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BMC Public Health
Published in: BMC Public Health 1/2019

Open Access 01-12-2019 | Study protocol

MOBIlity assessment with modern TEChnology in older patients’ real-life by the General Practitioner: the MOBITEC-GP study protocol

Authors: Mareike Münch, Robert Weibel, Alexandros Sofios, Haosheng Huang, Denis Infanger, Erja Portegijs, Eleftheria Giannouli, Jonas Mundwiler, Lindsey Conrow, Taina Rantanen, Arno Schmidt-Trucksäss, Andreas Zeller, Timo Hinrichs

Published in: BMC Public Health | Issue 1/2019

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Abstract

Background

Mobility limitations in older adults are associated with poor clinical outcomes including higher mortality and disability rates. A decline in mobility (including physical function and life-space) is detectable and should be discovered as early as possible, as it can still be stabilized or even reversed in early stages by targeted interventions. General practitioners (GPs) would be in the ideal position to monitor the mobility of their older patients. However, easy-to-use and valid instruments for GPs to conduct mobility assessment in the real-life practice setting are missing. Modern technologies such as the global positioning system (GPS) and inertial measurement units (IMUs) - nowadays embedded in every smartphone - could facilitate monitoring of different aspects of mobility in the GP's practice.

Methods

This project’s aim is to provide GPs with a novel smartphone application that allows them to quantify their older patients’ mobility. The project consists of three parts: development of the GPS- and IMU-based application, evaluation of its validity and reliability (Study 1), and evaluation of its applicability and acceptance (Study 2).
In Study 1, participants (target N = 72, aged 65+, ≥2 chronic diseases) will perform a battery of walking tests (varying distances; varying levels of standardization). Besides videotaping and timing (gold standard), a high-end GPS device, a medium-accuracy GPS/IMU logger and three different smartphone models will be used to determine mobility parameters such as gait speed. Furthermore, participants will wear the medium-accuracy GPS/IMU logger and a smartphone for a week to determine their life-space mobility. Participants will be re-assessed after 1 week. In Study 2, participants (target N = 60, aged 65+, ≥2 chronic diseases) will be instructed on how to use the application by themselves. Participants will perform mobility assessments independently at their own homes. Aggregated test results will also be presented to GPs. Acceptance of the application will be assessed among patients and GPs. The application will then be finalized and publicly released.

Discussion

If successful, the MOBITEC-GP application will offer health care providers the opportunity to follow their patients’ mobility over time and to recognize impending needs (e.g. for targeted exercise) within pre-clinical stages of decline.
Literature
1.
Marengoni A, Angleman S, Melis R, Mangialasche F, Karp A, Garmen A, Meinow B, Fratiglioni L. Aging with multimorbidity: a systematic review of the literature. Ageing Res Rev. 2011;10(4):430–9.PubMedCrossRef
2.
van den Akker M, Buntinx F, Metsemakers JFM, Roos S, Knottnerus JA. Multimorbidity in general practice: prevalence, incidence, and determinants of co-occurring chronic and recurrent diseases. J Clin Epidemiol. 1998;51(5):367–75.PubMedCrossRef
3.
4.
Weiss CO, Boyd CM, Yu QL. Patterns of prevalent major chronic disease among older adults in the United States. JAMA. 2007;298(10):1160–2.PubMedCrossRef
5.
Kostev K, Jacob L. Multimorbidity and polypharmacy among elderly people followed in general practices in Germany. Eur J Intern Med. 2018;55:66–8.PubMedCrossRef
6.
Fortin M, Bravo G, Hudon C, Lapointe L, Dubois MF, Almirall J. Psychological distress and multimorbidity in primary care. Ann Fam Med. 2006;4(5):417–22.PubMedPubMedCentralCrossRef
7.
Zhen CL, Sangl J, Bierman AS, Miller MR, Friedman B, Wickizer SW, Meyer GS. Potentially inappropriate medication use in the community-dwelling elderly - findings from the 1996 medical expenditure panel survey. JAMA. 2001;286(22):2823–9.CrossRef
8.
Gijsen R, Hoeymans N, Schellevis FG, Ruwaard D, Satariano WA, van den Bos GAM. Causes and consequences of comorbidity: a review. J Clin Epidemiol. 2001;54(7):661–74.PubMedCrossRef
9.
Pompei P, Charlson ME, Douglas RG. Clinical assessments as predictors of one year survival after hospitalization - implications for prognostic stratification. J Clin Epidemiol. 1988;41(3):275–84.PubMedCrossRef
10.
Rochon PA, Katz JN, Morrow LA, McGlincheyBerroth R, Ahlquist MM, Sarkarati M, Minaker KL. Comorbid illness is associated with survival and length of hospital stay in patients with chronic disability - a prospective comparison of three comorbidity indices. Med Care. 1996;34(11):1093–101.PubMedCrossRef
11.
Flocke SA, Frank SH, Wenger DA. Addressing multiple problems in the family practice office visit. J Fam Pract. 2001;50(3):211–6.PubMed
12.
Epping-Jordan JE, Pruitt SD, Bengoa R, Wagner EH. Improving the quality of health care for chronic conditions. Qual Saf Health Care. 2004;13(4):299–305.PubMedPubMedCentralCrossRef
13.
Bodenheimer T, Wagner EH, Grumbach K. Improving primary care for patients with chronic illness. JAMA. 2002;288(14):1775–9.PubMedCrossRef
14.
Wagner EH, Bennett SM, Austin BT, Greene SM, Schaefer JK, Vonkorff M. Finding common ground: patient-centeredness and evidence-based chronic illness care. J Altern Complement Med. 2005;11(Suppl 1):S7–15.PubMedCrossRef
15.
Tinetti ME, Bogardus ST Jr, Agostini JV. Potential pitfalls of disease-specific guidelines for patients with multiple conditions. N Engl J Med. 2004;351(27):2870–4.PubMedCrossRef
16.
17.
Boyd CM, Darer J, Boult C, Fried LP, Boult L, Wu AW. Clinical practice guidelines and quality of care for older patients with multiple comorbid diseases: implications for pay for performance. JAMA. 2005;294(6):716–24.PubMedCrossRef
18.
Fried TR, Tinetti ME, Iannone L, O'Leary JR, Towle V, Van Ness PH. Health outcome prioritization as a tool for decision making among older persons with multiple chronic conditions. Arch Intern Med. 2011;171(20):1854–6.PubMedPubMedCentralCrossRef
19.
St John PD, Tyas SL, Menec V, Tate R. Multimorbidity, disability, and mortality in community-dwelling older adults. Can Fam Physician. 2014;60(5):e272–80.PubMedPubMedCentral
20.
21.
Satariano WA, Guralnik JM, Jackson RJ, Marottoli RA, Phelan EA, Prohaska TR. Mobility and aging: new directions for public health action. Am J Public Health. 2012;102(8):1508–15.PubMedPubMedCentralCrossRef
22.
World Health Organisation. International classification of functioning, disability and health: ICF. Geneva: WHO; 2001.
23.
Webber SC, Porter MM, Menec VH. Mobility in older adults: a comprehensive framework. Gerontologist. 2010;50(4):443–50.PubMedCrossRef
24.
Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, Scherr PA, Wallace RB. A short physical performance battery assessing lower-extremity function - association with self-reported disability and prediction of mortality and nursing-home admission. J Gerontol. 1994;49(2):M85–94.CrossRefPubMed
25.
Baker PS, Bodner EV, Allman RM. Measuring life-space mobility in community-dwelling older adults. J Am Geriatr Soc. 2003;51(11):1610–4.CrossRefPubMed
26.
Podsiadlo D, Richardson S. The timed "up & go" - a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc. 1991;39(2):142–8.CrossRefPubMed
27.
Moyer VA, Force USPST. Prevention of falls in community-dwelling older adults: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med. 2012;157(3):197–204.PubMedCrossRef
28.
Montero-Odasso M, Schapira M, Soriano ER, Varela M, Kaplan R, Camera LA, Mayorga LM. Gait velocity as a single predictor of adverse events in healthy seniors aged 75 years and older. J Gerontol A Biol Sci Med Sci. 2005;60(10):1304–9.PubMedCrossRef
29.
Lawrence RH, Jette AM. Disentangling the disablement process. J Gerontol B Psychol Sci Soc Sci. 1996;51(4):S173–82.PubMedCrossRef
30.
Guralnik JM, Ferrucci L, Simonsick EM, Salive ME, Wallace RB. Lower-extremity function in persons over the age of 70 years as a predictor of subsequent disability. N Engl J Med. 1995;332(9):556–61.PubMedCrossRef
31.
Rosano C, Newman AB, Katz R, Hirsch CH, Kuller LH. Association between lower digit symbol substitution test score and slower gait and greater risk of mortality and of developing incident disability in well-functioning older adults. J Am Geriatr Soc. 2008;56(9):1618–25.PubMedPubMedCentralCrossRef
32.
von Bonsdorff M, Rantanen T, Laukkanen P, Suutama T, Heikkinen E. Mobility limitations and cognitive deficits as predictors of institutionalization among community-dwelling older people. Gerontology. 2006;52(6):359–65.CrossRef
33.
Reuben DB, Seeman TE, Keeler E, Hayes RP, Bowman L, Sewall A, Hirsch SH, Wallace RB, Guralnik JM. The effect of self-reported and performance-based functional impairment on future hospital costs of community-dwelling older persons. Gerontologist. 2004;44(3):401–7.PubMedCrossRef
34.
Cesari M, Kritchevsky SB, Penninx BW, Nicklas BJ, Simonsick EM, Newman AB, Tylavsky FA, Brach JS, Satterfield S, Bauer DC, et al. Prognostic value of usual gait speed in well-functioning older people--results from the health, aging and body composition study. J Am Geriatr Soc. 2005;53(10):1675–80.PubMedCrossRef
35.
Bernard SL, Kincade JE, Konrad TR, Arcury TA, Rabiner DJ, Woomert A, DeFriese GH, Ory MG. Predicting mortality from community surveys of older adults: the importance of self-rated functional ability. J Gerontol B Psychol Sci Soc Sci. 1997;52(3):S155–63.PubMedCrossRef
36.
Studenski S, Perera S, Patel K, Rosano C, Faulkner K, Inzitari M, Brach J, Chandler J, Cawthon P, Connor EB, et al. Gait speed and survival in older adults. JAMA. 2011;305(1):50–8.PubMedPubMedCentralCrossRef
37.
Peel C, Baker PS, Roth DL, Brown CJ, Bodner EV, Allman RM. Assessing mobility in older adults: the UAB study of aging life-space assessment. Phys Ther. 2005;85(10):1008–19.PubMed
38.
Vink D, Aartsen MJ, Schoevers RA. Risk factors for anxiety and depression in the elderly: a review. J Affect Disord. 2008;106(1–2):29–44.PubMedCrossRef
39.
Netuveli G, Wiggins RD, Hildon Z, Montgomery SM, Blane D. Quality of life at older ages: evidence from the English longitudinal study of aging (wave 1). J Epidemiol Community Health. 2006;60(4):357–63.PubMedPubMedCentralCrossRef
40.
Vasunilashorn S, Coppin AK, Patel KV, Lauretani F, Ferrucci L, Bandinelli S, Guralnik JM. Use of the short physical performance battery score to predict loss of ability to walk 400 meters: analysis from the InCHIANTI study. J Gerontol A Biol Sci Med Sci. 2009;64(2):223–9.PubMedCrossRef
41.
Panel on Prevention of Falls in Older Persons AGS, British Geriatrics S. Summary of the Updated American Geriatrics Society/British Geriatrics Society clinical practice guideline for prevention of falls in older persons. J Am Geriatr Soc. 2011;59(1):148–57.CrossRef
42.
Shumway-Cook A, Brauer S, Woollacott M. Predicting the probability for falls in community-dwelling older adults using the timed up & go test. Phys Ther. 2000;80(9):896–903.PubMed
43.
Tung JY, Rose RV, Gammada E, Lam I, Roy EA, Black SE, Poupart P. Measuring life space in older adults with mild-to-moderate Alzheimer's disease using mobile phone GPS. Gerontology. 2014;60(2):154–62.PubMedCrossRef
44.
Portegijs E, Rantakokko M, Viljanen A, Sipilä S, Rantanen T. Identification of older people at risk of ADL disability using the life-space assessment: a longitudinal cohort study. J Am Med Dir Assoc. 2016;17(5):410–4.PubMedCrossRef
45.
Sheppard KD, Sawyer P, Ritchie CS, Allman RM, Brown CJ. Life-space mobility predicts nursing home admission over 6 years. J Aging Health. 2013;25(6):907–20.PubMedPubMedCentralCrossRef
46.
Boyle PA, Buchman AS, Barnes LL, James BD, Bennett DA. Association between life space and risk of mortality in advanced age. J Am Geriatr Soc. 2010;58(10):1925–30.PubMedPubMedCentralCrossRef
47.
Xue QL, Fried LP, Glass TA, Laffan A, Chaves PH. Life-space constriction, development of frailty, and the competing risk of mortality: the Women's health and aging study I. Am J Epidemiol. 2008;167(2):240–8.PubMedCrossRef
48.
Lo AX, Brown CJ, Sawyer P, Kennedy RE, Allman RM. Life-space mobility declines associated with incident falls and fractures. J Am Geriatr Soc. 2014;62(5):919–23.PubMedPubMedCentralCrossRef
49.
Ullrich P, Werner C, Eckert T, Bongartz M, Kiss R, Feisst M, Delbaere K, Bauer JM, Hauer K. Cut-off for the life-space assessment in persons with cognitive impairment. Aging Clin Exp Res. 2019;31(9):1331–5.PubMedCrossRef
50.
Clauser SB, Bierman AS. Significance of functional status data for payment and quality. Health Care Financ Rev. 2003;24(3):1–12.PubMedPubMedCentral
51.
Pahor M, Guralnik JM, Ambrosius WT, Blair S, Bonds DE, Church TS, Espeland MA, Fielding RA, Gill TM, Groessl EJ, et al. Effect of structured physical activity on prevention of major mobility disability in older adults: the LIFE study randomized clinical trial. JAMA. 2014;311(23):2387–96.PubMedPubMedCentralCrossRef
52.
Botoseneanu A, Allore HG, Gahbauer EA, Gill TM. Long-term trajectories of lower extremity function in older adults: estimating gender differences while accounting for potential mortality bias. J Gerontol A Biol Sci Med Sci. 2013;68(7):861–8.PubMedCrossRef
53.
54.
Studenski S, Perera S, Wallace D, Chandler JM, Duncan PW, Rooney E, Fox M, Guralnik JM. Physical performance measures in the clinical setting. J Am Geriatr Soc. 2003;51(3):314–22.PubMedCrossRef
55.
Calkins DR, Rubenstein LV, Cleary PD, Davies AR, Jette AM, Fink A, Kosecoff J, Young RT, Brook RH, Delbanco TL. Failure of physicians to recognize functional disability in ambulatory patients. Ann Intern Med. 1991;114(6):451–4.PubMedCrossRef
56.
Calkins DR, Rubenstein LV, Cleary PD, Davies AR, Jette AM, Fink A, Kosecoff J, Young RT, Brook RH, Delbanco TL. Functional disability screening of ambulatory patients: a randomized controlled trial in a hospital-based group practice. J Gen Intern Med. 1994;9(10):590–2.PubMedCrossRef
57.
Tinetti ME, Brach JS. Translating the fall prevention recommendations into a covered service: can it be done, and who should do it? Ann Intern Med. 2012;157(3):213–4.PubMedCrossRef
58.
Hinrichs T, Brach M. The general practitioner’s role in promoting physical activity to older adults: a review based on program theory. Curr Aging Sci. 2011;5(1):41–50.CrossRef
59.
Saß AC, Wurm S, Ziese T. Inanspruchnahmeverhalten. In: Böhm K, Tesch-Römer C, Ziese T, editors. Beiträge zur Gesundheitsberichterstattung des Bundes: Gesundheit und Krankheit im Alter. Berlin: Robert Koch-Institut; 2009. p. 134–59.
60.
Brach M, Moschny A, Bücker B, Klaassen-Mielke R, Trampisch M, Wilm S, Platen P, Hinrichs T. Recruiting hard-to-reach subjects for exercise interventions: a multi-Centre and multi-stage approach targeting general practitioners and their community-dwelling and mobility-limited patients. Int J Environ Res Public Health. 2013;10(12):6611–29.PubMedPubMedCentralCrossRef
61.
Falvo D, Woehlke P, Deichmann J. Relationship of physician behaviour to patient compliance. Patient Couns Health Educ. 1980;2(4):185–8.PubMedCrossRef
62.
Harada K, Lee S, Lee S, Bae S, Harada K, Suzuki T, Shimada H. Objectively-measured outdoor time and physical and psychological function among older adults. Geriatr Gerontol Int. 2017;17(10):1455-62.
63.
Hirsch JA, Winters M, Ashe MC, Clarke P, McKay H. Destinations that older adults experience within their GPS activity spaces relation to objectively measured physical activity. Environ Behav. 2016;48(1):55–77.PubMedPubMedCentralCrossRef
64.
65.
Pesyna KM, Robert WH, Humphreys WH. Accuracy in the palm of your hand. GPS World. 2015;26(2):16–31.
66.
Elmezayen A, El-Rabbany A. Precise point positioning using world's first dual-frequency GPS/GALILEO smartphone. Sensors (Basel). 2019;19(11):2593.
67.
Scott MT, Scott TJ, Kelly VG. The validity and reliability of global positioning systems in team sport: a brief review. J Strength Cond Res. 2016;30(5):1470-90.
68.
Rampinini E, Alberti G, Fiorenza M, Riggio M, Sassi R, Borges TO, Coutts AJ. Accuracy of GPS devices for measuring high-intensity running in field-based team sports. Int J Sports Med. 2015;36(1):49–53.PubMed
69.
Hirsch JA, Winters M, Clarke P, McKay H. Generating GPS activity spaces that shed light upon the mobility habits of older adults: a descriptive analysis. Int J Health Geogr. 2014;13:51.PubMedPubMedCentralCrossRef
70.
Wanner M, Gotschi T, Martin-Diener E, Kahlmeier S, Martin BW. Active transport, physical activity, and body weight in adults: a systematic review. Am J Prev Med. 2012;42(5):493–502.PubMedCrossRef
71.
Gernigon M, Le Faucheur A, Noury-Desvaux B, Mahe G, Abraham P, Post GPSSCG. Applicability of global positioning system for the assessment of walking ability in patients with arterial claudication. J Vasc Surg. 2014;60(4):973–81 e971.PubMedCrossRef
72.
Gernigon M, Fouasson-Chailloux A, Colas-Ribas C, Noury-Desvaux B, Le Faucheur A, Abraham P. Test-retest reliability of GPS derived measurements in patients with claudication. Eur J Vasc Endovasc Surg. 2015;50(5):623–9.PubMedCrossRef
73.
Bertschi M, Celka P, Delgado-Gonzalo R, Lemay M, Calvo EM, Grossenbacher O, Renevey P. Accurate walking and running speed estimation using wrist inertial data. In: Annual IEEE International Conference on Engineering in Medicine and Biology Society (EMBC). 3rd ed; 2015. p. 8083–6.
74.
Wilson AM, Lowe JC, Roskilly K, Hudson PE, Golabek KA, McNutt JW. Locomotion dynamics of hunting in wild cheetahs. Nature. 2013;498(7453):185–9.PubMedCrossRef
75.
Sangha O, Stucki G, Liang MH, Fossel AH, Katz JN. The self-administered comorbidity questionnaire: a new method to assess comorbidity for clinical and health services research. Arthritis Rheum. 2003;49(2):156–63.PubMedCrossRef
76.
Streibelt M, Schmidt C, Brünger M, Spyra K. Komorbidität im Patientenurteil – geht das? Validität eines Instruments zur Selbsteinschätzung der Komorbidität (SCQ-D). Orthopade. 2012;41:303–10.PubMedCrossRef
77.
Fillekes MP, Giannouli E, Kim EK, Zijlstra W, Weibel R. Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research. Int J Health Geogr. 2019;18(1):17.PubMedPubMedCentralCrossRef
78.
Bohannon RW, Tudini F. Unipedal balance test for older adults: a systematic review and meta-analysis of studies providing normative data. Physiotherapy. 2018;104(4):376–82.PubMedCrossRef
79.
Trampisch US, Franke J, Jedamzik N, Hinrichs T, Platen P. Optimal Jamar dynamometer handle position to assess maximal isometric hand grip strength in epidemiological studies. J Hand Surg [Am]. 2012;37(11):2368–73.CrossRef
80.
Lamb SE, Jorstad-Stein EC, Hauer K, Becker C. Development of a common outcome data set for fall injury prevention trials: the prevention of falls network Europe consensus. J Am Geriatr Soc. 2005;53(9):1618–22.PubMedCrossRef
81.
Lamprecht M, Fischer A, Stamm H. Sport Schweiz 2014 - Sportaktivität und Sportinteresse der Schweizer Bevölkerung. Magglingen: Bundesamt für Sport BASPO; 2014.
82.
83.
Newell AM, VanSwearingen JM, Hile E, Brach JS. The modified gait efficacy scale: establishing the psychometric properties in older adults. Phys Ther. 2012;92(2):318–28.PubMedCrossRef
84.
Ustun TB, Chatterji S, Kostanjsek N, Rehm J, Kennedy C, Epping-Jordan J, Saxena S, von Korff M, Pull C, Project WNJ. Developing the World Health Organization disability assessment schedule 2.0. Bull World Health Organ. 2010;88(11):815–23.PubMedPubMedCentralCrossRef
85.
McGraw KO, Wong SP. Forming inferences about some intraclass correlations coefficients. Psychol Methods. 1996;1(1):30–46.CrossRef
86.
Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1(8476):307–10.CrossRefPubMed
87.
Costa-Santos C, Antunes L, Souto A, Bernardes J. Assessment of disagreement: a new information-based approach. Ann Epidemiol. 2010;20(7):555–61.PubMedCrossRef
88.
Kirkwood BR, Sterne JAC. Essential medical statistics. 2nd ed. Malden: Blackwell Science Ltd.; 2003.
89.
Bonett DG. Sample size requirements for estimating intraclass correlations with desired precision. Stat Med. 2002;21(9):1331–5.PubMedCrossRef
90.
Piegorsch WW. Sample sizes for improved binomial confidence intervals. Comput Stat Data Anal. 2004;46(2):309–16.CrossRef
91.
92.
93.
Abelson JS, Symer M, Peters A, Charlson M, Yeo H. Mobile health apps and recovery after surgery: what are patients willing to do? Am J Surg. 2017;214(4):616–22.PubMedCrossRef
Metadata
Title
MOBIlity assessment with modern TEChnology in older patients’ real-life by the General Practitioner: the MOBITEC-GP study protocol
Authors
Mareike Münch
Robert Weibel
Alexandros Sofios
Haosheng Huang
Denis Infanger
Erja Portegijs
Eleftheria Giannouli
Jonas Mundwiler
Lindsey Conrow
Taina Rantanen
Arno Schmidt-Trucksäss
Andreas Zeller
Timo Hinrichs
Publication date
01-12-2019
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2019
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-019-8069-2

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