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Is Health Information Exchange Participation Associated With Hospital Readmissions From Home Health Care?

  • Christine D. Jones
    Correspondence
    Address correspondence to Christine D. Jones, MD, MS, Division of Hospital Medicine, Department of Medicine, University of Colorado, Anschutz Medical Campus, Mail Stop F782, 12401 East 17th Avenue, Aurora, Colorado 80045, USA.
    Affiliations
    Division of Hospital Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
    Denver/Seattle Center of Innovation for Veteran-Centered and Value Driven Care, VHA Eastern Colorado Healthcare System, Aurora, CO, USA
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  • Jacob Thomas
    Affiliations
    Adult and Child Consortium for Health Outcomes Research and Delivery Science (ACCORDS), University of Colorado Anschutz Medical Campus, Aurora, CO, USA
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  • Kate Ytell
    Affiliations
    Data Science to Patient Value Program, ACCORDS, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
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  • Marisa L. Roczen
    Affiliations
    Division of Health Care Policy and Research, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
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  • Cari R. Levy
    Affiliations
    Denver/Seattle Center of Innovation for Veteran-Centered and Value Driven Care, VHA Eastern Colorado Healthcare System, Aurora, CO, USA
    Division of Health Care Policy and Research, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
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  • Sarah R. Jordan
    Affiliations
    Division of Geriatric Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
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  • Hillary D. Lum
    Affiliations
    Division of Geriatric Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
    VA Eastern Colorado Geriatrics Research Education and Clinical Center, Rocky Mountain Regional VA Medical Center, Aurora, CO, USA
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  • Mark Gritz
    Affiliations
    Adult and Child Consortium for Health Outcomes Research and Delivery Science (ACCORDS), University of Colorado Anschutz Medical Campus, Aurora, CO, USA
    Data Science to Patient Value Program, ACCORDS, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
    Division of Health Care Policy and Research, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
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Published:August 31, 2021DOI:https://doi.org/10.1016/j.jamda.2021.08.012
      To the Editor:
      Adults discharged from the hospital with skilled home health care (HHC) are at high risk for preventable adverse events, including medication errors and hospital readmissions.
      • Brody A.A.
      • Gibson B.
      • Tresner-Kirsch D.
      • et al.
      High prevalence of medication discrepancies between home health referrals and Centers for Medicare and Medicaid Services home health certification and plan of care and their potential to affect safety of vulnerable elderly adults.
      • Sterling M.R.
      • Kern L.M.
      • Safford M.M.
      • et al.
      Home health care use and post-discharge outcomes after heart failure hospitalizations.
      • Jones C.D.
      • Falvey J.
      • Hess E.
      • et al.
      Predicting hospital readmissions from home healthcare in Medicare beneficiaries.
      Health Information Exchanges (HIEs) are increasingly being used in multiple care settings across the United States.
      • Rahurkar S.
      • Vest J.R.
      • Finnell J.T.
      • Dixon B.E.
      Trends in user-initiated health information exchange in the inpatient, outpatient, and emergency settings.
      HIEs are designed to allow clinicians in different care settings to access a patient's medical information electronically, and have potential to improve information exchange between hospitals and other care settings.
      • Jones C.D.
      • Jones J.
      • Bowles K.H.
      • et al.
      Quality of hospital communication and patient preparation for home health care: Results from a statewide survey of home health care nurses and staff.
      • Cross D.A.
      • Adler-Milstein J.
      Investing in post-acute care transitions: Electronic information exchange between hospitals and long-term care facilities.
      • Cross D.A.
      • McCullough J.S.
      • Adler-Milstein J.
      Drivers of health information exchange use during postacute care transitions.
      The association between HIE participation during hospital to home health agency transitions and hospital readmissions has not previously been examined. Therefore, we completed a secondary data analysis using the statewide Colorado all payer claims database (COAPCD) to examine if hospital and/or home health agency participation in a regional HIE is associated with reductions in 30-day readmissions.
      The study sample included Medicare and Medicare Advantage (MA) beneficiaries hospitalized in Colorado between January 1, 2014, and August 31, 2018. The primary outcome was 30-day hospital readmission and the primary independent variables were HIE participation by the hospital and/or home health agency for each hospital to HHC transition. In multivariable generalized linear regression, additional patient, hospital, and home health agency characteristics that might influence the association between readmissions and HIE participation were included in the model.
      After exclusions (see Supplementary Figure 1), this analysis included 46,903 individuals with 54,016 hospital to home health transitions. Patients were 75 years old (median), 57.8% were female, 82.8% had Medicare, and 17.2% had MA insurance (see Supplementary Table 1). The overall 30-day readmission rate was 12.8%. Table 1 shows patient, hospital, and home health agency characteristics by 30-day readmissions. Hospital HIE participation [odds ratio (OR) 0.84, 95% confidence interval (CI) 0.79–0.89] but not home health agency HIE participation (OR 1.02, 95% CI 0.97–1.07) was associated with lower odds of 30-day readmissions in unadjusted models. After adjusting for multiple covariates, neither hospital nor home health agency HIE participation was associated with lower 30-day readmissions (adjusted hospital OR 0.94, 95% CI 0.87–1.02; adjusted home health agency OR 0.99, 95% CI 0.93–1.05).
      Table 1Patient, Hospital. and Home Health Agency Characteristics by 30-day Readmission (Row Percentages)
      VariableTotal n = 54,01630-Day ReadmissionP Value
      No n = 47,116Yes n = 6900
      Patient characteristics
       Age, median (IQR)75.0 (68.0–83.0)75.0 (68.0–83.0)76.0 (69.0–84.0)<.001
       Length of stay, median (IQR)3.0 (2.0–5.0)3.0 (2.0–5.0)4.0 (2.0–6.0)<.001
       Sex<.001
      Female57.8 (30,981)87.7 (27,177)12.3 (3804)
      Male42.2 (22,604)86.6 (19,570)13.4 (3034)
       Payer.828
      Medicare82.8 (44,750)87.2 (39,040)12.8 (5710)
      Medicare Advantage17.2 (9266)87.2 (8076)12.8 (1190)
       Charlson Comorbidity Index score<.001
      030.1 (16,265)92.9 (15,107)7.1 (1158)
      125.1 (13,579)88.8 (12,054)11.2 (1525)
      217.1 (9217)85.3 (7860)14.7 (1357)
      3+27.7 (14,955)80.9 (12,095)19.1 (2860)
      Primary diagnoses for hospitalization
       Acute myocardial infarction.002
      Yes1.5 (793)83.6 (663)16.4 (130)
      No98.5 (53,223)87.3 (46,453)12.7 (6770)
       Chronic obstructive pulmonary disease<.001
      Yes1.8 (994)83.5 (830)16.5 (164)
      No98.2 (53,022)87.3 (46,286)12.7 (6736)
       Pneumonia.004
      Yes2.8 (1498)84.8 (1270)15.2 (228)
      No97.2 (52,518)87.3 (45,846)12.7 (6672)
       Stroke.004
      Yes2.1 (1108)90.1 (998)9.9 (110)
      No97.9 (52,908)87.2 (46,118)12.8 (6790)
       Heart failure<.001
      Yes2.6 (1381)80.1 (1106)19.9 (275)
      No97.4 (52,635)87.4 (46,010)12.6 (6625)
       Total hip or knee arthroplasty<.001
      Yes21.9 (11,807)96.0 (11,336)4.0 (471)
      No78.1 (42,209)84.8 (35,780)15.2 (6429)
      Hospital characteristics
       Hospital type<.001
      Acute care hospitals98.4 (53,141)87.2 (46,316)12.8 (6825)
      Critical access hospitals1.6 (875)91.4 (800)8.6 (75)
       Hospital compare quality star rating<.001
      23.2 (1701)83.4 (1418)16.6 (283)
      339.7 (21,129)86.4 (18,246)13.6 (2883)
      446.9 (24,979)87.6 (21,874)12.4 (3105)
      510.2 (5432)89.1 (4840)10.9 (592)
       Discharges from hospital (total in cohort)<.001
      0–1391.6 (862)89.9 (775)10.1 (87)
      140–6168.4 (4542)89.3 (4057)10.7 (485)
      617–162228.4 (15,343)86.2 (13,231)13.8 (2112)
      >162261.6 (33,269)87.3 (29,053)12.7 (4216)
       Ownership - Hospital<.001
      Government15.7 (8474)85.8 (7269)14.2 (1205)
      Nonprofit68.5 (37,016)87.2 (32,273)12.8 (4743)
      Proprietary15.8 (8526)88.8 (7574)11.2 (952)
       Hospital - HIE use at discharge<.001
      Yes80.1 (43,292)87.6 (37,935)12.4 (5357)
      No19.9 (10,724)85.6 (9181)14.4 (1543)
      Home health agency characteristics
       Home health agency location<.001
      Rural11.4 (6183)88.9 (5494)11.1 (689)
      Urban88.6 (47,833)87.0 (41,622)13.0 (6211)
       Home health compare quality star rating.002
      ≤ 2.57.3 (3938)86.0 (3388)14.0 (550)
      313.4 (7193)88.1 (6334)11.9 (859)
      3.519.1 (10,222)87.8 (8971)12.2 (1251)
      428.6 (15,325)87.2 (13,367)12.8 (1958)
      4.523.7 (12,693)86.5 (10,981)13.5 (1712)
      57.9 (4213)87.6 (3691)12.4 (522)
       Number of referrals to home health agencies (total in cohort)<.001
      0–922.7 (1444)84.3 (1217)15.7 (227)
      93–2127.8 (4236)86.4 (3658)13.6 (578)
      213–47117.5 (9439)86.7 (8185)13.3 (1254)
      >47172.0 (38,897)87.6 (34,056)12.4 (4841)
       Ownership – Home Health Agencies<.001
      Government2.3 (1253)87.5 (1097)12.5 (156)
      Nonprofit40.3 (21,580)86.6 (18,678)13.4 (2902)
      Proprietary57.4 (30,751)87.7 (26,957)12.3 (3794)
       Home health agency – all services offered.431
      No4.1 (2214)87.8 (1943)12.2 (271)
      Yes95.9 (51,370)87.2 (44,789)12.8 (6581)
       Home health agency - HIE use at discharge.450
      No43.9 (23,697)87.3 (20,699)12.7 (2998)
      Yes56.1 (30,319)87.1 (26,417)12.9 (3902)
      Cells are % (n) by row, or median [interquartile range (IQR)]; P values from Pearson's χ2 test or the Wilcoxon Rank Sum test.
      These findings should be interpreted in the broader context of care transition interventions, in which multiple systematic reviews have identified that transitions of care interventions are more likely to reduce readmissions when they include multiple components.
      • Leppin A.L.
      • Gionfriddo M.R.
      • Kessler M.
      • et al.
      Preventing 30-day hospital readmissions: A systematic review and meta-analysis of randomized trials.
      • Fønss Rasmussen L.
      • Grode L.B.
      • Lange J.
      • et al.
      Impact of transitional care interventions on hospital readmissions in older medical patients: A systematic review.
      • Morkisch N.
      • Upegui-Arango L.D.
      • Cardona M.I.
      • et al.
      Components of the transitional care model (TCM) to reduce readmission in geriatric patients: A systematic review.
      For example, in a systematic review with a meta-analysis of 42 studies, care transition interventions that were composed of 5 or more unique components had a lower readmission risk compared with control groups (OR 0.63, 95% CI 0.53–0.76). In this review, examples of unique components included telephone follow-up, home visits, timely communication with the primary care provider, and timely postdischarge follow-up. As a result, it might be reasonable to conclude that although HIE participation may not alone reduce 30-day readmissions, HIE participation could support other components of a care transitions program to ultimately reduce readmissions.
      This analysis has multiple limitations. First, the observational nature of this study does not fully account for the self-selection of hospitals and home health agency participation in the HIE. Although we used multivariable regression to include variables that could influence the association between HIE participation and readmissions, given the complexity of information exchange and care transitions, it is likely that unmeasured confounders influenced our findings, such as actual use of the HIE for individual patients. In addition, although the COAPCD has multiple strengths, including the ability to follow individuals longitudinally across settings and payers, it lacks comprehensive race and ethnicity data, as well as home health assessment and functional data that could have enhanced this analysis and the interpretation of findings. Finally, this analysis did not capture use of information exchange mechanisms outside of HIE, such as direct access to hospital electronic health records for home health agencies, which may represent an important and unmeasured variable given the increasing use of these as supplements or alternatives to HIEs for information exchange.
      In sum, although HIEs are increasingly available to promote better coordination across care settings, HIE participation for hospitals and/or home health agencies was not significantly associated with reductions in 30-day readmissions when included in a full regression model. Future work to understand how best to implement and integrate the HIE into HHC workflow could provide important insights to optimize HIE use. In addition, because multiple components are frequently included in successful care transitions initiatives, future work could aim to understand how HIE use by hospitals and/or home health could be combined with other components of transitional care (eg, HHC frontloading, primary care follow-up) to improve outcomes beyond readmissions (eg, functional outcomes, patient quality of life) for patients as they transition from the hospital to HHC.

      Acknowledgments

      The authors acknowledge the Colorado Regional Health Information Organization for providing key data about hospital and home health agency HIE participation.
      The content is solely the responsibility of the authors and does not necessarily represent the official views of the University of Colorado School of Medicine, the Agency for Healthcare Research and Quality, the Colorado Department of Health Care Policy and Financing, the Center for Improving Value in Health Care or the Colorado Regional Health Information Organization.

      Supplementary Data

      Supplementary Table 1Patient, Hospital, and Home Health Agency Characteristics by Health Information Exchange Participation
      VariableTotal n = 54,016Hospital+/HHA+ n = 25,817Hospital+/HHA− n = 17,475Hospital−/HHA+ n = 4502Hospital−/HHA− n = 6222P Value
      Patient characteristics
       Age, median (IQR)75.0 (68.0–83.0)75.0 (69.0–83.0)75.0 (69.0–83.0)73.0 (67.0–81.0)75.0 (68.0–82.0)<.001
       Length of stay, median (IQR)3.0 (2.0–5.0)3.0 (2.0–5.0)3.0 (2.0–5.0)3.0 (2.0–6.0)3.0 (2.0–6.0)<.001
       Female57.8 (30,981)58.1 (14,908)57.6 (9941)56.5 (2531)58.4 (3601).156
       Payer<.001
      Medicare82.8 (44,750)85.9 (22,181)74.5 (13,021)92.3 (4156)86.7 (5392)
      Medicare Advantage17.2 (9266)14.1 (3636)25.5 (4454)7.7 (346)13.3 (830)
       Charlson Comorbidity Index Score<.001
      030.1 (16,265)30.8 (7953)30.2 (5273)26.9 (1210)29.4 (1829)
      125.1 (13,579)25.8 (6655)24.7 (4309)23.7 (1068)24.9 (1547)
      217.1 (9217)16.8 (4336)17.3 (3023)17.1 (771)17.5 (1087)
      3+27.7 (14,955)26.6 (6873)27.9 (4870)32.3 (1453)28.3 (1759)
      Primary diagnoses for hospitalization
       Acute myocardial infarction1.5 (793)1.4 (367)1.6 (281)1.2 (56)1.4 (89).224
       Chronic obstructive pulmonary disease1.8 (994)2.1 (537)1.5 (261)1.6 (74)2.0 (122)<.001
       Pneumonia2.8 (1498)2.9 (749)2.6 (457)2.3 (102)3.1 (190).026
       Stroke2.1 (1108)2.1 (549)1.9 (339)1.8 (82)2.2 (138).278
       Heart failure2.6 (1381)2.7 (691)2.2 (384)2.9 (129)2.8 (177).002
       Total hip or knee arthroplasty21.9 (11,807)22.3 (5768)22.7 (3965)19.8 (890)19.0 (1184)<.001
      Hospital characteristics
       Hospital type<.001
      Acute care hospitals98.4 (53,141)99.5 (25,677)100.0 (17,472)97.7 (4397)89.9 (5595)
      Critical access hospitals1.6 (875)0.5 (140)0.0 (3)2.3 (105)10.1 (627)
       Hospital compare quality star rating<.001
      23.2 (1701)0.0 (7)0.0 (0)26.2 (1132)9.3 (562)
      339.7 (21,129)41.6 (10,576)31.4 (5474)48.0 (2073)49.6 (3006)
      446.9 (24,979)50.3 (12,792)53.8 (9371)18.5 (798)33.3 (2018)
      510.2 (5432)8.1 (2054)14.8 (2587)7.3 (317)7.8 (474)
       Discharges from hospital (total in cohort)<.001
      0–1391.6 (862)0.6 (151)0.9 (166)1.8 (79)7.5 (466)
      140–6168.4 (4542)5.8 (1503)3.0 (521)8.6 (389)34.2 (2129)
      617–162228.4 (15,343)30.3 (7823)28.9 (5054)14.6 (657)29.1 (1809)
      >162261.6 (33,269)63.3 (16,340)67.1 (11,734)75.0 (3377)29.2 (1818)
       Ownership - Hospital<.001
      Government15.7 (8474)10.1 (2610)5.4 (947)57.3 (2579)37.6 (2338)
      Nonprofit68.5 (37,016)74.7 (19,297)80.2 (14,007)11.5 (518)51.3 (3194)
      Proprietary15.8 (8526)15.1 (3910)14.4 (2521)31.2 (1405)11.1 (690)
      Home health agency characteristics
       Home health agency location<.001
      Rural11.4 (6183)5.7 (1477)11.0 (1926)7.2 (324)39.5 (2456)
      Urban88.6 (47,833)94.3 (24,340)89.0 (15,549)92.8 (4178)60.5 (3766)
       Home health compare quality star rating<.001
      ≤ 2.57.3 (3938)4.1 (1046)9.8 (1701)5.8 (261)15.0 (930)
      313.4 (7193)9.6 (2455)14.9 (2600)7.7 (345)28.9 (1793)
      3.519.1 (10,222)18.9 (4823)20.9 (3636)16.4 (737)16.5 (1026)
      428.6 (15,325)25.7 (6548)39.4 (6856)18.2 (818)17.8 (1103)
      4.523.7 (12,693)29.6 (7557)12.3 (2149)48.3 (2164)13.3 (823)
      57.9 (4213)12.0 (3062)2.7 (462)3.5 (159)8.5 (530)
       Number of referrals to home health agencies (total in cohort)<.001
      0–922.7 (1444)1.7 (440)3.3 (583)3.3 (150)4.4 (271)
      93–2127.8 (4236)3.4 (866)8.9 (1563)3.3 (149)26.6 (1658)
      213–47117.5 (9439)13.5 (3486)20.9 (3661)14.2 (641)26.5 (1651)
      >47172.0 (38,897)81.4 (21,025)66.8 (11,668)79.1 (3562)42.5 (2642)
       Ownership – Home Health Agencies<.001
      Government2.3 (1253)1.1 (277)2.0 (349)0.6 (27)9.7 (600)
      Nonprofit40.3 (21,580)44.8 (11,427)37.0 (6433)31.8 (1428)36.9 (2292)
      Proprietary57.4 (30,751)54.1 (13,787)61.0 (10,622)67.6 (3029)53.4 (3313)
       All HHC services offered (ie, nursing, physical therapy, occupational therapy, social work, speech therapy, home health aides)95.9 (51,370)99.1 (25,257)92.4 (16,087)98.6 (4423)90.3 (5603)<.001
      Values are % (n) unless otherwise noted. P values from Pearson's χ2 test or the Kruskal-Wallis test.
      Figure thumbnail fx1
      Supplementary Fig. 1Cohort derivation with exclusions. CCN, Centers for Medicare and Medicaid Services Certification Number; CCS, Clinical Classifications Software code; HHA, Home Health Agency; HHC, home health care; NPI, National Provider Identifier.

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