Skip to main content

Exploring the general practitioners’ point of view about clinical scores: a qualitative study



Clinical scores help physicians to make clinical decisions, and some are recommended by health authorities for primary care use. As an increasing number of scores are becoming available, there is a need to understand general practitioner expectations for their use in primary care. The aim of this study was to explore general practitioner opinions about using scores in general practice.


This qualitative study, with a grounded theory approach, used focus groups with general practitioners recruited from their own surgeries to obtain verbatim. Two investigators performed verbatim analysis to ensure data triangulation. The verbatim was double-blind labeled for inductive categorization to conceptualize score use in general practice.


Five focus groups were planned, 21 general practitioners from central France participated. Participants appreciated scores for their clinical efficacy but felt that they were difficult to use in primary care. Their opinions revolved around validity, acceptability, and feasibility. Participants have little regard for score validity, they felt many scores are difficult to accept and do not capture contextual and human elements. Participants also felt that scores are unfeasible for primary care use. There are too many, they are hard to find, and either too short or too long. They also felt that scores were complex to administer and took up time for both patient and physician. Many participants felt learned societies should choose appropriate scores.


This study conceptualizes general practitioner opinions about score use in primary care. The participants weighed up score effectiveness with efficiency. For some participants, scores helped make decisions faster, others expressed being disappointed with the lack of patient-centeredness and limited bio-psycho-social approach.

Peer Review reports


Evidence-based medicine (EBM) integrates individual clinical expertise, patient values, and best available evidence from systematic research to make health care decisions [1]. In providing EBM, the general practitioner (GP) is “primarily responsible for providing comprehensive and continuing care” integrating “physical, psychological, social, cultural, and existential factors” [2]. In 2014, it was found that patients consult GPs for an average of 2.6 reasons per consultation [3]. To answer these numerous demands, GPs have to make efficient use of the resources the health system offers to make decisive decisions while in indecisive situations [4].

Clinical scores are tools designed to assist EBM decision-making processes. A score combines relevant clinical or paraclinical items, in a structured manner. The numerical score result reflects the probability of a diagnosis, a prognosis, a symptom, or a disease intensity [5, 6]. A score with strong internal validity, based on the psychometric attributes, reflects its ability to predict an exact result [7]. A score with a strong external validity reflects the replicability and transposability of score criteria [8]. Theoretically, these scores should enable decision-making processes to be standardized, replicable, and explicit, and in so doing, harmonize clinical practice [5].

The number of available scores has increased dramatically in recent years. Specific, online access to scores has increased from 13,500 in 2010 and 25,000 in 2019 [9]. In primary care, clinical scores have been developed for use in geriatrics [10], psychiatry [11, 12], cardiology [13] or surgery [14] and some current guidelines support their use [15], despite many not being validated in primary care [16]. Although, GPs are increasingly using scores, one study reported an increase from 35.2% in 2003 to 75% in 2010 [17, 18]; yet, many scores may be unfeasible for use in general practice and GPs are unaware of the variety of scores available. One report found GPs are aware of at least six scores but only use four [19]. This may be due to lack of knowledge, training or time, doubts towards their usefulness, access or remuneration issues, or a negative impact on the patient-practitioner relationship and poor patient acceptability [18, 20].

Despite this increased interest for using scores in primary care, little research about score feasibility in primary care is available. This is important because designing scores for primary care use should consider the specificities of the primary care setting and GP expectations for using scores in their everyday practice.

The aim of this study was to explore the GPs’ point of view regarding their use of clinical scores in their daily practice.


Study design

This qualitative study, with a grounded theory approach explored GP opinions about using clinical scores, based on previous experience. This method was chosen because it ensures that participants verbalize and present their opinions freely [21, 22]. Using a grounded theory approach, enabled investigators to build a model of the GP expectations for suitable scores.


GPs practicing in the Loire Region, France, were recruited according to predefined criteria elicited from a preliminary literature review [23] including age, gender, practice type (alone or within a group), setting (urban, suburban, or rural), number of appointments per hour, medical conference participation or continuing medical education, and complementary activities. The investigators called potential GPs to organize a focus group and then recruited additional GPs in the surrounding area using a snowball approach. Recruitment was completed throughout the research project using purposive theoretical sampling, as the emerging theory evolved. The sample size was closed after a focus group with few news ideas and a final focus group of confirmation which did not add more data, according to the sufficiency data principle [24].

Data collection

Focus groups were planned to collect the data, which were conducted in participating GP surgeries. Focus groups were chosen to enhance the dynamic exchange between GPs about their practice habits [24]. MP, a male GP and specialist in qualitative research, and RP, a male medical student who had received qualitative research training, conducted all the focus groups. There was no relationship between participants and the researchers prior to study commencement. Prior to the focus groups, the participants received information about the research and the researchers and provided written informed consent. Furthermore, the researchers explained their interest in the research topic at the start of the focus group. A semi-structured interview framework was developed to direct focus group discussions with open-ended questions that encouraged discussion (Additional file 1). This initial framework was progressively enriched with significant elements elicited from previous focus groups, according to an inductive analysis process. Sometimes, discussions were enhanced with examples of tests recommended for use in primary care, with a variety of multi-topic questionnaires, and shorter (CRB65) and longer tests (FINE) [25,26,27]. Field notes were made during the focus groups. Each focus group was audio recorded, fully transcribed, and anonymized. Participants could request to see the transcripts. Only participants and the two interviewing researchers were present during the focus groups.

Data analysis

At the end of each focus group the verbatim was blinded. Two experienced investigators separately performed the analysis to ensure analyst triangulation using a coding tree. The investigators labelled the verbatim in a double-blind fashion and individual labels were then combined into a single label through discussion and arbitration with a third investigator whenever needed. Labelled items would then be categorized in an inductive way using the same double-blind and arbitration process. QSR NVivo11® software was used for data collection and analysis. Participants received RP’s thesis and were able to provide feedback on the results.


Between August 2017 and June 2018, five focus groups were planned but data saturation was achieved after the fourth focus group. In all, 21 GPs participated, no GPs refused to participate or dropped out. The focus groups lasted for an average of 60 min. The focus groups and participant characteristics are described in Table 1 and Fig. 1. We found that opinions expressed regarding clinical scores revolved around the three major safety and quality characteristics of an intervention; validity, acceptability, and feasibility [28].

Table 1 Participant and focus group characteristics
Fig. 1
figure 1

Particularities of medical practice

GPs have little regard for score validity

Score popularity prevails over scientific validity

GPs reported favoring scores more for their popularity in the medical community than for their validity: “I have been using it since I was a medical student and I never really thought twice about it”. Some GPs assumed that the fact that they are using a score gives credit to their practice: “I found that it puts things in order on paper”.

Scores are more distrusted than trusted

GPs criticized some scores for not being designed for outpatient practice: “it is unusable; it’s more of an emergency department thing”. Also, they doubted the reliability of their own interpretation of score results: “I think that we can underestimate or overestimate score item values while actually using it”. The GPs also questioned the validity of a given score for subjective symptoms, such as in depression: “The HAMILTON scale is up to the interviewer’s estimation and not the patient’s. You’re not going to ask the patient ‘have you ever, rarely, or never’”. “It’s up to you to decide”. “I found it difficult to evaluate this”. It is hard to limit a symptom to a number without losing all its nuances: “The score item doesn’t match with the information you have in the first place. Then you end up mixing things that have nothing to do with one another in the same clinical score”. GPs also highlighted the lack of background information captured with a score. GPs know their patients’ personal background, which is difficult to quantify; “I especially need the context”. GPs reported “losing pieces of information” with a number alone. They never have “a blind trust in clinical scores”, “if elements are lacking, I’m going to consider it as invalid and then I cannot rely on it to make a decision”.

GPs report many scores are difficult to accept

Clinical scores are robotic, but general practice is a human science

For some practitioners, merely the thought of using a clinical score was unacceptable: The very word “score” tends to get on my nerves”. The idea of replacing a human relationship with pre-defined interactions by an algorithm was unacceptable for them: “This is the antithesis of general practice”, “medicine isn’t this; it’s a human science. It’s about our free will, our thoughts, our sensitivity and our knowledge, or else we just turn into computers”.

GPs were disappointed with the rigidity of score questions: “in all those questionnaires, the answers are a bit artificial, because our own attitude is artificial. It’s not the practitioner speaking anymore but a person reading a pre-prepared text with words that may not have used”. The GPs felt uncomfortable with pre-defined questions that replace their own routine: “it totally rips out the dialogue, patients feel like they are talking to a robot”, “the patient-practitioner relationship turns into mathematics”. Lastly, they were shocked by the “robotic” sounding names for the clinical scores: “The fact that someone decided to call a score for depressed patients “PHQ9”, I have no words”.

Patients expect a good listener, scores expect a checked box

“A depressed person needs to be listened to, not asked questions”. When listening to a patient, manner appears to be crucial for GPs: “you look at the person, you don’t check boxes”. They dreaded going from question to question without adapting to the patient answers: “we are asking questions, yes, but in an order that goes well with the consultation flow, and not a thing recited monotonously, this question then this one, and this one”, “you adapt your speech to the patient!”. GPs didn’t want “to be a lie detector” or be perceived as such. “If you have to ask trick questions… Well, I don’t want to do that”.

The expense of administering a score in primary care is an issue

Clinical scores take time, and time is money

GPs were uncomfortable charging specifically for performing a clinical score: “I didn’t even know that we could do that”, “I just don’t know how to bill for it” and “to search for the billing codes, this annoys me”. The participants debated charging for time spent performing a score: “even though I did it, I’m not going to ask for more because of that” and “If you are at a point where you tell yourself: well I spent half an hour so if I [also] bill that score I’m going to earn more”, on the other hand “it is still a small reward when you [go beyond the level of duty] for 45 min…” and “this is our bread and butter! I don’t do it to be famous!” Apart from this notion of charging for time spent, some participants reported performing a score for remuneration: “The value of the test is the money!” and “honestly this is more for the money than for the patients since it is questions that we already ask ourselves”. However, GPs feared that remuneration would generate too many inspections: “one is bound to be questioned by the social security office. It’s better to keep track”.

Scores are unfeasible for use in primary care

GPs can no longer see the wood for the trees

In general, the participating GPs could only recall a few clinical scores: “I know five that I can quote”. They also argued that the names given to clinical scores makes them hard to remember and claimed that: “it would be easier to find it back on the internet if they didn’t have those silly names”. The GPs were also exasperated things were changing too fast: “it keeps changing!”, “they are proliferating” and “I already feel lost when it comes to clinical scores because there is always a new one”. Some were expecting the learned society to sort it out: “I look at it a little bit closer now that there are the recommendations”.

A clinical score is like a GPS: it’s when you need it that you forget to bring it

GPs said they forgot about scores that they don’t use regularly: “if we don’t use them, then we forget about them” and “there were 4 or 5 that I managed to remember and that I used frequently thus they remained in my practice”. And yet it is in rarer pathologies that the help of a tool was more needed: “With rarer pathologies, clinical scores can, maybe, be more interesting. But I can’t quote any score for a rare pathology”.

When scores are short, they are inadequate but when they are long, they are useless!

GPs preferred using short scores: “it has to be 3 or 4 questions long”, “yes or no questions, closed questions…”, “rapidly interpretative” with simple questions: “we are doctors, so it is understandable [for us], but there are some sentences that are incomprehensible [for the patient]”. However, they admitted that shorter scores [CRB65] don’t capture contextual elements; “there is also the family background”. Yet more complete scores seemed impractical to them: “adding the context is going to give you another which is going to be more complete but unusable” and “the ideal score is one that is easy to use” and not those “where we don’t have the results in general practice” such as “blood gases”.

Scores can be more efficient to administer if someone else fills them out

Clinical scores are not seen as a priority: “I’d rather spend more time doing other things”. For those who use scores, they organized themselves specifically to have time to complete them: “I make them come just for that”, “it’s an appointment, I book them at a specific time”.

Some practitioners suggested that patients complete a self-administered questionnaire to have the patient face his own responsibility: “this way they can look in the mirror, and that can make them realize a few things”. They found that this saved time: “it also allows me to defer a consultation, not to overload one that is already [long]”. However, they debated which was the best way to make self-administered questionnaires acceptable: “you either give it to everyone in the waiting room as you used to do with alcohol, or you don’t, otherwise it’s a little bit like appearance discrimination”. Targeted screenings “such as the blood pressure self-measurements” were also suggested. Others considered developing e-health as a solution: “On [an app] you would have a form, a kind of questionnaire, for new patients to fill out”. Yet the doctors wondered how the patient would react: “mostly they are not going to get it”, being afraid that patients “end up alone [faced with] all those questions”. They also felt that patient implication in this type of score which is confirmed by a participant who had implemented self-questionnaires: “I have a less than 1% feedback”. Some practitioners delegated scores to other health professionals: “I prefer to delegate to someone else”, “I save time, I don’t do it [myself]”, “I send them to the specialized nurse”, “you give them to the social worker”.

GPs believe scores are relevant in some situations

Clinical scores are to doctors what Morse code is to sailors

Clinical scores were considered by some practitioners as a communication tool between professionals: “it’s difficult to relay written information”, the point was “to have a standardized measure, numbered, something that can be understood at the other end of the line”. GPs used clinical scores as a simple tool to give information to the patient in a split decision situation: “he didn’t make a decision, it was the patient that had to make it, so we showed him his score results and there you go”. Other practitioners saw scores as a way to tackle delicate issues: “the aim is to open the discussion on questions that we might not ask”, including through self-administered questionnaires; “they fill them out, then if they end up with the result: “big problems” maybe it’s going to push them towards their GP one day”.

Young doctors trust clinical scores while experienced doctors trust clinical judgement

GPs criticized clinical scores for not considering the context, which younger practitioners found stressful: “you’re already very organ-centered [when coming out of medical school], and yet you put scores on top of this”. Some GPs tended to use scores that they recently discovered: “you have a new grid to fill out, you’re happy, you add this in your professional credentials”. For others, scores can fall into oblivion: “I did none this year, I forgot about it”, “and then in practice, time flies, you tend to smooth your [practice] out and reproduce the old patterns”. Scores were progressively included in consultations without being formally implemented: “you start to know the questions so well that you’re using them during your consultation without putting any result number at the end”. Practitioners relied on their own experience rather than scores alone: “perception, remains the best thing for those cases”, “in the decision-making process we rely on our clinical judgement, and not a score, which is not going to tell us what to do” and “we have a certain semiology in our head, a much-vaunted «sense of alarm», clinical experience, and we don’t need to check boxes or to calculate”. This feeling seemed to grow over time: “I asked myself, in the end, what do we want from the tests? What is their use? And then I think I realized, with time, that I didn’t really need them because they weren’t of much use”.

No treatment, no test

GPs used scores that “changed something in the end”: “If we already know what needs to be done then we don’t do the test” and “if we take a memory loss problem, either scoring or not, the progression will be what it is, and the scales won’t change a thing”. GPs expected a score to add value, “bring something more to the table, an added value in comparison with daily practice”. The GPs expected a score to improve decision-making “in COPD or tonsillitis, scores help me decide whether or not to prescribe an antibiotic”; improve their care “It needs to help us with the diagnosis, or administer a treatment”, or provide patient information “It needs to provide us with information to convince the patient!”.

Clinical scores give way to catastrophism

Faced with doubt, practitioners did not feel clinical scores were reassuring: “I don’t believe they would reassure me that much”, “the test will still leave me alone with my uncertainty”, and “even if there was a reassuring test, I would still call saying that I’ve done the test and it looks reassuring, but I still don’t feel good about it”. Instead, an alarming score result led to more screening tests: “if the result number is really high, I tell myself that I’m missing something”. In the end, for the GP, “from a legal point of view it can protect us” but for the patient, “you’d just say that you’re sorry he is dead but he got 1 on the test score, it wouldn’t change a thing”.

Clinical scores are to monitoring what a dermascope is to a melanoma

Participating GPs used scores to monitor their patients: “I sometimes found it useful for monitoring because people would tell you that things are not getting better, but then when you do the test a second time you figure out that there has been an improvement”. They stressed reproducibility: “the scale needs to be reproducible” and “allow you to measure progression”, in terms of test-retests reliability. The value is increased when several medical professionals are monitoring the same patient: “it is not always the same person that sees the patient in the hospital”.

No pathway specialization without research, no research without clinical scores

GPs thought that research in primary care needed clinical scores: “for someone who’s going to study something, then these tests have significance for evaluations”. The tool brought forth necessary numbered data: “it can be biostatistics. It’s good because it can give you pointers on population health conditions and their practices”. This positive side was well perceived for general practice as a discipline, but less for their own practice: “it’s true that if we were to perform research in general medicine, clinical scores won’t help us with clinical judgement but may boost some [health] indicators”. Nevertheless, GPs did not feel involved in this process: “If it’s for research purposes then we are not directly in it”.


This study explored GPs’ opinion about their use of scores in their current practice. GPs expressed often seeing little value in using clinical scores. They tended to value relevance and feasibility over scientific validity but felt that scores didn’t take into account clinical circumstances and patient preferences, which are essential elements of EBM.

The findings in this study challenge using scores to provide EBM in general practice. Although GPs appreciated that scores have psychometric efficacy for use as good communication tools, or are a reference point for current scientific data, they questioned their efficiency in primary care. GPs clearly expressed concern about excluding patient preferences, using a robotic-like approach or box checking to obtain background context. A recent review suggested that a score could have some positive effect on process outcomes but their results may be context specific [29]. These elements are nonetheless necessary to the Engel’s model of bio-psycho-social approach [30]. The practitioner must therefore deliberate between the score psychometric efficacy and efficiency, before deciding to use it. The findings from this study conceptualize the efficacy-efficiency balance to guide which clinical scores are suitable for use in general practice (Fig. 2).

Fig. 2
figure 2

Conceptualization of clinical score properties for decision-making in primary care settings

Feasibility and relevance reflect the efficiency-efficacy balance

Efficient scores are those that are feasible and easily administered and influence patient management, which may encourage GPs to adopt scores in general practice. Currently, two scores meet these needs: the Ottawa score which confirms the need for an X-ray in only three questions for a twisted ankle, and the BITS test which points to suicidal risks for a teenager with four questions [31, 32]. Both scores have been developed by primary care practitioners which enhance their relevance. In contrast, the CHA2DS2VASC score to evaluate the need for an anti-coagulant treatment in atrial fibrillation, is also a short score [33]. Yet, the CHA2DS2VASC is seen as being “for hospital specialists” and inefficient for primary care: “in the end, the patient will still always end up at the cardiologist”. This perception was reiterated in a recent systematic review confirming that relatively few potentially relevant tools for primary care have undergone impact analysis, and their implementation has been restricted to a limited number of clinical domains, mainly musculoskeletal, cardiovascular and respiratory [34]. Also, even tools designed for primary care have not undergone impact analysis, making it difficult to obtain a significant increase in sensitivity or specificity in treatment decision-making between score-assisted and non-assisted clinical skills.

Validity, affordability, and acceptability

GPs were less concerned with the validity of the score than with the appropriateness of the test in their practice. Some GPs reworded validated tests to administer the test faster or reduce perceived patient discomfort. However, doing this has been shown to decrease their quality [35, 36]. Furthermore, participating GPs wanted to maintain human relationships and not rely on a standardized test, which has also been supported by the literature [17]. GPs are encouraged to use the mini mental state examination (MMS) for early diagnosis of dementia even though the inter-reliability is limited. GPs can correctly identify individuals with cognitive impairment, even if they scored their patients lower than the Alzheimer specialists scored.

Despite score use depending upon GP remuneration, it is considered encouraging that scores are used at a European Level [37, 38]. In France, the MMS or the Hamilton scale are among the top three most commonly used scores, and GPs can charge up to three times the standard price.

Professional experience reduces the interest given to clinical scores

We found mixed results concerning the value of scores with increased experience. We found more experienced GPs seemed less inclined to use scores, especially in situations they believe they have mastered, relying more on their gut feeling [39]. These results corroborate other work about GP expectations for scores to improve the decision-making process (diagnostic, complementary explorations, therapeutics) [40]. Other practitioners feel scores are valuable in unusual situations in which they are uncomfortable. However, GPs still admit that for those rare occasions they are often unaware of an appropriate score.

Participants thought that clinical scores could be helpful for the decision-making process among practitioners lacking experience such as newly qualified doctors or medical students: “it’s interesting in training, it’s true that it can help you ask yourself the right questions, remember the priorities”.

What is the role of clinical scores in general practice?

The GPs mentioned using scores to justify making medical decisions, particularly when healthcare professionals disagreed about the state of a patient in their care. They argued that although the psychometric features may be imperfect, were they better than the GP’s? They expect “irrefutable proof that scores improve the quality of healthcare”. Yet, a 2002 study about the systematic use of Numeric Pain Rating Scale in primary care concluded that scales did not affect chronic pain relief [41]. GPs were afraid of making mistakes by just relying on scores. We also found opinions similar to a recent National commission for data protection report about artificial intelligence that developing “algorithmic systems eroded individual vigilance” or also that “developing these technologies can affect human identity and dignity, its liberty and its responsibility” [42].

Study limitations

Although this study is limited by the inherent qualitative design, it is strengthened with a grounded theory approach and focus groups. This option was chosen instead of individual interviews to stimulate the emergence of a wide range of opinions from the GP community and pool their current practices. Despite this, social desirability bias may have occurred if some practitioners did not report their practice truthfully through fear of peer judgment. To minimalize this social desirability bias, the focus groups were chosen from nearby surgeries, among practitioners who already knew each other. By knowing each other well, the GPs also know each other’s practice and so we expected they would have been less likely to be untruthful. Furthermore, in our attempt to limit social desirability, we may have induced the possibility of “group think”. However, the sample was heterogenous and varied in terms of setting and age. We believe that this was sufficient to limit this effect. This resulted in free and convivial discussion. The level of comfort was so much so that unexpected opinions arose, indicating that all participants felt sufficiently at ease to speak freely.

One example, we recorded was a conversation about a conspiracy theory centered on unauthorized use of health data gathered through clinical scores to benefit big pharmaceutical companies, government, or assurance companies: “it’s information, big data, it’s a society issue, not a medical one. The sprawling society is sucking up data from everywhere…from our smartphones. You have to be really careful about this”. These unexpected results echo current societal preoccupations which led to a National commission for data protection report in December 2017 [42]. Two main principles emerged: the first stipulating that the algorithms needed to serve the using doctors, and the other stating the importance of ensuring algorithms do not dictate clinical decisions.

We chose not to restrict the list of scores to obtain an overall point of view from the GPs, independent of their individual situation and score experience. This choice to analyze focus group data using the grounded theory method gave us the opportunity to conceptualize general score use in primary care. In contrast, other studies described GP use of a restricted number of scores, which tightened the exploratory fields [17, 21]. These studies used questionnaires or individual interviews with thematic analyses, or literature review.

The COREQ criteria [43] for grounded theorizing research were respected at each stage.


The imperious necessity to sort out clinical scores

Participants told us that they rarely checked the validity level for scores they used, instead reproduced current practices within their professional network. This means they rely on learned societies to select and recommend relevant scores. Learned societies selecting scores has been previously raised and is influencing the future of score use in general practice. Having too many scores makes it difficult to find the most appropriate score for the situation which leads GPs to give up using them [44]. Clinical scores can also be selected from primary care research, such as an inventory conduced in 2015 for cardio-vascular pathologies which found 10 were validated in general medicine among the 26 clinical scores inventoried [7].

Can e-health rescue efficiency?

To facilitate clinical score access, participating GPs suggested some solutions. Electronic tools such as medical software, smartphone apps or websites could be developed. But electronic scores should be well organized and easy to access. Our results also echo previous research suggesting practitioners need to be trained to use scores in everyday practice [45]. Other propositions include self-administered questionnaires that patients complete when making online appointments. These questionnaires could then provide GPs with targeted health data before the appointment with would give them time to discuss health matters on a deeper level. A study suggested also using the waiting room to collect data through self-administered questionnaires [46].


The efficacy of clinical scores still needs to be optimized for primary care use, but their efficiency will always be an issue even though new technologies may solve some issues. Thus, using clinical scores in current primary care remains a challenge as it relies on an efficiency-efficacy scale.

Availability of data and materials

The full dataset is available from the corresponding author.



Evidence-based medicine


General practitioner


Mini mental state examination


  1. Sackett DL. Evidence-based medicine. Semin Perinatol. 1997;21(1):3–5.

    Article  CAS  PubMed  Google Scholar 

  2. Wonca E, Oms BE. La définition européenne de la médecine générale - médecine de famille. 2002. p. 52.

    Google Scholar 

  3. Letrilliart L, Supper I, Schuers M, Darmon D, Boulet P, Favre M, et al. ECOGEN: étude des Éléments de la COnsultation en médecine GENérale. Exercer, Rev Fran Méd Gén. 2014;25:148–57.

    Google Scholar 

  4. Kiderman A, Ilan U, Gur I, Bdolah-Abram T, Brezis M. Unexplained complaints in primary care: evidence of action bias. J Fam Pract. 2013;62(8):408-13.

  5. Beattie P, Nelson R. Clinical prediction rules: what are they and what do they tell us? Aust J Physiother. 2006;52(3):157–63.

    Article  PubMed  Google Scholar 

  6. Cuchera M. Lecture critique et interprétation des résultats des essais cliniques pour la pratique médicale. Med Sci Publ. 2004.

  7. Junod AF. De quelques scores en cardiologie. Revue Médicale Suisse. Disponible sur: [cité 27 janv 2019].

  8. Guessous I, Durieux-Paillard S. Validation des scores cliniques : notions théoriques et pratiques de base. Revue Médicale Suisse. Disponible sur: [cité 1 nov 2018].

  9. Medical Algorithms | Healthcare Decision Support | Disponible sur: [cité 27 janv 2019].

  10. Zulfiqar AA, de Longuemarre AT. Codex et MMSE: que choisir? Gériatr Psychol Neuropsychiatr Vieillissement. 2019;17(3):279–89.

    Google Scholar 

  11. Barr PJ, Forcino RC, Dannenberg MD, Mishra M, Turner E, Zisman-Ilani Y, et al. Healthcare Options for People Experiencing Depression (HOPE* D): the development and pilot testing of an encounter-based decision aid for use in primary care. BMJ Open. 2019;9(4):e025375.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Mason R, Doherty K, Eccleston C, Annear M, Lo A, Tierney L, et al. General practitioners attitude and confidence scale for dementia (GPACS-D): confirmatory factor analysis and comparative subscale scores among GPs and supervisors. BMC Fam Pract. 2019;20(1):1–8.

    Article  Google Scholar 

  13. Harskamp RE, Laeven SC, Himmelreich JC, Lucassen WA, van Weert HC. Chest pain in general practice: a systematic review of prediction rules. BMJ Open. 2019;9(2):e027081.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Norg RJ, Portegijs PJ, van de Beek K, van Schayck O, Knottnerus JA. A decision aid for GPs for the treatment of elderly male patients with lower urinary tract symptoms (LUTS). Fam Pract. 2006;23(6):666–73.

    Article  PubMed  Google Scholar 

  15. Synthèse, guide parcours de soins fibrillation atriale. Disponible sur: [cité 27 janv 2019].

  16. Robleda A. Recensement et validité des scores cliniques diagnostics dans le pathologies cardiovasculaires en soins primaires. [Paris 7]: Faculté de Gédecine Générale Denis Diderot; 2015 Disponible sur: [cité 11 oct 2016].

  17. Sarazin M, Chiappe SG, Kasprzyk M, Mismetti P, Lasserre A. A survey of French general practitioners and a qualitative study on their use and assessment of predictive clinical scores. Int J Gen Med. 2013;6:419–26.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Gautier A. Baromètre santé, médecins-pharmaciens 2003. Saint-Denis: Éditions INPES; 2007.

  19. Cario C. Tests et échelles en médecine générale ambulatoire: freins des généralistes à leur utilisation [Thèse d’exercice]. France: Université de Poitiers. UFR de médecine et de pharmacie; 2010.

    Google Scholar 

  20. Di Patrizio P, Blanchet E, Perret-Guillaume C, Benetos A. What use general practitioners do they tests and scales referred to geriatric? Gériatr Psychol Neuropsychiatr Vieillissement. 2013;11(1):21–31.

    Google Scholar 

  21. Glaser BG, Strauss AL. The discovery of grounded theory: strategies for qualitative research. 4. paperback printing. New Brunswick: Aldine; 1967.

    Google Scholar 

  22. Paillé P. L’analyse par théorisation ancrée. Cahiers Recherche Sociol. 1994;23:147.

    Google Scholar 

  23. CNOM. La démographie médicale en région centre. Situation en 2013.pdf. Disponible sur:

  24. Aubin-Auger I, Mercier A, Baumann L, Lehr-Drylewicz AM, Imbert P. Introduction à la recherche qualitative. exercer. 2008;84:142-5.

  25. Chidiac C. Antibiothérapie par voie générale dans les infections respiratoires basses de l’adulte. Pneumonie aiguë communautaire. Exacerbations de bronchopneumopathie chronique obstructive. AFSSAPS et SPILF - Médecine Maladies Infect. 2011;41(5):221–8.

    Article  CAS  Google Scholar 

  26. HAS. Outil d’aide au repérage précoce et intervention brève : alcool, cannabis, tabac chez l’adulte. 2014 Disponible sur: [cité 18 févr 2019].

  27. Fine MJ, Auble TE, Yealy DM, Hanusa BH, Weissfeld LA, Singer DE, et al. A prediction rule to identify low-risk patients with community-acquired pneumonia. N Engl J Med. 1997;336(4):243–50.

    Article  CAS  PubMed  Google Scholar 

  28. HAS. Fiche technique: suivi d’indicateurs de qualité et de sécurité des soins. 2017 Disponible sur: [cité 18 févr 2019].

  29. Sanders SL, Rathbone J, Bell KJL, Glasziou PP, Doust JA. Systematic review of the effects of care provided with and without diagnostic clinical prediction rules. Diagn Progn Res. 2017;1(1):13.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Engel GL. The clinical application of the biopsychosocial model. Am J Psychiatry. 1980;137(5):535–44.

    Article  CAS  PubMed  Google Scholar 

  31. Binder P, Heintz AL, Servant C, Roux MT, Robin S, Gicquel L, et al. Screening for adolescent suicidality in primary care: the bullying-insomnia-tobacco-stress test. A population-based pilot study. Early Interv Psychiatry. 2018;12(4):637–44.

    Article  PubMed  Google Scholar 

  32. Stiell IG, Greenberg GH, McKnight RD, Nair RC, McDowell I, Worthington JR. A study to develop clinical decision rules for the use of radiography in acute ankle injuries. Ann Emerg Med avr. 1992;21(4):384–90.

    Article  CAS  Google Scholar 

  33. Gage BF, Waterman AD, Shannon W, Boechler M, Rich MW, Radford MJ. Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation. JAMA. 2001;285(22):2864–70.

    Article  CAS  PubMed  Google Scholar 

  34. Wallace E, Uijen MJM, Clyne B, Zarabzadeh A, Keogh C, Galvin R, et al. Impact analysis studies of clinical prediction rules relevant to primary care: a systematic review. BMJ Open. 2016;6(3):e009957.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Williams EC, Achtmeyer CE, Rittmueller SE, Lapham GT, Chavez LJ, Thomas RM, et al. Factors underlying quality problems with alcohol screening in routine care. Addict Sci Clin Pract. Springer; 2013. vol. 8 p. 1‑1. Article number: A85.

  36. Bradley KA, Lapham GT, Hawkins EJ, Achtmeyer CE, Williams EC, Thomas RM, et al. Quality concerns with routine alcohol screening in VA clinical settings. J Gen Intern Med. 2011;26(3):299–306.

    Article  PubMed  Google Scholar 

  37. Müller-Riemenschneider F, Holmberg C, Rieckmann N, Kliems H, Rufer V, Müller-Nordhorn J, et al. Barriers to routine risk-score use for healthy primary care patients: survey and qualitative study. Arch Intern Med. 2010;170(8):719–24.

    Article  PubMed  Google Scholar 

  38. Sarazin M, Chiappe SG, Kasprzyk M, Mismetti P, Lasserre A. A survey of French general practitioners and a qualitative study on their use and assessment of predictive clinical scores. Int J Gen Med. 2013;6:419.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Stolper E, van Bokhoven M, Houben P, Van Royen P, van de Wiel M, van der Weijden T, et al. The diagnostic role of gut feelings in general practice A focus group study of the concept and its determinants. BMC Fam Pract. 2009;10(1):17.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Bourlet P. Dans quelles situations particulières est-il pertinent d’utiliser les échelles de dépression en médecine générale? [Thèse d’exercice]. France: Université de Versailles-Saint-Quentin-en-Yvelines; 2013.

    Google Scholar 

  41. Pouchain D. Echelles d’évaluation de la douleur: leur utilisation en ambulatoire a-t-elle un impact sur le soulagement de la douleur chronique ? Rev PratMed Gen. 2002;16(585):1299–303.

    Google Scholar 

  42. CNIL. Comment permettre À l’homme de garder la main ? 2017.

    Google Scholar 

  43. Charmaz K. Premises, principles, and practices in qualitative research: revisiting the foundations. Qual Health Res. 2004;14(7):976–93.

    Article  PubMed  Google Scholar 

  44. Marchand M. Pertinence de l’utilisation de l’équation de risque SCORE dans l’évaluation du risque cardiovasculaire global des patients en médecine générale [Thèse d’exercice]. France: Université de Reims Champagne-Ardenne; 2016.

    Google Scholar 

  45. Wells S, Furness S, Rafter N, Horn E, Whittaker R, Stewart A, et al. Integrated electronic decision support increases cardiovascular disease risk assessment four fold in routine primary care practice. Eur J Cardiovasc Prev Rehabil avr. 2008;15(2):173–8.

    Article  Google Scholar 

  46. Audran F. Intérêt de l’utilisation d’auto-questionnaires en salle d’attente de médecine générale: revue de littérature [Thèse d’exercice]. France: Université d'Angers; 2016.

Download references


Editing assistance and critical revision were provided by Charlotte Wright and Amy Whereat, Speak the Speech Consulting. This article is supported by the French network of University Hospitals HUGO (‘Hôpitaux Universitaires du Grand Ouest’).


No funding support was received for this study.

Author information

Authors and Affiliations



Study design and concept, M.P., R.P., J.P.L.; data collection, M.P., R.P.; writing—original draft preparation, M.P., R.P.; writing—review and editing, L.D., J.P.L.; supervision, J.P.L. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Maxime Pautrat.

Ethics declarations

Ethics approval and consent to participate

Each participant was given an information letter and signed a consent form. The study was approved by the “ERERC” (Espace de Réflexion Ethique Région Centre) review board (number 2017051) and was registered at the CNIL (Commision nationale informatique et liberté) n°2017096. All audio recordings were destroyed after transcription.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pautrat, M., Palluau, R., Druilhe, L. et al. Exploring the general practitioners’ point of view about clinical scores: a qualitative study. Diagn Progn Res 7, 12 (2023).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI:


  • Decision aids
  • Psychometrics
  • Primary health care
  • Qualitative research