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Application of an electronic Frailty Index in Australian primary care: data quality and feasibility assessment

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Abstract

Background

The primary care setting is the ideal location for identifying the condition of frailty in older adults.

Aims

The aim of this pragmatic study was twofold: (1) to identify data items to extract the data required for an electronic Frailty Index (eFI) from electronic health records (EHRs); and (2) test the ability of an eFI to accurately and feasibly identify frailty in older adults.

Methods

In a rural South Australian primary care clinic, we derived an eFI from routinely collected EHRs using methodology described by Clegg et al. We assessed feasibility and accuracy of the eFI, including complexities in data extraction. The reference standard for comparison was Fried’s frailty phenotype.

Results

The mean (SD) age of participants was 80.2 (4.8) years, with 36 (60.0%) female (n = 60). Frailty prevalence was 21.7% by Fried’s frailty phenotype, and 35.0% by eFI (scores > 0.21). When deriving the eFI, 85% of EHRs were perceived as easy or neutral difficulty to extract the required data from. Complexities in data extraction were present in EHRs of patients with multiple health problems and/or where the majority of data items were located other than on the patient’s summary problem list.

Discussion

This study demonstrated that it is entirely feasible to extract an eFI from routinely collected Australian primary care data. We have outlined a process for extracting an eFI from EHRs without needing to modify existing infrastructure. Results from this study can inform the development of automated eFIs, including which data items to best access data from.

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References

  1. Dent E, Kowal P, Hoogendijk EO (2016) Frailty measurement in research and clinical practice: a review. Eur J Intern Med 31:3–10

    Article  PubMed  Google Scholar 

  2. Noguchi N, Blyth FM, Waite LM et al (2016) Prevalence of the geriatric syndromes and frailty in older men living in the community: the Concord Health and Ageing in Men Project. Australas J Ageing 35:255–261

    Article  PubMed  Google Scholar 

  3. Syddall H, Roberts HC, Evandrou M et al (2010) Prevalence and correlates of frailty among community-dwelling older men and women: findings from the Hertfordshire Cohort Study. Age Ageing 39:197–203

    Article  PubMed  Google Scholar 

  4. Dent E, Lien C, Lim WS et al (2017) The Asia-Pacific clinical practice guidelines for the management of frailty. J Am Med Dir Assoc 18:564–575

    Article  PubMed  Google Scholar 

  5. Hoogendijk EO, van der Horst HE, Deeg DJ et al (2013) The identification of frail older adults in primary care: comparing the accuracy of five simple instruments. Age Ageing 42:262–265

    Article  PubMed  Google Scholar 

  6. Clegg A, Young J, Iliffe S et al (2013) Frailty in elderly people. Lancet 381:752–762

    Article  PubMed  Google Scholar 

  7. Morley JE, Vellas B, van Kan GA et al (2013) Frailty consensus: a call to action. J Am Med Dir Assoc 14:392–397

    Article  PubMed  PubMed Central  Google Scholar 

  8. Turner G, Clegg A (2014) Best practice guidelines for the management of frailty: a British Geriatrics Society, Age UK and Royal College of General Practitioners report. Age Ageing 43:744–747

    Article  PubMed  Google Scholar 

  9. Frank C, Wilson CR (2015) Models of primary care for frail patients. Can Fam Physician (Medecin de famille canadien) 61:601–606

    Google Scholar 

  10. Romero-Ortuno R (2015) Frailty in primary care. Interdiscip Top Gerontol Geriatr 41:85–94

    Article  PubMed  Google Scholar 

  11. Muscedere J, Andrew MK, Bagshaw SM et al (2016) Screening for frailty in Canada’s health care system: a time for action. Can J Aging (La revue canadienne du vieillissement) 35:281–297

    Article  Google Scholar 

  12. Mitnitski AB, Mogilner AJ, Rockwood K (2001) Accumulation of deficits as a proxy measure of aging. Sci World J 1:323–336

    Article  CAS  Google Scholar 

  13. Clegg A, Bates C, Young J et al (2016) Development and validation of an electronic Frailty Index using routine primary care electronic health record data. Age Ageing 45:353–360

    Article  PubMed  PubMed Central  Google Scholar 

  14. Drubbel I, de Wit NJ, Bleijenberg N et al (2013) Prediction of adverse health outcomes in older people using a frailty index based on routine primary care data. J Gerontol Ser A Biol Sci Med Sci 68:301–308

    Article  Google Scholar 

  15. Lansbury LN, Roberts HC, Clift E et al (2017) Use of the electronic Frailty Index to identify vulnerable patients: a pilot study in primary care. Br J Gen Pract J R Coll Gen Pract 67:e751–e756

    Article  Google Scholar 

  16. Stow D, Matthews FE, Barclay S et al (2018) Evaluating frailty scores to predict mortality in older adults using data from population based electronic health records: case control study. Age Ageing 47:564–569

    Article  PubMed  PubMed Central  Google Scholar 

  17. Clegg A, Bates C, Young J et al (2018) Development and validation of an electronic Frailty Index using routine primary care electronic health record data. Age Ageing 47:319

    PubMed  Google Scholar 

  18. Ambagtsheer R, Visvanathan R, Cesari M et al (2017) Feasibility, acceptability and diagnostic test accuracy of frailty screening instruments in community-dwelling older people within the Australian general practice setting: a study protocol for a cross-sectional study. BMJ Open 7:e016663

    Article  PubMed  PubMed Central  Google Scholar 

  19. Hofmans-Okkes IM, Lamberts H (1996) The international classification of primary care (ICPC): new applications in research and computer-based patient records in family practice. Fam Pract 13:294–302

    Article  CAS  PubMed  Google Scholar 

  20. Fried LP, Tangen CM, Walston J et al (2001) Frailty in older adults: evidence for a phenotype. J Gerontol Ser A Biol Sci Med Sci 56:M146–M156

    Article  CAS  Google Scholar 

  21. Washburn RA, Smith KW, Jette AM et al (1993) The Physical Activity Scale for the Elderly (PASE): development and evaluation. J Clin Epidemiol 46:153–162

    Article  CAS  PubMed  Google Scholar 

  22. Richardson MT, Leon AS, Jacobs DR Jr et al (1994) Comprehensive evaluation of the Minnesota Leisure Time Physical Activity Questionnaire. J Clin Epidemiol 47:271–281

    Article  CAS  PubMed  Google Scholar 

  23. Woo J, Leung J, Morley JE (2012) Comparison of frailty indicators based on clinical phenotype and the multiple deficit approach in predicting mortality and physical limitation. J Am Geriatr Soc 60:1478–1486

    Article  PubMed  Google Scholar 

  24. Searle SD, Mitnitski A, Gahbauer EA et al (2008) A standard procedure for creating a frailty index. BMC Geriatr 8:24

    Article  PubMed  PubMed Central  Google Scholar 

  25. Hoover M, Rotermann M, Sanmartin C et al (2013) Validation of an index to estimate the prevalence of frailty among community-dwelling seniors. Health Rep 24:10–17

    PubMed  Google Scholar 

  26. Blodgett J, Theou O, Kirkland S et al (2015) Frailty in NHANES: comparing the frailty index and phenotype. Arch Gerontol Geriatr 60:464–470

    Article  PubMed  Google Scholar 

  27. Dent E, Chapman I, Howell S et al (2014) Frailty and functional decline indices predict poor outcomes in hospitalised older people. Age Ageing 43:477–484

    Article  PubMed  Google Scholar 

  28. Ravindrarajah R, Hazra NC, Hamada S et al (2017) Systolic blood pressure trajectory, frailty, and all-cause mortality> 80 years of age: cohort study using electronic health records. Circulation 135:2357–2368

    Article  PubMed  PubMed Central  Google Scholar 

  29. Bailie R, Bailie J, Chakraborty A et al (2015) Consistency of denominator data in electronic health records in Australian primary healthcare services: enhancing data quality. Aust J Prim Health 21:450–459

    Article  PubMed  Google Scholar 

  30. Birkhead GS, Klompas M, Shah NR (2015) Uses of electronic health records for public health surveillance to advance public health. Ann Rev Public Health 36:345–359

    Article  Google Scholar 

  31. Nardi EA, Lentz LK, Winckworth-Prejsnar K et al (2016) Emerging issues and opportunities in health information technology. J Natl Compr Cancer Netw JNCCN 14:1226–1233

    Article  Google Scholar 

  32. van der Bij S, Khan N, Ten Veen P et al (2017) Improving the quality of EHR recording in primary care: a data quality feedback tool. J Am Med Inform Assoc JAMIA 24:81–87

    Article  PubMed  Google Scholar 

  33. Anzaldi LJ, Davison A, Boyd CM et al (2017) Comparing clinician descriptions of frailty and geriatric syndromes using electronic health records: a retrospective cohort study. BMC Geriatr 17:248

    Article  PubMed  PubMed Central  Google Scholar 

  34. Arokiasamy P, Kowal P, Capistrant BD et al (2017) Chronic noncommunicable diseases in 6 low- and middle-income countries: findings from wave 1 of the World Health Organization’s study on global ageing and adult health (SAGE). Am J Epidemiol 185:414–428

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

ED received support from an Australian National Health and Medical Research Council (NHMRC) Grant: #1112672. This research is supported by an NHMRC Centre of Research Excellence in Transdisciplinary Frailty Research to Achieve Healthy Ageing (Grant: #1102208). MA acknowledges fellowship support received from the Canadian Institutes of Health Research and the NHMRC in support of her postdoctoral research.

Author information

Authors and Affiliations

  1. Torrens University of Australia, 220 Victoria Square, Adelaide, SA, 5000, Australia

    Rachel C. Ambagtsheer, Justin Beilby & Elsa Dent

  2. National Health and Medical Research Council Centre of Research Excellence in Trans-Disciplinary Frailty Research to Achieve Healthy Ageing, Adelaide, Australia

    Rachel C. Ambagtsheer, Justin Beilby & Mandy M. Archibald

  3. University of Alberta, Edmonton, AB, Canada

    Julia Dabravolskaj & Marjan Abbasi

  4. Edmonton Oliver Primary Care Network, Edmonton, AB, Canada

    Julia Dabravolskaj & Marjan Abbasi

  5. College of Nursing and Health Sciences, Flinders University, Adelaide, Australia

    Mandy M. Archibald

  6. Baker Heart and Diabetes Institute, Melbourne, Australia

    Elsa Dent

Authors
  1. Rachel C. Ambagtsheer
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  2. Justin Beilby
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  3. Julia Dabravolskaj
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  4. Marjan Abbasi
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  5. Mandy M. Archibald
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  6. Elsa Dent
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Corresponding author

Correspondence to Rachel C. Ambagtsheer.

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Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Statement of human and animal rights

This study received ethics approval from the Torrens University HREC Committee (#H1/18) and was conducted in accordance with the Declaration of Helsinki.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Appendix

Appendix

See Table 3.

Table 3 Comparison of frailty status according to eFI and phenotype
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Ambagtsheer, R.C., Beilby, J., Dabravolskaj, J. et al. Application of an electronic Frailty Index in Australian primary care: data quality and feasibility assessment. Aging Clin Exp Res 31, 653–660 (2019). https://doi.org/10.1007/s40520-018-1023-9

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  • DOI: https://doi.org/10.1007/s40520-018-1023-9

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