Mora et al. BMC Primary Care (2023) 24:9 BMC Primary Care https://doi.org/10.1186/s12875-022-01935-0 RESEARCH Open Access “Decline and uneven recovery from 7 common long‑term conditions managed in the Catalan primary care after two pandemic years: an observational retrospective population‑based study using primary care electronic health records” Núria Mora1, Francesc Fina1, Leonardo Méndez‑Boo1, Roser Cantenys1, Mència Benítez1,2, Nemesio Moreno1, Elisabet Balló1, Eduardo Hermosilla1,3, Mireia Fàbregas1, Carolina Guiriguet1,2,4, Xavier Cos5,6,7,8, Sara Rodoreda5, Ariadna Mas5, Yolanda Lejardi5, Ermengol Coma1* and Manuel Medina1 Abstract Background The incidence of chronic diseases during the COVID-19 pandemic has drastically been reduced world‑ wide due to disruptions in healthcare systems. The aim of our study is to analyse the trends in the incidence of 7 com‑ monly managed primary care chronic diseases during the last 2 years of the COVID-19 pandemic in Catalonia. Methods We performed an observational retrospective population-based study using data from primary care elec‑ tronic health records from January 2018 to August 2022 (5.1 million people older than 14 years). We divided the study period into two: a pre-pandemic period (before 14 March 2020) and a pandemic period. We performed a segmented regression analysis of daily incidence rates per 100,000 inhabitants of 7 chronic diseases: type 2 diabetes mellitus (T2DM), asthma, chronic obstructive pulmonary disease (COPD), ischemic heart disease (IHD), heart failure (HF), hyper‑ tension and hypercholesterolemia. In addition, we compared annual incidence between pandemic years (2020, 2021 and 2022) and 2019. Associated incidence rate ratios (IRR) were also calculated. Finally, we estimated the number of expected diagnoses during the pandemic period using data from 2019 and we compared it with the observed data. Results We analysed 740,820 new chronic diseases’ diagnoses. Daily incidence rates of all 7 chronic diseases were drastically interrupted on 14 March 2020, and a general upward trend was observed during the following months. Reductions in 2020 were around 30% for all conditions except COPD which had greater reductions (IRR: 0.58 [95% CI: 0.57 to 0.6]) and HF with lesser drops (IRR: 0.86 [95% CI: 0.84 to 0.88]). Some of the chronic conditions have returned to pre-pandemic diagnosis levels, except asthma, COPD and IHD. The return to pre-pandemic diagnosis levels compen‑ sated for the drops in 2020 for T2DM and HF, but not for hypertension which presented an incomplete recovery. We also observed an excess of hypercholesterolemia diagnoses of 8.5% (95%CI: 1.81% to 16.15%). *Correspondence: Ermengol Coma ecomaredon@gencat.cat Full list of author information is available at the end of the article © The Author(s) 2023. 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The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​ mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Mora et al. BMC Primary Care (2023) 24:9 Page 2 of 11 Conclusions Although primary care has recovered the pre-pandemic diagnosis levels for some chronic diseases, there are still missing diagnoses of asthma, COPD and IHD that should be addressed. Keywords COVID-19, Electronic health records, Chronic diseases, Primary care, Incidence Background drops in the early days of the pandemic have resulted in The COVID-19 pandemic and the public health meas- prolonged underdiagnoses after two years. ures implemented to contain the spread of the SARS- The aim of our study is to analyse the trends of regis- CoV-2 virus have negatively affected all levels of health tered incidences of several common chronic diseases systems around the world [1–4]. Besides the direct effects managed in the Catalan primary care through the anal- of COVID-19 related illnesses, several studies have ysis of data from primary care electronic health records described disruption in the healthcare of non-COVID (EHR), after more than 2 years since the beginning of the patients which included the suspension of screening COVID-19 pandemic. In addition, we aim to quantify if programmes or some diagnostic procedures, the reduc- expected drops in 2020 were compensated during the tion of prevention, treatment and control of patients with second year of the pandemic and if the results differed chronic conditions; and a decline in the number of new depending on long-term conditions or sociodemographic non-COVID diagnoses, among others [2, 3, 5–13]. characteristics. The reduction of non-COVID diagnoses has been described in several countries, for both acute and chronic Methods disease [7]. But unlike infectious diseases [14, 15], the Design and data source drop of chronic disease diagnoses does not usually imply We performed an observational retrospective popula- a reduction of the real incidence, but rather a reduction tion-based study using data from the primary care elec- of detected cases, suggesting the incidence of a large tronic health records (EHR) of the Institut Català de la number of undetected conditions, untreated diseases Salut (Catalan Institute of Health; or ICS, its Catalan ini- and hence potentially increased long-term morbidity tials). ICS, the main primary care provider in Catalonia and mortality [2, 3, 6, 7, 16, 17]. For instance, in a study (Spain), manages around 75% of all primary care prac- performed in Catalonia central area in 2020, the reduc- tices in the Catalan public health system and gives cover- tions of new diagnoses accounted for 31%, with greater age to approximately 5.8 million people. Its demographic drops during the lockdown in Spain (March—June 2020) is highly representative of the population of Catalonia in [9]. Moreover, in a previous study from the same year, terms of geographical area, age distribution and gender we found a reduction of around 25% on the incidence of [20]. All primary care professionals in Catalonia use the patients with type 2 diabetes mellitus [11]. same EHR known as ECAP. ECAP is a software system Although reductions of chronic disease diagnoses that serves as a repository for structured data on diagno- have been well described [7, 9], the majority of the stud- ses, clinical variables, prescription data, laboratory test ies are focussed on trends from 2020 and early 2021, results, visits, diagnostic requests and referrals to other which raises doubts about the long-term impact of the health care specialties. pandemic in chronic disease diagnoses and its evolution thereafter. For instance, a study performed in Madrid Participants and study period (Spain) observed that, after huge declines of several long- We included all patients over 14 years of age assigned to a term conditions diagnosed in primary care in 2020, a primary care physician (GP) of ICS. In Catalonia, patients recovery on the number of diagnoses was observed dur- younger than this age are visited by paediatricians and ing 2021 for some diseases, while others remained miss- are not included in our study. We identify new diagnoses ing [18]. In this way, a previous study of our research of any of the following long-term conditions registered group showed that the number of cancer diagnoses per- in the primary care EHR—according to the International formed in primary care had returned to pre-pandemic Classification of Diseases, 10th Revision, Clinical Modi- levels by the end of 2021, although this did not com- fication ICD-10 CM -: type 2 diabetes mellitus (T2DM), pensate for the drops in 2020 and, therefore, missing asthma, chronic obstructive pulmonary disease (COPD), diagnoses during the two previous years were not fully ischemic heart disease (IHD), heart failure (HF), hyper- recovered [19]. Despite these studies, we have scarce tension or hypercholesterolemia (Table S1 contain the analyses regarding the evolution of other chronic condi- full list of ICD-10 CM codes used in this study). These tions after 2020; and thus it is uncertain whether these conditions were selected mostly because they are com- mon chronic diseases managed in primary care for which Mora et al. BMC Primary Care (2023) 24:9 Page 3 of 11 GP in Catalonia receive reminders and regular feedback The slope associated with the pre-pandemic period within indicators of the Catalan Healthcare Quality is estimated by ꞵtime, while the slope associated with Standard [21]. the pandemic period is estimated by ꞵtime + ꞵtime_covid. The study period spanned from January 2018 to August ꞵpandemic estimates the effect of the pandemic period on 2022. We divided this period into two periods: a pre-pan- the daily incidence. demic period (from January 2018 to 13 March 2020) and In order to calculate the difference of diagnoses a pandemic period (from 14 March 2020 until the end of between pandemic years and pre-pandemic years, we ­ 4th of March 2020 was the first day of the the study). The 1 compared the accumulated monthly incidence for each state of alarm and lockdown in Spain [22]. year; and we calculated the annual incidence rate for each year. Incidence rate ratios (IRRs) with the 95% con- Variables fidence interval (95%CI) were used to compare the inci- The main variable was the number of new chronic dis- dence in the years 2020, 2021 and 2022 to the incidence ease diagnoses registered in the primary care EHR, which in 2019. For the comparison between 2022 and 2019, we was obtained from the number of individuals diagnosed used 2019 data from the same months of 2022 (January— for the first time with each chronic condition included in August) as baseline. our study. Incidence rates per 100,000 inhabitants were Finally, we considered that there was a “diagnostic calculated by dividing the number of new chronic disease compensation” when the overall diagnoses observed diagnoses by the population size. The population size of each disease during the pandemic period (from 14 was extracted monthly from the primary care EHR and March 2020 to 31 August 2022) was statistically simi- it included the number of patients assigned to a GP at the lar to the expected diagnoses. To do that, we calculated end of each month. the expected diagnoses from the mean daily incidence As secondary variables we used age at the time of diag- of 2019, we multiplied this value by the number of days nosis categorised in 5 groups (15–44, 45–59, 60–69, and the population of the pandemic period and, then, we 70–79 and > 79 years), sex (men/women), rurality and divided it by 100,000. We estimated the expected value socioeconomic status. We assessed the socioeconomic and its 95%CI. We also calculated the difference between status using the validated deprivation index based on expected and observed diagnoses. Whenever the 95%CI census data (MEDEA deprivation index) constructed of the difference between expected and observed crossed by the project Mortality and socio-economic and envi- 0 it was considered to have achieved diagnostic com- ronmental inequalities in small areas of cities in Spain pensation, while an excess of diagnoses was determined (MEDEA project) [23] We categorised this index into when the 95%CI yielded over 0, and no diagnostic com- four groups, where first and fourth groups are the least pensation when it remained under 0. and the most deprived areas, respectively. Rural areas The significance level of all statistical tests is were categorised separately and were defined as areas alpha = 0.05. with less than 10,000 inhabitants and a population den- All analyses were conducted using R, version 3.5.1 [24] sity lower than 150 inhabitants/km2. Results Statistical analysis The baseline characteristics of our population are pre- We analysed daily incidence rates of each chronic disease sented in Table 1. The population over 14 years of age from January 2018 to August 2022 using a segmented slightly increased since 2018 while other characteristics regression analysis approach, expressed as follows: remained stable during the study period in terms of age, sex and socioeconomic status distribution. Y ∼ β0 + βtime ∗ time + βpandemic ∗ pandemic + βtime− covid ∗ time− covid + error where: Overall, 740,820 new chronic diseases’ diagnoses were Y is the 7-day moving average daily incidence. registered in the Catalan primary care EHR: 224,937 Time is the number of days between the beginning of hypertension diagnosis, 150,214 hypercholesterolemia, the study period and the date of diagnosis. 133,540 T2DM, 65,842 asthma, 62,313 HF, 55,762 COPD Pandemic is a dummy that takes 1 when Time is after and 48,212 IHD. The annual number of chronic diseases 14 March 2020 and 0 otherwise. were similar in 2018 and 2019 (with the exception of Time_covid is the number of days since 14 March 2020. hypercholesterolemia, which slightly increased in 2019). ꞵ is the coefficient for the indicated variable. However, in 2020 all diagnoses abruptly dropped. Mean Mora et al. BMC Primary Care (2023) 24:9 Page 4 of 11 Table 1 Baseline characteristics of the study population by year (2018—2022) 2018 2019 2020 2021 2022 Total 4,852,961 (100%) 4,957,155 (100%) 4,991,716 (100%) 5,053,670 (100%) 5,108,878 (100%) Age 15–44 2,183,988 (45%) 2,209,398 (44.57%) 2,216,414 (44.4%) 2,204,497 (43.62%) 2,218,929 (43.43%) 45–59 1,267,021 (26.11%) 1,306,846 (26.36%) 1,334,878 (26.74%) 1,370,374 (27.12%) 1,392,801 (27.26%) 60–69 607,066 (12.51%) 622,656 (12.56%) 635,927 (12.74%) 651,006 (12.88%) 660,190 (12.92%) 70–79 450,636 (9.29%) 479,562 (9.67%) 480,311 (9.62%) 489,048 (9.68%) 499,086 (9.77%) > 79 years 346,465 (7.14%) 346,589 (6.99%) 346,467 (6.94%) 346,519 (6.86%) 346,001 (6.77%) Sex Men 2,370,318 (48.84%) 2,421,966 (48.86%) 2,440,227 (48.89%) 2,475,074 (48.98%) 2,499,848 (48.93%) Women 2,482,643 (51.16%) 2,535,189 (51.14%) 2,551,489 (51.11%) 2,578,991 (51.03%) 2,609,701 (51.08%) Socioeconomic status Rural 1,159,868 (23.9%) 1,173,457 (23.67%) 1,187,011 (23.78%) 1,207,685 (23.9%) 1,222,434 (23.93%) 1st Q (least deprived) 1,080,159 (22.26%) 1,093,771 (22.06%) 1,100,788 (22.05%) 1,115,034 (22.06%) 1,128,103 (22.08%) 2nd Q 753,137 (15.52%) 763,990 (15.41%) 769,916 (15.42%) 778,361 (15.4%) 788,254 (15.43%) 3rd Q 991,232 (20.43%) 1,018,627 (20.55%) 1,024,027 (20.51%) 1,034,914 (20.48%) 1,045,552 (20.47%) 4th Q (most deprived) 868,565 (17.9%) 907,368 (18.3%) 913,508 (18.3%) 918,455 (18.17%) 927,458 (18.15%) age and percentage of women were similar across all 2022, the registered incidence of T2DM increased by 16% years within each chronic condition but the percentage and 24%, respectively; and by 34% and 49% in the case of rural areas decreased in 2020, 2021 and 2022 in some of hypercholesterolemia. Conversely, in asthma, COPD diagnoses (Supplementary Table S2 and Supplementary and IHD we still observed reductions during 2021 and Figure S1). 2022 although smaller than those from 2020. In particu- Figure 1 shows the results of the segmented regression lar, COPD presented reductions of 42%, 31% and 15% in analysis. The trends of daily rates for all diseases were 2020, 2021 and 2022, respectively, while asthma diagno- drastically interrupted on 14 March 2020 (the first day of ses decreased by 31%, 16% and 7% in the same years. the lockdown in Spain). During the subsequent months, When we compared the observed diagnoses regis- we observed a general upward trend, although in some tered during the pandemic period (from 14 March 2020 conditions the incidence at the end of the study period until 31 August 2022) with the expected ones in order was still below the pre-pandemic level. Supplementary to determine if the increase in some diagnoses in 2021 Table S3 shows the coefficients of the models for each and 2022 compensated for the drops, we observed, that disease. after more than two years since the beginning of the Figure 2 shows the monthly-accumulated rates by year pandemic, there was still a reduction of -24% (IC95%: of each chronic disease. We observed that the incidence -27.94% to -19.68%) in asthma diagnoses, a reduction of in 2020 decreased for all diseases around March—April -38.39% (IC95%: -41.94% to -34.37%) in COPD diagno- 2020. Nevertheless, monthly rates in 2021 and 2022 ses, a reduction of -21.25% (95%CI: -25.6% to -16.37%) in were hovering at diagnosis level of 2019 or were higher IHD and a reduction of -8.53% (IC95%: -13.5% to -2.95%) for T2DM, hypertension, HF and hypercholesterolemia. in hypertension. We estimated that the overall reduction On the other hand, rates of asthma, COPD and IHD during the whole pandemic period accounted for 14,644, remained below 2019 values. 9,719, 6,264 and 10,926 fewer COPD, asthma, IHD and Compared to 2019, the IRR associated with the reduc- hypertension diagnoses, respectively. Conversely, a 8.51% tions in 2020 are presented in Table 2 and Figure Sup- (95% CI: 1.81 to 16.15%) excess of registered diagnoses plementary S2. We observed reductions around 30% in was observed in hypercholesterolemia when compared to asthma, IHD, T2DM, hypertension and hypercholes- the expected. Finally, for T2DM and HF we observed a terolemia; a greater reduction of 42% (IRR: 0.58 [95% statistically non-significant difference of -3.81% (95%CI: CI: 0.57 to 0.6]) in COPD rates and lesser drops in HF -9.36% to 2.46%) and 2.88% (95% CI: -2.39% to 8.76%) (IRR: 0.86 [95% CI: 0.84 to 0.88]). In contrast, in 2021 respectively (Fig. 3 and Supplementary Table S4). and 2022, T2DM, hypercholesterolemia, hypertension In general, similar findings were observed when we and HF showed increases in the recorded incidence, with stratified data by age groups, sex and socioeconomic sta- IRR significantly > 1 (Table 2). For instance, in 2021 and tus (Fig. 3 and Supplementary Table S4). However, some Mora et al. BMC Primary Care (2023) 24:9 Page 5 of 11 Fig. 1 7-day moving average rates of daily chronic diseases since 2018 in Catalonia differences were observed in more advanced age groups incidence rates still below those of 2019. The return to with an excess of T2DM and hypercholesterolemia diag- pre-pandemic diagnosis levels compensated for the drops noses; and also with an increase of registered diagnoses in 2020 regarding T2DM and HF, but not for hyperten- of HF in more deprived areas and younger people. No sion, which presented an incomplete recovery. Further- difference were observed regarding sex. more, we identified an excess of registered diagnoses Finally, we estimated the time frame when the compen- of hypercholesterolemia (around 8%) that should raise sation for T2DM, HF and hypercholesterolemia occurred awareness of a possible overdiagnosis or an increase in by comparing the daily cumulative observed diagno- the number of clinical analyses due to worsening popula- ses during the pandemic period to the daily cumulative tion health. expected diagnoses. Compensation for hypercholester- Our findings for 2020 are aligned with those found in olemia took place at the beginning of November 2021, other studies. Several articles have described substantial for HF in mid-December 2021 and for T2DM at the end drops in the incidence of multiple non-communicable of April 2022. Excess of hypercholesterolemia diagnoses diseases. Reductions were observed both in new diagno- was observed at the end of May 2022 (Fig. 4 and Supple- ses performed during 2020 and new prescribing associ- mentary Table S5). ated medications [7, 9, 11, 25]. However, few studies have analysed such prolonged periods as the one presented Discussion in this study. For instance, an observational study con- We found important reductions ranging between -14% ducted in Madrid (Spain) found that some of the chronic and -42% in recorded new diagnoses of the main long- diseases analysed had returned to expected incidence term conditions managed in primary care during 2020, rates, but without compensation [18]. However, the study but an upward increase in some of them in 2021 and the period only comprised data spanning as far as mid-2021, first eight months of 2022. This situation led to a return while some diagnosis compensation found in our study to pre-pandemic diagnosis levels (or higher) for some started at the end of 2021. The Madrid study also found a chronic diseases except asthma, COPD and IHD, with low level of diagnosis for asthma and COPD, just like the Mora et al. BMC Primary Care (2023) 24:9 Page 6 of 11 Fig. 2 Cumulative rates of monthly chronic diseases registered by year in Catalonia (2019–2022) Table 2 Annual rates per 100,000 inhabitants of chronic diseases and incidence rate ratios (IRR) compared to 2019 Chronic disease Year Rate × 100,000 2019 Rate × 100,000 IRR 95% CI Asthma 2020 313.3 216.92 0.69 [0.68—0.71] 2021 313.3 262.01 0.84 [0.82—0.86] 2022$ 211.55 197.34 0.93 [0.91—0.96] Chronic obstructive pulmonary disease 2020 290.05 169.06 0.58 [0.57—0.6] (COPD) 2021 290.05 199.4 0.69 [0.67—0.71] 2022$ 195.15 166.51 0.85 [0.83—0.88] Heart failure (HF) 2020 259.6 223.63 0.86 [0.84—0.88] 2021 259.6 290.9 1.12 [1.09—1.15] 2022$ 180.35 223.85 1.24 [1.21—1.28] Hypercholesterolemia 2020 600.61 432.72 0.72 [0.71—0.73] 2021 600.61 807.45 1.34 [1.32—1.36] 2022$ 397.37 591.75 1.49 [1.46—1.52] Hypertension 2020 977.29 690.78 0.71 [0.7—0.72] 2021 977.29 1074.13 1.1 [1.09—1.11] 2022$ 653.84 784.58 1.2 [1.18—1.22] Ischemic heart disease (IHD) 2020 231.99 160.97 0.69 [0.67—0.71] 2021 231.99 203.46 0.88 [0.85—0.9] 2022$ 154.3 141.26 0.92 [0.89—0.95] Type 2 diabetes mellitus (T2DM) 2020 579.06 396.86 0.69 [0.67—0.7] 2021 579.06 669.04 1.16 [1.14—1.17] 2022$ 386.23 470.85 1.22 [1.2—1.24] $ Data until August Mora et al. BMC Primary Care (2023) 24:9 Page 7 of 11 Fig. 3 Percentage of difference between observed and expected chronic diagnoses during the pandemic period in Catalonia. Total and by age groups, sex and socioeconomic status present study. Finally, a Belgium study reported reduc- three face-to-face visits are required for the diagnosis of tions of most chronic incidence rates during the first hypertension (unlike hypercholesterolemia and diabetes, COVID-19 wave but a return to pre-pandemic levels at which only require a blood test, the request for and result the end of 2020 and beginning of 2021, also without com- of which can be telematic), may also explain the lower pensation as in the Spanish article[7]. diagnostic recovery from hypertension, since many of the The return to pre-pandemic levels of diagnosis for most visits continued to be non-face-to-face. of the chronic diseases analysed in our article points to a The persisting low level of asthma and COPD diagno- recovery of primary care activity. In addition, the com- ses is very concerning as patients with undiagnosed con- pensation of the missing diagnoses for T2DM, hypercho- ditions are unlikely to be receiving systematic monitoring lesterolemia and HF, suggests a great effort of primary and management, which could lead to increased morbid- care professionals in order to reduce the harms of the ity and future negative health outcomes. Reduction in backlogs that the first year of the COVID-19 pandemic asthma exacerbations during COVID-19 was detected caused in several non-COVID conditions. However, the and described in other works [6]. Although the continu- compensation observed is still incomplete in some con- ing low rates of asthma observed in our study could mark ditions, although it is possible that some diseases (such a true incidence drop, the most likely explanation for as hypertension) will achieve the expected values in the this low number of registered asthma and COPD diag- months to come, since the rates of diagnoses registered in nosis may be the disruptions of diagnostic procedures, 2021 and 2022 are significantly higher than those of the enforced by pandemic guidelines that recommended pre-pandemic threshold. In addition, the fact that two or postponing or reducing some procedures that might Mora et al. BMC Primary Care (2023) 24:9 Page 8 of 11 Fig. 4 Daily cumulative observed and expected (with 95%CI) new chronic disease diagnoses during the pandemic period (14 March 2020 to 31 August 2022) in Catalonia increase respiratory transmission, such as spirometry [3, in future research. Some studies observed an increase 18]. Further research should be performed to confirm of dyslipidemia and obesity during the pandemic, prob- these findings and to identify possible explanations; and ably related to the decrease of physical activity during appropriate actions should be taken to revert this situ- lockdowns, remote working or changes in dietary habits ation. Regarding the low levels of IHD new diagnoses, [6]. If the reason for this excess of hypercholesterolemia some studies have observed reductions in admissions for diagnoses is related to worsening population health, we stroke or heart attack treatments during the pandemic also should expect excess in T2DM and other chronic and therefore they suggest that part of the reduction in conditions in the months to come. In this sense, then, it prevalence and incidence of some chronic diseases could is possible that the compensation of T2DM diagnoses be related to the harvesting effect due to the high impact observed was actually a consequence of a greater real of the first COVID-19 wave in terms of mortality [26]. hidden incidence and therefore we would still be missing However, a study performed in Catalonia in 2020 esti- some diagnoses. It is crucial to unravel the causes associ- mated a low impact of this effect [9]. Conversely, a UK ated with these increases in future research. However, as study found a possible trend towards increased strokes in asthma and COPD, it is unlikely that all the observed after a year from the beginning of the COVID-19 pan- excess is merely a consequence of a real increment in demic [27]. It is crucial to establish the reasons behind the incidence of this condition, but rather a possible these still remaining backlogs in future research. overdiagnosis that should be taken into consideration The 8% excess of hypercholesterolemia diagnoses dur- and confirmed. In addition, the most recent vascular ing the pandemic period should also be analysed in depth risk guidelines favour a pharmacological treatment of Mora et al. BMC Primary Care (2023) 24:9 Page 9 of 11 dyslipidemia, by proposing very low LDL control targets, interventions should be carried out to revert this situa- which is why the diagnosis of hypercholesterolemia is tion, especially changes in COVID-19 guidelines that are also favoured [28, 29]. no longer justified considering the current epidemiologi- Our study has some limitations. First, as our analysis cal situation. In addition, more resources are required in is based on rates, major changes in the population pyr- primary care to tackle observed and anticipated work- amid could limit our findings. However, the population load as part of disease recovery and compensation; and in Catalonia has remained stable in terms of age, sex and specific strategic planning at the level of primary care socioeconomic characteristics during the study period, organisations may be required. Finally, periodic health as showed in the Results section. Second, the use of pri- data about incidence rates of chronic diseases is needed mary care EHR could imply a potential lack of hospital worldwide to track progress in the recovery of missed diagnoses and a potential diagnoses inaccuracy as rely diagnoses by strengthening clinical information sys- on routinely collected data. However, Catalan primary tems and using EHR to perform this continuing disease care EHR has been previously validated for research, the surveillance. chronic diseases chosen for the study are usually diag- nosed in primary care and, in Catalonia, there have been Abbreviations some healthcare quality indicators calculated with this 95%CI 95% Confidence interval data for more than 15 years [21, 30, 31]. Third, the lack COPD Chronic obstructive pulmonary disease of more pre-pandemic years to compare could hide pos- GP Primary care physician EHR Electronic health records sible previous trends. Finally, some alterations in patients’ HF Heart failure healthcare seeking behaviour during the COVID19 pan- IRR Incidence rate ratio demic could affect the observed trends, although this ICS Institut Català de la Salut IHD Ischemic heart disease effect is unlikely to hold throughout 2022. T2DM Type 2 diabetes mellitus Despite the limitations, our study also has strengths. Several studies have used the Catalan primary care EHR Supplementary Information data to perform useful research in real-world conditions The online version contains supplementary material available at https://​doi.​ [8, 11, 19, 23, 30–32]. Moreover, our study period lasted org/​10.​1186/​s12875-​022-​01935-0. for more than two pandemic years and thus it stretches the time frame from the majority of the literature avail- Additional file 1: Table S1. ICD-10 CM codes used to identify chronic diseases in the Catalan primary care electronic health records. Table S2. able to date. This long study period allows us to observe Characteristics of the patients with chronic disease diagnoses by year. Fig- not only the decrease of non-COVID conditions but also ure S1. Age distribution of chronic diseases diagnoses during the study the recovery and the remaining backlogs and areas to period. Table S3. Coefficients of the segmented regression model. Figure S2. Incidence rate ratios (IRR) by year. Relative to year 2019. Table S4. focus on during the following months. In addition, our Observed and expected diagnoses during the pandemic period (from 14 study includes 7 common long-term conditions man- March to 31 August 2022). Table S5. Date of compensation and excess of aged by primary care professionals that are also included diagnoses for each chronic disease. Total and stratified by age groups, sex and socioeconomic status. in several quality of care indicators calculated since 2006 and used to monitor these chronic diseases with perma- Acknowledgements nent feedback to GPs [21]. This ensures that in general We would like to acknowledge the efforts of all members of the SISAP team. the coding quality is high. Finally, as ICS manages about We would also like to thank all the primary care healthcare professionals in three in every four practices in Catalonia, our results may Catalonia involved in the management of patients in primary care during these challenging times. To Mireia Pijoan for their English style review of the be generalizable and our methods could be introduced in manuscript. other settings that also use EHR. Authors’ contributions All authors contributed to the design of the study, the interpretation of the Conclusions results, and the review of the manuscript. Ermengol Coma, Roser Cantenys Our work included long-term data showing different and Mència Benítez conducted bibliographic research. Ermengol Coma, Roser trends of chronic disease, with dramatic reductions at Cantenys, Francesc Fina, Leonardo Méndez-Boo, Eduardo Hermosilla and Núria Mora had access to data. Núria Mora performed the statistical analysis. Ermen‑ the early stages of the pandemic for all 7 chronic dis- gol Coma, Núria Mora and Leonardo Méndez-Boo wrote the first draft of the eases analysed here and subsequent recovery of some of manuscript. All authors critically revised the manuscript. The corresponding them. While in some cases registered diagnoses had been author attests that all listed authors meet authorship criteria and that no oth‑ ers meeting the criteria have been omitted.The author(s) read and approved recovered and compensated for the initial drops that took the final manuscript. place in 2020 (showing that primary care quickly adapted and resumed pre-pandemic activity), there is still a short- Funding The authors neither received, nor will receive, individual or group funding for fall in incidence rates of some conditions that should their work. alert policy makers and public health authorities. Some Mora et al. BMC Primary Care (2023) 24:9 Page 10 of 11 Availability of data and materials Environ Res Public Health. 2021;18(10):5335. https://​doi.​org/​10.​3390/​ijerp​ The datasets used during the current study are available upon reasonable h1810​5335. (Published 2021 May 17). request to the corresponding author. 10. Chudasama YV, Gillies CL, Zaccardi F, et al. Impact of COVID-19 on routine care for chronic diseases: A global survey of views from healthcare professionals. Diabetes Metab Syndr. 2020;14(5):965–7. https://​doi.​org/​10.​ Declarations 1016/j.​dsx.​2020.​06.​042. 11. Coma E, Miró Q, Medina M, et al. Association between the reduction of Ethics approval and consent to participate face-to-face appointments and the control of patients with type 2 diabe‑ This study is part of a project that analyses the impact of COVID-19 pandemic, tes mellitus during the Covid-19 pandemic in Catalonia. Diabetes Res Clin related control measures and organisational changes on primary care. All Pract. 2021;182:109127. https://​doi.​org/​10.​1016/j.​diabr​es.​2021.​109127. analysis and methods of this study have been performed in accordance with 12. Lear-Claveras A, Oliván-Blázquez B, Clavería A, Couso-Viana S, Botaya RM. the Declaration of Helsinki (last update, Fortaleza, Brazil 2013) and existing Analysis of Clinical Parameters, Drug Consumption and Use of Health relevant guidelines and regulations in Spain. The project was also approved by Resources in a Southern European Population with Diabetes That Did the Clinical Research Ethics Committee of the IDIAPJGol (project code: 20/172- Not Contract COVID-19: A Longitudinal Big Data Study. Int J Environ Res PCV), including a waiver for the informed consent of patients taking part in Public Health. 2022;19(11):6835. https://​doi.​org/​10.​3390/​ijerp​h1911​6835. the study. The data extracted from the EHR were fully anonymised. There was (Published 2022 Jun 2). no patient or public involvement in this study. 13. Kim Y, Gordon A, Rowerdink K, Herrera Scott L, Chi W. The Impact of the COVID-19 Pandemic on Health Care Utilization Among Insured Individu‑ Consent for publication als With Common Chronic Conditions [published online ahead of print, Not applicable. 2022 Jul 22]. Med Care. 2022;https://​doi.​org/​10.​1097/​MLR.​00000​00000​ 001747. doi:https://​doi.​org/​10.​1097/​MLR.​00000​00000​001747 Competing interests 14. Chen B, Wang M, Huang X, et al. Changes in Incidence of Notifiable The authors declare that they have no competing interests. Infectious Diseases in China Under the Prevention and Control Measures of COVID-19. Front Public Health. 2021;9:728768. https://​doi.​org/​10.​3389/​ Author details fpubh.​2021.​728768. (Published 2021 Oct 15). 1 Primary Care Services Information Systems (SISAP), Institut Català de la Salut 15. Kelsie Cassell, Casey M Zipfel, Shweta Bansal, Daniel M. Weinberger. (ICS), Gran Via de Les Corts Catalanes, 587, 08007 Barcelona, Spain. 2 Equip Trends in non-COVID-19 hospitalizations prior to and during the d’Atenció Primària de Gòtic, Institut Català de la Salut (ICS), Barcelona, Spain. COVID-19 pandemic period, United States, 2017 – 202. medRxiv 3 Institut Universitari d’Investigació en Atenció Primària Jordi Gol (IDIAPJGol), 2022.04.26.22274301; doi: https://​doi.​org/​10.​1101/​2022.​04.​26.​22274​301 Barcelona, Spain. 4 Universitat de Barcelona, Barcelona, Spain. 5 Direcció 16. Williams R, Jenkins DA, Ashcroft DM, et al. Diagnosis of physical and Assistencial d’Atenció Primària i a la Comunitat, Institut Català de la Salut (ICS), mental health conditions in primary care during the COVID-19 pandemic: Barcelona, Spain. 6 DAP_Cat Research Group, Gerència Territorial Barcelona a retrospective cohort study. Lancet Public Health. 2020;5(10):e543–50. 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Clin Epidemiol. 2019;11:1015–24. https://​doi.​org/​10.​2147/​CLEP.​S2255​68. (Published 2019 Dec 3). 32. Prieto-Alhambra D, Balló E, Coma E, et al. Filling the gaps in the char‑ acterization of the clinical management of COVID-19: 30-day hospital admission and fatality rates in a cohort of 118 150 cases diagnosed in outpatient settings in Spain. Int J Epidemiol. 2021;49(6):1930–9. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in pub‑ lished maps and institutional affiliations. Ready to submit your research ? Choose BMC and benefit from: • fast, convenient online submission • thorough peer review by experienced researchers in your field • rapid publication on acceptance • support for research data, including large and complex data types • gold Open Access which fosters wider collaboration and increased citations • maximum visibility for your research: over 100M website views per year At BMC, research is always in progress. 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