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The Continued Quest for Pediatric Readmission Risk Prediction
While the use of pediatric readmission rates as a quality metric remains controversial, pediatric hospital-to-home transitions need improvement.1 As many as a third of pediatric readmissions are preventable,2 but the multifactorial and complex nature of factors that contribute to pediatric readmissions presents a challenge in tackling readmission. Several factors are associated with increased risk of readmission; these factors include both clinical and sociodemographic characteristics;3 however, we still have much to learn. Further, the only large trial of an intervention to prevent pediatric readmissions across all comers (nontargeted) was unsuccessful in decreasing reutilization.4 By contrast, various studies have succeeded in reducing readmission and/or emergency department revisit rates associated with inpatient interventions in select populations.5 Currently, however, no standardized or validated pediatric risk prediction tool can reliably identify the high-risk patients who may benefit from interventions. In the Journal of Hospital Medicine, Brittan and colleagues add to the literature base exploring the factors associated with an increased 30-day readmission risk by trialing an electronic health record (EHR)-based tool composed of three components: presence of home health, polypharmacy in the form of ≥6 medications, and presence of a caregiver who prefers a language other than English.6
This brief report contributes significantly to the literature. First, the presence of a tool embedded within the pediatric EHR and readily accessible at the point of clinical care is novel. Study authors purposefully chose components easily extractable from the EHR which update automatically. This infrastructure generates an automated score that is easily accessible to clinicians in real-time. Second, the transparency of the tool is notable given its display via the EHR’s “Discharge Readiness Report,” where a clinician can view not only the total composite score (1 point for each component) but also the specific components for which a point was allocated. Although a composite score in and of itself is potentially helpful, understanding specific factors that contribute to a patient’s increased risk of readmission allows for better targeting of interventions. For example, in Brittan’s simple, three-component model, the presence of polypharmacy might trigger a pharmacist to meet with the family prior to discharge to discuss indications for and how to properly administer medications. Finally, a multidisciplinary team composed of clinicians, nurse-family educators, case managers, social workers, and informatics experts developed and implemented this tool. Although the roll-out and longitudinal use of this tool is not described, the engagement of these multiple provider-types is likely to increase successful roll-out and utilization of the tool.
Unfortunately, the utility of this tool in predicting readmission is limited as evidenced by its low c-statistic. This limitation may be due to several reasons. The tool was not originally built as a tool to predict readmissions but rather an instrument to identify complex discharge care as part of a quality improvement initiative to improve discharge processes. Given the questions about readmission risk prediction, the authors explored the potential for the tool to predict readmission risk. The authors acknowledge that the tool excluded many known readmission risk factors based upon inconsistent documentation within the EHR and the desire to emphasize only modifiable factors. Thus, variables, including prior hospitalization which is a well-documented risk factor for readmissions (but not modifiable) and social determinants of health (which are not consistently documented), were excluded. Additionally, the included variable of “language preference” may have been a considerably broad characteristic. Limited English proficiency has been increasingly recognized as a construct placing patients at higher risk for adverse outcomes. However, caregivers with high English proficiency also exhibit varying degrees of health literacy. The inclusion of health literacy may be additive to a readmission risk prediction tool. Finally, the outcome is not well-described with regard to identification of “unplanned” events. Thus, their outcome measure may have included planned admissions for which the readmission risk prediction tool would be irrelevant.
In summary, Brittan and colleagues engaged a multidisciplinary group of providers to address discharge planning processes and leveraged the EHR to support their efforts in the form of a brief screening tool. Although this tool was not predictive of hospital readmissions, it highlights the opportunity to better utilize the EHR to gather meaningful, real-time data and subsequently use this information to positively impact our clinical care and allocation of resources. The tool should serve as a stepping stone to building a more extensive tool with inclusion of other known and potential readmission risk factors, thus resulting in a clinically relevant readmission risk prediction tool.
The authors have nothing to disclose.
1. Solan LG, Beck AF, Brunswick SA, et al. The family perspective on hospital to home transitions: a qualitative study. Pediatrics 2015;136(6):e1539-1549. doi: 10.1542/peds.2015-2098. PubMed
2. Toomey SL, Peltz A, Loren S, et al. Potentially preventable 30-Day hospital readmissions at a children’s hospital. Pediatrics. 2016;138(2). doi: 10.1542/peds.2015-4182. PubMed
3. Berry JG, Hall DE, Kuo DZ, et al. Hospital utilization and characteristics of patients experiencing recurrent readmissions within children’s hospitals. JAMA. 2011;305(7):682-690. doi: 10.1001/jama.2011.122. PubMed
4. Auger KA, Simmons JM, Tubbs-Cooley H, et al. Hospital to home outcomes (H2O) randomized trial of a post-discharge nurse home visit. Pediatrics. In press. PubMed
5. Auger KA, Kenyon CC, Feudtner C, Davis MM. Pediatric hospital discharge interventions to reduce subsequent utilization: a systematic review. J Hosp Med. 2014;9(4):251-260. doi: 10.1002/jhm.2134. PubMed
6. Brittan MS, Martin SL, Anderson, Moss A,Torok MR. An electronic health record tool designed to improve pediatric hospital discharge has low predictive utility for readmissions [published online ahead of print August 29, 2018]. J Hosp Med. doi: 10.12788/jhm.3043. PubMed
While the use of pediatric readmission rates as a quality metric remains controversial, pediatric hospital-to-home transitions need improvement.1 As many as a third of pediatric readmissions are preventable,2 but the multifactorial and complex nature of factors that contribute to pediatric readmissions presents a challenge in tackling readmission. Several factors are associated with increased risk of readmission; these factors include both clinical and sociodemographic characteristics;3 however, we still have much to learn. Further, the only large trial of an intervention to prevent pediatric readmissions across all comers (nontargeted) was unsuccessful in decreasing reutilization.4 By contrast, various studies have succeeded in reducing readmission and/or emergency department revisit rates associated with inpatient interventions in select populations.5 Currently, however, no standardized or validated pediatric risk prediction tool can reliably identify the high-risk patients who may benefit from interventions. In the Journal of Hospital Medicine, Brittan and colleagues add to the literature base exploring the factors associated with an increased 30-day readmission risk by trialing an electronic health record (EHR)-based tool composed of three components: presence of home health, polypharmacy in the form of ≥6 medications, and presence of a caregiver who prefers a language other than English.6
This brief report contributes significantly to the literature. First, the presence of a tool embedded within the pediatric EHR and readily accessible at the point of clinical care is novel. Study authors purposefully chose components easily extractable from the EHR which update automatically. This infrastructure generates an automated score that is easily accessible to clinicians in real-time. Second, the transparency of the tool is notable given its display via the EHR’s “Discharge Readiness Report,” where a clinician can view not only the total composite score (1 point for each component) but also the specific components for which a point was allocated. Although a composite score in and of itself is potentially helpful, understanding specific factors that contribute to a patient’s increased risk of readmission allows for better targeting of interventions. For example, in Brittan’s simple, three-component model, the presence of polypharmacy might trigger a pharmacist to meet with the family prior to discharge to discuss indications for and how to properly administer medications. Finally, a multidisciplinary team composed of clinicians, nurse-family educators, case managers, social workers, and informatics experts developed and implemented this tool. Although the roll-out and longitudinal use of this tool is not described, the engagement of these multiple provider-types is likely to increase successful roll-out and utilization of the tool.
Unfortunately, the utility of this tool in predicting readmission is limited as evidenced by its low c-statistic. This limitation may be due to several reasons. The tool was not originally built as a tool to predict readmissions but rather an instrument to identify complex discharge care as part of a quality improvement initiative to improve discharge processes. Given the questions about readmission risk prediction, the authors explored the potential for the tool to predict readmission risk. The authors acknowledge that the tool excluded many known readmission risk factors based upon inconsistent documentation within the EHR and the desire to emphasize only modifiable factors. Thus, variables, including prior hospitalization which is a well-documented risk factor for readmissions (but not modifiable) and social determinants of health (which are not consistently documented), were excluded. Additionally, the included variable of “language preference” may have been a considerably broad characteristic. Limited English proficiency has been increasingly recognized as a construct placing patients at higher risk for adverse outcomes. However, caregivers with high English proficiency also exhibit varying degrees of health literacy. The inclusion of health literacy may be additive to a readmission risk prediction tool. Finally, the outcome is not well-described with regard to identification of “unplanned” events. Thus, their outcome measure may have included planned admissions for which the readmission risk prediction tool would be irrelevant.
In summary, Brittan and colleagues engaged a multidisciplinary group of providers to address discharge planning processes and leveraged the EHR to support their efforts in the form of a brief screening tool. Although this tool was not predictive of hospital readmissions, it highlights the opportunity to better utilize the EHR to gather meaningful, real-time data and subsequently use this information to positively impact our clinical care and allocation of resources. The tool should serve as a stepping stone to building a more extensive tool with inclusion of other known and potential readmission risk factors, thus resulting in a clinically relevant readmission risk prediction tool.
The authors have nothing to disclose.
While the use of pediatric readmission rates as a quality metric remains controversial, pediatric hospital-to-home transitions need improvement.1 As many as a third of pediatric readmissions are preventable,2 but the multifactorial and complex nature of factors that contribute to pediatric readmissions presents a challenge in tackling readmission. Several factors are associated with increased risk of readmission; these factors include both clinical and sociodemographic characteristics;3 however, we still have much to learn. Further, the only large trial of an intervention to prevent pediatric readmissions across all comers (nontargeted) was unsuccessful in decreasing reutilization.4 By contrast, various studies have succeeded in reducing readmission and/or emergency department revisit rates associated with inpatient interventions in select populations.5 Currently, however, no standardized or validated pediatric risk prediction tool can reliably identify the high-risk patients who may benefit from interventions. In the Journal of Hospital Medicine, Brittan and colleagues add to the literature base exploring the factors associated with an increased 30-day readmission risk by trialing an electronic health record (EHR)-based tool composed of three components: presence of home health, polypharmacy in the form of ≥6 medications, and presence of a caregiver who prefers a language other than English.6
This brief report contributes significantly to the literature. First, the presence of a tool embedded within the pediatric EHR and readily accessible at the point of clinical care is novel. Study authors purposefully chose components easily extractable from the EHR which update automatically. This infrastructure generates an automated score that is easily accessible to clinicians in real-time. Second, the transparency of the tool is notable given its display via the EHR’s “Discharge Readiness Report,” where a clinician can view not only the total composite score (1 point for each component) but also the specific components for which a point was allocated. Although a composite score in and of itself is potentially helpful, understanding specific factors that contribute to a patient’s increased risk of readmission allows for better targeting of interventions. For example, in Brittan’s simple, three-component model, the presence of polypharmacy might trigger a pharmacist to meet with the family prior to discharge to discuss indications for and how to properly administer medications. Finally, a multidisciplinary team composed of clinicians, nurse-family educators, case managers, social workers, and informatics experts developed and implemented this tool. Although the roll-out and longitudinal use of this tool is not described, the engagement of these multiple provider-types is likely to increase successful roll-out and utilization of the tool.
Unfortunately, the utility of this tool in predicting readmission is limited as evidenced by its low c-statistic. This limitation may be due to several reasons. The tool was not originally built as a tool to predict readmissions but rather an instrument to identify complex discharge care as part of a quality improvement initiative to improve discharge processes. Given the questions about readmission risk prediction, the authors explored the potential for the tool to predict readmission risk. The authors acknowledge that the tool excluded many known readmission risk factors based upon inconsistent documentation within the EHR and the desire to emphasize only modifiable factors. Thus, variables, including prior hospitalization which is a well-documented risk factor for readmissions (but not modifiable) and social determinants of health (which are not consistently documented), were excluded. Additionally, the included variable of “language preference” may have been a considerably broad characteristic. Limited English proficiency has been increasingly recognized as a construct placing patients at higher risk for adverse outcomes. However, caregivers with high English proficiency also exhibit varying degrees of health literacy. The inclusion of health literacy may be additive to a readmission risk prediction tool. Finally, the outcome is not well-described with regard to identification of “unplanned” events. Thus, their outcome measure may have included planned admissions for which the readmission risk prediction tool would be irrelevant.
In summary, Brittan and colleagues engaged a multidisciplinary group of providers to address discharge planning processes and leveraged the EHR to support their efforts in the form of a brief screening tool. Although this tool was not predictive of hospital readmissions, it highlights the opportunity to better utilize the EHR to gather meaningful, real-time data and subsequently use this information to positively impact our clinical care and allocation of resources. The tool should serve as a stepping stone to building a more extensive tool with inclusion of other known and potential readmission risk factors, thus resulting in a clinically relevant readmission risk prediction tool.
The authors have nothing to disclose.
1. Solan LG, Beck AF, Brunswick SA, et al. The family perspective on hospital to home transitions: a qualitative study. Pediatrics 2015;136(6):e1539-1549. doi: 10.1542/peds.2015-2098. PubMed
2. Toomey SL, Peltz A, Loren S, et al. Potentially preventable 30-Day hospital readmissions at a children’s hospital. Pediatrics. 2016;138(2). doi: 10.1542/peds.2015-4182. PubMed
3. Berry JG, Hall DE, Kuo DZ, et al. Hospital utilization and characteristics of patients experiencing recurrent readmissions within children’s hospitals. JAMA. 2011;305(7):682-690. doi: 10.1001/jama.2011.122. PubMed
4. Auger KA, Simmons JM, Tubbs-Cooley H, et al. Hospital to home outcomes (H2O) randomized trial of a post-discharge nurse home visit. Pediatrics. In press. PubMed
5. Auger KA, Kenyon CC, Feudtner C, Davis MM. Pediatric hospital discharge interventions to reduce subsequent utilization: a systematic review. J Hosp Med. 2014;9(4):251-260. doi: 10.1002/jhm.2134. PubMed
6. Brittan MS, Martin SL, Anderson, Moss A,Torok MR. An electronic health record tool designed to improve pediatric hospital discharge has low predictive utility for readmissions [published online ahead of print August 29, 2018]. J Hosp Med. doi: 10.12788/jhm.3043. PubMed
1. Solan LG, Beck AF, Brunswick SA, et al. The family perspective on hospital to home transitions: a qualitative study. Pediatrics 2015;136(6):e1539-1549. doi: 10.1542/peds.2015-2098. PubMed
2. Toomey SL, Peltz A, Loren S, et al. Potentially preventable 30-Day hospital readmissions at a children’s hospital. Pediatrics. 2016;138(2). doi: 10.1542/peds.2015-4182. PubMed
3. Berry JG, Hall DE, Kuo DZ, et al. Hospital utilization and characteristics of patients experiencing recurrent readmissions within children’s hospitals. JAMA. 2011;305(7):682-690. doi: 10.1001/jama.2011.122. PubMed
4. Auger KA, Simmons JM, Tubbs-Cooley H, et al. Hospital to home outcomes (H2O) randomized trial of a post-discharge nurse home visit. Pediatrics. In press. PubMed
5. Auger KA, Kenyon CC, Feudtner C, Davis MM. Pediatric hospital discharge interventions to reduce subsequent utilization: a systematic review. J Hosp Med. 2014;9(4):251-260. doi: 10.1002/jhm.2134. PubMed
6. Brittan MS, Martin SL, Anderson, Moss A,Torok MR. An electronic health record tool designed to improve pediatric hospital discharge has low predictive utility for readmissions [published online ahead of print August 29, 2018]. J Hosp Med. doi: 10.12788/jhm.3043. PubMed
© 2018 Society of Hospital Medicine
Preparing from the Outside Looking In for Safely Transitioning Pediatric Inpatients to Home
The transition of children from hospital to home introduces a unique set of challenges to patients and families who may not be well-versed in the healthcare system. In addition to juggling the stress and worry of a sick child, which can inhibit the ability to understand complicated discharge instructions prior to leaving the hospital,1 caregivers need to navigate the medical system to ensure continued recovery. The responsibility to fill and administer medications, arrange follow up appointments, and determine when to seek care if the child’s condition changes are burdens we as healthcare providers expect caregivers to manage but may underestimate how frequently they are reliably completed.2-4
In this issue of the Journal of Hospital Medicine, the article by Rehm et al.5 adds to the growing body of evidence highlighting challenges that caregivers of children face upon discharge from the hospital. The multicenter, retrospective study of postdischarge encounters for over 12,000 patients discharged from 4 children’s hospitals aimed to evaluate the following: (1) various methods for hospital-initiated postdischarge contact of families, (2) the type and frequency of postdischarge issues, and (3) specific characteristics of pediatric patients most commonly affected by postdischarge issues.
Using standardized questions administered through telephone, text, or e-mail contact, postdischarge issues were identified in 25% of discharges across all hospitals. Notably, there was considerable variation of rates of postdischarge issues among hospitals (from 16% to 62.8%). The hospital with the highest rate of postdischarge issues identified had attending hospitalists calling families after discharge. Thus, postdischarge issues may be most easily identified by providers who are familiar with both the patient and the expected postdischarge care.
Often, postdischarge issues represented events that could be mitigated with intentional planning to better anticipate and address patient and family needs prior to discharge. The vast majority of postdischarge issues identified across all hospitals were related to appointments, accounting for 76.3% of postdischarge issues, which may be attributed to a variety of causes, from inadequate or unclear provider recommendations to difficulty scheduling the appointments. The most common medication postdischarge issue was difficulty filling prescriptions, accounting for 84.8% of the medication issues. “Other” postdischarge issues (12.7%) as reported by caregivers included challenges with understanding discharge instructions and concerns about changes in their child’s clinical status. Forty percent of included patients had a chronic care condition. Older children, patients with more medication classes, shorter length of stay, and neuromuscular chronic care conditions had higher odds of postdischarge issues. Although a high proportion of postdischarge issues suggests a systemic problem addressing the needs of patients and families after hospital discharge, these data likely underestimate the magnitude of the problem; as such, the need for improvement may be higher.
Postdischarge challenges faced by families are not unique to pediatrics. Pediatric and adult medical patients face similar rates of challenges after
Given the prevalence of postdischarge issues after both pediatric and adult hospitalizations, how should hospitalists proceed? Physicians and health systems should explore approaches to better prepare caregivers, perhaps using models akin to the Seamless Transitions and (Re)admissions Network model of enhanced communication, care coordination, and family engagement.10 Pediatric hospitalists can prepare children for discharge long before departure by delivering medications to patients prior to discharge,11,12 providing discharge instructions that are clear and readable,13,14 as well as utilizing admission-discharge teaching nurses,15 inpatient care managers,16,17 and pediatric nurse practitioners18 to aid transition.
While a variety of interventions show promise in securing a successful transition to home from the hospitalist vantage point, a partnership with primary care physicians (PCPs) in our communities is paramount. Though the evidence linking gaps in primary care after discharge and readmission rates remain elusive, effective partnerships with PCPs are important for ensuring discharge plans are carried out, which may ultimately lead to decreased rates of unanticipated adverse outcomes. Several adult studies note that no single intervention is likely to prevent issues after discharge, but interventions should include high-quality communication with and involvement of community partners.9,19,20 In practice, providing a high-quality, reliable handoff can be difficult given competing priorities of busy outpatient clinic schedules and inpatient bed capacity concerns, necessitating efficient discharge practices. Some of these challenges are amenable to quality improvement efforts to improve discharge communication.21 Innovative ideas include collaborating with PCPs earlier in the admission to design the care plan up front, including PCPs in weekly team meetings for patients with chronic care conditions,16,17 and using telehealth to communicate with PCPs.
Ensuring a safe transition to home is our responsibility as hospitalists, but the solutions to doing so reliably require multi-fold interventions that build teams within hospitals, innovative outreach to those patients recently discharged to ensure their well-being and mitigate postdischarge issues and broad community programs—including greater access to primary care—to meet our urgent imperative.
Disclosure
The authors declare no conflicts of interest. Dr. Auger’s research is funded by the Agency for Healthcare Research and Quality (1K08HS024735).
1. Solan LG, Beck AF, Brunswick SA, et al. The Family Perspective on Hospital to Home Transitions: A Qualitative Study. Pediatrics. 2015;136(6):e1539-1549. PubMed
2. Misky GJ, Wald HL, Coleman EA. Post-hospitalization transitions: Examining the effects of timing of primary care provider follow-up. J Hosp Med. 2010;5(7):392-397. PubMed
3. Yin HS, Johnson M, Mendelsohn AL, Abrams MA, Sanders LM, Dreyer BP. The health literacy of parents in the United States: a nationally representative study. Pediatrics. 2009;124 Suppl 3:S289-298. PubMed
4. Glick AF, Farkas JS, Nicholson J, et al. Parental Management of Discharge Instructions: A Systematic Review. Pediatrics. 2017. [Epub ahead of print]. PubMed
5. Rehm KP, Brittan MS, Stephens JR, et al. Issues Identified by Post-Discharge Contact after Pediatric Hospitalization: A Multi-site Study (published online ahead of print February 2, 2018) J Hosp Med. doi: 10.12788/jhm.2934
6. Forster AJ, Murff HJ, Peterson JF, Gandhi TK, Bates DW. The incidence and severity of adverse events affecting patients after discharge from the hospital. Ann Intern Med. 2003;138(3):161-167. PubMed
7. Hansen LO, Greenwald JL, Budnitz T, et al. Project BOOST: effectiveness of a multihospital effort to reduce rehospitalization. J Hosp Med. 2013;8(8):421-427. PubMed
8. Auerbach AD, Kripalani S, Vasilevskis EE, et al. Preventability and Causes of Readmissions in a National Cohort of General Medicine Patients. JAMA Intern Med. 2016;176(4):484-493. PubMed
9. Kripalani S, LeFevre F, Phillips CO, Williams MV, Basaviah P, Baker DW. Deficits in communication and information transfer between hospital-based and primary care physicians: implications for patient safety and continuity of care. JAMA. 2007;297(8):831-841. PubMed
10. Auger KA, Simon TD, Cooperberg D, et al. Summary of STARNet: Seamless Transitions and (Re)admissions Network. Pediatrics. 2015;135(1):164-175. PubMed
11. Hatoun J, Bair-Merritt M, Cabral H, Moses J. Increasing Medication Possession at Discharge for Patients With Asthma: The Meds-in-Hand Project. Pediatrics. 2016;137(3):e20150461. PubMed
12. White CM, Statile AM, White DL, et al. Using quality improvement to optimise paediatric discharge efficiency. BMJ Qual Saf. 2014;23(5):428-436. PubMed
13. Unaka N, Statile A, Jerardi K, et al. Improving the Readability of Pediatric Hospital Medicine Discharge Instructions. J Hosp Med. 2017;12(7):551-557. PubMed
14. Wu S, Tyler A, Logsdon T, et al. A Quality Improvement Collaborative to Improve the Discharge Process for Hospitalized Children. Pediatrics. 2016;138(2). PubMed
15. Blankenship JS, Winslow SA. Admission-discharge-teaching nurses: bridging the gap in today’s workforce. J Nurs Adm. 2003;33(1):11-13. PubMed
16. White CM, Thomson JE, Statile AM, et al. Development of a New Care Model for Hospitalized Children With Medical Complexity. Hosp Pediatr. 2017;7(7):410-414. PubMed
17. Statile AM, Schondelmeyer AC, Thomson JE, et al. Improving Discharge Efficiency in Medically Complex Pediatric Patients. Pediatrics. 2016;138(2). PubMed
18. Dunn K, Rogers J. Discharge Facilitation: An Innovative PNP Role. J Pediatr Health Care. 2016;30(5):499-505. PubMed
19. Kripalani S, Jackson AT, Schnipper JL, Coleman EA. Promoting effective transitions of care at hospital discharge: a review of key issues for hospitalists. J Hosp Med. 2007;2(5):314-323. PubMed
20. Scott AM, Li J, Oyewole-Eletu S, et al. Understanding Facilitators and Barriers to Care Transitions: Insights from Project ACHIEVE Site Visits. Jt Comm J Qual Patient Saf. 2017;43(9):433-447. PubMed
21. Shen MW, Hershey D, Bergert L, Mallory L, Fisher ES, Cooperberg D. Pediatric hospitalists collaborate to improve timeliness of discharge communication. Hosp Pediatr. 2013;3(3):258-265. PubMed
The transition of children from hospital to home introduces a unique set of challenges to patients and families who may not be well-versed in the healthcare system. In addition to juggling the stress and worry of a sick child, which can inhibit the ability to understand complicated discharge instructions prior to leaving the hospital,1 caregivers need to navigate the medical system to ensure continued recovery. The responsibility to fill and administer medications, arrange follow up appointments, and determine when to seek care if the child’s condition changes are burdens we as healthcare providers expect caregivers to manage but may underestimate how frequently they are reliably completed.2-4
In this issue of the Journal of Hospital Medicine, the article by Rehm et al.5 adds to the growing body of evidence highlighting challenges that caregivers of children face upon discharge from the hospital. The multicenter, retrospective study of postdischarge encounters for over 12,000 patients discharged from 4 children’s hospitals aimed to evaluate the following: (1) various methods for hospital-initiated postdischarge contact of families, (2) the type and frequency of postdischarge issues, and (3) specific characteristics of pediatric patients most commonly affected by postdischarge issues.
Using standardized questions administered through telephone, text, or e-mail contact, postdischarge issues were identified in 25% of discharges across all hospitals. Notably, there was considerable variation of rates of postdischarge issues among hospitals (from 16% to 62.8%). The hospital with the highest rate of postdischarge issues identified had attending hospitalists calling families after discharge. Thus, postdischarge issues may be most easily identified by providers who are familiar with both the patient and the expected postdischarge care.
Often, postdischarge issues represented events that could be mitigated with intentional planning to better anticipate and address patient and family needs prior to discharge. The vast majority of postdischarge issues identified across all hospitals were related to appointments, accounting for 76.3% of postdischarge issues, which may be attributed to a variety of causes, from inadequate or unclear provider recommendations to difficulty scheduling the appointments. The most common medication postdischarge issue was difficulty filling prescriptions, accounting for 84.8% of the medication issues. “Other” postdischarge issues (12.7%) as reported by caregivers included challenges with understanding discharge instructions and concerns about changes in their child’s clinical status. Forty percent of included patients had a chronic care condition. Older children, patients with more medication classes, shorter length of stay, and neuromuscular chronic care conditions had higher odds of postdischarge issues. Although a high proportion of postdischarge issues suggests a systemic problem addressing the needs of patients and families after hospital discharge, these data likely underestimate the magnitude of the problem; as such, the need for improvement may be higher.
Postdischarge challenges faced by families are not unique to pediatrics. Pediatric and adult medical patients face similar rates of challenges after
Given the prevalence of postdischarge issues after both pediatric and adult hospitalizations, how should hospitalists proceed? Physicians and health systems should explore approaches to better prepare caregivers, perhaps using models akin to the Seamless Transitions and (Re)admissions Network model of enhanced communication, care coordination, and family engagement.10 Pediatric hospitalists can prepare children for discharge long before departure by delivering medications to patients prior to discharge,11,12 providing discharge instructions that are clear and readable,13,14 as well as utilizing admission-discharge teaching nurses,15 inpatient care managers,16,17 and pediatric nurse practitioners18 to aid transition.
While a variety of interventions show promise in securing a successful transition to home from the hospitalist vantage point, a partnership with primary care physicians (PCPs) in our communities is paramount. Though the evidence linking gaps in primary care after discharge and readmission rates remain elusive, effective partnerships with PCPs are important for ensuring discharge plans are carried out, which may ultimately lead to decreased rates of unanticipated adverse outcomes. Several adult studies note that no single intervention is likely to prevent issues after discharge, but interventions should include high-quality communication with and involvement of community partners.9,19,20 In practice, providing a high-quality, reliable handoff can be difficult given competing priorities of busy outpatient clinic schedules and inpatient bed capacity concerns, necessitating efficient discharge practices. Some of these challenges are amenable to quality improvement efforts to improve discharge communication.21 Innovative ideas include collaborating with PCPs earlier in the admission to design the care plan up front, including PCPs in weekly team meetings for patients with chronic care conditions,16,17 and using telehealth to communicate with PCPs.
Ensuring a safe transition to home is our responsibility as hospitalists, but the solutions to doing so reliably require multi-fold interventions that build teams within hospitals, innovative outreach to those patients recently discharged to ensure their well-being and mitigate postdischarge issues and broad community programs—including greater access to primary care—to meet our urgent imperative.
Disclosure
The authors declare no conflicts of interest. Dr. Auger’s research is funded by the Agency for Healthcare Research and Quality (1K08HS024735).
The transition of children from hospital to home introduces a unique set of challenges to patients and families who may not be well-versed in the healthcare system. In addition to juggling the stress and worry of a sick child, which can inhibit the ability to understand complicated discharge instructions prior to leaving the hospital,1 caregivers need to navigate the medical system to ensure continued recovery. The responsibility to fill and administer medications, arrange follow up appointments, and determine when to seek care if the child’s condition changes are burdens we as healthcare providers expect caregivers to manage but may underestimate how frequently they are reliably completed.2-4
In this issue of the Journal of Hospital Medicine, the article by Rehm et al.5 adds to the growing body of evidence highlighting challenges that caregivers of children face upon discharge from the hospital. The multicenter, retrospective study of postdischarge encounters for over 12,000 patients discharged from 4 children’s hospitals aimed to evaluate the following: (1) various methods for hospital-initiated postdischarge contact of families, (2) the type and frequency of postdischarge issues, and (3) specific characteristics of pediatric patients most commonly affected by postdischarge issues.
Using standardized questions administered through telephone, text, or e-mail contact, postdischarge issues were identified in 25% of discharges across all hospitals. Notably, there was considerable variation of rates of postdischarge issues among hospitals (from 16% to 62.8%). The hospital with the highest rate of postdischarge issues identified had attending hospitalists calling families after discharge. Thus, postdischarge issues may be most easily identified by providers who are familiar with both the patient and the expected postdischarge care.
Often, postdischarge issues represented events that could be mitigated with intentional planning to better anticipate and address patient and family needs prior to discharge. The vast majority of postdischarge issues identified across all hospitals were related to appointments, accounting for 76.3% of postdischarge issues, which may be attributed to a variety of causes, from inadequate or unclear provider recommendations to difficulty scheduling the appointments. The most common medication postdischarge issue was difficulty filling prescriptions, accounting for 84.8% of the medication issues. “Other” postdischarge issues (12.7%) as reported by caregivers included challenges with understanding discharge instructions and concerns about changes in their child’s clinical status. Forty percent of included patients had a chronic care condition. Older children, patients with more medication classes, shorter length of stay, and neuromuscular chronic care conditions had higher odds of postdischarge issues. Although a high proportion of postdischarge issues suggests a systemic problem addressing the needs of patients and families after hospital discharge, these data likely underestimate the magnitude of the problem; as such, the need for improvement may be higher.
Postdischarge challenges faced by families are not unique to pediatrics. Pediatric and adult medical patients face similar rates of challenges after
Given the prevalence of postdischarge issues after both pediatric and adult hospitalizations, how should hospitalists proceed? Physicians and health systems should explore approaches to better prepare caregivers, perhaps using models akin to the Seamless Transitions and (Re)admissions Network model of enhanced communication, care coordination, and family engagement.10 Pediatric hospitalists can prepare children for discharge long before departure by delivering medications to patients prior to discharge,11,12 providing discharge instructions that are clear and readable,13,14 as well as utilizing admission-discharge teaching nurses,15 inpatient care managers,16,17 and pediatric nurse practitioners18 to aid transition.
While a variety of interventions show promise in securing a successful transition to home from the hospitalist vantage point, a partnership with primary care physicians (PCPs) in our communities is paramount. Though the evidence linking gaps in primary care after discharge and readmission rates remain elusive, effective partnerships with PCPs are important for ensuring discharge plans are carried out, which may ultimately lead to decreased rates of unanticipated adverse outcomes. Several adult studies note that no single intervention is likely to prevent issues after discharge, but interventions should include high-quality communication with and involvement of community partners.9,19,20 In practice, providing a high-quality, reliable handoff can be difficult given competing priorities of busy outpatient clinic schedules and inpatient bed capacity concerns, necessitating efficient discharge practices. Some of these challenges are amenable to quality improvement efforts to improve discharge communication.21 Innovative ideas include collaborating with PCPs earlier in the admission to design the care plan up front, including PCPs in weekly team meetings for patients with chronic care conditions,16,17 and using telehealth to communicate with PCPs.
Ensuring a safe transition to home is our responsibility as hospitalists, but the solutions to doing so reliably require multi-fold interventions that build teams within hospitals, innovative outreach to those patients recently discharged to ensure their well-being and mitigate postdischarge issues and broad community programs—including greater access to primary care—to meet our urgent imperative.
Disclosure
The authors declare no conflicts of interest. Dr. Auger’s research is funded by the Agency for Healthcare Research and Quality (1K08HS024735).
1. Solan LG, Beck AF, Brunswick SA, et al. The Family Perspective on Hospital to Home Transitions: A Qualitative Study. Pediatrics. 2015;136(6):e1539-1549. PubMed
2. Misky GJ, Wald HL, Coleman EA. Post-hospitalization transitions: Examining the effects of timing of primary care provider follow-up. J Hosp Med. 2010;5(7):392-397. PubMed
3. Yin HS, Johnson M, Mendelsohn AL, Abrams MA, Sanders LM, Dreyer BP. The health literacy of parents in the United States: a nationally representative study. Pediatrics. 2009;124 Suppl 3:S289-298. PubMed
4. Glick AF, Farkas JS, Nicholson J, et al. Parental Management of Discharge Instructions: A Systematic Review. Pediatrics. 2017. [Epub ahead of print]. PubMed
5. Rehm KP, Brittan MS, Stephens JR, et al. Issues Identified by Post-Discharge Contact after Pediatric Hospitalization: A Multi-site Study (published online ahead of print February 2, 2018) J Hosp Med. doi: 10.12788/jhm.2934
6. Forster AJ, Murff HJ, Peterson JF, Gandhi TK, Bates DW. The incidence and severity of adverse events affecting patients after discharge from the hospital. Ann Intern Med. 2003;138(3):161-167. PubMed
7. Hansen LO, Greenwald JL, Budnitz T, et al. Project BOOST: effectiveness of a multihospital effort to reduce rehospitalization. J Hosp Med. 2013;8(8):421-427. PubMed
8. Auerbach AD, Kripalani S, Vasilevskis EE, et al. Preventability and Causes of Readmissions in a National Cohort of General Medicine Patients. JAMA Intern Med. 2016;176(4):484-493. PubMed
9. Kripalani S, LeFevre F, Phillips CO, Williams MV, Basaviah P, Baker DW. Deficits in communication and information transfer between hospital-based and primary care physicians: implications for patient safety and continuity of care. JAMA. 2007;297(8):831-841. PubMed
10. Auger KA, Simon TD, Cooperberg D, et al. Summary of STARNet: Seamless Transitions and (Re)admissions Network. Pediatrics. 2015;135(1):164-175. PubMed
11. Hatoun J, Bair-Merritt M, Cabral H, Moses J. Increasing Medication Possession at Discharge for Patients With Asthma: The Meds-in-Hand Project. Pediatrics. 2016;137(3):e20150461. PubMed
12. White CM, Statile AM, White DL, et al. Using quality improvement to optimise paediatric discharge efficiency. BMJ Qual Saf. 2014;23(5):428-436. PubMed
13. Unaka N, Statile A, Jerardi K, et al. Improving the Readability of Pediatric Hospital Medicine Discharge Instructions. J Hosp Med. 2017;12(7):551-557. PubMed
14. Wu S, Tyler A, Logsdon T, et al. A Quality Improvement Collaborative to Improve the Discharge Process for Hospitalized Children. Pediatrics. 2016;138(2). PubMed
15. Blankenship JS, Winslow SA. Admission-discharge-teaching nurses: bridging the gap in today’s workforce. J Nurs Adm. 2003;33(1):11-13. PubMed
16. White CM, Thomson JE, Statile AM, et al. Development of a New Care Model for Hospitalized Children With Medical Complexity. Hosp Pediatr. 2017;7(7):410-414. PubMed
17. Statile AM, Schondelmeyer AC, Thomson JE, et al. Improving Discharge Efficiency in Medically Complex Pediatric Patients. Pediatrics. 2016;138(2). PubMed
18. Dunn K, Rogers J. Discharge Facilitation: An Innovative PNP Role. J Pediatr Health Care. 2016;30(5):499-505. PubMed
19. Kripalani S, Jackson AT, Schnipper JL, Coleman EA. Promoting effective transitions of care at hospital discharge: a review of key issues for hospitalists. J Hosp Med. 2007;2(5):314-323. PubMed
20. Scott AM, Li J, Oyewole-Eletu S, et al. Understanding Facilitators and Barriers to Care Transitions: Insights from Project ACHIEVE Site Visits. Jt Comm J Qual Patient Saf. 2017;43(9):433-447. PubMed
21. Shen MW, Hershey D, Bergert L, Mallory L, Fisher ES, Cooperberg D. Pediatric hospitalists collaborate to improve timeliness of discharge communication. Hosp Pediatr. 2013;3(3):258-265. PubMed
1. Solan LG, Beck AF, Brunswick SA, et al. The Family Perspective on Hospital to Home Transitions: A Qualitative Study. Pediatrics. 2015;136(6):e1539-1549. PubMed
2. Misky GJ, Wald HL, Coleman EA. Post-hospitalization transitions: Examining the effects of timing of primary care provider follow-up. J Hosp Med. 2010;5(7):392-397. PubMed
3. Yin HS, Johnson M, Mendelsohn AL, Abrams MA, Sanders LM, Dreyer BP. The health literacy of parents in the United States: a nationally representative study. Pediatrics. 2009;124 Suppl 3:S289-298. PubMed
4. Glick AF, Farkas JS, Nicholson J, et al. Parental Management of Discharge Instructions: A Systematic Review. Pediatrics. 2017. [Epub ahead of print]. PubMed
5. Rehm KP, Brittan MS, Stephens JR, et al. Issues Identified by Post-Discharge Contact after Pediatric Hospitalization: A Multi-site Study (published online ahead of print February 2, 2018) J Hosp Med. doi: 10.12788/jhm.2934
6. Forster AJ, Murff HJ, Peterson JF, Gandhi TK, Bates DW. The incidence and severity of adverse events affecting patients after discharge from the hospital. Ann Intern Med. 2003;138(3):161-167. PubMed
7. Hansen LO, Greenwald JL, Budnitz T, et al. Project BOOST: effectiveness of a multihospital effort to reduce rehospitalization. J Hosp Med. 2013;8(8):421-427. PubMed
8. Auerbach AD, Kripalani S, Vasilevskis EE, et al. Preventability and Causes of Readmissions in a National Cohort of General Medicine Patients. JAMA Intern Med. 2016;176(4):484-493. PubMed
9. Kripalani S, LeFevre F, Phillips CO, Williams MV, Basaviah P, Baker DW. Deficits in communication and information transfer between hospital-based and primary care physicians: implications for patient safety and continuity of care. JAMA. 2007;297(8):831-841. PubMed
10. Auger KA, Simon TD, Cooperberg D, et al. Summary of STARNet: Seamless Transitions and (Re)admissions Network. Pediatrics. 2015;135(1):164-175. PubMed
11. Hatoun J, Bair-Merritt M, Cabral H, Moses J. Increasing Medication Possession at Discharge for Patients With Asthma: The Meds-in-Hand Project. Pediatrics. 2016;137(3):e20150461. PubMed
12. White CM, Statile AM, White DL, et al. Using quality improvement to optimise paediatric discharge efficiency. BMJ Qual Saf. 2014;23(5):428-436. PubMed
13. Unaka N, Statile A, Jerardi K, et al. Improving the Readability of Pediatric Hospital Medicine Discharge Instructions. J Hosp Med. 2017;12(7):551-557. PubMed
14. Wu S, Tyler A, Logsdon T, et al. A Quality Improvement Collaborative to Improve the Discharge Process for Hospitalized Children. Pediatrics. 2016;138(2). PubMed
15. Blankenship JS, Winslow SA. Admission-discharge-teaching nurses: bridging the gap in today’s workforce. J Nurs Adm. 2003;33(1):11-13. PubMed
16. White CM, Thomson JE, Statile AM, et al. Development of a New Care Model for Hospitalized Children With Medical Complexity. Hosp Pediatr. 2017;7(7):410-414. PubMed
17. Statile AM, Schondelmeyer AC, Thomson JE, et al. Improving Discharge Efficiency in Medically Complex Pediatric Patients. Pediatrics. 2016;138(2). PubMed
18. Dunn K, Rogers J. Discharge Facilitation: An Innovative PNP Role. J Pediatr Health Care. 2016;30(5):499-505. PubMed
19. Kripalani S, Jackson AT, Schnipper JL, Coleman EA. Promoting effective transitions of care at hospital discharge: a review of key issues for hospitalists. J Hosp Med. 2007;2(5):314-323. PubMed
20. Scott AM, Li J, Oyewole-Eletu S, et al. Understanding Facilitators and Barriers to Care Transitions: Insights from Project ACHIEVE Site Visits. Jt Comm J Qual Patient Saf. 2017;43(9):433-447. PubMed
21. Shen MW, Hershey D, Bergert L, Mallory L, Fisher ES, Cooperberg D. Pediatric hospitalists collaborate to improve timeliness of discharge communication. Hosp Pediatr. 2013;3(3):258-265. PubMed
© 2018 Society of Hospital Medicine
Pediatric Admission and Readmission
Patient outcomes tend to be worse for adults admitted on the weekend compared to the weekday.[1, 2, 3, 4] In pediatric populations, urgent surgeries on weekends are associated with increased morbidity and mortality[5]; however, studies of mortality and admission timing in the pediatric critical care setting are mixed.[6, 7] Hospital readmission is considered a potential marker of hospital quality. We hypothesized that (1) being admitted and (2) being discharged on the weekend would adversely affect 30‐day unplanned readmission for pediatric patients.
METHODS
Population
All discharges from January 1, 2006 through December 31, 2012 from C. S. Mott Children's Hospital were initially eligible. All hospitalizations were considered potential index admissions; therefore, children may contribute more than 1 hospitalization to the dataset. We excluded hospitalizations in which the patient died, was transferred to another institution, was discharged against medical advice, or was discharged to hospice. Newborns admitted to a normal newborn service were also excluded, as they do not represent a typical hospitalization for illness. Among newborns admitted to a higher‐intensity clinical service (eg, special care nursery or neonatal intensive care), we also excluded newborns with a length of stay <5 days, given the typical length of stay of up to 4 days for uncomplicated delivery via Cesarean section that would indicate infants for whom precautionary measures had been taken but there was low estimated health risk. We used International Classification of Diseases, Ninth Revision codes to identify children with complex chronic conditions (CCCs) and technology dependency.[8]
Outcome
We examined unplanned readmission within 30 days of discharge. We defined unplanned readmission as a readmission that was not entered into the hospital registration system at least 24 hours before discharge.[9] Additionally, we performed sensitive analyses examining any 30‐day readmissions.
Statistical Analysis
We fit multivariable logistic regression models for 30‐day unplanned readmission, with the primary predictor of either weekend (Saturday or Sunday) admission or weekend discharge (in separate models). We adjusted for patient age, gender, race/ethnicity, source of admission, insurance, and length of stay. We also adjusted for patient chronic illness complexity using the number of CCCs and technology dependency (yes/no). Variance in all analyses was clustered on individual patients.
RESULTS
We included a total of 55,383 hospitalizations from 32,112 patients (see Supporting Appendix Figure in the online version of this article for cohort derivation). All‐cause 30‐day readmissions occurred in 14.9% of hospital discharges; the 30‐day unplanned readmission rate was 10.3% (see the Supporting Appendix Table in the online version of this article for demographic characteristics).
Weekend Admission
Overall, 82% of admissions occurred during the week, with Tuesday as the highest admitting volume day (Figure 1). Children admitted on the weekend had higher odds of unplanned readmission compared to children admitted on weekdays (unadjusted odds ratio [OR]=1.15 [95% confidence interval {CI}: 1.07‐1.24]). Adjusting the analysis for age, gender, race/ethnicity, insurance, length of stay, CCCs, and technology dependency, higher odds of readmission remains significantly higher than weekday admission (adjusted OR=1.09 [95% CI: 1.004‐1.18]) (Table 1). Age, admission source, payer, length of stay, number of complex chronic conditions, and technology dependency were also significantly associated with readmission in the weekend admission model (see the Supporting Appendix Table in the online version of this article). A sensitivity analysis examining the association of weekend admission and readmission within different subpopulations of children with varying numbers of CCCs (ie, among children without CCCs, with 1 CCC, 2 CCCs, and 3+ CCCs) showed that the association remains the same in each subgroup. Further, a sensitivity analysis examining odds of any 30‐day readmission was similar to the primary analysis with higher odds of readmission in adjusted analysis (adjusted OR=1.09 [95% CI: 1.02‐1.18]).
| 30‐Day Unplanned Readmission Rate | Unadjusted Odds of Unplanned Readmission (95% CI) | Weekend Admission Model: Adjusted Odds of Unplanned Readmission (95% CI) | Weekend Discharge Model: Adjusted Odds of Unplanned Readmission (95% CI) | |
|---|---|---|---|---|
| ||||
| Weekend admission, n=7,533 | 11.4%, n=973 | 1.15 (1.07‐1.24)* | 1.09 (1.004‐1.18)* | |
| Weekend discharge, n=13,911 | 9.7%, n=1,344 | 0.91 (0.85‐0.97)* | 0.97 (0.91‐1.04) | |
Weekend Discharge
Weekend discharges accounted for 34% of all discharges. Fridays had the highest discharge volumes, with lowest discharge volumes on Sunday (Figure 1). Children discharged on the weekend had lower odds of unplanned readmission compared to children discharged on weekdays in bivariate analysis (unadjusted OR=0.91 [95% CI: 0.85‐0.97]). However, when adjusting for important confounders, the relationship was no longer statistically significant (adjusted OR=0.97 [95% CI: 0.91‐1.03]) (Table 1). Age, admission source, payer, length of stay, and number of complex chronic conditions were associated with readmission in the weekend discharge model (see the Supporting Appendix Table in the online version of this article). In a sensitivity analysis examining any 30‐day readmission, weekend discharge was not associated with readmission in adjusted analysis.
DISCUSSION
Although the so‐called weekend effect has been established in adults,[1, 2, 3, 4] evidence is mixed for children. In this sample, where the 30‐day pediatric readmission rate is consistent with national pediatric rates,[10] pediatric patients admitted on the weekend have higher odds of readmission compared to children admitted during the week, even when accounting for patient characteristics and hospital length of stay. In contrast, weekend discharge was not associated with readmission.
The association of weekend admission and subsequent readmission is intriguing and may be interpreted in 1 of 2 ways: either patients admitted on the weekend are fundamentally different and thus have higher readmission rates, or care on the weekend is different. It is important to note that we adjusted the analysis for patient characteristics including number of CCCs and technology dependency to account for differences in chronic illness. We also accounted for length of stay as a marker of severity of illness in the hospital. Yet even accounting for these known differences, we cannot discern from these data if the different outcomes for children admitted on the weekend are related to residual population differences (eg, lack of access to primary care or walk‐in clinics) or differences in initial clinical management on the weekend.
Initial clinical management on weekend may be different due to differences in physician, nursing, and other ancillary staffing affecting availability of diagnostic and therapeutic interventions. Additionally, smaller staff size on the weekend may lead to increased workload. Although we are unable to directly measure resident workload in our study, prior studies suggest higher workload is associated with worse outcomes for adult patients,[11] including readmission.[12] Additionally, nurse staffing, which may vary based on day of week, has been associated with pediatric readmission.[13]
Discharge timing in our population is consistent with prior literature, with Friday being the most common discharge day of week.[14] Prior literature has shown no difference in readmission rates between Friday discharge and midweek discharge for pediatric patients.[14] Our work builds on this existing literature, demonstrating no association with weekend discharge and readmission. There were lower discharge volumes on the weekends, particularly in patients with more CCCs, suggesting that physicians avoid complicated discharges on Saturday and Sunday.
This study should be interpreted in the context of several limitations. First, this study was conducted at a single tertiary care pediatric institution. Our patient population had a high rate of children with CCCs, potentially limiting generalizability to other pediatric institutions. Ideally, we would adjust our model for clusters at the clinical service or attending physician level; however, the heterogeneity of our services and data limits prohibited these analyses. Readmissions that may have occurred at other institutions are not observable in this dataset; however, there is no reason to believe patients admitted or discharged on the weekend would have different rates of other hospital readmissions than patients admitted or discharged on weekdays. Additionally, early readmissions may be particularly affected by in‐hospital and discharge factors.[15] However, the very low rate of early readmission prohibited limiting the analyses to early readmission. Finally, we relied on administrative data to adjust for patient severity using typical methods such as CCCs; however, other patient differences may have existed beyond those that could be captured with administrative data.
CONCLUSION
Children admitted to the hospital on the weekend have higher rates of 30‐day unplanned readmission than children admitted during the week, suggesting differences of care in initial management on the weekend. Understanding this difference from the perspectives of multiple stakeholders may illuminate potential reasons for this disparity.
Disclosures
Dr. Auger received salary support from the Robert Wood Johnson Foundation Clinical Scholars program during work on this project. The hospital database was assembled with funds from a grant from the Blue Cross Blue Shield of Michigan Foundation. The authors report no conflicts of interest.
- , , , . A comparison of in‐hospital mortality risk conferred by high hospital occupancy, differences in nurse staffing levels, weekend admission, and seasonal influenza. Med Care. 2010;48(3):224–232.
- , . Mortality among patients admitted to hospitals on weekends as compared with weekdays. N Engl J Med. 2001;345(9):663–668.
- , , , . Effects of weekend admission and hospital teaching status on in‐hospital mortality. Am J Med. 2004;117(3):151–157.
- , , . Weekend admission for myocardial infarction. N Engl J Med. 2007;357(1):86–87; author reply 87–88.
- , , , et al. The "weekend effect" in pediatric surgery—increased mortality for children undergoing urgent surgery during the weekend. J Pediatr Surg. 2014;49(7):1087–1091.
- , , , , , Paediatric Intensive Care Audit Network (PICANet). Effects of out‐of‐hours and winter admissions and number of patients per unit on mortality in pediatric intensive care. J Pediatr. 2013;163(4):1039–1044.e1035.
- , , , . Do weekends or evenings matter in a pediatric intensive care unit? Pediatr Crit Care Med. 2005;6(5):523–530.
- , , , , . Pediatric complex chronic conditions classification system version 2: updated for ICD‐10 and complex medical technology dependence and transplantation. BMC Pediatr. 2014;14:199.
- , , , et al. Using hospital designation to identify unplanned pediatric readmissions [abstract]. J Hosp Med. Available at: http://www.shmabstracts.com/abstract/using‐hospital‐designation‐to‐identify‐unplanned‐pediatric‐readmissions. Accessed July 15, 2015.
- , , , et al. Rates and impact of potentially preventable readmissions at children's hospitals. J Pediatr. 2015;166(3):613–619.e615.
- , , , , . House staff team workload and organization effects on patient outcomes in an academic general internal medicine inpatient service. Arch Intern Med. 2007;167(1):47–52.
- , . A "reverse july effect": association between timing of admission, medical team workload, and 30‐day readmission rate. J Grad Med Educ. 2014;6(1):65–70.
- , , , , . An observational study of nurse staffing ratios and hospital readmission among children admitted for common conditions. BMJ Qual Saf. 2013;22(9):735–742.
- , , , , . Day of discharge and hospital readmission rates within 30 days in children: a population‐based study. Paediatr Child Health. 2006;11(7):409–412.
- , , , , . Differences between early and late readmissions among patients: a cohort study. Ann Intern Med. 2015;162(11):741–749.
Patient outcomes tend to be worse for adults admitted on the weekend compared to the weekday.[1, 2, 3, 4] In pediatric populations, urgent surgeries on weekends are associated with increased morbidity and mortality[5]; however, studies of mortality and admission timing in the pediatric critical care setting are mixed.[6, 7] Hospital readmission is considered a potential marker of hospital quality. We hypothesized that (1) being admitted and (2) being discharged on the weekend would adversely affect 30‐day unplanned readmission for pediatric patients.
METHODS
Population
All discharges from January 1, 2006 through December 31, 2012 from C. S. Mott Children's Hospital were initially eligible. All hospitalizations were considered potential index admissions; therefore, children may contribute more than 1 hospitalization to the dataset. We excluded hospitalizations in which the patient died, was transferred to another institution, was discharged against medical advice, or was discharged to hospice. Newborns admitted to a normal newborn service were also excluded, as they do not represent a typical hospitalization for illness. Among newborns admitted to a higher‐intensity clinical service (eg, special care nursery or neonatal intensive care), we also excluded newborns with a length of stay <5 days, given the typical length of stay of up to 4 days for uncomplicated delivery via Cesarean section that would indicate infants for whom precautionary measures had been taken but there was low estimated health risk. We used International Classification of Diseases, Ninth Revision codes to identify children with complex chronic conditions (CCCs) and technology dependency.[8]
Outcome
We examined unplanned readmission within 30 days of discharge. We defined unplanned readmission as a readmission that was not entered into the hospital registration system at least 24 hours before discharge.[9] Additionally, we performed sensitive analyses examining any 30‐day readmissions.
Statistical Analysis
We fit multivariable logistic regression models for 30‐day unplanned readmission, with the primary predictor of either weekend (Saturday or Sunday) admission or weekend discharge (in separate models). We adjusted for patient age, gender, race/ethnicity, source of admission, insurance, and length of stay. We also adjusted for patient chronic illness complexity using the number of CCCs and technology dependency (yes/no). Variance in all analyses was clustered on individual patients.
RESULTS
We included a total of 55,383 hospitalizations from 32,112 patients (see Supporting Appendix Figure in the online version of this article for cohort derivation). All‐cause 30‐day readmissions occurred in 14.9% of hospital discharges; the 30‐day unplanned readmission rate was 10.3% (see the Supporting Appendix Table in the online version of this article for demographic characteristics).
Weekend Admission
Overall, 82% of admissions occurred during the week, with Tuesday as the highest admitting volume day (Figure 1). Children admitted on the weekend had higher odds of unplanned readmission compared to children admitted on weekdays (unadjusted odds ratio [OR]=1.15 [95% confidence interval {CI}: 1.07‐1.24]). Adjusting the analysis for age, gender, race/ethnicity, insurance, length of stay, CCCs, and technology dependency, higher odds of readmission remains significantly higher than weekday admission (adjusted OR=1.09 [95% CI: 1.004‐1.18]) (Table 1). Age, admission source, payer, length of stay, number of complex chronic conditions, and technology dependency were also significantly associated with readmission in the weekend admission model (see the Supporting Appendix Table in the online version of this article). A sensitivity analysis examining the association of weekend admission and readmission within different subpopulations of children with varying numbers of CCCs (ie, among children without CCCs, with 1 CCC, 2 CCCs, and 3+ CCCs) showed that the association remains the same in each subgroup. Further, a sensitivity analysis examining odds of any 30‐day readmission was similar to the primary analysis with higher odds of readmission in adjusted analysis (adjusted OR=1.09 [95% CI: 1.02‐1.18]).
| 30‐Day Unplanned Readmission Rate | Unadjusted Odds of Unplanned Readmission (95% CI) | Weekend Admission Model: Adjusted Odds of Unplanned Readmission (95% CI) | Weekend Discharge Model: Adjusted Odds of Unplanned Readmission (95% CI) | |
|---|---|---|---|---|
| ||||
| Weekend admission, n=7,533 | 11.4%, n=973 | 1.15 (1.07‐1.24)* | 1.09 (1.004‐1.18)* | |
| Weekend discharge, n=13,911 | 9.7%, n=1,344 | 0.91 (0.85‐0.97)* | 0.97 (0.91‐1.04) | |
Weekend Discharge
Weekend discharges accounted for 34% of all discharges. Fridays had the highest discharge volumes, with lowest discharge volumes on Sunday (Figure 1). Children discharged on the weekend had lower odds of unplanned readmission compared to children discharged on weekdays in bivariate analysis (unadjusted OR=0.91 [95% CI: 0.85‐0.97]). However, when adjusting for important confounders, the relationship was no longer statistically significant (adjusted OR=0.97 [95% CI: 0.91‐1.03]) (Table 1). Age, admission source, payer, length of stay, and number of complex chronic conditions were associated with readmission in the weekend discharge model (see the Supporting Appendix Table in the online version of this article). In a sensitivity analysis examining any 30‐day readmission, weekend discharge was not associated with readmission in adjusted analysis.
DISCUSSION
Although the so‐called weekend effect has been established in adults,[1, 2, 3, 4] evidence is mixed for children. In this sample, where the 30‐day pediatric readmission rate is consistent with national pediatric rates,[10] pediatric patients admitted on the weekend have higher odds of readmission compared to children admitted during the week, even when accounting for patient characteristics and hospital length of stay. In contrast, weekend discharge was not associated with readmission.
The association of weekend admission and subsequent readmission is intriguing and may be interpreted in 1 of 2 ways: either patients admitted on the weekend are fundamentally different and thus have higher readmission rates, or care on the weekend is different. It is important to note that we adjusted the analysis for patient characteristics including number of CCCs and technology dependency to account for differences in chronic illness. We also accounted for length of stay as a marker of severity of illness in the hospital. Yet even accounting for these known differences, we cannot discern from these data if the different outcomes for children admitted on the weekend are related to residual population differences (eg, lack of access to primary care or walk‐in clinics) or differences in initial clinical management on the weekend.
Initial clinical management on weekend may be different due to differences in physician, nursing, and other ancillary staffing affecting availability of diagnostic and therapeutic interventions. Additionally, smaller staff size on the weekend may lead to increased workload. Although we are unable to directly measure resident workload in our study, prior studies suggest higher workload is associated with worse outcomes for adult patients,[11] including readmission.[12] Additionally, nurse staffing, which may vary based on day of week, has been associated with pediatric readmission.[13]
Discharge timing in our population is consistent with prior literature, with Friday being the most common discharge day of week.[14] Prior literature has shown no difference in readmission rates between Friday discharge and midweek discharge for pediatric patients.[14] Our work builds on this existing literature, demonstrating no association with weekend discharge and readmission. There were lower discharge volumes on the weekends, particularly in patients with more CCCs, suggesting that physicians avoid complicated discharges on Saturday and Sunday.
This study should be interpreted in the context of several limitations. First, this study was conducted at a single tertiary care pediatric institution. Our patient population had a high rate of children with CCCs, potentially limiting generalizability to other pediatric institutions. Ideally, we would adjust our model for clusters at the clinical service or attending physician level; however, the heterogeneity of our services and data limits prohibited these analyses. Readmissions that may have occurred at other institutions are not observable in this dataset; however, there is no reason to believe patients admitted or discharged on the weekend would have different rates of other hospital readmissions than patients admitted or discharged on weekdays. Additionally, early readmissions may be particularly affected by in‐hospital and discharge factors.[15] However, the very low rate of early readmission prohibited limiting the analyses to early readmission. Finally, we relied on administrative data to adjust for patient severity using typical methods such as CCCs; however, other patient differences may have existed beyond those that could be captured with administrative data.
CONCLUSION
Children admitted to the hospital on the weekend have higher rates of 30‐day unplanned readmission than children admitted during the week, suggesting differences of care in initial management on the weekend. Understanding this difference from the perspectives of multiple stakeholders may illuminate potential reasons for this disparity.
Disclosures
Dr. Auger received salary support from the Robert Wood Johnson Foundation Clinical Scholars program during work on this project. The hospital database was assembled with funds from a grant from the Blue Cross Blue Shield of Michigan Foundation. The authors report no conflicts of interest.
Patient outcomes tend to be worse for adults admitted on the weekend compared to the weekday.[1, 2, 3, 4] In pediatric populations, urgent surgeries on weekends are associated with increased morbidity and mortality[5]; however, studies of mortality and admission timing in the pediatric critical care setting are mixed.[6, 7] Hospital readmission is considered a potential marker of hospital quality. We hypothesized that (1) being admitted and (2) being discharged on the weekend would adversely affect 30‐day unplanned readmission for pediatric patients.
METHODS
Population
All discharges from January 1, 2006 through December 31, 2012 from C. S. Mott Children's Hospital were initially eligible. All hospitalizations were considered potential index admissions; therefore, children may contribute more than 1 hospitalization to the dataset. We excluded hospitalizations in which the patient died, was transferred to another institution, was discharged against medical advice, or was discharged to hospice. Newborns admitted to a normal newborn service were also excluded, as they do not represent a typical hospitalization for illness. Among newborns admitted to a higher‐intensity clinical service (eg, special care nursery or neonatal intensive care), we also excluded newborns with a length of stay <5 days, given the typical length of stay of up to 4 days for uncomplicated delivery via Cesarean section that would indicate infants for whom precautionary measures had been taken but there was low estimated health risk. We used International Classification of Diseases, Ninth Revision codes to identify children with complex chronic conditions (CCCs) and technology dependency.[8]
Outcome
We examined unplanned readmission within 30 days of discharge. We defined unplanned readmission as a readmission that was not entered into the hospital registration system at least 24 hours before discharge.[9] Additionally, we performed sensitive analyses examining any 30‐day readmissions.
Statistical Analysis
We fit multivariable logistic regression models for 30‐day unplanned readmission, with the primary predictor of either weekend (Saturday or Sunday) admission or weekend discharge (in separate models). We adjusted for patient age, gender, race/ethnicity, source of admission, insurance, and length of stay. We also adjusted for patient chronic illness complexity using the number of CCCs and technology dependency (yes/no). Variance in all analyses was clustered on individual patients.
RESULTS
We included a total of 55,383 hospitalizations from 32,112 patients (see Supporting Appendix Figure in the online version of this article for cohort derivation). All‐cause 30‐day readmissions occurred in 14.9% of hospital discharges; the 30‐day unplanned readmission rate was 10.3% (see the Supporting Appendix Table in the online version of this article for demographic characteristics).
Weekend Admission
Overall, 82% of admissions occurred during the week, with Tuesday as the highest admitting volume day (Figure 1). Children admitted on the weekend had higher odds of unplanned readmission compared to children admitted on weekdays (unadjusted odds ratio [OR]=1.15 [95% confidence interval {CI}: 1.07‐1.24]). Adjusting the analysis for age, gender, race/ethnicity, insurance, length of stay, CCCs, and technology dependency, higher odds of readmission remains significantly higher than weekday admission (adjusted OR=1.09 [95% CI: 1.004‐1.18]) (Table 1). Age, admission source, payer, length of stay, number of complex chronic conditions, and technology dependency were also significantly associated with readmission in the weekend admission model (see the Supporting Appendix Table in the online version of this article). A sensitivity analysis examining the association of weekend admission and readmission within different subpopulations of children with varying numbers of CCCs (ie, among children without CCCs, with 1 CCC, 2 CCCs, and 3+ CCCs) showed that the association remains the same in each subgroup. Further, a sensitivity analysis examining odds of any 30‐day readmission was similar to the primary analysis with higher odds of readmission in adjusted analysis (adjusted OR=1.09 [95% CI: 1.02‐1.18]).
| 30‐Day Unplanned Readmission Rate | Unadjusted Odds of Unplanned Readmission (95% CI) | Weekend Admission Model: Adjusted Odds of Unplanned Readmission (95% CI) | Weekend Discharge Model: Adjusted Odds of Unplanned Readmission (95% CI) | |
|---|---|---|---|---|
| ||||
| Weekend admission, n=7,533 | 11.4%, n=973 | 1.15 (1.07‐1.24)* | 1.09 (1.004‐1.18)* | |
| Weekend discharge, n=13,911 | 9.7%, n=1,344 | 0.91 (0.85‐0.97)* | 0.97 (0.91‐1.04) | |
Weekend Discharge
Weekend discharges accounted for 34% of all discharges. Fridays had the highest discharge volumes, with lowest discharge volumes on Sunday (Figure 1). Children discharged on the weekend had lower odds of unplanned readmission compared to children discharged on weekdays in bivariate analysis (unadjusted OR=0.91 [95% CI: 0.85‐0.97]). However, when adjusting for important confounders, the relationship was no longer statistically significant (adjusted OR=0.97 [95% CI: 0.91‐1.03]) (Table 1). Age, admission source, payer, length of stay, and number of complex chronic conditions were associated with readmission in the weekend discharge model (see the Supporting Appendix Table in the online version of this article). In a sensitivity analysis examining any 30‐day readmission, weekend discharge was not associated with readmission in adjusted analysis.
DISCUSSION
Although the so‐called weekend effect has been established in adults,[1, 2, 3, 4] evidence is mixed for children. In this sample, where the 30‐day pediatric readmission rate is consistent with national pediatric rates,[10] pediatric patients admitted on the weekend have higher odds of readmission compared to children admitted during the week, even when accounting for patient characteristics and hospital length of stay. In contrast, weekend discharge was not associated with readmission.
The association of weekend admission and subsequent readmission is intriguing and may be interpreted in 1 of 2 ways: either patients admitted on the weekend are fundamentally different and thus have higher readmission rates, or care on the weekend is different. It is important to note that we adjusted the analysis for patient characteristics including number of CCCs and technology dependency to account for differences in chronic illness. We also accounted for length of stay as a marker of severity of illness in the hospital. Yet even accounting for these known differences, we cannot discern from these data if the different outcomes for children admitted on the weekend are related to residual population differences (eg, lack of access to primary care or walk‐in clinics) or differences in initial clinical management on the weekend.
Initial clinical management on weekend may be different due to differences in physician, nursing, and other ancillary staffing affecting availability of diagnostic and therapeutic interventions. Additionally, smaller staff size on the weekend may lead to increased workload. Although we are unable to directly measure resident workload in our study, prior studies suggest higher workload is associated with worse outcomes for adult patients,[11] including readmission.[12] Additionally, nurse staffing, which may vary based on day of week, has been associated with pediatric readmission.[13]
Discharge timing in our population is consistent with prior literature, with Friday being the most common discharge day of week.[14] Prior literature has shown no difference in readmission rates between Friday discharge and midweek discharge for pediatric patients.[14] Our work builds on this existing literature, demonstrating no association with weekend discharge and readmission. There were lower discharge volumes on the weekends, particularly in patients with more CCCs, suggesting that physicians avoid complicated discharges on Saturday and Sunday.
This study should be interpreted in the context of several limitations. First, this study was conducted at a single tertiary care pediatric institution. Our patient population had a high rate of children with CCCs, potentially limiting generalizability to other pediatric institutions. Ideally, we would adjust our model for clusters at the clinical service or attending physician level; however, the heterogeneity of our services and data limits prohibited these analyses. Readmissions that may have occurred at other institutions are not observable in this dataset; however, there is no reason to believe patients admitted or discharged on the weekend would have different rates of other hospital readmissions than patients admitted or discharged on weekdays. Additionally, early readmissions may be particularly affected by in‐hospital and discharge factors.[15] However, the very low rate of early readmission prohibited limiting the analyses to early readmission. Finally, we relied on administrative data to adjust for patient severity using typical methods such as CCCs; however, other patient differences may have existed beyond those that could be captured with administrative data.
CONCLUSION
Children admitted to the hospital on the weekend have higher rates of 30‐day unplanned readmission than children admitted during the week, suggesting differences of care in initial management on the weekend. Understanding this difference from the perspectives of multiple stakeholders may illuminate potential reasons for this disparity.
Disclosures
Dr. Auger received salary support from the Robert Wood Johnson Foundation Clinical Scholars program during work on this project. The hospital database was assembled with funds from a grant from the Blue Cross Blue Shield of Michigan Foundation. The authors report no conflicts of interest.
- , , , . A comparison of in‐hospital mortality risk conferred by high hospital occupancy, differences in nurse staffing levels, weekend admission, and seasonal influenza. Med Care. 2010;48(3):224–232.
- , . Mortality among patients admitted to hospitals on weekends as compared with weekdays. N Engl J Med. 2001;345(9):663–668.
- , , , . Effects of weekend admission and hospital teaching status on in‐hospital mortality. Am J Med. 2004;117(3):151–157.
- , , . Weekend admission for myocardial infarction. N Engl J Med. 2007;357(1):86–87; author reply 87–88.
- , , , et al. The "weekend effect" in pediatric surgery—increased mortality for children undergoing urgent surgery during the weekend. J Pediatr Surg. 2014;49(7):1087–1091.
- , , , , , Paediatric Intensive Care Audit Network (PICANet). Effects of out‐of‐hours and winter admissions and number of patients per unit on mortality in pediatric intensive care. J Pediatr. 2013;163(4):1039–1044.e1035.
- , , , . Do weekends or evenings matter in a pediatric intensive care unit? Pediatr Crit Care Med. 2005;6(5):523–530.
- , , , , . Pediatric complex chronic conditions classification system version 2: updated for ICD‐10 and complex medical technology dependence and transplantation. BMC Pediatr. 2014;14:199.
- , , , et al. Using hospital designation to identify unplanned pediatric readmissions [abstract]. J Hosp Med. Available at: http://www.shmabstracts.com/abstract/using‐hospital‐designation‐to‐identify‐unplanned‐pediatric‐readmissions. Accessed July 15, 2015.
- , , , et al. Rates and impact of potentially preventable readmissions at children's hospitals. J Pediatr. 2015;166(3):613–619.e615.
- , , , , . House staff team workload and organization effects on patient outcomes in an academic general internal medicine inpatient service. Arch Intern Med. 2007;167(1):47–52.
- , . A "reverse july effect": association between timing of admission, medical team workload, and 30‐day readmission rate. J Grad Med Educ. 2014;6(1):65–70.
- , , , , . An observational study of nurse staffing ratios and hospital readmission among children admitted for common conditions. BMJ Qual Saf. 2013;22(9):735–742.
- , , , , . Day of discharge and hospital readmission rates within 30 days in children: a population‐based study. Paediatr Child Health. 2006;11(7):409–412.
- , , , , . Differences between early and late readmissions among patients: a cohort study. Ann Intern Med. 2015;162(11):741–749.
- , , , . A comparison of in‐hospital mortality risk conferred by high hospital occupancy, differences in nurse staffing levels, weekend admission, and seasonal influenza. Med Care. 2010;48(3):224–232.
- , . Mortality among patients admitted to hospitals on weekends as compared with weekdays. N Engl J Med. 2001;345(9):663–668.
- , , , . Effects of weekend admission and hospital teaching status on in‐hospital mortality. Am J Med. 2004;117(3):151–157.
- , , . Weekend admission for myocardial infarction. N Engl J Med. 2007;357(1):86–87; author reply 87–88.
- , , , et al. The "weekend effect" in pediatric surgery—increased mortality for children undergoing urgent surgery during the weekend. J Pediatr Surg. 2014;49(7):1087–1091.
- , , , , , Paediatric Intensive Care Audit Network (PICANet). Effects of out‐of‐hours and winter admissions and number of patients per unit on mortality in pediatric intensive care. J Pediatr. 2013;163(4):1039–1044.e1035.
- , , , . Do weekends or evenings matter in a pediatric intensive care unit? Pediatr Crit Care Med. 2005;6(5):523–530.
- , , , , . Pediatric complex chronic conditions classification system version 2: updated for ICD‐10 and complex medical technology dependence and transplantation. BMC Pediatr. 2014;14:199.
- , , , et al. Using hospital designation to identify unplanned pediatric readmissions [abstract]. J Hosp Med. Available at: http://www.shmabstracts.com/abstract/using‐hospital‐designation‐to‐identify‐unplanned‐pediatric‐readmissions. Accessed July 15, 2015.
- , , , et al. Rates and impact of potentially preventable readmissions at children's hospitals. J Pediatr. 2015;166(3):613–619.e615.
- , , , , . House staff team workload and organization effects on patient outcomes in an academic general internal medicine inpatient service. Arch Intern Med. 2007;167(1):47–52.
- , . A "reverse july effect": association between timing of admission, medical team workload, and 30‐day readmission rate. J Grad Med Educ. 2014;6(1):65–70.
- , , , , . An observational study of nurse staffing ratios and hospital readmission among children admitted for common conditions. BMJ Qual Saf. 2013;22(9):735–742.
- , , , , . Day of discharge and hospital readmission rates within 30 days in children: a population‐based study. Paediatr Child Health. 2006;11(7):409–412.
- , , , , . Differences between early and late readmissions among patients: a cohort study. Ann Intern Med. 2015;162(11):741–749.
Pediatric Discharge Systematic Review
The process of discharging a pediatric patient from an acute care facility is currently fraught with difficulties. More than 20% of parents report problems in the transition of care from the hospital to the home and ambulatory care setting.[1] Clinical providers likewise note communication challenges around the time of discharge,[2, 3] especially when inpatient and outpatient providers are different, as with the hospitalist model.[4] Poor communication and problems in discharge transition and continuity of care often culminate in adverse events,[5, 6] including return to emergency department (ED) care and hospital readmission.[7]
Thirty‐day readmissions are common for certain pediatric conditions, such as oncologic diseases, transplantation, and sickle cell anemia and vary significantly across children's hospitals.[8] Discharge planning may decrease 30‐day readmissions in hospitalized adults[9]; however, it is not clear that the same is true in children. Both the preventability of pediatric readmissions[10] and the extent to which readmissions reflect suboptimal care[11] are subjects of debate. Despite these uncertainties, collaborative efforts intended to decrease pediatric readmissions[12] and improve discharge transitions[13, 14] are underway.
To inform these debates and efforts, we undertook a systematic review of the evidence of hospital‐initiated interventions to reduce repeat utilization of the ED and hospital. Acknowledging that existing evidence for condition‐specific discharge interventions in pediatrics might be limited, we sought to identify common elements of successful interventions across pediatric conditions.
METHODS
Search Strategy
With the assistance of a research librarian, we searched MEDLINE and CINAHL (Cumulative Index to Nursing and Allied Health Literature) from the inception of these databases through to March 28, 2012 (for search strategies, see the Supporting Information, Appendix, Part 1, in the online version of this article).
Study Selection
Two authors (K.A. and C.K.) independently reviewed abstracts identified by the initial search, as well as abstracts of references of included articles. Eligibility criteria for inclusion in full review included: (1) discharge‐oriented process or intervention initiated in the inpatient setting, (2) study outcomes related to subsequent utilization including hospital readmission or emergency department visit after hospitalization, (3) child‐ or adolescent‐focused or child‐specific results presented separately, and (4) written or available in English. If abstract review did not sufficiently clarify whether all eligibility criteria were met, the article was included in the full review. Two authors (K.A. and C.K.) independently reviewed articles meeting criteria for full review to determine eligibility. Disagreements regarding inclusion in the final analysis were discussed with all 4 authors. We excluded studies in countries with low or lower‐middle incomes,[15] as discharge interventions in these countries may not be broadly applicable.
Data Abstraction, Quality Assessment, and Data Synthesis
Two authors (K.A. and C.K.) independently abstracted data using a modified Cochrane Collaboration data collection form.[16] We independently scored the included studies using the Downs and Black checklist, which assesses the risk of bias and the quality of both randomized and nonrandomized studies.[17] This checklist yields a composite score of 0 to 28 points, excluding the item assessing power. As many studies either lacked power calculations or included power calculations based on outcomes not included in our review, we performed calculations to determine the sample size needed to detect a decrease in readmission or ED utilization by 20% from baseline or control rates. Due to the heterogeneous nature of included studies in terms of population, interventions, study design, and outcomes, meta‐analysis was not performed.
RESULTS
Electronic search yielded a total of 1296 unique citations. Review of abstracts identified 40 studies for full article review. We identified 10 articles that met all inclusion criteria. Subsequent review of references of included articles identified 20 additional articles for full review, 7 of which met all inclusion criteria. However, 3 articles[18, 19, 20] assessed the impact of violence interventions primarily on preventing reinjury and recidivism and thus were excluded (see Supporting Information, Appendix, Part 2, in the online version of this article for findings of the 3 articles). In total, we included 14 articles in our review[21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34] (Figure 1).
Patient Populations and Intervention Timing and Components
Studies varied regarding the specific medical conditions they evaluated. Eight of the papers reported discharge interventions for children with asthma, 5 papers focused on discharge from the neonatal intensive care unit (NICU), and a final study discussed a discharge intervention for children with cancer (Table 1). Although our primary goal was to synthesize discharge interventions across pediatric conditions, we provide a summary of discharge interventions by condition (see Supporting Information, Appendix, Part 3, in the online version of this article).
| Author, Year | Study Design | Age | Inclusion | Exclusion | Intervention | Control |
|---|---|---|---|---|---|---|
| ||||||
| Asthma | ||||||
| Davis, 2011[21] | Retrospective matched case control | 12 months18 years | Admitted for asthma at a single hospital in California. | 45 minutes of enhanced asthma education and phone call 3 weeks after discharge (n=698) | Patients were matched on age and past utilization who received standard education/care (n=698) | |
| Espinoza‐Palma, 2009[22] | RCT | 515 years | Admitted for asthma at a single hospital in Chile. | Chronic lung disease or neurologic alteration. | Self‐management education program with a postdischarge game to reinforce educational concepts (n=42) | Standard education (n=46) |
| Ng, 2006[23] | RCT | 215 years | Admitted for asthma in a pediatric ward at a single hospital in China. | Admitted to PICU or non‐Chinese speaking. | Evaluation by asthma nurse, animated asthma education booklet, 50‐minute discharge teaching session, follow‐up by phone at 1 week (n=55) | Evaluation by asthma nurse by physician referral, a written asthma education booklet, 30‐minute discharge teaching session (n=45) |
| Stevens, 2002[24] | RCT | 18 months5 years | In ED or admitted with primary diagnosis of asthma/wheezing at 2 hospitals in the United Kingdom. | Admitted when no researcher available. | Enhanced asthma education and follow‐up in a clinic 1 month after encounter (n=101) | Usual care (n=99) |
| Wesseldine, 1999[25] | RCT | 216 years | Admitted for asthma at a single hospital in the United Kingdom. | Admitted when no researcher available. | 20 minutes of enhanced asthma education including: guided self‐management plan, booklet, asthma hotline contact, and sometimes oral steroids (n=80) | Standard discharge that varied by provider (n=80) |
| Madge, 1997[26] | RCT | 214 years | Admitted for asthma at a single hospital in the United Kingdom. | Admitted on weekend. | 45 minutes of enhanced asthma education with written asthma plan, a nurse follow‐up visit 23 weeks postdischarge, telephone support, and a course of oral steroids (n=96) | Standard education (did not include written asthma plan) (n=105) |
| Taggart, 1991[27] | Pre‐post | 612 years | Admitted for asthma at single institution in Washington, DC with history of at least one ED visit in prior 6 months. | If resided outside of metro area. | Received written educational materials, adherence assistance, discussed emotions of asthma, video education provided, and tailored nursing interactions (n=40) | Enrolled patient's prior utilization |
| Mitchell, 1986[28] | RCT | >2 years | Admitted for asthma at single institution in New Zealand. | Having a previous life‐threatening attack. | 6 monthly postdischarge education sessions on lung anatomy/physiology, triggers and avoidance, asthma medication, advice on when and where to seek care (n=94 children of European descent, n=84 children of Polynesian descent) | Standard discharge (n=106 children of European descent; n=84 children of Polynesian descent) |
| Cancer | ||||||
| Caliskan Yilmaz, 2009[29] | Quasiexperimental | <18 years | New oncologic diagnoses in hospital in Turkey. | Children who died during follow‐up. | Frequent needs assessment, education, home visits, fever guidance, telephone consultation, and manual for home care; patients lived in Izmir (n=25) | Routine hospital services without formal education; patients lived outside of Izmir (n=24) |
| NICU | ||||||
| Broyles, 2000[30] | RCT | Neonate | Infants with birth weight <1500 g with mechanical vent use in 48 hours of life, born at single NICU in Texas. | Infant death, infant adopted or moved out of enrollment county. | Specialized follow‐up available 5 days a week for well or sick visits; access to medical advice via phone 24 hours a day, transportation to ED provided when needed; home visitation, parent education, and "foster grandmother" offered (n=446) | Specialized follow‐up available 2 mornings a week for well or sick visits; all other sick visits to be made through acute care clinic or ED (n=441) |
| Finello, 1998[31] | RCT | Neonate | Infants with birth weight between 750 and1750 g; discharged from 2 NICUs in California. | Infants with gross abnormalities. | Three separate intervention groups (n=20 in each): (1) home healthhome visits during the first 4 weeks after discharge, with physician consultation available at all times; (2) home visitinghealth and development support, parental support, support with referral services for 2 years after discharge; (3) home health and home visiting arms combined | Standard discharge (n=20). |
| Kotagal, 1995[32] | Pre‐post | Neonate | Infants discharged from a single NICU in Ohio. | Patients (n=257) discharged after restructuring of discharge practices including: removal of discharge weight criteria, engagement of family prior to discharge, evaluation of home environment prior to discharge, and arrangement of home health visits and follow‐up | Patients discharged before discharge restructuring (n=483) | |
| Casiro, 1993[33] | RCT | Neonate | Infants meeting discharge criteria from 1 of 2 NICUs in Canada. | Congenital anomalies, chronic neonatal illness, parent refusal, family complications, and death. | Early discharge based on prespecified criteria with 8 weeks of services including: assistance with infant care, sibling care and housekeeping; nurse availability via phone; follow‐up phone calls and home visitation tailored to family need (n=50) | Discharged at the discretion of their attending physicians; standard newborn public health referral for routine follow‐up (n=50) |
| Brooten, 1986[34] | RCT | Neonate | Infants born <1500 g at a single NICU in Pennsylvania. | Death, life‐threatening congenital anomalies, grade 4 IVH, surgical history, O2 requirement >10 weeks, family complications. | Early discharge based on prespecified criteria with weekly education prior to discharge, postdischarge follow‐up phone call, and home nurse visitation; consistent nurse availability via phone (n=39) | Standard discharge practices with a discharge weight minimum of 2.2 kg (n=40) |
Studies varied regarding the timing and nature of the intervention components. Eight discharge interventions included a major inpatient component, in addition to outpatient support or follow‐up.[21, 23, 24, 25, 26, 29, 32, 34] Two studies included an inpatient education component only.[22, 27] The remainder were initiated during index hospitalization but focused primarily on home visitation, enhanced follow‐up, and support after discharge (Figure 2).[28, 30, 31, 33]
Outcome Assessment Methods
Readmission and subsequent ED utilization events were identified using multiple techniques. Some authors accessed claims records to capture all outcomes.[30, 33] Others relied on chart review.[21, 25, 26, 27, 28, 31, 32] One study supplemented hospital records with outpatient records.[24] Some investigators used parental reports.[22, 23, 31] Two studies did not describe methods for identifying postdischarge events.[29, 34]
Study Quality
The quality of the included studies varied (Table 2). Many of the studies had inadequate sample size to detect a difference in either readmission or ED visit subsequent to discharge. Eight studies found differences in either subsequent ED utilization, hospitalization, or both and were considered adequately powered for these specific outcomes.[21, 23, 25, 26, 28, 30, 31, 32] In contrast, among studies with readmission as an outcome, 6 were not adequately powered to detect a difference in this particular outcome.[24, 30, 31, 32, 33, 34] In these 6 studies, all except 1 study30 had <10% of the sample size required to detect differences in readmission. Further, 2 studies that examined ED utilization were underpowered to detect differences between intervention and control groups.[24, 26] We were unable to perform power calculations for 3 studies,[22, 27, 29] as the authors presented the number of events without clear denominators.
| Author, Year | Study Design | D&B Score* | Adequately Powered (Yes/No)** | Timing of Outcome | Major Findings | Major Limitations |
|---|---|---|---|---|---|---|
| ||||||
| Asthma | ||||||
| Davis, 2011[21] | Retrospective matched case control | 14 | Readmission: N/A; ED: yes | 1 year | Patients with enhanced education had higher hazards of return to ED visit. | Intervention not randomized; only 29% of eligible children enrolled with unclear selection decisions due to lack of study personnel or caregiver presence in hospital; only 67% completed the intervention; 50% of patients were not local; follow‐up was not well described. |
| Espinoza‐Palma, 2009[22] | RCT | 19 | Readmission: b; ED:b | 1 year | No difference between the intervention and control in hospitalizations or ED visits. ED visits and hospitalizations decreased in year after compared to the year prior for both intervention and control. | Pre‐post analysis with similar effects in cases and controls, results may reflect regression to mean; follow‐up was not well described, and 12.5% who were lost to follow‐up were excluded from analysis; study was in Chile with different demographics than in the United States. |
| Ng, 2006[23] | RCT | 20 | Readmission: yes; ED: yes | 3 months | Patients in the intervention group were less likely to be readmitted or visit the ED. | Recruitment/refusal was not well described; number lost to follow‐up was not reported; study was in China with different demographics than the United States. |
| Stevens, 2002[24] | RCT | 20 | Readmission: no ED: no | 1 year | No differences between intervention and control for any outcomes. | 11% were lost to follow‐up; number of patients who refused was not reported; analysis did not adjust for site of recruitment (ED vs inpatient); 30% of children did not have a prior diagnosis of asthma; study was in England with different demographics than in the United States. |
| Wesseldine, 1999[25] | RCT | 20 | Readmission: yes; ED: yes | 6 months | Patients in intervention group less likely to be readmitted or visit ED. | Unclear if intervention group received oral steroids that might drive effect; number lost to follow‐up was not reported; high miss rate for recruitment; study was in England with different demographics than the United States. |
| Madge, 1997 [26] | RCT | 22 | Readmission: yes; ED: no | 214 months | Patients in intervention group were less likely to be readmitted compared to controls. No differences in repeat ED visits. | Unclear if education or oral steroids drove effect; number of patients who refused or were lost to follow‐not reported; time to outcome (214 months) varied for different patients, which may introduce bias given the seasonality of asthma; study was in Scotland with different demographics than the United States. |
| Taggart, 1991[27] | Pre‐post | 12 | Readmission:b; ED:b | 15 months | Overall there was no change in ED or hospitalization utilization from pre to post. When limited to children with severe asthma, there was a decrease in ED utilization after the intervention compared to prior ED use. | Use of historical utilization as a comparison does not account for potential effects of regression to mean or improvement with age; over one‐half of eligible patients were excluded due to lack of consent or inability to collect baseline data; inclusion criterion did not specify that prior utilization was necessarily for asthma exacerbation; number lost to follow‐up was not reported. |
| Mitchell, 1986[28] | RCT | 14 | Readmission: yesc; ED: N/A | 6 months and 618 months | Increase in percentage of readmission between 6 and 18 months for children of European descent. | Unclear exclusion criterion; full compliance with intervention only 52%; number of patients lost to follow‐up (outcome) was not reported; statistical analysis was not clearly described. |
| Cancer | ||||||
| Caliskan Yilmaz, 2009[29] | Quasiexperimental | 10 | Readmission:b; ED: N/A | Not specified | For the first readmission to the hospital, more of the readmissions were planned in the intervention group compared to the control group. Number of readmissions was not assessed. | Intervention was not randomized; children who died were excluded (4%); planned vs unplanned distinction not validated; unclear cointerventions regarding chemotherapy administration; recruitment and follow‐up was not well described; not all comparisons were described in methods. |
| NICU | ||||||
| Broyles, 2000[30] | RCT | 23 | Readmission: no; ED: yes | At 1 year adjusted age | Overall hospitalization rates were similar but there were fewer admissions to the ICU. Intervention group had fewer ED visits. Total costs were less in intervention group. | 10% refused to participate or consent was not sought, and 12% were excluded after randomization; different periods of follow‐up (outcomes observed at 1 year of life regardless of discharge timing); analysis did not adjust for site of recruitment (1 of 2 nurseries). |
| Finello, 1998[31] | RCT | 11 | Readmission: nod; ED: yes | At 6 months adjusted age and between 6 and 12 months adjusted age | No changes in hospitalization rates.d The home health+home visit arm had fewer ED visits between 6 and 12 months of life. Intervention was reported as saving money by decreasing initial length of stay. | Inclusion and exclusion criteria, recruitment/refusal, outcomes, and analysis plan were not clearly described; sample size was too small for effective randomization; different periods of follow‐up (outcomes observed at 1 year of life regardless of discharge timing); analysis did not adjust for site of recruitment; 15% of outcomes were missing. |
| Kotagal, 1995[32] | Pre‐post | 15 | Readmission: no; ED: yes | 14 days | Decreased number of ED visits in patients in intervention. No difference in readmission. Costs and length of stay were less in intervention. | Designed to decrease length of stay; pre‐post nature of study allows for possibility of other changes to practices other than the intervention. |
| Casiro, 1993[33] | RCT | 18 | Readmission: no; ED: N/A | 1 year of life | There were no differences in the readmissions or number of ambulatory care visits after discharge. Infants were discharged earlier in the intervention group, which resulted in cost savings. | Designed to decrease length of stay; 13% refused or were excluded due to family complications; and 8% were lost to follow‐up; different periods of follow‐up (outcomes observed at 1 year of life regardless of discharge timing); analysis did not adjust for site of recruitment (1 of 2 nurseries); 81% of infants were born to Caucasian women, which may limit generalizability. |
| Brooten, 1986[34] | RCT | 15 | Readmission: no; ED: N/A | 14 days and 18 months | No difference in readmission. Significantly lower charges during initial hospitalization for intervention group. | Designed to decrease length of stay; unclear when randomization occurred and exclusions unclear; 12.5% were excluded due to refusal or family issues; follow‐up not well described, and loss to follow‐up was unknown. |
Excluding the assessment of statistical power, Downs and Black scores ranged from 10 to 23 (maximum 28 possible points) indicating varying quality. As would be expected with discharge interventions, studies did not blind participants; 2 studies did, however, appropriately blind the outcome evaluators to intervention assignment.[22, 30] Even though 10 out of the 14 studies were randomized controlled trials, randomization may not have been completely effective due to sample size being too small for effective randomization,[31] large numbers of excluded subjects after randomization,[30] and unclear randomization process.[34] Several studies had varying follow‐up periods for patients within a given study. For example, 3 NICU studies assessed readmission at 1‐year corrected age,[30, 31, 33] creating the analytic difficulty that the amount of time a given patient was at risk for readmission was dependent on when the patient was discharged, yet this was not accounted for in the analyses. Only 2 studies demonstrated low rates of loss to follow‐up (<10%).[30, 33] The remainder of the studies either had high incompletion/loss to follow‐up rates (>10%)[22, 24, 31] or did not report rates.[21, 23, 25, 26, 27, 28, 29, 32, 34] Finally, 3 studies recruited patients from multiple sites,[24, 31, 33] and none adjusted for potential differences in effect based on enrollment site.
Findings Across Patient Populations Regarding Readmission
Of the 4 studies that demonstrated change in overall readmission,[23, 25, 26, 28] all were asthma focused; 3 demonstrated a decrease in readmissions,[23, 25, 26] and 1 an increase in readmissions.[28] The 3 effective interventions included 1‐on‐1 inpatient education delivered by an asthma nurse, in addition to postdischarge follow‐up support, either by telephone or clinic visit. Two of these interventions provided rescue oral steroids to some patients on discharge.[25, 26] In contrast, a study from New Zealand evaluated a series of postdischarge visits using an existing public health nurse infrastructure and demonstrated an increase in readmission between 6 to 18 months after admission in European children.[28] An additional study focused on outpatient support after discharge from the NICU, and demonstrated a lower frequency of readmission to the intensive care unit without overall reduction of hospital readmission (Tables 1 and 2).[30]
Findings Across Patient Populations Regarding Subsequent ED Visits
Of all the discharge interventions, 6 demonstrated differences in return to the ED after discharge. Five studies described a decrease in ED visits after hospitalization,[23, 25, 30, 31, 32] and 1 showed an increase.[21] Three studies in the NICU population demonstrated decreased ED utilization through a combination of augmented family engagement during hospitalization and/or enhanced support after discharge. Two inpatient asthma education interventions with structured postdischarge follow‐up decreased return visitation to the ED.[23, 26] The intervention that worsened subsequent ED utilization (ie, increased ED visit hazard compared to matched controls) provided enhanced inpatient education to a nonrandom group of children hospitalized with asthma and provided a follow‐up phone call 3 weeks after discharge (Tables 1 and 2).[21]
DISCUSSION
In this review, we synthesized evidence regarding pediatric hospital discharge‐focused interventions intended to reduce subsequent utilization through decreased readmission and ED visits. Our review identified 14 studies clustered in 3 clinical areas: asthma, NICU care (chiefly prematurity), and cancer. Overall, 6 interventions demonstrated a reduction either in subsequent hospitalization or ED use. Four of the 6 positive interventions included both an enhanced inpatient education and engagement component as well as enhanced follow‐up after discharge. Importantly, all of the interventions were multifaceted; thus, we could not ascertain which specific aspects of the interventions mediated the change. Many of the included studies had significant methodological limitations.
Current Conceptual Framework
There are a number of existing discharge transitional care frameworks from prior studies[35, 36] and professional societies.[37] The Stepping Up to the Plate (SUTTP) alliance, a collaborative of 9 professional organizations, including the American Academy of Pediatrics, introduced 1 such framework in 2007. SUTTP sought to enhance care transitions by outlining principles of discharge transitional care including: (1) enhanced accountability, (2) creation of a central coordination hub charged with communicating expectations for care, (3) clear and direct communication of treatment plans and follow‐up, (4) timely feedback/feed‐forward of relevant information, and (5) involvement of family member at every stage.[38] In the context of the SUTTP framework, we present 3 hypotheses based on our findings to guide future work.
Hypothesis: Appointing a Dedicated Individual or Coordinating Hub Reduces Subsequent Utilization
Ostensibly, each discharge intervention included in this review sought to enhance accountability of providers or their health systems for discharge transitional care. Two of the asthma interventions appointed a particular provider to coordinate the discharge transition and demonstrated reductions in readmission.[25, 26] The successful NICU discharge interventions provided an integrated accountability structure across the health system, with a transition of accountability to an outpatient provider or central coordinating hub available to provide assistance and resources for an extended period following discharge.
By contrast, interventions with more than 1 individual intervener or without a centrally coordinated system for discharge transitional care tended not to demonstrate reduction in subsequent utilization.[21, 24, 27, 28] In fact, the 1 asthma intervention that utilized a previously existing public health nurse infrastructure demonstrated an increase in readmission.[28] Future efforts to enhance transitional care might investigate directly the impact of accountability structure on subsequent utilization by varying the number of effector individuals or the organization to which they report (eg, hospital system vs public health department).
Hypothesis: Individualized Task Learning and Feedback Enhances Effectiveness
Studies varied with respect to the extent they incorporated the principles of enhanced communication of the treatment and follow‐up plan and timely feedback/feed‐forward of relevant information. Successful efforts, however, seemed to embrace these strategies. Each of the 3 interventions that demonstrated readmission reduction[23, 25, 26] developed an individualized treatment plan during hospitalization, with either a specific follow‐up plan or resources for outpatient support. Two of these interventions assessed asthma inhaler technique prior to discharge, creating an inpatient audit and feedback loop allowing for assessment of competence prior to discharge. Audit and feedback has demonstrated promise modifying provider behavior[39] and is a plausible approach to enhancing patient and family self‐care.
Hypothesis: Timing of Intervention Enhances Effectiveness
Discrete sentinel events such as inpatient admission, may serve as a teachable moment[40, 41] or a tipping point[42] for some patients/families to initiate behavior change. Four of the 6 positive studies had a robust inpatient education component. By providing enhanced inpatient support, providers may be engaging the family at a timely opportunity to improve care. Both timing of the intervention (at admission vs discharge) and content (education‐ vs family‐engagement focused) are likely important to their effect and should be further explored with prospective study.
Persistent Literature Gaps
Follow‐up with a primary care provider after discharge is another intervention that might decrease postdischarge utilization. We did not identify any studies that specifically examined primary care follow‐up. However, 2 studies[43, 44] that did not meet our inclusion criteria (because they included adults and did not stratify by age group in the analysis) examined any outpatient follow‐up after discharge using state‐specific Medicaid claims. One study found that outpatient follow‐up after sickle cell hospitalization was associated with lower rates of readmission.[43] The other found no difference in readmission across multiple conditions.[44] One recent review of outpatient follow‐up from the ED for asthma found that even when increases in follow‐up were achieved, no reduction in the subsequent utilization was observed.[45]
Additional important questions remain underexplored. First, are condition‐specific interventions superior to those that span conditions? All of the interventions that demonstrated reductions in readmission were condition‐specific, yet no generic interventions met our inclusion criteria. Importantly, only 1 study[29] in our review examined discharge processes from 1 of the pediatric conditions with the most variation[8] in readmission. Further, no studies focused on children with complex medical conditions, who are known to be at increased risk of readmission,[46] indicating a sizable knowledge gap persists in understanding how to prevent readmissions in the most vulnerable pediatric populations.
Lastly, who are the most appropriate effector individuals for discharge‐focused transitional care interventions? Demographically matched effector individuals have shown promise in improving care using community health workers.[47, 48] The degree to which the identity of the intervener mediates subsequent ED and hospital utilization warrants further investigation.
Limitations of This Systematic Review
The studies included in this review assessed different outcomes at different intervals, precluding meta‐analysis. With greater consistency in the collection of data on the quality of discharge processes and their subsequent outcomes, future studies may offer further clarity as to which discharge‐oriented practices are more effective than others. Because we only identified literature in 3 pediatric conditions, generalizability beyond these conditions may be limited. The settings of the interventions also occurred in multiple countries; we excluded countries from low or low‐middle incomes to facilitate generalizability. As many of the discharge processes contained multiple interventions, it is not possible to ascertain which, if any, singular action may decrease posthospitalization utilization. Additionally, some of the included interventions are older, and it is plausible that discharge processes have evolved with the expansion of the hospitalist model.
Methods of data collection influence the quality of results in the included studies. Most of the studies included in this review used either medical record review or parental self‐report of utilization. Parental report may be sufficient for hospitalizations and ED utilization; however, it is subject to recall bias. Chart review likely underestimates the number of postdischarge events, depending on the individual institution's proportion of the market and the tendency of individuals to seek care at multiple institutions. Claims data may offer the most accurate assessments of ED and hospital utilization and cost, but can be more difficult to obtain and do not provide the same potential for granularity as parent report or medical records review.
Finally, subsequent ED visits, readmissions, and cost may not be the best measures of the quality of discharge transitional care. A number of tools have been developed to more specifically evaluate the quality of transitional care in adults,[49, 50] including a validated instrument that consists of only 3 items,[50] which primarily assesses the extent to which patients are prepared for self‐care upon discharge. For pediatric populations, validated tools assessing caregiver experience with discharge[51] and discharge readiness[52] are also available. These instruments may assist those interested in assessing process‐related outcomes that specifically assess discharge transitional care elements and may mediate subsequent ED visits or hospitalizations.
CONCLUSION
Successful discharge interventions to reduce pediatric readmission and ED have some common features, including an individual or team with specialized knowledge of the condition that assumed responsibility for the inpatient‐to‐outpatient transition and offered ongoing support to the family following discharge. All studies included in our review examined multiple discharge interventions; however, many did not have enough participants to detect differences in the outcomes of interest. Future studies might adapt common features of effective interventions, which are consistent with professional societies' recommendations.
Acknowledgements
The authors thank Marisa Conte for her help with developing the search algorithms for the review.
Disclosures: Drs. Auger and Kenyon received salary support from the Robert Wood Johnson Foundation Clinical Scholars program. Dr. Feudtner does not have any funding sources to disclose. Dr. Davis is funded in part by the Michigan Department of Community Health to serve as the Chief Medical Executive. The views expressed herein are not necessarily the views of the Department of Community Health. The authors have no conflicts of interest to report.
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- , , , et al. Pediatric readmission prevalence and variability across hospitals. JAMA. 2013;309:372–380.
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- , , , , , . Preventability of early readmissions at a children's hospital. Pediatrics. 2012;131(1):e171–e181.
- , , , et al. State‐level child health system performance and the likelihood of readmission to children's hospitals. J Pediatr. 2010;157(1):98–102.e1.
- Ohio Children's Hospitals' solutions for patient safety. Available at: http://solutionsforpatientsafety.org/files/sps‐fact‐sheet.pdf. Accessed July 24, 2013.
- American Academy of Pediatrics. Value in inpatient pediatrics (VIP) network projects. Available at: http://www.aap.org/en‐us/professional‐resources/practice‐support/quality‐improvement/Quality‐Improvement‐Innovation‐Networks/Pages/Value‐in‐Inpatient‐Pediatrics‐Network‐Projects.aspx. Accessed July 24, 2013.
- Child Health Corporation of America. Resources for managing the patient discharge process. Available at: http://www.chca.com/news/index.html. Accessed October 31, 2013.
- The World Bank. World Development Indicators 2012. Available at: http://data.worldbank.org/sites/default/files/wdi‐2012‐ebook.pdf. Accessed July 5, 2013.
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- , , , et al. Effectiveness of asthma education with and without a self‐management plan in hospitalized children. J Asthma. 2009;46(9):906–910.
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The process of discharging a pediatric patient from an acute care facility is currently fraught with difficulties. More than 20% of parents report problems in the transition of care from the hospital to the home and ambulatory care setting.[1] Clinical providers likewise note communication challenges around the time of discharge,[2, 3] especially when inpatient and outpatient providers are different, as with the hospitalist model.[4] Poor communication and problems in discharge transition and continuity of care often culminate in adverse events,[5, 6] including return to emergency department (ED) care and hospital readmission.[7]
Thirty‐day readmissions are common for certain pediatric conditions, such as oncologic diseases, transplantation, and sickle cell anemia and vary significantly across children's hospitals.[8] Discharge planning may decrease 30‐day readmissions in hospitalized adults[9]; however, it is not clear that the same is true in children. Both the preventability of pediatric readmissions[10] and the extent to which readmissions reflect suboptimal care[11] are subjects of debate. Despite these uncertainties, collaborative efforts intended to decrease pediatric readmissions[12] and improve discharge transitions[13, 14] are underway.
To inform these debates and efforts, we undertook a systematic review of the evidence of hospital‐initiated interventions to reduce repeat utilization of the ED and hospital. Acknowledging that existing evidence for condition‐specific discharge interventions in pediatrics might be limited, we sought to identify common elements of successful interventions across pediatric conditions.
METHODS
Search Strategy
With the assistance of a research librarian, we searched MEDLINE and CINAHL (Cumulative Index to Nursing and Allied Health Literature) from the inception of these databases through to March 28, 2012 (for search strategies, see the Supporting Information, Appendix, Part 1, in the online version of this article).
Study Selection
Two authors (K.A. and C.K.) independently reviewed abstracts identified by the initial search, as well as abstracts of references of included articles. Eligibility criteria for inclusion in full review included: (1) discharge‐oriented process or intervention initiated in the inpatient setting, (2) study outcomes related to subsequent utilization including hospital readmission or emergency department visit after hospitalization, (3) child‐ or adolescent‐focused or child‐specific results presented separately, and (4) written or available in English. If abstract review did not sufficiently clarify whether all eligibility criteria were met, the article was included in the full review. Two authors (K.A. and C.K.) independently reviewed articles meeting criteria for full review to determine eligibility. Disagreements regarding inclusion in the final analysis were discussed with all 4 authors. We excluded studies in countries with low or lower‐middle incomes,[15] as discharge interventions in these countries may not be broadly applicable.
Data Abstraction, Quality Assessment, and Data Synthesis
Two authors (K.A. and C.K.) independently abstracted data using a modified Cochrane Collaboration data collection form.[16] We independently scored the included studies using the Downs and Black checklist, which assesses the risk of bias and the quality of both randomized and nonrandomized studies.[17] This checklist yields a composite score of 0 to 28 points, excluding the item assessing power. As many studies either lacked power calculations or included power calculations based on outcomes not included in our review, we performed calculations to determine the sample size needed to detect a decrease in readmission or ED utilization by 20% from baseline or control rates. Due to the heterogeneous nature of included studies in terms of population, interventions, study design, and outcomes, meta‐analysis was not performed.
RESULTS
Electronic search yielded a total of 1296 unique citations. Review of abstracts identified 40 studies for full article review. We identified 10 articles that met all inclusion criteria. Subsequent review of references of included articles identified 20 additional articles for full review, 7 of which met all inclusion criteria. However, 3 articles[18, 19, 20] assessed the impact of violence interventions primarily on preventing reinjury and recidivism and thus were excluded (see Supporting Information, Appendix, Part 2, in the online version of this article for findings of the 3 articles). In total, we included 14 articles in our review[21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34] (Figure 1).
Patient Populations and Intervention Timing and Components
Studies varied regarding the specific medical conditions they evaluated. Eight of the papers reported discharge interventions for children with asthma, 5 papers focused on discharge from the neonatal intensive care unit (NICU), and a final study discussed a discharge intervention for children with cancer (Table 1). Although our primary goal was to synthesize discharge interventions across pediatric conditions, we provide a summary of discharge interventions by condition (see Supporting Information, Appendix, Part 3, in the online version of this article).
| Author, Year | Study Design | Age | Inclusion | Exclusion | Intervention | Control |
|---|---|---|---|---|---|---|
| ||||||
| Asthma | ||||||
| Davis, 2011[21] | Retrospective matched case control | 12 months18 years | Admitted for asthma at a single hospital in California. | 45 minutes of enhanced asthma education and phone call 3 weeks after discharge (n=698) | Patients were matched on age and past utilization who received standard education/care (n=698) | |
| Espinoza‐Palma, 2009[22] | RCT | 515 years | Admitted for asthma at a single hospital in Chile. | Chronic lung disease or neurologic alteration. | Self‐management education program with a postdischarge game to reinforce educational concepts (n=42) | Standard education (n=46) |
| Ng, 2006[23] | RCT | 215 years | Admitted for asthma in a pediatric ward at a single hospital in China. | Admitted to PICU or non‐Chinese speaking. | Evaluation by asthma nurse, animated asthma education booklet, 50‐minute discharge teaching session, follow‐up by phone at 1 week (n=55) | Evaluation by asthma nurse by physician referral, a written asthma education booklet, 30‐minute discharge teaching session (n=45) |
| Stevens, 2002[24] | RCT | 18 months5 years | In ED or admitted with primary diagnosis of asthma/wheezing at 2 hospitals in the United Kingdom. | Admitted when no researcher available. | Enhanced asthma education and follow‐up in a clinic 1 month after encounter (n=101) | Usual care (n=99) |
| Wesseldine, 1999[25] | RCT | 216 years | Admitted for asthma at a single hospital in the United Kingdom. | Admitted when no researcher available. | 20 minutes of enhanced asthma education including: guided self‐management plan, booklet, asthma hotline contact, and sometimes oral steroids (n=80) | Standard discharge that varied by provider (n=80) |
| Madge, 1997[26] | RCT | 214 years | Admitted for asthma at a single hospital in the United Kingdom. | Admitted on weekend. | 45 minutes of enhanced asthma education with written asthma plan, a nurse follow‐up visit 23 weeks postdischarge, telephone support, and a course of oral steroids (n=96) | Standard education (did not include written asthma plan) (n=105) |
| Taggart, 1991[27] | Pre‐post | 612 years | Admitted for asthma at single institution in Washington, DC with history of at least one ED visit in prior 6 months. | If resided outside of metro area. | Received written educational materials, adherence assistance, discussed emotions of asthma, video education provided, and tailored nursing interactions (n=40) | Enrolled patient's prior utilization |
| Mitchell, 1986[28] | RCT | >2 years | Admitted for asthma at single institution in New Zealand. | Having a previous life‐threatening attack. | 6 monthly postdischarge education sessions on lung anatomy/physiology, triggers and avoidance, asthma medication, advice on when and where to seek care (n=94 children of European descent, n=84 children of Polynesian descent) | Standard discharge (n=106 children of European descent; n=84 children of Polynesian descent) |
| Cancer | ||||||
| Caliskan Yilmaz, 2009[29] | Quasiexperimental | <18 years | New oncologic diagnoses in hospital in Turkey. | Children who died during follow‐up. | Frequent needs assessment, education, home visits, fever guidance, telephone consultation, and manual for home care; patients lived in Izmir (n=25) | Routine hospital services without formal education; patients lived outside of Izmir (n=24) |
| NICU | ||||||
| Broyles, 2000[30] | RCT | Neonate | Infants with birth weight <1500 g with mechanical vent use in 48 hours of life, born at single NICU in Texas. | Infant death, infant adopted or moved out of enrollment county. | Specialized follow‐up available 5 days a week for well or sick visits; access to medical advice via phone 24 hours a day, transportation to ED provided when needed; home visitation, parent education, and "foster grandmother" offered (n=446) | Specialized follow‐up available 2 mornings a week for well or sick visits; all other sick visits to be made through acute care clinic or ED (n=441) |
| Finello, 1998[31] | RCT | Neonate | Infants with birth weight between 750 and1750 g; discharged from 2 NICUs in California. | Infants with gross abnormalities. | Three separate intervention groups (n=20 in each): (1) home healthhome visits during the first 4 weeks after discharge, with physician consultation available at all times; (2) home visitinghealth and development support, parental support, support with referral services for 2 years after discharge; (3) home health and home visiting arms combined | Standard discharge (n=20). |
| Kotagal, 1995[32] | Pre‐post | Neonate | Infants discharged from a single NICU in Ohio. | Patients (n=257) discharged after restructuring of discharge practices including: removal of discharge weight criteria, engagement of family prior to discharge, evaluation of home environment prior to discharge, and arrangement of home health visits and follow‐up | Patients discharged before discharge restructuring (n=483) | |
| Casiro, 1993[33] | RCT | Neonate | Infants meeting discharge criteria from 1 of 2 NICUs in Canada. | Congenital anomalies, chronic neonatal illness, parent refusal, family complications, and death. | Early discharge based on prespecified criteria with 8 weeks of services including: assistance with infant care, sibling care and housekeeping; nurse availability via phone; follow‐up phone calls and home visitation tailored to family need (n=50) | Discharged at the discretion of their attending physicians; standard newborn public health referral for routine follow‐up (n=50) |
| Brooten, 1986[34] | RCT | Neonate | Infants born <1500 g at a single NICU in Pennsylvania. | Death, life‐threatening congenital anomalies, grade 4 IVH, surgical history, O2 requirement >10 weeks, family complications. | Early discharge based on prespecified criteria with weekly education prior to discharge, postdischarge follow‐up phone call, and home nurse visitation; consistent nurse availability via phone (n=39) | Standard discharge practices with a discharge weight minimum of 2.2 kg (n=40) |
Studies varied regarding the timing and nature of the intervention components. Eight discharge interventions included a major inpatient component, in addition to outpatient support or follow‐up.[21, 23, 24, 25, 26, 29, 32, 34] Two studies included an inpatient education component only.[22, 27] The remainder were initiated during index hospitalization but focused primarily on home visitation, enhanced follow‐up, and support after discharge (Figure 2).[28, 30, 31, 33]
Outcome Assessment Methods
Readmission and subsequent ED utilization events were identified using multiple techniques. Some authors accessed claims records to capture all outcomes.[30, 33] Others relied on chart review.[21, 25, 26, 27, 28, 31, 32] One study supplemented hospital records with outpatient records.[24] Some investigators used parental reports.[22, 23, 31] Two studies did not describe methods for identifying postdischarge events.[29, 34]
Study Quality
The quality of the included studies varied (Table 2). Many of the studies had inadequate sample size to detect a difference in either readmission or ED visit subsequent to discharge. Eight studies found differences in either subsequent ED utilization, hospitalization, or both and were considered adequately powered for these specific outcomes.[21, 23, 25, 26, 28, 30, 31, 32] In contrast, among studies with readmission as an outcome, 6 were not adequately powered to detect a difference in this particular outcome.[24, 30, 31, 32, 33, 34] In these 6 studies, all except 1 study30 had <10% of the sample size required to detect differences in readmission. Further, 2 studies that examined ED utilization were underpowered to detect differences between intervention and control groups.[24, 26] We were unable to perform power calculations for 3 studies,[22, 27, 29] as the authors presented the number of events without clear denominators.
| Author, Year | Study Design | D&B Score* | Adequately Powered (Yes/No)** | Timing of Outcome | Major Findings | Major Limitations |
|---|---|---|---|---|---|---|
| ||||||
| Asthma | ||||||
| Davis, 2011[21] | Retrospective matched case control | 14 | Readmission: N/A; ED: yes | 1 year | Patients with enhanced education had higher hazards of return to ED visit. | Intervention not randomized; only 29% of eligible children enrolled with unclear selection decisions due to lack of study personnel or caregiver presence in hospital; only 67% completed the intervention; 50% of patients were not local; follow‐up was not well described. |
| Espinoza‐Palma, 2009[22] | RCT | 19 | Readmission: b; ED:b | 1 year | No difference between the intervention and control in hospitalizations or ED visits. ED visits and hospitalizations decreased in year after compared to the year prior for both intervention and control. | Pre‐post analysis with similar effects in cases and controls, results may reflect regression to mean; follow‐up was not well described, and 12.5% who were lost to follow‐up were excluded from analysis; study was in Chile with different demographics than in the United States. |
| Ng, 2006[23] | RCT | 20 | Readmission: yes; ED: yes | 3 months | Patients in the intervention group were less likely to be readmitted or visit the ED. | Recruitment/refusal was not well described; number lost to follow‐up was not reported; study was in China with different demographics than the United States. |
| Stevens, 2002[24] | RCT | 20 | Readmission: no ED: no | 1 year | No differences between intervention and control for any outcomes. | 11% were lost to follow‐up; number of patients who refused was not reported; analysis did not adjust for site of recruitment (ED vs inpatient); 30% of children did not have a prior diagnosis of asthma; study was in England with different demographics than in the United States. |
| Wesseldine, 1999[25] | RCT | 20 | Readmission: yes; ED: yes | 6 months | Patients in intervention group less likely to be readmitted or visit ED. | Unclear if intervention group received oral steroids that might drive effect; number lost to follow‐up was not reported; high miss rate for recruitment; study was in England with different demographics than the United States. |
| Madge, 1997 [26] | RCT | 22 | Readmission: yes; ED: no | 214 months | Patients in intervention group were less likely to be readmitted compared to controls. No differences in repeat ED visits. | Unclear if education or oral steroids drove effect; number of patients who refused or were lost to follow‐not reported; time to outcome (214 months) varied for different patients, which may introduce bias given the seasonality of asthma; study was in Scotland with different demographics than the United States. |
| Taggart, 1991[27] | Pre‐post | 12 | Readmission:b; ED:b | 15 months | Overall there was no change in ED or hospitalization utilization from pre to post. When limited to children with severe asthma, there was a decrease in ED utilization after the intervention compared to prior ED use. | Use of historical utilization as a comparison does not account for potential effects of regression to mean or improvement with age; over one‐half of eligible patients were excluded due to lack of consent or inability to collect baseline data; inclusion criterion did not specify that prior utilization was necessarily for asthma exacerbation; number lost to follow‐up was not reported. |
| Mitchell, 1986[28] | RCT | 14 | Readmission: yesc; ED: N/A | 6 months and 618 months | Increase in percentage of readmission between 6 and 18 months for children of European descent. | Unclear exclusion criterion; full compliance with intervention only 52%; number of patients lost to follow‐up (outcome) was not reported; statistical analysis was not clearly described. |
| Cancer | ||||||
| Caliskan Yilmaz, 2009[29] | Quasiexperimental | 10 | Readmission:b; ED: N/A | Not specified | For the first readmission to the hospital, more of the readmissions were planned in the intervention group compared to the control group. Number of readmissions was not assessed. | Intervention was not randomized; children who died were excluded (4%); planned vs unplanned distinction not validated; unclear cointerventions regarding chemotherapy administration; recruitment and follow‐up was not well described; not all comparisons were described in methods. |
| NICU | ||||||
| Broyles, 2000[30] | RCT | 23 | Readmission: no; ED: yes | At 1 year adjusted age | Overall hospitalization rates were similar but there were fewer admissions to the ICU. Intervention group had fewer ED visits. Total costs were less in intervention group. | 10% refused to participate or consent was not sought, and 12% were excluded after randomization; different periods of follow‐up (outcomes observed at 1 year of life regardless of discharge timing); analysis did not adjust for site of recruitment (1 of 2 nurseries). |
| Finello, 1998[31] | RCT | 11 | Readmission: nod; ED: yes | At 6 months adjusted age and between 6 and 12 months adjusted age | No changes in hospitalization rates.d The home health+home visit arm had fewer ED visits between 6 and 12 months of life. Intervention was reported as saving money by decreasing initial length of stay. | Inclusion and exclusion criteria, recruitment/refusal, outcomes, and analysis plan were not clearly described; sample size was too small for effective randomization; different periods of follow‐up (outcomes observed at 1 year of life regardless of discharge timing); analysis did not adjust for site of recruitment; 15% of outcomes were missing. |
| Kotagal, 1995[32] | Pre‐post | 15 | Readmission: no; ED: yes | 14 days | Decreased number of ED visits in patients in intervention. No difference in readmission. Costs and length of stay were less in intervention. | Designed to decrease length of stay; pre‐post nature of study allows for possibility of other changes to practices other than the intervention. |
| Casiro, 1993[33] | RCT | 18 | Readmission: no; ED: N/A | 1 year of life | There were no differences in the readmissions or number of ambulatory care visits after discharge. Infants were discharged earlier in the intervention group, which resulted in cost savings. | Designed to decrease length of stay; 13% refused or were excluded due to family complications; and 8% were lost to follow‐up; different periods of follow‐up (outcomes observed at 1 year of life regardless of discharge timing); analysis did not adjust for site of recruitment (1 of 2 nurseries); 81% of infants were born to Caucasian women, which may limit generalizability. |
| Brooten, 1986[34] | RCT | 15 | Readmission: no; ED: N/A | 14 days and 18 months | No difference in readmission. Significantly lower charges during initial hospitalization for intervention group. | Designed to decrease length of stay; unclear when randomization occurred and exclusions unclear; 12.5% were excluded due to refusal or family issues; follow‐up not well described, and loss to follow‐up was unknown. |
Excluding the assessment of statistical power, Downs and Black scores ranged from 10 to 23 (maximum 28 possible points) indicating varying quality. As would be expected with discharge interventions, studies did not blind participants; 2 studies did, however, appropriately blind the outcome evaluators to intervention assignment.[22, 30] Even though 10 out of the 14 studies were randomized controlled trials, randomization may not have been completely effective due to sample size being too small for effective randomization,[31] large numbers of excluded subjects after randomization,[30] and unclear randomization process.[34] Several studies had varying follow‐up periods for patients within a given study. For example, 3 NICU studies assessed readmission at 1‐year corrected age,[30, 31, 33] creating the analytic difficulty that the amount of time a given patient was at risk for readmission was dependent on when the patient was discharged, yet this was not accounted for in the analyses. Only 2 studies demonstrated low rates of loss to follow‐up (<10%).[30, 33] The remainder of the studies either had high incompletion/loss to follow‐up rates (>10%)[22, 24, 31] or did not report rates.[21, 23, 25, 26, 27, 28, 29, 32, 34] Finally, 3 studies recruited patients from multiple sites,[24, 31, 33] and none adjusted for potential differences in effect based on enrollment site.
Findings Across Patient Populations Regarding Readmission
Of the 4 studies that demonstrated change in overall readmission,[23, 25, 26, 28] all were asthma focused; 3 demonstrated a decrease in readmissions,[23, 25, 26] and 1 an increase in readmissions.[28] The 3 effective interventions included 1‐on‐1 inpatient education delivered by an asthma nurse, in addition to postdischarge follow‐up support, either by telephone or clinic visit. Two of these interventions provided rescue oral steroids to some patients on discharge.[25, 26] In contrast, a study from New Zealand evaluated a series of postdischarge visits using an existing public health nurse infrastructure and demonstrated an increase in readmission between 6 to 18 months after admission in European children.[28] An additional study focused on outpatient support after discharge from the NICU, and demonstrated a lower frequency of readmission to the intensive care unit without overall reduction of hospital readmission (Tables 1 and 2).[30]
Findings Across Patient Populations Regarding Subsequent ED Visits
Of all the discharge interventions, 6 demonstrated differences in return to the ED after discharge. Five studies described a decrease in ED visits after hospitalization,[23, 25, 30, 31, 32] and 1 showed an increase.[21] Three studies in the NICU population demonstrated decreased ED utilization through a combination of augmented family engagement during hospitalization and/or enhanced support after discharge. Two inpatient asthma education interventions with structured postdischarge follow‐up decreased return visitation to the ED.[23, 26] The intervention that worsened subsequent ED utilization (ie, increased ED visit hazard compared to matched controls) provided enhanced inpatient education to a nonrandom group of children hospitalized with asthma and provided a follow‐up phone call 3 weeks after discharge (Tables 1 and 2).[21]
DISCUSSION
In this review, we synthesized evidence regarding pediatric hospital discharge‐focused interventions intended to reduce subsequent utilization through decreased readmission and ED visits. Our review identified 14 studies clustered in 3 clinical areas: asthma, NICU care (chiefly prematurity), and cancer. Overall, 6 interventions demonstrated a reduction either in subsequent hospitalization or ED use. Four of the 6 positive interventions included both an enhanced inpatient education and engagement component as well as enhanced follow‐up after discharge. Importantly, all of the interventions were multifaceted; thus, we could not ascertain which specific aspects of the interventions mediated the change. Many of the included studies had significant methodological limitations.
Current Conceptual Framework
There are a number of existing discharge transitional care frameworks from prior studies[35, 36] and professional societies.[37] The Stepping Up to the Plate (SUTTP) alliance, a collaborative of 9 professional organizations, including the American Academy of Pediatrics, introduced 1 such framework in 2007. SUTTP sought to enhance care transitions by outlining principles of discharge transitional care including: (1) enhanced accountability, (2) creation of a central coordination hub charged with communicating expectations for care, (3) clear and direct communication of treatment plans and follow‐up, (4) timely feedback/feed‐forward of relevant information, and (5) involvement of family member at every stage.[38] In the context of the SUTTP framework, we present 3 hypotheses based on our findings to guide future work.
Hypothesis: Appointing a Dedicated Individual or Coordinating Hub Reduces Subsequent Utilization
Ostensibly, each discharge intervention included in this review sought to enhance accountability of providers or their health systems for discharge transitional care. Two of the asthma interventions appointed a particular provider to coordinate the discharge transition and demonstrated reductions in readmission.[25, 26] The successful NICU discharge interventions provided an integrated accountability structure across the health system, with a transition of accountability to an outpatient provider or central coordinating hub available to provide assistance and resources for an extended period following discharge.
By contrast, interventions with more than 1 individual intervener or without a centrally coordinated system for discharge transitional care tended not to demonstrate reduction in subsequent utilization.[21, 24, 27, 28] In fact, the 1 asthma intervention that utilized a previously existing public health nurse infrastructure demonstrated an increase in readmission.[28] Future efforts to enhance transitional care might investigate directly the impact of accountability structure on subsequent utilization by varying the number of effector individuals or the organization to which they report (eg, hospital system vs public health department).
Hypothesis: Individualized Task Learning and Feedback Enhances Effectiveness
Studies varied with respect to the extent they incorporated the principles of enhanced communication of the treatment and follow‐up plan and timely feedback/feed‐forward of relevant information. Successful efforts, however, seemed to embrace these strategies. Each of the 3 interventions that demonstrated readmission reduction[23, 25, 26] developed an individualized treatment plan during hospitalization, with either a specific follow‐up plan or resources for outpatient support. Two of these interventions assessed asthma inhaler technique prior to discharge, creating an inpatient audit and feedback loop allowing for assessment of competence prior to discharge. Audit and feedback has demonstrated promise modifying provider behavior[39] and is a plausible approach to enhancing patient and family self‐care.
Hypothesis: Timing of Intervention Enhances Effectiveness
Discrete sentinel events such as inpatient admission, may serve as a teachable moment[40, 41] or a tipping point[42] for some patients/families to initiate behavior change. Four of the 6 positive studies had a robust inpatient education component. By providing enhanced inpatient support, providers may be engaging the family at a timely opportunity to improve care. Both timing of the intervention (at admission vs discharge) and content (education‐ vs family‐engagement focused) are likely important to their effect and should be further explored with prospective study.
Persistent Literature Gaps
Follow‐up with a primary care provider after discharge is another intervention that might decrease postdischarge utilization. We did not identify any studies that specifically examined primary care follow‐up. However, 2 studies[43, 44] that did not meet our inclusion criteria (because they included adults and did not stratify by age group in the analysis) examined any outpatient follow‐up after discharge using state‐specific Medicaid claims. One study found that outpatient follow‐up after sickle cell hospitalization was associated with lower rates of readmission.[43] The other found no difference in readmission across multiple conditions.[44] One recent review of outpatient follow‐up from the ED for asthma found that even when increases in follow‐up were achieved, no reduction in the subsequent utilization was observed.[45]
Additional important questions remain underexplored. First, are condition‐specific interventions superior to those that span conditions? All of the interventions that demonstrated reductions in readmission were condition‐specific, yet no generic interventions met our inclusion criteria. Importantly, only 1 study[29] in our review examined discharge processes from 1 of the pediatric conditions with the most variation[8] in readmission. Further, no studies focused on children with complex medical conditions, who are known to be at increased risk of readmission,[46] indicating a sizable knowledge gap persists in understanding how to prevent readmissions in the most vulnerable pediatric populations.
Lastly, who are the most appropriate effector individuals for discharge‐focused transitional care interventions? Demographically matched effector individuals have shown promise in improving care using community health workers.[47, 48] The degree to which the identity of the intervener mediates subsequent ED and hospital utilization warrants further investigation.
Limitations of This Systematic Review
The studies included in this review assessed different outcomes at different intervals, precluding meta‐analysis. With greater consistency in the collection of data on the quality of discharge processes and their subsequent outcomes, future studies may offer further clarity as to which discharge‐oriented practices are more effective than others. Because we only identified literature in 3 pediatric conditions, generalizability beyond these conditions may be limited. The settings of the interventions also occurred in multiple countries; we excluded countries from low or low‐middle incomes to facilitate generalizability. As many of the discharge processes contained multiple interventions, it is not possible to ascertain which, if any, singular action may decrease posthospitalization utilization. Additionally, some of the included interventions are older, and it is plausible that discharge processes have evolved with the expansion of the hospitalist model.
Methods of data collection influence the quality of results in the included studies. Most of the studies included in this review used either medical record review or parental self‐report of utilization. Parental report may be sufficient for hospitalizations and ED utilization; however, it is subject to recall bias. Chart review likely underestimates the number of postdischarge events, depending on the individual institution's proportion of the market and the tendency of individuals to seek care at multiple institutions. Claims data may offer the most accurate assessments of ED and hospital utilization and cost, but can be more difficult to obtain and do not provide the same potential for granularity as parent report or medical records review.
Finally, subsequent ED visits, readmissions, and cost may not be the best measures of the quality of discharge transitional care. A number of tools have been developed to more specifically evaluate the quality of transitional care in adults,[49, 50] including a validated instrument that consists of only 3 items,[50] which primarily assesses the extent to which patients are prepared for self‐care upon discharge. For pediatric populations, validated tools assessing caregiver experience with discharge[51] and discharge readiness[52] are also available. These instruments may assist those interested in assessing process‐related outcomes that specifically assess discharge transitional care elements and may mediate subsequent ED visits or hospitalizations.
CONCLUSION
Successful discharge interventions to reduce pediatric readmission and ED have some common features, including an individual or team with specialized knowledge of the condition that assumed responsibility for the inpatient‐to‐outpatient transition and offered ongoing support to the family following discharge. All studies included in our review examined multiple discharge interventions; however, many did not have enough participants to detect differences in the outcomes of interest. Future studies might adapt common features of effective interventions, which are consistent with professional societies' recommendations.
Acknowledgements
The authors thank Marisa Conte for her help with developing the search algorithms for the review.
Disclosures: Drs. Auger and Kenyon received salary support from the Robert Wood Johnson Foundation Clinical Scholars program. Dr. Feudtner does not have any funding sources to disclose. Dr. Davis is funded in part by the Michigan Department of Community Health to serve as the Chief Medical Executive. The views expressed herein are not necessarily the views of the Department of Community Health. The authors have no conflicts of interest to report.
The process of discharging a pediatric patient from an acute care facility is currently fraught with difficulties. More than 20% of parents report problems in the transition of care from the hospital to the home and ambulatory care setting.[1] Clinical providers likewise note communication challenges around the time of discharge,[2, 3] especially when inpatient and outpatient providers are different, as with the hospitalist model.[4] Poor communication and problems in discharge transition and continuity of care often culminate in adverse events,[5, 6] including return to emergency department (ED) care and hospital readmission.[7]
Thirty‐day readmissions are common for certain pediatric conditions, such as oncologic diseases, transplantation, and sickle cell anemia and vary significantly across children's hospitals.[8] Discharge planning may decrease 30‐day readmissions in hospitalized adults[9]; however, it is not clear that the same is true in children. Both the preventability of pediatric readmissions[10] and the extent to which readmissions reflect suboptimal care[11] are subjects of debate. Despite these uncertainties, collaborative efforts intended to decrease pediatric readmissions[12] and improve discharge transitions[13, 14] are underway.
To inform these debates and efforts, we undertook a systematic review of the evidence of hospital‐initiated interventions to reduce repeat utilization of the ED and hospital. Acknowledging that existing evidence for condition‐specific discharge interventions in pediatrics might be limited, we sought to identify common elements of successful interventions across pediatric conditions.
METHODS
Search Strategy
With the assistance of a research librarian, we searched MEDLINE and CINAHL (Cumulative Index to Nursing and Allied Health Literature) from the inception of these databases through to March 28, 2012 (for search strategies, see the Supporting Information, Appendix, Part 1, in the online version of this article).
Study Selection
Two authors (K.A. and C.K.) independently reviewed abstracts identified by the initial search, as well as abstracts of references of included articles. Eligibility criteria for inclusion in full review included: (1) discharge‐oriented process or intervention initiated in the inpatient setting, (2) study outcomes related to subsequent utilization including hospital readmission or emergency department visit after hospitalization, (3) child‐ or adolescent‐focused or child‐specific results presented separately, and (4) written or available in English. If abstract review did not sufficiently clarify whether all eligibility criteria were met, the article was included in the full review. Two authors (K.A. and C.K.) independently reviewed articles meeting criteria for full review to determine eligibility. Disagreements regarding inclusion in the final analysis were discussed with all 4 authors. We excluded studies in countries with low or lower‐middle incomes,[15] as discharge interventions in these countries may not be broadly applicable.
Data Abstraction, Quality Assessment, and Data Synthesis
Two authors (K.A. and C.K.) independently abstracted data using a modified Cochrane Collaboration data collection form.[16] We independently scored the included studies using the Downs and Black checklist, which assesses the risk of bias and the quality of both randomized and nonrandomized studies.[17] This checklist yields a composite score of 0 to 28 points, excluding the item assessing power. As many studies either lacked power calculations or included power calculations based on outcomes not included in our review, we performed calculations to determine the sample size needed to detect a decrease in readmission or ED utilization by 20% from baseline or control rates. Due to the heterogeneous nature of included studies in terms of population, interventions, study design, and outcomes, meta‐analysis was not performed.
RESULTS
Electronic search yielded a total of 1296 unique citations. Review of abstracts identified 40 studies for full article review. We identified 10 articles that met all inclusion criteria. Subsequent review of references of included articles identified 20 additional articles for full review, 7 of which met all inclusion criteria. However, 3 articles[18, 19, 20] assessed the impact of violence interventions primarily on preventing reinjury and recidivism and thus were excluded (see Supporting Information, Appendix, Part 2, in the online version of this article for findings of the 3 articles). In total, we included 14 articles in our review[21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34] (Figure 1).
Patient Populations and Intervention Timing and Components
Studies varied regarding the specific medical conditions they evaluated. Eight of the papers reported discharge interventions for children with asthma, 5 papers focused on discharge from the neonatal intensive care unit (NICU), and a final study discussed a discharge intervention for children with cancer (Table 1). Although our primary goal was to synthesize discharge interventions across pediatric conditions, we provide a summary of discharge interventions by condition (see Supporting Information, Appendix, Part 3, in the online version of this article).
| Author, Year | Study Design | Age | Inclusion | Exclusion | Intervention | Control |
|---|---|---|---|---|---|---|
| ||||||
| Asthma | ||||||
| Davis, 2011[21] | Retrospective matched case control | 12 months18 years | Admitted for asthma at a single hospital in California. | 45 minutes of enhanced asthma education and phone call 3 weeks after discharge (n=698) | Patients were matched on age and past utilization who received standard education/care (n=698) | |
| Espinoza‐Palma, 2009[22] | RCT | 515 years | Admitted for asthma at a single hospital in Chile. | Chronic lung disease or neurologic alteration. | Self‐management education program with a postdischarge game to reinforce educational concepts (n=42) | Standard education (n=46) |
| Ng, 2006[23] | RCT | 215 years | Admitted for asthma in a pediatric ward at a single hospital in China. | Admitted to PICU or non‐Chinese speaking. | Evaluation by asthma nurse, animated asthma education booklet, 50‐minute discharge teaching session, follow‐up by phone at 1 week (n=55) | Evaluation by asthma nurse by physician referral, a written asthma education booklet, 30‐minute discharge teaching session (n=45) |
| Stevens, 2002[24] | RCT | 18 months5 years | In ED or admitted with primary diagnosis of asthma/wheezing at 2 hospitals in the United Kingdom. | Admitted when no researcher available. | Enhanced asthma education and follow‐up in a clinic 1 month after encounter (n=101) | Usual care (n=99) |
| Wesseldine, 1999[25] | RCT | 216 years | Admitted for asthma at a single hospital in the United Kingdom. | Admitted when no researcher available. | 20 minutes of enhanced asthma education including: guided self‐management plan, booklet, asthma hotline contact, and sometimes oral steroids (n=80) | Standard discharge that varied by provider (n=80) |
| Madge, 1997[26] | RCT | 214 years | Admitted for asthma at a single hospital in the United Kingdom. | Admitted on weekend. | 45 minutes of enhanced asthma education with written asthma plan, a nurse follow‐up visit 23 weeks postdischarge, telephone support, and a course of oral steroids (n=96) | Standard education (did not include written asthma plan) (n=105) |
| Taggart, 1991[27] | Pre‐post | 612 years | Admitted for asthma at single institution in Washington, DC with history of at least one ED visit in prior 6 months. | If resided outside of metro area. | Received written educational materials, adherence assistance, discussed emotions of asthma, video education provided, and tailored nursing interactions (n=40) | Enrolled patient's prior utilization |
| Mitchell, 1986[28] | RCT | >2 years | Admitted for asthma at single institution in New Zealand. | Having a previous life‐threatening attack. | 6 monthly postdischarge education sessions on lung anatomy/physiology, triggers and avoidance, asthma medication, advice on when and where to seek care (n=94 children of European descent, n=84 children of Polynesian descent) | Standard discharge (n=106 children of European descent; n=84 children of Polynesian descent) |
| Cancer | ||||||
| Caliskan Yilmaz, 2009[29] | Quasiexperimental | <18 years | New oncologic diagnoses in hospital in Turkey. | Children who died during follow‐up. | Frequent needs assessment, education, home visits, fever guidance, telephone consultation, and manual for home care; patients lived in Izmir (n=25) | Routine hospital services without formal education; patients lived outside of Izmir (n=24) |
| NICU | ||||||
| Broyles, 2000[30] | RCT | Neonate | Infants with birth weight <1500 g with mechanical vent use in 48 hours of life, born at single NICU in Texas. | Infant death, infant adopted or moved out of enrollment county. | Specialized follow‐up available 5 days a week for well or sick visits; access to medical advice via phone 24 hours a day, transportation to ED provided when needed; home visitation, parent education, and "foster grandmother" offered (n=446) | Specialized follow‐up available 2 mornings a week for well or sick visits; all other sick visits to be made through acute care clinic or ED (n=441) |
| Finello, 1998[31] | RCT | Neonate | Infants with birth weight between 750 and1750 g; discharged from 2 NICUs in California. | Infants with gross abnormalities. | Three separate intervention groups (n=20 in each): (1) home healthhome visits during the first 4 weeks after discharge, with physician consultation available at all times; (2) home visitinghealth and development support, parental support, support with referral services for 2 years after discharge; (3) home health and home visiting arms combined | Standard discharge (n=20). |
| Kotagal, 1995[32] | Pre‐post | Neonate | Infants discharged from a single NICU in Ohio. | Patients (n=257) discharged after restructuring of discharge practices including: removal of discharge weight criteria, engagement of family prior to discharge, evaluation of home environment prior to discharge, and arrangement of home health visits and follow‐up | Patients discharged before discharge restructuring (n=483) | |
| Casiro, 1993[33] | RCT | Neonate | Infants meeting discharge criteria from 1 of 2 NICUs in Canada. | Congenital anomalies, chronic neonatal illness, parent refusal, family complications, and death. | Early discharge based on prespecified criteria with 8 weeks of services including: assistance with infant care, sibling care and housekeeping; nurse availability via phone; follow‐up phone calls and home visitation tailored to family need (n=50) | Discharged at the discretion of their attending physicians; standard newborn public health referral for routine follow‐up (n=50) |
| Brooten, 1986[34] | RCT | Neonate | Infants born <1500 g at a single NICU in Pennsylvania. | Death, life‐threatening congenital anomalies, grade 4 IVH, surgical history, O2 requirement >10 weeks, family complications. | Early discharge based on prespecified criteria with weekly education prior to discharge, postdischarge follow‐up phone call, and home nurse visitation; consistent nurse availability via phone (n=39) | Standard discharge practices with a discharge weight minimum of 2.2 kg (n=40) |
Studies varied regarding the timing and nature of the intervention components. Eight discharge interventions included a major inpatient component, in addition to outpatient support or follow‐up.[21, 23, 24, 25, 26, 29, 32, 34] Two studies included an inpatient education component only.[22, 27] The remainder were initiated during index hospitalization but focused primarily on home visitation, enhanced follow‐up, and support after discharge (Figure 2).[28, 30, 31, 33]
Outcome Assessment Methods
Readmission and subsequent ED utilization events were identified using multiple techniques. Some authors accessed claims records to capture all outcomes.[30, 33] Others relied on chart review.[21, 25, 26, 27, 28, 31, 32] One study supplemented hospital records with outpatient records.[24] Some investigators used parental reports.[22, 23, 31] Two studies did not describe methods for identifying postdischarge events.[29, 34]
Study Quality
The quality of the included studies varied (Table 2). Many of the studies had inadequate sample size to detect a difference in either readmission or ED visit subsequent to discharge. Eight studies found differences in either subsequent ED utilization, hospitalization, or both and were considered adequately powered for these specific outcomes.[21, 23, 25, 26, 28, 30, 31, 32] In contrast, among studies with readmission as an outcome, 6 were not adequately powered to detect a difference in this particular outcome.[24, 30, 31, 32, 33, 34] In these 6 studies, all except 1 study30 had <10% of the sample size required to detect differences in readmission. Further, 2 studies that examined ED utilization were underpowered to detect differences between intervention and control groups.[24, 26] We were unable to perform power calculations for 3 studies,[22, 27, 29] as the authors presented the number of events without clear denominators.
| Author, Year | Study Design | D&B Score* | Adequately Powered (Yes/No)** | Timing of Outcome | Major Findings | Major Limitations |
|---|---|---|---|---|---|---|
| ||||||
| Asthma | ||||||
| Davis, 2011[21] | Retrospective matched case control | 14 | Readmission: N/A; ED: yes | 1 year | Patients with enhanced education had higher hazards of return to ED visit. | Intervention not randomized; only 29% of eligible children enrolled with unclear selection decisions due to lack of study personnel or caregiver presence in hospital; only 67% completed the intervention; 50% of patients were not local; follow‐up was not well described. |
| Espinoza‐Palma, 2009[22] | RCT | 19 | Readmission: b; ED:b | 1 year | No difference between the intervention and control in hospitalizations or ED visits. ED visits and hospitalizations decreased in year after compared to the year prior for both intervention and control. | Pre‐post analysis with similar effects in cases and controls, results may reflect regression to mean; follow‐up was not well described, and 12.5% who were lost to follow‐up were excluded from analysis; study was in Chile with different demographics than in the United States. |
| Ng, 2006[23] | RCT | 20 | Readmission: yes; ED: yes | 3 months | Patients in the intervention group were less likely to be readmitted or visit the ED. | Recruitment/refusal was not well described; number lost to follow‐up was not reported; study was in China with different demographics than the United States. |
| Stevens, 2002[24] | RCT | 20 | Readmission: no ED: no | 1 year | No differences between intervention and control for any outcomes. | 11% were lost to follow‐up; number of patients who refused was not reported; analysis did not adjust for site of recruitment (ED vs inpatient); 30% of children did not have a prior diagnosis of asthma; study was in England with different demographics than in the United States. |
| Wesseldine, 1999[25] | RCT | 20 | Readmission: yes; ED: yes | 6 months | Patients in intervention group less likely to be readmitted or visit ED. | Unclear if intervention group received oral steroids that might drive effect; number lost to follow‐up was not reported; high miss rate for recruitment; study was in England with different demographics than the United States. |
| Madge, 1997 [26] | RCT | 22 | Readmission: yes; ED: no | 214 months | Patients in intervention group were less likely to be readmitted compared to controls. No differences in repeat ED visits. | Unclear if education or oral steroids drove effect; number of patients who refused or were lost to follow‐not reported; time to outcome (214 months) varied for different patients, which may introduce bias given the seasonality of asthma; study was in Scotland with different demographics than the United States. |
| Taggart, 1991[27] | Pre‐post | 12 | Readmission:b; ED:b | 15 months | Overall there was no change in ED or hospitalization utilization from pre to post. When limited to children with severe asthma, there was a decrease in ED utilization after the intervention compared to prior ED use. | Use of historical utilization as a comparison does not account for potential effects of regression to mean or improvement with age; over one‐half of eligible patients were excluded due to lack of consent or inability to collect baseline data; inclusion criterion did not specify that prior utilization was necessarily for asthma exacerbation; number lost to follow‐up was not reported. |
| Mitchell, 1986[28] | RCT | 14 | Readmission: yesc; ED: N/A | 6 months and 618 months | Increase in percentage of readmission between 6 and 18 months for children of European descent. | Unclear exclusion criterion; full compliance with intervention only 52%; number of patients lost to follow‐up (outcome) was not reported; statistical analysis was not clearly described. |
| Cancer | ||||||
| Caliskan Yilmaz, 2009[29] | Quasiexperimental | 10 | Readmission:b; ED: N/A | Not specified | For the first readmission to the hospital, more of the readmissions were planned in the intervention group compared to the control group. Number of readmissions was not assessed. | Intervention was not randomized; children who died were excluded (4%); planned vs unplanned distinction not validated; unclear cointerventions regarding chemotherapy administration; recruitment and follow‐up was not well described; not all comparisons were described in methods. |
| NICU | ||||||
| Broyles, 2000[30] | RCT | 23 | Readmission: no; ED: yes | At 1 year adjusted age | Overall hospitalization rates were similar but there were fewer admissions to the ICU. Intervention group had fewer ED visits. Total costs were less in intervention group. | 10% refused to participate or consent was not sought, and 12% were excluded after randomization; different periods of follow‐up (outcomes observed at 1 year of life regardless of discharge timing); analysis did not adjust for site of recruitment (1 of 2 nurseries). |
| Finello, 1998[31] | RCT | 11 | Readmission: nod; ED: yes | At 6 months adjusted age and between 6 and 12 months adjusted age | No changes in hospitalization rates.d The home health+home visit arm had fewer ED visits between 6 and 12 months of life. Intervention was reported as saving money by decreasing initial length of stay. | Inclusion and exclusion criteria, recruitment/refusal, outcomes, and analysis plan were not clearly described; sample size was too small for effective randomization; different periods of follow‐up (outcomes observed at 1 year of life regardless of discharge timing); analysis did not adjust for site of recruitment; 15% of outcomes were missing. |
| Kotagal, 1995[32] | Pre‐post | 15 | Readmission: no; ED: yes | 14 days | Decreased number of ED visits in patients in intervention. No difference in readmission. Costs and length of stay were less in intervention. | Designed to decrease length of stay; pre‐post nature of study allows for possibility of other changes to practices other than the intervention. |
| Casiro, 1993[33] | RCT | 18 | Readmission: no; ED: N/A | 1 year of life | There were no differences in the readmissions or number of ambulatory care visits after discharge. Infants were discharged earlier in the intervention group, which resulted in cost savings. | Designed to decrease length of stay; 13% refused or were excluded due to family complications; and 8% were lost to follow‐up; different periods of follow‐up (outcomes observed at 1 year of life regardless of discharge timing); analysis did not adjust for site of recruitment (1 of 2 nurseries); 81% of infants were born to Caucasian women, which may limit generalizability. |
| Brooten, 1986[34] | RCT | 15 | Readmission: no; ED: N/A | 14 days and 18 months | No difference in readmission. Significantly lower charges during initial hospitalization for intervention group. | Designed to decrease length of stay; unclear when randomization occurred and exclusions unclear; 12.5% were excluded due to refusal or family issues; follow‐up not well described, and loss to follow‐up was unknown. |
Excluding the assessment of statistical power, Downs and Black scores ranged from 10 to 23 (maximum 28 possible points) indicating varying quality. As would be expected with discharge interventions, studies did not blind participants; 2 studies did, however, appropriately blind the outcome evaluators to intervention assignment.[22, 30] Even though 10 out of the 14 studies were randomized controlled trials, randomization may not have been completely effective due to sample size being too small for effective randomization,[31] large numbers of excluded subjects after randomization,[30] and unclear randomization process.[34] Several studies had varying follow‐up periods for patients within a given study. For example, 3 NICU studies assessed readmission at 1‐year corrected age,[30, 31, 33] creating the analytic difficulty that the amount of time a given patient was at risk for readmission was dependent on when the patient was discharged, yet this was not accounted for in the analyses. Only 2 studies demonstrated low rates of loss to follow‐up (<10%).[30, 33] The remainder of the studies either had high incompletion/loss to follow‐up rates (>10%)[22, 24, 31] or did not report rates.[21, 23, 25, 26, 27, 28, 29, 32, 34] Finally, 3 studies recruited patients from multiple sites,[24, 31, 33] and none adjusted for potential differences in effect based on enrollment site.
Findings Across Patient Populations Regarding Readmission
Of the 4 studies that demonstrated change in overall readmission,[23, 25, 26, 28] all were asthma focused; 3 demonstrated a decrease in readmissions,[23, 25, 26] and 1 an increase in readmissions.[28] The 3 effective interventions included 1‐on‐1 inpatient education delivered by an asthma nurse, in addition to postdischarge follow‐up support, either by telephone or clinic visit. Two of these interventions provided rescue oral steroids to some patients on discharge.[25, 26] In contrast, a study from New Zealand evaluated a series of postdischarge visits using an existing public health nurse infrastructure and demonstrated an increase in readmission between 6 to 18 months after admission in European children.[28] An additional study focused on outpatient support after discharge from the NICU, and demonstrated a lower frequency of readmission to the intensive care unit without overall reduction of hospital readmission (Tables 1 and 2).[30]
Findings Across Patient Populations Regarding Subsequent ED Visits
Of all the discharge interventions, 6 demonstrated differences in return to the ED after discharge. Five studies described a decrease in ED visits after hospitalization,[23, 25, 30, 31, 32] and 1 showed an increase.[21] Three studies in the NICU population demonstrated decreased ED utilization through a combination of augmented family engagement during hospitalization and/or enhanced support after discharge. Two inpatient asthma education interventions with structured postdischarge follow‐up decreased return visitation to the ED.[23, 26] The intervention that worsened subsequent ED utilization (ie, increased ED visit hazard compared to matched controls) provided enhanced inpatient education to a nonrandom group of children hospitalized with asthma and provided a follow‐up phone call 3 weeks after discharge (Tables 1 and 2).[21]
DISCUSSION
In this review, we synthesized evidence regarding pediatric hospital discharge‐focused interventions intended to reduce subsequent utilization through decreased readmission and ED visits. Our review identified 14 studies clustered in 3 clinical areas: asthma, NICU care (chiefly prematurity), and cancer. Overall, 6 interventions demonstrated a reduction either in subsequent hospitalization or ED use. Four of the 6 positive interventions included both an enhanced inpatient education and engagement component as well as enhanced follow‐up after discharge. Importantly, all of the interventions were multifaceted; thus, we could not ascertain which specific aspects of the interventions mediated the change. Many of the included studies had significant methodological limitations.
Current Conceptual Framework
There are a number of existing discharge transitional care frameworks from prior studies[35, 36] and professional societies.[37] The Stepping Up to the Plate (SUTTP) alliance, a collaborative of 9 professional organizations, including the American Academy of Pediatrics, introduced 1 such framework in 2007. SUTTP sought to enhance care transitions by outlining principles of discharge transitional care including: (1) enhanced accountability, (2) creation of a central coordination hub charged with communicating expectations for care, (3) clear and direct communication of treatment plans and follow‐up, (4) timely feedback/feed‐forward of relevant information, and (5) involvement of family member at every stage.[38] In the context of the SUTTP framework, we present 3 hypotheses based on our findings to guide future work.
Hypothesis: Appointing a Dedicated Individual or Coordinating Hub Reduces Subsequent Utilization
Ostensibly, each discharge intervention included in this review sought to enhance accountability of providers or their health systems for discharge transitional care. Two of the asthma interventions appointed a particular provider to coordinate the discharge transition and demonstrated reductions in readmission.[25, 26] The successful NICU discharge interventions provided an integrated accountability structure across the health system, with a transition of accountability to an outpatient provider or central coordinating hub available to provide assistance and resources for an extended period following discharge.
By contrast, interventions with more than 1 individual intervener or without a centrally coordinated system for discharge transitional care tended not to demonstrate reduction in subsequent utilization.[21, 24, 27, 28] In fact, the 1 asthma intervention that utilized a previously existing public health nurse infrastructure demonstrated an increase in readmission.[28] Future efforts to enhance transitional care might investigate directly the impact of accountability structure on subsequent utilization by varying the number of effector individuals or the organization to which they report (eg, hospital system vs public health department).
Hypothesis: Individualized Task Learning and Feedback Enhances Effectiveness
Studies varied with respect to the extent they incorporated the principles of enhanced communication of the treatment and follow‐up plan and timely feedback/feed‐forward of relevant information. Successful efforts, however, seemed to embrace these strategies. Each of the 3 interventions that demonstrated readmission reduction[23, 25, 26] developed an individualized treatment plan during hospitalization, with either a specific follow‐up plan or resources for outpatient support. Two of these interventions assessed asthma inhaler technique prior to discharge, creating an inpatient audit and feedback loop allowing for assessment of competence prior to discharge. Audit and feedback has demonstrated promise modifying provider behavior[39] and is a plausible approach to enhancing patient and family self‐care.
Hypothesis: Timing of Intervention Enhances Effectiveness
Discrete sentinel events such as inpatient admission, may serve as a teachable moment[40, 41] or a tipping point[42] for some patients/families to initiate behavior change. Four of the 6 positive studies had a robust inpatient education component. By providing enhanced inpatient support, providers may be engaging the family at a timely opportunity to improve care. Both timing of the intervention (at admission vs discharge) and content (education‐ vs family‐engagement focused) are likely important to their effect and should be further explored with prospective study.
Persistent Literature Gaps
Follow‐up with a primary care provider after discharge is another intervention that might decrease postdischarge utilization. We did not identify any studies that specifically examined primary care follow‐up. However, 2 studies[43, 44] that did not meet our inclusion criteria (because they included adults and did not stratify by age group in the analysis) examined any outpatient follow‐up after discharge using state‐specific Medicaid claims. One study found that outpatient follow‐up after sickle cell hospitalization was associated with lower rates of readmission.[43] The other found no difference in readmission across multiple conditions.[44] One recent review of outpatient follow‐up from the ED for asthma found that even when increases in follow‐up were achieved, no reduction in the subsequent utilization was observed.[45]
Additional important questions remain underexplored. First, are condition‐specific interventions superior to those that span conditions? All of the interventions that demonstrated reductions in readmission were condition‐specific, yet no generic interventions met our inclusion criteria. Importantly, only 1 study[29] in our review examined discharge processes from 1 of the pediatric conditions with the most variation[8] in readmission. Further, no studies focused on children with complex medical conditions, who are known to be at increased risk of readmission,[46] indicating a sizable knowledge gap persists in understanding how to prevent readmissions in the most vulnerable pediatric populations.
Lastly, who are the most appropriate effector individuals for discharge‐focused transitional care interventions? Demographically matched effector individuals have shown promise in improving care using community health workers.[47, 48] The degree to which the identity of the intervener mediates subsequent ED and hospital utilization warrants further investigation.
Limitations of This Systematic Review
The studies included in this review assessed different outcomes at different intervals, precluding meta‐analysis. With greater consistency in the collection of data on the quality of discharge processes and their subsequent outcomes, future studies may offer further clarity as to which discharge‐oriented practices are more effective than others. Because we only identified literature in 3 pediatric conditions, generalizability beyond these conditions may be limited. The settings of the interventions also occurred in multiple countries; we excluded countries from low or low‐middle incomes to facilitate generalizability. As many of the discharge processes contained multiple interventions, it is not possible to ascertain which, if any, singular action may decrease posthospitalization utilization. Additionally, some of the included interventions are older, and it is plausible that discharge processes have evolved with the expansion of the hospitalist model.
Methods of data collection influence the quality of results in the included studies. Most of the studies included in this review used either medical record review or parental self‐report of utilization. Parental report may be sufficient for hospitalizations and ED utilization; however, it is subject to recall bias. Chart review likely underestimates the number of postdischarge events, depending on the individual institution's proportion of the market and the tendency of individuals to seek care at multiple institutions. Claims data may offer the most accurate assessments of ED and hospital utilization and cost, but can be more difficult to obtain and do not provide the same potential for granularity as parent report or medical records review.
Finally, subsequent ED visits, readmissions, and cost may not be the best measures of the quality of discharge transitional care. A number of tools have been developed to more specifically evaluate the quality of transitional care in adults,[49, 50] including a validated instrument that consists of only 3 items,[50] which primarily assesses the extent to which patients are prepared for self‐care upon discharge. For pediatric populations, validated tools assessing caregiver experience with discharge[51] and discharge readiness[52] are also available. These instruments may assist those interested in assessing process‐related outcomes that specifically assess discharge transitional care elements and may mediate subsequent ED visits or hospitalizations.
CONCLUSION
Successful discharge interventions to reduce pediatric readmission and ED have some common features, including an individual or team with specialized knowledge of the condition that assumed responsibility for the inpatient‐to‐outpatient transition and offered ongoing support to the family following discharge. All studies included in our review examined multiple discharge interventions; however, many did not have enough participants to detect differences in the outcomes of interest. Future studies might adapt common features of effective interventions, which are consistent with professional societies' recommendations.
Acknowledgements
The authors thank Marisa Conte for her help with developing the search algorithms for the review.
Disclosures: Drs. Auger and Kenyon received salary support from the Robert Wood Johnson Foundation Clinical Scholars program. Dr. Feudtner does not have any funding sources to disclose. Dr. Davis is funded in part by the Michigan Department of Community Health to serve as the Chief Medical Executive. The views expressed herein are not necessarily the views of the Department of Community Health. The authors have no conflicts of interest to report.
- , , , , . Are hospital characteristics associated with parental views of pediatric inpatient care quality? Pediatrics. 2003;111(2):308–314.
- , , , , , . Deficits in communication and information transfer between hospital‐based and primary care physicians: implications for patient safety and continuity of care. JAMA. 2007;297(8):831–841.
- , , , et al. Improving transitions of care at hospital discharge‐‐implications for pediatric hospitalists and primary care providers. J Healthc Qual. 2010;32(5):51–60.
- , . Hospitalists in children's hospitals: what we know now and what we need to know. J Pediatr. 2006;148(3):296–299.
- , , , , . The incidence and severity of adverse events affecting patients after discharge from the hospital. Ann Intern Med. 2003;138(3):161–167.
- , , , et al. Adverse events among medical patients after discharge from hospital. CMAJ. 2004;170(3):345–349.
- , , , . Medical errors related to discontinuity of care from an inpatient to an outpatient setting. J Gen Intern Med. 2003;18(8):646–651.
- , , , et al. Pediatric readmission prevalence and variability across hospitals. JAMA. 2013;309:372–380.
- , , , , , . Discharge planning from hospital to home. Cochrane Database Syst Rev. 2013;(1):CD000313.
- , , , , , . Preventability of early readmissions at a children's hospital. Pediatrics. 2012;131(1):e171–e181.
- , , , et al. State‐level child health system performance and the likelihood of readmission to children's hospitals. J Pediatr. 2010;157(1):98–102.e1.
- Ohio Children's Hospitals' solutions for patient safety. Available at: http://solutionsforpatientsafety.org/files/sps‐fact‐sheet.pdf. Accessed July 24, 2013.
- American Academy of Pediatrics. Value in inpatient pediatrics (VIP) network projects. Available at: http://www.aap.org/en‐us/professional‐resources/practice‐support/quality‐improvement/Quality‐Improvement‐Innovation‐Networks/Pages/Value‐in‐Inpatient‐Pediatrics‐Network‐Projects.aspx. Accessed July 24, 2013.
- Child Health Corporation of America. Resources for managing the patient discharge process. Available at: http://www.chca.com/news/index.html. Accessed October 31, 2013.
- The World Bank. World Development Indicators 2012. Available at: http://data.worldbank.org/sites/default/files/wdi‐2012‐ebook.pdf. Accessed July 5, 2013.
- The Cochrane Collaboration. Data collection form: Intervention review—RCTs and non‐RCTs. Available at: http://hiv.cochrane.org/sites/hiv.cochrane.org/files/uploads/Data%20extraction%20form_all%20studies.docx. Accessed July 24, 2013.
- , . The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non‐randomised studies of health care interventions. J Epidemiol Community Health. 1998;52(6):377–384.
- , , , et al. Brief violence interventions with community case management services are effective for high‐risk trauma patients. J Trauma. 2011;71(1):228–237.
- , , , , , . Benefits of a hospital‐based peer intervention program for violently injured youth. J Am Coll Surg. 2007;205(5):684–689.
- , , , , . Caught in the crossfire: the effects of a peer‐based intervention program for violently injured youth. J Adolesc Health. 2004;34(3):177–183.
- , , , , . A matched‐cohort evaluation of a bedside asthma intervention for patients hospitalized at a large urban children's hospital. J Urban Health. 2011;88(suppl 1):49–60.
- , , , et al. Effectiveness of asthma education with and without a self‐management plan in hospitalized children. J Asthma. 2009;46(9):906–910.
- , , , , And . Effect of a structured asthma education program on hospitalized asthmatic children: a randomized controlled study. Pediatr Int. 2006;48(2):158–162.
- , , , , , Parental education and guided self‐management of asthma and wheezing in the pre‐school child: a randomised controlled trial. Thorax. 2002;57(1):39–44.
- , , . Structured discharge procedure for children admitted to hospital with acute asthma: a randomised controlled trial of nursing practice. Arch Dis Child. 1999;80(2):110–114.
- , , . Impact of a nurse‐led home management training programme in children admitted to hospital with acute asthma: a randomised controlled study. Thorax. 1997;52(3):223–228.
- , , , et al. You Can Control Asthma: evaluation of an asthma education program for hospitalized inner‐city children. Patient Educ Couns. 1991;17(1):35–47.
- , , . Asthma education by community child health nurses. Arch Dis Child. 1986;61(12):1184–1189.
- , . Effectiveness of a discharge‐planning program and home visits for meeting the physical care needs of children with cancer. Support Care Cancer. 2009;18(2):243–253.
- , , , et al. Comprehensive follow‐up care and life‐threatening illnesses among high‐risk infants: a randomized controlled trial. JAMA. 2000;284(16):2070–2076.
- , , , . Very low birth weight infants and their families during the first year of life: comparisons of medical outcomes based on after care services. J Perinatol. 1998;18(5):365–371.
- , , , , . Description and evaluation of a program for the early discharge of infants from a neonatal intensive care unit. J Pediatr. 1995;127(2):285–290.
- , , , et al. Earlier discharge with community‐based intervention for low birth weight infants: a randomized trial. Pediatrics. 1993;92(1):128–134.
- , , , et al. A randomized clinical trial of early hospital discharge and home follow‐up of very‐low‐birth‐weight infants. N Engl J Med. 1986;315(15):934–939.
- , , . Care transitions from inpatient to outpatient settings: ongoing challenges and emerging best practices. Hosp Pract (1995). 2011;39(3):128–139.
- , , , , . Interventions to reduce 30‐day rehospitalization: a systematic review. Ann Intern Med. 2011;155(8):520–528.
- . Clinical report—physicians' roles in coordinating care of hospitalized children. Pediatrics. 2010;126(4):829–832.
- . White space or black hole: what can we do to improve care transitions? ABIM Foundation. Available at: http://www.abimfoundation.org/∼/media/Files/Publications/F06‐05‐2007_6.ashx. Accessed September 5, 2012.
- , , , et al. Audit and feedback: effects on professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2012;(6):CD000259.
- , , , , . A smoking cessation intervention for parents of children who are hospitalized for respiratory illness: the stop tobacco outreach program. Pediatrics. 2003;111(1):140–145.
- , . A randomized, controlled trial of smoking cessation counseling provided during child hospitalization for respiratory illness. Pediatr Pulmonol. 2008;43(6):561–566.
- , . Embracing chaos and complexity: a quantum change for public health. Am J Public Health. 2008;98(8):1382–1389.
- , , , , , . Outpatient follow‐up and rehospitalizations for sickle cell disease patients. Pediatr Blood Cancer. 2012;58(3):406–409.
- , , . Does having an outpatient visit after hospital discharge reduce the likelihood of readmission? Del Med J. 2003;75(8):291–298.
- , , . Follow‐up after acute asthma episodes. Proc Am Thorac Soc. 2009;6(4):386–393.
- , , , et al. Hospital utilization and characteristics of patients experiencing recurrent readmissions within children's hospitals. JAMA. 2011;305(7):682–690.
- , , , et al. A randomized controlled evaluation of the effect of community health workers on hospitalization for asthma: the asthma coach. Arch Pediatr Adolesc Med. 2009;163(3):225–232.
- , , , . The Seattle‐King County Healthy Homes Project: a randomized, controlled trial of a community health worker intervention to decrease exposure to indoor asthma triggers. Am J Public Health. 2005;95(4):652–659.
- , , , , , . Development and testing of a measure designed to assess the quality of care transitions. Int J Integr Care. 2002;2:e02.
- , , , . Assessing the quality of transitional care: further applications of the care transitions measure. Med Care. 2008;46(3):317–322.
- , , , et al. Hospital readmission and parent perceptions of their child's hospital discharge. Int J Qual Health Care. 2013;25(5):573–581.
- , . Psychometric properties of the Readiness for Hospital Discharge Scale. J Nurs Meas. 2006;14(3):163–180.
- , , , , . Are hospital characteristics associated with parental views of pediatric inpatient care quality? Pediatrics. 2003;111(2):308–314.
- , , , , , . Deficits in communication and information transfer between hospital‐based and primary care physicians: implications for patient safety and continuity of care. JAMA. 2007;297(8):831–841.
- , , , et al. Improving transitions of care at hospital discharge‐‐implications for pediatric hospitalists and primary care providers. J Healthc Qual. 2010;32(5):51–60.
- , . Hospitalists in children's hospitals: what we know now and what we need to know. J Pediatr. 2006;148(3):296–299.
- , , , , . The incidence and severity of adverse events affecting patients after discharge from the hospital. Ann Intern Med. 2003;138(3):161–167.
- , , , et al. Adverse events among medical patients after discharge from hospital. CMAJ. 2004;170(3):345–349.
- , , , . Medical errors related to discontinuity of care from an inpatient to an outpatient setting. J Gen Intern Med. 2003;18(8):646–651.
- , , , et al. Pediatric readmission prevalence and variability across hospitals. JAMA. 2013;309:372–380.
- , , , , , . Discharge planning from hospital to home. Cochrane Database Syst Rev. 2013;(1):CD000313.
- , , , , , . Preventability of early readmissions at a children's hospital. Pediatrics. 2012;131(1):e171–e181.
- , , , et al. State‐level child health system performance and the likelihood of readmission to children's hospitals. J Pediatr. 2010;157(1):98–102.e1.
- Ohio Children's Hospitals' solutions for patient safety. Available at: http://solutionsforpatientsafety.org/files/sps‐fact‐sheet.pdf. Accessed July 24, 2013.
- American Academy of Pediatrics. Value in inpatient pediatrics (VIP) network projects. Available at: http://www.aap.org/en‐us/professional‐resources/practice‐support/quality‐improvement/Quality‐Improvement‐Innovation‐Networks/Pages/Value‐in‐Inpatient‐Pediatrics‐Network‐Projects.aspx. Accessed July 24, 2013.
- Child Health Corporation of America. Resources for managing the patient discharge process. Available at: http://www.chca.com/news/index.html. Accessed October 31, 2013.
- The World Bank. World Development Indicators 2012. Available at: http://data.worldbank.org/sites/default/files/wdi‐2012‐ebook.pdf. Accessed July 5, 2013.
- The Cochrane Collaboration. Data collection form: Intervention review—RCTs and non‐RCTs. Available at: http://hiv.cochrane.org/sites/hiv.cochrane.org/files/uploads/Data%20extraction%20form_all%20studies.docx. Accessed July 24, 2013.
- , . The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non‐randomised studies of health care interventions. J Epidemiol Community Health. 1998;52(6):377–384.
- , , , et al. Brief violence interventions with community case management services are effective for high‐risk trauma patients. J Trauma. 2011;71(1):228–237.
- , , , , , . Benefits of a hospital‐based peer intervention program for violently injured youth. J Am Coll Surg. 2007;205(5):684–689.
- , , , , . Caught in the crossfire: the effects of a peer‐based intervention program for violently injured youth. J Adolesc Health. 2004;34(3):177–183.
- , , , , . A matched‐cohort evaluation of a bedside asthma intervention for patients hospitalized at a large urban children's hospital. J Urban Health. 2011;88(suppl 1):49–60.
- , , , et al. Effectiveness of asthma education with and without a self‐management plan in hospitalized children. J Asthma. 2009;46(9):906–910.
- , , , , And . Effect of a structured asthma education program on hospitalized asthmatic children: a randomized controlled study. Pediatr Int. 2006;48(2):158–162.
- , , , , , Parental education and guided self‐management of asthma and wheezing in the pre‐school child: a randomised controlled trial. Thorax. 2002;57(1):39–44.
- , , . Structured discharge procedure for children admitted to hospital with acute asthma: a randomised controlled trial of nursing practice. Arch Dis Child. 1999;80(2):110–114.
- , , . Impact of a nurse‐led home management training programme in children admitted to hospital with acute asthma: a randomised controlled study. Thorax. 1997;52(3):223–228.
- , , , et al. You Can Control Asthma: evaluation of an asthma education program for hospitalized inner‐city children. Patient Educ Couns. 1991;17(1):35–47.
- , , . Asthma education by community child health nurses. Arch Dis Child. 1986;61(12):1184–1189.
- , . Effectiveness of a discharge‐planning program and home visits for meeting the physical care needs of children with cancer. Support Care Cancer. 2009;18(2):243–253.
- , , , et al. Comprehensive follow‐up care and life‐threatening illnesses among high‐risk infants: a randomized controlled trial. JAMA. 2000;284(16):2070–2076.
- , , , . Very low birth weight infants and their families during the first year of life: comparisons of medical outcomes based on after care services. J Perinatol. 1998;18(5):365–371.
- , , , , . Description and evaluation of a program for the early discharge of infants from a neonatal intensive care unit. J Pediatr. 1995;127(2):285–290.
- , , , et al. Earlier discharge with community‐based intervention for low birth weight infants: a randomized trial. Pediatrics. 1993;92(1):128–134.
- , , , et al. A randomized clinical trial of early hospital discharge and home follow‐up of very‐low‐birth‐weight infants. N Engl J Med. 1986;315(15):934–939.
- , , . Care transitions from inpatient to outpatient settings: ongoing challenges and emerging best practices. Hosp Pract (1995). 2011;39(3):128–139.
- , , , , . Interventions to reduce 30‐day rehospitalization: a systematic review. Ann Intern Med. 2011;155(8):520–528.
- . Clinical report—physicians' roles in coordinating care of hospitalized children. Pediatrics. 2010;126(4):829–832.
- . White space or black hole: what can we do to improve care transitions? ABIM Foundation. Available at: http://www.abimfoundation.org/∼/media/Files/Publications/F06‐05‐2007_6.ashx. Accessed September 5, 2012.
- , , , et al. Audit and feedback: effects on professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2012;(6):CD000259.
- , , , , . A smoking cessation intervention for parents of children who are hospitalized for respiratory illness: the stop tobacco outreach program. Pediatrics. 2003;111(1):140–145.
- , . A randomized, controlled trial of smoking cessation counseling provided during child hospitalization for respiratory illness. Pediatr Pulmonol. 2008;43(6):561–566.
- , . Embracing chaos and complexity: a quantum change for public health. Am J Public Health. 2008;98(8):1382–1389.
- , , , , , . Outpatient follow‐up and rehospitalizations for sickle cell disease patients. Pediatr Blood Cancer. 2012;58(3):406–409.
- , , . Does having an outpatient visit after hospital discharge reduce the likelihood of readmission? Del Med J. 2003;75(8):291–298.
- , , . Follow‐up after acute asthma episodes. Proc Am Thorac Soc. 2009;6(4):386–393.
- , , , et al. Hospital utilization and characteristics of patients experiencing recurrent readmissions within children's hospitals. JAMA. 2011;305(7):682–690.
- , , , et al. A randomized controlled evaluation of the effect of community health workers on hospitalization for asthma: the asthma coach. Arch Pediatr Adolesc Med. 2009;163(3):225–232.
- , , , . The Seattle‐King County Healthy Homes Project: a randomized, controlled trial of a community health worker intervention to decrease exposure to indoor asthma triggers. Am J Public Health. 2005;95(4):652–659.
- , , , , , . Development and testing of a measure designed to assess the quality of care transitions. Int J Integr Care. 2002;2:e02.
- , , , . Assessing the quality of transitional care: further applications of the care transitions measure. Med Care. 2008;46(3):317–322.
- , , , et al. Hospital readmission and parent perceptions of their child's hospital discharge. Int J Qual Health Care. 2013;25(5):573–581.
- , . Psychometric properties of the Readiness for Hospital Discharge Scale. J Nurs Meas. 2006;14(3):163–180.
