Abstract

Background Healthcare costs and shortages of healthcare professionals are challenges for healthcare systems. Optimal resource allocation is needed, notably in the management of minor ailments. Community pharmacy services (e.g. minor ailment schemes) are often underused by the population. This study aims to explore the decision-making process when people are managing minor ailments: What criteria influence their choices among the management options? What is their level of information and willingness to use and pay for pharmacy services?

Methods In this cross-sectional online survey, participants were invited to complete a self-administered questionnaire (convenience sampling) from 07.11.2023 to 08.12.2023. The questionnaire explored general decision-making process in minor ailment management through three clinical scenarios, factors influencing whether to choose pharmacy services to manage minor ailments, as well as public knowledge about three pharmacy services in Switzerland and their willingness to use and pay for them.

Results The proportion of valid questionnaires was 99.8% (508/514). Perceived severity of symptoms and time to deal with symptoms were the most important criteria in making the management decision. The more serious the symptoms were perceived, the less the pharmacy and self-medication were privileged. Respondent's decision about whether to go to the pharmacy when dealing with minor ailments depended mainly on the perceived staff's skills and direct access to medicines. Pharmacy services were little known by the public. Respondents were more willing to use autonomous prescribing than other services, with low willingness to pay out of their pocket.

Conclusions This study shows that respondents are willing to use pharmacy services to manage minor ailments but are unaware of their existence and have low willingness to pay. Communication and uniformization of pharmacy services are needed, as well as the identification of right incentives to achieve the political goal of adequate orientation in the healthcare system when managing minor ailments.

Geographic coverage

French speaking part of Switzerland

Analysis unit

Individuals

Universe

People going to pharmacies, to ED or to GP or people having access to internet (QR code)

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size: 508 respondents. Selection process: As many answers as possible Stratification: none Stage of sample selection : explorative without sample selection Level of representation: not representative of the swiss population

Sampling deviation

-

Mode of data collection

Internet [int]

Research instrument

The questionnaire was created following the recommendations in the Unisanté document “D1808 Creating a questionnaire”. An initial review of the questionnaire was carried out by the project supervisor. Following modifications, the questionnaire was sent to the Unisanté pharmacy research group for an initial correction phase. Suggestions from 5 members of the research group were returned and taken into account. The questionnaire was then sent to two people outside the research group for an initial pilot test to assess comprehension and completion time. The final version of the questionnaire was submitted to the Head of Pharmacy, as well as to two people outside Unisanté for a final pilot test. It was estimated that the final version of the questionnaire would take 10 to 15 minutes to complete.

Cleaning operations

The dataset has been anonymized in June 2025. Greographical information were removed from comments and free answers. Some variables have been removed, as they might contained personal information : autre_a, autre_b,autre_mod_ass_alt,commentaires_formulaire.

Response rate

There is no tracability of the number of people that scanned the QR code and didn't finish the questionnaire or didn't start it

Sampling error estimates

-

Data appraisal

The sample population responding to the questionnaire was recruited by convenience and was not representative of the Swiss population. The sample contained more women (70% vs. 50%) (1) and was better educated (59% with a higher education qualification vs. 30%) (2). What's more, in Romandie, the canton of Vaud was over-represented (81% vs. 36%) (1), as were people with standard AOS models (40% vs. 22%) (3). People with alternative “telemedicine or pharmacy” models (7% vs. 29.4% for 19-26 year-olds and 28% for >26 year-olds) (3), as well as extreme deductibles (300.- : 37% vs. 46% ; 2500. : 36% vs. 41%) (3) were under-represented. There was also a possible over-representation of young people (4).

1. OFS, Office fédéral de la statistique [Internet]. 2023 [cité 18 déc 2023]. Structure de la population résidante permanente selon le canton, de 1999 à 2022 - 1999-2022 | Tableau. Disponible sur: https://www.bfs.admin.ch/asset/fr/26565149
2. OFS, Office fédéral de la statistique [Internet]. 2023 [cité 18 déc 2023]. Niveau de formation de la population – Données de l’indicateur - 2000-2022 | Tableau. Disponible sur: https://www.bfs.admin.ch /asset/fr/24485173
3. Grize S. Statistique de l’assurance-maladie obligatoire Edition 2021. Berne: OFSP, Office fédéral de la santé publique; 2023. Report No.: 6.
4. OFS, Office fédéral de la statistique [Internet]. [cité 26 déc 2023]. Age. Disponible sur: https://www.bfs.admin.ch/bfs/fr/home/statistiken/bevoelkerung/stand-entwicklung/alter.html

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A spatial representation of Tax Parcels. Key attributes include KeyPIN. The KeyPIN is the unique parcel identification number used to link the tax parcel to the parcel attributes which are stored and maintained in Oakland County land records.

There is no definite accuracy related to parcel boundaries. The information shown on these maps is for representation purposes only and is not intended to be a legally recorded map or survey. The information was compiled from a number of sources including recorded deeds, plats, tax maps surveys and other public records and data. Users of this data should consult the information sources listed above for verification of the information.

Abstract

Despite repeated efforts both on the supply side (improving facility equipment and supplies, and financial incentives to providers) and on the demand side (communication campaign including mass-media outreach), screening rates for diabetes and hypertension are still lagging in the Armenian population. Hypertension and diabetes are among the top drivers of preventable death and disability due to non-communicable diseases in Armenia. The focus of this evaluation will be on increasing screening rates for diabetes and hypertension for males and females ages 35-68. Current screening rates are: diabetes mellitus, females 48.1%, males 30.9%; hypertension, females 75.4%; males 48.3%. We will evaluate different types of demand-side incentives to increase the take-up of the screenings. We will compare regular incentives for patients to come for screenings, including personal invitations, personal invitations mentioning that peers have tested, a labeled but unconditional cash transfer (in the form of “cash like” pharmacy voucher) and a conditional cash transfer, also in the form of a pharmacy voucher.

Geographic coverage

4 Marzes: Ararat, Armavir, Kotayq, Lori

Analysis unit

Individual interview conducted at the household level

Universe

Males and Females aged 35-68 who have not been screened for diabetes and hypertension in the last 12 months in the 4 above mentioned regions of Armenia.

Kind of data

Sample survey data [ssd]

Sampling procedure

We used the administrative records of the public health clinics in Armenia. Armenia has a nationwide e-health system that is updated following the patients' visits. Because the health sector is dominated by public health facilities, we are very likely to have information on most of the diabetes and hypertension screening tests conducted. We first randomly selected public health facilities in urban and rural areas that will be sufficient to reach our desired sample size of 2000 individuals. From the patient records at these public health facilities, we then randomly drew our experimental sample, proportionally to the size of the catchment population of the health facilities, from the list of individuals 35-68 who have not been screened in the last 12 months.

From the control group, 400 individuals were administered the baseline questionnaire at the end of the intervention between January 2020 and February 2020. All 400 individuals granted consent for participation for a 100 percent response rate. It is also during this time that the extraction of the screening status from the Armenian e-health administrative data system was conducted on the 1600 study participants from the intervention groups and the 400 participants from the control group, for a total of 2,000 individuals.

Sampling deviation

Note that to avoid contamination of the control group by asking specific questions about diabetes and hypertension screening, the baseline survey was not administered to the control group between July and September 2019 but instead was administered between January 2020 and February 2020, at the end of the intervention period. This short rime difference in administering a survey consisting of questions linked to fairly stable socio-demographic variables was deemed preferable to the risk of changing the behavior of the control group by asking them health specific questions and in particular asking them why they had not screened in the last 12 months.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The baseline and endline questionnaires were administered in English, they are provided for download as related materials.

Response rate

Baseline: A total of 1641 individuals were contacted for F2F visit in four regions, of them 1600 individuals granted consent for participation. The response rate (percentage of individuals who agreed to participate) across targeted communities stands at 97.5%.

Endline: 100%

Health services within the Glasgow area run by NHS Greater Glasgow and Clyde Health Board. Service locations are described by location type e.g. Hospitals, Pharmacies etc. and by address including post code along with OSGR Easting, OSGR Northing, WGS84 Latitude, WGS84 Longitude and a resolvable URI for the post code from the Ordnance Survey Linked Data repository. NHS data extracted October 2013 and provided by NHS Greater Glasgow and Clyde Health Board. Ordnance Survey data published under the terms of an OS OpenData Licence. OS data extracted: 2014-02-19 Contains Ordnance Survey data (c) Crown copyright and database right 2014 Contains Royal Mail data (c) Royal Mail copyright and database right 2014 Contains National Statistics data (c) Crown copyright and database right 2014 Licence: None 2014-04-24-v2-glasgow-loc-geo.json - https://dataservices.open.glasgow.gov.uk/Download/Organisation/556566ae-bb58-44b3-9752-f03abe4075a1/Dataset/1a43bd67-6fbb-475c-97fd-872c2e2fb4c8/File/81be1253-21ab-4875-b075-07789aa88f83/Version/de41260a-983c-426a-91b8-0ed2625a2234

The Innovation Scorecard reports on the use of medicines and medical technologies in the NHS in England, which have been positively appraised by the National Institute for Health and Care Excellence (NICE) since 2012. NHS Digital has produced and published the Innovation Scorecard quarterly as an Official Statistic since January 2013 on behalf of the Office for Life Sciences. It can be used by local NHS organisations to monitor progress in implementing NICE Technology Appraisal (TA) recommendations. We produce the scorecard using a range of data sources from two to five years prior to publication and no central data collection is involved. Medical technologies on the Innovation Scorecard were suspended pending the development of an inclusion criterion. This has now been established and this release sees the reintroduction of 5 medical technologies with updated data and refreshed methodologies from the previously published medical technologies. We are keen to receive feedback on satisfaction with different aspects of the Innovation Scorecard and we would be grateful if you could spare 5-10 minutes of your time to complete a short survey. Survey Open the new web platform tool to access the data. Latest Data to December 2016

Advil was the leading name-brand internal analgesic tablet in the United States in 2019, not including private label. In that year, Advil generated ***** million U.S. dollars in sales, while private label internal analgesic tablet sales amounted to nearly **** billion U.S. dollars. Internal analgesics are often used to treat minor aches and pains, such as headaches. Over-The-Counter products In 2017, total OTC drug retail sales amounted to **** billion U.S. dollars, up from ** billion dollars the previous year. The largest segment of the OTC medicines market in the United States is vitamins and minerals, followed by cold, cough, and flu medicines. Drugstore and pharmacy retail in the U.S. U.S. pharmacy and drug stores generated sales of ****** billion U.S. dollars in 2017. CVS Health and Walgreens were the two leading drug store chains in the United States based on prescription sales, at **** billion U.S. dollars and **** billion U.S. dollars respectively. In 2017, CVS Health operated ***** locations, more than any other drug store chain in the United States.

PSI Somaliland conducted pharmacy MAP (Monitoring Access and Performance) studies in 2011 and 2012, in view of assessing the availability of PSI's BiyoSifeeye, Nasiye and Shuban-Daweeye brands and the associated quality standards across main cities in five regions of Somaliland. This is the third round and is anticipated to identify any changes that may have occurred in the period after the second round. The previous rounds were conducted in 10 main cities, namely Hargeisa, Erigavo, Borama, Berbera, Sheikh, Buroa, Wajale, Gabiley, Ceel-afweyn and Arabsiyo where PSI had strong presence with program activities. As PSI has expanded its interventions to more geographically in Somaliland two additional cities were included in this round. The two additional towns for this round were Dilla of Awdal region and Odweyne of Togdheer region). Five teams of two interviewers with their supervisor and local guides visited every street and corner , even going through residential areas to audit all existing pharmacies. The MOH representative for the data collection were part of the superv ision for the field work. Data collection took place during the time most pharmacies are open both in the morning and in the afternoon. The interviewers administered a questionnaire to the provider at the pharmacy (see Appendix 1). GPS coordinates were also taken.