Members of the India Health Systems Project team will present several areas of work at the upcoming AcademyHealth 2021 Annual Research Meeting, June 14-17, 2021.
Related to Odisha Health System Assessment
Providers’ Knowledge of Diagnosis and Treatment Best Practices for Acute Myocardial Infarction (AMI): Evidence from India Using Clinical Vignettes
Authors: Anuska Kalita, Neha Gupta, Liana Woskie, Winnie Yip
Research Objective: Cardiovascular diseases (CVDs) are a leading cause of death worldwide, and 80% of CVD deaths occur in low- and middle-income countries (LMICs). The Global Burden of Disease Study estimates that CVDs contribute 28·1% of total deaths in India. Acute Myocardial Infarctions (AMI) make up a large share of these deaths. Early diagnosis and correct treatment of AMI is critical to preventing CVD-related deaths. This study aims to assess the competence of primary care providers in India to diagnose and treat AMI and examine differences between public and private sector providers.
Study Design: We conducted a cross-sectional study of healthcare providers’ knowledge of diagnosis and treatment for AMI. Data collection took place in Odisha, one of the poorest states in India, from August 2019 to March 2020. Using data from vignette-based interviews with primary care providers in the public and private sectors, we assessed providers’ knowledge of best practices in clinical care. The public sector providers within this study included physicians at government-run primary health centers, and the private sector providers were engaged in solo-practice, irrespective of medical qualifications. The vignette-responses were evaluated against standard treatment guidelines (STGs) for AMI at the primary care level.
Population Studied: 110 primary care providers working in Odisha, India a state with ~47 million people, of which 32.5% earn < $1.90/day and ~60% belong to indigenous or vulnerable social groups.
Principal Findings: Overall, providers demonstrated low levels of knowledge: only 67.27% diagnosed AMI correctly, and 0% recommended the correct treatment as per STGs. Providers seldom asked key diagnostic questions such as family and medical history (6.36% of cases) and the nature of the chest pain (10.91%) or results from diagnostic tests like ECG and EKG (30%), lipid profile (1.82%), or angiograms (3.64%). Private sector providers showed higher competence in making a correct diagnosis than public providers (difference of 32.73 percentage points). 82.43% of providers referred AMI cases to hospitals, a treatment advice in STGs, with more private than public providers making referrals. 55.41% of providers prescribed at least one correct drug (in combination with unnecessary drugs). More private providers prescribed at least one correct drug than public sector providers. However, 44.74% public providers prescribed only unnecessary drugs, without a single medicine recommended for angina.
Conclusions: Healthcare providers in Odisha, India, have low levels of knowledge regarding AMI diagnosis and treatment, with public providers showing lower competence than private providers.
Implications for Policy or Practice: Our findings indicate strikingly poor quality of care for AMI at the primary care level. The widespread misdiagnosis of AMI, the prescription of unnecessary drugs, and a lack of appropriate referral raise concerns for India’s efforts to address rising rates of CVD. Our findings suggest addressing CVD in LMIC contexts is complex and requires improving the baseline knowledge of providers in both public and private sectors; which may be particularly relevant in contexts with little de facto regulation.
Patient Satisfaction and Education: The Danger of Low Expectations & Implications for Measuring Health System Performance
Authors: Liana Woskie, Irene Papanicolas, Anuska Kalita, and Winnie Yip
Research Objective: Person-centeredness is a fundamental domain of healthcare quality. It is both a goal in its own right, and valued for its relationship with other, more objectives, measures of performance. However, how best to define, and in turn measure, this aspect of quality has been less clear. As national governments work to ensure their efforts to achieve universal health coverage (UHC) include quality, there is a renewed focus on person-centeredness. We therefore sought to assess the relevance of patient satisfaction ratings, which are often used in isolation, for vulnerable patients.
Study Design: Following a four-stage formal pre-testing process, the Hospital Consumer Assessment of Healthcare Providers andSystems (HCAHPS) tool was administered to patients in 5 districts of Odisha, India. For each hospital (1 per district), patients were interviewed using a time-limited total sample of eligible adult patients until a threshold of 100 was met. Additional data on patient demographics, care seeking behavior and visit characteristics were collected. Drivers of satisfaction were estimated using three linear OLS models with satisfaction as a dependent variable, first as an unadjusted model, second controlling for visit-characteristics e.g. department, presence of a family member etc. and, third, adding additional controls for market characteristics e.g. choice of alternate facilities and presence of insurance.
Population Studied: 507 patients hospitalized for 24 hours or more in five hospitals across Odisha, India.
Principal Findings:
Patients with no formal education, low caste patients and obstetrics patients were subject to the lowest quality interpersonal care. The two HCAHPS domains with the lowest ratings, particularly amongst obstetric patients, were“understandings of care” (e.g. preferences being taken seriously, understanding the purpose of medications, etc.) and post discharge planning. In general, experience scores were highly predictive of a patient’s overall satisfaction rating and likelihood of recommending a given facility. Interpersonal care from doctors was most predictive of overall satisfaction 0.714 (SE: 0.103) followed by the hospital environment 0.284 (SE: 0.067) and care from nurses 0.207 (SE: 0.096). However, there was discordance between HCAHPS sub-items and overall satisfaction for less educated patients. Less educated patients were more satisfied than any other group, but also reported receipt of the worst quality interpersonal care (as assessed through the more objective experience sub-items). This relationship, between education level and satisfaction discordance, was signifiant and not mediated by visit-level characteristics or insurance coverage.
Conclusions: Patients with less education received the worst quality interpersonal care, yet reported the highest overall satisfaction with their care when compared to more educated peers.
Implications for Policy or Practice: These data raise concern regarding the use of patient satisfaction as a health system performance measure. Satisfaction is subjective and if certain patients evaluate and/or report satisfaction differently than peers, the use of these ratings in isolation may mask, as opposed to reveal, poor quality interpersonal care. This suggests the need to concurrently examine more objective experience measures, particularly in contexts where patient voice compromised.
Other
Heterogeneity in Response to India’s Initial COVID-19 Nationwide-Lockdown: A Quasi-Experimental Study Using Aggregate MobilityData
Presenting Author: Liana Woskie
Research Objective: India’s March 2020 nationwide lockdown garnered early support from the World Health Organization, but has also been the subject of criticism due to strict enforcement and the inaccessibility of basic supplies for those under lockdown.Given the scale of the policy and relevant concerns, there is an urgent need to better understand the impact of this policy on its intended outcome: slowing covid case growth.
Study Design: We assessed state-level variation in response to the nation-wide lockdown. Using a public dataset of differentially privatized aggregate mobility data, we assessed the combined impact of the Janta Curfew and lockdown using a SingleInterrupted Time Series (SITS) design. Our primary outcomes were change in relative mobility and change in state-level COVID-19case growth. We first looked at variation in mobility between states and then used the results from state-level SITS to assess the relationship with COVID-19 case growth. To do so, we used a model with rate of increase in COVID-19 cases over time as our dependent variable and change in aggregate mobility as our predictor, controlling for population demographics, such as: size, urbanicity and poverty as well as known COVID-19 cases(cumulative as of March 25th). For COVID-19, we used“Covid19India” which aggregated statistics from the Ministry ofHealth and Family Welfare (MoHFW), each state or union territory and the Indian Council of Medical Research (ICMR).
Population Studied: Our analytic sample included 10,512 state-day observations, representing 1.21 billion individuals across 36states and union territories in India.
Principal Findings: We observed an immediate and pronounced decrease in mobility following the policy’s implementation. Overall the lockdown was associated with an 86% decrease in mobility as compared to a location-specific pre-lockdown baseline. However, these effects were not homogeneous by mobility type, nor were they homogeneously sustained in the post-policy period. Visits to grocery stores and pharmacies (slope = 0.62% increase in visits per day) and transit stations (slope = 0.24%) began to recover relatively quickly whereas visits to retail and recreation (slope =-0.41%), and parks (slope -0.47%) continued to decline during the post period. We observed significant state-level variation in mobility responses (71% to 95% decrease in visits to retail and recreation sites). States with the largest decreases in aggregate mobility to retail and recreational sites had a relatively slow (7.2%)rate of increase in COVID-19 case growth in contrast to states with the lowest decreases in mobility, who saw a 53% rate increase inCOVID-19 cases (p=0.03) over the same time period.
Conclusions: States that were most effective in responding to the lockdown policy, as measured by decreased mobility, were also most effective in slowing covid case growth (controlling for state wealth, size, and urbanicity).
Implications for Policy or Practice: While our findings suggestIndia’s nationwide lockdown may have been effective in achieving its primary goal, we require a better understanding of what drives sub-national variation in policy adherence over time as well as careful tracking of unintended economic and wellbeing costs.