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      Responses to hypothetical health scenarios overestimate healthcare utilization for common infectious syndromes: a cross-sectional survey, South Africa, 2012

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          Abstract

          Background

          Asking people how they would seek healthcare in a hypothetical situation can be an efficient way to estimate healthcare utilization, but it is unclear how intended healthcare use corresponds to actual healthcare use.

          Methods

          We performed a cross-sectional survey between August and September 2012 among households in Soweto and Klerksdorp, South Africa, to compare healthcare seeking behaviors intended for hypothetical common infectious syndromes (pneumonia, influenza-like illness [ILI], chronic respiratory illness, meningitis in persons of any age, and diarrhea in a child < 5 years old) with the self-reported healthcare use among patients with those syndromes.

          Results

          For most syndromes, the proportion of respondents who intended to seek healthcare at any facility or provider (99–100%) in a hypothetical scenario exceeded the proportion that did seek care (78–100%). More people intended to seek care for a child < 5 years old with diarrhea (186/188 [99%]) than actually did seek care (32/41 [78%], P < 0.01). Although most people faced with hypothetical scenarios intended to seek care with licensed medical providers such as hospitals and clinics (97–100%), patients who were ill reported lower use of licensed medical providers (55–95%).

          Conclusions

          People overestimated their intended healthcare utilization, especially with licensed medical providers, compared with reported healthcare utilization among patients with these illnesses. Studies that measure intended healthcare utilization should consider that actual use of healthcare facilities may be lower than intended use.

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          Most cited references29

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          Methods of coping with social desirability bias: A review

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            Determinants of health care seeking for childhood illnesses in Nairobi slums.

            The practice of appropriate health seeking has a great potential to reduce the occurrence of severe and life-threatening child illnesses. We assessed the influence of socio-demographic, economic and disease-related factors in health care seeking for child illnesses among slum dwellers of Nairobi, Kenya. A survey round of the Nairobi Urban Demographic Surveillance System (NUDSS) generated information on 2-week child morbidity, illness symptoms, perceived illness severity and use of modern health services. During this round of data collection, interviewers visited a total of 15,174 households, where 3015 children younger than 5 years lived. Of the 999 (33.1%) children who were reported to have been sick, medical care of some sort was sought for 604 (60.5%). Lack of finances (49.6%) and a perception that the illness was not serious (28.1%) were the main reasons given for failure to seek health care outside the home. Health care seeking was most common for sick children in the youngest age group (0-11 months). Caretakers sought medical care more frequently for diarrhoea symptoms than for coughing and even more so when the diarrhoea was associated with fever. Perception of illness severity was strongly associated with health care seeking. Household income was significantly associated with health care seeking up to certain threshold levels, above which its effects stabilized. Improving caretaker skills to recognize danger signs in child illnesses may enhance health-seeking behaviour. Integrated Management of Child Illnesses (IMCI) programmes must be accessible free of charge to the urban poor in order to increase health care seeking and bring about improvements in child survival.
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              Evaluation of the optimal recall period for disease symptoms in home-based morbidity surveillance in rural and urban Kenya

              Background In African settings with poor access to health care, surveillance and surveys of disease burden are often done through home visits. The optimal recall period to capture data on symptoms and health utilization is unknown. Methods We collected illness data among 53 000 people during fortnightly home visits in rural and urban Kenya. Dates of cough, fever and diarrhoea in the past 2 weeks and health-seeking behaviour were recorded. Incidence rates were modelled using Poisson regression for data collected from 1 July 2006 to 30 June 2007. Results Incidence rates were higher in days 0–6 before the home visit than in days 7–13 before the home visit for all three symptoms, for the rural and urban sites, for children and adults, for self- and proxy-reported symptoms and for severe and non-severe illness in children. Recall decay was steeper in the rural than the urban sites, and for proxy- than self-reported symptoms. The daily prevalence of symptoms fell 3 days before the home visit for children and >4 days for persons ≥5 years of age. Recall of previously documented clinic visits, and prescriptions of antimalarials and antibiotics also declined by ∼7, 15 and 23% per week, respectively, in children aged <5 years, and 6, 20 and 16%, respectively, in older persons (P < 0.0001 for each decline). Conclusions A 2-week recall period underestimates true disease rates and health-care utilization. Shorter recall periods of 3 days in children and 4 days in adults would likely yield more accurate data.
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                Author and article information

                Contributors
                kwong@cdc.gov
                alcohen1@cdc.gov
                martinson@phru.co.za
                Shane.Norris@wits.ac.za
                stefanot@nicd.ac.za
                clairevm@nicd.ac.za
                sibongilew@nicd.ac.za
                shabirm@nicd.ac.za
                mmcmorrow@cdc.gov
                cherylc@nicd.ac.za
                Journal
                BMC Infect Dis
                BMC Infect. Dis
                BMC Infectious Diseases
                BioMed Central (London )
                1471-2334
                25 July 2018
                25 July 2018
                2018
                : 18
                : 344
                Affiliations
                [1 ]ISNI 0000 0001 2163 0069, GRID grid.416738.f, Centers for Disease Control, ; 1600 Clifton Rd NE, MS C-09, Atlanta, GA 30329 USA
                [2 ]ISNI 0000 0001 1554 5300, GRID grid.417684.8, United States Public Health Service, ; Rockville, USA
                [3 ]ISNI 0000 0004 1937 1135, GRID grid.11951.3d, MRC Developmental Pathways for Health Research Unit, , University of Witwatersrand, ; Johannesburg, South Africa
                [4 ]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Johns Hopkins University, ; Baltimore, MD USA
                [5 ]ISNI 0000 0004 1937 1135, GRID grid.11951.3d, University of Witwatersrand, ; Johannesburg, South Africa
                [6 ]ISNI 0000 0004 0630 4574, GRID grid.416657.7, National Institute for Communicable Diseases, ; Johannesburg, South Africa
                Article
                3252
                10.1186/s12879-018-3252-0
                6060471
                30045687
                6429281e-c42d-4088-8adf-e021fe2b892e
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 15 February 2017
                : 11 July 2018
                Funding
                Funded by: Centers for Disease Control and Prevention (US)
                Award ID: 5U19/GH000622
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Infectious disease & Microbiology
                pneumonia,influenza,diarrhea,meningitis,south africa,healthcare utilization

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