Presentation for NOVA Health Workshop "Management and efficiency of healthcare organizations" (2016.04.27)

1. Impact evaluation of the creation of Local
Health Units on the readmission of patients with
chronic conditions
Óscar Brito Fernandes1, Rui Santana1,2, Sílvia Lopes1,2
1 Escola Nacional de Saúde Pública | 2 Centro de Investigação em Saúde Pública
Management and Efficiency of Healthcare Organizations
Workshop NOVAhealth
2016.04.27

2.  Overview
 Aims
 Research design
 Results
 Discussion
 Conclusions
 References
SUMMARY
2

3. OVERVIEW
3

4.  Ageing populations(1,2), prevalence of multiple chronic conditions(2) and
the increasing pressure of burden of disease challenge nowadays
healthcare systems(3,4) and the way healthcare delivery is designed(5).
 Integrated care is an organizational principle for care delivery(6) as a
managerial response to differentiation and fragmentation(7).
 Integrated care is a way of assuming that there are modifiable factors
driving readmissions that could be targeted at a hospital-level to reduce
them(8).
 Readmission is a subsequent inpatient admission to any acute care facility
which occurs within 30 days of the discharge date of an eligible index
admission(9).
 Excessive unplanned readmission rates among hospitals could be a sign of
frail integrated care(8).
OVERVIEW 4

5.  Chronic conditions(10) includes health conditions that persist across time
and require healthcare, including non-communicable diseases, mental
disorders, some communicable conditions and on-going physical
impairments.
 Individuals with chronic conditions are more likely to experience hospital
readmission since they are more vulnerable to non-effective home
transitions after hospital discharge(11).
 The focus of many integrated care approached seems to have in common
the support to individuals with chronic conditions to live more
independently(12,13), with improvements to the patients’ care experience
and health outcomes.
OVERVIEW 5

6. AIMS
6

7.  Compare 30-day readmission rates in patients with chronic conditions in
Local Health Units and other hospitals.
 Assess the relationship of gender, age group, chronic conditions,
Elixhauser comorbidity index and institution type to time to readmission.
AIMS 7

8. RESEARCH DESIGN
8

9.  Outcome research
 Observational, analytical, longitudinal, and retrospective cohort study
 Datasets were provided by ACSS, Portuguese Central Administration for
Health Care System.
 Data refers to Portugal mainland hospital morbidity from 2002 to 2014,
including the period before and after creation of seven LHU.
 Statistic analysis:
 Generalized linear mixed models at the speciality cohort (AHRQ)
 (covariates age, discharge condition, comorbidities)
 Cox regression
 (covariates gender, age group, chronic conditions, comorbidities and hospital of treatment)
 Difference in differences
RESEARCH DESIGN 9

10. RESEARCH DESIGN 10
9 523 432 1 679 634
Treatment
n=845 275
Selected index admissions Treatment – Control sample
Control
n=834 359
Treatment group Control group
Included 7 LHU 6 hospitals
Selection criteria
Data available from pre- and post-
integration periods
(observation period: 8 years, 5 years
pre-integration, 3 post-integration)
- Be part of the same ACSS hospital
benchmark group as LHU
- Excluded hospitals with different
contexts (e.g., public-private
ventures)

11. RESEARCH DESIGN 11
Global impact models
Annual impact model
Difference in differences models

12. RESULTS
12

13. 13
Adjusted-readmission rate by chronic conditions
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
LHU (0 Chronic conditions)
Control group (0 Chronic conditions)
National readmission rate
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
8.0%
LHU (1 Chronic condition)
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
LHU (3 Chronic conditions)
Control group (3 Chronic…
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
16.0%
LHU (5 Chronic conditions)
Control group (5 Chronic…

14. Time to readmission: Cox regression
RESULTS 14
Covariate Scoring B SE(B) Hazard ratio (95% CI)
Gender 0: Male (Reference)
1: Female -0.125 0.007 0.882 (0.870 - 0.894)
Age 0: 0 - 19 (Reference)
1: 20 - 44 -0.233 0.014 0.792 (0.771 - 0.814)
2: 45 - 64 -0.260 0.014 0.771 (0.751 - 0.792)
3: 65 - 84 0.213 0.012 1.237 (1.208 - 1.266)
4: 85+ 0.553 0.014 1.739 (1.691 - 1.788)
Number of chronic
conditions 0 (Reference)
1 0.297 0.013 1.346 (1.311 - 1.382)
2 0.313 0.016 1.368 (1.325 - 1.413)
3 0.312 0.018 1.366 (1.318 - 1.417)
4 0.271 0.022 1.311 (1.256 - 1.369)
5+ 0.244 0.026 1.276 (1.212 - 1.343)
Elixhauser
comorbidity index 0 (Reference)
1 0.250 0.014 1.284 (1.250 - 1.319)
2 0.468 0.016 1.597 (1.546 - 1.649)
3 0.655 0.019 1.925 (1.854 - 1.998)
4 0.808 0.024 2.244 (2.143 - 2.350)
5+ 0.897 0.029 2.453 (2.317 - 2.596)
Institution type 0: Non-LHU (Reference)
1: LHU -0.129 0.007 0.879 (0.868 - 0.891)

15. RESULTS 15
Diff-in-Diff
Risk of readmission
Model 1 Model 2 Model 3 Specification test
Sample size
(LHU cases)
Odds Ratio
(95% CI)
R2 Odds Ratio
(95% CI)
R2 Odds Ratio
(95% CI)
R2
Wald test p-value
LHU 1
600 086 0.872
0.078
0.875
0.079
1.017
0.079 2.15 0.142
(69 725) (0.807 – 0.941) (0.810 – 0 .946) (0.940 – 1.101)
LHU 2
594 776 0.899
0.074
0.902
0.075
0.991
0.075 5.03 0.025
(62 738) (0.846 – 0.956) (0.846 – 0.961) (0.952 – 1.032)
LHU 3
603 417 0.949
0.083
0.949
0.083
0.911
0.083 1.06 0.304
(94 839) (0.859 – 1.049) (0.856 – 1.052) (0.837 – 0.991)
LHU 4
589 376 1.042
0.079
1.046
0.079
1.240
0.079 10.74 0.001
(64 711) (0.976 – 1.111) (0.980 – 1.117) (1.149 – 1.338)
LHU 5
614 334 0.844
0.079
0.846
0.080
0.860
0.080 3.73 0.05
(83 973) (0.779 – 0.914) (0.779 – 0.919) (0.790 – 0.936)
LHU 6
667 178 0.976
0.079
0.980
0.080
1.076
0.080 0.94 0.331
(136 817) (0.923 – 1.057) (0.905 – 1.061) (0.992 – 1.166)
LHU 7
527 353 0.947
0.087
0.946
0.088
0.937
0.088 0.05 0.820
(28 246) (0.832 – 1.079) (0.826 – 1.083) (0.866 – 1.013)

16. RESULTS 16
Diff-in-Diff
Risk of readmission
Model 1 Model 2 Model 3 Specification test
Sample size
(LHU cases)
Odds Ratio
(95% CI)
R2 Odds Ratio
(95% CI)
R2 Odds Ratio
(95% CI)
R2
Wald test p-value
LHU 1
600 086 0.872
0.078
0.875
0.079
1.017
0.079 2.15 0.142
(69 725) (0.807 – 0.941) (0.810 – 0 .946) (0.940 – 1.101)
LHU 2
594 776 0.899
0.074
0.902
0.075
0.991
0.075 5.03 0.025
(62 738) (0.846 – 0.956) (0.846 – 0.961) (0.952 – 1.032)
LHU 3
603 417 0.949
0.083
0.949
0.083
0.911
0.083 1.06 0.304
(94 839) (0.859 – 1.049) (0.856 – 1.052) (0.837 – 0.991)
LHU 4
589 376 1.042
0.079
1.046
0.079
1.240
0.079 10.74 0.001
(64 711) (0.976 – 1.111) (0.980 – 1.117) (1.149 – 1.338)
LHU 5
614 334 0.844
0.079
0.846
0.080
0.860
0.080 3.73 0.05
(83 973) (0.779 – 0.914) (0.779 – 0.919) (0.790 – 0.936)
LHU 6
667 178 0.976
0.079
0.980
0.080
1.076
0.080 0.94 0.331
(136 817) (0.923 – 1.057) (0.905 – 1.061) (0.992 – 1.166)
LHU 7
527 353 0.947
0.087
0.946
0.088
0.937
0.088 0.05 0.820
(28 246) (0.832 – 1.079) (0.826 – 1.083) (0.866 – 1.013)

17. RESULTS 17
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
I-4 I-3 I-2 I-1 I I+1 I+2
LHU 1
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
I-4 I-3 I-2 I-1 I I+1 I+2
LHU 2
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
I-4 I-3 I-2 I-1 I I+1 I+2
LHU 3
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
I-4 I-3 I-2 I-1 I I+1 I+2
LHU 4
0.6
0.7
0.8
0.9
1.0
1.1
1.2
I-4 I-3 I-2 I-1 I I+1 I+2
LHU 5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
I-4 I-3 I-2 I-1 I I+1 I+2
LHU 6
0.6
0.7
0.8
0.9
1.0
1.1
1.2
1.3
1.4
1.5
I-4 I-3 I-2 I-1 I I+1 I+2
LHU 7
Diff-in-Diff
Risk of readmission
(Annual model for each LHU)

18.  Age increase risk of readmission (85+ 74% more at risk than 0-19)
 Chronic conditions increase risk of readmission (from 28% to 37%)
 Increased comorbidites present higher risk of readmission
 LHU episodes present 12% less of a risk of readmission than control group
 Adjusted-readmission rates: LHU have lower rates for patients with
chronic conditions
 Decreased risk of readmission for 4 LHU ( 2 of them significant)
 Most LHU showed a decreasing risk of readmission after integration
RESULTS 18
MAIN FINDINGS

19. DISCUSSION
19

20. DISCUSSION 20
 Despite efforts for a better integrated care, LHU risk of
readmission do not follow a clear pattern for all. Other
studies found similar results over health outcomes(14,15).
 Evidence of different barriers for integrated care for each organization (e.g.,
higher number of primary care physicians associated with increase of
readmissions(16,17))
 There are vary interventions addressed to reduce hospital readmission with
different potential of effectiveness(18): e.g., case management(19), referral
networks(20), or follow-up after discharge(21-23)

21. DISCUSSION 21
 Chronic condition 5+ group is the one with decreased risk of
readmission compared to the reference group, in the
multivariate Cox regression .
 Univariate model shows increased risk of readmission along chronic condition
groups, similar to other studies(24).
 Possible evidence of better coordinated care for these patients?
 Adjusting readmission rates by chronic conditions, LHU
present lower readmission rates for chronic patients.
 Readmission rates reflect not only the quality of hospital care(25-27) but also
factors in patient’s homes and communities(28-30).

22. CONCLUSIONS
22

23. CONCLUSIONS 23
 There’s a research gap over integrated care and integration in Portugal.
 People with multiple chronic conditions are a growing sector of the
population(31) and attention should be given to younger age groups(13).
 Vertical integration in Portugal presents some evidence of reducing 30-day
readmissions for patients with chronic conditions, but it’s not consistent.
 Portugal needs to evolve towards a more integrated approach of
healthcare, increasing and deepening relations among levels of care(32).

24. REFERENCES
24
[1] Lee KH, Low LL, Allen J, Barbier S, Ng L, Ng M, et al. Transitional care for the highest risk patients: Findings of a randomized control study. Int J Integr
Care. 2015;15(October):1–10.
[2] Valentijn PP, Schepman SM, Opheij W, Bruijnzeels MA. Understanding integrated care: A comprehensive conceptual framework based on the integrative
functions of primary care. Int J Integr Care. 2013;13(4):1-10.
[3] Rachev BT. The economics of health service transformation. Clin Gov [Internet]. 2015;20(3):113. Available from:
http://search.proquest.com/docview/1719955705?accountid=45153
[4] Minkman MMN. The current state of integrated care: an overview. J Integr Care [Internet]. Emerald Group Publishing Limited; 2012 Nov 28;20(6):346–
58. Available from: http://www.emeraldinsight.com/doi/abs/10.1108/14769011211285147
[5] Mohrman SA, Kanter MH. Chapter 3 Designing for Health: Learning from Kaiser Permanente [Internet]. Organizing for Sustainable Health Care. Emerald
Group Publishing Ltd.; 2012. 77-111 p. Available from: http://dx.doi.org/10.1108/S2045-0605(2012)0000002007
[6] Shaw S, Rosen R, Rumbold B. What is integrated care? [Internet]. 2011. Available from:
http://www.nuffieldtrust.org.uk/sites/files/nuffield/publication/what_is_integrated_care_research_report_june11.pdf
[7] Lillrank P. Integration and coordination in healthcare: an operations management view. J Integr Care [Internet]. Emerald Group Publishing Limited; 2012
Feb 10 [cited 2016 Apr 18];20(1):6–12. Available from: http://www.emeraldinsight.com/doi/abs/10.1108/14769011211202247
[8] Bisognano, M, Boutwell A. Improving transitions to reduce readmissions. Front Health Serv Manage. 2009;25(3):3–10.
[9] Horwitz L, Grady J, Zhang W, DeBuhr J, Deacon S, Krumholz H, et al. 2015 Measure Updates and Specifications Report: Hospital-Wide All-Cause
Unplanned Readmission Measure - Version 4.0. 2015.
[10] WHO. Innovative care for chronic conditions: building blocks for action: global report. Noncommunicable Diseases and Mental Health. 2002. p. 1–99.
[11] Jackson CT, Trygstad TK, DeWalt DA, DuBard CA. Transitional care cut hospital readmissions for North Carolina medicaid patients with complex chronic
conditions. Health Aff. 2013;32(8):1407–15.
[12] Dorling G, Fountaine T, McKenna S, Suresh B. The Evidence for Integrated Care [Internet]. 2015. Available from:
http://www.mckinsey.com/~/media/McKinsey/dotcom/client_service/Healthcare Systems and Services/PDFs/The evidence for integrated care.ashx
[13] OECD. Health Reform: Meeting the Challenge of Ageing and Multiple Morbidities [Internet]. Meeting the Challenge of Ageing and Multiple Morbidities.
2011. Available from: http://www.oecd-ilibrary.org/social-issues-migration-health/health-reform_9789264122314-en
[14] Nolte E, Pitchforth E. What is the evidence on the economic impacts of integrated care? 2014;1–55.
[15] Walston SL, Kimberly JR, Burns LR. Owned vertical integration and health care: Promise and performance. Health Care Manage Rev [Internet]. 1996 Jan
[cited 2016 Apr 20];21(1):83–92. Available from: http://www.ncbi.nlm.nih.gov/pubmed/8647695
[16] Hernandez AF, Greiner M a, Fonarow GC, Hammill BG, Heidenreich P a, Yancy CW, et al. Relationship between early physician follow-up and 30-day
readmission among Medicare beneficiaries hospitalized for heart failure. JAMA [Internet]. 2010 May 5;303(17):1716–22. Available from:
http://www.ncbi.nlm.nih.gov/pubmed/20442387
[17] Sharma G, Kuo Y-F, Freeman JL, Zhang DD, Goodwin JS. Outpatient follow-up visit and 30-day emergency department visit and readmission in patients
hospitalized for chronic obstructive pulmonary disease. Arch Intern Med [Internet]. 2010 Oct 11;170(18):1664–70. Available from:
http://www.ncbi.nlm.nih.gov/pubmed/20937926
[18] Bradley EH, Curry L, Horwitz LI, Sipsma H, Thompson JW, Elma M, et al. Contemporary evidence about hospital strategies for reducing 30-day
readmissions: A national study. J Am Coll Cardiol [Internet]. Elsevier Inc.; 2012;60(7):607–14. Available from: http://dx.doi.org/10.1016/j.jacc.2012.03.067

25. REFERENCES
25
[19] White B, Carney PA, Flynn J, Marino M, Fields S. Reducing hospital readmissions through primary care practice transformation. J Fam Pract.
2014;63(2):67–74.
[20] Mascia D, Angeli F, Di Vincenzo F. Effect of hospital referral networks on patient readmissions. Soc Sci Med [Internet]. Elsevier Ltd; 2015;132:113–21.
Available from: http://dx.doi.org/10.1016/j.socscimed.2015.03.029
[21] Boccuti C, Casillas G. Aiming for Fewer Hospital U-turns : The Medicare Hospital Readmission Reduction Program. Policy Brief. 2015;1–10. Available
from: http://bit.ly/1KWsOkd
[22] Conroy SP, Dowsing T, Reid J, Hsu R. Understanding readmissions: An in-depth review of 50 patients readmitted back to an acute hospital within 30
days. Eur Geriatr Med [Internet]. Elsevier Masson SAS; 2013;4(1):25–7. Available from: http://dx.doi.org/10.1016/j.eurger.2012.02.007
[23] Hansen LO, Young RS, Hinami K, Leung A, Williams M V. Interventions to reduce 30-day rehospitalization: a systematic review. Ann Intern Med
[Internet]. 2011 Oct 18 [cited 2016 Apr 16];155(8):520–8. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22007045
[24] Friedman B, Jiang HJ, Elixhauser A. Costly hospital readmissions and complex chronic illness. Inquiry [Internet]. 2008;45(4):408–21. Available from:
http://www.ncbi.nlm.nih.gov/pubmed/19209836
[25] Bianco A, Molè A, Nobile CGA, Di Giuseppe G, Pileggi C, Angelillo IF. Hospital Readmission Prevalence and Analysis of Those Potentially Avoidable in
Southern Italy. PLoS One. 2012;7(11).
[26] Fischer C, Lingsma HF, Marang-van De Mheen PJ, Kringos DS, Klazinga NS, Steyerberg EW. Is the readmission rate a valid quality indicator? A review of
the evidence. PLoS One. 2014;9(11):1–10.
[27] Horwitz LI, Partovian C, Lin Z, Grady JN, Herrin J, Conover M, et al. Development and use of an administrative claims measure for profiling hospital-wide
performance on 30-day unplanned readmission. Ann Intern Med. 2014;161:S66–75.
[28] Kangovi S, Grande D, Meehan P, Mitra N, Shannon R, Long JA. Perceptions of readmitted patients on the transition from hospital to home. J Hosp Med.
2012;7(9):709–12.
[29] Hu J, Gonsahn MD, Nerenz DR. Socioeconomic status and readmissions: evidence from an urban teaching hospital. Health Aff (Millwood) [Internet].
2014 May;33(5):778–85. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24799574
[30] Joynt KE, Jha AK. A path forward on Medicare readmissions. N Engl J Med [Internet]. 2013 Mar 28;368(13):1175–7. Available from:
http://www.ncbi.nlm.nih.gov/pubmed/23465069
[31] Navickas R, Visockienė Ž, Puronaitė R, Rukšėnienė M, Kasiulevičius V, Jurevičienė E. Prevalence and structure of multiple chronic conditions in
Lithuanian population and the distribution of the associated healthcare resources. Eur J Intern Med. 2015;26(3):160–8.
[32] OECD. OECD Reviews of Health Care Quality: Portugal 2015. OECD Reviews of Health Care Quality. OECD Publishing; 2015 Apr.

26. Impact evaluation of the creation of Local Health Units on the readmission of
patients with chronic conditions
Óscar Brito Fernandes1, Rui Santana1,2, Sílvia Lopes1,2
1 Escola Nacional de Saúde Pública | 2 Centro de Investigação em Saúde Pública
o.fernandes@ensp.unl.pt
Management and Efficiency of Healthcare Organizations
Workshop NOVAhealth
2016.04.27
Thank you!