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Australian Commission on Safety and Quality in Health Care

Contents

Research question.

Research Strategy

Analysis.

How big was the treatment effect?.

How precise was the estimate of the treatment effect?.

Can the findings be generalized to, or beyond, the local population?.

Were all results of clinically significance considered?.

Are the costs and the damages worth the benefits?.

References.

The WHO defines Palliative care as “an approach that improves the quality of life of patients -young and old - and their families who are facing the challenges associated with life-threatening illness” (Simon, 2018). Nurses play a significant role in the delivery of end-of-life treatment and help patients reduce stress (Nursing and Midwifery Board of Australia, 2020). Comprehensive standard of care also involves end-of-life care that follows the principle of patient-centered and compassionate care (ACSQHC, 2019). Choosing a preferred place of death (PPoD) is the key component of palliative care (Chapman et al., 2018). Despite Advanced Care Planning and PPoD, the rate of deaths at hospitals remain high (Chapman et al., 2018). Hospitalization not only decreases the quality of life but also add burdens to the patient and their families (Chapman et al., 2018). There is a need for some strategies to be implemented to allow the people approaching their end of lives to die at their preferred place. Specialist Palliative Care (SPC) is the solution for the requirement for people seeking their choice at the end of life. Research studies have shown that Specialist Palliative Care interventions have significantly reduced the frequency and stay at acute hospitals. Also, it has been evidenced that SPC has improved symptoms of pain, nausea, and fatigue (Kassianos et al., 2018). A research question on Specialist Palliative Care interventions has been developed to know the usefulness of SPC interventions in reducing the hospital stay and whether these interventions are effective.

Research question

In people aged 65 and above, receiving end of life care in residential care homes, is Specialist Palliative Care interventions effective in the reduction of hospital stay?

Population- people aged 65 and above receiving end of life care, in residential homes/nursing care homes

Intervention- interventions/Specialist Palliative Care needs rounds/ ‘Needs Round’ to reduce hospital stay

Comparison- non-Specialist Palliative Care

Outcome- reduced frequency and length of stay at acute hospitals.

Research Strategy

Apart from framing a clinical question, the PICO framework was also used to develop research strategies (Palaskar, 2017).

PICO framework leads to the development of the following search terms:

  • Special* (specialist, specialized)
  • Hospital* (hospitalized, hospitalization, hospitals)

CINAHL plus was the website where research was conducted. Keyword fields were used to search for different terms. Synonyms such as palliative care or end of life care or terminal care were used and combined with the Boolean operator ‘OR’ to widen the search range.

  • Residential care ‘OR’ nursing home ‘OR’ nursing homes
  • The Boolean operator ‘AND’ was used to combine the search terms to narrow the results.

Truncator (*) was added to the search terms such as special* and hospital* to search these words in all their different forms simultaneously. For instance:

  • Special*(specialist, specialized)
  • Hospital*(hospitals, hospitalized, hospitalization, hospitalizations)

The search came out with 78 results.

Below is the screenshot of CINAHL Plus search results:

Analysis of Specialist Palliative Care Interventions

Forbat et al. (2020) chose stepped-wedge randomized control trial as it is most applicable to the study the research question (White et al., 2017). Forbat et al. (2020) randomized study trial with stepped-wedge comprises of the highest sample size to date (12 Australian care homes, 1700 residents). This research also employed the stepped wedge method (Forbat et al., 2020). Both clusters are in the control condition at the start of a stepped-wedge trial (SWT), and each cluster receives intervention as the trial ends (Thompson et al., 2017).The Critical Appraisal Skills Program tool (2018) for randomized controlled trials was utilized to examine the study.

Has the trial addressed a concentrated problem?

The study addressed the Specialist Palliative Care Needs Rounds (hereafter ‘Needs Rounds’) as an intervention in nursing homes, to reduce stay at acute hospitals. The trial aimed at nursing home residents aged 65 and above. ‘Needs Rounds’ means 60-min triage meetings conducted monthly in which about 10 residents were discussed (Forbat et al., 2020). These residents had no plan of care and had high burden symptoms. The intervention involved risk stratification to ensure the equal distribution of Specialist Palliative Care Services (Forbat et al., 2020). 

Primary and secondary results were explicitly stated. The primary finding was a test of the duration of stay for nursing home residents in hospitals. The total number, hospital admission costs, the standard of death, and the place of death were all included in the secondary result (Forbat et al., 2020).

Was the careful selection of patients randomized?

A Stepped Wedge Randomised Controlled Trial was adopted to reduce bias (Forbat et al., 2020). 21 Australian facilities were invited and participated in the trial. Residential homes were simply randomized to one of the five clusters by a researcher independent of the trial (Forbat et al., 2020). Sequence generation and site selection was managed by an internet-based program. The intervention phase consisted of indirect support and direct support which included clinical work with the residents that involves ‘Needs Rounds’. Another phase, that is the controlled phase, received the usual care (Forbat et al., 2020). The chief investigator of the study decided the timing of migration from a controlled condition to intervention.

Upon its conclusion, were all the patients who joined the trial adequately accounted for?

The trial accomplished as planned until the final site received intervention. The study involved 74 months and 124 months in the control phase and the intervention respectively. However, one of the twelve sites withdrew at month 12, leaving a negligible impact on the trial.

Are all of the patients, health professionals, and research staff 'blind' to treatment?

This trial does not include masking of the sites as it was inconvenient to blind the staff administering intervention (Forbat et al., 2020). The researchers have acknowledged the limitations of masking and there is no evidence of potential bias associated with the lack of blinding.

However, there were some measures taken in place to reduce the bias. As randomization was conducted by a trial independent researcher and the use of internet programming in site selection for interventions.

By the start of the study, were all of the groups similar?

Residents participating in the trial included age group of 65 and above, 36% of them were male and with varying physical diagnosis (Forbat et al., 2020).

Apart from the experimental intervention, did the groups receive equal treatment?

Care home residents were treated equally and according to their preferences. 'Needs Rounds' intervention ensures that Specialist Palliative Care Services are equally and effectively distributed (Forbat et al., 2020).

How big was the treatment effect?

The initial outcome was identified and achieved, as the trial ended successfully with fewer acute hospital transfers (Forbat et al., 2020). Duration of stay (primary outcome) decreased significantly in the intervention phase by 23%, from 5.6 to 4.3 days per facility per month. In total, hospital days reduced from 39 to 27 (by 31%) per facility per month (Forbat et al., 2020). Apart from the primary outcome, Specialist Palliative Care Needs Rounds resulted in several secondary outcomes. These included an increase in the number of individuals dying at their preferred place, reduced frequency, and cost of hospitalization. Annual net saving of A$ 1,759,011 from reduced hospital admissions was observed. 

How precise was the estimate of the treatment effect?

Adjusting demographics, exposure and fidelity duration, resident characteristics, ‘Needs Round’ reduced the hospital stay by 0.22 days (95% Confidence Interval, p=0.038). High and moderate fidelity sites resulted in reduced length of stay by 0.26 days (95% Confidence Interval, p=0.015) (Forbat et al., 2020). 95% Confidence Interval means that there is a 5% probability of getting wrong results, corresponding to p<0.05 (Cathala & Moorley, 2018). Probability or p-value of less than 1 in 20 (5%, p<0.05) is considered as statistically significant and determines the effectiveness of intervention (Gupta, 2012). The null hypothesis can be rejected, and the intervention can be considered of statistical significance, if the probability is p<0.05 (Gupta, 2012). Thus, the effect of ‘Needs Rounds’ is considered to be effective.

Can the findings be generalized to, or beyond, the local population?

These outcomes can be applied in international as well as local nursing home settings because of the effective primary and secondary outcomes. Implementation of Needs Rounds is easy and reduces stay, frequency, and cost related to hospital admissions (Forbat et al., 2020). Reduced hospitalization also improves the quality of living for people staying in nursing homes, approaching their end of life (Forbat et al., 2020).

Were all results of clinically significance considered?

This study included all the essential clinical outcomes and resulted in positive primary and secondary outcomes already mentioned.

Are the costs and the damages worth the benefits?

There were no harms or adverse effects reported (Forbat et al., 2020). Reduced hospitalizations resulted in substantial savings related to admission costs. ‘Needs Rounds’ is a cost-effective mechanism where the Government can invest in, to decrease acute admission related costs (Forbat et al., 2020).

References for Specialist Palliative Care Interventions

Australian Commission on Safety and Quality in Health Care (ACSQHC). (2019). National Safety and Quality Health Service Standards. http://www.safetyandquality.gov.au.

Simon, J. (2018). Who needs palliative care? CMAJ : Canadian Medical Association Journal = Journal de l'Association Medicale Canadienne, 190(9), E234–E235. https://doi.org/10.1503/cmaj.170956

Chapman, M., Johnston, N., Lovell, C., Forbat, L., & Liu, W. (2018). Avoiding costly hospitalization at the end of life: Findings from a specialist palliative care pilot in residential care for older adults. BMJ Supportive & Palliative Care, 8(1), 102. http://dx.doi.org/10.1136/bmjspcare-2015-001071

Kassianos, A. P., Ioannou, M., Koutsantoni, M., & Charalambous, H. (2018). The impact of specialized palliative care on cancer patients’ health-related quality of life: A systematic review and meta-analysis. Supportive Care in Cancer, 26(1), 61-79. http://dx.doi.org/10.1007/s00520-017-3895-1

Nursing and Midwifery Board of Australia (2020). Code of Conduct. https://www.nursingmidwiferyboard.gov.au.

Palaskar, J. (2017). Framing the research question using PICO strategy. Journal of Dental & Allied Sciences, 6(2), 55. http://dx.doi.org/10.4103/jdas.jdas_46_17

Forbat, L., Liu, W.-M., Koerner, J., Lam, L., Samara, J., Chapman, M., & Johnston, N. (2020). Reducing time in acute hospitals: A stepped-wedge randomised control trial of a specialist palliative care intervention in residential care homes. Palliative Medicine34(5), 571–579. https://doi.org/10.1177/0269216319891077

Thompson, J. A., Fielding, K. L., Davey, C., Aiken, A. M., Hargreaves, J. R., & Hayes, R. J. (2017). Bias and inference from misspecified mixed‐effect models in stepped wedge trial analysis. Statistics in Medicine36(23), 3670–3682. https://doi.org/10.1002/sim.7348

White, S., Raghavendra, P., & Mcallister, S. (2017). Letting the CAT out of the bag: Contribution of critically appraised topics to evidence-based practice. Evidence-Based Communication Assessment and Intervention11(1-2), 27–37. https://doi.org/10.1080/17489539.2017.1333683

Gupta S. K. (2012). The relevance of confidence interval and P-value in inferential statistics. Indian Journal of Pharmacology44(1), 143–144. https://doi.org/10.4103/0253-7613.91895

Cathala X, Moorley C. (2018). How to appraise quantitative research. Evidence-Based Nursing, 21, 99-101. http://dx.doi.org/10.1136/eb-2018-102996

Remember, at the center of any academic work, lies clarity and evidence. Should you need further assistance, do look up to our Nursing Assignment Help

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