Lyfas Life Care

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Birac Big Grant Feb 2022 Premenopause Women Health

Title-

Towards Screening and monitoring Metabolic and Mental Dysregulation using AI/ML in Perimenopausal Indian Women with the help of non-invasive optical biomarker instrument, Lyfas.

Description:

About 25 million women pass through the menopausal phase every year. Early menopause (25-39 years) is now reported amongst 4% of Indian females i.e. a whopping 24 crores. This group is the worst sufferer of emotional, memory, and cognitive balances, which remain undetected and rarely taken care of. With time, they also pose risks for Cardiovascular disorders, Diabetes, Hypothyroidism, Dyslipidemia, Cancer, Arthritis, Osteoporosis, and so forth, resulting in more depression, anxiety, and pathologically suffering low quality of life in Perimenopausal women. This directly or indirectly affects the family caregivers, affecting the lives of almost 50 crore Indians.

m-Health is going to be the future of digital healthcare due to its ubiquity. Lyfas is an m-health instrument that can capture Heart Rate Variability (HRV) and its correlated optical biomarkers ) from the index finger capillary using an android smartphone. HRV and its correlates provide the physiological snapshot of mind-body homeostasis, which is dysregulated in perimenopausal women due to the persistent depletion of estrogen. 

The project aims to capture, analyze and develop an AI/ML-based technology to assess the mental & metabolic risk in this group. 

1. Proposal Summary [Provide a brief one-paragraph overview of the proposal, i.e. the idea and the problem it may solve and brief project plan.]

 

The perimenopausal phase in women’s life is turbulent due to the persistent depletion of estrogen that is the key regulator of their reproductive, cardiovascular, and mental health (mood, memory, and cognitive abilities). If left neglected and untreated, they have a high risk of metabolic and mental disorders. 

Mobile health (m-health) is gaining popularity in the 21st century’s digital healthcare by virtue of its non-invasive and pervasive advantage. Lyfas is an m-health technology that runs in android smartphones. Using the principle of reflected arterial plethysmography, it captures the Heart Rate Variability (HRV) and its associated cardiovascular optical biomarkers (CVb) from the index finger capillary blood flow using the inbuilt optical sensor and the torchlight in the main rear camera of the phone. CVb surrogate for the Cardiac Autonomic Modulation (CAM) that is expected to happen in the perimenopausal phase. The project aims to (a) capture the ‘significant’ CVb at the backdrop of the metabolic and mental dysregulations in the study group as the screening and monitoring biomarkers using Lyfas and (b) develop an AI/ML-based ‘severity’ assessment engine in the Lyfas application. Early screening of severity would help medical doctors to initiate appropriate management to prevent a reduction in their quality of life.

Opportunity
[What is the potential societal and market impact? Provide details of the problem you propose to solve.] What is the problem? Why the Problem is imporatnt to address?How big is the problem? Current societal and country impact of the proble? What are the possible solutions? Why pepblem remain unaddressed? Why no one is working t solve the problem? Why it is important to solve the problem? What societal benefit will be the outcome of the solution of the problem?

Problem Definition

A. Quantified Problem:

The average menopause age in Indian women is about 46.2 years, whereas the same in the developed and western countries is around 51 years[1]. According to a recent survey published in Times of India[2], as many as 4% of the Indian female population is now seeing early menopause between the age of 29-35, and as many as 8% of the women in India has menopause between the age of 35-40. Therefore, it can be said that about 10% of the Indian female population goes through menopause, at least 10 years earlier than expected.

Perimenopause, or the menopausal transition, represents a period of time, that can be between a few months to 4 years[3]. Perimenopause years are the timeline, during which newly arising symptoms can present complex management decisions for providers. Many women present to care with complaints of hot flashes, vaginal and sexual changes, altered mood and sleep, and changing bleeding patterns. The effect of these symptoms on quality of life, even before a woman enters menopause, can be significant[4].

In Short, 10% of the females between the age of 25-44, ie 1.4 Crore females(total population is 28 crore in this age bracket[5], female population at 50% is estimated to be 14 crores), and 6 crore females between the age of 45 to 60, or a total 7.4 Crore females in India at this moment are either going through menopause, or has menopause, or are in the perimenopausal state.

Other than falling fertility, many other health issues called comorbidities are associated with perimenopausal women. In a population study amongst 10,000 Spanish Perimenopausal women[6], The prevalence of risk factors for osteoporosis and cardiovascular disease were 67.6% and 74.8%, respectively. In an Indian study[7], the major ailments associated with menopause were found to be arthritis (25%), hypertension (23%), and diabetes (6%). Another study[8] confirmed that Indian women, who had less than three children were having a significantly higher risk of breast cancer. Because the fertility rate in India [9] has fallen to 2.2 in 2019, almost a majority of the perimenopausal women are at a high risk of such comorbidities. A study in Indian women[10] Conclusion that The two main challenges were not knowing how to correctly access information (38%) and not being aware of reliable sources of information (36%). Therefore, it is essential for policymakers and decision-makers to provide reliable and accurate information to increase awareness and reduce the anxiety of women experiencing menopause.

Thus, almost 7.4 crore Indian females are facing not only perimenopausal anxiety and symptoms but also associated comorbidities of Cancer, Cardiovascular disease, Diabetes, Hypertension, Osteoporosis, Arthritis, all of them further have a significant effect on the mental health of the women, resulting in a degradation of the overall quality of life. The problem is there is no solution for self-monitoring of mental health, metabolic health, and cardiovascular health of perimenopausal women in India.


B. Subjective Problem:

The problem for this work can be defined as to build an affordable, accessible, and scalable personalized screening, and monitoring system for perimenopausal women to detect the early traces of mental health issues, cardiovascular and metabolic issues associated with the perimenopausal phase, and help the women to improve their compromised quality of life associated with perimenopausal phase.


C. Overall Societal efect of the problem:

Almost 7.4 Crore Indian female population, out of the overall female population of about 66.9 Crore is suffering low quality of life, and living with elevated risks of mental health issues(like Anxiety and Depression), metabolic health issues (like Diabetes, Hypertension, Cancer, Osteoporosis), and Cardiovascular health issues (like heart disease), which affects another 22 Crore Indians(1 partner+average 2.2 children) because of ripple-effect of the mental and pathological health disorders spreading to the family and caregivers[11]. Hence, over 20% of the Indian population suffer a compromised quality of life, due to the perimenopausal phase of the women, due to lack of proper monitoring and clinical management.


D. Curremt technologies available as solution

Currently, most of the symptoms associated with the Perimenopausal phase, including cognitive decline, memory decline, mood swings, anxiety, depression, and cardio-metabolic health remain undiagnosed till they become pathological postmenopausal phase. There is no standard clinical protocol, National health policy, or WHO recommendation associated with the problem-set of Perimenopausal women. The only help available is primary health centers, private health clinics, and the regular health checkup available with them, along with basic home monitoring facilities with devices like pulse oximeter, glucometer, blood pressure device, and so on. Certain wearable devices like Apple Watch, helps female track their physical activities, but doesn’t deal specifically with the mental health, and associated Cardio-Metabolic health issues of perimenopausal women. Hence, we can conclude that modern technologies, existing systems have not been able to address the acute and chronic health concerns of perimenopausal women and their families.


E. Why current solution is insuffiecinet

Current solutions are also inefficient because of the prolonged Perimenopausal period of average 4 years, and varying degrees of the symptoms every day. Indian women are traditionally more focused on their family wellness, care less about their own problems. Lack of education and awareness to them in this phase leads to a cascading family effect and leads to unmanaged and unmonitored health issues in the Perimenopausal phase. Mental stigma, physiological, psychological, and pathological health challenges that females suffer during this phase, make them uncomfortable to seek proper clinical help.

The lack of any definite policies makes it hard for the clinical community to provide any dedicated support. The growing cost of private healthcare further deters our females from seeking proper clinical help. Lack of availability of significant population data on such a women group has resulted in a lack of proper national health policies for perimenopausal women, even though the problem affects almost 20% of the overall population.

Not only that, the perimenopausal health challenges are not even defined as and under any specific sets of health challenges. Therefore, there is no distinct diagnosis of perimenopause in either Diagnostics and Statistical Manual 5(DSM-5), or the International Classification of Diseases(ICD-11). Clinically, the clinicians deal with every symptom in isolation, which changes frequently over the four years of the perimenopausal phase. Thus the hormonal, mental, cardio-metabolic, cognitive, and emotional health is not seen as a single interdependent problem and addressed.

In summary, the current systems are insufficient in addressing Perimenopausal female health because:-

  1. Lack of monitoring
  2. Lack of distinct clinical protocol.
  3. Lack of clinical and policy acknowledgement of perimenopause health problems as a category.
  4. Lack of proper education to the perimenopausal women, due to 1,2,3.
  5. Lack of proper knowledge amongst the clinical community to help the patients going through perimenopausal phase.
  6. Lack of acceptance and acknowledgement of the mental health problems, and their ripple-effect in India.
  7. No diagnostics criteria acceptance of the perimenopausal phase.
  8. No interdependent cluster condition of Hormonal, Cognitive, Cardio-Metabolic, Emotional, and Mental health set asscociated with Perimenopausal phase is defined, and management strategies are defined.


F. Proposed system

  1. Repurpose the Clinically Validated Digital Optical Biomarker Mobile Application Lyfas, that is a digital health instrument [12] as a personalized health device for the perimenopausal women, and capture their regular vitals.
  2. Use the Clinically validated Cardiovascular and Cardiopulmonary risk assessment capability of Lyfas[13], to develop Cardio-Metabolic risk assessment, early detection, and monitoring of perimenopausal phase as a single entity.
  3. Develop the validated subclinical-depression detection tracking ability of mHealth instrument Lyfas[14], to detect the perimenopause specific mental health conditions.
  4. Combine step(1-3), to develop a clinical mHealth personalized instrument for perimenopausal women, such that their android smartphone becomes their personalized health device for perimenopausal phase, giving them holistic insight about their cardio-metabolic health, emotional health, mental health as a whole, and provide the same holistic information to the clinican.
  5. Correlate the conditions detected by mHealth instrument Lyfas, with standard sets of questionnaire.
  6. Obtain pathological data of the subjects, including blood tests, cardiovascular tests, USG.
  7. Obtain clinical observation of the subjects, from practicing clinicians.
  8. Develop AI and ML engine specific to Indian Perimenopausal women, by the correlated metric of data obtained from step-4,step-5, step-6 and step-7, to build a screening, monitoring, risk-assessment, and early detection mHealth system for perimenopausal women.
  9. Enroll a group of women in pilot longitudunal observation phase, to develop statistical and analytics engine to obtain key metrics and trends specific to Perimeopausal group.
  10. Provide the statistically significant Insight to the health authority and clinical community to develop Combined Holistic Diagnostics and Management for Perimenopausal women that incorporates Integrated health of Hormonal, Cognitive, Emotional, Cardio-metabolic, and Mental health conditions.
  11. Obtain the quality of life Quantitative metric of all the subjects from the study group from [15].
  12. Create a knowledgebase(Blog, Video, Podcast, Discussion Forum) depending upon the step-8 and step-9, and obtain the quantified quality of life of the study group at the end of the study.
  13. Demonstrate that Lyfas Perimenopause can significantly improve the quality of life in the perimenopausal women.
  14. Publish the statistical data, clinical findings, observation, correlation, validation, of Lyfas Perimenopausal mHealth System(Comprising of Lyfas mHealth personalized mobile application, AI and ML for risk prediction, Content for Education, Analytics for monitoring) as a Clinically validated standard mHealth system for the Perimenopausal women.
  15. Seek CDSCO clearance of the Lyfas Perimenopausal mHealth System, and roll out the system for all the females of the country.


G. Benefit of the poposed system

  1. Low Infrastructure Cost:- The system can be implemented at no cost for the infrastructure, as the personal mobiles of the usergroup will be turned into a personalized mHealth clinical instrument.
  2. Fast Adaptation:- The Application can be adiopted really fast by publishing in the app store/ or digital distribution channel.
  3. Data Driven Educational Content:- Anonymized statistical insights can be published in the public domain for the relevant authorities and autonomous self-help group to develop educational content to educate the usergroup, and their caregivers, families.
  4. Improved Quality of Life:- By combining screening, monitoring, and education, quality of life of the perimenopausal women can be improved significantly.
  5. Lesser Burden on the Healthcare:- By early detection and intervention of the associated mental and cardiometabolic health comorbities, the early symptoms can be prevented from becoming chronic, thereby reducing significant load from the already stressed healthcare system.
  6. Overall Family Mental Health Improvement:- By the law of ripple effect, improved quality of life in the perimeopausal women will also result in an overall improvement in their overall family quality of life.
  7. Financial Savings on Health:- Females can avail the service at a very low cost monthly subscription, reducing their burden on spending in major health issues, due to early detection and intervention.
  8. Job Creation:- Additional jobs can be created for educated women currently not working(around 50 lakh of them), through training, to act as the health assistants for the perimenopausal women.
  9. Integrated Digital Health Infrastructure for Perimenopausal Women:- A single digital health infrastructure can be offered accross the country, making digital mHealth a supportive healthcare for the unadressed group of perimenopausal women.
  10. Better Holistic Health Management:- Based on the data driven learning, the clinical authorities can device better Integrated holistic health management strategies for the perimenopausal women.
  11. Improved Productivity:- As the perimenopausal phase affects the mental and pathological health of the females, the overall productivity of the workplaces where a huge percentage of these females work decreases. By providing better care to this group, the ovserall productivity of the workplace, and thus the country can be improved.
  12. Healthcare Availibility:- mHealth will make it possible for better pentration even in the remotest parts of the India, and a large population can be brought into digital health umbrella through the females, making healthcare available to every part of India, and to every Indian a reality.
  13. Government Benifits:- Data driven policy, resource allocation would help the governments significantly to plan and manage the budget for the Perimenopausal woman. The government would become the first government of the world to offer a single integrated holistic digital mHealth for perimenopausal women.


H. Current srtate of the proposed system

  1. mHealth instrument Lyfas is developed, and the Optical biomarkers are validated[12].
  2. A preliminary Cardiovascular and Cardiopulmonary risk assessment system is developed and validated[13].
  3. Such Cardiovascular Biomarkers can be repurposed for monitoring Cardiovascular risks in other user groups is demonstrated by using the cardiovascular markers to assess the risks in Duchene Muscular Dystrophy genetic disorder by [16].
  4. That smartphone based mHealth instrument can be used to monitor Physiological health like Sleep, and associated clinical conditions can be correlated is demonstrated by the observational study[17].
  5. That Lyfas can detect early mental health problems is validated in [14].
  6. Quantitative Quality of Life Assessment Mental Health instrument is implemented [15].
  7. That Lyfas can be used to monitor women health, and early intervention can improve women’s health is proved through a public domain case study of Amenorrhea reversal case study[18].
  8. That female health can be screened with Lyfas is shown through public domain case study[19].
  9. That country wide statistics can be developed, and generated, and meaningful information can be extracted has been demonstrated through public domain population case study[20]
  10. That Lyfas is an acceptable and viable digital health instrument is proven in COVID, through its Aysmptomatic COVID Detection System, developed by the support of Kawach grant[21].
  11. That Lyfas is a accepted digital mHealth tool by the governmet is proven by its inclusion in Digital India COVID resource in official Digital India listing[22].
  12. That Lyfas Holistic health can significantly improve the quality of life is validated by our patients, in their Google Review testimony[23]

In summary, Lyfas is validated as a viable mHealth instrument, capable of early detection, monitoring, and intervention assessment and prognosis mental, cardiometabolic health instrument, that is affordable, commercially viable, and that can improve the quality of life of the patients, and that can be repurposed for other applications. Now we want to build the digital mHealth infrastructure for perimenopausal women, to serve 7.5 Crore Indian women, and almost 30 crore Indians directly and indirectly affected by the perimenopausal health issues through Birac Big Grant Support.


I. How proposed systtem will be implemented to user group?

Phase I: Observational Study
  1. First An awareness program will be run to invite participation of 100 perimenopausal women to participate in the early observational study through our content awareness drive using Blog and Videos.
  2. The applicants will be screened by the in house clinical team for qualifying in the study.
  3. All the necessary compliances including consent form would be signed by the enrolled subjects.
  4. Vagus Hospital Bangalore would be partnered for the study.
  5. Lyfas mHealth instrument will be installed in the selected subjects.
  6. A digital form will be provided to the subjects, to input their daily symptoms of physiological, physical, emotional, and mental health conditions.
  7. Their pathological tests will be conducted as per standard clinical recommendation at the beginning of the study.
  8. The subjects would be asked to take three Lyfas tests everyday for one month.
  9. The Lyfas Biomarkers, Clinical Observation, Pathology data, Emotional, Mental health and Symptom data will all be evaluated statistically for correlation.
  10. Various Correlation tests like Linear Regression, Pearson’s Correlation, Bland Altman, Man Whiney will be run to distinguish the significant biomarkers, their association with the conditions, internal consistancy and statistical significance.
  11. The findings will be provided to practicing Gynecologists for clinical relevance and correlation.
  12. The findings will be published in Peer Reviewed Journal.
Phase II: Accuracy Study

11. Another set of 100 subjects would be enrolled, following the criteria as specified in steps 1,2,3.

12. Lyfas mHealth Instrument would be repurposed based on statistically significant biomarkers as developed in phase I.

13. The new Lyfas Perimenopausal mHealth instrument would be installed in the enrolled subjects.

14. One month of monitoring by Lyfas mHealth perimenopausal instrument would be performed in the subjects, by asking them to take three Lyfas tests every day for one month.

15. Subjects would be asked to fill their emotional, mental health, and physiological health conditions through a specifically designed questionnaire instrument.

16. The data from Lyfas, and the questionnaire instrument would be provided to an independent practicing gynecologist, along with the Phase-I study. The clinician will validate the correlation of Lyfas finding with self-reported conditions, as well as clinical findings.

17. Accuracy, Specificity, and Sensitivity would be derived statistically and would be published in a peer-reviewed journal.

Phase-III: Validation Study

18. The selected 200 subjects from Phase-I and Phase-II would be re-enrolled in the validation study.

19. Current gold-standard clinical investigation techniques and tests will be done on the subjects, as well as their monitoring with Lyfas mHealth instrument.

20. Correlation of Lyfas findings, with Measured clinical conditions through current gold-standard would be performed.

21. Closeness of Lyfas findings with that of the current gold standard would be evaluated.

22. Yoden’s Index would be calculated for the same.

23. The study will be repeated with updates in the heuristics and algorithms, till an accepted Yoden’s index>0.6 is not achieved.

24. The findings would be published in a peer-reviewed journal.

25. This would establish Lyfas mHealth Perimenopausal Instrument as a valid clinical assessment instrument.

Phase-IV: Case-Control Study

26. A group of 100 menstruating females and another group of 100 post-menopause women will be enrolled in the study, along with the 200 perimenopausal women part of Phase-I, II, and III studies.

27. The subjects are divided into three groups: I) Menopause Women II) Perimenopausal Women III) Menstruating Women.

28. Lyfas mHealth Perimenopausal instrument will be installed in all the subjects.

29. Subjects would be taking three Lyfas tests every day for one month, along with self-reporting of their emotional, mental, physical health conditions.

30. After a month, cluster analysis would be performed amongst the groups. It must be shown that Lyfas can distinguish the health conditions of all the three groups separately and that there is a significant statistical difference amongst the biomarkers in the different groups.

31. Symptomatic, and Biomarker derived health conditions will be correlated for inter-group, and intragroup significance, as well as intraclass and interclass significance.

32. The statistical data will then be correlated clinically by a team of Independent practicing Gynecologists.

32. The results and the findings would be published in a peer-reviewed journal.

33. At the end of this phase, it would be proven that Lyfas can distinctively assess the health conditions of perimenopausal women, in relation to other groups of women. This will also establish the Lyfas Perimenopausal mHealth instrument as a clinically relevant instrument for Perimenopausal women.

Phase V: AI and ML development for the Early Detection and Risk Assessment

34. All the data from the past studies would be used to design a Machine Learning and AI algorithm.

35. Existing data will be divided into a Training set and Test Set.

36. Classification algorithms will be developed using AI.

37. Accuracy, sensitivity, and specificity would be calculated. This is called base Performance.

38. Reinforcement learning from New data would be implemented.

39. All three groups of women would be asked to capture data for another month.

40. The new data would be again divided into training and test sets.

41. The ML must enforce its learning with a new set of training data.

42. New test data would be classified with the AI. The new performance(Accuracy, Sensitivity, and Specificity) would be called Post-Learning Performance.

43. It would be shown that the post-learning performance is better than the base performance. The entire engine would be fine-tuned till this goal is achieved.

44. The AI, ML, training, Testing, and Learning results would be published in a peer-reviewed journal.

45. This will establish the Lyfas Perimenopausal mHealth instrument, as a complete mHealth System for Perimenopausal health assessment.

Phase VI: Longitudinal Study

46. A group of 500 perimenopausal women, that may include the already participating women, into a 6-month Longitudinal study. The objective of the study would be to predict the health conditions with Lyfas Perimenopausal mHealth Instrument and measure the accuracy of the prediction.

47. Monthly health conditions would be predicted by Lyfas Perimenopausal mHealth System, from the data acquired from Lyfas Perimenopausal mHealth instrument of the subjects.

48. Monthly clinical investigations would be carried out by the practicing Gynecologist for all the subjects, and the clinician would document the monthly health condition of the subjects.

49. The clinician would also be provided with predictive analytics from the Lyfas Perimenopausal mHealth system. He would correlate both the data in blind clinical correlation.

50. After 6 months, the accuracy of Lyfas Perimenopausal mHealth System, with the Clinical observation would be estimated.

51. The findings will be validated by standard statistical tools.

52. The results would be published in a peer-reviewed journal. This will establish Lyfas Perimenopausal mHealth System as a clinically relevant system, capable of screening, detecting, and forecasting the early risks of holistic integrated health conditions amongst perimenopausal women, including their mental, emotional, cognitive, physiological, and pathological health conditions.

Phase VII: Quality of Life Improvement Study

53. The 500 subjects from the last study, would be re-enrolled for the current study. The objective of the current study would be to demonstrate that Quality of Life can be improved in perimenopausal women, by early intervention, counseling, and educating the women with data-driven insight and counseling.

56. Trained mental health practitioners, practicing gynecologists would be selected and would be educated about Lyfas mHealth System findings, and the progressive and key clinical conditions observed in the perimenopausal women in the previous study.

57. The team would be assigned the task of designing simple counseling, content, and clinical care-based protocol to assist the women to improve their health conditions.

56. Quantitative Quality of Life Measurement[15] will be taken from all the subjects.

57. Weekly predictions and assessment of the health conditions of the enrolled subjects as provided by Lyfas mHealth System, from the data captured from Lyfas mHealth instrument of the subjects would be provided to the Clinical team.

56. The clinical team of Gynecologists and Counsellors will identify the risks and would create relevant content, to be given to the subjects for taking care of those conditions.

57. Monthly online counseling and consulting would be facilitated to the subjects, to further guide them to improve their health.

58. After 6 months, again the quality of life of the subjects would be measured through [15].

59. It would be shown that the health deterioration of the subjects is much lesser after this intervention than observed in Phase-V. Also, there is an improvement in the quality of life.

60. The simple management protocol, along with the quality of life improvement would be tested through the standard statistical tests, and would be published in a peer-reviewed journal.

61. This will establish the Lyfas health system as a clinically reliable prognosis system that can assist in adaptive perimenopausal management protocol, and that early detection and intervention can significantly lower the risk in perimenopausal women.

Phase VIII: Pilot Implementation

62. The developed system would be offered in a Pilot commercial study amongst 2000 Perimenopausal women, at an affordable monthly subscription fee.

63. A group of mental health counselors and practicing Gynecologists would be invited to get trained in Lyfas Perimenopausal mHealth System.

64. The clinical team would be duly trained in the system.

65. The females availing of the service may take the clinical service from the trained clinicians in Perimenopausal digital health.

66. Proper Digital Health Workflow would be built and curated as a platform to integrate screening, monitoring, health assessment, and clinical services in a single solution called Lyfas Perimenopausal mHealth Platform.

67. Customer feedback on the improvement of the quality of life in the commercial user group would be obtained.

68. Feedback from the clinicians part of the pilot would be taken.

68. The findings would be published in a peer-reviewed paper. This will establish that Lyfas mHealth Platform is a commercially viable, and clinically significant platform that can offer integrated health solutions to perimenopausal women, through dedicated clinical service, specialized in perimenopausal health.

69. This will also establish Perimenopausal health as a single clinical entity, allowing better clinical protocol and management strategies.

Phase IX: Perimenopausal Digital mHealth Solution Project Report Submission

70. A detailed and comprehensive project report would be created for submission to the government to enable the government to evaluate the policy-level implementation of the solution.


J. what will be societal -country-benefit, if you solve the problem

The quality of life of 7.5 crore Indian women and their associated family members will be improved. The Indian women would have the world’s first dedicated digital clinical solution to help them with their health conditions in the perimenopausal phase. The solution will reduce the comorbidity risks in perimenopausal women, thereby reducing the load on healthcare. The data and insights from the solution would enable the government to devise data-driven policies for Perimenopausal women, leading to acknowledging perimenopause as a recognized clinical entity. This would facilitate clinicians coming forward wanting to be dedicated perimenopausal healthcare professionals, creating an entire ecosystem. This ecosystem would further create enormous jobs amongst women, housewives in particular to become perimenopausal counselors. Better management protocols can be designed by the clinical authorities based on real data and insights that would finally result in improvement in the menopausal age amongst Indian women. The cascading effect in 3-5 years’ time, may improve the menstrual health of the females, resulting in the extended menstrual age, improved fertility rate, and reduced mortality in females due to perimenopausal comorbidities. Preventive perimenopausal health may in turn benefit the overall economy, by reducing the healthcare expenditure in chronic disease management in the user group, allowing more investment in the infrastructure in the healthcare.

Women are worshipped in India as goddesses. The system can put India as the pioneer country in Perimenopausal women’s Health, and the country can become a leader in the Global Perimenopausal Digital Healthcare. It is well-known fact that every woman serves at least ten people in society. Improving the overall mental, cognitive, emotional, hormonal, and cardiometabolic health in perimenopausal women would result in overall improvement of quality of life in nearly the entire society.

In ten years’ time, India can emerge as a healthy country through women’s health empowerment, putting forward the foundation for a healthier, happier India of tomorrow. Free from health risks, the country can push forward to become the global leader and driver of the health, and economy.

Briefly state the Objectives and Proposed Approach[Describe how the proposed project addresses the problem.
Clarify the current status of the innovation.]
The description should cover the following points:
1). Strategy and/or methodology of work.
2). Scope and boundaries of the work, including any issues that will not be covered.
3). Data analysis (sample size,data collection)

A. Scalable and accurate, easily adoptable solution to mentioned quantified problem:-


B. Description of the solution – covering following points.

a. Customer Demography and Problem Set:

Females between the age group of 29-50, have early symptoms of Menopause, including missed periods, pre-menopausal syndrome, hormonal depletion symptoms, Amenohhrea, and other symptoms that are clinically accepted as Perimenopausal risks. The proposed system would offer an Integrated holistic health assessment of Mental, and Cardiometabolic Health amongst the women who are either in a perimenopausal state or are on the verge of entering the stage.


b. How they will come to know:

  1. Through Awareness Content publishing in the social media and through blogs.
  2. By partnering with NGOs in awareness drive.
  3. By partnering with women self-help groups and spreading the awareness through them.
  4. By approaching successful women influencers and doing influencer marketing through them.
  5. Training Asha and Anganwadi workers about Lyfas Perimenopausal mHealth Solution, and carrying out awareness drive to the end users, as well as through primary health centers.
  6. By scientific publications in reputed journals, clinical community would be attracted towards the solution.
  7. The awareness would be driven through the trained clinical community.
  8. Government authorities and wings will be presented with the solution to encourage the state and central governemnt to incorporate the solution as part of their digital health program.
  9. Customer testimoneies will be published to encourage other women to opt-in for the service through the concept of social-proof.


c. How they will approah us (availing service):

The Lyfas Perimenopausal mHealth instrument would be distributed through App Store or other Digital Channels. The clinicians, primary, secondary, and tertiary health centers, as well as the private clinics would advise the relevant user group to avail of the service from the digital distribution channel.

Consumers will download, and install the application on their Android smartphone seamlessly.


d. Educating potential consumer about the product:

  1. By publishing success stories in Social media and Blog.
  2. By publishing the Video and text testimoneies of the consumers.
  3. By publishing the testimoneis of the primary caregivers and the families.
  4. By publishing the case studies and real stories.
  5. By collecting email ids of the females from partners and publishing regular newsletters.
  6. Through the Asha workers, Anganwadi workers and the nurses, the females visiting the health centers would be educated.
  7. Dedicated mHealth Assistants might be onboarded inline with the LIC agents, and these females can be entrusted with spreading the awareness and onboarding the females needing the service.


e. Deployment

The system doesn’t need any additional hardware. Therefore the Lyfas Perimenopausal mHealth Instrument, which is a mobile application can be distributed through the digital channel. The application will be integrated into the Lyfas Perimenopausal mHealth platform, which would have the AI and ML-enabled Lyfas Perimenopausal mHealth System, and Lyfas Perimenopausal mHealth System trained clinicians and counselors.

Online training programs and certified courses would be designed for the clinical professionals to expedite the clinical support system onboarding efficiently and to build the overall digital mHealth ecosystem for perimenopausal women.

Partners might be invited to create curated content for different clinical and subclinical conditions associated with the Perimenopausal phase, to spread more awareness and dedicated education and knowledgebase.

Through secured APIs, statistical insight can be shared with relevant government agencies, and medical institutions for carrying out epidemiological studies and research, further strengthening the scientific core of the solution.

Prognosis insights can then be used by the clinical community to improve the management protocol, which can be integrated into the solution seamlessly.

IoT and Big data-enabled real-time alert systems can be developed to trigger timely intervention.


f. Monitoring

Self-monitoring and statistical insights of different aspects of integrated health conditions pertaining to perimenopausal women would be integrated into the application. Users can search for improvement recommendations in the management content and can take a self-improvement path.

A Digital forum can be built to empower the users to share their learnings and stories for the benefit of the other users. The live dashboard can be built to track the health of the users segregated by geography and demography for policy-level strategic decision-making.


g. Analytics

Predictive, Monitoring, Statistical Analytics will be integrated onto the Lyfas Perimenopausal mHealth solution at the instrument, platform, and dashboard levels for dedicated curated real-time insights to the users, caregivers, clinical community, and authority.


h. Alert and awareness

Risk heuristics on the Analytics would be integrated to generate a real-time alert, that would be sent to the users, primary caregivers, and the associated clinical team to enable early intervention to minimize the risks.


i. Technical brief

  1. Lyfas Perimenopausal mHealth Instrument:- A clinically validated mobile application that captures the digital psychophysiological biomarkers in average five minutes, when a user puts her index finger on the mobile rare camera in an Android smartphone, using Photoplethymography, Arterioplethymography, and Photochromatography principles.
  2. Lyfas Perimenopausal mHealth Heuristics:- This is an algorithm engine, that would filter the relevant biomarkers, from the group of biomarkers, and would attach distinguished Physiological, Psychological, and Pathological health conditions from the biomarkers.
  3. Lyfas Perimenopausal mHealth System:- An AI and ML enabled system to screen early health risks, detect any underline silent health condition, and predict the progress of the condition.
  4. Lyfas Perimenopausal Clinical Support System:- Trained group of human clinicans, support staffs, and counsellors, trained in the Lyfas and Perimenopausal health, who are equipped to help the users with their health conditions.
  5. Lyfas Perimenopausal mHealth Platform:- An integrated digital health workflow to integrate the instrument, system, users and clinical support staffs.
  6. Lyfas Perimenopausal mHealth Content Service:- Content developed by inhouse team or partners to help educating the users about the perimenopausal health and management. This content services would be integrated into the platform.
  7. Lyfas Perimenopausal mHealth Analytics:- Curated data analytics and insights to enable users, caregivers, and the clincial team to take better care of the mental, and cardiometabolic health of the users.
  8. Lyfas Perimenopausal mHealth Public API:- To enable anonymized statistical data ingestion over IoT accross various entities for facilitating data driven research, management protocol development, policy making, strategy development, public awareness, and content development.
  9. Lyfas Perimenopausal mHealth Training Module:- Curated Digital Training content for efficient training and onboarding of clinical, support and counselling staff into the system.
  10. Lyfas Perimenopausal mHealth Dashboard:- To facilitate a dashbaord that can be customized based on geography and demography, for real time insight monitoring of group of users.
  11. Lyfas Perimenopausal mHealth Management Protocol Inventory: Clinical observation, recommendation, and protocols for management as developed and published by the associated clinical entities. This inventory can be used as a global inventory for taking standardized measures and management decisions by the existing and new clinical team of Lyfas perimenopausal mHealth Clinical experts.

Current Innnovation & innovation stage:

Strategy:


A. Validation Startegy:

  1. The entire validation will be conducted in seven phases: i) Observational study(100 Subjects) ii) Accuracy Study(subjects 100), iii) Validation Study( subjects 200), iv) Case Control Study(Subjects 300), v) AI and ML study(existing data), VI) Longitudunal study(subjects 500) VII) Pilot implementation study(subjects 2000).
  2. In each study, relevant clinical observation, clinical data from other gold-standard instruments would be taken. Data from from Lyfas Perimenopausal mHealth instrument, and system will be correlated with other data using statistical correlation and human practicing clinician’s correlation.
  3. All the findings would be published in reputed peer reviewed journals.

B. Awareness Startegy :

  1. Blogs, Case Studies, Testimonials, Newsletters, Videos, Scientific findings, Clinician’s testimonials, Caregiver’s testimonials would be sent through emails, published in our blogs, in the social medium channels for more awareness.
  2. Same content will be distributed through our implementation partners, including but not limited to NGOs, women self-help groups, Asha workers, Anganwadi workers, trained nurses, onboarded clinicains, primary jealth centers, private clinics, and government authorities.
  3. Digital Forum or Messageboard would be created for the users and clinicans to share their questions, answers and findings.
  4. Scientific publications would be published to motivate more practicing clinicans to become part of Lyfas Perimenopausal mHealth clincial community.

C. Implementation Strategy

  1. The project would be implemented in phases, validating the objectives of each phase, and publishing the findings in the peer reviewed journals.
  2. Once the entire platform is validated through well designed study and publication, the findings will be shared as a single project report to enable the authorities to accept the same as part of Digital Health initiative.
  3. Partnerships will be made with the relevant groups, individuals, bodies, and authorities to seamlessless spread the awareness, onboard more relevant support system, motivate more users from the relevant user groups to avail the service.
  4. The solution will be distributed through secured digital channel that wouldn’t require any investment on the additional hardware and software.


D. Scalability Strategy

Scalability would be implemented in phases:-

  1. In Pilot phase, commercial viability and business model would be created with digital workflow to connect the stakeholders such as clinicians and users. This will be implemented through private restricted digital channel distribution.
  2. Once the pilot phase is completed, the Lyfas Perimenopausal mHealth project would be scaled through dedicated partners to 5000 users, and the implementation would be optimized. This will be implemented through private restricted digital channel distribution.
  3. The system would be finetuned for 5000 use groups, and then the system would be rolled out for the public domain mass adoptation. At this stage the project would be hosted on a scalable cloud and proper data, security, and other compliances would be implemented to support mass usage.

Note: Only phase I implementation would be part of the grant project. The following two stages would be carried out after the project for the grant is successfully accomplished.


E. Pricing startegy

  1. Survey Pricing will be carried out with different pricing models.
  2. Market research on the current spendings by rural and urban perimenopausal women on their health would be estimated.
  3. Income vs spending ratio of women for their health would be calculated.
  4. Market research would be carried out on all the competitors price offering.
  5. Customer acquisition and retention cost would be calculated in based on spending during study phase.
  6. Competitive pricing model, differentiating pricing based on differential services would be developed.
  7. Product pricing would be adjusted in the Pilot phase.
  8. Final pricing would be offred based on the above calculations, which will be a monthly subscription model with basic plan, premium plan, and add-on plans.
  9. As a whole the solution, along with the services would be offered as a SaaS model.

F. Competition startegy

  1. Affordability:- The system would be more affordable than any other current or future compititors.
  2. Unit Economics:- The unit economics would be calculated using the standard market tools, and would be made profitable, unlike current startup culture of bearing huge unit economy loss at the early stage.
  3. Fast Scalability:- Due to minimum implementation cost, and first mover’s advantage, we would be scaling the project fast enough to win over any existing competition.
  4. Accessibility:- The solution is a mHealth solution, and therefore would be accissible across the country in a ubiquitus model.
  5. Availibility:- Because the health test can be conducted just from the mobile, the solution would be available to Perimenopausal women, anywhere, anytime.
  6. Shared Economy:- From the solution to the services, all would offer the stakeholders to plugin services just as apple playstore, thereby enabling more employment and income generation accross various stakeholders, creating a shared circular economy.
  7. Constant Improvement:- Our proposed data driven API model will enable global and continuous research and development by third parties, thereby enabling constant upgradation of the system.


G. Market Penetration strategy(Got to Market Strategy or GTM)

  1. Lyfas Perimenopausal mHealth mobile instrument development and validation.
  2. Lyfas Peimenopausal mHealth System with AI, ML and Analytics development and Validation.
  3. Pilot Implementation of the Same.
  4. Clinical support system training and onboarding.
  5. Integrated Platform development of Lyfas Perimenopausal mHealth System, Instrument, Clinical ecosystem, and Users.
  6. Spreading awareness through Blogs, Videos, Newsletters, Case studies and other contents that are primarily categorized into data driven insights, real succcess stories of the stakeholders, testimonials.
  7. Partnership with various woman groups and stake holders to accelerate the implementation and adoptation.
  8. Partnering witht the government authorities, to promote the project from the government bodies, and to encourage various state governments to adopt the solution as part of their digital health policy.
  9. Corporate partnerships, to secure CSR projects, and adoptation of the project amongst Perimenopausal women working in the corporates.


H. Market Winning strategy

The following approach would be adopted for winning the market:

I) Scientific Validation: Most of the current technologies that enable monitoring are all related to wellness, and very few clinically validated technologies are available, thereby giving us a distinct advantage of trust.

II) Economy of Scale: Due to no cost on the device and the infrastructure, the project can be scaled to different geographies fast and efficiently.

III) Social-Proof: Females tend to follow the other females of similar affinity. By allowing social share and testimonials, other perimenopausal women would be encouraged to join the platform to avail of the service.

IV) Technological Advancements and Integrations: AI, ML, Big data analytics, Dashboard, IoT enabled real-time alert, Dashboard, and various technological entities would be seamlessly integrated into the solution core, enabling modular plugins, that would enable us to implement various business models and service models.

V) Human-Machine Mixed Intelligence: Most of the modern healthcare are not digitally equipped, and the digital infrastructures are not powered by scalable screening, monitoring tools, and data-driven prognosis. We will win the market because of the mixed intelligence model, which was first implemented successfully by PayPal.

VI) SaaS model:- Software as a service has been a proven viable and unbeatable business model. By offering various modular add ons to other clinical entities like clinics and hospitals, we would not only be building commercial viability from the D2C model but also enabling B2B service delivery, thus making us one of its kind in not only the perimenopausal health but the entire modern digital healthcare.

VII) Collaborations: Collaboration of Public, Private, and Government entities would enable us to win the market, as other services and companies lag such an extensive collaborative model.

IX) Constant Research and Development:- The data model, and API interface would attract global researchers, therefore integrating ongoing research and development onto the system, thereby creating a massive scientific and technological degradation and growth.


J. Business Sustainability strategy

Following strategies could be adopted for business sustaining:-

  1. Gammification of the system, through which good health can be promoted, and those of the users who achieves their health goals might be rewarded.
  2. Customer Loyality Points:- Using customer loyality points, customers can be awarded virtual points which can later on be encashed by opting for other services.
  3. This would further encourage the customers to promote the service in their near and dear ones.
  4. Using circular shared enonomy model, more capital rotation would be achieved within the ecosystem, making the ecosystem more commercially sustainable.
  5. More services and solutions can be integrated over the time into the platform, like digital health store offering various supplements and medicines, homecare and nursing services, and so on, improving the revenue verticals of the solution.
  6. More certified courses would be offered to interested careproviders, and clinicians such that number of service providers increase along with the increase in the end-users.
  7. Targetted revenue growth must be achieved through month on month planned growth achievement, to scale and grow the business commercially.

Methodology:

The following points explain only the science and technology methodology

A. Sensing

Lyfas Perimenopausal mHealth instrument is an android smartphone software application, that would sense video data, when the end-user places her index finger over the rare mobile camera, and then would convert the 2D video data to one-dimensional pulse signal by using the pulse volume variation principle of photoplethysmography. [12]

B. Filtering

Data capture might be affected by variation in environment, muscle noise, noise due to user’s posture changes, inherent breathing envelop attached with the pulse signal. The signal will be filtered using the proprietory filtering algorithms.

C. Data

Continuous heart rate would be calculated from this cardiac pulse signal, from which heart rate variability Cardiovascular Biomarkers would be calculated[12]. These biomarkers are the data of the test and the system.

D. Algorithms

Algorithms will form the Heuristic layer of the system. They will be used to correlate the Cvb to various Psychological, Physiological, and Pathological conditions.

E. Biomarkers

The result of the Algorithms would be the final sets of biomarkers relevant to Perimenopausal Mental and Cardiometabolic health. These biomarkers can be used for screening, monitoring, predictive analytics, and clinical decision-making.

F. Knowledge Base

The biomarkers and associated clinical conditions would act as the Knowledgebase for the machine, from which the machine will be periodically trained using reinforcement learning.

G. Big data system

Big data is a scalable opensource architecture for large Hybrid data storage, where data has Velocity, Variety, and Veracity. Because the Lyfas Perimenopausal mHealth solution would require a complex data definition to be integrated, that includes biomarkers, clinical symptoms, clinical data, pathological data, clinical observations, management protocols, and so on and so forth, Big data technology will be used to host this data. As big data also enables easy geographical maintenance of the data, and important features like scaling, replication, and backup, this would provide a high level of security and flexibility to our data.

H. Machine Learning

A multi-layer Neural network or hybrid neural network would be implemented as ML, enabled with reinforcement learning, so that the network can train itself based on the new data and insights, thereby increasing the accuracy and efficiency of the system.

I. AI, heuristics, detection, classifiation

Clustering, Regression, Classification, and predictive analytics would be the major AI algorithms, that would be used to make sense of data, detect the clinical conditions at an early stage, monitor the conditions, and predict any future health adversity of the conditions.

J. IoT and alert

Real-time Alert based on IoT would be implemented(using scalable MQTT protocol), or a push notification system would be integrated for in-time alert, enabling real-time risk mitigation through early intervention.

Scope and Opportunity of the Project

1. Scope

A. Type of users we will service

Women, between the age of 29 to 50, who are either clinically declared to be going through the Perimenopausal phase, or are suspecting perimenopausal phase, or have symptoms that are defined as the clinical symptoms associated with the Perimenopausal phase, for early detection, screening, monitoring, and risk prediction of perimenopausal mental, or cardiometabolic health, by the suggestion of their clinicians, for the clinicians to be able to make appropriate clinical decisions, and offer a management protocol to the users based on data-driven early intervention.

B. Psychological conditions addressed:-

We will be addressing negative thoughts, depression, anger, and anxiety as primary mental health conditions.

C. Physiological Conditions Addressed

Our focus would be to address the most common physiological conditions such as 1) Sleep 2) Stress 3) Autonomic Homeostasis 4) Energy and tiredness 5) Vo2Max 6) Biological Aging 7) Pain and Neurological response.

C. Pathlogical risks addresd

Our primary objective would be to provide a detailed cardiometabolic risk profile to the users, and their clinicians. Primary Cardiovascular risks are intended at this stage(but not ensured or limited to) are I) Ecopics II) Erratic Heart rate III) Fibrillation and palpitation, IV) Sinus Arrhythmia of Bradycardia and Tachycardia V) Non-sinus arrhythmia VI) Cardiac fitness VII) Arterial Stiffness and Endothelial Dysfunction.

Metabolic risk assessment as planned as of now(not limited to or subjected to change based on observational study) are Hypertension, Insulin resistance, Hormonal variance, Digestive health, Musculoskeletal Health.

D. End service and outcome (how digital workflow between the doctor and the patient carried out):-

  1. A Perimenopausal woman would be advised by her clinician to opt-in for Lyfas Perimenopausal mHealth solution.
  2. The patient would visit our digital distribution channel, make online payment, and would avail the service.
  3. She will install Lyfas Perimenopausal mHealth Instrument, that is an android application, in her Android smartphone.
  4. She would take her non-invasive 5 minute’s Lyfas health test by keeping her index finger on the rare mobile camera. She would take the tests at specific time of the days, or on specified days as advised by the clinician.
  5. An instant report with summary of her mental and cardiometabolic health will be given to her as pdf report.
  6. She can learn more about the conditions and how to manage them, by visiting our knowledge content portal.
  7. If there is any issue that needs immidiate medical intervention, an alert would be generated to the clinician.
  8. The clinican would be able to communicate with the patient through digital communication(either in-App or any other applications).
  9. Raw biomarker data of each test would be stored in Bigdata storage.
  10. Event triggers running on the server, would create automatic statistical and data insights.
  11. Visualization layer, that forms the dashboard would be updated based on this data, so that patients, and their relevant clinicains can see individual dashboar, or a cumilative dashboard, filtered by demography and geography.
  12. The patient can obtain online consultations once a month. All the records associated with the consultancy, including prescriptions, observations, symptoms, recommendations would be updated in the bigdata storage linked by the patient ID.
  13. Provision for updating other relevant clinical information, such as pathological test reports or symptoms would be associated would be provided as a portal integration with the solution.
  14. Forum for open discussion and knowledge sharing would be part of the solution, that would enable the stakeholders to discuss various healthconditions related to perimenopausal women health for public consumption.
  15. Relevant clinical protocols for management and monitoring, as developed by entities or authorities would be uploaded in the storage, that can act as processflow guidelines for the patient and her clinical support system.
  16. Secured API would be provided for third parties to ingest relevant data and insights from the integrated BigData system.

2. Boundaries:

a. Work flow that will not implemented and why?

The following workflow will not be implemented

  1. EHR system ( as there are several EHR systems already available as open source, which will be integrated in the post BigGrant Project completion, at mass scalability stage)
  2. Data Encryption techniques would not be implemented as standard encryption would require end-to-end system implementation, testing, and optimization.
  3. Automatic recommendation would not be part of the project, because such recommendations would need extensive clinical study and publishing.
  4. Manual input of other home monitoring devices such as Blood Pressure, glucometer, weight scale would be provided, but wearable device integrations like Polar H10 belt wouldn’t be part of the system as wearable devices serves wellness, whereas Lyfas Perimenopausal mHealth solution is intended as serious clinica workflow.

b. Type of users we will not be able to serve and why?

  1. Apple iPhone application would not be part of the system, as our base system is built and validated for Android users and almost 70% of India’s population uses Android. Thus 30% of the iPhone users would be excluded from the users, more so because they belong to more economically stable groups who can afford extensive medical care.
  2. Women with Amenorrhea and those who misses their regular periods, having similar symptoms as Perimenopausal women, but are diagnosed of metabolic disorder like PCOS as the condition resulting in their condition would be excluded. This is primarily because, such women would have high enough Estrogen level to have a completely different signature of Mental Health, and associated Cardiometabolic health, then the Perimenopausal women, whose conditions are distinctly result of depleting Estrogen levels.
  3. Post Menopausal, and Menstruating women would be excluded from user groups, because of their low not changing, and high and slowly changing Estrogen levels respectively, which are distinct different signatures from the consistantly depleting Estrogen levels in the Perimenopausal women.
  4. Further, women undergoing Estrogen therapy, due to low/falling estrogen levels wouldn’t be considered in the user group because, such a condition is pathological metabolic and endocrine disorder, rather than Perimenopausal phase, which is a biological reality that every women phases.
  5. Perimenopausal women with acute clinical comorbidity, such as hyperthyroidism, would not be served, as our system is meant to serve early stage chronic comorbidities that are prone to get developed into a pathological condition along with the progress of the perimenopausal stage. We won’t serve actute pathological patients, as they need more structured clincial infrastructure help, due to elevated risks due to comorbidites.
  6. Perimenopausal women with diagnosed cluster-B mental health disorder, who are under the medication wouldn’t be served by us, as monitoring of such clincial mental health conditions, and variations in the conditions during menopause can not be studied under the current project.

c. Psychological Conditions that wouldn’t be covered:-

Other mental health conditions such as schizophrenia, bipolar disorder, any of the Cluster-B personality disorders wouldn’t be served by the system. As such, user groups with diagnosed mental health conditions other than the mentioned four conditions would be excluded from both the study, as well as primary implementation users.

d. Physiological health conditions that wouldn’t be covered:-

Other physiological conditions, such as appetite, thirst, lethargy, etc wouldn’t be covered. In short, any physiology that is not linked to the autonomic nervous system wouldn’t be covered by the system.

e. Pathologial risk not addressed

Metabolic Risks that would not be covered are risks of immunity including cancer risk.

Cardiovascular risks that wouldn’t be covered would include the risks of the Cardio-pulmonary axis like Heartfailue, Structural Cardiac Anomalies such as Coronary Artery Disease, and any acute cardiometabolic disease such as Myocardial Infarction.

3. Analysis

a. Efficacy Analysis

The clinical study will analyze health risks as assessed by Lyfas Perimenopausal mHealth system with that of both pure Human Analysis, and Expert Analysis based on existing Gold Standard instrument, and the Efficacy of the system will be measured by:

I) Internal Consistency

II) Negative Biomarker correlation across different control groups.

III) Positive Biomarker correlation within control groups.

IV) Statistical Significance of the Biomarkers.

V) Inter-Class and Inter-class consistency of the Biomarkers, in test-retest settings.

VI) Accuracy, Specificity, Sensitivity of the detected health conditions that with the existing human, as well as gold standard instruments.

VII) Prediction Efficacy would be measured in the longitudinal study as the closeness of the health condition as predicted by Lyfas Perimenopausal mHealth system with that of a clinically diagnosed medical condition, after a specific period of monitoring.

b. Usefulness Analysis

The system efficacy must not differ across different stages of Perimenopausal women(for example early, suspected, one year into perimenopause, progressed perimenopause, and so on).

The quality of life quantified scale before and after intervention using Lyfas Perimenopausal mHealth solution should demonstrate statistically significant scale improvement.

C. Robustness Analysis

The system performance must be the same across different national demographics(for example North, East, West, South, etc).

Also, the system efficacy must not change based on different times of the day, or based on skin tonality, and difference must be minimum between different smartphone devices.

Novelty[Explain how your idea is innovative and how it is different from the existing products in the markets or
current state-of-the-art. Tabular representation of the difference between your idea and the other products in market or
competitive product which are under development will be appreciated. Concrete market data is encouraged.]

  1. Existing products A. B and C with their advantage and limitations
  2. How Lyfas covers the same advantage in less cost with more efficiency and with better scalability.
  3. How Lyfas overcome the disadvantages
  4. What is Lyfas diaadvantages
  5. How Lyfas will address the disadvantages

Website URL, quantitive analysis

Potential societal impact :

Individual Impact

  1. Quality of life factor of Perimenopausal women is expected to improve between 20-30%
  2. Health expenditure of women is expected to reduce by 33%, by preventing progress of the health condition to progress to chronic conditions.
  3. Mental Health and Mood Regulation may improve the menopausal age by 1-3 Years.
  4. Due to better health conditions, and improvement in the quality of life, productivity of the working women is expected to improve by 20% to 30%.
  5. As women are conceiving late now due to career and profession, improvement in Menopausal age may improve the fertility of the women.

Group Impact

  1. There would be better emotional stability between the perimenopausal women, and her collegues in the workplace.
  2. By reducing the irritability, workplace outburst might be reduced, reducing the rate of women leaving the workplaces.
  3. Peer groups would have better mental and emotional health, due to an improvement of the same of the perimenopausal woman.

Family Impact

  1. Overall mental health condition of the family of perimenopausal women subscribing to our service is expected to be 20-30% better than the women who doesn’t subscribe to our services.
  2. As mental health condition is directly linked to Cardiometabolic health, the overall cardiometabolic health of the family is expected to improve between 20-30%, reducing the healthcare expense of the family.
  3. More stability would come to the families, due to mental peace and emotional stability.

Societal Impact

  1. Due to cascading effect of health, overall societal health might be improved by a factor of 20-30%, with an improvement in the average quality of life in the entire society.
  2. More women could be given employment through training to work from home as Perimenopausal counsellors, or health assistants, increasing the employment amongst the women.
  3. School teachers are mostly women. Improvement of the Perimenopausal women would result in happier learning, and can shape the next generation of the country better.
  4. Healthcare support staff if primarily driven by women. Improving quality of life of Perimenopausal women in healthcare can result in better healthcare outcome.
  5. Perimenopausal mood swings have resulted in many divorces, and by improving that, divorce rate might actually be brought down.

Economical Impact

  1. Healthcare expenditure might reduce in entire family, due to improvement of Mental, Emotional, and Cardiometabolic health.
  2. Improvement of quality of life of the entire society by 20-30% would long term result in better productivity and therefore can significantly contribute towards GDP growth by 3-10%.
  3. Reduced load in the chronic healthcare may provide the government to allocate more budget for infrastructure and other essentials, pushing the economy further.

Country Impact

  1. Overall health Index of the entire nation may improve by a factor of 20-30%, by improving the overall health of the families, and society, by improving the mental and cardiometabolic health of the perimenopausal women, and people associated with them directly or indirectly.
  2. More innovations may enter the mHealth, making India a pioneer and leader in digital mHealth.

Market Impact:

  1. mHealth digital infrastructure can be built inline with digital banking solutions, thereby enabling the healthcare facilities to be extended to the last Indian, in the furthest mile of the country.
  2. Several services can be plugged into the solution, creating a sustainable digital circular economy around mHealth.
  3. Even if we assume 1 counsellor per 100 women, for 70,00,000 annual subscribers, over 70,000 indirect employment might be created.

Current Market size (Total Addressable Market TAM):-

According to [24], the current market potential(size) of FemTech is around $22.5 B, which is expected to grow at a CAGR of 16.2% from 2021 to 2027. The Gynecology device industry is estimated to be US$ 10.76 Billion in 2020. Looking forward, IMARC Group expects the market to grow at a CAGR of 8.2% during 2021-2026[25]. Therefore the total market size can be stated to be between US $10 Billion to the US $22 Billion, with a CAGR between 8-16%.

So, our market segment is 3% of the overall medical device industry, but has 300% more CAGR, than the average MedTech market. This puts our solution not only an important social and healthcare need, but also provides us to play in a fast-growing sub-segment of medical devices.

Service addressable market (SAM)

The global pharmaceutical market has experienced significant growth in recent years. As of end-2020, the total global pharmaceutical market was valued at about 1.27 trillion U.S. dollars. This is a significant increase from 2001 when the market was valued at just 390 billion U.S. dollars[27].

The global medical devices market reached a value of nearly $456.8 billion in 2020, having increased at a compound annual growth rate (CAGR) of 3.5% since 2015. The market is expected to grow from $456.8 billion in 2020 to $62.0 billion in 2025 at a rate of 7.7%.[28], whereas the global Pharma Market size is the US $1.27 Trillion[27].

Thus, the MedicalDevice/Pharma Market Ratio is 0.35. Global PCOS and PCOD treatment market size is estimated to be the US $3.39 Billion[29]. Applying the 35% rule of the market size of the medical device vs pharma market, we see that the US $1.18 Billion is the potential market size of a PCOS/PCOD Medical Device Market size. Considering that PCOS and Perimenopausal symptoms are almost similar [30], we can estimate that our Global Addressable Market(GAM) is about US $1.18 Billion.

Indian Medical device market is the US $ 2.1 Billion[31], which is 0.46% of the Global Medical Device Market. Thus at .46% of GAM, our potential TAM is the US $54 Million. At a 30% market capture, as a first entrant, we can estimate our Indian potential TAM to be the US $16.2 Million per year.

Share of the current solutions in the market

Global Wearable Device Market size is estimated to be US $ 118.16 Billion, whereas the global mHealth market size is about US$50 Billion[33]. Thus, it can be estimated that mHealth market is 50% of the global monitoring market. Global Patient Monitoring Market size is US $19 Billion[34]. Therefore, wearable monitoring, that also includes wellness is about 6 times more than the patient monitoring market size. Patient monitoring market size is about 4.16% of the overall medical device market size. As our Global Addressable market size is US $1.18 Billion, which is 4.16% of the the actual Market size in Perimenopausal women. Thus our actual estimated market size is US $ 4.72 Billion. This is 9.44% of the overall mHealth market.

Hence, through Lyfas Perimenopausal mHealth solution, we can have 9.44% global marketshare of the mHealth market with a potential of US $16.2 Million revenue every year from Indian operations alone, if the project is successfully implemented.

Annual expected growth to win the market

As discussed earlier, our potential CAGR is between 8-16% annually. As the Indian medical device market is still in its infancy and growing at a CAGR of 29%[31], we can estimate an average CAGR of 17.66% for Lyfas Perimenopausal health Solution for the next 6-7 years.

Customer aquisition market

The average patient acquisition cost in India for OPD patients is between INR 3,000 to INR 10,000, with an average expenditure of around INR 4,000/-[35]. The perimenopausal period lasts for about 4 years. As per [36] Current medical of Menopausal symptoms is around $248 per year in the United state. For a four-year period, this is around $992 minimum, which is about INR 74,000. Per capita healthcare expenses in India are $73 annually[37]. Hence Indian annual expenditure on health is about 29% that of US numbers. Thus 29% of 74,000 is about INR 21,460/-. Therefore Customer Acquisition vs Customer Revenue cost in the Perimenopausal segment is around 5x.

Hence, if the customer acquisition cost is reduced to 10% of the current cost born by the private players, the overall pricing can be brought down to as low as 200/- every month. 10% customer of the overall 7 Crore potential customers, our monthly revenue even at 200/- per month lowest cost, can be around $ 18 Million, whereas the customer acquisition annual cost every month for the same can be $3.6 Million(at 20% cost on revenue).

At 1% merge market share, our annual revenue can be around $21 Million, and customer acquisition cost around %4 Million.

Expected custmer retention rate

The average customer retention rate in the healthcare industry is 54%[38], which can be considered as our base model.

Revenue to cost ratio

Our Revenue to Cost Ratio is 5, as elaborated previously.

Overall market impact

Lyfas Perimenopausal mHealth solution can acquire about 9.44% of the Global mHealth market through the solution, thereby making India a pioneer in global mHealth. As App economy in India has already been proven to drive the market through Banking(PayTM), Trading(Zerodha), Delivery(Swiggy) have all gone on to become Unicorns, driving the digital business market, Lyfas mHealth can drive the Digital mHealth market through Lyfas Perimenopausal mHealth solution.

Challenges or risk factors associated with the project
[What are the challenges and risk factors that you envision which may affect this project?]What are the critical success factors/potential barriers

Challenges:

The major challenges that we might face in the project are as follows:

  1. Implementation challenge and overcome strategy
  2. Technical challenge and overcome stratagy
  3. False acceptance challnege and overcome strategy
  4. False rejection and overcome strategy
  5. Validation challenges
  6. Marketing challenge
  7. Scalability challenge
  8. profitatbility challenge
  9. sustainability challenge
  10. Workflow challenge
  11. Project mgmt challenges

We will overcome the challenges using Agile model of project development, where design, development and testing will be modularized and parallelized, such that hindrance in any of the stages doesn’t affect the overall stages.

Risks:

Major risks that we might encounter in the project are as follows:

  1. Technical Risk
  2. Financial Risk
  3. Partnership risk
  4. Compliance risk
  5. Adaptability risk
  6. Mgmt risk
  7. Policy risk
  8. Data Risk

We will use the “Watch and Monitor” type of risk mitigation strategy and would adopt the strategy from [39], which is a standard medical device software risk mitigation strategy.

Potential barriers:

The following potential barrier might be encountered by the project.

  1. Market resistance
  2. Competition
  3. Compliance barrier
  4. Behavioural barrier
  5. Emotional barrier
  6. Cost barrier

Each of the barriers will be overcome by designing small-scale experiments, gathering data, and building barrier overcoming strategies based on the data. For instance, in the pre-pilot stage, we may offer 5 different cost models to 20 different potential users, and calculate the conversion ratio. We can select the pricing model associated with the highest conversion.

Similarly, market resistance can be overcome by the right set of partnerships and positioning. We can design content marketing with 5 different marketing styles, and observe the user interest, and lead generation, to choose the best model.

Future Plan of Commercialization
[What do you envision to be the key next step to making impact with this innovation (e.g., sponsored research support, licensing, venture financing)? What is the time frame?]
Commercialization plan should indicate :
1). Market entry strategy.
2). Timelines and Milestones.
3). Data analysis (sample size,data collection)

A. Deliverable before market entry

  1. Publications
  2. Promotion(Press releases, content marketing)
  3. Promotion through women support groups 5. Influencer promotion
  4. Partnering with govt. entities for promotion
  5. Public and private health centers partnership and promotion
  6. Clinician awareness onboarding and certifications
  7. Pilot workflow implementation
  8. Lyfas Perimenopausal mHealth Instrument, Lyfas Perimenopausal mHealth System, Lyfas Perimenopausal mHealth Platform, Lyfas Perimenopausal mHealth Ecosystem, Lyfas Perimenopausal mHealth Solution must be delivered.

B. Market Entry (Milestone mention with timeline )

Overall Start of the Project to Market Milestones

  • Phase I: Observational Study: 2 Months
  • Phase II: Accuracy Study: 2 Months
  • Phase-III: Validation Study: 2 Months
  • Phase-IV: Case-Control Study: 2 Months
  • Phase V: AI and ML development for the Early Detection and Risk Assessment: 2 Months
  • Phase VI: Longitudinal Study & Phase VII: Quality of Life Improvement Study conducted parallely for 6 Months
  • Phase VIII: Pilot Implementation 3 Months
  • Phase IX: Perimenopausal Digital mHealth Solution Project Report Submission: 1 Month

The overall project is estimated to complete in 20 months.

Go to Market Milestones

  • Awareness:- 3 Weeks of Marketing through Content, Blogs, Videos, Social Media Campaigns, Influencer Marketing, Newsletters.
  • Medical Community Awareness:- 2 Weeks of Webinars, Live Workshops and Sessions to relevant practicing clinicians and Counsellors for onboarding with the project.
  • Clinician Onboarding: Post workshop training for 1 week to interested clinicians wanting to be part of the project.
  • Digital Distribution Channel Preparation:- 2 Weeks for creating and testing the Distribution channel for the application, and integrating the portal.
  • Health Awareness Content Development: 4 Weeks of Contents developed on various Health risk management as observed throughout the study.
  • Beta-testing:- Pre-piolot testing of the end-to-end solution delivery for 4 weeks.

C. Data analysis

Following measurement metrics would be used for measuring the success of the project.

  1. Total reachability:- Using Google Analytics in our contents for tracking.
  2. Total awareness:- Number of users showing interest by filling our subscription form.
  3. Total clinician onboarded:- Total number of practicing clinicians taking Lyfas Perimenopausal mHealth training course to register with the platform.
  4. Total customers enrolled:- Total number of customers opting for the service in the commercial stage(expected numbers=2000 customers)
  5. Customer satisfaction:- Google rating by the customers.
  6. Customer refferals:- Total leads generated by the referral of satisfied customers.
  7. Total revenue:- Total Revenue generated in the pilot implementation stage.
  8. Customer Acquisition Cost:- Total marketing cost/total number of customers.
  9. Clnical correlation:- Efficacy(Accuracy, Statistical Significance, Correlation, Sensitivity, Specificity, Yuden’s Index for each phase of the study).
  10. We will use standard tracking tools, followed by open source statistical analysis tools, for analyzing the project data, tracking metrices and other parameters.

Please provide current and expected Technology Readiness Level (TRL)
Current (1,2,3):
Expected (4,5,6,7,8):

TRL LevelsDescriptionURL
Current TRL 1Lyfas mHealth Instrument1. Hindi Demonstration: https://www.youtube.com/watch?v=PUsua748uvk
2. English Demonstration: https://www.youtube.com/watch?v=sDxXlOH5Vnc
Current TRL 2Lyfas mHealth Clinical ValidationsReference Number [12], [13], [14], [16], [17]
Current TRL 3Quality of Life Gold-Standard Instrument Implementation5]https://lyfas.com/test/quality-of-life-questionnaire-instrument-stanford-sparqtools/
Proposed TRL1Biomarker and Clinical Condition Correlation and ValidationPhase I: Observational Study
Phase II: Accuracy Study
Phase-III: Validation Study
Phase-IV: Case-Control Study
Proposed TRL2AI and ML development and TestingPhase V: AI and ML development for the Early Detection and Risk Assessment
Phase VI: Longitudinal Study
Proposed TRL3Quality of Life Improvement Demonstration Phase VII: Quality of Life Improvement Study
Proposed TRL4Platform, IoT, Analytics Readiness for Pilot implementationPhase VIII: Pilot Implementation

Please upload declaration document on ethical/legal/safety/regulatory issues involved, if any :


Vagus hospital clinical trial doc upload

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Undertaking by the Principal Investigator with regards to the originality of proposal submitted (Click here to download format)

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Tabular Format: OBJECTIVES | Methodologies | Alternate strategies

Internal Link to the Answer


OBJECTIVE WISE ACTIVITIES & TIMELINES: Work Plan, financial plan

Tabular : Milestone name | Month of end of activity (in months)

Internal Link

Budgeting in lakhs


Nonrecurring cost in lakhs Tabular : Equipment/Accessorries | Total

Sl No.ParticularQuantityUnit CostTotal Cost
1.Statistical Analysis, Data Management of Trials61,00,000/-6,00,000/-
2. Project Auditing and Accounting175,000/-75,000/-
3. LCD Screen for Dashboard180,000/-80,000/-
4.Portal Hosting 2 Years, 2 Hosting Znet Portals7,000/- per Portal Per Year28,000/-
5. Text Content for Marketing30 Blogs5,000/- per blog1,50,000/-
6. Video Content content for marketing30 Videos10,000/- per Video3,00,000/-
7. Marketing Material(Designing, Brochure, Printing)3000200/-6,00,000/-
8.Paper Publication Cost850,000/-4,00,000/-
22,33,000/-


Recurring cost in lakhs: HR a | consumable b | Other heads c | total a b c

HR
Sl No.ParticularQuantityTotal MonthsMonthly CostTotal Cost
1.PI11850,000/-9,00,000/-
2.Software Developer11825,000/-4,50,000/-
3.Consultant Clinicians 11220,000/-2,40,000/-
4.Support Staff31820,000/-10,80,000/-
5.Sales and Marketing1240,000/- 80,000/-
27,50,000/-

Relevant References

[1] Population study on Menopause of Indian women: Ahuja M. Age of menopause and determinants of menopause age: A PAN India survey by IMS. J Midlife Health. 2016;7(3):126-131. doi:10.4103/0976-7800.191012, Url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5051232

[2] TOI Survey on Early Menopause: URL: https://timesofindia.indiatimes.com/life-style/health-fitness/health-news/premature-menopause-on-the-rise/articleshow/36665763.cms

[3] URL: https://my.clevelandclinic.org/health/diseases/21608-perimenopause

[4] Delamater L, Santoro N. Management of the Perimenopause. Clin Obstet Gynecol. 2018;61(3):419-432. doi:10.1097/GRF.0000000000000389, URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6082400/

[5] Census Data: URL: https://censusindia.gov.in/census_and_you/age_structure_and_marital_status.aspx

[6] Mahajan N, Aggarwal M, Bagga A. Health issues of menopausal women in North India. J Midlife Health. 2012;3(2):84-87. doi:10.4103/0976-7800.104467, from Url:-https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3555032/

[7]Pérez, José Antonio Martínez, et al. “Epidemiology of risk factors and symptoms associated with menopause in Spanish women.” Maturitas 62.1 (2009): 30-36.

[8]Kour A, Sharma S, Sambyal V, et al. Risk Factor Analysis for Breast Cancer in Premenopausal and Postmenopausal Women of Punjab, India. Asian Pac J Cancer Prev. 2019;20(11):3299-3304. Published 2019 Nov 1. doi:10.31557/APJCP.2019.20.11.3299, fromURL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7062992/

[9] [10] Fertility Statistics of India: https://www.statista.com/statistics/271309/fertility-rate-in-india

[10]Hajesmaeel-Gohari, S., Shafiei, E., Ghasemi, F. et al. A study on women’s health information needs in menopausal age. BMC Women’s Health 21, 434 (2021). https://doi.org/10.1186/s12905-021-01582-0

[11]Nebhinani Naresh, Subodh B N, How mental illness affects the family – Different worlds, similar suffering, Indian Journal of Social Psychiatry, Year : 2017  |  Volume : 33  |  Issue : 3  |  Page : 187-188

[12]Subhagata Chattopadhyay, Rupam Das,” Comparing Heart Rate Variability with Polar H10 Sensor and Pulse Rate Variability with LYFAS: A Novel Study”, Journal of Biomedical Engineering and Technology, 2021, Vol. 9, No. 1, 1-9

[13]Chattopadhyay S, Das R. Statistical Validation of Cardiovascular Digital Biomarkers Towards Monitoring the Cardiac Risk in COPD: A Lyfas Case Study. Artificial Intelligence Evolution [Internet]. 2022Jan.10 [cited 2022Jan.21];3(1):1-16. Available from: https://ojs.wiserpub.com/index.php/AIE/article/view/1252

[14] Chattopadhyay S, Das R. Lyfas, A Smartphone-Based Subclinical Depression Tracker. Int J Psychiatr Res 2021; 4(6):
1-9.

[15]https://lyfas.com/test/quality-of-life-questionnaire-instrument-stanford-sparqtools/

[16] Rupam Das, Subhagata Chattopadhyay, “Towards Cardiac Risk Monitoring of Duchene Muscular Dystrophy
using Lyfas”, Journal of Nanotechnology in Diagnosis and Treatment, 2021, 7, 25-32

[17] Deepa HS, Rupam Das, EVALUATION OF NON-INVASIVE SMARTPHONE BASED DIGITAL BIOMARKER TOOL LYFAS® IN DETECTING SLEEP DEFICIENCY AND ITS EFFECTS: A RETROSPECTIVE OBSERVATIONAL STUDY, Indian Journal of Applied Research, Volume – 11 | Issue – 01 | January – 2021 | . PRINT ISSN No 2249 – 555X | DOI : 10.36106/ijar

[18] Public Domain Lyfas Case Study: https://lyfas.com/gynecology/amenorrhea-early-menopause-reversal-lyfas-case-study/rupam_lyfas/

[19] False Positive PCOS Diagnosis by conventional system detected by Lyfas: https://lyfas.com/gynecology/false-diagnosis-treatment-of-pcos-a-lyfas-case-study/rupam_lyfas/

[20] Public Domain Population Case Study: https://lyfas.com/chronic-disease-management/india-diabetesinsulin-resistance-risk/rupam_lyfas/

[21] Dr. Deepa HS, Rupam Das, A CONTROLLED CLINICAL STUDY TO EVALUATE A PROPRIETARY NON-INVASIVE SMARTPHONE BASED DIGITAL BIOMARKER TOOL LYFAS IN ENABLING EARLY DETECTION OF COVID-19 INFECTION AMONG ASYMPTOMATIC INDIVIDUALS, International Journal of Scientific Research, Volume X, Issue 1, January 2021

[22] https://www.indiascienceandtechnology.gov.in/technologies/lyfas-mobile-app?field_area_id=4783

[23] Lyfas Google Review: https://www.google.com/search?q=Acculi+Labs+Pvt.+LTD.&rlz=1C1CHBF_enIN919IN920&oq=acculi+l&aqs=chrome.0.69i59j46i39i175i199j69i57j0i22i30l2j69i60l3.2335j0j4&sourceid=chrome&ie=UTF-8#lrd=0x3bae3fa4524c338b:0x72266f431f80279,1,,,

[24] FemTech Market Research: https://www.gminsights.com/industry-analysis/femtech-market

[25]Gynecology Device Market: https://www.imarcgroup.com/gynecology-devices-market

[26] MedTech Market Research: https://www.bccresearch.com/market-research/healthcare/medical-devices-technologies-and-global-markets

[27]https://www.statista.com/statistics/263102/pharmaceutical-market-worldwide-revenue-since-2001/

[28]https://www.thebusinessresearchcompany.com/report/medical-devices-market

[29]https://www.globenewswire.com/news-release/2021/01/12/2156805/28124/en/Global-3-39-Billion-PCOS-Polycystic-Ovary-Syndrome-Treatment-Markets-Analysis-2015-2019-Forecasts-2020-2025.html

[30] https://www.healthline.com/health/menopause/pcos-and-menopause#symptoms

[31] https://www.ibef.org/industry/medical-devices.aspx

[32] https://www.businesswire.com/news/home/20220104005806/en/Global-Wearable-Technology-Market-Trends-Analysis-Report-2021-2028-Adoption-of-Fitness-Trackers-and-Health-based-Wearables-is-Anticipated-to-Propel-Growth—ResearchAndMarkets.com

[33] https://www.grandviewresearch.com/industry-analysis/mhealth-market

[34] https://www.bccresearch.com/market-research/healthcare/patient-monitoring-devices-global-markets.html

[35] https://www.linkedin.com/pulse/hospitals-marketing-roi-how-track-reduce-user-cost-tenzin-thargay/

[36] Assaf AR, Bushmakin AG, Joyce N, Louie MJ, Flores M, Moffatt M. The Relative Burden of Menopausal and Postmenopausal Symptoms versus Other Major Conditions: A Retrospective Analysis of the Medical Expenditure Panel Survey Data. Am Health Drug Benefits. 2017;10(6):311-321. from URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5620512/

[37]https://knoema.com/atlas/India/topics/Health/Health-Expenditure/Health-expenditure-per-capita

[38]https://surveysparrow.com/blog/heres-something-didnt-know-average-customer-retention-rate-industry/

[39]Lindholm, Christin, Jesper Pedersen Notander, and Martin Höst. “A case study on software risk analysis and planning in medical device development.” Software Quality Journal 22.3 (2014): 469-497.

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