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Table 1.  
Sample Characteristics
Sample Characteristics
Table 2.  
Multivariable-Adjusted Model Examining the Effect of Postdischarge Outpatient Visits Completed Within 7 Days on 30-Day Readmissiona
Multivariable-Adjusted Model Examining the Effect of Postdischarge Outpatient Visits Completed Within 7 Days on 30-Day Readmissiona
1.
Hansen  LO, Young  RS, Hinami  K, Leung  A, Williams  MV.  Interventions to reduce 30-day rehospitalization: a systematic review.  Ann Intern Med. 2011;155(8):520-528.PubMedGoogle ScholarCrossref
2.
Hernandez  AF, Greiner  MA, Fonarow  GC,  et al.  Relationship between early physician follow-up and 30-day readmission among Medicare beneficiaries hospitalized for heart failure.  JAMA. 2010;303(17):1716-1722.PubMedGoogle ScholarCrossref
3.
Jackson  C, Shahsahebi  M, Wedlake  T, DuBard  CA.  Timeliness of outpatient follow-up: an evidence-based approach for planning after hospital discharge.  Ann Fam Med. 2015;13(2):115-122.PubMedGoogle ScholarCrossref
4.
Field  TS, Ogarek  J, Garber  L, Reed  G, Gurwitz  JH.  Association of early post-discharge follow-up by a primary care physician and 30-day rehospitalization among older adults.  J Gen Intern Med. 2015;30(5):565-571.PubMedGoogle ScholarCrossref
5.
van Walraven  C, Dhalla  IA, Bell  C,  et al.  Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community.  CMAJ. 2010;182(6):551-557.PubMedGoogle ScholarCrossref
6.
Schmid  NA.  Reducing patient falls: a research-based comprehensive fall prevention program.  Mil Med. 1990;155(5):202–207. PubMedGoogle Scholar
7.
McCaffrey  DF, Griffin  BA, Almirall  D, Slaughter  ME, Ramchand  R, Burgette  LF.  A tutorial on propensity score estimation for multiple treatments using generalized boosted models.  Stat Med. 2013;32(19):3388-3414.PubMedGoogle ScholarCrossref
Research Letter
January 2017

Association of a Dedicated Post–Hospital Discharge Follow-up Visit and 30-Day Readmission Risk in a Medicare Advantage Population

Author Affiliations
  • 1Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena
  • 2Clincial Operations, Kaiser Permanente Southern California, Pasadena
JAMA Intern Med. 2017;177(1):132-135. doi:10.1001/jamainternmed.2016.7061

The effectiveness of post–hospital discharge (POSH) follow-up visits in reducing 30-day readmissions has been mixed.1-4 We aimed to advance the evidence base by examining whether a dedicated 20-minute POSH visit with a primary care clinician (PCC) completed within 7 days after discharge is associated with a lower 30-day readmission rate compared with any other or no scheduled outpatient visit.

Methods

Medicare Advantage patients who were discharged from 14 Kaiser Permanente Foundation hospitals between January 1, 2011, and December 31, 2014, to home or to home health care and remained enrolled in the health care plan for at least 30 days after discharge were included (n = 71 231). Only the first hospitalization during this period was examined. A POSH visit was scheduled while the patient was in the hospital; at the POSH visit, electronic health record (EHR) reminders for routine care issues were suppressed. The PCCs were trained to focus on the postdischarge summary and issues that require follow-up. A non-POSH visit may have been scheduled before or after hospitalization by the patient or a clinician (PCC or specialist) for any reason. The primary outcome was 30-day readmission obtained from the EHR and claims. This study was approved by the institutional review board of Kaiser Permanente Southern California, which waived the need for informed consent for use of EHRs.

We used Cox proportional hazards regression and treated visit completion as a time-dependent variable that could change within the first 7 days. Patients who died within 30 days after discharge were censored. We obtained covariates that were meaningfully associated with visit completion or outcome—age, sex, having a spouse or domestic partner, history of missed appointments in the last 12 months, risk for readmission or early death (LACE readmission risk score, derived from length of stay, acuity of admission, comorbidity score, and emergency department use5; range, 1 to 19, with higher scores indicating higher risk), discharge disposition, service (medicine vs surgical), service site, functional status (nonambulatory vs ambulatory), and Schmid fall risk score6 (range, 0-6, with higher scores indicating a higher risk for falls) within 24 hours of discharge—from the EHR. Analyses were stratified by service and LACE readmission risk score (<11 vs ≥11; with higher scores indicating higher risk); inverse probability of treatment weights were used to adjust for differences in these covariates.7 Statistical analysis was performed with SAS software (version 9.3; SAS Institute). P < .05 was considered significant.

Results

Of the 71 231 eligible patients (33 039 men [46.4%] and 38 192 women [53.6%]; mean [SD] age, 75 [9] years), a total of 7236 (10.2%) and 630 (0.9%) were readmitted or died, respectively, within 30 days of live discharge (Table 1). Patients who completed any outpatient visit within 7 days had a 12% to 24% lower risk for 30-day readmission (Table 2). POSH visits were associated with a lower risk for 30-day readmission compared with non-POSH visits (hazard ratio, 0.72; 95% CI, 0.66-0.79). For patients on the medicine service with a LACE readmission risk score of 11 or greater, seeing a PCC during a POSH visit had stronger effects compared with a non-POSH PCC visit (hazard ratio, 0.80; 95% CI, 0.67-0.94). Follow-up visits did not have an effect on readmission in surgical patients.

Discussion

We found that any follow-up visit with a PCC within 7 days of discharge was associated with a lower risk for 30-day readmission for patients on the medicine service and that a POSH PCC visit was better than a non-POSH PCC visit for higher-risk patients. These positive findings that differ from other published findings4 could be attributed to our overall, system-wide efforts to ensure continuity between the inpatient and outpatient settings. Having a POSH visit likely heightened the care team’s preparedness to address patients’ immediate postdischarge care needs, including an assessment of clinical status and treatment intensification if needed, follow-up of pending test results and referrals, medication review, and patient and family education.

This analysis was limited to Medicare Advantage patients discharged from Kaiser Permanente hospitals to home; these findings may not generalize to patients discharged to other higher-level settings or non-Medicare patients. Omission of unmeasured confounders, such as exposure to other care transition interventions, treatment adherence, and social risks, are other notable limitations. Although we do not know what aspect of the visit was helpful in reducing readmissions, our findings highlight the value of postdischarge visits in integrated systems with a comprehensive EHR.

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Article Information

Corresponding Author: Huong Q. Nguyen, PhD, RN, Department of Research and Evaluation, Kaiser Permanente Southern California, 100 S Los Robles Ave, Second Floor, Pasadena, CA 91101 (huong.q2.nguyen@kp.org).

Published Online: November 21, 2016. doi:10.1001/jamainternmed.2016.7061

Author Contributions: Drs Shen and Nguyen had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Koyama, Huynh, Watson, Mittman, Kanter, Nguyen.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Shen, Huynh, Watson, Nguyen.

Critical revision of the manuscript for important intellectual content: Shen, Koyama, Watson, Mittman, Kanter, Nguyen.

Statistical analysis: Shen, Nguyen.

Obtained funding: Nguyen.

Administrative, technical, or material support: Koyama, Kanter, Nguyen.

Study supervision: Koyama, Watson, Nguyen.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was partially supported through our collaboration with Project ACHIEVE—a Patient-Centered Outcomes Research Institute (PCORI) Awardee (TC-1403-14049)—and partially through internal operational funding from Kaiser Permanente Southern California.

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: All statements in this study, including its findings and conclusions, are solely those of the authors and do not necessarily represent the views of the PCORI, its board of governors, or its methodology committee.

Additional Contributions: Janet Lee, MS, and Jianjin Wang, MS, Department of Research and Evaluation, Kaiser Permanente Southern California, assisted in acquiring the data. They received no extra compensation for this contribution. We thank the Project ACHIEVE (Achieving Patient-Centered Care and Optimized Health In Care Transitions by Evaluating the Value of Evidence) Team for their helpful comments and suggestions.

References
1.
Hansen  LO, Young  RS, Hinami  K, Leung  A, Williams  MV.  Interventions to reduce 30-day rehospitalization: a systematic review.  Ann Intern Med. 2011;155(8):520-528.PubMedGoogle ScholarCrossref
2.
Hernandez  AF, Greiner  MA, Fonarow  GC,  et al.  Relationship between early physician follow-up and 30-day readmission among Medicare beneficiaries hospitalized for heart failure.  JAMA. 2010;303(17):1716-1722.PubMedGoogle ScholarCrossref
3.
Jackson  C, Shahsahebi  M, Wedlake  T, DuBard  CA.  Timeliness of outpatient follow-up: an evidence-based approach for planning after hospital discharge.  Ann Fam Med. 2015;13(2):115-122.PubMedGoogle ScholarCrossref
4.
Field  TS, Ogarek  J, Garber  L, Reed  G, Gurwitz  JH.  Association of early post-discharge follow-up by a primary care physician and 30-day rehospitalization among older adults.  J Gen Intern Med. 2015;30(5):565-571.PubMedGoogle ScholarCrossref
5.
van Walraven  C, Dhalla  IA, Bell  C,  et al.  Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community.  CMAJ. 2010;182(6):551-557.PubMedGoogle ScholarCrossref
6.
Schmid  NA.  Reducing patient falls: a research-based comprehensive fall prevention program.  Mil Med. 1990;155(5):202–207. PubMedGoogle Scholar
7.
McCaffrey  DF, Griffin  BA, Almirall  D, Slaughter  ME, Ramchand  R, Burgette  LF.  A tutorial on propensity score estimation for multiple treatments using generalized boosted models.  Stat Med. 2013;32(19):3388-3414.PubMedGoogle ScholarCrossref
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