Understanding Therapeutic Inertia in the Management of Hypertension in Primary Care: Examining Contributing Factors at the Patient and Provider Levels in Chittoor District, Andhra Pradesh, India – A Mixed Methods Study

Understanding Therapeutic Inertia in the Management of Hypertension in Primary Care: Examining Contributing Factors at the Patient and Provider Levels in Chittoor District, Andhra Pradesh, India – A Mixed Methods Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Understanding Therapeutic Inertia in the Management of Hypertension in Primary Care: Examining Contributing Factors at the Patient and Provider Levels in Chittoor District, Andhra Pradesh, India – A Mixed Methods Study Shruti Krishnan, Dorothy Lall, Harsh Shah This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8418875/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Background Hypertension remains a significant global health challenge, affecting approximately 1.4 billion adults aged 30–79 worldwide. In India, the age-standardised prevalence is 28.1%, and blood pressure (BP) control remains suboptimal. Therapeutic inertia, the failure to initiate or intensify treatment when therapeutic goals are unmet, is recognised as a key contributor to uncontrolled hypertension. In this study, we aimed to understand the prevalence and factors contributing to therapeutic inertia in hypertension management within primary care settings in Chittoor, with a focus on shared decision-making (SDM). Methods A convergent parallel mixed-methods design was adopted. The quantitative strand involved 104 adults with uncontrolled hypertension attending primary care facilities. Data on sociodemographic variables, cardiovascular risk factors, consultation and treatment details, and SDM were collected through a structured questionnaire. The qualitative strand included in-depth interviews with nine patients and eight medical officers. Findings from both strands were integrated and triangulated with field observations. Results The prevalence of therapeutic inertia was 76.9%. Patients aged under 60 years (AOR = 4.36; 95% CI: 1.13–16.90) and those with borderline or mildly elevated blood pressure (AOR = 4.81; 95% CI: 1.38–16.70) had greater odds of inertia. In contrast, illiteracy (AOR = 0.23; 95% CI: 0.05–0.99), the presence of comorbidities (AOR = 0.18; 95% CI: 0.04–0.79), and higher SDM scores (AOR = 0.93; 95% CI: 0.88–0.99) were associated with lower odds. The participants with inertia had significantly lower mean SDM scores (20.36 vs. 28.4, p = 0.003). Thematic analysis highlighted seven key drivers: patient beliefs and perceptions, reluctance to adopt lifestyle changes, fragmented care and conflicting advice, provider caution and clinical judgement, poor follow-up and adherence, workforce constraints in outreach programmes, and limited SDM. Conclusions Therapeutic inertia is highly prevalent within India’s primary healthcare system, resulting from a complex interplay of factors at the patient, provider and system levels. Limited engagement in shared decision making, particularly regarding hypertension, has been consistently associated with increased inertia. Strengthening provider capacity, enhancing patient engagement and incorporating SDM into routine clinical practice could help reduce inertia and improve hypertension management outcomes in primary care settings. Therapeutic inertia Hypertension Primary care Shared decision making (SDM) Mixed methods India Figures Figure 1 Background According to the World Health Organisation (WHO), non-communicable diseases (NCDs) are responsible for 41 million deaths annually, accounting for 74% of all deaths globally. Among these, cardiovascular diseases contribute to 17.9 million deaths, representing approximately one-third of total NCD-related fatalities worldwide [1]. Hypertension, the leading metabolic risk factor for cardiovascular diseases, affects an estimated 1.4 billion adults aged 30–79 years globally, with approximately two-thirds of those affected residing in low- and middle-income countries [2]. In India, NCDs contribute to approximately 5.87 million deaths annually, accounting for 60% of all deaths and representing over two-thirds of total NCD-related deaths in the WHO Southeast Asia region [3]. Cardiovascular diseases, including coronary artery disease, stroke, and hypertension, account for 45% of all NCD-related deaths [4]. According to the Fifth National Family Health Survey (NFHS-5), the age-standardised prevalence of hypertension in India is 28.1% (95% CI, 27.9%-28.3%). Furthermore, among those with diagnosed hypertension, less than one-fourth achieve target control of their blood pressure (BP) [5]. Guidelines for the management of hypertension focus on reducing cardiovascular risk factors and achieving optimum BP through a combination of lifestyle modification and appropriate use of antihypertensive drugs [6]. Patients who adhere to antihypertensive medication are more likely to achieve optimal BP control, resulting in a reduced risk of adverse outcomes [7]. This adherence leads to a 40% reduction in stroke risk and a 30% reduction in cardiovascular mortality [8]. Achieving better control of hypertension is crucial for reducing cardiovascular morbidity and mortality. Several factors contribute to the poor control of hypertension, which can be broadly classified into patient-related, provider-related, and health system-related factors. Among patient-related issues, non-adherence to medication is the most significant challenge for achieving optimal BP control. However, nearly half of the challenges in managing hypertension arise from provider-related factors, with therapeutic inertia recognised as the primary cause of uncontrolled hypertension [9,10]. Therapeutic inertia, also referred to as clinical inertia, is defined “as the failure to initiate or intensify therapy when therapeutic goals of hypertension are not met” [11]. This concept can be summarised as “recognition of the problem, but failure to act.” Several studies have shown that therapeutic inertia in managing hypertension and other chronic conditions, such as dyslipidemia and diabetes, contributes to 80% of heart attacks and strokes [12]. Phillips identified three key reasons for therapeutic inertia: overestimating the quality of care, feeling that control has improved, and being close to the target. Additionally, a lack of training in achieving treatment targets contributes to this issue [13]. The India Hypertension Control Initiative (IHCI), a multi-partner initiative implementing and scaling public health hypertension control programs in India, identified therapeutic inertia as one of the major factors contributing to suboptimal control of BP, emphasising the importance of understanding the phenomenon and the influencing factors better, especially in the Indian context, to improve hypertension management in primary care settings [14]. Despite the growing burden of hypertension and evidence of suboptimal control in India, there is limited research investigating why therapeutic inertia persists. Furthermore, the role of shared decision-making (SDM) in influencing treatment initiation or intensification remains underexplored. In this study, we aimed to identify factors contributing to therapeutic inertia in the management of hypertension among patients attending primary care facilities in the Chittoor district, with a focus on SDM. We also aimed to understand, from both patient and provider perspectives, the barriers to treatment intensification. Methods Study design We employed a convergent parallel mixed-methods design to achieve a comprehensive and in-depth understanding of therapeutic inertia, enabling a rich interpretation through data triangulation. A mixed methods study is characterised by the integration of both qualitative and quantitative data at various stages of the research process, including data collection, analysis, and interpretation [15]. In our study, both quantitative and qualitative data were collected concurrently, and they were given equal weights. After collection, we analysed the data from both strands simultaneously and separately. Finally, the results were integrated for meaningful interpretation. Study setting and context The study was conducted in Chittoor, one of the 26 districts in the southern Indian state of Andhra Pradesh. Health care services for hypertension in this district are delivered through both the public and private health sectors. In the public sector, services are offered at District Hospitals, Community Health Centres (CHCs), Primary Health Centres (PHCs) and Sub-centres (SCs). The PHC and SC form the primary level of the health care system. The rural PHC, typically staffed by a medical officer, caters to a population of 20,000–30,000, while the urban PHC (UPHC) is established for every 50,000 population, and is located close to urban slums. Chittoor district has 48 rural PHCs and 13 urban PHCs spread across its 31 Mandals (sub-district divisions). CHCs, which serve as the first referral unit for every 80,000–1,20,000 people, offer multiple specialised services [16]. To strengthen the response to NCDs, the government of India launched the National Programme for Control of Diabetes, Cancers and Stroke (NPCDCS) in 2010. This initiative was later broadened and renamed as the National Programme for Prevention and Control of Non-Communicable Diseases (NP-NCD) [17]. Under this programme, NCD clinics have been established at CHCs and district hospitals to provide care for conditions such as hypertension and diabetes. In addition, the government of Andhra Pradesh introduced the Family Doctor Programme (FDP) [18], a novel initiative aimed at delivering health services to the rural population at their doorstep. Under this programme, each PHC is provided with two medical officers (MOs). One MO is assigned to 6–7 SCs and visits each one once a month to provide medical services, while the other MO manages outpatient duties at the PHC. The services are further supported by 104 mobile medical units (MMUs), with NCD screening and management being among the major services offered. For our study, we focused on FDP centres, PHCs, and CHCs, as therapeutic decisions for the management of hypertension are actively made at these facilities, and patients are followed up at this level, making them suitable for understanding therapeutic inertia. Study participants and sampling In the quantitative strand, we used a stratified purposive sampling approach to select 15 primary care facilities, including 8 rural PHCs, 5 urban PHCs, and 2 CHCs, all of which were based on their high volume of hypertension cases, while ensuring proportional representation. Among the selected facilities, a consecutive sampling method (total enumerative sampling) was used to recruit eligible patients. All patients meeting the inclusion criteria were approached consecutively during clinic hours until the facility sampling target was achieved. The inclusion criteria were all adult patients aged 18 years and above with a documented diagnosis of hypertension for at least six months, whose blood pressure was measured specifically by an electronic or digital BP monitor during the consultation. Patients whose blood pressure readings were at a therapeutic target (SBP < 140 mmHg or DBP < 90 mmHg for general patients; SBP < 130 mmHg or DBP < 80 mmHg for those with diabetes; history of stroke; chronic kidney disease), those whose blood pressure was measured via a manual blood pressure monitor, minors, individuals who were too ill to complete the interview, and those who refused to provide consent were excluded. The sample size was calculated using the single population proportion formula, which assumes a 50% prevalence of therapeutic inertia as a conservative estimate to ensure adequate power due to the absence of previous studies in the Indian context that utilised a standardised questionnaire to assess therapeutic inertia. A 95% confidence level (Z = 1.96) was used, with an absolute precision of 10% for a hypertensive population in the Chittoor district of approximately 4,79,284. An anticipated non-response rate of 10% was considered, resulting in a final sample size of 110 patients. For the qualitative strand, we used a purposive sampling strategy to select hypertensive patients, who were a subset of the quantitative sample. The participants were selected to ensure diversity in age, sex, education level, duration of hypertension, presence of cardiovascular risk factors, comorbidities, and treatment preferences. Medical officers were purposively selected on the basis of their current role in primary care settings, with a minimum of one year of experience and involvement in managing hypertension. Variation in age, years of experience, training, and experience in hypertension management were also considered during selection. Recruitment continued until data saturation was achieved [19]. A total of 9 patients and 8 medical officers were enrolled in the qualitative analysis. Data collection For the quantitative strand, we used a structured, cross-sectional questionnaire comprising 5 sections (see Supplementary file 1): (i) sociodemographic and anthropometric details, (ii) cardiovascular risk factors and comorbidities, (iii) dietary and physical activity behaviour based on the WHO stepwise approach to NCD risk factor surveillance [20], (iv) consultation and treatment details, and (v) shared decision making measured via the SDM-Q-9 tool [21], which has been validated in the Indian context [22]. The questionnaire was developed in English and then translated into local languages (Telugu and Tamil), followed by back-translation to ensure linguistic and cultural appropriateness. Content validity was established through expert review by a panel consisting of a community medicine specialist, a primary care physician, and a behavioural science expert. The tool was pilot tested on 10% of the estimated sample, and face validity was assessed. Minor revisions were made on the basis of the pilot findings to improve clarity. The data collected through Kobo Toolbox was exported to Excel 2021 for cleaning, then coded and analysed using SPSS® version 27.0 for Windows. For the qualitative strand, we conducted in-depth interviews in April and May 2025, utilising a semi-structured interview guide (see Supplementary file 2). This guide was designed using a funnelling technique beginning with introductory questions and then progressing to more specific thematic questions. For hypertensive patients, the guide explored their experiences with managing the condition, adhering to treatment and participating in decision-making. For medical officers, it addressed hypertension management practices, treatment decisions for uncontrolled hypertension, patient engagement in shared decision making, and barriers to treatment intensification. The interviews were held in consultation rooms and other private spaces within healthcare facilities. All interviews were audio recorded with consent, and field notes were made immediately after each interview. Verbatim transcription was performed for all the interviews. The average duration was 17 minutes for patients and 32 minutes for medical officers, with the overall duration ranging from 13–40 minutes. Outcome measures Outcome measures The primary binary outcome variable is therapeutic inertia. Therapeutic inertia was recognised on the basis of 3 major criteria: (i) uncontrolled BP at the time of consultation (SBP > or = 140 or DBP > or = 90 mmHg in all patients; SBP > or = 130 or DBP > or = 80 in patients with diabetes or stroke); (ii) no initiation or intensification of treatment during the particular consultation (no change in dose or medication addition); and (iii) inappropriate deintensification without justification [23,24]. The point prevalence of therapeutic inertia was calculated using the following formula: In addition to the primary outcome, selected explanatory variables were operationally defined. The blood pressure classification followed the European Society of Cardiology and European Society of Hypertension (ESC/ESH) 2023 guidelines [25], with high normal defined as SBP 130–139 mmHg and/or DBP 85–89 mmHg; grade 1 hypertension defined as SBP 140–159 mmHg and/or DBP 90–99 mmHg; grade 2 hypertension defined as SBP 160–179 mmHg and/or DBP 100–109 mmHg; grade 3 hypertension defined as SBP ≥ 180 mmHg and/or DBP ≥ 110 mmHg; and isolated systolic hypertension defined as SBP ≥ 140 mmHg with DBP < 90 mmHg. Treatment compliance was assessed using the pill count method and defined as adherent when ≥ 80% of prescribed doses had been taken, which was calculated on the basis of the number of pills dispensed minus the number remaining at follow-up [26]. Physical activity was classified as sufficient if participants engaged in ≥ 150 minutes per week of moderate-intensity activity, ≥ 75 minutes per week of vigorous-intensity activity, or an equivalent combination, derived by multiplying the reported number of days per minute across intensity categories [27]. Data analysis For the quantitative data, descriptive statistics were used to summarise categorical and continuous variables, which are presented as frequencies, proportions, means (standard deviations), and medians (IQRs), as appropriate. Bidirectional stepwise multivariable logistic regression was performed to examine the associations between therapeutic inertia (binary outcome) and explanatory variables. First, univariate analysis was conducted, and variables with a p-value < 0.15 were included in the multivariate model. The assumptions of logistic regression were tested, including multicollinearity using a variance inflation factor (VIF 0.1). Model fit was assessed using the Hosmer‒Lemeshow goodness-of-fit test (p value = 0.208). A significance level of p < 0.05 was considered statistically significant for multivariate analysis. The results are reported as crude (COR) and adjusted odds ratios (AOR) with 95% confidence intervals (CIs) and corresponding p-values. The SDM score was measured using the 9-item SDM-Q-9 tool, with each item rated on a 6-point Likert scale ranging from 0 (strongly disagree) to 5 (strongly agree), yielding a total score ranging from 0–45. The total score was treated as a continuous variable, and normality was assessed via the Shapiro‒Wilk test. Based on the data distribution, an independent samples t-test was conducted to examine whether there was a statistically significant difference in SDM scores between those with and without inertia. For the qualitative strand, the transcribed data were analysed inductively using thematic analysis, following a six-phase approach [28]. This process included becoming familiar with the data through note-taking during interviews and transcript reviews, developing initial codes, merging codes into categories on the basis of key phrases, common perceptions/factors, and recurring patterns, and finally charting them into themes. The analysis was conducted using NVivo 15 for Windows. A contiguous narrative approach was used for reporting and integrating mixed-method findings, presenting quantitative results followed by qualitative insights, while identifying areas of convergence and divergence. Results Sociodemographic and clinical characteristics of patients with uncontrolled hypertension Among the 110 patients approached, 104 were included in the final analysis. Six patients were excluded: three whose blood pressure was within target levels and three whose blood pressure was less than 90/60 mm Hg. The average age of the participants was 62.3 years (SD = ± 10.5), with a slight majority being female (56.7%). 60% had at least one comorbidity, including type 2 diabetes, dyslipidemia, cerebrovascular disease, chronic kidney disease, and coronary heart disease. 73.1% of individuals reported insufficient physical activity, and the same percentage also indicated low salt intake. The mean systolic blood pressure (SBP) was 148.25 mmHg (SD = ± 15.23), and the mean diastolic blood pressure (DBP) was 89.93 mmHg (SD = ± 10.84). Among the participants, 36.5% had Grade 2 hypertension, and 26.9% had isolated systolic hypertension (ISH). Most (62.5%) patients were on monotherapy, predominantly amlodipine. Notably, self-reported medication adherence was high, with 85.1% of the participants consistently taking their prescribed treatment (Table 1). Table 1 Sociodemographic and clinical characteristics of patients with uncontrolled hypertension ( N = 104) Characteristics Categories N (%) Mean ± S. D Age (in years) ≤ 60 41 (39.4) > 60 63 (60.6) Gender Female 59 (56.7) Education Illiterate 49 (47.1) Primary school certificate 24 (23.1) Middle school 17 (16.3) High school certificate 6 (5.8) Intermediate or Diploma 7 (6.7) Graduate 1 (1.0) Occupation Unemployed/Retired/Homemaker 72 (69.2) Self-employed/Business 13 (12.5) Unskilled 10 (9.6) Semiskilled 7 (6.7) Professional/Skilled worker 2 (1.9) Residence Rural 81 (77.9) BMI Underweight 6 (5.8) Normal 31 (29.8) Overweight 56 (53.8) Obese 11 (10.6) Alcohol consumption Yes 17 (83.7) Smoking status Current 9 (8.7) Former 11 (10.6) Never 84 (80.8) Cardiovascular heredity Yes 38 (36.5) No 53 (51.0) Don’t know 13 (12.5) Comorbidities Type-2 diabetes 56 (53.8) Dyslipidemia 19 (18.3) Cerebrovascular disease 3 (2.9) Chronic renal failure/chronic kidney disease 2 (1.9) Coronary heart disease 6 (5.8) Physical activity Insufficient physical activity 76 (73.1) Reduced salt intake Yes 76 (73.1) Fruit and vegetable intake (Days a week) 1–2 10 (9.6) 3–4 48 (46.2) 5–6 30 (28.8) High sodium intake Never 35 (33.7) Rarely (Once a week or less) 41 (39.4) Sometimes (2–3 times a week) 20 (19.2) Often (4–6 times a week) 7 (6.7) Daily 1 (1.0) High fat intake Never 21 (20.2) Rarely (Once a week or less) 1 (1.0) Sometimes (2–3 times a week) 67 (64.4) Often (4–6 times a week) 15 (14.4) Mean blood pressure Mean systolic blood pressure (SBP) 148.2 ± 15.23 Mean diastolic blood pressure (DBP) 89.9 3 ± 10.84 Stages of hypertension High normal 9 (8.7) Grade 1 24 (23.1) Grade 2 38 (36.5) Grade 3 5 (4.8) Isolated systolic hypertension 28 (26.9) Duration of hypertension (in years) Less than 1 22 (21.2) 1–5 60 (57.7) 6–10 10 (9.6) 11–15 2 (1.9) 16–20 5 (4.8) More than 20 5 (4.8) Number of antihypertensives taken 0 5 (4.8) 1 65 (62.5) 2 29 (27.9) 3 5 (4.8) Commonly used antihypertensives Amlodipine 59 (56.7) Telmisartan 42 (40.4) Atenolol 15 (14.4) Hydrochlorothiazide 4 (3.8) Combination tablets 5 (4.8) Treatment compliance (N = 100) Yes 86 (85.1) Adverse effects Yes 12 (11.5) BMI body mass index, SBP systolic blood pressure, DBP diastolic blood pressure Factors associated with therapeutic inertia A univariate logistic regression analysis was performed to compare hypertensive patients with and without therapeutic inertia, considering sociodemographic, clinical, and treatment-related factors. The analysis revealed that age, education, smoking status, reduced salt intake, comorbidities, continuity of care, stage of hypertension, and SDM score were significant factors (p value < 0.15). In the multivariate analysis, age (AOR 4.36, 95% CI 1.13–16.90), education (AOR = 0.23, 95% CI = 0.05–0.99), comorbidities (AOR = 0.18, 95% CI = 0.04–0.79), stage of hypertension (AOR = 4.81, 95% CI = 1.38–16.70), and the SDM score (AOR = 0.93, 95% CI = 0.88–0.99) were identified as independent predictors of inertia (Table 2). Table 2 Factors associated with therapeutic inertia among patients with uncontrolled hypertension estimated by multivariate logistic regression Variables Therapeutic inertia COR (95% CI) AOR (95% CI) p value No (%) Yes (%) Age (in years) >60 18 (75) 6 (25) Reference Reference ≤60 45 (56.3) 35 (43.8) 2.33 (0.83–6.49) 4.36 (1.13–16.90) 0.032 * Education Literate 9 (16.4) 46 (83.6) Reference Reference Illiterate 15 (30.6) 34 (69.4) 0.44 (0.17–1.13) 0.23 (0.05–0.99) 0.048 * Smoking Never 19 (20) 76 (80) Reference Reference Current 5 (55.6) 4 (44.4) 0.20 (0.05–0.81) 0.22 (0.03–1.50) 0.123 Reduced salt intake Yes 14 (18.4) 62 (81.6) Reference Reference No 10 (35.7) 18 (64.3) 0.40 (0.15–1.06) 0.64 (0.19–2.12) 0.469 Comorbidities No 5 (11.9) 37 (88.1) Reference Reference Yes 19 (30.6) 43 (69.4) 0.30 (0.10–0.89) 0.18 (0.04–0.79) 0.023 * Continuity of care Routine care (PHC/CHC/Private) 20 (27.4) 53 (72.6) Reference Reference Nonroutine care (FDP) 4 (12.9) 27 (87.1) 2.54 (0.79–8.20) 2.20 (0.47–10.31) 0.315 Stage of hypertension Grade 2/Grade 3 15 (34.9) 28 (65.1) Reference Reference High normal/ISH/Grade 1 9 (14.8) 52 (85.2) 3.09 (1.2–7.96) 4.81 (1.38–16.70) 0.013 * SDM score 0.93 (0.90–0.98) 0.93 (0.88–0.99) 0.031 * * Significant values (p < 0.05) COR , crude odds ratio; AOR , adjusted odds ratio; CI , confidence interval; PHC , primary health centre; CHC , community health centre; FDP , family doctor programme; ISH , isolated systolic hypertension; SDM , shared decision-making Shared decision making (SDM) Figure 1 presents the distribution of participant responses across the 9 items of the SDM-Q-9 scale, arranged in descending order based on the level of agreement. Overall, moderate agreement was observed across the SDM-Q-9 items. The highest levels of agreement were seen for the information-related items: Item 1 (doctors made it clear that a BP treatment decision needs to be made) had 39.4% scoring 3 and 33.7% scoring 4, while Item 3 (doctor told me that there are different options for treating my medical condition) had 38.5% scoring 3 and 34.6% scoring 4. In contrast, items reflecting active collaborative decision-making showed considerably lower scores. Items 9 (doctor and I reached an agreement on how to proceed) and 8 (doctor and I selected a treatment option together) each had 16.4% scoring 0 and 27.9% scoring 1, while Item 7 (doctor asked me which treatment option I prefer) had 15.4% scoring 0 and 28.8% scoring 1, indicating limited patient involvement in treatment selection and shared decision-making. The total SDM score was calculated as the sum of all 9 SDM-Q-9 items, with the total scores ranging from 0–45, where higher scores indicated greater shared decision making. The total scores were found to be normally distributed (Shapiro‒Wilk p = 0.247). In this study, the mean total SDM score across all participants was 22.23 ± 11.82. An independent samples t-test revealed a statistically significant difference in mean total SDM scores between patients with and without inertia (p = 0.003). Patients who experienced inertia had a significantly lower mean score of 20.36 ± 11.15 compared to those without inertia (28.4 ± 12.11). The effect size for this difference was medium to large (Cohen’s d = 0.71), indicating that the association between lower SDM and therapeutic inertia is statistically significant and clinically meaningful. Qualitative results We present the findings within each theme from both the patients’ and providers’ perspectives to enable a comprehensive understanding of therapeutic inertia. Supplementary file 3 describes the characteristics of the medical officers and patients involved in the in-depth interviews. Theme 1: Patient beliefs and perceptions shape treatment decisions Patients expressed beliefs about the efficacy, safety, and long-term consequences of medication prescribed through government facilities that strongly influenced their willingness to initiate, continue, or intensify treatment for hypertension. One of the major concerns was the perceived ineffectiveness of government medicines. Patients frequently reported that, despite regular consumption, their blood pressure levels remained uncontrolled. In addition, patients expressed concerns related to the quality of medicines and the accuracy of dose strength in government facilities. As a result, many patients chose to discontinue treatment or switch to private medicines despite the higher cost. “No, the government medicines don’t work well...it doesn’t suit me; BP levels have not come down. I am thinking of shifting to CMC (private provider).” (Patient 7) Furthermore, treatment burden was identified as a significant barrier. Patients, especially those with coexisting diabetes and hypertension, reported difficulties in managing complex regimens involving multiple tablets. Due to the burden of multiple medicines, patients resisted the addition of new medicines even when BP remained uncontrolled. “Here, in the government, they give 5 tablets for sugar due to low doses, and in total, in one day, I take 8 tablets, which is very difficult, but in private, it is only 1–1 tablet for BP and sugar.” (Patient 8) Patients also reported concerns about lifelong medication use and its potential side effects, particularly kidney damage. These fears contributed to a preference for lifestyle modification over initiating or escalating treatment. “Most are okay with lifestyle modifications, but they don’t want tablets. They’ll say, ‘Let’s wait one more month, I’ll follow diet and exercise strictly, then you can start medicines.’ They don’t want lifelong treatment and prefer managing with diet alone.” (Provider 3). Theme 2: Lifestyle habits and resistance to behaviour change Lifestyle habits, particularly dietary preferences, smoking and physical activity, were central to both patient narratives and providers’ perspectives. These behaviours often pose challenges to hypertension control and contribute to inertia when providers choose to delay the initiation or intensification of treatment for two reasons: first, they believe that lifestyle changes might bring BP under control, and second, they feel that initiating or escalating treatment despite resistance to behaviour change is meaningless. Salt consumption and food preferences emerged as major barriers that patients found difficult to modify. “When I eat rice items like curd rice or something else, I need pickle compulsorily.” (Patient 2) Providers acknowledged this resistance: “Everybody wants to eat salt. They are not up to their mark. In fact, even when I tell them they are not understanding my point. This is a major problem. If they do not follow the diet, no point in adding medicines.” (Provider 2) Physical activity was also limited for many, either because of safety concerns or the belief that occupational work provided sufficient exercise. Substance use, particularly smoking and alcohol, was one domain in which providers described frustration over patients’ inability to change. “Yeah, I walk a mile every day right for work. That’s it. That’s my physical activity” (Patient 1) “Smoking and alcohol how much ever I tell, they are not changing. Maybe 1 percent are trying to change.” (Provider 5) Theme 3: Fragmented care, multiple care providers and conflicting treatment plans Patients frequently navigated between multiple sources of care, including government, private and other informal providers. This disrupted treatment continuity and hindered the ability to make timely, consistent treatment adjustments. Several patients reported using government services only for BP monitoring while relying on private providers for medication. In such cases, government medical officers were reluctant to intensify treatment without knowing the full regimen. “Some patients come just for check-ups without their private medicines. If their BP is high, we ask them to bring their medications for review and may adjust the dosage using government drugs. While some stick to private prescriptions despite high readings, some agree to switch or follow up with their doctor when explained.” (Provider 4) Adding to this complexity was the conflicting guidance patients received from different providers, which led to confusion and doubt, causing them to take medications prescribed by various physicians simultaneously. This inconsistency in medical advice left patients uncertain about whose guidance to follow, resulting in delays in adopting or adjusting in case of altered treatment. “Those (Chittoor GH) doctors tell don’t take these medicines; take the ones we are prescribing. It is confusing, so I take both medicines, the one they have prescribed (Chittoor GH) and the one these people (PHCs) have prescribed.” (Patient 3). In cases of polypharmacy, providers delayed treatment adjustments to avoid duplication or drug interaction, reinforcing inertia despite persistent uncontrolled blood pressure. Theme 4: Provider caution and clinical judgement delaying treatment intensification Providers frequently described therapeutic decisions as a deliberate process shaped by clinical judgement. Several providers stated that treatment escalation was avoided or delayed, especially in patients with borderline hypertension, and preferred to observe patients over multiple readings and prescribe lifestyle modifications before treatment intensification. In addition, the perceived risk of overtreatment and fear of hypotension in patients, especially those with borderline BP, has raised concerns for clinicians, particularly those working in agricultural fields. “If it is persistently more than 150 even after their diet and lifestyle modification, then I will double the dose. Otherwise, diet and lifestyle are my main treatment.” (Provider 5) “If we intensify, they might go to a hypotensive state, 110/70, working people in the sun, so it might be a problem, so we are not intensifying the treatment for those people who are diagnosed and whose BP levels are 130/80.” (Provider 4). Moreover, decisions concerning treatment intensification were influenced by age and comorbidities, as providers reported being more aggressive in initiating or intensifying treatment in high-risk patients, such as those with diabetes, but exercised caution in low-risk younger patients. “For borderline BP in patients with existing disease, I feel it’s better to start treatment immediately; they’re already at risk.” (Provider 4) “For younger patients, we follow a thorough check, including serum creatinine, lipid profile and, if eligible, thyroid profile. For older patients, we avoid risk; if there is no concerning family history, we start CCB.” (Provider 1) Theme 5: Interruption in follow-up, referrals and medication adherence as drivers of therapeutic inertia Follow-up care emerged as a major challenge, as several providers described low rates of return among patients after initial diagnosis and medication initiation, with visits often occurring only when medication was over. “Follow-up is the most difficult part. Patients do not return on time; they return only after the medicines are over. Out of those diagnosed, only 1–5% come for regular check-ups.” (Provider 4) Referral practices also influence inertia. Healthcare staff at the sub-centres fail to refer patients with Grade 2 or 3 hypertension unless they complained of any symptoms or when complications were present. Even when referrals were made to higher centres, providers noted that many patients did not follow through. These delays in referral and regular follow-up meant that patients often remained on the same regimen for extended periods without intensification despite persistent uncontrolled blood pressure. “At the village level, unless the patient complains, they (CHO) don’t usually call or refer even if BP is 170/90. Only when symptoms such as severe headache occur, they contact us to escalate treatment. We then adjust the dose on the basis of previous treatment. When patients visit us, and we observe abnormal values, we advise them to visit Chittoor GH, but very few go.” (Provider 4) Providers expressed concerns about regular intake of medicines, noting that patients took their medications only when symptomatic. Poor medication adherence was cited as a major reason for non-intensification of treatment by the providers. In contrast, almost all patients reported high adherence, especially when medicines were provided free of cost and were conveniently available. “I will see whether they are telling right or wrong first, I will decide, and then only change the drug, the patient never says the truth.. they always say that they are taking the medicines regularly..”(Provider 7) “No, no, I never miss taking my medicines… I take my BP tablets regularly.” (Patient 6) The above factors led to inertia by creating a lack of consistent feedback mechanisms to verify adherence or track follow-up, often leading to provider uncertainty and cautious treatment decisions. Theme 6: Systemic barriers to workforce availability at FDP and drug limitations contribute to therapeutic inertia Therapeutic inertia was not solely a result of patient behaviour or provider decision-making but also stemmed from systemic barriers, particularly the non-availability of doctors at FDP and the limited availability of appropriate antihypertensive medications. Several patients reported that they were rarely seen by a doctor during follow-up visits, especially at FDPs. Instead, clinical encounters were often managed by an ANM (Auxiliary Nurse Midwife) or a CHO (Community Health Officer). This lack of clinical authority led to delays in treatment adjustment, as the staff without prescribing authority and a lack of teleconsultation often continued the same medication without escalation, despite uncontrolled BP. “Where is the doctor? These people (CHO, ANM) here are only doctors..The big doctor comes very rarely to the FDP.” (Patient 4) “Doctors are scarce now. Earlier, there were separate doctors for 104 and OP at PHCs, but now they’ve limited everything. Many doctors leave for PG, so buffer doctors are not sufficient.” (Provider 6) Providers also reported challenges in tailoring treatment due to a lack of suitable drug formulations in the public supply. For example, when a lower starting dose was needed, such as telmisartan 20 mg or hydrochlorothiazide 12.5 mg, providers were forced to split the existing dosage and administer half of the available amount. These limitations reduced the provider’s ability to adjust regimens effectively, especially for patients with borderline readings. "If BP is borderline (140/90 or 150/90), we recommend half a 40 mg telmisartan tablet. For higher BPs, we provide the full dose. Hydrochlorothiazide's 25 mg tablet is difficult to split, and the full dose can lead to dehydration." (Provider 4) Aside from the concerns mentioned above, providers reported the availability of adequate classes of drugs at public facilities, except for a few emergency drugs, such as labetalol, which are prescribed specifically during pregnancy-induced hypertension. Theme 7: Limited provider-patient interaction and shared decision-making While many patients described consultations marked by limited engagement with providers, there were a few instances in which patients expressed positive experiences in their involvement in decision-making, highlighting wide variability in interactions across facilities. Some providers acknowledged their own biases regarding shared decision making, expressing the belief that doctors are better equipped to make treatment decisions. Despite this, they reported making efforts to involve patients, particularly during treatment initiation or when managing borderline values. “When we are initiating drugs or when sugar is borderline, I give the choice: ‘Do you want to start now or wait?’ and let them decide. They are not that educated... maybe we are biased that we make better decisions than them.. maybe I’m wrong.” (Provider 5) From the patient’s perspective, some described positive, respectful interactions where providers actively asked about symptoms and offered guidance, whereas others felt dismissed or ignored, especially at the FDP, owing to the lack of doctors, as highlighted earlier. “Yeah, the staff is good. Therefore, when I had come here, the doctor scolded me and said, “You have a very high BP.. why have you kept it that way?” and so many other questions were asked.” (Patient 1) “In government hospitals, they don’t see patients properly.. they keep looking at their phone and don’t even ask what the issue is.” (Patient 9) Together, these narratives show that while some providers attempt shared decision making, systemic barriers and, at times, individual attitudes lead to one-sided consultations with minimal space for patient input. This may undermine trust and reduce patient motivation to follow through with treatment, ultimately contributing to delays in treatment intensification. Discussion This study contributes to a better understanding of therapeutic inertia in hypertension patients within various tiers of government primary care facilities. The results offer insights into how individual-level factors and systemic barriers significantly impact treatment decisions, often leading to therapeutic inertia. We found that the prevalence of therapeutic inertia in this study was 76.9%, indicating that in more than three-quarters of the patients with uncontrolled BP, the treatment was neither initiated nor intensified. This finding is consistent with global estimates reported in studies from Ethiopia (72%) [23] and Spain (75%) [29] but is notably higher than those reported in countries such as the UK (33.1%) [30] and Malaysia (38.6%) [31]. The variations in prevalence across different countries may be attributed to differences in resource availability, healthcare delivery models, and the extent of physician awareness and adherence to clinical protocols. We identified several challenges contributing to therapeutic inertia from both patient and provider perspectives. Two major factors include the reluctance of providers to intensify treatment in borderline cases and the insufficient involvement of patients in shared decision-making processes regarding their care. Additional significant contributors include patients' beliefs and perceptions about hypertension treatment, resistance to lifestyle modifications, fragmented care, conflicting advice from multiple healthcare providers, interruptions in follow-up and referrals, and the limited availability of physicians at the FDP. Primary drivers of therapeutic inertia In our study, patients with high-normal, ISH, or Grade 1 hypertension were found to be 4.8 times more likely to experience therapeutic inertia than those with Grade 2 or Grade 3 hypertension, making it the strongest predictor of inertia. This was strongly supported by the qualitative findings, where physicians described a deliberate, cautious “wait-and-watch approach” toward treatment intensification in borderline cases. Many providers preferred to recommend lifestyle modification first and monitor subsequent readings, particularly in outdoor labourers, where there was a concern of hypotension. This delay in intensification was framed not as an oversight but as a calculated clinical decision. Our findings align with those of previous studies that reported similar reasons [23,32,33]. Additionally, shared decision-making in hypertension management was explored through the SDM-Q-9 questionnaire and qualitative interviews. The mean total SDM score was 22.23 ± 11.82 out of 45, and patients who experienced therapeutic inertia had scores that were, on average, 8 points lower. A one-point increase in the SDM score reduced the odds of inertia by 7%, indicating an inverse relationship. Qualitative interviews revealed that some patients experienced limited engagement, often due to the absence of doctors, which are missed opportunities for engaging with patients to make shared treatment decisions, thereby delaying treatment adjustments and reducing follow-up motivation. When doctors are present, providers themselves acknowledge that SDM is inconsistently applied. Other clinical and patient-related drivers of therapeutic inertia Age and comorbidities were significantly associated with therapeutic inertia. Patients aged ≤ 60 years were 4.36 times more likely to experience inertia than those who were > 60 years. This was supported by qualitative findings, where physicians intensified treatment in older patients owing to perceived higher risk. This contradicts current hypertension guidelines, which recommend more aggressive action in younger patients, especially those ≤ 60 years. This finding diverges from those of previous studies that reported greater therapeutic inertia among older adults [32,34–36]. These inconsistencies underscore the need for enhanced provider training and the dissemination of updated hypertension management guidelines, particularly regarding age-specific treatment decisions. In contrast, the presence of comorbidities was associated with an 82% reduction in inertia, which is consistent with provider narratives where patients with diabetes or other comorbidities were often treated more aggressively. This finding aligns with prior literature suggesting that clinicians act when the perceived risk of complication is high [32,33]. Another significant challenge was resistance to lifestyle change, which emerged as a key factor in the qualitative strand. Patients frequently reported high salt consumption and low physical activity, and in certain cases, use alcohol and tobacco, often viewing them as difficult to change. For providers, this persistent non-adherence offered a rationale for delaying treatment intensification, reflected in sentiments such as “ no point in intensifying if they will not change their diet,” suggesting that lifestyle-related barriers reinforce inertia. A few important factors emerged from the qualitative interviews, but were not identified as predictors in the quantitative analysis. Treatment burden, particularly among patients with both diabetes and hypertension, was frequently mentioned. Although the number of drugs used was not significantly associated with inertia, patients reported feeling overwhelmed by polypharmacy and resisted the addition of new medications. Providers echoed this, expressing reluctance to intensify treatment owing to concerns about intolerance and non-compliance. These findings align with earlier studies highlighting the impact of polypharmacy on inertia [23,31]. Another factor was medication adherence. Quantitatively, adherence was high, with 85% self-reported compliance, and nearly all patients confirmed regular intake during in-depth interviews. In contrast, it was not significantly associated with therapeutic inertia in the regression analysis. Moreover, some providers expressed distrust in patients’ self-reports, influencing their hesitation to change treatment. This has also been noted in previous studies [33]. These findings suggest that even when patient-reported adherence is high, perceived non-adherence by providers may still drive inertia. Systemic barriers to therapeutic inertia In addition to patient- and provider-level barriers, several systemic constraints contribute to therapeutic inertia. A major challenge was the lack of physician availability at the FDPs, which emerged through both field observations and qualitative interviews. FDPs, held monthly in villages, often operate without a regular physician presence, leaving patients dependent on CHOs to continue medication without clinical review or dose titration. In many cases, treatment decisions were delayed, and medications were distributed without adjustments, with teleconsultation options also not being utilised. Patients who relied solely on FDPs and were unable to visit PHCs or higher centres were particularly vulnerable to prolonged periods of uncontrolled hypertension. In this context, inertia appeared systemic and was embedded in staffing patterns rather than the decisions of individual providers. Together, these findings highlight the pressing need for coordinated multilevel strategies to combat therapeutic inertia in hypertension management. For providers, it is crucial to integrate training modules on this issue into NP-NCD programs for MOs, particularly those focused on borderline hypertension. These should emphasise adherence to protocols for adjusting treatment and include case-based simulations and SDM skills to facilitate timely intervention. While SDM is not yet widespread in India, its inclusion in clinical training could improve patient engagement and mitigate inertia. Moreover, strengthening the capacity of frontline workers, i.e., ASHAs, ANMs, and CHOs, is essential. Training should cover basic BP assessment, uncontrolled hypertension identification, and referral criteria. Culturally relevant health communication methods, including short videos and group counselling sessions, can encourage patients to adopt healthier lifestyle changes. Additionally, engaging community leaders and caregivers can foster better patient adherence and follow-up. At a systemic level, it is vital to improve the availability of the healthcare workforce, particularly by ensuring the regular presence of doctors at FDPs, facilitating timely adjustments to treatment and ensuring continuity of care. By adopting these strategies, we can enhance the responsiveness of primary care to the growing challenge of NCDs and strengthen blood pressure management within India’s primary healthcare system. There are certain limitations to this research that must be acknowledged. Although definitions of therapeutic inertia exist in the literature, there is no universally accepted operational standard in practice. Some instances of inertia identified in this study may represent apparent rather than true inertia, particularly when providers choose to wait for subsequent readings, schedule follow-up prior to modifying medicines, or when a treatment change would have been made during earlier consultations. This ambiguity in classification highlights the need for clearer criteria to reduce overestimation or underestimation of true inertia. Certain quantitative variables (e.g., self-reported adherence and side effects) may not fully capture clinical nuances, leading to potential misclassification. Finally, as a cross-sectional study, this work captures inertia at a single time point and does not assess how therapeutic inertia evolves or resolves over time. Conclusion Overall, this study demonstrates that therapeutic inertia is not solely the result of clinical oversight, as often reported in previous literature, but rather emerges as a complex interplay of patient behaviours, provider reasoning, and systemic constraints. In the Indian context, where this concept remains underexplored, our study provides a comprehensive understanding of the extent and underlying drivers of inertia in hypertension management. The implications of these findings extend beyond hypertension to other chronic conditions that require long-term management, such as diabetes, chronic kidney disease, and other cardiovascular diseases, where therapeutic inertia similarly hampers outcomes. These findings underscore the need for longitudinal research to evaluate the impact of inertia on long-term blood pressure control and cardiovascular outcomes, as well as intervention-based research focusing on therapeutic inertia across various chronic conditions. A comprehensive health system approach to addressing inertia can strengthen the management of chronic diseases under the NP-NCD framework. Abbreviations AHA Antihypertensive agent ANM Auxiliary Nurse Midwife AOR Adjusted odds ratio ASHA Accredited Social Health Activist BP Blood pressure CHC Community Health Centre CHO Community Health Officer CI Confidence interval COR Crude odds ratio DBP Diastolic blood pressure ESC European Society of Cardiology ESH European Society of Hypertension FDP Family Doctor Programme IHCI India Hypertension Control Initiative IQR Interquartile range ISH Isolated systolic hypertension MMU Mobile Medical Unit MO Medical Officer NCD Non-communicable disease NFHS-5 National Family Health Survey-5 NPCDCS National Programme for Control of Diabetes, Cancers and Stroke NP-NCD National Programme for Non-Communicable Diseases PHC Primary Health Centre SBP Systolic blood pressure SC Sub-Centre SDM Shared decision making UPHC Urban Primary Health Centre VIF Variable inflation factor WHO World Health Organisation Declarations Ethical approval and consent to participate The study was approved by the Institutional Ethics Committee (IEC) of the Indian Institute of Public Health, Gandhinagar (IIPHG) (IIPHGIEC/2024-25/21–33) and the Institutional Review Board (IRB) of Christian Medical College (CMC, Vellore) (IRB Min. No. 2502132). The study was conducted in accordance with the Declaration of Helsinki. Participation in both the quantitative and qualitative strands was voluntary, and written informed consent was obtained from all participants before data collection. Confidentiality and anonymity were maintained throughout. For the qualitative strand, audio-recorded interviews and transcripts were encrypted and securely stored. Exit interviews also ensured that participants’ identities remained confidential. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding The authors declare that no form of funding was received for this study. Author Contribution The study was conceptualised and designed by SK and DL. SK collected and analysed the data, and, along with DL, interpreted the findings. All the authors were involved in drafting the manuscript and revising its content. Each author approved the final manuscript. 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Additional Declarations No competing interests reported. Supplementary Files Supplementaryfile1.docx Supplementaryfile3.docx Supplementaryfile2.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 21 Jan, 2026 Editor invited by journal 25 Dec, 2025 Editor assigned by journal 23 Dec, 2025 Submission checks completed at journal 23 Dec, 2025 First submitted to journal 21 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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07:14:07","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":123662,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8418875/v1/1e8ea0d6f4288a4869c8d493.html"},{"id":101067703,"identity":"449e78ab-ebd0-4f11-8f17-3711cd0e3a1e","added_by":"auto","created_at":"2026-01-25 07:14:07","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":147998,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of responses to the nine items of the SDM-Q-9\u003c/p\u003e\n\u003cp\u003eHeatmap illustrating the distribution of responses for each SDM-Q-9 item across a 6-point Likert scale (0 = strongly disagree to 5 = strongly agree), where higher scores indicate greater involvement in the decision-making process. The items are arranged in descending order of agreement to show which items received higher and lower ratings across the SDM-Q-9. The cell values represent the percentage of participants selecting each score for each item. Shading differentiates low and high response percentages, with darker shades indicating a higher concentration of responses within a given score category. This allows for a visual comparison of which shared decision-making items were more or less consistently experienced by participants.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8418875/v1/327ade6b1863a89c455a2d38.jpg"},{"id":101297208,"identity":"5c65f601-78d2-4c3d-8db1-7a6b08822f96","added_by":"auto","created_at":"2026-01-28 09:25:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1505335,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8418875/v1/10b2716c-8f9d-4aa6-bc91-bfbe7144d1f8.pdf"},{"id":101067701,"identity":"f24d3e51-d8ea-4849-900d-243823824298","added_by":"auto","created_at":"2026-01-25 07:14:06","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":39491,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8418875/v1/6e6fa242b16c86bdf7471064.docx"},{"id":101067709,"identity":"fe2a934b-51e9-4f23-a5d7-09735e527487","added_by":"auto","created_at":"2026-01-25 07:14:07","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":17705,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile3.docx","url":"https://assets-eu.researchsquare.com/files/rs-8418875/v1/cd0d93bfd119816b5c152277.docx"},{"id":101067704,"identity":"63bdf0ad-3b9b-447f-8fe4-9be7fc21f6dc","added_by":"auto","created_at":"2026-01-25 07:14:07","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":26355,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8418875/v1/54b73b5321249d95d170fe69.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Understanding Therapeutic Inertia in the Management of Hypertension in Primary Care: Examining Contributing Factors at the Patient and Provider Levels in Chittoor District, Andhra Pradesh, India – A Mixed Methods Study","fulltext":[{"header":"Background","content":"\u003cp\u003eAccording to the World Health Organisation (WHO), non-communicable diseases (NCDs) are responsible for 41\u0026nbsp;million deaths annually, accounting for 74% of all deaths globally. Among these, cardiovascular diseases contribute to 17.9\u0026nbsp;million deaths, representing approximately one-third of total NCD-related fatalities worldwide [1]. Hypertension, the leading metabolic risk factor for cardiovascular diseases, affects an estimated 1.4\u0026nbsp;billion adults aged 30\u0026ndash;79 years globally, with approximately two-thirds of those affected residing in low- and middle-income countries [2].\u003c/p\u003e \u003cp\u003eIn India, NCDs contribute to approximately 5.87\u0026nbsp;million deaths annually, accounting for 60% of all deaths and representing over two-thirds of total NCD-related deaths in the WHO Southeast Asia region [3]. Cardiovascular diseases, including coronary artery disease, stroke, and hypertension, account for 45% of all NCD-related deaths [4]. According to the Fifth National Family Health Survey (NFHS-5), the age-standardised prevalence of hypertension in India is 28.1% (95% CI, 27.9%-28.3%). Furthermore, among those with diagnosed hypertension, less than one-fourth achieve target control of their blood pressure (BP) [5].\u003c/p\u003e \u003cp\u003e Guidelines for the management of hypertension focus on reducing cardiovascular risk factors and achieving optimum BP through a combination of lifestyle modification and appropriate use of antihypertensive drugs [6]. Patients who adhere to antihypertensive medication are more likely to achieve optimal BP control, resulting in a reduced risk of adverse outcomes [7]. This adherence leads to a 40% reduction in stroke risk and a 30% reduction in cardiovascular mortality [8]. Achieving better control of hypertension is crucial for reducing cardiovascular morbidity and mortality.\u003c/p\u003e \u003cp\u003eSeveral factors contribute to the poor control of hypertension, which can be broadly classified into patient-related, provider-related, and health system-related factors. Among patient-related issues, non-adherence to medication is the most significant challenge for achieving optimal BP control. However, nearly half of the challenges in managing hypertension arise from provider-related factors, with therapeutic inertia recognised as the primary cause of uncontrolled hypertension [9,10].\u003c/p\u003e \u003cp\u003eTherapeutic inertia, also referred to as clinical inertia, is defined \u0026ldquo;as the failure to initiate or intensify therapy when therapeutic goals of hypertension are not met\u0026rdquo; [11]. This concept can be summarised as \u0026ldquo;recognition of the problem, but failure to act.\u0026rdquo; Several studies have shown that therapeutic inertia in managing hypertension and other chronic conditions, such as dyslipidemia and diabetes, contributes to 80% of heart attacks and strokes [12]. Phillips identified three key reasons for therapeutic inertia: overestimating the quality of care, feeling that control has improved, and being close to the target. Additionally, a lack of training in achieving treatment targets contributes to this issue [13]. The India Hypertension Control Initiative (IHCI), a multi-partner initiative implementing and scaling public health hypertension control programs in India, identified therapeutic inertia as one of the major factors contributing to suboptimal control of BP, emphasising the importance of understanding the phenomenon and the influencing factors better, especially in the Indian context, to improve hypertension management in primary care settings [14].\u003c/p\u003e \u003cp\u003eDespite the growing burden of hypertension and evidence of suboptimal control in India, there is limited research investigating why therapeutic inertia persists. Furthermore, the role of shared decision-making (SDM) in influencing treatment initiation or intensification remains underexplored. In this study, we aimed to identify factors contributing to therapeutic inertia in the management of hypertension among patients attending primary care facilities in the Chittoor district, with a focus on SDM. We also aimed to understand, from both patient and provider perspectives, the barriers to treatment intensification.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eWe employed a convergent parallel mixed-methods design to achieve a comprehensive and in-depth understanding of therapeutic inertia, enabling a rich interpretation through data triangulation. A mixed methods study is characterised by the integration of both qualitative and quantitative data at various stages of the research process, including data collection, analysis, and interpretation [15]. In our study, both quantitative and qualitative data were collected concurrently, and they were given equal weights. After collection, we analysed the data from both strands simultaneously and separately. Finally, the results were integrated for meaningful interpretation.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy setting and context\u003c/h3\u003e\n\u003cp\u003eThe study was conducted in Chittoor, one of the 26 districts in the southern Indian state of Andhra Pradesh. Health care services for hypertension in this district are delivered through both the public and private health sectors. In the public sector, services are offered at District Hospitals, Community Health Centres (CHCs), Primary Health Centres (PHCs) and Sub-centres (SCs). The PHC and SC form the primary level of the health care system. The rural PHC, typically staffed by a medical officer, caters to a population of 20,000\u0026ndash;30,000, while the urban PHC (UPHC) is established for every 50,000 population, and is located close to urban slums. Chittoor district has 48 rural PHCs and 13 urban PHCs spread across its 31 Mandals (sub-district divisions). CHCs, which serve as the first referral unit for every 80,000\u0026ndash;1,20,000 people, offer multiple specialised services [16].\u003c/p\u003e \u003cp\u003eTo strengthen the response to NCDs, the government of India launched the National Programme for Control of Diabetes, Cancers and Stroke (NPCDCS) in 2010. This initiative was later broadened and renamed as the National Programme for Prevention and Control of Non-Communicable Diseases (NP-NCD) [17]. Under this programme, NCD clinics have been established at CHCs and district hospitals to provide care for conditions such as hypertension and diabetes. In addition, the government of Andhra Pradesh introduced the Family Doctor Programme (FDP) [18], a novel initiative aimed at delivering health services to the rural population at their doorstep. Under this programme, each PHC is provided with two medical officers (MOs). One MO is assigned to 6\u0026ndash;7 SCs and visits each one once a month to provide medical services, while the other MO manages outpatient duties at the PHC. The services are further supported by 104 mobile medical units (MMUs), with NCD screening and management being among the major services offered.\u003c/p\u003e \u003cp\u003eFor our study, we focused on FDP centres, PHCs, and CHCs, as therapeutic decisions for the management of hypertension are actively made at these facilities, and patients are followed up at this level, making them suitable for understanding therapeutic inertia.\u003c/p\u003e\n\u003ch3\u003eStudy participants and sampling\u003c/h3\u003e\n\u003cp\u003e In the quantitative strand, we used a stratified purposive sampling approach to select 15 primary care facilities, including 8 rural PHCs, 5 urban PHCs, and 2 CHCs, all of which were based on their high volume of hypertension cases, while ensuring proportional representation. Among the selected facilities, a consecutive sampling method (total enumerative sampling) was used to recruit eligible patients. All patients meeting the inclusion criteria were approached consecutively during clinic hours until the facility sampling target was achieved. The inclusion criteria were all adult patients aged 18 years and above with a documented diagnosis of hypertension for at least six months, whose blood pressure was measured specifically by an electronic or digital BP monitor during the consultation. Patients whose blood pressure readings were at a therapeutic target (SBP\u0026thinsp;\u0026lt;\u0026thinsp;140 mmHg or DBP\u0026thinsp;\u0026lt;\u0026thinsp;90 mmHg for general patients; SBP\u0026thinsp;\u0026lt;\u0026thinsp;130 mmHg or DBP\u0026thinsp;\u0026lt;\u0026thinsp;80 mmHg for those with diabetes; history of stroke; chronic kidney disease), those whose blood pressure was measured via a manual blood pressure monitor, minors, individuals who were too ill to complete the interview, and those who refused to provide consent were excluded.\u003c/p\u003e \u003cp\u003eThe sample size was calculated using the single population proportion formula, which assumes a 50% prevalence of therapeutic inertia as a conservative estimate to ensure adequate power due to the absence of previous studies in the Indian context that utilised a standardised questionnaire to assess therapeutic inertia. A 95% confidence level (Z\u0026thinsp;=\u0026thinsp;1.96) was used, with an absolute precision of 10% for a hypertensive population in the Chittoor district of approximately 4,79,284. An anticipated non-response rate of 10% was considered, resulting in a final sample size of 110 patients.\u003c/p\u003e \u003cp\u003eFor the qualitative strand, we used a purposive sampling strategy to select hypertensive patients, who were a subset of the quantitative sample. The participants were selected to ensure diversity in age, sex, education level, duration of hypertension, presence of cardiovascular risk factors, comorbidities, and treatment preferences. Medical officers were purposively selected on the basis of their current role in primary care settings, with a minimum of one year of experience and involvement in managing hypertension. Variation in age, years of experience, training, and experience in hypertension management were also considered during selection. Recruitment continued until data saturation was achieved [19]. A total of 9 patients and 8 medical officers were enrolled in the qualitative analysis.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eFor the quantitative strand, we used a structured, cross-sectional questionnaire comprising 5 sections (see Supplementary file 1): (i) sociodemographic and anthropometric details, (ii) cardiovascular risk factors and comorbidities, (iii) dietary and physical activity behaviour based on the WHO stepwise approach to NCD risk factor surveillance [20], (iv) consultation and treatment details, and (v) shared decision making measured via the SDM-Q-9 tool [21], which has been validated in the Indian context [22].\u003c/p\u003e \u003cp\u003eThe questionnaire was developed in English and then translated into local languages (Telugu and Tamil), followed by back-translation to ensure linguistic and cultural appropriateness. Content validity was established through expert review by a panel consisting of a community medicine specialist, a primary care physician, and a behavioural science expert. The tool was pilot tested on 10% of the estimated sample, and face validity was assessed. Minor revisions were made on the basis of the pilot findings to improve clarity. The data collected through Kobo Toolbox was exported to Excel 2021 for cleaning, then coded and analysed using SPSS\u0026reg; version 27.0 for Windows.\u003c/p\u003e \u003cp\u003eFor the qualitative strand, we conducted in-depth interviews in April and May 2025, utilising a semi-structured interview guide (see Supplementary file 2). This guide was designed using a funnelling technique beginning with introductory questions and then progressing to more specific thematic questions. For hypertensive patients, the guide explored their experiences with managing the condition, adhering to treatment and participating in decision-making. For medical officers, it addressed hypertension management practices, treatment decisions for uncontrolled hypertension, patient engagement in shared decision making, and barriers to treatment intensification. The interviews were held in consultation rooms and other private spaces within healthcare facilities. All interviews were audio recorded with consent, and field notes were made immediately after each interview. Verbatim transcription was performed for all the interviews. The average duration was 17 minutes for patients and 32 minutes for medical officers, with the overall duration ranging from 13\u0026ndash;40 minutes.\u003c/p\u003e\n\u003ch3\u003eOutcome measures\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eOutcome measures\u003c/div\u003e \u003cp\u003eThe primary binary outcome variable is therapeutic inertia. Therapeutic inertia was recognised on the basis of 3 major criteria: (i) uncontrolled BP at the time of consultation (SBP\u0026thinsp;\u0026gt;\u0026thinsp;or =\u0026thinsp;140 or DBP\u0026thinsp;\u0026gt;\u0026thinsp;or =\u0026thinsp;90 mmHg in all patients; SBP\u0026thinsp;\u0026gt;\u0026thinsp;or =\u0026thinsp;130 or DBP\u0026thinsp;\u0026gt;\u0026thinsp;or =\u0026thinsp;80 in patients with diabetes or stroke); (ii) no initiation or intensification of treatment during the particular consultation (no change in dose or medication addition); and (iii) inappropriate deintensification without justification [23,24].\u003c/p\u003e \u003cp\u003eThe point prevalence of therapeutic inertia was calculated using the following formula:\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn addition to the primary outcome, selected explanatory variables were operationally defined. The blood pressure classification followed the European Society of Cardiology and European Society of Hypertension (ESC/ESH) 2023 guidelines [25], with high normal defined as SBP 130\u0026ndash;139 mmHg and/or DBP 85\u0026ndash;89 mmHg; grade 1 hypertension defined as SBP 140\u0026ndash;159 mmHg and/or DBP 90\u0026ndash;99 mmHg; grade 2 hypertension defined as SBP 160\u0026ndash;179 mmHg and/or DBP 100\u0026ndash;109 mmHg; grade 3 hypertension defined as SBP\u0026thinsp;\u0026ge;\u0026thinsp;180 mmHg and/or DBP\u0026thinsp;\u0026ge;\u0026thinsp;110 mmHg; and isolated systolic hypertension defined as SBP\u0026thinsp;\u0026ge;\u0026thinsp;140 mmHg with DBP\u0026thinsp;\u0026lt;\u0026thinsp;90 mmHg. Treatment compliance was assessed using the pill count method and defined as adherent when \u0026ge;\u0026thinsp;80% of prescribed doses had been taken, which was calculated on the basis of the number of pills dispensed minus the number remaining at follow-up [26]. Physical activity was classified as sufficient if participants engaged in \u0026ge;\u0026thinsp;150 minutes per week of moderate-intensity activity, \u0026ge; 75 minutes per week of vigorous-intensity activity, or an equivalent combination, derived by multiplying the reported number of days per minute across intensity categories [27].\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eFor the quantitative data, descriptive statistics were used to summarise categorical and continuous variables, which are presented as frequencies, proportions, means (standard deviations), and medians (IQRs), as appropriate. Bidirectional stepwise multivariable logistic regression was performed to examine the associations between therapeutic inertia (binary outcome) and explanatory variables. First, univariate analysis was conducted, and variables with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.15 were included in the multivariate model. The assumptions of logistic regression were tested, including multicollinearity using a variance inflation factor (VIF\u0026thinsp;\u0026lt;\u0026thinsp;10) and tolerance (\u0026gt;\u0026thinsp;0.1). Model fit was assessed using the Hosmer‒Lemeshow goodness-of-fit test (p value\u0026thinsp;=\u0026thinsp;0.208). A significance level of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant for multivariate analysis. The results are reported as crude (COR) and adjusted odds ratios (AOR) with 95% confidence intervals (CIs) and corresponding p-values.\u003c/p\u003e \u003cp\u003eThe SDM score was measured using the 9-item SDM-Q-9 tool, with each item rated on a 6-point Likert scale ranging from 0 (strongly disagree) to 5 (strongly agree), yielding a total score ranging from 0\u0026ndash;45. The total score was treated as a continuous variable, and normality was assessed via the Shapiro‒Wilk test. Based on the data distribution, an independent samples t-test was conducted to examine whether there was a statistically significant difference in SDM scores between those with and without inertia. For the qualitative strand, the transcribed data were analysed inductively using thematic analysis, following a six-phase approach [28]. This process included becoming familiar with the data through note-taking during interviews and transcript reviews, developing initial codes, merging codes into categories on the basis of key phrases, common perceptions/factors, and recurring patterns, and finally charting them into themes. The analysis was conducted using NVivo 15 for Windows.\u003c/p\u003e \u003cp\u003eA contiguous narrative approach was used for reporting and integrating mixed-method findings, presenting quantitative results followed by qualitative insights, while identifying areas of convergence and divergence.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003eSociodemographic and clinical characteristics of patients with uncontrolled hypertension\u003c/h2\u003e\n \u003cp\u003eAmong the 110 patients approached, 104 were included in the final analysis. Six patients were excluded: three whose blood pressure was within target levels and three whose blood pressure was less than 90/60 mm Hg. The average age of the participants was 62.3 years (SD\u0026thinsp;=\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5), with a slight majority being female (56.7%). 60% had at least one comorbidity, including type 2 diabetes, dyslipidemia, cerebrovascular disease, chronic kidney disease, and coronary heart disease. 73.1% of individuals reported insufficient physical activity, and the same percentage also indicated low salt intake. The mean systolic blood pressure (SBP) was 148.25 mmHg (SD\u0026thinsp;=\u0026thinsp;\u0026plusmn;\u0026thinsp;15.23), and the mean diastolic blood pressure (DBP) was 89.93 mmHg (SD\u0026thinsp;=\u0026thinsp;\u0026plusmn;\u0026thinsp;10.84). Among the participants, 36.5% had Grade 2 hypertension, and 26.9% had isolated systolic hypertension (ISH). Most (62.5%) patients were on monotherapy, predominantly amlodipine. Notably, self-reported medication adherence was high, with 85.1% of the participants consistently taking their prescribed treatment (Table\u0026nbsp;1).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSociodemographic and clinical characteristics of patients with uncontrolled hypertension (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;104)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCategories\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;S. D\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (in years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41 (39.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63 (60.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59 (56.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIlliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49 (47.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary school certificate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24 (23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMiddle school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17 (16.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh school certificate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntermediate or Diploma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGraduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOccupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnemployed/Retired/Homemaker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72 (69.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSelf-employed/Business\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnskilled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSemiskilled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProfessional/Skilled worker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e81 (77.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnderweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31 (29.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56 (53.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11 (10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlcohol consumption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17 (83.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurrent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFormer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11 (10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84 (80.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCardiovascular heredity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38 (36.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53 (51.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComorbidities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eType-2 diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56 (53.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDyslipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCerebrovascular disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChronic renal failure/chronic kidney disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCoronary heart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysical activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInsufficient physical activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e76 (73.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReduced salt intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e76 (73.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFruit and vegetable intake\u003c/p\u003e\n \u003cp\u003e(Days a week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u0026ndash;4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48 (46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u0026ndash;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30 (28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh sodium intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35 (33.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRarely (Once a week or less)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41 (39.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSometimes (2\u0026ndash;3 times a week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20 (19.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOften (4\u0026ndash;6 times a week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDaily\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh fat intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21 (20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRarely (Once a week or less)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSometimes (2\u0026ndash;3 times a week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e67 (64.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOften (4\u0026ndash;6 times a week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15 (14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean blood pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean systolic blood pressure (SBP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e148.2\u0026thinsp;\u0026plusmn;\u0026thinsp;15.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean diastolic blood pressure (DBP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e89.9 3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStages of hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh normal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24 (23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38 (36.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIsolated systolic hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28 (26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDuration of hypertension (in years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLess than 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60 (57.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u0026ndash;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u0026ndash;15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u0026ndash;20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMore than 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of antihypertensives taken\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65 (62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29 (27.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCommonly used antihypertensives\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmlodipine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59 (56.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTelmisartan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42 (40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAtenolol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15 (14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHydrochlorothiazide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCombination tablets\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTreatment compliance (N\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e86 (85.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdverse effects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12 (11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\u003cem\u003eBMI\u003c/em\u003e body mass index, \u003cem\u003eSBP\u003c/em\u003e systolic blood pressure, \u003cem\u003eDBP\u003c/em\u003e diastolic blood pressure\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003eFactors associated with therapeutic inertia\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003eA univariate logistic regression analysis was performed to compare hypertensive patients with and without therapeutic inertia, considering sociodemographic, clinical, and treatment-related factors. The analysis revealed that age, education, smoking status, reduced salt intake, comorbidities, continuity of care, stage of hypertension, and SDM score were significant factors (p value\u0026thinsp;\u0026lt;\u0026thinsp;0.15). In the multivariate analysis, age (AOR 4.36, 95% CI 1.13\u0026ndash;16.90), education (AOR\u0026thinsp;=\u0026thinsp;0.23, 95% CI\u0026thinsp;=\u0026thinsp;0.05\u0026ndash;0.99), comorbidities (AOR\u0026thinsp;=\u0026thinsp;0.18, 95% CI\u0026thinsp;=\u0026thinsp;0.04\u0026ndash;0.79), stage of hypertension (AOR\u0026thinsp;=\u0026thinsp;4.81, 95% CI\u0026thinsp;=\u0026thinsp;1.38\u0026ndash;16.70), and the SDM score (AOR\u0026thinsp;=\u0026thinsp;0.93, 95% CI\u0026thinsp;=\u0026thinsp;0.88\u0026ndash;0.99) were identified as independent predictors of inertia (Table\u0026nbsp;2).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eFactors associated with therapeutic inertia among patients with uncontrolled hypertension estimated by multivariate logistic regression\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTherapeutic inertia\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCOR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAOR (95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYes (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eAge (in years)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (56.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (43.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.33 (0.83\u0026ndash;6.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.36 (1.13\u0026ndash;16.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.032\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (83.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIlliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (30.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (69.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.44 (0.17\u0026ndash;1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.23 (0.05\u0026ndash;0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.048\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76 (80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurrent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (44.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.20 (0.05\u0026ndash;0.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22 (0.03\u0026ndash;1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eReduced salt intake\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62 (81.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (35.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (64.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.40 (0.15\u0026ndash;1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.64 (0.19\u0026ndash;2.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.469\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eComorbidities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (88.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (30.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (69.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.30 (0.10\u0026ndash;0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.18 (0.04\u0026ndash;0.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.023\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eContinuity of care\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoutine care (PHC/CHC/Private)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (27.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53 (72.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNonroutine care (FDP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (12.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (87.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.54 (0.79\u0026ndash;8.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.20 (0.47\u0026ndash;10.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.315\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\n \u003cp\u003eStage of hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrade 2/Grade 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (34.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (65.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh normal/ISH/Grade 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52 (85.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.09 (1.2\u0026ndash;7.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.81 (1.38\u0026ndash;16.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.013\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSDM score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.93 (0.90\u0026ndash;0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.93 (0.88\u0026ndash;0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.031\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\u003cstrong\u003e*\u003c/strong\u003eSignificant values (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\u003cem\u003eCOR\u003c/em\u003e, crude odds ratio; \u003cem\u003eAOR\u003c/em\u003e, adjusted odds ratio; \u003cem\u003eCI\u003c/em\u003e, confidence interval; \u003cem\u003ePHC\u003c/em\u003e, primary health centre; \u003cem\u003eCHC\u003c/em\u003e, community health centre; \u003cem\u003eFDP\u003c/em\u003e, family doctor programme; \u003cem\u003eISH\u003c/em\u003e, isolated systolic hypertension; \u003cem\u003eSDM\u003c/em\u003e, shared decision-making\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003eShared decision making (SDM)\u003c/h2\u003e\n \u003cp\u003eFigure 1 presents the distribution of participant responses across the 9 items of the SDM-Q-9 scale, arranged in descending order based on the level of agreement. Overall, moderate agreement was observed across the SDM-Q-9 items. The highest levels of agreement were seen for the information-related items: Item 1 (doctors made it clear that a BP treatment decision needs to be made) had 39.4% scoring 3 and 33.7% scoring 4, while Item 3 (doctor told me that there are different options for treating my medical condition) had 38.5% scoring 3 and 34.6% scoring 4. In contrast, items reflecting active collaborative decision-making showed considerably lower scores. Items 9 (doctor and I reached an agreement on how to proceed) and 8 (doctor and I selected a treatment option together) each had 16.4% scoring 0 and 27.9% scoring 1, while Item 7 (doctor asked me which treatment option I prefer) had 15.4% scoring 0 and 28.8% scoring 1, indicating limited patient involvement in treatment selection and shared decision-making.\u003c/p\u003e\n \u003cp\u003eThe total SDM score was calculated as the sum of all 9 SDM-Q-9 items, with the total scores ranging from 0\u0026ndash;45, where higher scores indicated greater shared decision making. The total scores were found to be normally distributed (Shapiro‒Wilk p\u0026thinsp;=\u0026thinsp;0.247). In this study, the mean total SDM score across all participants was 22.23\u0026thinsp;\u0026plusmn;\u0026thinsp;11.82. An independent samples t-test revealed a statistically significant difference in mean total SDM scores between patients with and without inertia (p\u0026thinsp;=\u0026thinsp;0.003). Patients who experienced inertia had a significantly lower mean score of 20.36\u0026thinsp;\u0026plusmn;\u0026thinsp;11.15 compared to those without inertia (28.4\u0026thinsp;\u0026plusmn;\u0026thinsp;12.11). The effect size for this difference was medium to large (Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.71), indicating that the association between lower SDM and therapeutic inertia is statistically significant and clinically meaningful.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\"\u003e\n \u003ch2\u003eQualitative results\u003c/h2\u003e\n \u003cp\u003eWe present the findings within each theme from both the patients\u0026rsquo; and providers\u0026rsquo; perspectives to enable a comprehensive understanding of therapeutic inertia. Supplementary file 3 describes the characteristics of the medical officers and patients involved in the in-depth interviews.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003eTheme 1: Patient beliefs and perceptions shape treatment decisions\u003c/h2\u003e\n \u003cp\u003ePatients expressed beliefs about the efficacy, safety, and long-term consequences of medication prescribed through government facilities that strongly influenced their willingness to initiate, continue, or intensify treatment for hypertension. One of the major concerns was the perceived ineffectiveness of government medicines. Patients frequently reported that, despite regular consumption, their blood pressure levels remained uncontrolled. In addition, patients expressed concerns related to the quality of medicines and the accuracy of dose strength in government facilities. As a result, many patients chose to discontinue treatment or switch to private medicines despite the higher cost.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;No, the government medicines don\u0026rsquo;t work well...it doesn\u0026rsquo;t suit me; BP levels have not come down. I am thinking of shifting to CMC (private provider).\u0026rdquo; (Patient 7)\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eFurthermore, treatment burden was identified as a significant barrier. Patients, especially those with coexisting diabetes and hypertension, reported difficulties in managing complex regimens involving multiple tablets. Due to the burden of multiple medicines, patients resisted the addition of new medicines even when BP remained uncontrolled.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Here, in the government, they give 5 tablets for sugar due to low doses, and in total, in one day, I take 8 tablets, which is very difficult, but in private, it is only 1\u0026ndash;1 tablet for BP and sugar.\u0026rdquo; (Patient 8)\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003ePatients also reported concerns about lifelong medication use and its potential side effects, particularly kidney damage. These fears contributed to a preference for lifestyle modification over initiating or escalating treatment.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Most are okay with lifestyle modifications, but they don\u0026rsquo;t want tablets. They\u0026rsquo;ll say, \u0026lsquo;Let\u0026rsquo;s wait one more month, I\u0026rsquo;ll follow diet and exercise strictly, then you can start medicines.\u0026rsquo; They don\u0026rsquo;t want lifelong treatment and prefer managing with diet alone.\u0026rdquo; (Provider 3).\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\"\u003e\n \u003ch2\u003eTheme 2: Lifestyle habits and resistance to behaviour change\u003c/h2\u003e\n \u003cp\u003eLifestyle habits, particularly dietary preferences, smoking and physical activity, were central to both patient narratives and providers\u0026rsquo; perspectives. These behaviours often pose challenges to hypertension control and contribute to inertia when providers choose to delay the initiation or intensification of treatment for two reasons: first, they believe that lifestyle changes might bring BP under control, and second, they feel that initiating or escalating treatment despite resistance to behaviour change is meaningless. Salt consumption and food preferences emerged as major barriers that patients found difficult to modify.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;When I eat rice items like curd rice or something else, I need pickle compulsorily.\u0026rdquo; (Patient 2)\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\"\u003e\n \u003ch2\u003eProviders acknowledged this resistance:\u003c/h2\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Everybody wants to eat salt. They are not up to their mark. In fact, even when I tell them they are not understanding my point. This is a major problem. If they do not follow the diet, no point in adding medicines.\u0026rdquo; (Provider 2)\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003ePhysical activity was also limited for many, either because of safety concerns or the belief that occupational work provided sufficient exercise. Substance use, particularly smoking and alcohol, was one domain in which providers described frustration over patients\u0026rsquo; inability to change.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Yeah, I walk a mile every day right for work. That\u0026rsquo;s it. That\u0026rsquo;s my physical activity\u0026rdquo; (Patient 1)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Smoking and alcohol how much ever I tell, they are not changing. Maybe 1 percent are trying to change.\u0026rdquo; (Provider 5)\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\"\u003e\n \u003ch2\u003eTheme 3: Fragmented care, multiple care providers and conflicting treatment plans\u003c/h2\u003e\n \u003cp\u003ePatients frequently navigated between multiple sources of care, including government, private and other informal providers. This disrupted treatment continuity and hindered the ability to make timely, consistent treatment adjustments.\u003c/p\u003e\n \u003cp\u003eSeveral patients reported using government services only for BP monitoring while relying on private providers for medication. In such cases, government medical officers were reluctant to intensify treatment without knowing the full regimen.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Some patients come just for check-ups without their private medicines. If their BP is high, we ask them to bring their medications for review and may adjust the dosage using government drugs. While some stick to private prescriptions despite high readings, some agree to switch or follow up with their doctor when explained.\u0026rdquo; (Provider 4)\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eAdding to this complexity was the conflicting guidance patients received from different providers, which led to confusion and doubt, causing them to take medications prescribed by various physicians simultaneously. This inconsistency in medical advice left patients uncertain about whose guidance to follow, resulting in delays in adopting or adjusting in case of altered treatment.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Those (Chittoor GH) doctors tell don\u0026rsquo;t take these medicines; take the ones we are prescribing. It is confusing, so I take both medicines, the one they have prescribed (Chittoor GH) and the one these people (PHCs) have prescribed.\u0026rdquo; (Patient 3).\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eIn cases of polypharmacy, providers delayed treatment adjustments to avoid duplication or drug interaction, reinforcing inertia despite persistent uncontrolled blood pressure.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\"\u003e\n \u003ch2\u003eTheme 4: Provider caution and clinical judgement delaying treatment intensification\u003c/h2\u003e\n \u003cp\u003eProviders frequently described therapeutic decisions as a deliberate process shaped by clinical judgement. Several providers stated that treatment escalation was avoided or delayed, especially in patients with borderline hypertension, and preferred to observe patients over multiple readings and prescribe lifestyle modifications before treatment intensification. In addition, the perceived risk of overtreatment and fear of hypotension in patients, especially those with borderline BP, has raised concerns for clinicians, particularly those working in agricultural fields.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;If it is persistently more than 150 even after their diet and lifestyle modification, then I will double the dose. Otherwise, diet and lifestyle are my main treatment.\u0026rdquo; (Provider 5)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;If we intensify, they might go to a hypotensive state, 110/70, working people in the sun, so it might be a problem, so we are not intensifying the treatment for those people who are diagnosed and whose BP levels are 130/80.\u0026rdquo; (Provider 4).\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eMoreover, decisions concerning treatment intensification were influenced by age and comorbidities, as providers reported being more aggressive in initiating or intensifying treatment in high-risk patients, such as those with diabetes, but exercised caution in low-risk younger patients.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;For borderline BP in patients with existing disease, I feel it\u0026rsquo;s better to start treatment immediately; they\u0026rsquo;re already at risk.\u0026rdquo; (Provider 4)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;For younger patients, we follow a thorough check, including serum creatinine, lipid profile and, if eligible, thyroid profile. For older patients, we avoid risk; if there is no concerning family history, we start CCB.\u0026rdquo; (Provider 1)\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\"\u003e\n \u003ch2\u003eTheme 5: Interruption in follow-up, referrals and medication adherence as drivers of therapeutic inertia\u003c/h2\u003e\n \u003cp\u003eFollow-up care emerged as a major challenge, as several providers described low rates of return among patients after initial diagnosis and medication initiation, with visits often occurring only when medication was over.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Follow-up is the most difficult part. Patients do not return on time; they return only after the medicines are over. Out of those diagnosed, only 1\u0026ndash;5% come for regular check-ups.\u0026rdquo; (Provider 4)\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eReferral practices also influence inertia. Healthcare staff at the sub-centres fail to refer patients with Grade 2 or 3 hypertension unless they complained of any symptoms or when complications were present. Even when referrals were made to higher centres, providers noted that many patients did not follow through. These delays in referral and regular follow-up meant that patients often remained on the same regimen for extended periods without intensification despite persistent uncontrolled blood pressure.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;At the village level, unless the patient complains, they (CHO) don\u0026rsquo;t usually call or refer even if BP is 170/90. Only when symptoms such as severe headache occur, they contact us to escalate treatment. We then adjust the dose on the basis of previous treatment. When patients visit us, and we observe abnormal values, we advise them to visit Chittoor GH, but very few go.\u0026rdquo; (Provider 4)\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eProviders expressed concerns about regular intake of medicines, noting that patients took their medications only when symptomatic. Poor medication adherence was cited as a major reason for non-intensification of treatment by the providers. In contrast, almost all patients reported high adherence, especially when medicines were provided free of cost and were conveniently available.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;I will see whether they are telling right or wrong first, I will decide, and then only change the drug, the patient never says the truth.. they always say that they are taking the medicines regularly..\u0026rdquo;(Provider 7)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;No, no, I never miss taking my medicines\u0026hellip; I take my BP tablets regularly.\u0026rdquo; (Patient 6)\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eThe above factors led to inertia by creating a lack of consistent feedback mechanisms to verify adherence or track follow-up, often leading to provider uncertainty and cautious treatment decisions.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTheme 6: Systemic barriers to workforce availability at FDP and drug limitations contribute to therapeutic inertia\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eTherapeutic inertia was not solely a result of patient behaviour or provider decision-making but also stemmed from systemic barriers, particularly the non-availability of doctors at FDP and the limited availability of appropriate antihypertensive medications.\u003c/p\u003e\n \u003cp\u003eSeveral patients reported that they were rarely seen by a doctor during follow-up visits, especially at FDPs. Instead, clinical encounters were often managed by an ANM (Auxiliary Nurse Midwife) or a CHO (Community Health Officer). This lack of clinical authority led to delays in treatment adjustment, as the staff without prescribing authority and a lack of teleconsultation often continued the same medication without escalation, despite uncontrolled BP.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Where is the doctor? These people (CHO, ANM) here are only doctors..The big doctor comes very rarely to the FDP.\u0026rdquo; (Patient 4)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Doctors are scarce now. Earlier, there were separate doctors for 104 and OP at PHCs, but now they\u0026rsquo;ve limited everything. Many doctors leave for PG, so buffer doctors are not sufficient.\u0026rdquo; (Provider 6)\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eProviders also reported challenges in tailoring treatment due to a lack of suitable drug formulations in the public supply. For example, when a lower starting dose was needed, such as telmisartan 20 mg or hydrochlorothiazide 12.5 mg, providers were forced to split the existing dosage and administer half of the available amount. These limitations reduced the provider\u0026rsquo;s ability to adjust regimens effectively, especially for patients with borderline readings.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026quot;If BP is borderline (140/90 or 150/90), we recommend half a 40 mg telmisartan tablet. For higher BPs, we provide the full dose. Hydrochlorothiazide\u0026apos;s 25 mg tablet is difficult to split, and the full dose can lead to dehydration.\u0026quot; (Provider 4)\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eAside from the concerns mentioned above, providers reported the availability of adequate classes of drugs at public facilities, except for a few emergency drugs, such as labetalol, which are prescribed specifically during pregnancy-induced hypertension.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\"\u003e\n \u003ch2\u003eTheme 7: Limited provider-patient interaction and shared decision-making\u003c/h2\u003e\n \u003cp\u003eWhile many patients described consultations marked by limited engagement with providers, there were a few instances in which patients expressed positive experiences in their involvement in decision-making, highlighting wide variability in interactions across facilities.\u003c/p\u003e\n \u003cp\u003eSome providers acknowledged their own biases regarding shared decision making, expressing the belief that doctors are better equipped to make treatment decisions. Despite this, they reported making efforts to involve patients, particularly during treatment initiation or when managing borderline values.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;When we are initiating drugs or when sugar is borderline, I give the choice: \u0026lsquo;Do you want to start now or wait?\u0026rsquo; and let them decide. They are not that educated... maybe we are biased that we make better decisions than them.. maybe I\u0026rsquo;m wrong.\u0026rdquo; (Provider 5)\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eFrom the patient\u0026rsquo;s perspective, some described positive, respectful interactions where providers actively asked about symptoms and offered guidance, whereas others felt dismissed or ignored, especially at the FDP, owing to the lack of doctors, as highlighted earlier.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;Yeah, the staff is good. Therefore, when I had come here, the doctor scolded me and said, \u0026ldquo;You have a very high BP.. why have you kept it that way?\u0026rdquo; and so many other questions were asked.\u0026rdquo; (Patient 1)\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003e\u0026ldquo;In government hospitals, they don\u0026rsquo;t see patients properly.. they keep looking at their phone and don\u0026rsquo;t even ask what the issue is.\u0026rdquo; (Patient 9)\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eTogether, these narratives show that while some providers attempt shared decision making, systemic barriers and, at times, individual attitudes lead to one-sided consultations with minimal space for patient input. This may undermine trust and reduce patient motivation to follow through with treatment, ultimately contributing to delays in treatment intensification.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study contributes to a better understanding of therapeutic inertia in hypertension patients within various tiers of government primary care facilities. The results offer insights into how individual-level factors and systemic barriers significantly impact treatment decisions, often leading to therapeutic inertia. We found that the prevalence of therapeutic inertia in this study was 76.9%, indicating that in more than three-quarters of the patients with uncontrolled BP, the treatment was neither initiated nor intensified. This finding is consistent with global estimates reported in studies from Ethiopia (72%) [23] and Spain (75%) [29] but is notably higher than those reported in countries such as the UK (33.1%) [30] and Malaysia (38.6%) [31]. The variations in prevalence across different countries may be attributed to differences in resource availability, healthcare delivery models, and the extent of physician awareness and adherence to clinical protocols. We identified several challenges contributing to therapeutic inertia from both patient and provider perspectives. Two major factors include the reluctance of providers to intensify treatment in borderline cases and the insufficient involvement of patients in shared decision-making processes regarding their care. Additional significant contributors include patients' beliefs and perceptions about hypertension treatment, resistance to lifestyle modifications, fragmented care, conflicting advice from multiple healthcare providers, interruptions in follow-up and referrals, and the limited availability of physicians at the FDP.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003ePrimary drivers of therapeutic inertia\u003c/h2\u003e \u003cp\u003eIn our study, patients with high-normal, ISH, or Grade 1 hypertension were found to be 4.8 times more likely to experience therapeutic inertia than those with Grade 2 or Grade 3 hypertension, making it the strongest predictor of inertia. This was strongly supported by the qualitative findings, where physicians described a deliberate, cautious \u003cem\u003e\u0026ldquo;wait-and-watch approach\u0026rdquo;\u003c/em\u003e toward treatment intensification in borderline cases. Many providers preferred to recommend lifestyle modification first and monitor subsequent readings, particularly in outdoor labourers, where there was a concern of hypotension. This delay in intensification was framed not as an oversight but as a calculated clinical decision. Our findings align with those of previous studies that reported similar reasons [23,32,33].\u003c/p\u003e \u003cp\u003eAdditionally, shared decision-making in hypertension management was explored through the SDM-Q-9 questionnaire and qualitative interviews. The mean total SDM score was 22.23\u0026thinsp;\u0026plusmn;\u0026thinsp;11.82 out of 45, and patients who experienced therapeutic inertia had scores that were, on average, 8 points lower. A one-point increase in the SDM score reduced the odds of inertia by 7%, indicating an inverse relationship. Qualitative interviews revealed that some patients experienced limited engagement, often due to the absence of doctors, which are missed opportunities for engaging with patients to make shared treatment decisions, thereby delaying treatment adjustments and reducing follow-up motivation. When doctors are present, providers themselves acknowledge that SDM is inconsistently applied.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eOther clinical and patient-related drivers of therapeutic inertia\u003c/h2\u003e \u003cp\u003eAge and comorbidities were significantly associated with therapeutic inertia. Patients aged\u0026thinsp;\u0026le;\u0026thinsp;60 years were 4.36 times more likely to experience inertia than those who were \u0026gt;\u0026thinsp;60 years. This was supported by qualitative findings, where physicians intensified treatment in older patients owing to perceived higher risk. This contradicts current hypertension guidelines, which recommend more aggressive action in younger patients, especially those\u0026thinsp;\u0026le;\u0026thinsp;60 years. This finding diverges from those of previous studies that reported greater therapeutic inertia among older adults [32,34\u0026ndash;36]. These inconsistencies underscore the need for enhanced provider training and the dissemination of updated hypertension management guidelines, particularly regarding age-specific treatment decisions. In contrast, the presence of comorbidities was associated with an 82% reduction in inertia, which is consistent with provider narratives where patients with diabetes or other comorbidities were often treated more aggressively. This finding aligns with prior literature suggesting that clinicians act when the perceived risk of complication is high [32,33].\u003c/p\u003e \u003cp\u003eAnother significant challenge was resistance to lifestyle change, which emerged as a key factor in the qualitative strand. Patients frequently reported high salt consumption and low physical activity, and in certain cases, use alcohol and tobacco, often viewing them as difficult to change. For providers, this persistent non-adherence offered a rationale for delaying treatment intensification, reflected in sentiments such as \u0026ldquo;\u003cem\u003eno point in intensifying if they will not change their diet,\u0026rdquo;\u003c/em\u003e suggesting that lifestyle-related barriers reinforce inertia.\u003c/p\u003e \u003cp\u003eA few important factors emerged from the qualitative interviews, but were not identified as predictors in the quantitative analysis. Treatment burden, particularly among patients with both diabetes and hypertension, was frequently mentioned. Although the number of drugs used was not significantly associated with inertia, patients reported feeling overwhelmed by polypharmacy and resisted the addition of new medications. Providers echoed this, expressing reluctance to intensify treatment owing to concerns about intolerance and non-compliance. These findings align with earlier studies highlighting the impact of polypharmacy on inertia [23,31].\u003c/p\u003e \u003cp\u003eAnother factor was medication adherence. Quantitatively, adherence was high, with 85% self-reported compliance, and nearly all patients confirmed regular intake during in-depth interviews. In contrast, it was not significantly associated with therapeutic inertia in the regression analysis. Moreover, some providers expressed distrust in patients\u0026rsquo; self-reports, influencing their hesitation to change treatment. This has also been noted in previous studies [33]. These findings suggest that even when patient-reported adherence is high, perceived non-adherence by providers may still drive inertia.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eSystemic barriers to therapeutic inertia\u003c/h2\u003e \u003cp\u003eIn addition to patient- and provider-level barriers, several systemic constraints contribute to therapeutic inertia. A major challenge was the lack of physician availability at the FDPs, which emerged through both field observations and qualitative interviews. FDPs, held monthly in villages, often operate without a regular physician presence, leaving patients dependent on CHOs to continue medication without clinical review or dose titration. In many cases, treatment decisions were delayed, and medications were distributed without adjustments, with teleconsultation options also not being utilised. Patients who relied solely on FDPs and were unable to visit PHCs or higher centres were particularly vulnerable to prolonged periods of uncontrolled hypertension. In this context, inertia appeared systemic and was embedded in staffing patterns rather than the decisions of individual providers.\u003c/p\u003e \u003cp\u003eTogether, these findings highlight the pressing need for coordinated multilevel strategies to combat therapeutic inertia in hypertension management. For providers, it is crucial to integrate training modules on this issue into NP-NCD programs for MOs, particularly those focused on borderline hypertension. These should emphasise adherence to protocols for adjusting treatment and include case-based simulations and SDM skills to facilitate timely intervention. While SDM is not yet widespread in India, its inclusion in clinical training could improve patient engagement and mitigate inertia. Moreover, strengthening the capacity of frontline workers, i.e., ASHAs, ANMs, and CHOs, is essential. Training should cover basic BP assessment, uncontrolled hypertension identification, and referral criteria. Culturally relevant health communication methods, including short videos and group counselling sessions, can encourage patients to adopt healthier lifestyle changes. Additionally, engaging community leaders and caregivers can foster better patient adherence and follow-up. At a systemic level, it is vital to improve the availability of the healthcare workforce, particularly by ensuring the regular presence of doctors at FDPs, facilitating timely adjustments to treatment and ensuring continuity of care. By adopting these strategies, we can enhance the responsiveness of primary care to the growing challenge of NCDs and strengthen blood pressure management within India\u0026rsquo;s primary healthcare system.\u003c/p\u003e \u003cp\u003eThere are certain limitations to this research that must be acknowledged. Although definitions of therapeutic inertia exist in the literature, there is no universally accepted operational standard in practice. Some instances of inertia identified in this study may represent apparent rather than true inertia, particularly when providers choose to wait for subsequent readings, schedule follow-up prior to modifying medicines, or when a treatment change would have been made during earlier consultations. This ambiguity in classification highlights the need for clearer criteria to reduce overestimation or underestimation of true inertia. Certain quantitative variables (e.g., self-reported adherence and side effects) may not fully capture clinical nuances, leading to potential misclassification. Finally, as a cross-sectional study, this work captures inertia at a single time point and does not assess how therapeutic inertia evolves or resolves over time.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eOverall, this study demonstrates that therapeutic inertia is not solely the result of clinical oversight, as often reported in previous literature, but rather emerges as a complex interplay of patient behaviours, provider reasoning, and systemic constraints. In the Indian context, where this concept remains underexplored, our study provides a comprehensive understanding of the extent and underlying drivers of inertia in hypertension management. The implications of these findings extend beyond hypertension to other chronic conditions that require long-term management, such as diabetes, chronic kidney disease, and other cardiovascular diseases, where therapeutic inertia similarly hampers outcomes.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eThese findings underscore the need for longitudinal research to evaluate the impact of inertia on long-term blood pressure control and cardiovascular outcomes, as well as intervention-based research focusing on therapeutic inertia across various chronic conditions. A comprehensive health system approach to addressing inertia can strengthen the management of chronic diseases under the NP-NCD framework.\u003c/p\u003e"},{"header":"Abbreviations","content":" \u003cp\u003eAHA Antihypertensive agent\u003c/p\u003e \u003cp\u003eANM Auxiliary Nurse Midwife\u003c/p\u003e \u003cp\u003eAOR Adjusted odds ratio\u003c/p\u003e \u003cp\u003eASHA Accredited Social Health Activist\u003c/p\u003e \u003cp\u003eBP Blood pressure\u003c/p\u003e \u003cp\u003eCHC Community Health Centre\u003c/p\u003e \u003cp\u003eCHO Community Health Officer\u003c/p\u003e \u003cp\u003eCI Confidence interval\u003c/p\u003e \u003cp\u003eCOR Crude odds ratio\u003c/p\u003e \u003cp\u003eDBP Diastolic blood pressure\u003c/p\u003e \u003cp\u003eESC European Society of Cardiology\u003c/p\u003e \u003cp\u003eESH European Society of Hypertension\u003c/p\u003e \u003cp\u003eFDP Family Doctor Programme\u003c/p\u003e \u003cp\u003eIHCI India Hypertension Control Initiative\u003c/p\u003e \u003cp\u003eIQR Interquartile range\u003c/p\u003e \u003cp\u003eISH Isolated systolic hypertension\u003c/p\u003e \u003cp\u003eMMU Mobile Medical Unit\u003c/p\u003e \u003cp\u003eMO Medical Officer\u003c/p\u003e \u003cp\u003eNCD Non-communicable disease\u003c/p\u003e \u003cp\u003eNFHS-5 National Family Health Survey-5\u003c/p\u003e \u003cp\u003eNPCDCS National Programme for Control of Diabetes, Cancers and Stroke\u003c/p\u003e \u003cp\u003eNP-NCD National Programme for Non-Communicable Diseases\u003c/p\u003e \u003cp\u003ePHC Primary Health Centre\u003c/p\u003e \u003cp\u003eSBP Systolic blood pressure\u003c/p\u003e \u003cp\u003eSC Sub-Centre\u003c/p\u003e \u003cp\u003eSDM Shared decision making\u003c/p\u003e \u003cp\u003eUPHC Urban Primary Health Centre\u003c/p\u003e \u003cp\u003eVIF Variable inflation factor\u003c/p\u003e \u003cp\u003eWHO World Health Organisation\u003c/p\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e \u003cp\u003e The study was approved by the Institutional Ethics Committee (IEC) of the Indian Institute of Public Health, Gandhinagar (IIPHG) (IIPHGIEC/2024-25/21\u0026ndash;33) and the Institutional Review Board (IRB) of Christian Medical College (CMC, Vellore) (IRB Min. No. 2502132). The study was conducted in accordance with the Declaration of Helsinki. Participation in both the quantitative and qualitative strands was voluntary, and written informed consent was obtained from all participants before data collection. Confidentiality and anonymity were maintained throughout. For the qualitative strand, audio-recorded interviews and transcripts were encrypted and securely stored. Exit interviews also ensured that participants\u0026rsquo; identities remained confidential.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors declare that no form of funding was received for this study.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eThe study was conceptualised and designed by SK and DL. SK collected and analysed the data, and, along with DL, interpreted the findings. All the authors were involved in drafting the manuscript and revising its content. Each author approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and analysed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePiovani D, Nikolopoulos GK, Bonovas S. Non-Communicable Diseases: The Invisible Epidemic. JCM. 2022 Oct 8;11(19):5939.\u003c/li\u003e\n\u003cli\u003eWorld Health Organisation. Hypertension. 2023. https://www.who.int/news-room/fact-sheets/detail/hypertension. Accessed 29 June 2025\u003c/li\u003e\n\u003cli\u003eNethan S, Sinha D, Mehrotra R. Non Communicable Disease Risk Factors and their Trends in India. Asian Pac J Cancer Prev. 2017 July;18(7):2005–10.\u003c/li\u003e\n\u003cli\u003eSreeniwas Kumar A, Sinha N. Cardiovascular disease in India: A 360 degree overview. 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Circulation [Internet]. 2022 Nov 8 [cited 2025 July 1];146(Suppl_1).\u003c/li\u003e\n\u003cli\u003eMyers O, Markossian T, Probst B, Hiura G, Habicht K, Egan B, et al. Age and sex disparities in blood pressure control and therapeutic inertia: Impact of a quality improvement program. American Journal of Preventive Cardiology. 2024 Mar;17:100632.\u003c/li\u003e\n\u003cli\u003eZheutlin AR, Addo DK, Jacobs JA, Derington CG, Herrick JS, Greene T, et al. Evidence for Age Bias Contributing to Therapeutic Inertia in Blood Pressure Management: A Secondary Analysis of SPRINT. Hypertension. 2023 July;80(7):1484–93.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-primary-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"famp","sideBox":"Learn more about [BMC Primary Care](https://bmcprimcare.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12875","title":"BMC Primary Care","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Therapeutic inertia, Hypertension, Primary care, Shared decision making (SDM), Mixed methods, India","lastPublishedDoi":"10.21203/rs.3.rs-8418875/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8418875/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHypertension remains a significant global health challenge, affecting approximately 1.4\u0026nbsp;billion adults aged 30\u0026ndash;79 worldwide. In India, the age-standardised prevalence is 28.1%, and blood pressure (BP) control remains suboptimal. Therapeutic inertia, the failure to initiate or intensify treatment when therapeutic goals are unmet, is recognised as a key contributor to uncontrolled hypertension. In this study, we aimed to understand the prevalence and factors contributing to therapeutic inertia in hypertension management within primary care settings in Chittoor, with a focus on shared decision-making (SDM).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA convergent parallel mixed-methods design was adopted. The quantitative strand involved 104 adults with uncontrolled hypertension attending primary care facilities. Data on sociodemographic variables, cardiovascular risk factors, consultation and treatment details, and SDM were collected through a structured questionnaire. The qualitative strand included in-depth interviews with nine patients and eight medical officers. Findings from both strands were integrated and triangulated with field observations.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe prevalence of therapeutic inertia was 76.9%. Patients aged under 60 years (AOR\u0026thinsp;=\u0026thinsp;4.36; 95% CI: 1.13\u0026ndash;16.90) and those with borderline or mildly elevated blood pressure (AOR\u0026thinsp;=\u0026thinsp;4.81; 95% CI: 1.38\u0026ndash;16.70) had greater odds of inertia. In contrast, illiteracy (AOR\u0026thinsp;=\u0026thinsp;0.23; 95% CI: 0.05\u0026ndash;0.99), the presence of comorbidities (AOR\u0026thinsp;=\u0026thinsp;0.18; 95% CI: 0.04\u0026ndash;0.79), and higher SDM scores (AOR\u0026thinsp;=\u0026thinsp;0.93; 95% CI: 0.88\u0026ndash;0.99) were associated with lower odds. The participants with inertia had significantly lower mean SDM scores (20.36 vs. 28.4, p\u0026thinsp;=\u0026thinsp;0.003). Thematic analysis highlighted seven key drivers: patient beliefs and perceptions, reluctance to adopt lifestyle changes, fragmented care and conflicting advice, provider caution and clinical judgement, poor follow-up and adherence, workforce constraints in outreach programmes, and limited SDM.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eTherapeutic inertia is highly prevalent within India\u0026rsquo;s primary healthcare system, resulting from a complex interplay of factors at the patient, provider and system levels. Limited engagement in shared decision making, particularly regarding hypertension, has been consistently associated with increased inertia. Strengthening provider capacity, enhancing patient engagement and incorporating SDM into routine clinical practice could help reduce inertia and improve hypertension management outcomes in primary care settings.\u003c/p\u003e","manuscriptTitle":"Understanding Therapeutic Inertia in the Management of Hypertension in Primary Care: Examining Contributing Factors at the Patient and Provider Levels in Chittoor District, Andhra Pradesh, India – A Mixed Methods Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-25 07:14:02","doi":"10.21203/rs.3.rs-8418875/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-01-21T08:31:23+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-25T11:37:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-23T05:27:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-23T05:24:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Primary Care","date":"2025-12-21T17:40:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-primary-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"famp","sideBox":"Learn more about [BMC Primary Care](https://bmcprimcare.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12875","title":"BMC Primary Care","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"23b33f63-c8cc-4465-b331-d6d97f69452a","owner":[],"postedDate":"January 25th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-25T07:14:02+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-25 07:14:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8418875","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8418875","identity":"rs-8418875","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}