Healthcare Blogs

Notes from the field: 

Building With Imperfect Tools: Notes from the Field on Data Quality and Uncertainty

Alekhya Chaparala, Research Assistant, Max Institute of Healthcare Management 

On a cool day last December, I visited the Kopaganj Community Center in Uttar Pradesh’s Mau district. Implementation of an MIHM costing study on family planning was about to begin, and I was in the field to finalize operations and brief local officials before data collection commenced the following week. My work largely involved traveling between our study districts and tracking down various district health officials. At any given moment these officials could be in their offices, on a site visit, or performing a surgery – which is how I ended up at the CHC in Kopaganj, looking for the Chief Medical Officer (CMO) of Mau. Kopaganj was not one of our originally selected study facilities. The facilities for the costing study had been selected based on service delivery data recorded online in the Uttar Pradesh Health Management Information System (UPHMIS) portal, and delivery of female sterilization had been a priority inclusion criterium. We had originally selected the nearby Ratanpura CHC for our study, which had performed the most female sterilizations in the past year based on UPHMIS data. However, upon reaching Kopaganj, I quickly learned that this was not the case. I found the CMO sitting in a packed administrative office with a steady stream of staff flowing in and out. He beckoned me to sit next to him, and I quickly explained the purpose of my visit before we could get interrupted by one of the many people vying for his attention. When I mentioned that we planned to collect data from Ratanpura CHC, he frowned.  “Why are you studying Ratanpura? Study this facility,” the CMO said, gesturing emphatically. I tried to explain that we had already selected Ratanpura, but he continued insisting. “No, no, this is a better facility. You will get better data here.” Perhaps the Ratanpura facility was poorly maintained, I thought, and he worried it would reflect badly on his team.  
“We are looking for the facilities that perform the most female sterilization,” I explained. “Haan, then study here!” the CMO responded, tapping the desk in front of him. “Female sterilization is performed only here.” What? How could that be? “What do you mean?” I asked. “This is the only CHC which performs female sterilization,” he repeated. “In the whole district?” “Yes. I know because I am the only one who performs sterilization!” he laughed at my confusion, finally delivering the punchline. “But, that’s not what the UPHMIS data said,” I attempted weakly, realizing even before I finished that the data we had originally consulted was likely very flawed. UPHMIS data is facility-reported, after all, leaving plenty of opportunity for embellishment. I looked across the room at a large PC where the facility’s designated data operator sat, and wondered if were we about to embark on a data-collecting mission in all the wrong facilities. After ten minutes of back-and-forth questions with the CMO, I accepted that we would have to swap out Ratanpura for Kopaganj in our study. As an early career researcher, this was my first experience with what seasoned researchers know well – that data is messy, flawed, and often misrepresentative of reality. Despite having carefully pored over UPHMIS data for dozens of facilities and health indicators before selecting the study facilities, I suddenly felt as if we had been flying blind the whole time. 
Although our study was a relatively small-scale one, breakdown in data quality is not an uncommon occurrence. Primary data forms the bedrock of social services – implementing, assessing and recalibrating public programs requires an understanding of what is happening on the ground. And when the story we see is incomplete or inaccurate, the decisions we make about how to fund, expand or implement social programs can lead to resources being allocated in ways that ultimately prove  ineffective, or even harmful. The National Family Health Survey (NFHS) is a larger example of this. As the largest source of primary health data in India, NFHS provides data upon which thousands of health-related research studies, public programs and policy decisions are based. Yet NFHS’s well-documented weaknesses -- including a lengthy questionnaire and poorly trained and compensated field researchers -- pose a significant vulnerability to India’s public health sector, which has built its programs largely based on NFHS findings for the last twenty-plus years. 
So what do we do when the data we’re working with is flawed? How do we implement solutions when we don’t fully know the scope and details of the problem? There is no perfect solution -- how large the gap between data and reality is for any given dataset is, by nature, impossible to fully ascertain. Instead, we must commit to thorough investigations of data quality at every point of the research process, and recognize current limitations as a jumping-off point for future study. 
Firstly, investigators should be mindful of the challenges of data collection, and be amenable to accommodations in study protocol which allow the most accurate data possible to be captured. Likewise, field researchers should have not just proper training but also an investment in the study, in order to understand when and how to make these accommodations in real-time. And lastly, policy-makers, social program implementors and other stakeholders who use base their decision-making on ground-level evidence should allow a buffer for the dynamic, imperfect nature of primary research, and likewise work to improve conditions for program data collection wherever possible. Data tells a story, translating the world around us into building blocks for growth and innovation. Much can get lost in translation, however, and it up to us as researchers and program architects to constantly question and clarify the message we receive, in order to gather the clearest, most holistic picture of the truth as possible. 


Point of Care Technologies for Rural Settings: Relevance and Advances

Preeti Singh, Analyst, Max Institute of Healthcare Management, ISB Mohali


Point of Care (PoC) technologies refers to bringing care closer to the first point of contact in both temporal and organizational dimensions through use of technology. Over the years, health sector has seen interdisciplinary PoC technology innovations, such as smartphone health applications, biosensors, lab-on-a-chip, and wearable devices, across healthcare settings; from primary care, to home care, to emergency medical settings. Despite its growing demand, little is known about its relevance at the level of primary health care in rural settings. So, what is the need for point of care technologies in rural areas? How to address the needs of training and capacity building to use these technologies among primary health care workers? These were among the questions discussed at Health 2.0 conference hosted by Max Institute of Healthcare Management, ISB. 
 According to Sivan Menon, CTO GE Healthcare, in developing nations such as India, where health system faces multiple challenges in terms of physical and financial inaccessibility to healthcare, shortage of skilled manpower, and inequity in the distribution of skills,  technology interventions can overcome these challenges. However, he added, that not much has been done in rural sector in India on this front. His views were supported by Tanushree Chaudhary, Technical Officer AMTZ. According to Tanushree, although  government has provided basic health infrastructure in rural areas, the challenge of providing quality care remains pervasive. She emphasized that point of care is a medium which is not only affordable but requires minimal infrastructure, is well connecting, and provides real-time data. Where having a PoC technology in “rural setting” has received a fair bit of perceived value from experts, Guruprasad Seetharaiah, Director-Medical Screening Solutions Bosch Healthcare, argues that these devices are only screening solutions and should not be extended as a composite solution to higher levels of care.
Besides, the above mentioned advantages, PoC technology is also a comprehensive low-cost digital health solution. This is because PoC technology not only requires minimal infrastructure but can be easily used by frontline health workers with little or no college education. This has an added value addition as it empowers front line workers to act as a proxy for doctors in rural areas. But one must be careful in understanding that simply handing out these devices is not the solution. “As per previous experience, community health workers in public health system have been introduced with several new gadgets. Every time an innovation is introduced, these workers are being trained to use these devices. But there is no long terms hand holding by innovators. Innovators need to find out ways to go along with them and just give away the product”, said Tanushree Chaudhary.
With its core focus on providing clinically actionable information at or near the patient, PoC technologies have seen maximum proliferation and advancements in the space of diagnostics and imaging—PoC testing. Technology for PoC testing refers to the ability to acquire clinical parameters where the patient is, thereby allowing faster turnaround times (TAT). PoC testing has evolved quickly from the early tablet tests to dipsticks to the current range of all-in-one tests for broader spectrum of diseases. Some of the commonly known examples are glucose meters, blood pressure monitors, scales, coagulation meters, spirometers, and thermometers. With recent technology advancements, PoC testing is penetrating into broader spectrum of diseases. As an example, a device used to screen for cervical cancer screenings at primary healthcare settings was demonstrated at the conference. Ariel Berry, CEO of MobileODT, introduced to the audience a mobile medical-grade colposcope that uses Enhanced Visual Assessment (EVA) System. In addition to providing enhanced visualization, this device enables direct patient information input, image/video capture, image annotation, and green digital filter application. Deploying the Enhanced Visual Assessment (EVA) System at initial cervical cancer screenings can lead to a higher screening of suspected precancerous and cancerous lesions for women as compared to a Pap smear alone.   
 It is evident from the above example that the PoC testing ensures quicker test results i.e. faster turnaround times (TAT). It must be emphasized the PoC testing will only lead to an improvement in the clinical outcomes if the faster TAT is utilized efficiently by the healthcare delivery chain. Nonetheless, such products can revolutionize the health care especially in developing countries like India which suffers from massive resource gap.  In India, there is a deficiency of over 4 million health workers and to compound problems, nearly 60% of existing health workers practice in urban areas where only 30% of the population resides[1]. PoC testing devices are poised to grow by factors such as demographic and epidemiological transition leading to rising geriatric population and incidences of chronic diseases. With 70% of its people living in rural areas in India, often far from health care providers, it's clear that there’s a lot of room for affordable health services to grow in India.

References:
1. https://www.forbes.com/sites/suparnadutt/2016/11/21/indias-most-remote-villages-are-getting-better-healthcare-with-this-cloud-based-solution/#261b048b593b
 



Revolutionizing Healthcare through Patient Engagement

Naireet Ghosh, Analyst, Max Institute of Healthcare Management, ISB Hyderabad


Historically, the healthcare industry has been relatively reluctant in adopting technology for non-clinical processes. Only recently, care providers seem to have realized the value of enhancing patient experience by the use of technology in order to improve healthcare outcomes. This is evident from the recent boom of the patient engagement solutions market globally. In this article, we look at how some entrepreneurs are helping India keep up with this global change.
At the Health 2.0 conference organized at ISB Hyderabad last month, Madhubala Radhakrishnan, founder of mCURA, demonstrated the clinical management software that her company has recently launched. This software, in addition to providing an interactive user interface to care providers that enables efficient flow of information within the organization, also allows patients to interact with providers through mobile devices outside the clinical setting. Forgot your appointment thanks to your busy schedule? No worries! The mCURA application will send you an SMS reminder a day ahead of the appointment. Reached the hospital, but don’t want to wait outside the doctor’s chamber for your token number to arrive? No worries! You can now spend time at the hospital cafeteria while the mCURA application updates you of the current token number. Other features include medicine reminders, video advice to patients, etc.
mCURA isn’t the only player that is aiming to use technology to change the way that patients interact with the rest of the healthcare ecosystem. Medsolis has a mobile application that acts as a portal for the patient to communicate with the care provider. In addition to providing smart alerts and reminders, it also allows patients to chat with participating physicians and care managers. Healtho5’s online patient portal goes a step further in building a trustworthy relationship with the patient by making them feel supported and appreciated. Timely response to any trouble that the patient may be going through, motivating them to keep going at moments of weakness, persuading them to regularly record their vitals and to not skip follow-up appointments are some of the practices built into Healtho5’s mobile application. Navia Life Care, Saviance, and PharmaSecure are some of the other players that are trying to get a foothold into this USD 8 billion (approx., globally) patient engagement solutions market.
One might ask why the sudden buzz about patient engagement. Traditionally, patients have played a passive role in managing their health. Even the educated class of patients has been reluctant in completing the entire course of medicine, following post-consultation exercise and diet regimens, and attending follow-up visits. The patient engagement solutions seek to change that by making patients active participants in their care. As a basic step, this would mean understanding when and where you need to seek care from. Making and keeping appointments, active participation in medical decision making, compliance with the caregiver’s advices, putting efforts to make healthy lifestyle changes, and open communication with the caregiver are some of the other components of patient engagement. Bringing about such a major change in healthcare delivery would have been difficult a decade back. But today, with technology bridging communication gaps and fostering information sharing, the healthcare ecosystem is poised to make patients an active participant in managing their health.
Patient engagement works wonders for the healthcare industry in ways more than one. The most obvious way would be in leading to better health outcomes. It can also reduce costs by making scheduling more efficient, by reducing dependence on non-clinical staff in hospitals, and by integrating insurance and payments in the patient portal. By getting patients involved and encouraging them to communicate openly with caregivers, the patient experience can be enhanced, thus leading to better patient retention. Furthermore, the patient engagement softwares can collect a myriad of information about patient behavior which can be used by the healthcare community to improve health outcomes of the population as a whole. Patient engagement can, therefore, be rightfully be termed as “The Blockbuster Drug of the Century" [1]. 

References:
1. https://www.forbes.com/sites/davechase/2012/09/09/patient-engagement-is-the-blockbuster-drug-of-the-century/#862ae1256381