Impact of early primary care follow-up after discharge on hospital readmissions

Bricard, Damien; Or, Zeynep

doi:10.1007/s10198-018-1022-y

Cited by 28 publications

(13 citation statements)

References 48 publications

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“…Our research confirms and extends previous work, 9,33 suggesting that at the hospital level, higher care transition scores are associated with higher rates of PCP follow-up visits. In fully adjusted analysis, however, the relationship between transition scores and rates of PCP follow-up was no longer significant, suggesting that community characteristics facilitate or impede timely PCP follow-up to an extent that may overshadow in-hospital efforts.…”

Section: Discussionsupporting

confidence: 91%

“…Several of these factors are not directly under a hospital's control, including economic conditions in the hospital county, rates of uninsured, and the proportion of Medicaid recipients in the hospital patient population. Poorer followup rates in poorer counties, if these rates lead to increased readmissions and thus to lower reimbursement for care, have the potential to financially weaken hospitals in the counties most in need of adequate health care 9,33.…”

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confidence: 99%

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The association between hospital care transition planning and timely primary care follow‐up

Mitchell

Probst

2021

The Journal of Rural Health

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Purpose To determine whether Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) Care Transitions (CTM‐3) Scores were associated with timely (14‐day) primary care provider (PCP) follow‐up visits, and to look for disparities across various types of urban and rural hospitals. Methods Data were obtained for 3,299 hospitals: 2,000 urban, 544 micropolitan prospective payment system (PPS), 109 micropolitan critical access hospital (CAH), 252 noncore rural PPS, and 394 noncore rural CAH. HCAPPS data were drawn from CMS Hospital Compare (2015). The dependent variable, 14‐day PCP follow‐up rate for each hospital, was drawn from the 2015 Dartmouth Atlas. Findings In analysis adjusting only for hospital characteristics, higher CTM‐3 scores were positively associated with PCP follow‐up; however, the relationship was no longer significant after controlling for area‐level (contextual) measures, such as percent minority population, percent unemployed, and percent uninsured. In the fully adjusted model, rates of PCP follow‐up were significantly higher for micropolitan PPS, noncore PPS, and noncore CAH hospitals than for urban hospitals. Conclusions In fully adjusted analysis, the lack of significance between CTM‐3 scores and PCP follow‐up suggests that community characteristics facilitate or impede timely PCP follow‐up to an extent that may overshadow in‐hospital efforts. Disparities between CAHs and rural PPS hospitals may be due to differing enrollments in quality incentive plans; future research is needed to address this issue. Compounding this issue, the strong negative relationship between percent Medicaid reimbursement (payor mix) and PCP follow‐up suggests possible disparities for safety net hospitals.

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Section: Discussionsupporting

confidence: 91%

mentioning

confidence: 99%

The association between hospital care transition planning and timely primary care follow‐up

Mitchell

Probst

2021

The Journal of Rural Health

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“…Overseas observational studies have found that health outcomes can be improved and health service use reduced by enrolling people with a preferred general practitioner in order to promote continuity of care, 1 providing longer GP consultations, 2 and more timely general practice follow‐up after major health events, such as emergency department presentations and hospitalisations 3 . In 2017, the Royal Australian College of General Practitioners, in collaboration with the Australian government, invited proposals from general practice research networks for two trials to assess the effects on health outcomes and health service use in Australia of interventions including these three components.…”

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confidence: 99%

A general practice intervention for people at risk of poor health outcomes: the Flinders QUEST cluster randomised controlled trial and economic evaluation

Reed

Roeger

Kwok

et al. 2022

Medical Journal of Australia

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Objective To determine whether a multicomponent general practice intervention cost‐effectively improves health outcomes and reduces health service use for patients at high risk of poor health outcomes. Design, setting Clustered randomised controlled trial in general practices in metropolitan Adelaide. Participants Three age‐based groups of patients identified by their general practitioners as being at high risk of poor health outcomes: children and young people (under 18 years), adults (18–64 years) with two or more chronic diseases, and older people (65 years or more). Intervention Enrolment of patients with a preferred GP, longer general practice appointments, and general practice follow‐up within seven days of emergency department and hospital care episodes. Intervention practices received payment of $1000 per enrolled participant. Main outcome measures Primary outcome: change in self‐rated health between baseline and 12‐month follow‐up for control (usual care) and intervention groups. Secondary outcomes: numbers of emergency department presentations and hospital admissions, Medicare specialist claims and Pharmaceutical Benefits Scheme (PBS) items supplied, Health Literacy Questionnaire scores, and cost‐effectiveness of the intervention (based on the number of quality‐adjusted life‐years [QALYs] gained over 12 months, derived from EQ‐5D‐5L utility scores for the two adult groups). Results Twenty practices with a total of 92 GPs were recruited, and 1044 eligible patients participated. The intervention did not improve self‐rated health (coefficient, –0.29; 95% CI, –2.32 to 1.73), nor did it have significant effects on the numbers of emergency department presentations (incidence rate ratio [IRR], 0.90; 95% CI, 0.69–1.17), hospital admissions (IRR, 0.90; 95% CI, 0.66–1.22), Medicare specialist claims (IRR, 1.00; 95% CI, 0.91–1.09), or PBS items supplied (IRR, 0.99; 95% CI, 0.96–1.03), nor on Health Literacy Questionnaire scores. The intervention was effective in terms of QALYs gained (v usual care: difference, 0.032 QALYs; 95% CI, 0.001–0.063), but the incremental cost‐effectiveness ratio was $69 585 (95% CI, $22 968–$116 201) per QALY gained, beyond the willingness‐to‐pay threshold. Conclusions Our multicomponent intervention did not improve self‐rated health, health service use, or health literacy. It achieved greater improvement in quality of life than usual care, but not cost‐effectively. Trial registration Australian New Zealand Clinical Trials Registry, ACTRN12617001589370 (prospective).

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“…Referral to tertiary care (ie, hospital) should occur soon after admission if possible 14. Several actions that involve multiple domains, such as early outpatient follow-up,15–17 medication reconciliation,18,19 self-management education, home care services, and remote follow-up (eg, telemedicine and telephone appointments),20,21 have successfully reduced readmission rates for patients discharged home 22. It should be noted that both the simplified and original HOSPITAL scores23 cannot (and should not) be calculated until discharge.…”

Section: Discussionmentioning

confidence: 99%

Accuracy of the Simplified HOSPITAL Score to Predict Nonelective Readmission in a Brazilian Tertiary Care Public Teaching Hospital

Júnior

Ulbrich

Gheno

et al. 2022

Quality Management in Health Care

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Background and Objectives: Predictive models to identify patients at high risk of readmission have gained the attention of health care teams, which have focused the strategies to reduce unnecessary readmissions on the "atrisk" patients. The HOSPITAL score includes 7 predictor variables with a C-statistic of 0.70 or more when applied to international datasets. Its simplified version retains a C-statistic at around the same level, but only incipient external validation has been attempted to date. The primary objective of this study was to evaluate the prognostic accuracy of the simplified HOSPITAL score to predict nonelective hospital readmissions in a tertiary care public teaching hospital in Brazil. Methods: We used a retrospective cohort that included all patients discharged from the internal medicine service of a Brazilian tertiary care public teaching hospital in 2018. We excluded patients who died before index discharge, were transferred to another institution, left against medical advice, or were readmitted electively. We calculated the simplified HOSPITAL score for each admission, and admissions were divided into low (0-4 points) or high risk (≥ 5 points) of nonelective 30-day readmission. We estimated accuracy, area under the receiver operating characteristic curve (AUC), and observed/expected (O/E) readmission ratio; the latter using the mid-P exact test with Miettinen's modification at a 95% confidence interval (CI). A P value < .05 was considered significant. Results: A total of 4472 hospital discharges were analyzed during the study period after application of the exclusion criteria. The nonelective 30-day readmission rate was 14.0% (n = 625). Of all patients discharged, 3173 (71.0%) were considered to be at low risk and 1299 (29.0%) at high risk of readmission according to the simplified HOSPITAL score. The AUC was 0.68 (95% CI: 0.66-0.71; P < .001). The nonelective 30-day readmission rate was 9.2% in the low-risk group (expected: 9.2%; O/E: 1.0 [95% CI: 0.89-1.12]) and 25.7% in the high-risk group (expected: 27.2%; O/E: 0.95 [95% CI: 0.85-1.05]) (P < .001). At a cut-off of 5 points, the score had a sensitivity of 53.4%, specificity of 74.9%, positive predictive value of 25.7%, and negative predictive value (NPV) of 90.8%. Conclusions: The parameters of the score were almost identical to the original study, with better applicability to exclude low-risk patients given its high NPV. Additional adjustments are still needed for better applicability in daily clinical practice.

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Impact of early primary care follow-up after discharge on hospital readmissions

Cited by 28 publications

References 48 publications

The association between hospital care transition planning and timely primary care follow‐up

The association between hospital care transition planning and timely primary care follow‐up

A general practice intervention for people at risk of poor health outcomes: the Flinders QUEST cluster randomised controlled trial and economic evaluation

Accuracy of the Simplified HOSPITAL Score to Predict Nonelective Readmission in a Brazilian Tertiary Care Public Teaching Hospital

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