Identifying Predictors of Nursing Home Admission by Using Electronic Health Records and Administrative Data: Scoping Review

Eunkyung Han; Hadi Kharrazi; Leiyu Shi

doi:10.2196/42437

journal article Nov 20, 2023

Identifying Predictors of Nursing Home Admission by Using Electronic Health Records and Administrative Data: Scoping Review

Eunkyung Han

Hadi Kharrazi

Leiyu Shi

JMIR Aging Vol. 6 pp. e42437-e42437 · JMIR Publications Inc.

View at Publisher Save 10.2196/42437

Abstract

Abstract

Background
Among older adults, nursing home admissions (NHAs) are considered a significant adverse outcome and have been extensively studied. Although the volume and significance of electronic data sources are expanding, it is unclear what predictors of NHA have been systematically identified in the literature via electronic health records (EHRs) and administrative data.

Objective
This study synthesizes findings of recent literature on identifying predictors of NHA that are collected from administrative data or EHRs.

Methods
The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines were used for study selection. The PubMed and CINAHL databases were used to retrieve the studies. Articles published between January 1, 2012, and March 31, 2023, were included.

Results
A total of 34 papers were selected for final inclusion in this review. In addition to NHA, all-cause mortality, hospitalization, and rehospitalization were frequently used as outcome measures. The most frequently used models for predicting NHAs were Cox proportional hazards models (studies: n=12, 35%), logistic regression models (studies: n=9, 26%), and a combination of both (studies: n=6, 18%). Several predictors were used in the NHA prediction models, which were further categorized into sociodemographic, caregiver support, health status, health use, and social service use factors. Only 5 (15%) studies used a validated frailty measure in their NHA prediction models.

Conclusions
NHA prediction tools based on EHRs or administrative data may assist clinicians, patients, and policy makers in making informed decisions and allocating public health resources. More research is needed to assess the value of various predictors and data sources in predicting NHAs and validating NHA prediction models externally.

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References

62

[1]

The World Health Organization (WHO) approach to healthy ageing

Ewa Rudnicka, Paulina Napierała, Agnieszka Podfigurna et al.

Maturitas 10.1016/j.maturitas.2020.05.018

[2]

World Health Organization. Integrated care for older people: realigning primary health care to respond to population ageing. World Health Organization. 2018. URL: https://apps.who.int/iris/handle/10665/326295 [Accessed 13-10-2023]

[3]

Shi L Singh DA . Essentials of the US Health Care System. 4thed. Jones & Bartlett Learning; 2017.

[4]

Mayo "Does the addition of functional status indicators to case-mix adjustment indices improve prediction of hospitalization, institutionalization, and death in the elderly?" Med Care 10.1097/01.mlr.0000185749.04875.cb

[5]

Wysocki A Butler M Kane RL Kane RA Shippee T Sainfort F . Long-term care for older adults: a review of home and community-based services versus institutional care. Agency for Healthcare Research and Quality. Nov2012. URL: https://effectivehealthcare.ahrq.gov/sites/default/files/pdf/long-term-care-adults_research.pdf [Accessed 13-10-2023]

[6]

Salminen "Factors associated with institutionalization among home-dwelling patients of urgent geriatric outpatient clinic: a 3-year follow-up study" Eur Geriatr Med 10.1007/s41999-020-00338-7

[7]

Predicting readmission and death after hospital discharge: a comparison of conventional frailty measurement with an electronic health record-based score

Yong Yong Tew, Juen Hao Chan, Polly Keeling et al.

Age and Ageing 10.1093/ageing/afab043

[8]

Seibert "The influence of primary care quality on nursing home admissions in a multimorbid population with and without dementia in Germany: a retrospective cohort study using health insurance claims data" BMC Geriatr 10.1186/s12877-021-02731-8

[9]

Gaugler "Predicting NHA in the U.S: a meta-analysis" BMC Geriatr 10.1186/1471-2318-7-13

[10]

Pawelek "The power of patient engagement with electronic health records as research participants" JMIR Med Inform 10.2196/39145

[11]

Cadarette "An introduction to health care administrative data" Can J Hosp Pharm 10.4212/cjhp.v68i3.1457

[12]

Kharrazi "Comparing population-based risk-stratification model performance using demographic, diagnosis and medication data extracted from outpatient electronic health records versus administrative claims" Med Care 10.1097/mlr.0000000000000754

[13]

Scoping studies: towards a methodological framework

Hilary Arksey, Lisa O'Malley

International Journal of Social Research Methodolo... 10.1080/1364557032000119616

[14]

Peters M Godfrey C McInerney P Soares C Khalil H Parker D . The Joanna Briggs Institute Reviewers’ Manual 2015: Methodology for JBI Scoping Reviews. The Joanna Briggs Institute; 2015.

[15]

PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation

Andrea C. Tricco, Erin Lillie, Wasifa Zarin et al.

Annals of Internal Medicine 10.7326/m18-0850

[16]

Meiqari "How have researchers defined and used the concept of ‘continuity of care’ for chronic conditions in the context of resource-constrained settings? a scoping review of existing literature and a proposed conceptual framework" Health Res Policy Syst 10.1186/s12961-019-0426-1

[17]

Martinez-Reig "The orthogeriatrics model of care: systematic review of predictors of Institutionalization and mortality in post-hip fracture patients and evidence for interventions" J Am Med Dir Assoc 10.1016/j.jamda.2012.07.011

[18]

Korhonen "Time-varying effects of socio-demographic and economic factors on the use of institutional long-term care before dementia-related death: a Finnish register-based study" PLoS One 10.1371/journal.pone.0199551

[19]

Nerius "The impact of antipsychotic drugs on long-term care, nursing home admission, and death in dementia patients" J Gerontol A Biol Sci Med Sci 10.1093/gerona/glx239

[20]

Müller "Development and internal validation of prognostic models to predict negative health outcomes in older patients with multimorbidity and polypharmacy in general practice" BMJ Open 10.1136/bmjopen-2020-039747

[21]

Runte "Predictors of institutionalization in people with dementia: a survey linked with administrative data" Aging Clin Exp Res 10.1007/s40520-017-0737-4

[22]

Joling "Time from diagnosis to institutionalization and death in people with dementia" Alzheimers Dement 10.1002/alz.12063

[23]

Park "Predictors of institutionalization in patients with Alzheimer's disease in South Korea" J Clin Neurol 10.3988/jcn.2018.14.2.191

[24]

Byers "Burden of depressive symptoms over 2 decades and risk of nursing home placement in older women" J Am Geriatr Soc 10.1111/jgs.15496

[25]

Joundi "Temporal trends in case fatality, discharge destination, and admission to long-term care after acute stroke" Neurology 10.1212/wnl.0000000000011791

[26]

Wahlsten "Living settings and cognitive impairment are stronger predictors of nursing home admission after hip fracture surgery than physical comorbidities a nationwide Danish cohort study" Injury 10.1016/j.injury.2020.06.041

[27]

Le Pogam "Development and validation of a knowledge-based score to predict Fried’s frailty phenotype across multiple settings using one-year hospital discharge data: the electronic frailty score" EClinicalMedicine 10.1016/j.eclinm.2021.101260

[28]

Amuah "Development and validation of a hospital frailty risk measure using Canadian clinical administrative data" CMAJ 10.1503/cmaj.220926

[29]

Hendin "Frailty is associated with decreased time spent at home after critical illness: a population-based study" J Intensive Care Med 10.1177/0885066620939055

[30]

Pappadis "Care patterns and predictors of community residence among older patients after hospital discharge for traumatic brain injury" J Am Geriatr Soc 10.1111/jgs.18308

[31]

Bailey "Traumatic brain injury and risk of long-term nursing home entry among older adults: an analysis of Medicare administrative claims data" J Neurotrauma 10.1089/neu.2022.0003

[32]

Kan "Defining and assessing geriatric risk factors and associated health care utilization among older adults using claims and electronic health records" Med Care 10.1097/mlr.0000000000000865

[33]

Kinosian "Validation of the JEN frailty index in the National Long-Term Care Survey community population: identifying functionally impaired older adults from claims data" BMC Health Serv Res 10.1186/s12913-018-3689-2

[34]

Byrne "Predictors of nursing home admission among a cohort of homeless older adults entering emergency shelter" Med Care 10.1097/mlr.0000000000001500

[35]

Segal "Development of a claims-based frailty indicator anchored to a well-established frailty phenotype" Med Care 10.1097/mlr.0000000000000729

[36]

Spoelstra "The contribution falls have to increasing risk of nursing home placement in community-dwelling older adults" Clin Nurs Res 10.1177/1054773811431491

[37]

Wang "The impact of different patterns of home- and community-based services on nursing home admission: national data from Taiwan" Soc Sci Med 10.1016/j.socscimed.2021.113679

[38]

Edmans "The Identification of Seniors at Risk (ISAR) score to predict clinical outcomes and health service costs in older people discharged from UK acute medical units" Age Ageing 10.1093/ageing/aft054

[39]

Temple "Informal care relationships and residential aged care recommendations: evidence from administrative data" BMC Geriatr 10.1186/s12877-017-0656-4

[40]

Betini "A longitudinal study looking at and beyond care recipient health as a predictor of long term care home admission" BMC Health Serv Res 10.1186/s12913-017-2671-8

[41]

Aspell "Predicting admission to long-term care and mortality among community-based, dependent older people in Ireland" Int J Geriatr Psychiatry 10.1002/gps.5101

[42]

Franchi "Multiple medication adherence and related outcomes in community-dwelling older people on chronic polypharmacy: a retrospective cohort study on administrative claims data" Int J Environ Res Public Health 10.3390/ijerph19095692

[43]

Franchi "Changes in clinical outcomes for community-dwelling older people exposed to incident chronic polypharmacy: a comparison between 2001 and 2009" Pharmacoepidemiol Drug Saf 10.1002/pds.3938

[44]

Clegg "Development and validation of an electronic frailty index using routine primary care electronic health record data" Age Ageing 10.1093/ageing/afw039

[45]

Pilotto "Using the Multidimensional Prognostic Index to predict clinical outcomes of hospitalized older persons: a prospective, multicenter, international study" J Gerontol A Biol Sci Med Sci 10.1093/gerona/gly239

[46]

Van den Bosch "Long-term care use and socio-economic status in Belgium: a survival analysis using health care insurance data" Arch Public Health 10.1186/0778-7367-71-1

[47]

Kim "Combined effects of four major geriatric syndromes on adverse outcomes based on Korean National Health Insurance claims data" Geriatr Gerontol Int 10.1111/ggi.13513

[48]

Cegri "The impact of frailty on admission to home care services and nursing homes: eight-year follow-up of a community-dwelling, older adult, Spanish cohort" BMC Geriatr 10.1186/s12877-020-01683-9

[49]

Moriyama "Effect of short-stay service use on stay-at-home duration for elderly with certified care needs: analysis of long-term care insurance claims data in Japan" PLoS One 10.1371/journal.pone.0203112

[50]

Berete "Predictors of nursing home admission in the older population in Belgium: a longitudinal follow-up of health interview survey participants" BMC Geriatr 10.1186/s12877-022-03496-4

Showing 50 of 62 references

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Details

Published: Nov 20, 2023
Vol/Issue: 6
Pages: e42437-e42437

Authors

Cite This Article

Eunkyung Han, Hadi Kharrazi, Leiyu Shi (2023). Identifying Predictors of Nursing Home Admission by Using Electronic Health Records and Administrative Data: Scoping Review. JMIR Aging, 6, e42437-e42437. https://doi.org/10.2196/42437

Identifying Predictors of Nursing Home Admission by Using Electronic Health Records and Administrative Data: Scoping Review

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