Phase V .Apa seven

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Influence Of Transitional Care in Hospital Readmission Among Elderly Patients

Phase 4- Outcomes

Dania Morejon

Florida National University

Nursing Research

Professor Dr. Barry E. Graham, DNP, MSN-Ed, RN

July 17, 2021

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Introduction

The key purpose regarding this study is to offer an explanation as well as the right set of

exploration regarding the nature of the identified relationships between the identified early

provider follow you as well as the nursing care coordination or intensity management type of

intensity. In this phase of the assignment, sample features will be illustrated first, with the right set

of comparisons between the various groups for the readmission as well as identified EPF within a

period of 14 days. Bivariate type of correlations between the identified variables will also be

effectively presented. Finally, the identified statistical analysis outcomes regarding each of the

research objectives will be effectively addressed (Albert, 2016).

Results

Research

In the following study, there was the identification of the vital upstream elements which are

associated with impacting the identified provision of the identified transitional care for the

identified elderly population. Transitional type of care for the elderly people by the identified

providers as well as nurses can be effectively tailored to the identified population elements like the

identified HF disease burden as well as the upstream elements like the neighborhood disadvantage

among others. Future CCTM type of nursing research should build on these types of individual

level types of interventions as well as in the identification of the trends and even designing of the

population level types of interventions to enhance outcomes (Bergethon et al., 2016).

Sample Characteristics

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After the identified extraction of cases meeting the identified inclusion criteria from the

given primary data associated file, exclusions as well as the identified data cleaning, a final study

associated sample that was if 1280 cases was effectively attained. The identified mean age

regarding the identified subjects was considered to be 79.5 whereby half of then were female

making up 50.7% of the total demographic and 25.9% of them were of the non white race. Given

the identified inclusion criteria regarding age ≥ 65, most of the identified subjects were found to be

effectively insured by the prominent Medicare which was 94.9%. 1.6% had been insured by the

famous Medicaid while 3.6% had been insured by private insurance. The median length regarding

the hospital stay was considered to be 5 days and about 31.8% were effectively discharged with

identified home associated healthcare (DeVore et al., 2016).

The primary residences of the subject were effectively disseminated across the identified

west which was 34.5% as well as the main which made up 18.4% and the east which made up

47.1% regions regarding the identified health associated system area. This made up a representing

of 6 key counties. Approximately all of the identified subjects in the identified study resided in the

urban places that is 92.0% as well as 20.2 % are considered to have lived in the most

disadvantaged types of neighborhoods which made up a number of 258. The identified 30 day

readmission level of rate for the identified final sample comprised of 13% (Butterfield, 2017).

The identified rate regarding the identified EPF within the identified 7 days was

considered to be 34 1% as well as 60.1% regarding subjects possessed EPF within the 14 days. The

identified CCTM intensity was one that ranged from 0-5 contacts for the identified sample, with

the identified 46.3% being in possession of at least a single CCTM contact within the identified 30

days as well as 38.8% being in possession of a CCTM contact within the identified 3 days after the

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given discharge. The tables below offer a summary regarding the patient features by readmission

status as well as EPF within the identified 14 days (Chetty et al., 2015).

Table 1

Patient Features as well as 30-Day Readmission type of Status

Readmission

Total No Yes p-

Sex .718

Female 649 50.7% 567 50.9% 82 49.4%

Male

Race

631

49.3%

547

49.1%

84

50.6%

.059

white 948 74.1% 835 75.0% 113 68.1%

non-white 332 25.9% 279 25.0% 53 31.9%

Length of stay*

Discharge disposition

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3,10

4

3,10

4

3,14

.069

.565

Home 873 68.2% 763 68.5% 110 66.3%

Home health 407 31.8% 351 31.5% 56 33.7%

Comorbidity Index* 37 27,62 36 26,62 44 32,65 <.001

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Neighborhood .029

least disadvantaged 1022 79.8% 900 80.8% 122 73.5%

most disadvantaged 258 20.2% 214 19.2% 44 26.5%

N=1114 (87.0%) value

Age* 79 80 73,94 .031

Comparison of Groups

It is important to note that six types of variables that is age as well as comorbidity index,

the identified neighborhood disadvantage, identified EPF within the 7days as well as the 14 days

and being in possession of 2 CCTM contacts were related with the readmission asked. The

identified patients who were considered to be readmitted were highly likely to be considered to be

younger as well as in possession of more types of comorbidities and living in the disadvantaged

N=1280 N=166 (13.0%)

73 94, 78 71 93,

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neighborhood as is compared to those that lacked readmission. The identified patients with the

identified readmissions more often were in possession of 2 CCTM types of contacts as well as the

fewer provider type of follow ups within the identified 7 or even 14 days than those that had no

readmissions. Moreover, the overall CCTM type of intensity was not related with the aspect of

readmission (Benjamin et al., 2017).

Table 1

Transitional type of Care as well as 30-Day Readmission type of Status

Readmission

Total

N=1280

No

N=1114 (87.0%)

Yes

N=166 (13.0%)

value

EPF competed

within 7 days

438

34.2%

396

35.5%

42

25.3% .009

within 14 days 769 60.1% 683 61.3% 86 51.8% .020

CCTM Intensity* 0 0, 4 0 0, 4 0 0, 4 .143

CCTM contact completed

within 3 days

496

38.8%

439

39.4%

57

34.3%

.211

within 30 days 592 46.3% 510 45.8% 82 49.4% .383

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Number of CCTM contacts

None

688

53.8%

604

54.2%

84

50.6%

.383

1 contact 271 21.2% 244 21.9% 27 16.3% .097

2 contacts 154 12.0% 124 11.1% 30 18.1% .010

3 contacts 78 6.1% 67 6.0% 11 6.6% .758

4 contacts 52 4.1% 44 3.9% 8 4.8% .597

5 contacts 37 2.9% 31 2.8% 6 3.6% .551

Early provider type of follow-up

In the comparison of patients who are considered to have completed a 14 day type of EPF

to those that did not, it is vital to note that 11 types of variables were essential as depicted by the

table below.

Table 3

Patient features as well as Early Provider type of Follow-Up Within the 14 Days

Early Provider type of Follow-up

No Yes p-value

Age* 80 72, 87 79 73, 86 .159

Sex <.001

Female 293 57.3% 356 46.3%

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Male 218 42.7% 413 53.7%

Race <.001

white 344 67.3% 604 78.5%

non-white 167 32.7% 165 21.5%

Length of stay* 4 3, 6 4 2, 6 .030

Discharge disposition .008

Home 327 64.0% 546 71.0%

Home health 184 36.0% 223 29.0%

Comorbidity Index* 38 27, 51 36 26, 47 .027

Neighborhood <.001

least disadvantaged 377 73.8% 645 83.9%

most disadvantaged 134 26.2% 124 16.1%

30-day readmission 80 15.7% 86 11.2% .020

CCTM Intensity* 0 0, 1 1 0, 2 <.001

CCTM contact completed

within 3 days

150

29.4%

346

45.0%

<.001

within 30 days 179 35.0% 413 53.7% <.001

Number of CCTM contacts

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None 332 65.0% 356 46.3% <.001

1 contact 72 14.1% 199 25.9% <.001

2 contacts 53 10.4% 101 13.1% 0.137

3 contacts 25 4.9% 53 6.9% 0.143

4 contacts 19 3.7% 33 4.3% 0.611

5 contacts 10 2.0% 27 3.5% 0.104

Relationship among the variables

Bivariate correlations among the identified study associated variable as well as the

covariates are considered to have ranged from the small to the moderate did the most of the

participants. The identified directions regarding the identified correlations are effectively

summarized in the figure below.

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Table 4

Multivariable Analysis of elements related with 30-Day type of Readmission

Variable B SE Wald df OR 95% CI p-value

EPF within 14 days -.364 .169 4.613 1 .695 .499, .969 .032

CCTM, 2 contacts .511 .227 5.075 1 1.666 1.069, 2.598 .024

Comorbidity Index .023 .006 16.324 1 1.023 1.012, 1.034 <.001

Limitations

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A limitation regarding the identified study was that the identified sample was taken from a

single health associated system which could lead to a threat to an identified external validity

associated to the identified context dependent type of mediation. Policies as well as the practices

associated to the transitional care type of activities may be particular to this kind of health

associated system, thus the identified associated between the identified early provider type of

follow up as well as the nursing type of CCTM may not take place in the other types of health

associated systems. However, the identified nursing practices at the given time regarding the

identified study were considered to be evidence based as well as they adhered to the AACN CCTM

type of model (Albert et al., 2015).

Moreover, the utility of the retrospective type of data in the identified primary study from

the identified medical records as well as billing type of data may lead to limitations associated to

accuracy as well as matching to the identified study associated variable. Also, the readmission type

of data that is attained from the original study may possess some limitations because of the utility

regarding solely the identified health system administrative type of data base for the identified

identification regarding the hospital readmissions.

Conclusion

The identified relationship that exists between the identified Early provider type of follow

up as well as the identified CCTM intensity, the identified hospital readmission and even the

identified neighborhood deprivation are considered to be complex. Living in the identified highly

disadvantaged type of neighborhood as well as high level of comorbidity were related with the

higher level of readmissions. Patients who are considered to have been associated with an EPF

within the identified 14 days possessed 30% decreased odds regarding being readmitted as is

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compared to the identified patients that possessed no EPF. However, it is vital to note that the

identified neighborhood type of disadvantage as well as comorbidity were related with minimized

EPF within the identified 14 days. Moreover, the identified comorbidity was related with the

higher level of the CCTM intensity, but higher level of neighborhood type of disadvantage was

related with less CCTM type of intensity (Bazemore et al., 2016).

The Identified early provider type of follow up was one that was directly related with the

decrement in the identified readmission in the identified elderly patients with HF as well as was not

considered to be conditional on level regarding the neighborhood type of disadvantage. Nursing

CCTM type of intensity did not in any way lead to an indirect impact regarding EPF within the 14

days on the identified readmission. However, it is vital to note that EPF within the identified 14

days was considered to be positively related with the identified CCTM intensity as well as

effectively moderated by the identified neighborhood disadvantage. Patients that were in

possession of early follow up types of appointments as well as were living in the areas of low to

the identified moderate neighborhood type of disadvantage were considered to possess more levels

of CCTM contacts (Cowell, 2018).

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References

Albert, N. M. (2016). A systematic review of transitional-care strategies to reduce rehospitalization

in patients with heart failure. Heart and Lung: Journal of Acute and Critical Care, 45, 100-

113. doi:10.1016/j.hrtlng.2015.12.001

Albert, N. M., Barnason, S., Deswal, A., Hernandez, A., Kociol, R., Lee, E., . . . White-Williams,

C. (2015). Transitions of care in heart failure: A scientific statement from the American

heart association. Circulation: Heart Failure, 8, 384-409.

doi:10.1161/HHF.0000000000000006

Bazemore, A. W., Cottrell, E. K., Gold, R., Hughes, L. S., Phillips, R. L., Angier, H., . . . DeVoe, J.

E. (2016). "Community vital signs": Incorporating geocoded social determinants into

electronic records to promote patient and population health. Journal of the American

Medical Informatics Association, 23, 407-412. doi:10.1093/jamia/ocv088

Benjamin, E. J., Blaha, M. J., Chiuve, S. E., Cushman, M., Das, S. R., Deo, R., . . . Muntner, P.

(2017). Heart disease and stroke statistics-2017 update: A report from the American Heart

Association. Circulation, 135(10), e146-e603.

Bergethon, K. E., Ju, C., DeVore, A. D., Hardy, N. C., Fonarow, G. C., Yancy, C. W., . . .

Hernandez, A. F. (2016). Trends in 30-day readmission rates for patients hospitalized with

heart failure: Findings from the get with the guidelines-heart failure registry.

Butterfield, P. G. (2017). Thinking Upstream: A 25-Year Retrospective and Conceptual Model

Aimed at Reducing Health Inequities. Advances in Nursing Science, 40(1), 2-11.

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Chetty, R., Stepner, M., Abraham, S., Lin, S., Scuderi, B., Turner, N., . . . Cutler, D. (2016). The

Association Between Income and Life Expectancy in the United States, 2001-2014.

Cowell, J. M. (2018). Population health: school health services and school nursing. The Journal of

School of Nursing, 34(1), 10. doi:10.1177/1059840517748720

DeVore, A. D., Hammill, B. G., Hardy, N. C., Eapen, Z. J., Peterson, E. D., & Hernandez, A. F.

(2016). Has Public Reporting of Hospital Readmission Rates Affected Patient Outcomes?:

Analysis of Medicare Claims Data. Journal of the American College of Cardiology, 67(8),

963-972. doi:10.1016/j.jacc.2015.12.037