Economic Evaluation of Quality Improvement Interventions Designed to Prevent Hospital Readmission

Nuckols, Teryl K.; Keeler, Emmett B.; Morton, Sally C.; Anderson, Laura; Doyle, Brian; Pevnick, Joshua M; Booth, Marika; Shanman, Roberta; Arifkhanova, Aziza; Shekelle, Paul G

doi:10.1001/jamainternmed.2017.1136

Cited by 86 publications

(74 citation statements)

References 82 publications

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“…This may be particularly valuable in many health care settings worldwide where health care resources may be scarce. In those settings, it is of utmost importance that the resources are prudently allocated to patients who need them the most, making it more crucial for accurate positive prediction of readmission . Further research may be useful to study efficiency of a threshold that reasonably maximizes sensitivity along the derivation cohort's ROC curve to achieve higher PPV.…”

Section: Discussionmentioning

confidence: 99%

Independent prospective validation of a medication‐based 15‐day readmission risk stratification algorithm in a tertiary acute care hospital

Yeo

Chew

Lai

2018

J Am Coll Clin Pharm

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Background To decrease health care costs and burden, reducing preventable readmissions is essential. A 2017 Singapore‐developed prediction model for readmission 15 days postdischarge was developed and validated. However, it has yet to be validated independently, and its predictability of 30‐day readmission is unknown. The model utilizes variables including age, anemia, malignancy, peptic ulcer disease, chronic obstructive pulmonary disease, number of discharge medications, discharge destination, and premature discharge against medical advice to calculate readmission risk. This study aimed to evaluate the model's performance in predicting readmissions 15 and 30 days postdischarge. Methods This single‐center, independent, prospective cohort study involved Singapore's Alexandra Hospital inpatients from September to November 2017. Readmission risk was calculated utilizing the developed model and information from electronic medical records. Primary and secondary outcomes were the model's performance for 15‐ and 30‐day readmission rates, respectively. Results One hundred thirteen and 112 patients were analyzed for primary and secondary outcomes, respectively. The model performed reproducibly against the original study derivation and validation cohorts. C‐statistics were 0.64 and 0.65, and Hosmer‐Lemeshow χ2’s were 7.28 and 6.85, respectively, for 15‐ and 30‐day readmissions. The Brier score was 0.26 for both end points. The low positive predictive value of 14% to 18% and correctly classified prediction rate of 53% to 54% could possibly be overcome by making the model more stringent in predicting readmissions. This may enhance efficiency in allocation of resources to assist patients with a higher likelihood of readmission. Conclusion This model's performance was reproducible in comparison to the original study's derivation and validation cohorts. Given the multifaceted nature of readmissions, it is challenging to accurately predict readmission. Along with clinical judgment, this model can potentially be a useful tool to health care providers for discharge planning purposes. Further research into optimizing the cut‐off probability may be useful to determine model utility in actual clinical practice.

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Section: Discussionmentioning

confidence: 99%

Independent prospective validation of a medication‐based 15‐day readmission risk stratification algorithm in a tertiary acute care hospital

Yeo

Chew

Lai

2018

J Am Coll Clin Pharm

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“…This cost (between $8.3 billion and $11.5 billion in 2009), if eliminated, would result in savings of $9.9 billion to $13.7 billion (CPI) . The total cost of HAIs is perhaps higher because the costs associated with physicians’ services, home nursing, and other nonhospital costs are excluded from this estimate …”

Section: Categories With Expenditures Not Intended For Carementioning

confidence: 99%

“…17 The total cost of HAIs is perhaps higher because the costs associated with physicians' services, home nursing, and other nonhospital costs are excluded from this estimate. 43…”

Section: Health Care-associated Infections (Hais)mentioning

confidence: 99%

How much of US health care spending provides direct care or benefit to patients?

Fredell

Kantarjian

Shih

et al. 2019

Cancer

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Plans to optimize health care in the United States highlight the high cost but rarely explore opportunities for redirecting resources within the existing system to increase access to care while lowering spending. This analysis indicates that, of the total national health care expenditures of $3.21 trillion in 2015, only $1.4 trillion to $2.86 trillion was used to provide care to patients. This range was reached by the subtraction of excess spending in 7 categories. Thus, many opportunities exist to repurpose wasted expenditures to increase access to health care without the need for additional funding.

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“…6,8 Of these efforts, interventions with a multidisciplinary, multicomponent approach have lowered readmission rates as well as improved patient care, patient adherence, and patient outcomes. [17][18][19][20][21][22][23][24][25] Specific quality improvement strategies that were significantly associated with reduced HF RSRR include a partnership with physicians or area hospitals, increased nursing involvement with medication reconciliation upon patient discharge, prearranged necessary follow-up appointments prior to discharge, providing patient discharge information directly to primary care physicians, and designation of hospital staff to follow-up with patient laboratory tests that return after patient discharge. 18 One study showed that the addition of postdischarge calls by a pharmacist in addition to a nurse discharge advocate resulted in a lower rate of hospital readmission.…”

Section: Introductionmentioning

confidence: 99%

Utilization of a multidisciplinary team to reduce the rate of hospital readmissions in high‐risk heart failure patients at a community teaching hospital: The pharmacist's role in transitions of care

Thurston

Liao

Lim

et al. 2019

J Am Coll Clin Pharm

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Introduction Since the implementation of the Hospital Readmission Reduction Program, health systems have been working to reduce hospital readmission rates of patients with heart failure (HF). Of these efforts, the interventions with a multidisciplinary, multicomponent approach have lowered readmission rates as well as improved patient care, patient adherence, and patient outcomes. Objectives The primary objective of this study was to determine if the addition of a pharmacist to the Transitional Care Team (TCT) would decrease the number of high‐risk HF patients readmitted to the hospital before 30 days. Secondarily, this study assessed the change in self‐reported medication adherence. Methods This study was conducted at a community teaching hospital. A retrospective chart review was performed to identify HF patients who were at high risk for readmission admitted to the hospital from May 2012 to October 2013, as the historical control group. The intervention group included high‐risk patients with HF admitted from May 2014 to October 2015, who received the pharmacist‐led intervention during hospitalization and postdischarge. The pharmacist‐led intervention comprised five components: medication reconciliation, medication cost/formulary review, medication discharge counseling, providing and educating patients regarding self‐monitoring resources and postdischarge telephone follow‐up. The 8‐item Morisky Medication Adherence Scale was used to measure patients' self‐reported medication adherence at baseline, then 30 days after discharge. Results The pharmacist‐led intervention assisted in decreasing the readmission rate from 33.7% in the historical control group to 21.3% in the intervention group with a relative risk reduction of 0.696 (confidence interval: 0.488‐0.994). There was also a significant improvement in self‐reported patient medication adherence scores. Conclusion The addition of a pharmacist to the TCT that managed HF patients was associated with a decrease in the readmission rate for patients who were at high risk of readmission and improved self‐reported patient medication adherence.

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Economic Evaluation of Quality Improvement Interventions Designed to Prevent Hospital Readmission

Cited by 86 publications

References 82 publications

Independent prospective validation of a medication‐based 15‐day readmission risk stratification algorithm in a tertiary acute care hospital

Independent prospective validation of a medication‐based 15‐day readmission risk stratification algorithm in a tertiary acute care hospital

How much of US health care spending provides direct care or benefit to patients?

Utilization of a multidisciplinary team to reduce the rate of hospital readmissions in high‐risk heart failure patients at a community teaching hospital: The pharmacist's role in transitions of care

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