curbing healthcare costs has had unintended negative consequences [18]. Researchers have also identified increases in negative post-discharge outcomes such as hospital readmissions, mortality, and health deterioration [11, 12, 16, 17, 19–21]. Kosecoff et al. (1990) found that the proportion of patients discharged home in unstable conditions increased from 10% before the PPS (1981–1982) to 15% shortly afterward (1985–1986) [5]. This gave rise to the term “quicker and sicker” referring to the trend of hospital patients discharging sooner than the average LOS for their respective diagnosis while less stable than was previously customary [22–26]. From a patient perspective, reductions in LOS have generated feelings of pressure to leave the hospital with suboptimal care, diagnostic errors, poor communication and information exchange [1, 2, 8].
Currently, early discharges are attributed to additional causes besides economic and policy pressures. Enhanced recovery programs, early mobility programs, and discharge planning strategies have been developed to reduce hospital LOS. Literature reviews on hospital interventions driving early discharges or reduced LOS and their impact on patient outcomes and hospitalization costs remains limited. Coffey et al. (2019) and Siddique et al. (2020) are presently the only two systematic reviews on early discharge interventions [27, 28]. Neither systematic review focuses on pre-discharge interventions (interventions occurring before the discharge planning stage) associated with acute care hospital early discharging. Additionally, no single review on pre-discharge interventions targets explicitly older adults, a high-risk population for hospital readmissions, mortality, and health deterioration due to hospitalization.
In this paper, we review acute care pre-discharge interventions promoting or indirectly influencing early discharging of older adult patients. We also synthesize contextual factors driving their development and implementation and assess author sentiment on the perceived intervention’s impact.
Research questions
The research questions guiding this scoping review were:
- What type of pre-discharge interventions were developed and implemented to promote or indirectly drive early discharge or decreases in LOS of older adult patients in hospitals?
- What motivates the development and implementation of these interventions?
- What is the author’s sentiment regarding the impact of these interventions?
Materials and methods
This scoping review was guided by the Arksey and O’Malley five-stage framework [29]. This methodology summarizes the available evidence on a topic, mapping the existing literature in a field of interest to convey its breadth and depth, including the volume, nature, and characteristics of primary research, while also identifying gaps. Following the methodology of scoping reviews, we did not formally evaluate the studies’ quality.
We disclose that this scoping review’s protocol was not pre-registered due to the inherent methodological flexibility inherent to this research design. Scoping reviews are exploratory in nature, often requiring iterative refinement of the research question and search strategy, which makes advance registration challenging. Nonetheless, to ensure rigor and transparency, we adhered to established methodological frameworks, following best practices recommended by Arksey and O’Malley, as previously mentioned. This approach maintained scientific integrity throughout the review process.
The review included the following key stages: (1) identifying the research question; (2) identifying relevant studies; (3) selecting relevant search studies; (4) charting the data and (5) collating, summarizing, and reporting results. We also applied the checklist for the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) to ensure a comprehensive and systematic approach (see S1 Checklist in Supporting Information) [30]. However, the review protocol was not registered in a publicly accessible database prior to the commencement of the review.
Search strategy
Articles in PubMed, Scopus, and Embase, published from 1983 to September 2020, were retrieved using the following keywords: early discharge, reduced length of stay, pre-discharge intervention, acute care, hospitalization, and older adults. The age criteria for ‘older adults’ were defined by the articles themselves. Exclusion keywords that were added to refine the search strategy in PubMed included: telephone, telemedicine, labor, mother, early follow-up, mental health, psychiatric, delayed discharge, and follow-up. The start date of 1983 was selected to identify pre-discharge hospital interventions developed and implemented after the PPS establishment. The end date was selected to create a buffer period that would ensure studies were not influenced by the COVID-19 pandemic, which had a significant impact on hospital management and care delivery [31]. To further support this approach, the specific search strategies for each database are provided in S1 Appendix.
Selection criteria
Inclusion and exclusion criteria were refined after the initial article pull. Articles were eligible if they reported on early discharge, premature discharge, or reduced LOS associated with any type of intervention developed and implemented before the discharge planning phase among older adults in U.S. acute hospitals and were published in English. Our interest was in studying the U.S. healthcare system. There was no additional restriction on study design, hospital diagnosis, or patient characteristics. Exclusion criteria included articles focusing on surgical interventions emphasizing procedural innovations rather than hospital care management improvement efforts. Interventions related to hospital transfers were excluded, as they do not represent overall early discharge from acute care. Additionally, interventions for patients with psychiatric conditions were excluded, as physical and mental health acute care stays are fundamentally distinct. Articles concerning follow-up care, hospice care, advance care planning, discharging against medical advice, or telehealth/telemedicine were also excluded.
Selection process
Studies were selected through a two-step process. First, abstracts were collated in Rayyan, a collaborative free web and mobile app tool, where both reviewers independently screened titles and abstracts [32]. Then, potentially eligible articles were assessed at the full-text level by both reviewers. Studies without accessible full-texts, those behind paywalls, or those not discussing hospital-driven interventions were excluded, with reasons for exclusion noted. Any discrepancies between reviewers were resolved through discussion.
Data charting
We developed a data dictionary detailing information to collect, for consistency between reviewers throughout charting. Each reviewer extracted key data elements, including authors, publication year, study design, intervention description and motivation, targeted population, cohort size (if applicable), measured study outcomes, and authors’ sentiment and reasoning regarding early discharge. To enhance understanding of the study population and the intervention’s effect size, a single reviewer extracted additional data elements, including gender distribution (if available), average age (if available), and quantitative outcome results, as this task was deemed manageable for a single reviewer. One of the two reviewers checked the data extracted for consistency throughout the charting process. The quality of the extracted data was not appraised, as this was out of the scope of our review’s objectives.
Author sentiment
Early discharge sentiment was defined on a scale of positive, negative, and neutral. Positive early discharge sentiment indicated cost reductions, improvements in patient outcomes, or similar measurements being highlighted by the author. Negative sentiment derived from increased costs, increased patient adverse outcomes, or similar measurements being mentioned. Neutral sentiment reflected a mix of positive and negative outcomes outlined by the author.
Data analysis and synthesis
We conducted a thematic analysis of extracted data frequencies to identify predominant categories of pre-discharge interventions. Next, we conducted a content analysis using extracted data to synthesize contextual factors motivating the development and implementation of pre-discharge interventions for early discharge of older adults. Author sentiment was also assessed via content analysis. Finally, reviewers met as needed to discuss key findings.
Results
The database searches yielded a total of 5,455 abstracts (Fig 1): 5,084 from PubMed, 247 from Embase, and 124 from Scopus. After removing duplicates, 5,417 abstracts were screened, resulting in 148 articles identified for full-text screening. Of these, 91 articles met our selection criteria and were included in our review. We report characteristics of included studies (Table 1), followed by a classification of identified pre-discharge interventions and an analysis of author sentiment regarding intervention outcomes.
Characteristics of included studies
Our sample included 91 primary research articles. Charted characteristics of the included articles are displayed in Table 1 (see S1 Table for detailed charted characteristics of the study populations), while S2 Table presents the charted measured outcomes and quantitative results of the interventions. The dominant study design observed was pre-post studies (n = 24), followed by cohort-based studies (n = 19), analysis-based studies (n = 13), randomized controlled trials (n = 8), cohort vs. control studies (n = 8), comparison-based studies (n = 6), correlational studies (n = 3), and observational studies (n = 3). The remainder varied among training and validation, cross-sectional, quasi-experimental, basic stepped wedge, investigation, nonrandomized, and quality improvement project-based studies (n = 1, respectively). The distribution of articles per publication year is illustrated in Fig 2. Over half of the research studies (n = 56/92) were published in the last 10 years of the search period.
The most common patient populations targeted were those with heart diseases or undergoing heart surgery procedures and treatments (n = 32) and those with respiratory diseases or community acquired pulmonary infections (n = 19), including pneumonia and chronic obstructive pulmonary disease (COPD). Some studies targeted older adults of different ages (n = 16) or patients with hip or knee joint fractures (n = 8). The remaining studies focused on patients during their post-surgery recovery (n = 4), undergoing radiology procedures (n = 2), with gastrointestinal diseases (n = 2), specifically being in the emergency department (ED) (n = 2), treated with routine specific medication treatment (n = 2), diabetes mellitus (n = 1), brain injuries (n = 1), or envenomization (n = 1). Patient sample sizes varied from 23 patients to 1,471,295 patients [33, 34].
Classification of interventions
We identified eight categories to classify pre-discharge interventions: clinical management, diagnostic/risk assessment tools, staffing enhancements, drug administration, LOS protocols, nutrition planning, and communication improvements. For each category, we provide a definition and examples.
Clinical management
Of the 87 distinct pre-discharge interventions identified among the 91 primary studies included in this scoping review, 30 (34%) were classified under the category of clinical management [33, 35–63]. This category includes pre-discharge interventions involving the development and implementation of clinical practice guidelines, pathways, programs, care standardizations, or care units for specific patient populations. For example, Collier (1995) conducted a 3.5-year cohort study to determine the effects of a clinical pathway for patients undergoing elective carotid endarterectomy, which provided patient education and early discharge in the first postoperative day [36]. Gross (1995) conducted a prospective analysis of patient interviews and medical records to determine the safety and efficacy of early extubation as a redesigned perioperative management approach for cardiovascular surgical patients [37]. Bachman et al. (1987) analyzed an implemented geriatric acute care model with specialized discharge planning initiated upon admission, which included care team conferences with patients’ families [35]. Reddy et al. (2001) compared the impact of using the new community-acquired pneumonia (CAP) clinical practice guideline against the care provided to patients via the hospitalist system used by the University of California San Francisco Medical Center since 1995 [43].
In more recent investigations, Soto et al. (2018) developed HEART TRACKS—a structured transitional care pathway for patients presenting with cardiac-related complaints—to improve care-coordination for appropriate testing and follow-up appointments with a cardiologist after an ED visit [61]. Weems et al. (2019) performed a pre-post analysis of clinical practice, patient outcomes, and costs to determine if standardizing care provided by hospitalists for heart failure and pneumonia patients at Novant Health reduced intrafacility care variation [62]. Shilian et al. (2020) conducted a retrospective investigation at two Ohio osteopathic community hospitals on the use of daily integrated care conferences (ICCs) meant to improve care coordination of COPD patients [63].
Diagnostic/risk assessment tools
Diagnostic protocols, screening tools, risk assessments, triage system adjustments, risk stratifying tools, and risk scoring algorithms defined the category of diagnostic/risk assessment tools, which consisted of 22 (25%) different interventions identified in this review [64–89]. Four distinct studies discussed the same intervention, the HEART Pathway [74, 82, 85, 87], and two others discussed the Early Screen for Discharge Planning (ESDP) risk stratifying tool [71, 80]. We found that these tools were available either as fillable hand sheets and computerized software or interfaces. This category was predominantly associated more with publications from 2001–2020. The only pre-2000s intervention in this category is of Hay et al., 1997 where a retrospectively validated scoring system using four independent variables (hemodynamics, time from bleeding, comorbidity, and esophagogastroduodenoscopy (EGD)) was used to predict risk of adverse events and identify patients potentially suitable for early hospital discharge [64].
Interventions developed and implemented at the beginning of the 21st century mainly focused on improving the discharge planning process and reducing discharge delays that may contribute to longer LOS. In 2001, Hou et al., studied the usage of clinical assessments to identify patients who may benefit from a social worker’s help to expedite the discharge planning process and reduce the overall hospitalization LOS of patients [65]. Similarly, Holland et al., in 2003 used a Probability of Repeated Admission (PRA) screening tool to identify patients that would incur a nontypical discharge process by requiring a new referral for services, to improve their discharge planning. In 2013, Holland et al., also created and applied a distinctive early screen for discharge planning (ESDP) risk stratifying tool to aid in the decision making of hospital discharging and identification of patients that would need or require more time allocated to the discharge planning phase [71]. The ESDP risk stratifying tool was later on integrated at a regional hospital to verify that it performed as expected even with a different population and setting in 2017 [80].
Remarkably, fourteen different studies targeted patients with chest pain and cardiovascular conditions such as acute myocardial infarctions (AMI) [67, 70, 72, 74–79, 82, 84–87]. In 2003, Kontos et al., determined the cost-effectiveness of a comprehensive, risk-based triage system that used early myocardial perfusion imaging (MPI) [67]. Shah et al.’s 2012 study examined the impact of using the Thrombolysis in Myocardial Infarction (TIMI) risk stratification scoring model in chest pain observation units (CPOUs) of EDs among patients admitted [70]. Mahler et al. (2015) developed and tested a 2-hour accelerated diagnostic protocol (ADP) to help identify chest pain patients for early discharge [75]. Another example of an ADP for chest pain patients is the emergency department assessment of chest pain score accelerated diagnostic protocol (EDACS-ADP) created by Stopyra et al. (2015) to improve risk stratification of patients [77]. Only two other studies focused on a patient population besides those with chest pain cardiovascular conditions. Specifically Meneghini et al. (2017) and Rozell et al. (2017) calculated and assessed the risk score for potential complications in post-arthroplasty patients using risk assessment algorithms [81, 83].
Rather than focusing on specific patient populations, several studies concentrated on developing risk assessments for various health concerns. These assessments aimed to measure the potential risk of a patients incurring malnutrition [69], developing delirium [73], or using certain drugs [89]. Notably, some risk assessment interventions, such as the HEART Pathway [75], the Controlled Abciximab and Device Investigation to Lower Late Angioplasty Complications (CADILLAC) risk score [84], and the Zwolle Risk Score (ZRS) [86], were developed to serve dual purposes:
- Evaluate the likelihood of complications and adverse events in their respective patient populations.
- Use the risk scores as proxies for early discharge.
In all three cases, this dual functionality of the risk assessment tools is a key feature that distinguishes them from others and enables clinicians to make decisions regarding patient disposition and resource allocation. This dual functionality also underscores the value of these risk assessment tools in enhancing clinical decision-making and optimizing patient care pathways.
Hospital staffing enhancements
Thirteen (15%) interventions in this category involved changes in hospital staffing [90–102]. These included increased employment of hospitalists, dedicated use of nurse practitioners or hospitalists, improved access to a specialist/physician, additional use of social workers for specific care management, incorporation of new care roles or multidisciplinary care teams, and extensions of medical service times in hospitals. The earliest published intervention in this category was in 1994 by Naughton et al., who assigned a geriatrician and social worker as the primary management team for the care of older adult patients, reducing LOS by 2.1 days [90]. Similarly, Southern et al. (2007) evaluated the impact of a new hospitalist model of care for inpatients requiring complex discharge planning and close monitoring. This model assigned patients to hospitalists rather than traditional attending physicians, aiming to minimize subspecialist consultations and coordinate timely discharge plans [95]. A more recent example of having dedicated hospital staffing is the 2016 study by Zhu et al., which examined studied the effectiveness of using a nurse practitioner (NP)-run unit for evaluating patients with chest pain. The intervention proved effective, increasing the use of diagnostic testing and reduced LOS by an average of 2.7 days [97].
More recent studies published in 2020 focused on the usage of multidisciplinary care teams. Melamed et al. (2020) evaluated the use of a multidisciplinary pulmonary embolism response team (PERT) and a consensus-based treatment algorithm (TA) [100]. The TA was designed to guide the PERT in selecting and discussing a single treatment per patient, based on existing guidelines, current publications, and the treatment center’s expertise and resources [100]. Peralta et al. assessed the implementation of a care delivery redesign (CDR) multidisciplinary team [101]. This team included the Chief of Vascular Surgery, an inpatient NP, a dedicated case manager, a clinical documentation improvement specialist, and vascular surgery residents and faculty. The NP facilitated patient care coordination, resident system-based education, and multidisciplinary collaboration. Similarly, Perry et al. studied the impact of a dedicated multiprofessional acute trauma health care (mPATH) team on the LOS of patients with severe traumatic brain and spinal cord injuries [102]. The mPATH team comprised of a physical, occupation, speech, and respiratory therapists, a nurse navigator, a social worker, an advance care provider, and a physician.
Drug administration
Pharmaceutical-related interventions also played a significant role in reducing hospital LOS, accounting for 10% (9) of the interventions reviewed [103–111]. This category encompasses a range of strategies, including the use of alternative drug treatments, changes in medication timing, revisions to drug treatment approval processes, and implementation of therapeutic drug monitoring (TDM) programs.
The earliest published interventions in this category relate to TDM programs. Horn et al. (1985) focused on a pharmacist-led pharmacokinetic monitoring service (PKS) for digoxin, a medication with a narrow therapeutic index, to improve patient dosing and lead to shorter hospital stays [103]. Similarly, Crist et al. (1987) implemented a TDM program for aminoglycoside antibiotics to assess its impact on total dose administered and reduce hospitalization costs [104]. Building on these approaches, Mansouri et al. (2011) later introduced an antibiotic restriction program (ARP) intervention. While sharing the goal of optimizing pharmaceutical use, the ARP focused more on regulating the prescription of antibiotics for CAP by enforcing approval prior to the dispensing of any restricted antibiotics such as piperacillin/tazobactam, cefepime, and ertapenem [108].
LOS protocols
Six interventions (7%) in this category focused exclusively on hospital policies mandating patient LOS to be reduced by at least one day [34, 112–116]. Ni et al., (1999) demonstrated that for patients with congestive heart failure, hospital policies and management strategies significantly shortened LOS. This reduction was accompanied by an increase in discharges to skilled nursing facilities (SNFs) and home health services, ensuring continued post-discharge care [112]. Similarly, Kozma et al. (2010) implemented a 1-day reduction policy for patients with CAP, aiming to achieve economic benefits in response to healthcare reforms targeting reduced hospital expenditures [34].
Nutrition planning
This category encompassed specialized nutrition programs, alternative methods for delivering nutrition, and oral nutritional supplements, accounting for four interventions (5%) [117–120]. Nyswonger and Helmchen (1992) focused on the use of enteral nutrition or tube feeding [117]. More recent studies, such as those by Snider et al. (2015) and Babb and Rohrer (2017) examined the effects of oral nutrition supplementation among patients with COPD and heart failure patients [119, 120].
Communication improvements
Interventions aimed at improving communication between healthcare providers, between providers and their patients, or between a hospital and other post-acute care services comprised this category, which included three (3%) interventions [121–123]. An example is the study by Horowitz and Chassin (2002), which enforced provider education on antibiotics to enhance patient knowledge and reduce antibiotic usage in the treatment of pneumonia [122]. These interventions highlight the importance of effective communication in optimizing patient care.
Intervention drivers
Motivations driving the development and implementation of each intervention can be found in Table 1. Common motivations included the need to reduce healthcare costs or increase hospital profitability, either directly or through resource optimization (n = 35), improve, standardize, or validate care protocols or tools (n = 35), and decrease LOS (n = 32). Other common motivational drivers included the desire to reduce mortality (n = 5), hospital readmissions (n = 4), or post-procedural complications (n = 2).
Author sentiment on reported outcomes
Frequently measured outcomes to evaluate the intervention’s effectiveness or efficiency included patient LOS (n = 72), hospital readmissions over varying time frames (n = 31), hospitalization costs (n = 26), mortality (n = 22), post procedural adverse events or complications (n = 20), and discharge destination or disposition to a specific post-acute care facility (n = 20) (S2 Table). Additional measures included quality of care, time to treatment, physician adherence to risk assessment tool, care service utilization. Notably, only two studies measured patient satisfaction while one determined physician satisfaction.
Author sentiment regarding the impact of early discharge interventions was generally positive (53%, n = 48). For instance, Crist et al. (1987) viewed the implementation of a therapeutic drug-monitoring program favorably, noting reductions in unnecessary additional drug therapy among patients [104]. Hay et al. (1997) demonstrated the efficacy of a risk stratification scoring system for UGIH, which safely reduced hospital LOS for selected low-risk patients. Their study was pioneering in considering the efficacy, safety, and acceptability of implementing a UGIH LOS guideline [64]. In more recent years, Ahmed et al. (2018) highlighted how providing non-emergency radiology services on the weekends helped reduce patient LOS and unnecessary hospital admissions [98]. Similarly, Rodriguez-Arajo et al. (2018) reported that a same-day discharge policy was cost-savings effective with no difference in readmission or mortality rates [114].
Neutral author sentiment (mixed outcomes) was noted in 43% of interventions (n = 39). For instance, Lee et al. (1999) regarded that the intervention of early extubating along with the fast-track treatment protocol in elderly patients was safe and feasible but only in 34% of the older population [40]. Mahler et al. (2015) observed that the usage of ADPs for chest pain was associated with no major adverse cardiac events within 30 days but due to intervention nonadherence, safe early discharge decreased by 13% [75].
Negative author sentiment was described in the remaining 4% of interventions (n = 4). The study of Collier (1995) describes that complications and admissions to the ICU were observed because of the new clinical care pathway which in turn increased patients’ LOS and costs [36]. More recently, Ansari et al. (2018) observed that a strict hospital policy to reduce patient LOS among hospitalized neurosurgical patients was associated with an increased readmission rate, increasing care costs for patients and reimbursement penalties for the hospital [113].
Discussion
In this scoping review, we analyzed 91 articles published between 1985 and 2020 that focused on pre-discharge interventions aiming at decreasing LOS among older adults in acute care settings. Our findings suggest that pre-discharge hospital interventions are increasingly used to promote early hospital discharge of older adults in acute care older settings in the US under the PPS. Furthermore, our literature synthesis builds on previous reviews of early discharge interventions by providing a broader understanding of intervention characteristics and author sentiment regarding their impact.
To address the type of interventions that exist, we identified eight different categories of pre-discharge interventions, expanding both in number and scope those identified in previous reviews. Unlike Coffey et al. (2019) and Siddique et al. (2021), our scoping review exclusively focused on interventions developed for and implemented in older adults from the time of admission to an acute care setting up to the discharge planning phase [27, 28]. By concentrating on older adults, we aim to understand the impact of interventions on a commonly hospitalized at-risk population, characterized by a wide range of cognitive and functional health states. This targeted approach provides valuable insights for enhancing care, especially considering the projected increase in the US older adult population to 94.7 million by 2060 [124]. Focusing on interventions before the discharge planning phase allows us to compare and analyze the effects experienced by patients resulting from the modified care they receive within a hospital. Additionally, this approach also enables us to evaluate hospital resource utilization for cost-analysis purposes.
It is worth noting that clinical management changes, particularly quality-improvement initiatives, were the most commonly observed category, a finding also emphasized by Coffey et al. (2019) [27]. Our review also identified the use of diagnostic and risk assessment tools as a growing type of pre-discharge intervention. These tools, broadly known as computerized clinical decision support systems (CDSSs), help provide healthcare professionals with valuable information to aid in patient care. Technological advancements, including the use of electronic medical records and advanced computerized healthcare algorithms, have significantly contributed to the prevalence and widespread adoption of CDSSs [125]. In fact, with the ongoing innovations in artificial intelligence, the CDSS market is expected to grow from $1.3 to $2.2 billion USD in the next 3–5 years [126].
Our findings also revealed that most of the pre-discharge interventions were developed and implemented with three primary goals: to benefit hospitals financially, improve the quality of care provided, and optimize resource utilization. Additional motivators included population health management and regulatory compliance. While these interventions were primarily designed from the hospital’s perspective, they inevitably impact patient care delivery. Notably, only two distinct interventions mentioned patient education as an area needing improvement. This observation highlights a significant gap in prioritizing patient interests in the development and implementation of pre-discharge interventions for early discharge.
While most authors expressed positive sentiment, a significant portion (45%) of the studies reported mixed or negative views on intervention outcomes. This diversity in author sentiment may be attributed to the lack of consistent metrics and inadequate post-development follow-up, which are crucial for evaluating the continuous efficacy and reliability of pre-discharge interventions before widespread adoption. Remarkably, most studies prioritized hospital-centered outcomes, often overlooking patient-centered outcomes—an increasingly important consideration in healthcare evaluation.
As we transition towards a value-based healthcare system focused on whole-person care and patient outcomes, this review underscores the need for further research into how pre-discharge interventions, particularly those utilizing automated decision-making through CDSS, impact the most crucial stakeholder: the patient. Incorporating a patient-centered focus is vital to assess whether early discharge, facilitated by these interventions, poses additional risks to vulnerable, socioeconomically disadvantaged patient groups. These groups already face challenges such as increased mortality and readmission risk, limited access to post-discharge care, and emotional and physical challenges stemming from anxiety about managing their health without adequate support [127, 128].
Balancing hospital and patient interests in the development phase to create consistent guidelines for measuring intervention impact will be essential. Furthermore, advances in patient-centered outcomes research (PCOR) and intervention evaluation can enhance adoption across acute care settings, ensuring that the benefits of early discharge are realized without compromising patient care quality or safety.
Limitations
We acknowledge that several articles on pre-discharge interventions have been published since 2020, although those we are aware of are not yet in the testing or evaluation phase. Additionally, pre-discharge intervention articles from other database sources may differ in the distribution of early discharge sentiment found in this review. In addition, it is important to emphasize that early discharge sentiment was derived from the positivity or negativity of outcomes described in the articles by their authors; it may be that longer follow-up evaluation of post-discharge patient outcomes could alter the sentiment.
Conclusions
This review highlights new pre-discharge interventions promoting early discharge of hospitalized older adults continue to be driven by economic and governmental policies. Evaluation of these interventions post-development primarily reflects the hospital perspective. Incorporating the patient perspective in both the development and evaluation of pre-discharge interventions may help hospitals achieve better patient-centered care delivery.
Supporting information
S1 Checklist. Preferred Reporting Items for Systemic reviews and Meta-Analyses extensions for Scoping Reviews (PRISMA-ScR) checklist.
https://doi.org/10.1371/journal.pone.0318233.s001
(PDF)
S1 Appendix. Specific search strategies for PubMed, Embase, and Scopus databases.
https://doi.org/10.1371/journal.pone.0318233.s002
(DOCX)
S1 Table. Demographic characteristics of study populations in included articles.
https://doi.org/10.1371/journal.pone.0318233.s003
(DOCX)
S2 Table. Measured outcomes and quantitative outcomes of included articles.
https://doi.org/10.1371/journal.pone.0318233.s004
(DOCX)
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