Dr Foster global frailty score: an international retrospective observational study developing and validating a risk prediction model for hospitalised older persons from administrative data sets

Objectives This study aimed to examine the prevalence of frailty coding within the Dr Foster Global Comparators (GC) international database. We then aimed to develop and validate a risk prediction model, based on frailty syndromes, for key outcomes using the GC data set. Design A retrospective cohort analysis of data from patients over 75 years of age from the GC international administrative data. A risk prediction model was developed from the initial analysis based on seven frailty syndrome groups and their relationship to outcome metrics. A weighting was then created for each syndrome group and summated to create the Dr Foster Global Frailty Score. Performance of the score for predictive capacity was compared with an established prognostic comorbidity model (Elixhauser) and tested on another administrative database Hospital Episode Statistics (2011-2015), for external validation. Setting 34 hospitals from nine countries across Europe, Australia, the UK and USA. Results Of 6.7 million patient records in the GC database, 1.4 million (20%) were from patients aged 75 years or more. There was marked variation in coding of frailty syndromes between countries and hospitals. Frailty syndromes were coded in 2% to 24% of patient spells. Falls and fractures was the most common syndrome coded (24%). The Dr Foster Global Frailty Score was significantly associated with in-hospital mortality, 30-day non-elective readmission and long length of hospital stay. The score had significant predictive capacity beyond that of other known predictors of poor outcome in older persons, such as comorbidity and chronological age. The score’s predictive capacity was higher in the elective group compared with non-elective, and may reflect improved performance in lower acuity states. Conclusions Frailty syndromes can be coded in international secondary care administrative data sets. The Dr Foster Global Frailty Score significantly predicts key outcomes. This methodology may be feasibly utilised for case-mix adjustment for older persons internationally.

[1]  J. Bongaarts,et al.  United Nations Department of Economic and Social Affairs, Population Division World Family Planning 2020: Highlights, United Nations Publications, 2020. 46 p. , 2020 .

[2]  Kenneth Rockwood,et al.  Measuring Frailty in Medicare Data: Development and Validation of a Claims-Based Frailty Index , 2018, The journals of gerontology. Series A, Biological sciences and medical sciences.

[3]  A. Street,et al.  Development and validation of a Hospital Frailty Risk Score focusing on older people in acute care settings using electronic hospital records: an observational study , 2018, The Lancet.

[4]  Susan C. Hu,et al.  Frailty and Its Contributory Factors in Older Adults: A Comparison of Two Asian Regions (Hong Kong and Taiwan) , 2017, International journal of environmental research and public health.

[5]  H. Wunsch,et al.  A Scoping Review of Frailty and Acute Care in Middle-Aged and Older Individuals with Recommendations for Future Research , 2017, Canadian geriatrics journal : CGJ.

[6]  D. Bell,et al.  Finding consensus on frailty assessment in acute care through Delphi method , 2016, BMJ Open.

[7]  C. van Walraven,et al.  Association of Frailty and 1-Year Postoperative Mortality Following Major Elective Noncardiac Surgery: A Population-Based Cohort Study. , 2016, JAMA surgery.

[8]  John Young,et al.  Development and validation of an electronic frailty index using routine primary care electronic health record data , 2016, Age and ageing.

[9]  A. Bottle,et al.  Multi-Morbidity in Hospitalised Older Patients: Who Are the Complex Elderly? , 2015, PloS one.

[10]  D. Bell,et al.  Developing and validating a risk prediction model for acute care based on frailty syndromes , 2015, BMJ Open.

[11]  D. Bell,et al.  Quantifying the prevalence of frailty in English hospitals , 2015, BMJ Open.

[12]  H. Wunsch,et al.  Frailty Before Critical Illness and Mortality for Elderly Medicare Beneficiaries , 2015, Journal of the American Geriatrics Society.

[13]  M. Brookhart,et al.  Using claims data to predict dependency in activities of daily living as a proxy for frailty , 2015, Pharmacoepidemiology and drug safety.

[14]  A. Bottle,et al.  Effect of the readmission primary diagnosis and time interval in heart failure patients: analysis of English administrative data , 2014, European journal of heart failure.

[15]  Brian M. Gryzlak,et al.  Beyond Comorbidity: Expanding the Definition and Measurement of Complexity Among Older Adults Using Administrative Claims Data , 2014, Medical care.

[16]  A. Bottle,et al.  Global comparators project: international comparison of hospital outcomes using administrative data. , 2013, Health services research.

[17]  C. Cooper,et al.  Immune-endocrine biomarkers as predictors of frailty and mortality , 2016 .

[18]  M. Edelman,et al.  A novel approach to improve health status measurement in observational claims-based studies of cancer treatment and outcomes. , 2013, Journal of Geriatric Oncology.

[19]  S. Conroy,et al.  Quality care for older people with urgent and emergency care needs in UK emergency departments , 2012, Emergency Medicine Journal.

[20]  A. Bottle,et al.  Systematic Review of Comorbidity Indices for Administrative Data , 2012, Medical care.

[21]  C. Liao,et al.  How comorbidities and preoperative expenditures correlate with postoperative adverse outcomes. , 2012, The American journal of managed care.

[22]  J. Lemberger,et al.  Identifying frail older people using predictive modeling. , 2012, The American journal of managed care.

[23]  K. Rockwood,et al.  Frailty in primary care: a review of its conceptualization and implications for practice , 2012, BMC Medicine.

[24]  A. Bottle,et al.  Comorbidity scores for administrative data benefited from adaptation to local coding and diagnostic practices. , 2011, Journal of clinical epidemiology.

[25]  Sathya Karunananthan,et al.  The Identification of Frailty: A Systematic Literature Review , 2011, Journal of the American Geriatrics Society.

[26]  L. Fratiglioni,et al.  Aging with multimorbidity: A systematic review of the literature , 2011, Ageing Research Reviews.

[27]  C. Roy Anemia in frailty. , 2011, Clinics in geriatric medicine.

[28]  Q. Xue The frailty syndrome: definition and natural history. , 2011, Clinics in geriatric medicine.

[29]  M. Dubois,et al.  Assessing comorbidity in older adults using prescription claims data , 2010 .

[30]  Gary B. Smith,et al.  ViEWS--Towards a national early warning score for detecting adult inpatient deterioration. , 2010, Resuscitation.

[31]  M. Loeb,et al.  Aging, frailty and age-related diseases , 2010, Biogerontology.

[32]  I. Lang,et al.  Frailty, body mass index, and abdominal obesity in older people. , 2010, The journals of gerontology. Series A, Biological sciences and medical sciences.

[33]  S. Bandinelli,et al.  Frailty and the role of nutrition in older people. A review of the current literature. , 2010, Acta bio-medica : Atenei Parmensis.

[34]  Rural Affairs,et al.  Survey of public attitudes and behaviours towards the environment , 2009 .

[35]  E. Marcantonio,et al.  Risk Factors for Hospitalization Among Community-Dwelling Primary Care Older Patients: Development and Validation of a Predictive Model , 2008, Medical care.

[36]  J. Hirdes,et al.  Validation of Resource Utilization Groups Version III for Home Care (RUG-III/HC): Evidence From a Canadian Home Care Jurisdiction , 2008, Medical care.

[37]  R. Varadhan,et al.  Higher levels and blunted diurnal variation of cortisol in frail older women. , 2008, The journals of gerontology. Series A, Biological sciences and medical sciences.

[38]  G. Paolisso,et al.  Is there a relationship between insulin resistance and frailty syndrome? , 2008, Current pharmaceutical design.

[39]  L. Ferrucci,et al.  Interleukin-6 in aging and chronic disease: a magnificent pathway. , 2006, The journals of gerontology. Series A, Biological sciences and medical sciences.

[40]  S. Bandinelli,et al.  Frailty syndrome and skeletal muscle: results from the Invecchiare in Chianti study. , 2006, The American journal of clinical nutrition.

[41]  Stuart Parker,et al.  Follow up of people aged 65 and over with a history of emergency admissions: analysis of routine admission data , 2005, BMJ : British Medical Journal.

[42]  A. Rudd,et al.  Secondary prevention for stroke in the United Kingdom: results from the National Sentinel Audit of Stroke. , 2004, Age and ageing.

[43]  L. Ferrucci,et al.  Untangling the concepts of disability, frailty, and comorbidity: implications for improved targeting and care. , 2004, The journals of gerontology. Series A, Biological sciences and medical sciences.

[44]  M. Schroll,et al.  Muscle Strength After Resistance Training Is Inversely Correlated with Baseline Levels of Soluble Tumor Necrosis Factor Receptors in the Oldest Old , 2004, Journal of the American Geriatrics Society.

[45]  J. Lynn,et al.  Profiles of Older Medicare Decedents , 2002, Journal of the American Geriatrics Society.

[46]  Christianna S. Williams,et al.  Development and Validation of a Risk‐Adjustment Index for Older Patients: The High‐Risk Diagnoses for the Elderly Scale , 2002, Journal of the American Geriatrics Society.

[47]  B H Chang,et al.  Risk Adjustment for Measuring Health Outcomes: An Application in VA Long term Care , 2001, American journal of medical quality : the official journal of the American College of Medical Quality.

[48]  A. Kramer,et al.  Application of functional independence measure-function related groups and resource utilization groups-version III systems across post acute settings. , 1998, Medical care.

[49]  D. Hosmer,et al.  A comparison of goodness-of-fit tests for the logistic regression model. , 1997, Statistics in medicine.

[50]  G. Carpenter,et al.  Casemix for inpatient care of elderly people: rehabilitation and post-acute care. Casemix for the Elderly Inpatient Working Group. , 1997, Age and ageing.

[51]  G. Monette,et al.  Generalized Collinearity Diagnostics , 1992 .

[52]  E H Wagner,et al.  A chronic disease score from automated pharmacy data. , 1992, Journal of clinical epidemiology.

[53]  D. O’Neill,et al.  Acute hospital care: how much activity is attributable to caring for patients with dementia? , 2016, QJM : monthly journal of the Association of Physicians.

[54]  G. Pope,et al.  CMS Frailty Adjustment Model , 2004, Health care financing review.