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Signalling waiting times to citizens on public oral healthcare providers’ websites

Signalling waiting times to citizens on public oral healthcare providers’ websites Act A OdOnt Ol Ogic A Sc AndinA vic A https://doi.org/10.1080/00016357.2023.2204934 Signalling waiting times to citizens on public oral healthcare providers’ websites Riitta Söderlund Unit of information Systems Science, University of t urku, t urku, Finland ARTICLE HISTORY ABSTRACT Received 16 June 2022 Objective: The study aimed to analyse the usefulness of signalling waiting times to citizens on Revised 28 March 2023 the websites of public primary oral healthcare providers in Finland. Finnish laws require this Accepted 17 April 2023 signalling. Material and methods: We gathered data with two cross-sectional surveys in 2021. One electronic KEYWORDS questionnaire was for Finnish-speaking citizens in Southwest Finland. The other was for public Agency theory; citizen; primary oral healthcare managers (n = 159). We also gathered data on 15 public primary oral oral healthcare; healthcare providers’ websites. For the theoretical framework, we combined the agency and signalling theory; signalling theories. waiting times Results: Of the citizen respondents (n = 411), 57% knew about the waiting time signalling on the websites. The respondents considered waiting time a high-priority criterion in choosing a dentist, but they rarely searched for information anywhere on the choice of a dentist, wanting to visit the dentist they had earlier visited. The quality of signalled waiting times was low. One out of five managers (response rate 62%) answered that signalled waiting times were based on speculation. Conclusions: Waiting times were signalled to comply with the legislation rather than to inform citizens and to reduce information asymmetry. Further research is needed to acquire information on rethinking waiting time signalling and its desired goals. Introduction providers, the state actors are the principals, and they provide resources and specify objectives for the healthcare providers, Information asymmetry is typical in healthcare [1]. The area the agents. Conversely, healthcare providers must provide is full of different agencies. Agency between two parties state actors with information on how the objectives have refers to one party, the agent, acting for the other, the prin- been reached. In the third relationship, the citizens are the cipal, in a particular domain of decision problems [2]. Agency principals, and they convey their health needs regarding problems emerge if the parties have different goals and the services to the service providers, the agents, who try to principal cannot determine whether the agent behaves satisfy these needs. appropriately [3]. Agency problems are common; they exist All three parties agree that better health is the primary in all cooperative efforts and all organizations [4]. goal of healthcare actions. There are also non-health aspects In healthcare, there are three major parties: citizens, of citizens’ expectations that need a response. These expec- healthcare providers, and state actors, meaning politicians tations include, e.g. reasonable waiting times for non-urgent and government officials [5]. Citizens are healthcare clients care and a choice of a provider [7,p.22–46]. In primary care, who intend to use, use, or have used health services [6]. waiting time has been defined as waiting to see a healthcare Citizens also are members of communities, and they may or professional [8]. In hospital care, three waiting periods are may not be interested in public issues and taking a stance used: waiting to see a specialist, waiting for hospital treat- on them. ment and total waiting time [9]. Between these three parties, three agency relationships Waiting time for hospital treatment is the quality issue can be distinguished [5]. The relationship between citizens, signalled most frequently to citizens [10]. Also, other quality the principals, and the state actors, the agents, is based on issues, such as rates of complications and patient satisfaction, a voting system expressing citizens’ demands to state actors are signalled. Citizens should receive information for con- and the state actors’ responsiveness to these demands. In scious decision-making on their care [11]. This decision-making the relationship between state actors and healthcare is quite complex, and citizens do not base their decisions CONTACT Riitta Söderlund riitta.soderlund@utu.fi University of t urku Rehtorinpellonkatu 3, 20500 t urku, Finland © 2023 t he Author(s). Published by informa UK limited, trading as t aylor & Francis group on behalf of Acta Odontologica Scandinavica Society. t his is an Open Access article distributed under the terms of the c reative c ommons Attribution license ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. t he terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. 2 R. SÖDERLUND only on factual outcome indicators. Previous service experi- sector provided about half of the adult dentist visits in 2020 ences are essential in choosing a healthcare provider, e.g. a [23]. Based on the FinHealth 2017 study [24,p.151–155], 52% physician or a hospital [12]. There is little evidence that cit- of men and 67% of women visited a dentist regularly for izens require increased possibilities to choose their healthcare check-ups. One out of five expressed that long waiting times provider except in cases where local health services are poor made it difficult to access care, and one out of six said that or have long waiting times [13]. Public healthcare patients the client fee was too high. About 2% felt it was difficult to do not feel that enabling freedom of choice is a central issue. travel to the dentist because of poor transport It would not be realistic or possible to enable freedom of connections. choice in areas where the provision of general practitioners’ Long waiting times for non-urgent care are a problem of services is low [14]. Overall, patients are loyal, but even the public oral healthcare. An appointment for urgent care is most loyal patients change service providers when the quality obtained without waiting. According to the care guarantee of the services significantly decreases [15,p.76–105]. from 2005 [25], a patient must get an appointment with a Waiting times may seem a straightforward indicator of dentist within six months in non-urgent cases. In spring 2021, healthcare actions. However, this is not the case. This indi- about 10% of the patients had to wait more than three cator serves different purposes for different actors and is months to see a dentist for non-urgent care [26]. Citizens difficult to interpret. Incentives, norms and traditions influ- have considered that the waiting time for non-urgent public ence how this indicator is processed and used [16]. When oral health services should be, at most, 46 days [27]. waiting times are signalled to state actors for monitoring, The Finnish Healthcare Act [22] requires that public service the number of patients on the waiting list has been sug- providers signal waiting times for non-urgent care on their gested as a measure [17]. This indicator shows the provider’s websites. Waiting times should be signalled every fourth current actions intended to keep waiting times reasonable. month by functional units. In signalling, for example, the When signalling to citizens, the waiting times of treated third next available non-on-call dentist appointment time is patients can be used [17]. Their interest is the total wait- used [28]. This is preferred in primary care, as random can- ing time. cellations in these cases do not have as much effect as on Studies during 2010–2019 in Canada [18,19] have found first available appointments [29]. In 2003, it was suggested that citizens want to receive more information about waiting that a receptionist could count these waiting times daily or times for elective surgery and primary care. Information is weekly [29]. likely valuable if it is at least somewhat more accurate than In 2020 [30], 89% of Finnish households had access to individuals’ prior knowledge [20,p.319–352]. In 2020, study the Internet at home. Health and nutrition information was results from Italy indicated that it was not easy to find web- searched on the Internet by 72% of Finnish citizens during sites giving information on waiting times for outpatient visits the three-month period prior to the survey. Accordingly, 58% of different kinds of public healthcare organizations, and the had used MyKanta, a digital service offering personal health quality of this information tended to fluctuate [21]. De Rosis data, prescription information and prescription renewals, and et  al. [21] concluded that signalling waiting times was per- 50% had booked an appointment with a physician. formed to comply with the law rather than provide informa- tion to citizens. This study aims to analyse the usefulness of signalling Theoretical framework waiting times to citizens on the websites of public primary oral healthcare providers in Finland. Usefulness requires that We derived the theoretical framework of our study (Figure signalled waiting times positively influence citizens to reach 1) from agency theory [2, 3] and signalling theory [31]. the desired outcomes of oral healthcare providers. To posi- Signalling theory is useful to describe the behaviour of two tively influence citizens, waiting times should be signalled parties when there is information asymmetry between the via easy-access means, and the signalled information should parties, and both have access to different information [32]. meet citizens’ decision-making needs. The research questions Signalling aims to reduce the information asymmetry between are the following: (1) Do citizens screen their environment the parties–the signaller and the receiver–to positively influ- for signals of waiting times for choices of a dentist? (2) What ence the receiver to reach the desired outcomes of the sig- is the quality of signalled waiting times on the websites of naller. Signalling theory has been used in studies on online public oral healthcare providers? (3) How does the manage- activities [33–36] and healthcare [37–40]. ment of oral healthcare providers perceive signalling waiting In oral healthcare, the citizens (principals, receivers) decide times to citizens? on the provider (agent, signaller) whom they will visit, in principle. For this decision-making, citizens may screen their environment for information signals on the oral service pro- viders’ attributes, such as professional competence, person- The context of the study ality and the attitude of dentists [41–44]. Criteria also used In Finland, citizens can choose whether to use public or include service location [45,46], ability to obtain appoint- private oral healthcare services. Using private services is more ments at convenient times and reasonable waiting times for expensive than using public services. If one chooses public appointments [42]. Costs may form barriers to using dental sector services, there are some possibilities to choose the services [46–48]. Citizens may trade off the choice criterion service provider, the unit and the dentist [22]. The public for another, for example, visiting their regular dentist and ACTA ODONTOLOgICA SCANDINAvICA 3 Figure 1. t he theoretical framework derived from agency [2, 3] and signalling [31] theories. speed of access [49]. In general, patients are loyal; only participants were 18 years or older. In addition, the partici- around one out of six will change their dentist if the circum- pants had to provide their informed consent to participate stances, such as the address or the right to services, do not in the study. Therefore, each participant was asked to provide change [50]. In a freedom-of-choice pilot in Finland, a citizen this consent at the beginning of the electronic could choose private sector services with short waiting times questionnaire. and public client fees. The service use depended on subjec- We also required a research permit from all public primary tive oral health [51]. healthcare organizers in Finland for the manager survey. To screen for information on oral health services, family, Applications for research permits were submitted to 135 friends and other dentists are important information sources organizers in March 2021. Of these, 48% had a population [42, 52]. Word of mouth has been [53], and still is, a key means base of more than 20,000 inhabitants. We obtained permits [44]. Dental clinics’ websites are also used [42, 54]. However, from 105. Concerning the citizen survey, we obtained a their usage is minor compared to the number of these web- research permit from all 15 public primary oral healthcare sites. The role of social media is diverse. In one study, one-third organizers of Southwest Finland. of the respondents had used social media in choosing a den- tist [55], and in another study, social media did not play a Citizen survey significant role [56]. In general, citizens seeking dental care use information sources they consider important [42]. For the citizen survey, nonprobability convenience sampling Oral healthcare providers can send out signals to help was chosen, as forming a probability sampling of the citizens citizens to make decisions. These signals are mainly for mar- of Southwest Finland would have been prohibitively resource keting or public reporting purposes. Through marketing, intensive. Thus, any Finnish-speaking adult who accessed the healthcare providers try to attract citizens to care [57], how- website of the study questionnaire in Finnish could partici- ever, citizens seldom receive adequate information from these pate in the study. Nonprobability sampling decreases the sources to evaluate the care they are receiving [58, 59]. Public validity and credibility of study results, but the method is reporting provides citizens with factual performance data for suitable for exploratory research to ascertain whether a prob- decision-making. Citizens often consider this data too com- lem exists or not [62,p.17–32]. plex [60]. To help citizens, performance indicators should be The officials of public primary healthcare organizers in signalled via easy-access means and meet citizens’ Southwest Finland published electronic newsletters about decision-making needs [61]. the survey to inform citizens. These newsletters were pub- lished on the websites of these organizers at the beginning of May 2021, including a link to the survey website. In addi- Materials and methods tion, if the healthcare organizers preferred, they could use To analyse the usefulness of signalling waiting times to cit- other means such as social media for disseminating informa- izens on the websites of public primary oral healthcare pro- tion. Furthermore, some of the chairpersons of the health viders in Finland, we gathered data using two cross-sectional and social services boards in the area were informed about surveys during May and June 2021. One survey was for the survey by phone or email. Finnish public primary oral healthcare managers and the To find out whether citizens screen their environment for other for citizens of Southwest Finland. The surveys were signals of waiting times for choices of a dentist, we used 16 conducted using the software Webropol Survey & Reporting, questions (Table 1). The questions, modified from similar version 3.0. In addition, on 15 September 2021, we gathered surveys [42, 45, 46], concerned the importance of waiting waiting time data on the websites of public primary oral time in choosing a dentist and the sources used to search healthcare providers in Southwest Finland. for information for this decision-making. In addition, we The Ethics Committee for Human Sciences at the University asked about waiting time signalling on the websites of public of Turku approved the study proposal in February 2021 oral healthcare providers and the possibilities to access this (Permit July 2021). This ethical permit required that eligible information, as well as respondents’ personal information, 4 R. SÖDERLUND Table 1. t he citizen survey questions translated into English. Question Answer options Importance of waiting time as an attribute Prioritize the following six criteria in the choice of a dentist for non-urgent care. Mark the main criterion client fee with the number 1, the second most important with the number 2, etc. (c riteria in alphabetical c ompetence of a dentist order in Finnish) interaction skills Waiting time Opening hours l ocation in my opinion, short waiting times for non-urgent care are important when choosing a dentist. Strongly disagree d isagree neither agree nor disagree Agree Strongly agree i can visit any dentist for non-urgent care if the waiting time is short. Strongly disagree d isagree neither agree nor disagree Agree Strongly agree Sources used for screening When choosing a dentist, i screen information from never 1. My relatives, acquaintances, or friends Rarely 2. Social media Sometimes 3. Public service providers’ websites Often 4. Private service providers’ websites Almost always i don’t screen any information from anywhere when choosing a dentist, as i book an appointment with totally disagree the dentist whom i have earlier visited. d isagree neither agree nor disagree Agree totally agree Waiting times on public service providers’ websites i know that this information is reported on the websites of public service providers. Yes no (an automatically skipping of the following question) i have visited these websites. Yes no i would screen this waiting time information on the internet for decision-making when choosing a never dentist. Rarely Sometimes Often Almost always i would use this waiting time information on the internet to assess whether i got a dentist appointment never time in line with reported waiting times. Rarely Sometimes Often Almost always in my opinion, reporting waiting times for dental care on the websites of public service providers is Yes no useful. in my opinion, no-one is interested in the information on waiting times for dental care reported on the Strongly disagree internet. d isagree neither agree nor disagree Agree Strongly agree Access to the websites i have the opportunity to use the internet at home. Yes no On a scale from 1 to 7, how would you assess your digital competence? 1 (very poor) − 2–3–4–5–6–7 (very good) i search for health and disease information on the internet. never or very rarely A couple of times a year About once a month About once a week Several times a week i search for information on health services on the never or very rarely internet. A couple of times a year About once a month About once a week Several times a week i use different health applications, such as never or very rarely MyKanta, on the internet. A couple of times a year About once a month About once a week Several times a week ACTA ODONTOLOgICA SCANDINAvICA 5 Table 2. t he manager survey questions translated into English. Question Answer options Signalling waiting times to citizens What percentage of the citizen survey respondents know about waiting time 0–100% signalling on the websites? My estimate is: What percentage of the citizen survey respondents consider waiting time 0–100% signalling as useful? My estimate is: in my opinion, signalling waiting times for dental care on the websites is Yes no useful for citizens. Should we signal on the websites on the average durations of the different Yes no dental treatment episodes we provide in our organization? Processing waiting time information How is the information on waiting times for accessing non-urgent dental c alculated automatically with the electronic patient information system care processed to be signalled on the website of your organization? c alculated manually using t1, the first available non-on-call dentist appointment time c alculated manually using t3, the third next available non-on-call dentist appointment time Estimated by speculation i don’t know how the information is processed t he electronic patient information system should automatically process the Strongly disagree necessary information on waiting times for access to non-urgent dental d isagree care. neither agree nor disagree Agree Strongly agree such as gender, year of birth, education and use of oral The survey included six questions on managers’ percep- health services. tions of signalling waiting times to citizens on the websites (Table 2). Managers’ backgrounds, such as their degree and qualification, the number of years of management, and the Gathering waiting time data population of the area they managed, were also surveyed as data to be used in other studies. We gathered waiting time data on the websites of the 15 public primary oral healthcare providers of Southwest Finland on 15 September 2021. Finding relevant data on the websites Statistical analyses was challenging. The data included the precision and unit of measurement of waiting time and the release date for Statistical analyses were carried out using the software IBM signalling. We assessed the quality as low if the release date SPSS Statistics for Windows, version 28.0.0.0. In SPSS, the was earlier than 15 May 2021 or missing; this signalling was cases where data on a variable was missing were excluded against the law as waiting times should be signalled every from the analyses. The categorical data of the study enabled fourth month. The quality was also assessed to be low if descriptive statistics to be predominantly used. Some data imprecise wording, such as about, was used. was gathered using a five-point Likert scale or another five-point ordinal scale. The distance between each response in the item of these scales was not considered to be equal, Manager survey but this data was also handled as internal-level data, and means were calculated. This lack of equality of intervals has The research design included gathering data from every oral little impact on the statistical conclusions of studies, though healthcare manager working in the public primary sector in parametric statistics are applied [63,p.1–25]. Finland in the spring of 2021. As not all public primary healthcare organizers granted the research permit, we chose the managers for the study using convenience sampling. The Results number of managers of the 105 healthcare organizers included in our study was 159. Citizens The survey was implemented in Finnish with an open Descriptive statistics Internet link to allow anonymous responses. The Internet link Four hundred and eleven citizens answered the questionnaire. was sent to the contact persons of the oral healthcare orga- Of these, 17 had answered the questions but did not provide nizations, detailed in the granted research permits, at the informed consent to participate in the study. Thus, the num- beginning of May 2021. Reminders to answer were sent at ber of respondents included in the analysis was 394. In addi- the end of May. Originally, we informed the oral healthcare tion, there was a minimal lack of data because not all managers that it would be possible to reply to the question- respondents answered all questions. The number of respon- naire by June 11. On June 2, the national waiting time website dents answering different questions varied from 385 to 394. referred to in the survey was updated, resulting in us closing In the case of each question, the number of valid responses our questionnaire on that date. We sent a message regarding (n) is separately reported. this to the oral healthcare organizations the next day. 6 R. SÖDERLUND Regarding gender, 87% of the respondents (n = 391) were from private service providers’ websites 16% and 63% women, and the age range was from 20 to 80 years (n = 385). (n = 386) and using social media 4% and 82% (n = 385). Both the mean and the median ages were 49, 7% of respon- Seventy-three percent of the respondents (n = 392) agreed dents were younger than 30, and 4% were 70 or older. or strongly agreed that they do not screen any information Twenty-one percent of the respondents (n = 393) had a mas- from anywhere when choosing a dentist, booking appoint- ter’s degree, 46% had a bachelor’s degree or college-level ments with dentists whom they have visited earlier. education, 30% had completed a vocational education or matriculation examination and 4% elementary or compre- Waiting times on the public service providers’ websites hensive school qualifications. Fifty-seven percent of the respondents (n = 394) knew that Sixty-five percent of the respondents (n = 393) visited a public providers signal waiting times for non-urgent oral dentist regularly for check-ups, 28% visited a dentist irregu- healthcare on their websites. Of those, 71% had visited these larly and 7% only when suffering from a toothache or other websites, corresponding to 40% of all respondents. Sixty-nine problems. Fifty-three percent only used public oral services, percent of all respondents (n = 392) presumed that they could while 7% only used private sector services (n = 393). The at least sometimes use signalled waiting time information in remainder, 40%, used both public and private oral health decision-making when choosing a dentist. Accordingly, 68% services in different proportions. thought to use the information for assessing whether they got their appointment in line with signalled waiting times (n = 392). Ninety-three percent of the respondents (n = 390) Importance of waiting time as an attribute considered signalling waiting times on the service providers’ The respondents ( n = 393) prioritized the attributes websites useful. In contrast, 17% agreed or strongly agreed Competence of a dentist and Waiting time as the most that the information does not interest anyone (n = 394). important in choosing a dentist for non-urgent care (Figure 2). The respondents (n = 393) agreed that short waiting times for non-urgent care are important in choosing a dentist. Table Access to the websites 3 presents the variation of this importance by the personal Only three of the citizen survey respondents could not access information of the respondents. Of the respondents (n = 394), the Internet at home (n = 393). On a scale from 1 (very poor) 62% agreed or strongly agreed that they could visit any to 7 (very good), they assessed their digital competence to dentist for non-urgent care if the waiting time is short. be, on average, 5.9 (n = 391). The standard deviation was 1.1, the median 6 and the range 1–7. Of the respondents (n = 394), 27% searched the Internet for health information at least Sources used for screening once a week, 29% searched once a month, 36% a couple of In choosing a dentist, 15% of respondents often or almost times a year and 8% never. Furthermore, 18% searched for always screened information from relatives, acquaintances information about health services at least once a week, 31% and/or friends (n = 388). Information from these sources was once a month, 45% a couple of times a year and 6% never never or rarely screened by 62%. The corresponding propor- (n = 394). Ten percent of the respondents (n = 393) used health tions for screening information from public service providers’ applications, e.g. MyKanta, at least once a week, 38% once websites were 19% and 58% (n = 388), screening information a month, 45% a couple of times a year and 7% never. Figure 2. t he priority of waiting time among providers’ attributes in citizens’ choices of a dentist for non-urgent care (n = 393). ACTA ODONTOLOgICA SCANDINAvICA 7 Table 3. t he importance of short waiting times for non-urgent dental care by the citizen respondents’ personal information. a a a a a Personal information n Mean Median Std. deviation Minimum Maximum Age   20–29 27 4.0 4 1.3 1 5   30–39 66 4.2 5 1.0 2 5   40–49 101 4.0 4 1.1 1 5   50–59 90 4.2 4 1.1 1 5   60–69 86 4.0 4 1.0 1 5   70– 14 3.4 3 1.2 2 5   t otal 384 4.1 4 1.1 1 5 g ender   Man 47 4.0 4 1.1 2 5   Woman 340 4.1 4 1.1 1 5   Other 3 4.7 5 .6 4 5   t otal 390 4.1 4 1.1 1 5 Education  A 14 3.6 4 1.3 1 5  B 119 4.2 4 1.1 1 5   c 178 4.0 4 1.1 1 5   d 81 4.0 4 1.1 1 5   t otal 392 4.1 4 1.1 1 5 ServProvider   Only pub 210 4.0 4 1.1 1 5   Mainly pub 98 4.1 4 1.1 1 5   Pub and priv 20 4.3 4.5 .9 2 5   Mainly priv 37 4.2 5 1.1 1 5   Only priv 27 4.0 4 1.1 2 5   t otal 392 4.1 4 1.1 1 5 v isits   Regular 255 4.0 4 1.1 1 5   irregular 111 4.2 5 1.1 1 5   t oothache 26 3.8 4 1.4 1 5   t otal 392 4.1 4 1.1 1 5 importance measured using a five-point likert scale (1 = strongly disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, 5 = strongly agree). (A) Elementary or comprehensive school, (B) A vocational education or matriculation examination, (c ) A bachelor’s degree or college-level education, (d) A master’s degree. Pub = Public sector service provider, Priv = Private sector service provider. Quality of signalled waiting times Perceptions of signalling waiting times to citizens Ninety percent of the managers (n = 96) perceived signalling Table 4 presents how the 15 public primary oral healthcare waiting times for non-urgent dental care to citizens on the web- providers signalled waiting times on their websites on 15 sites as useful. Only 41% presumed that the average durations September 2021. of different dental treatment episodes should also be signalled to citizens (n = 97). The managers (n = 92) estimated that, on average, 25% of the citizen respondents knew about waiting time signalling on Managers the websites. The lower quartile was 10%, the median 20% and the upper quartile 35%. Furthermore, they (n = 91) esti- Descriptive statistics mated that, on average, 53% of the citizen respondents con- Ninety-eight of the 159 managers potentially participating in sidered signalling waiting times useful. The lower quartile was the study answered our questionnaire, a response rate of 62%. 30%, the median 55% and the upper quartile 75%. One of the managers had answered the questions but did not provide informed consent to participate in the study, so the number of managers included in the analysis was 97. There also Processing waiting time information was a minimal lack of data as not all the managers answered Twelve percent of the managers (n = 96) answered that the all questions. The number of respondents answering different electronic patient information system processed waiting time questions varied from 91 to 97. indicators. The indicators were processed manually using Sixty percent of the managers (n = 96) had a licentiate either the first or third next available appointment time degree in dentistry, 20% were specialist dentists and 20% according to the answers of 64% of the managers, and 18% had other qualifications, for example, eight were dental answered that estimates by speculation were used. hygienists. As managers, 40% had worked for 5 years or less, Eighty-eight percent of the organizations in which waiting 16% from 6 to 10 years and 44% longer than 10 years (n = 93). times were estimated by speculation had a population base Approximately half worked in organizations with a population of up to 20,000. Seven managers did not know how the base of up to 20,000 and the other half in organizations with indicators were processed. Of these, two managed an orga- a larger population base (n = 95). nization with a population base of up to 20,000. 8 R. SÖDERLUND Table 4. Waiting time indicators signalled on the websites of the 15 public previous studies [42]. Less than one-fifth of the citizen primary oral healthcare providers on 15.9.2021. respondents often or almost always searched for information Provider Waiting time Release date for this decision-making. The citizen respondents did not A About four months no date need to search for information, as they wanted to visit the B 82, 94, 114 days 19 July 2021 dentist they had visited earlier, perhaps based on their pre- c t arget five months no date d 61, 79 24 h May 2021 vious service experiences [12]. Previous studies have also E 104 days 2 August 2021 emphasized patients’ loyalty to their dentists [50]. getting F 1½, 1½, 3, 3, 3½ months Week 22 information from family and friends by word of mouth has g 34 weekdays 1 September 2021 H t wo–three months no date been a standard method of obtaining information in earlier i 75 24 h 1 September 2021 literature [42,44,52,53]. This was also visible in our study, J About six months September 2021 though the respondents used private and public service pro- K About four months 18 June 2021 l t hree months April 2021 viders’ websites a little more. M 67 calendar days August 2021 We agreed with the conclusions of De Rosis et  al. [21]. n 62, 62, 75, 98 24 h no date Also, in Finland, providers signalled waiting times on the O 93 weekdays August 2021 a websites to comply with the law rather than to provide infor- Waiting times signalled by units. mation to citizens. The quality of the signals was low: one-third were imprecise, giving timeframes such as Ninety-five percent of the managers (n = 95) agreed or ‘two-three months’. One-third missed the release date, or the agreed strongly that electronic patient information systems date was not within four months, as specified by law [22]. should automatically process waiting time indicators. The researchers did not easily find this information on the providers’ websites. The fact that public oral healthcare providers had no stra- Discussion tegic goals for signalling may explain the low-quality waiting Our survey analysed the usefulness of signalling waiting time information. Providers did not need to increase their times to citizens on the websites of public primary oral clientele and competition with private and other public pro- healthcare providers in Finland. Using websites to signal wait- viders was minimal. For some citizens, client fees form bar- ing times is effective, as most of the citizen respondents riers to using private services [24,46–48]. Choosing another have access to the Internet and use it to search for health public service provider may be difficult because of poor information. Approximately 60% of the citizen respondents transport connections [24], or it may increase traveling time knew about this signalling, and about 70% presumed that and costs. Based on other studies, public healthcare patients they at least sometimes could use the information. The citizen do not consider freedom of choice as a central matter, espe- respondents considered waiting time a high-priority criterion cially in sparsely populated areas [13,14]. when choosing a dentist for non-urgent care. In practice, they had minimal need to search for any information for decision-making, preferring to visit the dentist they had ear- Practical implications lier visited. Also, the choice possibility when using public services was minor. Though the managers perceived signal- The citizen respondents perceived waiting time signalling on ling waiting times on the websites as useful, the quality of the websites as useful, though the need for waiting time signalled waiting times was low. Approximately one out of information was minor. They could access the Internet at five managers answered that the signalled information was home, and many used it to search for health information. estimated by speculation. The study results indicated that The websites were a proper means to signal waiting times. waiting times were signalled to comply with Finnish legisla- However, the low-quality information was a problem. Every tion rather than to reduce the information asymmetry oral healthcare provider had an electronic patient information between citizens and oral healthcare providers. system, but only about 10% used the system to calculate We derived the theoretical framework of our study from the waiting times. the agency theory [2, 3] and signalling theory [31]. The In these systems, providers have the data required to framework worked well to analyse the usefulness of waiting calculate waiting time indicators [64]. Supplementing the time signalling in the study context. As a result of information systems with proper functionalities would enable the auto- asymmetry between citizens (principals) and oral healthcare matic calculation of waiting times to be published daily on providers (agents), citizens, unlike providers, do not know the websites. The information could be categorized by all the attributes of providers, such as waiting times for access- attributes, such as the dentist, recorded into the systems. ing care, to influence decision-making in choosing a dentist. Different statistical key figures, such as the mean and median To reduce information asymmetry, providers can signal some of waiting time, could be calculated. Providers could get attributes to citizens to achieve the desired outcomes of accurate information on the waiting times of those patients providers, such as increasing the clientele. The content and who received an appointment on the day in question. Of means of signalling should be the ones that citizens consider course, cancellations should be taken into consideration. For useful and can and will use for decision-making. automatic calculations, oral healthcare providers need Waiting time information was a high-priority criterion in national definitions, specifications for electronic patient infor- choosing a dentist for non-urgent care in our study, as in mation systems and instructions for personnel. A dental nurse ACTA ODONTOLOgICA SCANDINAvICA 9 should no longer use worktime to calculate the third next needed to acquire information on rethinking waiting time sig- available appointment time [28, 29], instead, providers should nalling in oral healthcare and its desired goals. use automatic data management. Acknowledgements Limitations and future research The authors thank the Finnish public primary healthcare organizers for enabling the study. In addition, the authors thank the officials of the Our study is not without limitations. With a cross-sectional organizers of public primary healthcare in Southwest Finland for dis- survey, we can never verify any causality. As convenience seminating information of the study to citizens by different media. sampling was used, it decreased the validity and credibility of the study results [62]. The challenge is that the respon- dents taking part in the study may be those who have a Disclosure statement very positive or negative view of the studied issue. It is easier No potential conflict of interest was reported by the author(s). to arouse their attention to participate than to arouse the interest of others. In our citizen study, the method of inform- ing about the survey may also have caused bias in the Funding results; some political decision-makers of the area were informed more personally about the survey than other citi- There was no external funding for the study. zens. The proportions of the citizen respondents knowing of and visiting websites signalling waiting times were probably ORCID higher than with probability sampling. It is also probable that citizens taking part in electronic surveys have better Riitta Söderlund http://orcid.org/0000-0003-3026-8246 digital competence and easier access to the Internet and electronic services than citizens on average. Finally, although we would have used probability sampling, the possibility to Data availability statement generalize the study results to other environments is restricted. The healthcare systems and social and cultural According to the privacy policy, the researcher can process the survey aspects differ remarkably by country. data for the time required for her thesis. During the time, the data will Access to non-urgent dental care within a reasonable time not be transferred outside the University of Turku. After that, the data without the credentials is disclosed to the Finnish Social Science Data is essential for citizens [7]. The participants in our study were Archive without conditions for the use of the disclosed materials. ready to visit any dentist for non-urgent care if the waiting time for access to care was short. Reducing waiting times is also a key objective in the healthcare strategies of many countries. However, speeding up access to dental care may References lengthen dental treatment episodes. It is easy to speed up [1] Arrow K. Uncertainty and the welfare economics of medical care. access to care by lengthening the intervals between other Am Econ Rev. 1963;53(5):941–973. visits required for the dental treatment episode of a patient. [2] Ross S. The economic theory of agency: the principal’s problem. Instead of focusing only on speeding up access to care, meth- Am Econ Rev. 1973;63(2):134–139. ods of keeping the durations of the dental treatment episodes [3] Eisenhardt K. 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Signalling waiting times to citizens on public oral healthcare providers’ websites

Acta Odontologica Scandinavica , Volume 81 (7): 11 – Oct 3, 2023

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Taylor & Francis
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© 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of Acta Odontologica Scandinavica Society.
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1502-3850
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10.1080/00016357.2023.2204934
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Abstract

Act A OdOnt Ol Ogic A Sc AndinA vic A https://doi.org/10.1080/00016357.2023.2204934 Signalling waiting times to citizens on public oral healthcare providers’ websites Riitta Söderlund Unit of information Systems Science, University of t urku, t urku, Finland ARTICLE HISTORY ABSTRACT Received 16 June 2022 Objective: The study aimed to analyse the usefulness of signalling waiting times to citizens on Revised 28 March 2023 the websites of public primary oral healthcare providers in Finland. Finnish laws require this Accepted 17 April 2023 signalling. Material and methods: We gathered data with two cross-sectional surveys in 2021. One electronic KEYWORDS questionnaire was for Finnish-speaking citizens in Southwest Finland. The other was for public Agency theory; citizen; primary oral healthcare managers (n = 159). We also gathered data on 15 public primary oral oral healthcare; healthcare providers’ websites. For the theoretical framework, we combined the agency and signalling theory; signalling theories. waiting times Results: Of the citizen respondents (n = 411), 57% knew about the waiting time signalling on the websites. The respondents considered waiting time a high-priority criterion in choosing a dentist, but they rarely searched for information anywhere on the choice of a dentist, wanting to visit the dentist they had earlier visited. The quality of signalled waiting times was low. One out of five managers (response rate 62%) answered that signalled waiting times were based on speculation. Conclusions: Waiting times were signalled to comply with the legislation rather than to inform citizens and to reduce information asymmetry. Further research is needed to acquire information on rethinking waiting time signalling and its desired goals. Introduction providers, the state actors are the principals, and they provide resources and specify objectives for the healthcare providers, Information asymmetry is typical in healthcare [1]. The area the agents. Conversely, healthcare providers must provide is full of different agencies. Agency between two parties state actors with information on how the objectives have refers to one party, the agent, acting for the other, the prin- been reached. In the third relationship, the citizens are the cipal, in a particular domain of decision problems [2]. Agency principals, and they convey their health needs regarding problems emerge if the parties have different goals and the services to the service providers, the agents, who try to principal cannot determine whether the agent behaves satisfy these needs. appropriately [3]. Agency problems are common; they exist All three parties agree that better health is the primary in all cooperative efforts and all organizations [4]. goal of healthcare actions. There are also non-health aspects In healthcare, there are three major parties: citizens, of citizens’ expectations that need a response. These expec- healthcare providers, and state actors, meaning politicians tations include, e.g. reasonable waiting times for non-urgent and government officials [5]. Citizens are healthcare clients care and a choice of a provider [7,p.22–46]. In primary care, who intend to use, use, or have used health services [6]. waiting time has been defined as waiting to see a healthcare Citizens also are members of communities, and they may or professional [8]. In hospital care, three waiting periods are may not be interested in public issues and taking a stance used: waiting to see a specialist, waiting for hospital treat- on them. ment and total waiting time [9]. Between these three parties, three agency relationships Waiting time for hospital treatment is the quality issue can be distinguished [5]. The relationship between citizens, signalled most frequently to citizens [10]. Also, other quality the principals, and the state actors, the agents, is based on issues, such as rates of complications and patient satisfaction, a voting system expressing citizens’ demands to state actors are signalled. Citizens should receive information for con- and the state actors’ responsiveness to these demands. In scious decision-making on their care [11]. This decision-making the relationship between state actors and healthcare is quite complex, and citizens do not base their decisions CONTACT Riitta Söderlund riitta.soderlund@utu.fi University of t urku Rehtorinpellonkatu 3, 20500 t urku, Finland © 2023 t he Author(s). Published by informa UK limited, trading as t aylor & Francis group on behalf of Acta Odontologica Scandinavica Society. t his is an Open Access article distributed under the terms of the c reative c ommons Attribution license ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. t he terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. 2 R. SÖDERLUND only on factual outcome indicators. Previous service experi- sector provided about half of the adult dentist visits in 2020 ences are essential in choosing a healthcare provider, e.g. a [23]. Based on the FinHealth 2017 study [24,p.151–155], 52% physician or a hospital [12]. There is little evidence that cit- of men and 67% of women visited a dentist regularly for izens require increased possibilities to choose their healthcare check-ups. One out of five expressed that long waiting times provider except in cases where local health services are poor made it difficult to access care, and one out of six said that or have long waiting times [13]. Public healthcare patients the client fee was too high. About 2% felt it was difficult to do not feel that enabling freedom of choice is a central issue. travel to the dentist because of poor transport It would not be realistic or possible to enable freedom of connections. choice in areas where the provision of general practitioners’ Long waiting times for non-urgent care are a problem of services is low [14]. Overall, patients are loyal, but even the public oral healthcare. An appointment for urgent care is most loyal patients change service providers when the quality obtained without waiting. According to the care guarantee of the services significantly decreases [15,p.76–105]. from 2005 [25], a patient must get an appointment with a Waiting times may seem a straightforward indicator of dentist within six months in non-urgent cases. In spring 2021, healthcare actions. However, this is not the case. This indi- about 10% of the patients had to wait more than three cator serves different purposes for different actors and is months to see a dentist for non-urgent care [26]. Citizens difficult to interpret. Incentives, norms and traditions influ- have considered that the waiting time for non-urgent public ence how this indicator is processed and used [16]. When oral health services should be, at most, 46 days [27]. waiting times are signalled to state actors for monitoring, The Finnish Healthcare Act [22] requires that public service the number of patients on the waiting list has been sug- providers signal waiting times for non-urgent care on their gested as a measure [17]. This indicator shows the provider’s websites. Waiting times should be signalled every fourth current actions intended to keep waiting times reasonable. month by functional units. In signalling, for example, the When signalling to citizens, the waiting times of treated third next available non-on-call dentist appointment time is patients can be used [17]. Their interest is the total wait- used [28]. This is preferred in primary care, as random can- ing time. cellations in these cases do not have as much effect as on Studies during 2010–2019 in Canada [18,19] have found first available appointments [29]. In 2003, it was suggested that citizens want to receive more information about waiting that a receptionist could count these waiting times daily or times for elective surgery and primary care. Information is weekly [29]. likely valuable if it is at least somewhat more accurate than In 2020 [30], 89% of Finnish households had access to individuals’ prior knowledge [20,p.319–352]. In 2020, study the Internet at home. Health and nutrition information was results from Italy indicated that it was not easy to find web- searched on the Internet by 72% of Finnish citizens during sites giving information on waiting times for outpatient visits the three-month period prior to the survey. Accordingly, 58% of different kinds of public healthcare organizations, and the had used MyKanta, a digital service offering personal health quality of this information tended to fluctuate [21]. De Rosis data, prescription information and prescription renewals, and et  al. [21] concluded that signalling waiting times was per- 50% had booked an appointment with a physician. formed to comply with the law rather than provide informa- tion to citizens. This study aims to analyse the usefulness of signalling Theoretical framework waiting times to citizens on the websites of public primary oral healthcare providers in Finland. Usefulness requires that We derived the theoretical framework of our study (Figure signalled waiting times positively influence citizens to reach 1) from agency theory [2, 3] and signalling theory [31]. the desired outcomes of oral healthcare providers. To posi- Signalling theory is useful to describe the behaviour of two tively influence citizens, waiting times should be signalled parties when there is information asymmetry between the via easy-access means, and the signalled information should parties, and both have access to different information [32]. meet citizens’ decision-making needs. The research questions Signalling aims to reduce the information asymmetry between are the following: (1) Do citizens screen their environment the parties–the signaller and the receiver–to positively influ- for signals of waiting times for choices of a dentist? (2) What ence the receiver to reach the desired outcomes of the sig- is the quality of signalled waiting times on the websites of naller. Signalling theory has been used in studies on online public oral healthcare providers? (3) How does the manage- activities [33–36] and healthcare [37–40]. ment of oral healthcare providers perceive signalling waiting In oral healthcare, the citizens (principals, receivers) decide times to citizens? on the provider (agent, signaller) whom they will visit, in principle. For this decision-making, citizens may screen their environment for information signals on the oral service pro- viders’ attributes, such as professional competence, person- The context of the study ality and the attitude of dentists [41–44]. Criteria also used In Finland, citizens can choose whether to use public or include service location [45,46], ability to obtain appoint- private oral healthcare services. Using private services is more ments at convenient times and reasonable waiting times for expensive than using public services. If one chooses public appointments [42]. Costs may form barriers to using dental sector services, there are some possibilities to choose the services [46–48]. Citizens may trade off the choice criterion service provider, the unit and the dentist [22]. The public for another, for example, visiting their regular dentist and ACTA ODONTOLOgICA SCANDINAvICA 3 Figure 1. t he theoretical framework derived from agency [2, 3] and signalling [31] theories. speed of access [49]. In general, patients are loyal; only participants were 18 years or older. In addition, the partici- around one out of six will change their dentist if the circum- pants had to provide their informed consent to participate stances, such as the address or the right to services, do not in the study. Therefore, each participant was asked to provide change [50]. In a freedom-of-choice pilot in Finland, a citizen this consent at the beginning of the electronic could choose private sector services with short waiting times questionnaire. and public client fees. The service use depended on subjec- We also required a research permit from all public primary tive oral health [51]. healthcare organizers in Finland for the manager survey. To screen for information on oral health services, family, Applications for research permits were submitted to 135 friends and other dentists are important information sources organizers in March 2021. Of these, 48% had a population [42, 52]. Word of mouth has been [53], and still is, a key means base of more than 20,000 inhabitants. We obtained permits [44]. Dental clinics’ websites are also used [42, 54]. However, from 105. Concerning the citizen survey, we obtained a their usage is minor compared to the number of these web- research permit from all 15 public primary oral healthcare sites. The role of social media is diverse. In one study, one-third organizers of Southwest Finland. of the respondents had used social media in choosing a den- tist [55], and in another study, social media did not play a Citizen survey significant role [56]. In general, citizens seeking dental care use information sources they consider important [42]. For the citizen survey, nonprobability convenience sampling Oral healthcare providers can send out signals to help was chosen, as forming a probability sampling of the citizens citizens to make decisions. These signals are mainly for mar- of Southwest Finland would have been prohibitively resource keting or public reporting purposes. Through marketing, intensive. Thus, any Finnish-speaking adult who accessed the healthcare providers try to attract citizens to care [57], how- website of the study questionnaire in Finnish could partici- ever, citizens seldom receive adequate information from these pate in the study. Nonprobability sampling decreases the sources to evaluate the care they are receiving [58, 59]. Public validity and credibility of study results, but the method is reporting provides citizens with factual performance data for suitable for exploratory research to ascertain whether a prob- decision-making. Citizens often consider this data too com- lem exists or not [62,p.17–32]. plex [60]. To help citizens, performance indicators should be The officials of public primary healthcare organizers in signalled via easy-access means and meet citizens’ Southwest Finland published electronic newsletters about decision-making needs [61]. the survey to inform citizens. These newsletters were pub- lished on the websites of these organizers at the beginning of May 2021, including a link to the survey website. In addi- Materials and methods tion, if the healthcare organizers preferred, they could use To analyse the usefulness of signalling waiting times to cit- other means such as social media for disseminating informa- izens on the websites of public primary oral healthcare pro- tion. Furthermore, some of the chairpersons of the health viders in Finland, we gathered data using two cross-sectional and social services boards in the area were informed about surveys during May and June 2021. One survey was for the survey by phone or email. Finnish public primary oral healthcare managers and the To find out whether citizens screen their environment for other for citizens of Southwest Finland. The surveys were signals of waiting times for choices of a dentist, we used 16 conducted using the software Webropol Survey & Reporting, questions (Table 1). The questions, modified from similar version 3.0. In addition, on 15 September 2021, we gathered surveys [42, 45, 46], concerned the importance of waiting waiting time data on the websites of public primary oral time in choosing a dentist and the sources used to search healthcare providers in Southwest Finland. for information for this decision-making. In addition, we The Ethics Committee for Human Sciences at the University asked about waiting time signalling on the websites of public of Turku approved the study proposal in February 2021 oral healthcare providers and the possibilities to access this (Permit July 2021). This ethical permit required that eligible information, as well as respondents’ personal information, 4 R. SÖDERLUND Table 1. t he citizen survey questions translated into English. Question Answer options Importance of waiting time as an attribute Prioritize the following six criteria in the choice of a dentist for non-urgent care. Mark the main criterion client fee with the number 1, the second most important with the number 2, etc. (c riteria in alphabetical c ompetence of a dentist order in Finnish) interaction skills Waiting time Opening hours l ocation in my opinion, short waiting times for non-urgent care are important when choosing a dentist. Strongly disagree d isagree neither agree nor disagree Agree Strongly agree i can visit any dentist for non-urgent care if the waiting time is short. Strongly disagree d isagree neither agree nor disagree Agree Strongly agree Sources used for screening When choosing a dentist, i screen information from never 1. My relatives, acquaintances, or friends Rarely 2. Social media Sometimes 3. Public service providers’ websites Often 4. Private service providers’ websites Almost always i don’t screen any information from anywhere when choosing a dentist, as i book an appointment with totally disagree the dentist whom i have earlier visited. d isagree neither agree nor disagree Agree totally agree Waiting times on public service providers’ websites i know that this information is reported on the websites of public service providers. Yes no (an automatically skipping of the following question) i have visited these websites. Yes no i would screen this waiting time information on the internet for decision-making when choosing a never dentist. Rarely Sometimes Often Almost always i would use this waiting time information on the internet to assess whether i got a dentist appointment never time in line with reported waiting times. Rarely Sometimes Often Almost always in my opinion, reporting waiting times for dental care on the websites of public service providers is Yes no useful. in my opinion, no-one is interested in the information on waiting times for dental care reported on the Strongly disagree internet. d isagree neither agree nor disagree Agree Strongly agree Access to the websites i have the opportunity to use the internet at home. Yes no On a scale from 1 to 7, how would you assess your digital competence? 1 (very poor) − 2–3–4–5–6–7 (very good) i search for health and disease information on the internet. never or very rarely A couple of times a year About once a month About once a week Several times a week i search for information on health services on the never or very rarely internet. A couple of times a year About once a month About once a week Several times a week i use different health applications, such as never or very rarely MyKanta, on the internet. A couple of times a year About once a month About once a week Several times a week ACTA ODONTOLOgICA SCANDINAvICA 5 Table 2. t he manager survey questions translated into English. Question Answer options Signalling waiting times to citizens What percentage of the citizen survey respondents know about waiting time 0–100% signalling on the websites? My estimate is: What percentage of the citizen survey respondents consider waiting time 0–100% signalling as useful? My estimate is: in my opinion, signalling waiting times for dental care on the websites is Yes no useful for citizens. Should we signal on the websites on the average durations of the different Yes no dental treatment episodes we provide in our organization? Processing waiting time information How is the information on waiting times for accessing non-urgent dental c alculated automatically with the electronic patient information system care processed to be signalled on the website of your organization? c alculated manually using t1, the first available non-on-call dentist appointment time c alculated manually using t3, the third next available non-on-call dentist appointment time Estimated by speculation i don’t know how the information is processed t he electronic patient information system should automatically process the Strongly disagree necessary information on waiting times for access to non-urgent dental d isagree care. neither agree nor disagree Agree Strongly agree such as gender, year of birth, education and use of oral The survey included six questions on managers’ percep- health services. tions of signalling waiting times to citizens on the websites (Table 2). Managers’ backgrounds, such as their degree and qualification, the number of years of management, and the Gathering waiting time data population of the area they managed, were also surveyed as data to be used in other studies. We gathered waiting time data on the websites of the 15 public primary oral healthcare providers of Southwest Finland on 15 September 2021. Finding relevant data on the websites Statistical analyses was challenging. The data included the precision and unit of measurement of waiting time and the release date for Statistical analyses were carried out using the software IBM signalling. We assessed the quality as low if the release date SPSS Statistics for Windows, version 28.0.0.0. In SPSS, the was earlier than 15 May 2021 or missing; this signalling was cases where data on a variable was missing were excluded against the law as waiting times should be signalled every from the analyses. The categorical data of the study enabled fourth month. The quality was also assessed to be low if descriptive statistics to be predominantly used. Some data imprecise wording, such as about, was used. was gathered using a five-point Likert scale or another five-point ordinal scale. The distance between each response in the item of these scales was not considered to be equal, Manager survey but this data was also handled as internal-level data, and means were calculated. This lack of equality of intervals has The research design included gathering data from every oral little impact on the statistical conclusions of studies, though healthcare manager working in the public primary sector in parametric statistics are applied [63,p.1–25]. Finland in the spring of 2021. As not all public primary healthcare organizers granted the research permit, we chose the managers for the study using convenience sampling. The Results number of managers of the 105 healthcare organizers included in our study was 159. Citizens The survey was implemented in Finnish with an open Descriptive statistics Internet link to allow anonymous responses. The Internet link Four hundred and eleven citizens answered the questionnaire. was sent to the contact persons of the oral healthcare orga- Of these, 17 had answered the questions but did not provide nizations, detailed in the granted research permits, at the informed consent to participate in the study. Thus, the num- beginning of May 2021. Reminders to answer were sent at ber of respondents included in the analysis was 394. In addi- the end of May. Originally, we informed the oral healthcare tion, there was a minimal lack of data because not all managers that it would be possible to reply to the question- respondents answered all questions. The number of respon- naire by June 11. On June 2, the national waiting time website dents answering different questions varied from 385 to 394. referred to in the survey was updated, resulting in us closing In the case of each question, the number of valid responses our questionnaire on that date. We sent a message regarding (n) is separately reported. this to the oral healthcare organizations the next day. 6 R. SÖDERLUND Regarding gender, 87% of the respondents (n = 391) were from private service providers’ websites 16% and 63% women, and the age range was from 20 to 80 years (n = 385). (n = 386) and using social media 4% and 82% (n = 385). Both the mean and the median ages were 49, 7% of respon- Seventy-three percent of the respondents (n = 392) agreed dents were younger than 30, and 4% were 70 or older. or strongly agreed that they do not screen any information Twenty-one percent of the respondents (n = 393) had a mas- from anywhere when choosing a dentist, booking appoint- ter’s degree, 46% had a bachelor’s degree or college-level ments with dentists whom they have visited earlier. education, 30% had completed a vocational education or matriculation examination and 4% elementary or compre- Waiting times on the public service providers’ websites hensive school qualifications. Fifty-seven percent of the respondents (n = 394) knew that Sixty-five percent of the respondents (n = 393) visited a public providers signal waiting times for non-urgent oral dentist regularly for check-ups, 28% visited a dentist irregu- healthcare on their websites. Of those, 71% had visited these larly and 7% only when suffering from a toothache or other websites, corresponding to 40% of all respondents. Sixty-nine problems. Fifty-three percent only used public oral services, percent of all respondents (n = 392) presumed that they could while 7% only used private sector services (n = 393). The at least sometimes use signalled waiting time information in remainder, 40%, used both public and private oral health decision-making when choosing a dentist. Accordingly, 68% services in different proportions. thought to use the information for assessing whether they got their appointment in line with signalled waiting times (n = 392). Ninety-three percent of the respondents (n = 390) Importance of waiting time as an attribute considered signalling waiting times on the service providers’ The respondents ( n = 393) prioritized the attributes websites useful. In contrast, 17% agreed or strongly agreed Competence of a dentist and Waiting time as the most that the information does not interest anyone (n = 394). important in choosing a dentist for non-urgent care (Figure 2). The respondents (n = 393) agreed that short waiting times for non-urgent care are important in choosing a dentist. Table Access to the websites 3 presents the variation of this importance by the personal Only three of the citizen survey respondents could not access information of the respondents. Of the respondents (n = 394), the Internet at home (n = 393). On a scale from 1 (very poor) 62% agreed or strongly agreed that they could visit any to 7 (very good), they assessed their digital competence to dentist for non-urgent care if the waiting time is short. be, on average, 5.9 (n = 391). The standard deviation was 1.1, the median 6 and the range 1–7. Of the respondents (n = 394), 27% searched the Internet for health information at least Sources used for screening once a week, 29% searched once a month, 36% a couple of In choosing a dentist, 15% of respondents often or almost times a year and 8% never. Furthermore, 18% searched for always screened information from relatives, acquaintances information about health services at least once a week, 31% and/or friends (n = 388). Information from these sources was once a month, 45% a couple of times a year and 6% never never or rarely screened by 62%. The corresponding propor- (n = 394). Ten percent of the respondents (n = 393) used health tions for screening information from public service providers’ applications, e.g. MyKanta, at least once a week, 38% once websites were 19% and 58% (n = 388), screening information a month, 45% a couple of times a year and 7% never. Figure 2. t he priority of waiting time among providers’ attributes in citizens’ choices of a dentist for non-urgent care (n = 393). ACTA ODONTOLOgICA SCANDINAvICA 7 Table 3. t he importance of short waiting times for non-urgent dental care by the citizen respondents’ personal information. a a a a a Personal information n Mean Median Std. deviation Minimum Maximum Age   20–29 27 4.0 4 1.3 1 5   30–39 66 4.2 5 1.0 2 5   40–49 101 4.0 4 1.1 1 5   50–59 90 4.2 4 1.1 1 5   60–69 86 4.0 4 1.0 1 5   70– 14 3.4 3 1.2 2 5   t otal 384 4.1 4 1.1 1 5 g ender   Man 47 4.0 4 1.1 2 5   Woman 340 4.1 4 1.1 1 5   Other 3 4.7 5 .6 4 5   t otal 390 4.1 4 1.1 1 5 Education  A 14 3.6 4 1.3 1 5  B 119 4.2 4 1.1 1 5   c 178 4.0 4 1.1 1 5   d 81 4.0 4 1.1 1 5   t otal 392 4.1 4 1.1 1 5 ServProvider   Only pub 210 4.0 4 1.1 1 5   Mainly pub 98 4.1 4 1.1 1 5   Pub and priv 20 4.3 4.5 .9 2 5   Mainly priv 37 4.2 5 1.1 1 5   Only priv 27 4.0 4 1.1 2 5   t otal 392 4.1 4 1.1 1 5 v isits   Regular 255 4.0 4 1.1 1 5   irregular 111 4.2 5 1.1 1 5   t oothache 26 3.8 4 1.4 1 5   t otal 392 4.1 4 1.1 1 5 importance measured using a five-point likert scale (1 = strongly disagree, 2 = disagree, 3 = neither agree nor disagree, 4 = agree, 5 = strongly agree). (A) Elementary or comprehensive school, (B) A vocational education or matriculation examination, (c ) A bachelor’s degree or college-level education, (d) A master’s degree. Pub = Public sector service provider, Priv = Private sector service provider. Quality of signalled waiting times Perceptions of signalling waiting times to citizens Ninety percent of the managers (n = 96) perceived signalling Table 4 presents how the 15 public primary oral healthcare waiting times for non-urgent dental care to citizens on the web- providers signalled waiting times on their websites on 15 sites as useful. Only 41% presumed that the average durations September 2021. of different dental treatment episodes should also be signalled to citizens (n = 97). The managers (n = 92) estimated that, on average, 25% of the citizen respondents knew about waiting time signalling on Managers the websites. The lower quartile was 10%, the median 20% and the upper quartile 35%. Furthermore, they (n = 91) esti- Descriptive statistics mated that, on average, 53% of the citizen respondents con- Ninety-eight of the 159 managers potentially participating in sidered signalling waiting times useful. The lower quartile was the study answered our questionnaire, a response rate of 62%. 30%, the median 55% and the upper quartile 75%. One of the managers had answered the questions but did not provide informed consent to participate in the study, so the number of managers included in the analysis was 97. There also Processing waiting time information was a minimal lack of data as not all the managers answered Twelve percent of the managers (n = 96) answered that the all questions. The number of respondents answering different electronic patient information system processed waiting time questions varied from 91 to 97. indicators. The indicators were processed manually using Sixty percent of the managers (n = 96) had a licentiate either the first or third next available appointment time degree in dentistry, 20% were specialist dentists and 20% according to the answers of 64% of the managers, and 18% had other qualifications, for example, eight were dental answered that estimates by speculation were used. hygienists. As managers, 40% had worked for 5 years or less, Eighty-eight percent of the organizations in which waiting 16% from 6 to 10 years and 44% longer than 10 years (n = 93). times were estimated by speculation had a population base Approximately half worked in organizations with a population of up to 20,000. Seven managers did not know how the base of up to 20,000 and the other half in organizations with indicators were processed. Of these, two managed an orga- a larger population base (n = 95). nization with a population base of up to 20,000. 8 R. SÖDERLUND Table 4. Waiting time indicators signalled on the websites of the 15 public previous studies [42]. Less than one-fifth of the citizen primary oral healthcare providers on 15.9.2021. respondents often or almost always searched for information Provider Waiting time Release date for this decision-making. The citizen respondents did not A About four months no date need to search for information, as they wanted to visit the B 82, 94, 114 days 19 July 2021 dentist they had visited earlier, perhaps based on their pre- c t arget five months no date d 61, 79 24 h May 2021 vious service experiences [12]. Previous studies have also E 104 days 2 August 2021 emphasized patients’ loyalty to their dentists [50]. getting F 1½, 1½, 3, 3, 3½ months Week 22 information from family and friends by word of mouth has g 34 weekdays 1 September 2021 H t wo–three months no date been a standard method of obtaining information in earlier i 75 24 h 1 September 2021 literature [42,44,52,53]. This was also visible in our study, J About six months September 2021 though the respondents used private and public service pro- K About four months 18 June 2021 l t hree months April 2021 viders’ websites a little more. M 67 calendar days August 2021 We agreed with the conclusions of De Rosis et  al. [21]. n 62, 62, 75, 98 24 h no date Also, in Finland, providers signalled waiting times on the O 93 weekdays August 2021 a websites to comply with the law rather than to provide infor- Waiting times signalled by units. mation to citizens. The quality of the signals was low: one-third were imprecise, giving timeframes such as Ninety-five percent of the managers (n = 95) agreed or ‘two-three months’. One-third missed the release date, or the agreed strongly that electronic patient information systems date was not within four months, as specified by law [22]. should automatically process waiting time indicators. The researchers did not easily find this information on the providers’ websites. The fact that public oral healthcare providers had no stra- Discussion tegic goals for signalling may explain the low-quality waiting Our survey analysed the usefulness of signalling waiting time information. Providers did not need to increase their times to citizens on the websites of public primary oral clientele and competition with private and other public pro- healthcare providers in Finland. Using websites to signal wait- viders was minimal. For some citizens, client fees form bar- ing times is effective, as most of the citizen respondents riers to using private services [24,46–48]. Choosing another have access to the Internet and use it to search for health public service provider may be difficult because of poor information. Approximately 60% of the citizen respondents transport connections [24], or it may increase traveling time knew about this signalling, and about 70% presumed that and costs. Based on other studies, public healthcare patients they at least sometimes could use the information. The citizen do not consider freedom of choice as a central matter, espe- respondents considered waiting time a high-priority criterion cially in sparsely populated areas [13,14]. when choosing a dentist for non-urgent care. In practice, they had minimal need to search for any information for decision-making, preferring to visit the dentist they had ear- Practical implications lier visited. Also, the choice possibility when using public services was minor. Though the managers perceived signal- The citizen respondents perceived waiting time signalling on ling waiting times on the websites as useful, the quality of the websites as useful, though the need for waiting time signalled waiting times was low. Approximately one out of information was minor. They could access the Internet at five managers answered that the signalled information was home, and many used it to search for health information. estimated by speculation. The study results indicated that The websites were a proper means to signal waiting times. waiting times were signalled to comply with Finnish legisla- However, the low-quality information was a problem. Every tion rather than to reduce the information asymmetry oral healthcare provider had an electronic patient information between citizens and oral healthcare providers. system, but only about 10% used the system to calculate We derived the theoretical framework of our study from the waiting times. the agency theory [2, 3] and signalling theory [31]. The In these systems, providers have the data required to framework worked well to analyse the usefulness of waiting calculate waiting time indicators [64]. Supplementing the time signalling in the study context. As a result of information systems with proper functionalities would enable the auto- asymmetry between citizens (principals) and oral healthcare matic calculation of waiting times to be published daily on providers (agents), citizens, unlike providers, do not know the websites. The information could be categorized by all the attributes of providers, such as waiting times for access- attributes, such as the dentist, recorded into the systems. ing care, to influence decision-making in choosing a dentist. Different statistical key figures, such as the mean and median To reduce information asymmetry, providers can signal some of waiting time, could be calculated. Providers could get attributes to citizens to achieve the desired outcomes of accurate information on the waiting times of those patients providers, such as increasing the clientele. The content and who received an appointment on the day in question. Of means of signalling should be the ones that citizens consider course, cancellations should be taken into consideration. For useful and can and will use for decision-making. automatic calculations, oral healthcare providers need Waiting time information was a high-priority criterion in national definitions, specifications for electronic patient infor- choosing a dentist for non-urgent care in our study, as in mation systems and instructions for personnel. A dental nurse ACTA ODONTOLOgICA SCANDINAvICA 9 should no longer use worktime to calculate the third next needed to acquire information on rethinking waiting time sig- available appointment time [28, 29], instead, providers should nalling in oral healthcare and its desired goals. use automatic data management. Acknowledgements Limitations and future research The authors thank the Finnish public primary healthcare organizers for enabling the study. In addition, the authors thank the officials of the Our study is not without limitations. With a cross-sectional organizers of public primary healthcare in Southwest Finland for dis- survey, we can never verify any causality. As convenience seminating information of the study to citizens by different media. sampling was used, it decreased the validity and credibility of the study results [62]. The challenge is that the respon- dents taking part in the study may be those who have a Disclosure statement very positive or negative view of the studied issue. It is easier No potential conflict of interest was reported by the author(s). to arouse their attention to participate than to arouse the interest of others. In our citizen study, the method of inform- ing about the survey may also have caused bias in the Funding results; some political decision-makers of the area were informed more personally about the survey than other citi- There was no external funding for the study. zens. The proportions of the citizen respondents knowing of and visiting websites signalling waiting times were probably ORCID higher than with probability sampling. It is also probable that citizens taking part in electronic surveys have better Riitta Söderlund http://orcid.org/0000-0003-3026-8246 digital competence and easier access to the Internet and electronic services than citizens on average. Finally, although we would have used probability sampling, the possibility to Data availability statement generalize the study results to other environments is restricted. The healthcare systems and social and cultural According to the privacy policy, the researcher can process the survey aspects differ remarkably by country. data for the time required for her thesis. During the time, the data will Access to non-urgent dental care within a reasonable time not be transferred outside the University of Turku. 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Journal

Acta Odontologica ScandinavicaTaylor & Francis

Published: Oct 3, 2023

Keywords: Agency theory; citizen; oral healthcare; signalling theory; waiting times

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