Preventing hospitalizations in children with medical complexity: a systematic review.
OBJECTIVE
Children with medical complexity (CMC) account for disproportionately high hospital use, and it is unknown if hospitalizations may be prevented. Our objective was to summarize evidence from (1) studies characterizing potentially preventable hospitalizations in CMC and (2) interventions aiming to reduce such hospitalizations.


METHODS
Our data sources include Medline, Cochrane Central Register of Controlled Trials, Web of Science, and Cumulative Index to Nursing and Allied Health Literature databases from their originations, and hand search of article bibliographies. Observational studies (n = 13) characterized potentially preventable hospitalizations, and experimental studies (n = 4) evaluated the efficacy of interventions to reduce them. Data were extracted on patient and family characteristics, medical complexity and preventable hospitalization indicators, hospitalization rates, costs, and days. Results of interventions were summarized by their effect on changes in hospital use.


RESULTS
Preventable hospitalizations were measured in 3 ways: ambulatory care sensitive conditions, readmissions, or investigator-defined criteria. Postsurgical patients, those with neurologic disorders, and those with medical devices had higher preventable hospitalization rates, as did those with public insurance and nonwhite race/ethnicity. Passive smoke exposure, nonadherence to medications, and lack of follow-up after discharge were additional risks. Hospitalizations for ambulatory care sensitive conditions were less common in more complex patients. Patients receiving home visits, care coordination, chronic care-management, and continuity across settings had fewer preventable hospitalizations.


CONCLUSIONS
There were a limited number of published studies. Measures for CMC and preventable hospitalizations were heterogeneous. Risk of bias was moderate due primarily to limited controlled experimental designs. Reductions in hospital use among CMC might be possible. Strategies should target primary drivers of preventable hospitalizations.
Department of Pediatrics, University of Wisconsin, Madison School of Medicine and Public Health, Madison, Wisconsin; rcoller@pediatrics.wisc.edu.
Ryan J
RJ
Coller
Department of Pediatrics, David Geffen School of Medicine, Children's Discovery and Innovation Institute, Mattel Children's Hospital.
Bergen B
BB
Nelson
Department of Pediatrics, University of Wisconsin, Madison School of Medicine and Public Health, Madison, Wisconsin;
Daniel J
DJ
Sklansky
Department of Pediatrics, David Geffen School of Medicine.
Adrianna A
AA
Saenz
Department of Pediatrics, David Geffen School of Medicine.
Thomas S
TS
Klitzner
Department of Pediatrics, David Geffen School of Medicine.
Carlos F
CF
Lerner
Department of Pediatrics, David Geffen School of Medicine, Children's Discovery and Innovation Institute, Mattel Children's Hospital, Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California; and RAND Health, The RAND Corporation, Santa Monica, California.
Paul J
PJ
Chung
D000553:Ambulatory Care / Q000191:economics* / Q000706:statistics & numerical data*; D019090:Case Management / Q000191:economics / Q000706:statistics & numerical data; D002648:Child; D002908:Chronic Disease / Q000191:economics* / Q000628:therapy*; D003266:Continuity of Patient Care / Q000191:economics / Q000706:statistics & numerical data; D017046:Cost Savings; D019988:Children with Disabilities / Q000706:statistics & numerical data*; D006760:Hospitalization / Q000191:economics* / Q000706:statistics & numerical data*; D006792:House Calls / Q000191:economics / Q000706:statistics & numerical data; D006801:Humans; D007902:Length of Stay / Q000191:economics / Q000706:statistics & numerical data; D010359:Patient Readmission / Q000191:economics / Q000706:statistics & numerical data; D012307:Risk Factors; D014481:United States
chronic illness/conditions; hospitalization; medical complexity; readmission