eISSN: 1896-9151
ISSN: 1734-1922
Archives of Medical Science
Current issue Archive Manuscripts accepted About the journal Special issues Editorial board Abstracting and indexing Subscription Contact Instructions for authors
SCImago Journal & Country Rank
5/2018
vol. 14
 
Share:
Share:
more
 
 
Clinical research

Discharge home health services referral and 30-day all-cause readmission in older adults with heart failure

Cherinne Arundel, Helen Sheriff, Donna M. Bearden, Charity J. Morgan, Paul A. Heidenreich, Gregg C. Fonarow, Javed Butler, Richard M. Allman, Ali Ahmed

Arch Med Sci 2018; 14, 5: 995–1002
Online publish date: 2018/08/13
Article file
- discharge home.pdf  [0.09 MB]
Get citation
ENW
EndNote
BIB
JabRef, Mendeley
RIS
Papers, Reference Manager, RefWorks, Zotero
AMA
APA
Chicago
Harvard
MLA
Vancouver
 
 

Introduction

Heart failure (HF) is a leading cause of 30-day all-cause readmission, a metric used in the U.S. healthcare system to reduce readmission to lower Medicare costs [1, 2]. Few transitional care interventions have been shown to be consistently associated with a lower risk of 30-day all-cause readmission in HF [3–5]. While some of the evidence-based HF drugs are effective in lowering the risk of 30-day all-cause readmission [6–12], none are effective in HF patients with preserved ejection fraction (HFpEF), who constitute over half of all older HF patients [13]. We have previously demonstrated that a discharge hospice referral is associated with a lower risk of 30-day all-cause readmission in patients with HF regardless of EF [14]. However, less is known about the association between home health care and 30-day all-cause readmission in HF [15, 16]. In the current analysis we examined the association between discharge home health referral and 30-day all-cause readmission in a propensity score-matched balanced cohort of HF patients.

Material and methods

Data source and study patients

The Alabama HF Project is a Medicare quality improvement project, the details of which have been previously described [8, 17, 18]. Briefly, medical records of 9649 fee-for-service Medicare beneficiaries who had a principal discharge diagnosis of HF based on International Classification of Diseases 9 codes were abstracted by trained abstractors. These patients were admitted for acute HF to 106 Alabama hospitals between July 1, 1998 and October 31, 2001. The 9649 hospitalizations occurred in 8555 unique patients, of whom 8049 were discharged alive. We restricted our analysis to the 6406 patients who were not admitted from nursing homes, who were discharged home, and who did not receive a discharge hospice referral. Of these, 1369 (21%) patients received a discharge referral for home health services (Figure 1).

Retrospective assembly of a balanced cohort

We used a non-parsimonious logistic regression model to estimate propensity scores for home health services referral for each of the 6406 patients [19–22]. In the model, home health services referral was the dependent variable and 33 measured baseline characteristics displayed in Figure 1 were used as covariates. The propensity score for home health referral is the conditional probability of receiving a home health referral based on these 33 baseline characteristics. We then used the propensity scores to assemble a matched cohort of 1253 pairs of patients receiving and not receiving home health referrals and examined between-group post-match balances for all 33 baseline characteristics using absolute standardized differences [23].

Outcomes data

Our primary outcome of interest was 30-day all-cause readmission. Other outcomes studied included 30-day all-cause mortality, 30-day HF readmissions, and a combined end-point of all-cause mortality or all-cause readmission at 30 days. All outcomes were examined at 12 months. Data on outcomes and time to events were obtained from Medicare claims data [17].

Statistical analyses

Descriptive analyses included Pearson’s 2 and Wilcoxon rank-sum tests as appropriate. Association analysis included Cox regression models among matched patients. Kaplan-Meier survival analysis was used to generate plots for 1-year all-cause readmissions by home health services referral. Formal sensitivity analyses were performed to determine the confounding impact of a potentially unmeasured baseline characteristic on our observed outcomes [24]. We also examined the association of home health services use with the primary outcome among the 6406 pre-match patients using Cox regression models, unadjusted and separately adjusting for propensity scores and the 33 variables used to estimate propensity scores. All statistical tests were two-tailed with a p-value < 0.05 considered significant. IBM SPSS Statistics for Windows, Version 23 Armonk, NY: IBM Corp. was used for data analyses.

Results

Baseline characteristics The 2506 matched patients had a mean age of 78 years, 61% were women, and 27% were African American. Before matching, patients receiving referrals for home health services were generally older and more likely to be female. More patients in the home health services group had prior HF, chronic obstructive pulmonary disease (COPD), or stroke, and fewer patients received discharge prescriptions for angiotensin-converting enzyme (ACE) inhibitors or angiotensin-receptor blockers (ARBs), and -blockers (Table I). These along with other imbalances were balanced in the matched cohort (Table I, Figure 2).

Associations with 30-day outcomes

Among matched patients, 30-day all-cause readmission occurred in 28% and 19% of matched patients receiving and not receiving home health services referrals, respectively (hazard ratio (HR) = 1.52; 95% confidence interval (CI): 1.29–1.80; Table II). Among pre-match patients, unadjusted, propensity score-adjusted, and multivariable-adjusted HRs for 30-day all-cause readmission associated with home health referrals were 1.59 (1.42–1.80), 1.46 (1.28–1.67), and 1.45 (1.27–1.65), respectively. Associations of home health referral with other 30-day outcomes are displayed in Table II.
Of the 1253 matched pairs of patients receiving and not receiving a home health referral, in 509 pairs we were able to identify patients who clearly had longer readmission-free 30-day survival than their matched counterparts. In the absence of a hidden bias, a sign-score test for matched data with censoring demonstrated that in 60% (303 pairs of the 509 pairs), the home health referral group had shorter event-free survival time than their matched counterparts without a home health referral (p < 0.001). A hidden covariate that is a near-perfect predictor of 30-day all-cause readmission could explain away this association if it increased the odds of home health referral by 19%.

Associations with 12-month outcomes

Twelve-month all-cause readmission occurred in 73% and 69% of matched patients receiving and not receiving home health care referrals, respectively (HR = 1.24; 95% CI: 1.13–1.36; Table II and Figure 3). Home health services referral was associated with a borderline significantly higher risk of HF readmission at 1 month but not at 12 months. Associations of home health services with other 12-month outcomes are displayed in Table II.

Discussion

Findings from our current analysis demonstrate that hospitalized older patients with HF who were discharged home with home health services had a significantly higher risk of both 30-day all-cause readmission and all-cause mortality, which persisted during 12 months of follow-up. The association with 30-day HF readmission was modest and of borderline significance, and disappeared during 12-month follow-up. To the best of our knowledge, this is the first propensity score-matched study to demonstrate that Medicare beneficiaries hospitalized for HF who were discharged home with home health services, a Medicare benefit, had a higher risk of 30-day all-cause readmission, the reduction of which is a goal of the Medicare Hospital Readmission Reduction Program [2].
Patients eligible for Medicare home health services must be homebound and need intermittent skilled nursing care, both of which must be certified by a physician, who must also establish a plan of care and regularly review it. Thus, home health care services that involve intermittent skilled nursing care under supervision of a physician are unlikely to have any causal association with poor outcomes in these patients. A higher risk of mortality in patients receiving home health services is likely explained by selection or indication bias, akin to higher mortality in patients receiving insulin, where the indication bias would be diabetes [25]. Because matched patients in our study were balanced on 33 key baseline characteristics, balanced unmodifiable baseline characteristics such as age or sex are unlikely to act as confounders. However, balanced modifiable baseline characteristic such as diabetes, chronic obstructive pulmonary disease, stroke, dementia, pneumonia, and pressure ulcer may act as confounders. If these conditions were more severe or advanced in the home health group, that may in part explain the higher mortality in the home health group, as matching cannot balance disease severity or incidence of new complications during follow-up. Bias due to unmeasured or unmeasurable confounders is also possible. Finally, lower ACE inhibitor and -blocker use in the home health group may also contribute to the higher mortality in that group [9, 11]. Although the use of these drugs was balanced after matching, if the causes of underuse at baseline (e.g., low blood pressure) continued during follow-up, then these drugs may be discontinued in more home health patients during follow-up.
Physician-supervised intermittent skilled nursing care received by home health patients is not likely to be causally associated with a higher risk of all-cause readmission, and bias by indication may explain the higher readmission in these patients. However, skilled nursing care, ironically, may also lead to a higher rate of hospital readmission due to frequent and prompt identification and reporting of the warning symptoms and signs to patients’ primary care physicians, who may perceive them to be more objective than those reported by patients and/or family [26]. Unlike hospice agencies, home health care agencies do not have provisions for paid in-house medical directors, and early warning signs need to be discussed with patients’ primary care physicians, which may lead to delays, worsening symptoms, and readmission [26]. Finally, the heterogeneity of care across home health teams, the lack of nursing staff specifically trained to manage HF patients, and unstructured communication during transition from hospital to home health care may also contribute [27, 28].
Interestingly, most of the 30-day all-cause readmissions associated with a home health referral was due to non-HF related causes. Of the 1253 pairs of matched patients, those in the home health group had 106 (346–240) more 30-day all-cause readmissions, but only 27 (137–110) of those were due to HF (Table II). Therefore, about 75% of all 30-day all-cause readmissions were non-HF related. The association of home health referral with HF readmission is weak and likely complex. The slightly higher 30-day HF readmission in the home health group, of borderline significance, disappeared during longer follow-up. It is possible that patients were referred to home health services for reasons other than HF, such as dementia and pressure ulcer. This notion is also supported by the observation that there was no between-group difference in HF severity as indicated by similar use of digoxin and diuretics. It is possible that the incidence of worsening HF symptoms was similar in both groups, but was identified and reported at a higher rate in home health patients [26]. For example, an older HF patient may respond to worsening shortness of breath and weight gain by limiting physical activity and mobility, but may be identified by a visiting home health team. This association disappears during 1-year follow-up as the average duration of home health services is about 3 months [29].
Several studies have examined the role of home health care in readmission in HF patients. In one study that compared home health care with three home visits by a nurse versus one outpatient visit to a physician during the first post-discharge week, neither approach was found to be associated with a significant reduction in 30-day all-cause readmission [16]. However, when both approaches were combined, there was evidence of a modest reduction in the risk of readmission that was significant. Findings from two small studies suggest that programs involving home visits by nurses or pharmacists to educate or reconcile medications may have a modest association with a lower risk of 30-day all-cause readmission, but HF readmission was not reported [4]. To the best of our knowledge, this is the first report of an association of home health care with poor outcomes in a propensity score-matched cohort of HF patients.
The Veterans Health Administration (VHA) Home Based Primary Care (HBPC) program that provides comprehensive multidisciplinary services to veterans with complex health care needs has been shown to be associated with a lower readmission rate in selected veterans with medically complex diabetes mellitus [30]. Hospitalized HF patients receiving discharge hospice referral are also sick and have a higher mortality but lower readmission [14]. Hospice patients forgo aggressive medical care in favor of palliative care, which in part may explain the lower readmission rates. However, it has also been suggested that the presence of a hospice medical director and standing orders may also contribute to the lower risk of readmission. Future randomized controlled trials need to examine whether these and other strategies such as improving physical activity and mobility incorporated into the home health services program would improve outcomes, thus providing evidence of cost effectiveness of a program that often allows hospitalized frail patients to go home [31, 32].
Our study has several limitations. We had no data on patient mobility, frailty, health literacy, social support, and need for skilled nursing care for patients not receiving home health services to determine their eligibility. As mentioned above, bias from unmeasured confounders and residual bias from measured confounders are possible. We had no data on compliance, and post-discharge crossover of home health use may result in misclassification and regression dilution [33]. Our analysis is based on fee-for-service Medicare beneficiaries from a single state in an earlier era of HF management, which may limit its generalizability. Additionally, our study cannot account for changes in Medicare payment policies that affect home health utilization and services. Despite these limitations, we hope that these data highlight the need and provide incentives for randomized controlled trials that can demonstrate the beneficial effect of home health care on mortality and readmission.
In conclusion, among hospitalized older HF patients, a discharge referral for home health services was associated with higher risks for 30-day and 1-year all-cause readmission and mortality but not with HF readmission. Future studies need to replicate these intriguing findings and explain the underlying reasons for the poor outcomes among patients referred to home health care.

Acknowledgments

Dr. Ali Ahmed was in part supported by the National Institutes of Health through grants (R01-HL085561, R01-HL085561-S and R01-HL097047) from the National Heart, Lung, and Blood Institute.

Conflict of interest

Dr. Fonarow reports consulting with Amgen, Novartis, Medtronic, and St Jude Medical and was the Principle Investigator of OPTIMIZE-HF. None of the other authors report any conflicts of interest related to this manuscript.

References

1. Jencks SF, Williams MV, Coleman EA. Rehospitalizations among patients in the Medicare fee-for-service program. N Engl J Med 2009; 360: 1418-28.
2. Konstam MA. Heart failure in the lifetime of musca domestica (The Common Housefly). JACC: Heart Failure 2013; 1: 178-80.
3. Hansen LO, Young RS, Hinami K, Leung A, Williams MV. Interventions to reduce 30-day rehospitalization: a systematic review. Ann Intern Med 2011; 155: 520-8.
4. Feltner C, Jones CD, Cene CW, et al. Transitional care interventions to prevent readmissions for persons with heart failure: a systematic review and meta-analysis. Ann Intern Med 2014; 160: 774-84.
5. Pierre-Louis B, Rodriques S, Gorospe V, et al. Clinical factors associated with early readmission among acutely decompensated heart failure patients. Arch Med Sci 2016; 12: 538-45.
6. Aronow WS. Update of treatment of heart failure with reduction of left ventricular ejection fraction. Arch Med Sci Atheroscler Dis 2016; 1: e106-16.
7. Bourge RC, Fleg JL, Fonarow GC, et al. Digoxin reduces 30-day all-cause hospital admission in older patients with chronic systolic heart failure. Am J Med 2013; 126: 701-8.
8. Ahmed A, Bourge RC, Fonarow GC, et al. Digoxin use and lower 30-day all-cause readmission for Medicare beneficiaries hospitalized for heart failure. Am J Med 2014; 127: 61-70.
9. Sanam K, Bhatia V, Bajaj NS, et al. Renin-angiotensin system inhibition and lower 30-day all-cause readmission in medicare beneficiaries with heart failure. Am J Med 2016; 129: 1067-73.
10. Desai AS, Claggett BL, Packer M, et al. Influence of sacubitril/valsartan (LCZ696) on 30-day readmission after heart failure hospitalization. J Am Coll Cardiol 2016; 68: 241-8.
11. Bhatia V, Bajaj NS, Sanam K, et al. Beta-blocker use and 30-day all-cause readmission in medicare beneficiaries with systolic heart failure. Am J Med 2015; 128: 715-21.
12. Lam PH, Dooley DJ, Inampudi C, et al. Lack of evidence of lower 30-day all-cause readmission in medicare beneficiaries with heart failure and reduced ejection fraction discharged on spironolactone. Int J Cardiol 2017; 227: 462-6.
13. Fonarow GC, Stough WG, Abraham WT, et al. Characteristics, treatments, and outcomes of patients with preserved systolic function hospitalized for heart failure: a report from the OPTIMIZE-HF Registry. J Am Coll Cardiol 2007; 50: 768-77.
14. Kheirbek RE, Fletcher RD, Bakitas MA, et al. Discharge hospice referral and lower 30-day all-cause readmission in medicare beneficiaries hospitalized for heart failure. Circ Heart Fail 2015; 8: 733-40.
15. Madigan EA, Gordon NH, Fortinsky RH, Koroukian SM, Pina I, Riggs JS. Rehospitalization in a national population of home health care patients with heart failure. Health Serv Res 2012; 47: 2316-38.
16. Murtaugh CM, Deb P, Zhu C, et al. Reducing readmissions among heart failure patients discharged to home health care: effectiveness of early and intensive nursing services and early physician follow-up. Health Serv Res 2017; 52: 1445-72.
17. Feller MA, Mujib M, Zhang Y, et al. Baseline characteristics, quality of care, and outcomes of younger and older medicare beneficiaries hospitalized with heart failure: findings from the Alabama Heart Failure Project. Int J Cardiol 2012; 162: 39-44.
18. Ahmed A, Fonarow GC, Zhang Y, et al. Renin-angiotensin inhibition in systolic heart failure and chronic kidney disease. Am J Med 2012; 125: 399-410.
19. Rosenbaum PR, Rubin DB. The central role of propensity score in observational studies for causal effects. Biometrika 1983; 70: 41-55.
20. Rubin DB. Using propensity score to help design observational studies: application to the tobacco litigation. Health Serv Outcomes Res Methodol 2001; 2: 169-88.
21. Ahmed MI, White M, Ekundayo OJ, et al. A history of atrial fibrillation and outcomes in chronic advanced systolic heart failure: a propensity-matched study. Eur Heart J 2009; 30: 2029-37.
22. Ahmed A, Husain A, Love TE, et al. Heart failure, chronic diuretic use, and increase in mortality and hospitalization: an observational study using propensity score methods. Eur Heart J 2006; 27: 1431-9.
23. Wahle C, Adamopoulos C, Ekundayo OJ, Mujib M, Aronow WS, Ahmed A. A propensity-matched study of outcomes of chronic heart failure (HF) in younger and older adults. Arch Gerontol Geriatr 2009; 49: 165-71.
24. Rosenbaum PR. Sensitivity to hidden bias. In: Observational Studies. Vol. 1. Rosenbaum PR (ed.). Springer-Verlag, New York 2002: 105-70.
25. Currie CJ, Poole CD, Evans M, Peters JR, Morgan CL. Mortality and other important diabetes-related outcomes with insulin vs other antihyperglycemic therapies in type 2 diabetes. J Clin Endocrinol Metab 2013; 98: 668-77.
26. Sanford DE, Olsen MA, Bommarito KM, et al. Association of discharge home with home health care and 30-day readmission after pancreatectomy. J Am Coll Surg 2014; 219: 875-86 e871.
27. Jones CD, Bowles KH, Richard A, Boxer RS, Masoudi FA. High-value home health care for patients with heart failure: an opportunity to optimize transitions from hospital to home. Circ Cardiovasc Qual Outcomes 2017; 10:pii: e003676.
28. Santomassino M, Costantini GD, McDermott M, Primiano D, Slyer JT, Singleton JK. A systematic review on the effectiveness of continuity of care and its role in patient satisfaction and decreased hospital readmissions in the adult patient receiving home care services. JBI Libr Syst Rev 2012; 10: 1214-59.
29. O’Connor M, Hanlon A, Naylor MD, Bowles KH. The impact of home health length of stay and number of skilled nursing visits on hospitalization among medicare-reimbursed skilled home health beneficiaries. Res Nurs Health 2015; 38: 257-67.
30. Edwards ST, Saha S, Prentice JC, Pizer SD. Preventing hospitalization with veterans affairs home-based primary care: which individuals benefit most? J Am Geriatr Soc 2017; 65: 1676-83.
31. Smolis-Bak E, Rymuza H, Kazimierska B, et al. Improvement of exercise tolerance in cardiopulmonary testing with sustained safety after regular training in outpatients with systolic heart failure (NYHA III) and an implantable cardioverter-defibrillator. Prospective 18-month randomized study. Arch Med Sci 2017; 13: 1094-101.
32. Fisher SR, Kuo YF, Sharma G, et al. Mobility after hospital discharge as a marker for 30-day readmission. J Gerontol A Biol Sci Med Sci 2013; 68: 805-10.
33. Clarke R, Shipley M, Lewington S, et al. Underestimation of risk associations due to regression dilution in long-term follow-up of prospective studies. Am J Epidemiol 1999; 150: 341-53.
Copyright: © 2018 Termedia & Banach. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License (http://creativecommons.org/licenses/by-nc-sa/4.0/), allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material, provided the original work is properly cited and states its license.
FEATURED PRODUCTS
Quick links
© 2018 Termedia Sp. z o.o. All rights reserved.
Developed by Bentus.
PayU - płatności internetowe